Miracle-dz/UniFAR-FTUs huggingface dataset:
The Anti-Inflammatory Role of Omega-3 Polyunsaturated Fatty Acids Metabolites in Pre-Clinical Models of Psychiatric, Neurodegenerative, and Neurological Disorders

Inflammation has been identified as one of the main pathophysiological mechanisms underlying neuropsychiatric and neurodegenerative disorders. Despite the role of inflammation in those conditions, there is still a lack of effective anti-inflammatory therapeutic strategies. Omega-3 polyunsaturated fatty acids (n-3 PUFAs) can reduce depressive symptoms and exert anti-inflammatory action putatively by the production of distinct n-3 PUFA-derived metabolites, such as resolvins D (RvD) and E (RvE) series, maresins (MaR) and protectins (PD), which are collectively named specialized pro-resolving mediators (SPMs) and act as strong anti-inflammatory agents. In this review we summarize evidence showing the effects of treatment with those metabolites in pre-clinical models of psychiatric, neurodegenerative and neurological disorders. A total of 25 pre-clinical studies were identified using the PubMed database. Overall, RvD and RvE treatment improved depressive-like behaviors, whereas protectins and maresins ameliorated neurological function. On a cellular level, RvDs increased serotonin levels in a model of depression, and decreased gliosis in neurodegenerative disorders. Protectins prevented neurite and dendrite retraction and apoptosis in models of neurodegeneration, while maresins reduced cell death across all studies. In terms of mechanisms, all SPMs down-regulated pro-inflammatory cytokines. Resolvins activated mTOR and MAP/ERK signaling in models of depression, while resolvins and maresins activated the NF-κB pathway in models of neurodegeneration and neurological disorders. Our review indicates a potential promising approach for tailored therapy with n-3 PUFAs-derived metabolites in the treatment of psychiatric, neurodegenerative, and neurological conditions.
A cross mosaic based partial fingerprint recognition strategy with multiple templates

In order to enrich the effective feature information of fingerprint template and improve the matching performance of local fingerprint identification system, this paper proposes a multi-template partial fingerprint recognition strategy based on cross mosaicing. In the registration phase, the template feature cross-splicing process is performed on the fingerprint feature template extracted from the local fingerprint image to enrich the effective feature information of the fingerprint template, thereby avoiding the occurrence of mosaicing failure due to different mosaicing sequences. In view of the problem that the fingerprint image recombination rate is too low and will cause the fail of registration, this paper base on multiple storage templates, and continuously enriches the effective information contained in the feature template through the template update strategy in the authentication phase. The experimental results have shown that the strategy of this paper has better matching performance.
Convolutional neural network for early detection of gastric cancer by endoscopic video analysis

Computer-aided diagnosis of cancer based on endoscopic image analysis is a promising area in the field of computer vision and machine learning. Convolutional neural networks are one of the most popular approaches in the endoscopic image analysis. The paper presents an endoscopic video analysis algorithm based on the use of convolutional neural network. To analyze the quality of the algorithm on the video data from the endoscope, the intersection over union (IoU) metric for object detection is used. The experimental results shows that the average value of IoU coefficient for the developed algorithm is 0.767, which corresponds to a high degree of intersection of areas identified by an expert and the algorithm.
Genes Involved in Stress Response and Especially in Phytoalexin Biosynthesis Are Upregulated in Four Malus Genotypes in Response to Apple Replant Disease

Apple replant disease (ARD) is a soil-borne disease, which is of particular importance for fruit tree nurseries and fruit growers. The disease manifests by a poor vegetative development, stunted growth, and reduced yield in terms of quantity and quality, if apple plants (usually rootstocks) are replanted several times at the same site. Genotype-specific differences in the reaction of apple plants to ARD are documented, but less is known about the genetic mechanisms behind this symptomatology. Recent transcriptome analyses resulted in a number of candidate genes possibly involved in the plant response. In the present study, the expression of 108 selected candidate genes was investigated in root and leaf tissue of four different apple genotypes grown in untreated ARD soil and ARD soil disinfected by γ-irradiation originating from two different sites in Germany. Thirty-nine out of the 108 candidate genes were differentially expressed in roots by taking a p-value of < 0.05 and a fold change of > 1.5 as cutoff. Sixteen genes were more than 4.5-fold upregulated in roots of plants grown in ARD soil. The four genes MNL2 (putative mannosidase); ALF5 (multi antimicrobial extrusion protein); UGT73B4 (uridine diphosphate (UDP)-glycosyltransferase 73B4), and ECHI (chitin-binding) were significantly upregulated in roots. These genes seem to be related to the host plant response to ARD, although they have never been described in this context before. Six of the highly upregulated genes belong to the phytoalexin biosynthesis pathway. Their genotype-specific gene expression pattern was consistent with the phytoalexin content measured in roots. The biphenyl synthase (BIS) genes were found to be useful as early biomarkers for ARD, because their expression pattern correlated well with the phenotypic reaction of the Malus genotypes investigated.
G-CNN type recognition of typical aircraft based on target characteristics

This paper is aimed at the type recognition of aircraft, with four kinds of typical military aircraft as research objects. In this paper, we establish a database on aircraft type and propose an effective and efficient method of type recognition called Geometric-Convolutional Neutral Networks(G-CNN) in a coarse-to-fine manner. We start with target characteristics for the first time and establish a target characteristics database by analyzing the acquired characteristics such as geometric characteristics and optical characteristics. Next, aiming at the problem that the dataset on aircraft types is few, we build 3D models based on the characteristics database and make an aircraft type dataset using 3D simulation creatively, which is of great significance for the research on aircraft type recognition. Finally, we extract the geometric characteristics of the aircraft—affine invariant moments and aspect ratios, realizing a fast and efficient region selecting; we improve residual blocks with dilated convolution, which is used for type recognition for the first time. Our method achieves 89.0%mAP and the experiments show that it tackles the type recognition problems with improved performance.
M.A.G.E.C: machine assisted geometry extraction and creation

The GIS industry relies heavily on manual efforts to build and maintain digital maps. This approach is timeconsuming and requires a sizable workforce not only for map-making but also for quality-checks that are required to resolve the potential errors resulting from manual digitization. With recent advancements in computer vision, several organizations are using machine-learning algorithms to generate map data from images. In the current machine learning based geometry creation process three limitations prevails. Firstly, the output of the algorithms is never served on-demand to a map editing tool. Secondly, after being further fine-tuned manually by annotators/validators, the results are never fed back to the algorithms to identify the errors incurred and improve accuracy. Finally, a lot of manual effort is required to create training data for new terrains and regions. We propose an end-to-end machine learning system integrated with current map-making tools to address these limitations and reduce the manual effort in creating and updating geometry.
Optimal design of optical refractometer for seawater salinity measurement

Salinity of seawater is one of the most important ocean parameters. Salinity of seawater is mainly obtained by conductivity measurement using CTD (Conductivity-Temperature-Depth). Conversion accuracy between conductivity and salinity relies on the assumption that components of seawater are fixed, as well as high accuracy and synchronism measurements of conductivity, temperature and pressure. The study of seawater salinity based on the V-block optical refractive index method provides a total different principle for salinity measurement. Achieving high resolution seawater optical refractive index measurements could help to study factors affecting the accuracy of salinity measurement. In this paper, the various instrument parameters that affect the accuracy of seawater refractive index measurement are analyzed and the optical refractometer is optimized based on the components on the shelf. This paper systematically analyzed the resolution and tolerance of refractive index measurement on the parameters of V-block refractometer, such as incident angle, external environment and prism refractive index, etc. The optical refractometer with an air film layer on both sides of the V-block was proposed for seawater salinity measurement. With such an optimization, the measurement accuracy is further improved and the tolerance is increased. The theoretical resolution to the seawater refractive index and salinity are 1.8×10-6 and 0.01‰, respectively. Experimentally, we have achieved 3.9×10-6 and 0.021‰ respectively, and a good linearity. The difference between theoretical and experimental results are analyzed.
An improved object detection algorithm based on depthwise separable convolutions

Aiming at small objects detection such as unmanned aerial vehicle (UAV), this paper proposes a fast object detection algorithm based on depth wise separable convolutions. Firstly, the inverted residuals units based on depth wise convolutions and pointwise convolutions are used to construct a lightweight feature extraction network to improve the network’s speed. Secondly, the feature pyramid network is used to detect the five scale feature maps to improve the detection performance of small objects. Otherwise, we make an UAV dataset based on the urban background for training and testing of our experiments. The experimental results show that the improved method proposed in this paper can effectively improve the detection accuracy and real-time performance of UAVs in complex urban backgrounds, and the computation of network is greatly reduced, thereby making it possible to achieve object detection on embedded systems.
Propagation of the Bessel-Gaussian beams generated by coherent beam combining in oceanic turbulence

Coherent beam combining (CBC) is recently used to generate high power vortex beams which are strongly required in specific applications. In this paper, based on the extended HuygensFresnel principle, the exact theoretical forms for the intensity distribution of the CBC Bessel-Gaussian beams (BGBs) in turbulent ocean are derived. To show the superiority of CBC BGBs in turbulent channels, the comparison in the intensity evolution of the CBC BGBs with the ideal BGBs is performed. It is found that the beam spreading of the CBC BGBs is smaller than that of the ideal BGBs under the same oceanic turbulence conditions. Moreover, the effect of the different optical source parameter on the quality of the CBC BGBs is also analyzed. The results show that the increasing number of the beamlets causes the optical energy to be more concentrated, and thus leading to a longer non-diffraction propagation distance.
Inshore ship detection based on improved faster R-CNN

Ship object detection has a wide range of applications in both military and civilian. In the military, as an important and classical object in the field of military, the quick and accurate detection of ship is closely related to the success or failure of the battle. Similarly, as survival tools in civilian use, whether the number and location of ships can be quickly and accurately identified has a strong impact on marine rescue. In recent years, various object detection methods have been applied to ship detection, which include traditional methods and methods based on deep learning. However, due to the complicated background of inshore ships, the detection process is easily interfered by the buildings on the shore. As a result, the effects of ship detection are not yet satisfactory and researchers are making efforts to further improve these methods. In this paper, we propose an inshore ship detection method based on improved Faster R-CNN. As a typical and benchmark framework in the detection field, Faster R-CNN is chosen as the base pipeline. On the basis of this method, Soft NMS and Focal Loss are added with consideration of the characteristics that sizes of ships and distances between them are all different. Experiments on various data sets validate the effectiveness of our improvement. The mean Average Precision on our own 200 ship dataset has increased by 6% to 80.4%. The mean Average Precision on the public HRSC2016 ship dataset has increased by 1.1% to 84.5%.
Image analysis for the fault diagnosis in a rocket engine failure

Rocket engine is a complex and accident-frequently-occurring system. Its fault location and cause analysis is challenge. This paper analyze a rocket launching fault based on the video captured by a visible light camera on the rocket during the flight. The primary mission is to judge whether the suspected "flame" is caused by the combustion luminescence or the reflection of sunlight by the fluids. A qualitative and semi-quantitative analysis is carried out from the perspective of intensity and color. The possibility of self-luminescence is analyzed, and the spectrum from visible to near infrared of hydrogen and oxygen combustion is measured on the ground. The atomic radiation spectra of Na, Ka and other related metal elements are detected. The combustion brightness and atmospheric scattering brightness are compared. Combining with other prior information of the engine, it is considered that the brightness of the re-burning of hydrogen and oxygen should be lower than the atmospheric scattering brightness. The real color of the suspected "flame" area in the image is analyzed by using the characteristics of the white balance processing algorithm. By comparing with other similar gray scale and similar color images, it is inferred that the real color is white, and the yellowish of the “flame” is caused by compensation of the blue background by the automatic white balance of the camera. Based on the above analysis, it is inferred that the "flame" is caused by the reflection of sunlight by liquid particles, not by combustion, and the region should be located at the bottom of the rocket.
Identification and Characterization of Bluetongue Virus Serotype 14 in Russia

This paper reports a case of bluetongue virus (BTV) infection in the Smolensk and Kaluga regions of Russia in 2011–2012. The virus was initially detected in heifers transferred in Russia from Germany through Poland and Belarus in 2011. On day 27 of quarantine, RNA and infectious viruses of BTV were detected in four heifers, but five were serologically positive. However, on day 3 before shipment, all heifers were seronegative and PCR-negative for BTV. Thus, a few animals from this consignment were viremic without any evident subclinical infection. Based on Seg-2 (VP2 gene) and Seg-5 (NS1 gene) sequencing, the recovered virus had 99.86–100% nucleotide identity with BTV-14-like viruses such as the vaccine BTV-14 strain RSArrrr/BTV 14 and the BTV-14 isolates detected in Lithuania and Poland in 2012. Subsequently, BTV-14 was also reported in local animals in two regions of Russia. During the monitoring survey, 1623 local animals within a 300-km radius were tested, of which 471 tested positive by ELISA and 183 by PCR for BTV-14 RNA. No other serotypes were identified in either imported or aboriginal animals within that radius. The Culicoides midges trapped at the site of the outbreak in May 2012 tested positive for the BTV-14 genome, indicating that the possible mechanism of spread most likely occurs via vector bites. However, further investigation is required to confirm this hypothesis, which would provide an improved understanding of the circulation and overwintering of BTV in northern latitudes.
Five new eriophyid mite species from Egypt (Acari: Eriophyidae) associated with the weeds of the family Poaceae

Abstract Five new eriophyoid mites infesting weeds of the family Poaceae are described and illustrated from Egypt. They are Abacarus stagninis sp. nov. from Echinochloa stagnina (Retz.) P. Beauv. , vagrants in grooves between veins on the upper leaf surface, causing discoloration of the leaves; and four new species from genus Aceria (A. echinochloae sp. nov., A. barnyardi sp. nov., and A. stagninis sp. nov.) from E. stagnina and E. crus–galli (L.) Beauv. , and Aceria pennisetosa sp. nov., from Pennisetum purpureum Schumach. These species are vagrants underneath inner surface of the leaf sheath around stem and no symptoms were observed. However, A. barnyardi sp. nov. is a vagrant underneath inner surface of the leaf sheath around stem and are endoparasitic inside tissue of leaves causing rusted leaves.
PAX1 is essential for development and function of the human thymus

PAX1 deficiency causes a syndromic form of SCID by altering differentiation of thymic epithelial cells and other pharyngeal pouch tissues. PAX1 in the thymus Severe combined immunodeficiency (SCID) encompasses a wide spectrum of genetic disorders. Here, Yamazaki et al. have studied immune deficits in six patients with otofaciocervical syndrome type 2, a genetic abnormality attributed to biallelic mutations in PAX1. In addition to immunodeficiency, the disease is also characterized by facial dysmorphism, hearing loss and skeletal abnormalities. The patients were subjected to hematopoietic stem cell transplantation to rectify their immunodeficiency. Despite successful engraftment in three of these patients, all three of them failed to develop T cells. By generating patient-derived induced pluripotent stem cells and differentiating then ex vivo into thymic epithelial progenitors (TEPs), the authors find that PAX1 plays an important role in regulating the development of TEPs. We investigated the molecular and cellular basis of severe combined immunodeficiency (SCID) in six patients with otofaciocervical syndrome type 2 who failed to attain T cell reconstitution after allogeneic hematopoietic stem cell transplantation, despite successful engraftment in three of them. We identified rare biallelic PAX1 rare variants in all patients. We demonstrated that these mutant PAX1 proteins have an altered conformation and flexibility of the paired box domain and reduced transcriptional activity. We generated patient-derived induced pluripotent stem cells and differentiated them into thymic epithelial progenitor cells and found that they have an altered transcriptional profile, including for genes involved in the development of the thymus and other tissues derived from pharyngeal pouches. These results identify biallelic, loss-of-function PAX1 mutations as the cause of a syndromic form of SCID due to altered thymus development.
Ultrafast control of vortex microlasers

Ultrafast vortex microlasers For applications in ultrafast communication, all-optical switches will require low energy consumption, high speed, a strong modulation ratio, a small footprint, and on-chip integration. Although the small footprint and on-chip integration are accessible, the trade-off between low energy consumption and high speed has been challenging. Huang et al. exploited the idea of bound states in the continuum, effectively a high–quality (Q) cavity without the physical cavity, to design vortex lasers with highly directional output and single-mode operation. With the trade-off between low energy consumption and high speed now broken, it should be possible to realize ultrafast optical switching that meets all the requirements of modern classic and quantum information. Science, this issue p. 1018 Ultrafast vortex lasers with highly directional output and single-mode operation have been realized. The development of classical and quantum information–processing technology calls for on-chip integrated sources of structured light. Although integrated vortex microlasers have been previously demonstrated, they remain static and possess relatively high lasing thresholds, making them unsuitable for high-speed optical communication and computing. We introduce perovskite-based vortex microlasers and demonstrate their application to ultrafast all-optical switching at room temperature. By exploiting both mode symmetry and far-field properties, we reveal that the vortex beam lasing can be switched to linearly polarized beam lasing, or vice versa, with switching times of 1 to 1.5 picoseconds and energy consumption that is orders of magnitude lower than in previously demonstrated all-optical switching. Our results provide an approach that breaks the long-standing trade-off between low energy consumption and high-speed nanophotonics, introducing vortex microlasers that are switchable at terahertz frequencies.
Kinetic pathways of ionic transport in fast-charging lithium titanate

Metastable pathways allow high rates In batteries that allow for fast charging and discharging, lithium usually forms a solid solution with the anode so that the only limiting factor is the ionic diffusion. However, for a lithium titanate (Li4Ti5O12) anode, the lithium ions interact with two phases and the diffusion is slow in both, but it still shows high-rate capabilities. Zhang et al. used electron energy-loss spectroscopy combined with density functional theory calculations to probe the anomalous behavior. They found that a diffuse interface forms between the starting and ending compositions, Li4Ti5O12 and Li7Ti5O12, and this is what allows the lithium ions to travel quickly. Science, this issue p. 1030 Operando electron energy-loss spectroscopy aided by ab initio simulations reveals how Li+ migrates in a fast-charging anode. Fast-charging batteries typically use electrodes capable of accommodating lithium continuously by means of solid-solution transformation because they have few kinetic barriers apart from ionic diffusion. One exception is lithium titanate (Li4Ti5O12), an anode exhibiting extraordinary rate capability apparently inconsistent with its two-phase reaction and slow Li diffusion in both phases. Through real-time tracking of Li+ migration using operando electron energy-loss spectroscopy, we reveal that facile transport in Li4+xTi5O12 is enabled by kinetic pathways comprising distorted Li polyhedra in metastable intermediates along two-phase boundaries. Our work demonstrates that high-rate capability may be enabled by accessing the energy landscape above the ground state, which may have fundamentally different kinetic mechanisms from the ground-state macroscopic phases. This insight should present new opportunities in searching for high-rate electrode materials.