Siameses

Here, we announce the complete genome of a previously undescribed papillomavirus from a betta fish, Betta splendens . The genome is 5,671 bp with a GC content of 38.2%. Variants were detected in public databases. This genome is most similar to papillomaviruses that infect sea bass (52.9 % nucleotide identity).

Image reconstruction from incomplete measurements is one basic task in imaging. While supervised deep learning has emerged as a powerful tool for image reconstruction in recent years, its applicability is limited by its prerequisite on a large number of latent images for model training. To extend the application of deep learning to the imaging tasks where acquisition of latent images is challenging, this paper proposes an unsupervised deep learning method that trains a deep model for image reconstruction with the access limited to measurement data...

Question matching is the fundamental task in retrieval-based dialogue systems which assesses the similarity between Query and Question. Unfortunately, existing methods focus on improving the accuracy of text similarity in the general domain, without adaptation to the financial domain. Financial question matching has two critical issues: (1) How to accurately model the contextual representation of a financial sentence? (2) How to accurately represent financial key phrases in an utterance? To address these issues, this paper proposes a novel Fin ancial K nowledge E nhanced Net work (FinKENet) that significantly injects financial knowledge into contextual text...

Increased sales of natural products (NPs) in the US and growing safety concerns highlight the need for NP pharmacovigilance. A challenge for NP pharmacovigilance is ambiguity when referring to NPs in spontaneous reporting systems. We used a combination of fuzzy string-matching and a neural network to reduce this ambiguity. Our aim is to increase the capture of reports involving NPs in the US Food and Drug Administration Adverse Event Reporting System (FAERS). For this, we utilized Gestalt pattern-matching (GPM) and Siamese neural network (SM) to identify potential mentions of NPs of interest in 389,386 FAERS reports with unmapped drug names...

Most single-object trackers currently employ either a convolutional neural network (CNN) or a vision transformer as the backbone for object tracking. In CNNs, convolutional operations excel at extracting local features but struggle to capture global representations. On the other hand, vision transformers utilize cascaded self-attention modules to capture long-range feature dependencies but may overlook local feature details. To address these limitations, we propose a target-tracking algorithm called CVTrack, which leverages a parallel dual-branch backbone network combining CNN and Transformer for feature extraction and fusion...

Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used...

Breast cancer is one of the most prevalent cancers among women. It is the second leading cause of death in cancer-related deaths. Early detection and personalized risk assessment can reduce the mortality rate and improve survival rates. Classical risk prediction models which rely on traditional risk factors produce inconsistent results among the different populations. Thus, they are not routinely used in screening programs. Deep learning was proven to improve the results of breast cancer risk prediction. CNNs can detect risk cues from screening mammograms...

Deformable medical image registration plays an important role in many clinical applications. It aims to find a dense deformation field to establish point-wise correspondences between a pair of fixed and moving images. Recently, unsupervised deep learning-based registration methods have drawn more and more attention because of fast inference at testing stage. Despite remarkable progress, existing deep learning-based methods suffer from several limitations including: (a) they often overlook the explicit modeling of feature correspondences due to limited receptive fields; (b) the performance on image pairs with large spatial displacements is still limited since the dense deformation field is regressed from features learned by local convolutions; and (c) desirable properties, including topology-preservation and the invertibility of transformation, are often ignored...

The purpose of this study is to determine how photo biomodulation therapy utilizing infrared diode laser irradiation (975.2 nm) affects the gonadal maturity level (GML) of male Siamese catfish (Pan-gasianodon hypothalamus). The interest in applying laser therapy in medicine and dentistry has remarkably increased in the last decade. Different types of lasers are available, and their usage is well-defined by different parameters, such as wavelength, energy density, power output, duration of radiation, power density and radiation mode...

Face verification, crucial for identity authentication and access control in our digital society, faces significant challenges when comparing images taken in diverse environments, which vary in terms of distance, angle, and lighting conditions. These disparities often lead to decreased accuracy due to significant resolution changes. This paper introduces an adaptive face verification solution tailored for diverse conditions, particularly focusing on Unmanned Aerial Vehicle (UAV)-based public safety applications...

AA-amyloidosis in Siamese and Oriental shorthair cats is a lethal condition in which amyloid deposits accumulate systemically, especially in the liver and the thyroid gland. The age at death of affected cats varies between one and seven years. A previous study indicated a complex mode of inheritance involving a major locus. In the present study, we performed a multi-locus genome-wide association study (GWAS) using five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB and ISIS EM-BLASSO) to identify variants associated with AA-amyloidosis in Siamese/Oriental cats...

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Alzheimer's disease (AD) is a degenerative neurologic condition that results in the deterioration of several brain processes (e.g. memory loss). The most notable physical alteration in AD is the impairment of brain cells. An accurate examination of brain pictures may help to find the disease earlier because early diagnosis is crucial to enhancing patient care and treatment outcomes. Therefore, an easy and error-free system for AD diagnosis has recently received much research attention. Conventional image processing techniques sometimes cannot observe the significant features...

BACKGROUND: Siamese network (SN) using longitudinal DCE-MRI for pathologic complete response (pCR) identification lack a unified approach to phases selection. PURPOSE: To identify pCR in early-stage NAC, using SN with longitudinal DCE-MRI and introducing IPS for phases selection. STUDY TYPE: Multicenter, longitudinal. POPULATION: Center A: 162 female patients (50.63 ± 8.41 years) divided 7:3 into training and internal validation cohorts...

Conjoined twins (CTs), popularly referred to as Siamese twins, are a rare anomaly due to monochorionic and monoamniotic twin pregnancies. Dicephalus dibrachius dipus, a type of parapagus conjoined twin which is characterized by possessing two arms, two legs, a single trunk and two heads, epidemiologically, is an even rarer occurrence of CTs. In this article, a rare, well-preserved anatomical specimen of a dicephalus dibrachius dipus conjoined twin is presented. This study was conducted in a specimen which is part of the collection of the Embryology Museum of the institution by donation and approved by the Research Ethics Committee (REC)...

Systemic treatment is a main way for pancreas cancer patients that are ineligible for surgery. A subgroup of patients showed good response to systemic treatment and the rest received limited benefits. CT images provide a non-invasive way to assess the treatment response. Alternative non-image methods include radiology analysis, tumor marker analysis and combination analysis. To combine the image and non-image data, we propose the Siamese Delta Network with Multimodality Fusion (SDN-MF) to predict systemic treatment response in an end-to-end way...

Hyperspectral images provide a wealth of spectral and spatial information, offering significant advantages for the purpose of tracking objects. However, Siamese trackers are unable to fully exploit spectral features due to the limited number of hyperspectral videos. The high-dimensional nature of hyperspectral images complicates the model training process. In order to address the aforementioned issues, this article proposes a hyperspectral object tracking (HOT) algorithm callled SiamPKHT, which leverages the SiamCAR model by incorporating pyramid shuffle attention (PSA) and knowledge distillation (KD)...

The growing on-board processing capabilities have led to more complex sensor configurations, enabling autonomous car prototypes to expand their operational scope. Nowadays, the joint use of LiDAR data and multiple cameras is almost a standard and poses new challenges for existing multi-modal perception pipelines, such as dealing with contradictory or redundant detections caused by inference on overlapping images. In this paper, we address this last issue in the context of sequential schemes like F-PointNets, where object candidates are obtained in the image space, and the final 3D bounding box is then inferred from point cloud information...

Barrier islands are vital dynamic landforms that not only host ecological resources but often protect coastal ecosystems from storm damage. The Waisanding Barrier (WSDB) in Taiwan has suffered from continuous beach erosion in recent decades. In this study, we developed a SiamUnet network compared to three basic DeepUnet networks with different image sizes to effectively detect barrier waterlines from 207 high-resolution satellite images. The evolution of the barrier waterline shape is obtained to present two special morphologic changes at the southern end and the evolution of the entire waterline...

Colorectal cancer is a leading cause of cancer-related deaths globally. In recent years, the use of convolutional neural networks in computer-aided diagnosis (CAD) has facilitated simpler detection of early lesions like polyps during real-time colonoscopy. However, the majority of existing techniques require a large training dataset annotated by experienced experts. To alleviate the laborious task of image annotation and utilize the vast amounts of readily available unlabeled colonoscopy data to further improve the polyp detection ability, this study proposed a novel self-supervised representation learning method called feature pyramid siamese networks (FPSiam)...