For scalar maximum distance separable (MDS) codes, the conventional repair schemes that achieve the cut-set bound with equality for the single-node repair have been proven to require a super-exponential sub-packetization level.As is well known, such an extremely high level severely limits the practical deployment of MDS codes.To address this challenge, we introduce a partial-exclusion (PE) repair scheme for scalar linear codes.In the proposed PE repair framework, each node is associated with an exclusion set.The cardinality of the exclusion set is called the flexibility of the node.The maximum value of flexibility over all nodes defines the flexibility of the PE repair scheme. Notably, the conventional repair scheme is the special case of PE repair scheme where the flexibility is 1. Under the PE repair framework, for any valid flexibility, we establish a lower bound on the sub-packetization level of MDS codes that meet the cut-set bound with equality for single-node repair. To realize MDS codes attaining the cut-set bound under the PE repair framework, we propose two generic constructions of Reed-Solomon (RS) codes. Moreover, we demonstrate that for a sufficiently large flexibility, the sub-packetization level of our constructions is strictly lower than the known lower bound established for the conventional repair schemes.This implies that, from the perspective of sub-packetization level, our constructions outperform all existing and potential constructions designed for conventional repair schemes. Finally, we implement the repair process for these codes as executable Magma programs, thereby exhibiting the practical efficiency of our constructions.

Locally repairable codes (LRCs) characterize the repair overhead in terms of locality. Optimal LRCs attain the best possible trade-off between dimension and minimum distance. For optimal LRCs, a larger code length relative to a given symbol field size offers the advantage of a larger minimum distance. Extensive research has been conducted on the explicit construction of optimal LRCs with super-linear code length (relative to the field size). However, all existing optimal LRCs with super-linear code length possess a small minimum distance. Constructing optimal LRCs with super-linear code length and a large minimum distance remains a challenging and meaningful problem. In this paper, we propose a generic construction of LRCs. This construction is based on bivariate polynomial evaluation approach. Using this construction, we obtain a new class of optimal LRCs with super-linear code lengths. To the best of our knowledge, the proposed class of optimal LRCs attains the largest minimum distance while the code lengths up to O(q2).

Parathyroid carcinoma (PC) and atypical parathyroid tumor (APT) are rare malignant lesions characterized by high recurrence and metastasis rates, and accurate preoperative diagnosis remains a clinical challenge. The purpose of this study was to explore the diagnostic value of preoperative grayscale ultrasound combined with shear wave elastography (SWE) for such lesions. In this retrospective case-control study, patients with primary hyperparathyroidism and suspicious parathyroid abnormality on ultrasonography were recruited. All the lesions were assessed by SWE before surgery. Sonographic features and SWE performance along with demographic and related clinical parameters between PC/APT and PA groups were analyzed. This study included 21 patients with PC or APT matched to 84 patients with PA who underwent parathyroid surgery. The best subset selection method and multiple logistic regression analysis identified the sonographic features of intra-nodal fibrous bands and the ratio of mean shear wave velocity in tumor (SWVmean)/shear wave velocity in thyroid parenchyma (SWVth) as independent factors for PC/APT prediction (odds ratio [OR] = 38.536, 95

Reed-Solomon (RS) codes are widely used in distributed storage systems (DSS), where node repair is a critical and frequent operation. This work addresses the repair of RS codes under the rack-aware model, wherein nodes are organized into equal-size racks, and only cross-rack communication contributes to repair bandwidth. While existing rack-aware RS codes support efficient repair, few achieve the minimum repair bandwidth dictated by the rack-aware cut-set bound. This paper extends prior optimal constructions by introducing a new class of rack-aware RS codes that achieve the rack-aware cut-set bound with equality for single-node repair. Compared to the existing rack-aware RS codes with optimal repair bandwidth, our construction offers greater parameter flexibility and a reduced sub-packetization level.

Grammatical error classification plays a crucial role in language learning systems, but existing classification taxonomies often lack rigorous validation, leading to inconsistencies and unreliable feedback. In this paper, we revisit previous classification taxonomies for grammatical errors by introducing a systematic and qualitative evaluation framework. Our approach examines four aspects of a taxonomy, i.e., exclusivity, coverage, balance, and usability. Then, we construct a high-quality grammatical error classification dataset annotated with multiple classification taxonomies and evaluate them grounding on our proposed evaluation framework. Our experiments reveal the drawbacks of existing taxonomies. Our contributions aim to improve the precision and effectiveness of error analysis, providing more understandable and actionable feedback for language learners.

Symbol-pair codes are a class of block codes with symbol-pair metrics designed to protect against pair errors that may occur in high-density data storage systems. Maximum distance separable (MDS) symbol-pair codes are optimal in the sense that they can attain the highest pair-error correctability within the same code length and code size. Constructing MDS symbol-pair codes is one of the main topics in symbol-pair code research. In this paper, we investigate and characterize the symbol-pair distances of constacyclic codes of arbitrary lengths over finite fields and finite chain rings. Using the characterization of the symbol-pair distance, we present three new classes of MDS symbol-pair constacyclic codes that exhibit large minimum distances.

A locally repairable code (LRC) with locality r allows for the recovery of any erased codeword symbol using at most r other codeword symbols. The Singleton-type bound dictates a best possible tradeoff between the dimension, the minimum distance and the locality of LRCs. An LRC attaining this tradeoff is said to be optimal. A constacyclic LRC is an LRC with constacyclic structure which can be encoded efficiently using any encoding algorithm for cyclic codes in general. In this paper we consider the optimal constacyclic LRCs of length ηps over finite fields, where p is the characteristic of the finite fields, s is a positive integer and η is a positive integer coprime to p. We obtain several infinite classes of optimal constacyclic LRCs with new parameters. Furthermore, under a further assumption that the ambient space Fpm[x]/〈xηps−λ〉 of the repeated-root constacyclic codes is a chain ring, we characterize all the possible optimal constacyclic LRCs in Fpm[x]/〈xηps−λ〉.

The annotation scarcity of medical image segmentation poses challenges in collecting sufficient training data for deep learning models. Specifically, models trained on limited data may not generalize well to other unseen data domains, resulting in a domain shift issue. Consequently, domain generalization (DG) is developed to boost the performance of segmentation models on unseen domains. However, the DG setup requires multiple source domains, which impedes the efficient deployment of segmentation algorithms in clinical scenarios. To address this challenge and improve the segmentation model's generalizability, we propose a novel approach called the Frequency-mixed Single-source Domain Generalization method (FreeSDG). By analyzing the frequency's effect on domain discrepancy, FreeSDG leverages a mixed frequency spectrum to augment the single-source domain. Additionally, self-supervision is constructed in the domain augmentation to learn robust context-aware representations for the segmentation task. Experimental results on five datasets of three modalities demonstrate the effectiveness of the proposed algorithm. FreeSDG outperforms state-of-the-art methods and significantly improves the segmentation model's generalizability. Therefore, FreeSDG provides a promising solution for enhancing the generalization of medical image segmentation models, especially when annotated data is scarce. The code is available at https://github.com/liamheng/Non-IID_Medical_Image_Segmentation.

Determining the weight distribution of a linear code is a classical and fundamental topic in coding theory that has been extensively investigated. Repeated-root cyclic codes, which form a significant subclass of error-correcting codes, have found broad applications in quantum error-correcting codes, symbol-pair codes, and storage codes. Through polynomial derivation, we derive the monomial equivalent codes for these repeated-root cyclic codes with prime power lengths. Given that monomial equivalent codes exhibit identical weight distributions, we transform the computation of the weight distribution of these repeated-root cyclic codes into the computation of the weight distribution of their monomial equivalent codes. Leveraging the classical results on the weight distribution of MDS codes, we explicitly determine the weight distribution of these repeated-root cyclic codes. Moreover, we apply the weight distribution formula to construct a class of p-weight cyclic codes for any prime p.

Aim Intrathyroidal parathyroid adenoma (IPA) is rare and may easily be mistaken for thyroid nodule in ultrasonography. The aim of this study was to investigate the characteristic features of IPA and explore the value of preoperative and intraoperative ultrasound in the diagnosis and localization of IPA. Methods 13 of 216 patients who were found to have intrathyroidal parathyroid lesions underwent parathyroidectomy in our hospital because of PHPT. According to the relationship between parathyroid adenoma and thyroid gland, parathyroid adenoma was divided into extra-thyroid type or intra-thyroid type (partial or complete) and the results were compared with surgical and histopathological reports as gold standard. The sonographic features of intrathyroidal parathyroid lesions were analyzed retrospectively. Results A total of 12 intrathyroidal lesions showed profoundly hypoechoic solid nodules with well-defined border, abundant blood flow and polar feeding vessels originating from the superior or inferior thyroid artery (92.3%, 12/13). These nodules were finally confirmed as IPA (or IPAC) after surgery. Polar feeding vessel was not detected in one case of parathyroid hyperplasia confirmed by pathology (7.7%, 1/13). 12 cases were diagnosed and localized on ultrasonography before operation and 10 cases were localized on Tc-99m MIBI SPECT/CT. Conclusions The color Doppler ultrasound findings of IPA were confirmed as profoundly hypoechoic nodules with clear boundary and abundant internal blood flow. The presence of polar feeding vessels which originate from thyroid artery were identified as characteristic features of US for IPA. Preoperative and intraoperative ultrasound could be helpful in the localization and treatment of intrathyroidal parathyroid diseases.

Asymmetric quantum error-correcting codes (AQECCs) with high code rates and large distances play a crucial role in protecting quantum information from noise and decoherence. Our contributions of this paper are twofold. One is the construction of new AQECCs by repeated-root cyclic codes and proposing some AQECCs with higher code rates or asymmetries than those in the literature that match or exceed the asymmetric quantum Gilbert–Varshamov bound. The other is the construction of five classes of MDS AQECCs attaining the asymmetric quantum Singleton bound, which have higher code rates than most of the ones obtained in the literature.

Abstract Background Primary hyperparathyroidism (PHPT) results from an excess of parathyroid hormone (PTH) produced from an overactive parathyroid gland. The study aimed to explore the sonographic features of parathyroid adenomas and assess the diagnostic performance of ultrasonography (US) and Tc-99m MIBI SPECT/CT for preoperative localization of parathyroid adenomas. Methods A total of 107 patients were enrolled in this retrospective study who had PHPT and underwent parathyroidectomy. Of the 107 patients, 97 performed US and Tc-99m MIBI SPECT/CT examinations for preoperative localization of parathyroid nodules. The sensitivity and accuracy of each modality were calculated. Results In this study, residual parathyroid sign and polar vascular sign were identified as characteristic US features of parathyroid adenomas. These manifestations were closely related to the size of the abnormal parathyroid lesions. Among the 108 parathyroid nodules from 97 patients with PHPT, the sensitivity and accuracy of US for locating the parathyroid nodules were significantly higher than those of Tc-99m MIBI SPECT/CT (93.0% vs. 63.0% and 88.0% vs. 63.0% respectively; χ2 = 26.224, 18.227 respectively, P < 0.001). The differences between US + Tc-99m MIBI SPECT/CT and Tc-99m MIBI SPECT/CT-alone were statistically significant (χ2 = 33.410, 21.587 respectively, P < 0.001), yet there were no significant differences in the sensitivity or accuracy between US + Tc-99m MIBI SPECT/CT and US-alone (χ2 = 0.866, 0.187 respectively, P = 0.352 and 0.665). Conclusions US shows significantly better sensitivity and accuracy for localization of parathyroid adenomas than Tc-99m MIBI SPECT/CT. However, US combined with Tc-99m MIBI SPECT/CT is of great clinical value in the preoperative localization of parathyroid nodules in patients with PHPT.

Image alignment and colour consistency are two challenging tasks for image stitching. Traditional point correspondence methods are difficult to achieve good alignments due to their insufficiency and unreliability. The results are prone to errors and distortions. On the other hand, the problem of colour inconsistency in overlapping area between image pairs is still difficult to solve, especially when the illumination difference between images is large. To solve these problems, the authors integrate point features and line features into a warping model through a designed energy function. Line features will provide geometric constraints for image stitching, and remedy the defect of point correspondences in low-textured image stitching. A global colour consistency optimization method with colour mapping via a histogram extreme point-matching algorithm is proposed. The colour characteristic of reference images will be transferred to the others to achieve a global colour consistency. The proposed method is evaluated on a series of images, and compared with other methods. The experiments demonstrate that the proposed method provides convincing stitching results and achieves satisfied colour consistency results.

目的 分析原发性甲状旁腺功能亢进症(PHPT)甲状旁腺病变声像图特征.方法 对临床诊断为PHPT的107例患者术前采集超声图像,以手术切除后病理作为金标准,探讨PHPT的声像图特征.结果 对术后病理明确诊断为甲状旁腺病变的107个结节绘制ROC曲线,曲线下面积分别为0.670和0.675,与0.05相比有统计学差异(P=0.005、0.001),故当结节最大直径≤1.55 cm时,残余甲状旁腺征预测甲状旁腺病变的灵敏度和特异度分别为63.0％和63.9％;当结节最大直径≥1.35 cm时,极性供支血管征预测甲状旁腺病变的灵敏度和特异度分别为79.0％和55.6％;当两种征象同时显示时,联合灵敏度和特异度分别为92.2％和35.5％.结论 残余甲状旁腺征及极性供支血管征是PHPT时甲状旁腺病变的特征性的声像图改变,且此两种征象的显示与甲状旁腺病变的大小密切相关.

Symbol-pair codes are block codes when considering the pair-metric, and are designed to protect against pair-errors occur in the pair-read vector which consisting of overlapping pairs of symbols. A code that achieves the analog of Singleton bound for symbol-pair codes is called a maximum distance separable (MDS) symbol-pair code. The contribution of this letter is twofold. First, we give a lower bound of minimum pair-distance of repeated-root constacyclic codes in terms of minimum Hamming distance, which extends the lower bound given by Chen, Lin and Liu. Second, we give three new classes of MDS symbol-pair codes. As we know, for an MDS symbol-pair code with a fixed minimum pair-distance, the larger the code length of the code has, the higher the code rate is. The first class of MDS symbol-pair codes we show has unbounded code length and the other two classes of MDS symbol-pair codes have larger code lengths than the code lengths of existing MDS symbol-pair codes under the same minimum pair-distance 6.

In this paper, we propose to align sentence representations from different languages into a unified embedding space, where semantic similarities (both cross-lingual and monolingual) can be computed with a simple dot product. Pre-trained language models are fine-tuned with the translation ranking task. Existing work (Feng et al., 2020) uses sentences within the same batch as negatives, which can suffer from the issue of easy negatives. We adapt MoCo (He et al., 2020) to further improve the quality of alignment. As the experimental results show, the sentence representations produced by our model achieve the new state-of-the-art on several tasks, including Tatoeba en-zh similarity search (Artetxe and Schwenk, 2019b), BUCC en-zh bitext mining, and semantic textual similarity on 7 datasets.

PURPOSE:To explore the application value of SMI scoring assignment method combined with 2017 American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS) in differentiating benign and malignant thyroid nodules.METHODS:According to the 2017 ACR TI-RADS classification, the enrolled nodules were divided into 3 points group, 4 points group, 5 points group, 6 points group and≥7 points group. The nodules were assigned scores according to the echocity of the nodules and the microvessels detected by SMI and their distribution patterns based on ACR TI-RADS. Accompany with the scores increased or decreased after assignment, the thyroid nodules were re-grouped.RESULTS:The AUC after the scores assignment is better than before (Z = 3.881, P < 0.001). The specificity, positive predictive value and accuracy after score assigned are better than those of before (Z = 8.323, P < 0.001; Z = 8.619, P < 0.001; Z = 5.345, P < 0.001), there is no statistical difference in sensitivity before and after score assigned (Z = -0.513, P = 0.60), and the negative predictive value before assigned score is better than that of after (Z = -3.826, P < 0.001).CONCLUSION:The diagnostic efficacy after scoring was better than that of before.

The multi-label electrocardiogram (ECG) classification is to automatically predict a set of concurrent cardiac abnormalities in an ECG record, which is significant for clinical diagnosis. Modeling the cardiac abnormality dependencies is the key to improving classification performance. To capture the dependencies, we proposed a multi-label classification method based on the weighted graph attention networks. In the study, a graph taking each class as a node was mapped and the class dependencies were represented by the weights of graph edges. A novel weights generation method was proposed by combining the self-attentional weights and the prior learned co-occurrence knowledge of classes. The algorithm was evaluated on the dataset of the Hefei Hi-tech Cup ECG Intelligent Competition for 34 kinds of ECG abnormalities classification. And the micro-f1 and the macro-f1 of cross validation respectively were 91.45% and 44.48%. The experiment results show that the proposed method can model class dependencies and improve classification performance.

Lens structures segmentation on anterior segment optical coherence tomography (AS-OCT) images is a fundamental task for cataract grading analysis. In this paper, in order to reduce the computational cost while keeping the segmentation accuracy, we propose an efficient segmentation method for lens structures segmentation. At first, we adopt an efficient semantic segmentation network in the work, and used it to extract the lens area image instead of the conventional object detection method, and then used it once again to segment the lens structures. Finally, we introduce the curve fitting processing (CFP) on the segmentation results. Experiment results show that our method has good performance on accuracy and processing speed, and could be applied to CASIA II device for practical applications.

In the service oriented architecture (SOA), software and systems are abstracted as web services to be invoked by other systems. Service composition is a technology, which builds a complex system by combining existing simple services. With the development of SOA and web service technology, massive web services with the same function begin to spring up. These services are maintained by different organizations and have different QoS (Quality of Service). Thus, how to choose the appropriate service to make the whole system to deliver the best overall QoS has become a key problem in service composition research. Furthermore, because of the complexity and dynamics of the network environment, QoS may change over time. Therefore, how to adjust the composition system dynamically to adapt to the changing environment and ensure the quality of the composed service also poses challenges. To address the above challenges, we propose a service composition approach based on QoS prediction and reinforcement learning. Specifically, we use a recurrent neural network to predict the QoS, and then make dynamic service selection through reinforcement learning. This approach can be well adapted to a dynamic network environment. We carry out a series of experiments to verify the effectiveness of our approach.