Analytic decay width of the Higgs boson to massive bottom quarks at next-to-next-to-leading order in QCD

The Higgs boson decay to a massive bottom quark pair provides the dominant contribution to the Higgs boson width. We present an exact result for such a decay induced by the bottom quark Yukawa coupling with next-to-next-to-leading order (NNLO) QCD corrections. We have adopted the canonical differential equations in the calculation and obtained the result in terms of multiple polylogarithms. We also compute the contribution from the decay to four bottom quarks which consist of complete elliptic integrals or their one-fold integrals. The small bottom quark mass limit coincides with the previous calculation using the large momentum expansion. The threshold expansion exhibits power divergent terms in the bottom quark velocity, which has a structure different from that in $e^+e^-\to t\bar{t}$ but can be reproduced by computing the corresponding Coulomb Green function. The NNLO corrections significantly reduce the uncertainties from both the renormalization scale and the renormalization scheme of the bottom quark Yukawa coupling. Our result can be applied to a heavy scalar decay to a top quark pair.Comment: 29 pages, 11 figure

El patrimonio intangible como recurso turístico cultural: diseño de un producto turístico basado en el Bordado Shu

El patrimonio intangible ha demostrado ser un recurso turístico esencial para el turismo cultural. Dicho patrimonio incluye expresiones culturales muy diversas transmitidas de generación en generación. En este trabajo se aborda el uso de un tipo concreto de patrimonio intangible, el bordado Shu, como recurso turístico. El bordado Shu tiene una gran importancia histórica, pero su desarrollo en la actualidad es relativamente lento, por lo que es un patrimonio cultural inmaterial que se enfrenta a una crisis de herencia y desarrollo. Por ello, el presente Trabajo Fin de Máster tiene como objetivo descubrir si el bordado Shu tiene la capacidad de convertirse en un producto turístico exitoso, para así estudiar el interés del público, comprender el perfil de la clientela interesada y diseñar un producto turístico completo que lo incorpore. Para ello se llevó a cabo un cuestionario online a 326 personas que mostró la idoneidad de introducir este recurso junto a otros de carácter cultural, conformando un producto único.<br /

Clinical outcomes following surgical mitral valve plasty or replacement in patients with infectious endocarditis: A meta-analysis

BackgroundFor degenerative mitral disease, more and more evidences support that mitral valve plasty (MVP) has much better clincial outcomes than mitral valve replacement (MVR). However, the advantages of MVP in patients suffering from infectious endocarditis (IE) are unclear. To evaluate the appropriateness of MVP in IE patients, we conducted this meta-analysis. Based on the difference between active and healed phase, we not only compared the result of patients with IE, but also identified the subgroup with active IE.MethodsWe systematically searched the clinical trials comparing clinical outcomes of MVP and MVR in patients suffering from IE. Relevant articles were searched from January 1, 2000 to March 18, 2021 in Pubmed and Cochrane Library. Studies were excluded if they were with Newcastle–Ottawa Scale (NOS) score less than 6 or lacking of direct comparisons between MVP and MVR.Results23 studies were involved and 25,615 patients were included. Pooled analysis showed fewer adverse events and early or long-term death in the MVP group. However, more reoperations existed in this patient group. And the reinfection rate was close between two groups. Similar results were observed after identifying active IE subgroup, but there is no difference in the freedom from reoperation due to all-events.ConclusionsAlthough limitimations exited in this study, patients suffering from IE can benefit from both MVP and MVR. For surgeons with consummate skills, MVP can be the preferred choice for suitable IE patients

Neural Locality Sensitive Hashing for Entity Blocking

Locality-sensitive hashing (LSH) is a fundamental algorithmic technique widely employed in large-scale data processing applications, such as nearest-neighbor search, entity resolution, and clustering. However, its applicability in some real-world scenarios is limited due to the need for careful design of hashing functions that align with specific metrics. Existing LSH-based Entity Blocking solutions primarily rely on generic similarity metrics such as Jaccard similarity, whereas practical use cases often demand complex and customized similarity rules surpassing the capabilities of generic similarity metrics. Consequently, designing LSH functions for these customized similarity rules presents considerable challenges. In this research, we propose a neuralization approach to enhance locality-sensitive hashing by training deep neural networks to serve as hashing functions for complex metrics. We assess the effectiveness of this approach within the context of the entity resolution problem, which frequently involves the use of task-specific metrics in real-world applications. Specifically, we introduce NLSHBlock (Neural-LSH Block), a novel blocking methodology that leverages pre-trained language models, fine-tuned with a novel LSH-based loss function. Through extensive evaluations conducted on a diverse range of real-world datasets, we demonstrate the superiority of NLSHBlock over existing methods, exhibiting significant performance improvements. Furthermore, we showcase the efficacy of NLSHBlock in enhancing the performance of the entity matching phase, particularly within the semi-supervised setting

HAM-TTS: Hierarchical Acoustic Modeling for Token-Based Zero-Shot Text-to-Speech with Model and Data Scaling

Token-based text-to-speech (TTS) models have emerged as a promising avenue for generating natural and realistic speech, yet they grapple with low pronunciation accuracy, speaking style and timbre inconsistency, and a substantial need for diverse training data. In response, we introduce a novel hierarchical acoustic modeling approach complemented by a tailored data augmentation strategy and train it on the combination of real and synthetic data, scaling the data size up to 650k hours, leading to the zero-shot TTS model with 0.8B parameters. Specifically, our method incorporates a latent variable sequence containing supplementary acoustic information based on refined self-supervised learning (SSL) discrete units into the TTS model by a predictor. This significantly mitigates pronunciation errors and style mutations in synthesized speech. During training, we strategically replace and duplicate segments of the data to enhance timbre uniformity. Moreover, a pretrained few-shot voice conversion model is utilized to generate a plethora of voices with identical content yet varied timbres. This facilitates the explicit learning of utterance-level one-to-many mappings, enriching speech diversity and also ensuring consistency in timbre. Comparative experiments (Demo page: https://anonymous.4open.science/w/ham-tts/)demonstrate our model's superiority over VALL-E in pronunciation precision and maintaining speaking style, as well as timbre continuity

Binary quantization vision transformer for effective segmentation of red tide in multi-spectral remote sensing imagery.

As a global marine disaster, red tides pose serious threats to marine ecology and the blue economy, making their monitoring crucial for preventing harmful algal blooms and protecting the marine environment. In this study, satellite remote sensing was utilized to provide timely, large-scale, and continuous observation capabilities, overcoming the high cost and spatial and temporal limitations of in-situ monitoring. However, existing remote sensing-based methods often exhibit coarse segmentation granularity and suffer from high computational complexity. To overcome these challenges, we propose a novel bi-modal multispectral dynamic offset binary quantization visual transformer (DoBi-SWiP-ViT) that utilizes the ViT for global feature aggregation and parameter quantization for efficient segmentation. With the Bi-modal Swin-ViT with Unified Perceptual Parsing architecture, our model integrates data from multiple spectral bands to achieve fine-grained segmentation of large-scale remote sensing images. Additionally, we introduce a dynamic magnitude offset binary quantization ViT block to reduce the parameter redundancy and improve the computational efficiency. In addition, we validated the performance of our model through extensive comparative experiments on high-resolution imagery datasets of sea surface red tides collected from different satellite platforms. The results show that our proposed DoBi-SWiP-ViT has significantly improved the mean accuracy (mAcc) of the segmentation results. For the two test areas acquired from different satellite platforms, the improvements are 8.78% and 10.18%, respectively. This has demonstrated the superior performance of our model in detecting the red tides from high-resolution visible images, highlighting its effectiveness in capturing complex patterns and subtle features in multi-spectral imagery

Causes and predictors of unplanned reoperations within 30 days post laparoscopic pancreaticoduodenectomy: a comprehensive analysis

ObjectiveTo delineate the risk factors and causes of unplanned reoperations within 30 days following laparoscopic pancreaticoduodenectomy (LPD).MethodsA retrospective study reviewed 311 LPD patients at Ningbo Medical Center Li Huili Hospital from 2017 to 2024. Demographic and clinical parameters were analyzed using univariate and multivariate analyses, with P &lt; 0.05 indicating statistical significance.ResultsOut of 311 patients, 23 (7.4%) required unplanned reoperations within 30 days post-LPD, primarily due to postoperative bleeding (82.6%). Other causes included anastomotic leakage, abdominal infection, and afferent loop obstruction. The reoperation intervals varied, with the majority occurring within 0 to 14 days post-surgery. Univariate analysis identified significant risk factors: diabetes, liver cirrhosis, elevated CRP on POD-3 and POD-7, pre-operative serum prealbumin &lt; 0.15 g/L, prolonged operation time, intraoperative bleeding &gt; 120 ml, vascular reconstruction, soft pancreatic texture, and a main pancreatic duct diameter ≤3 mm (all P &lt; 0.05). Multivariate analysis confirmed independent risk factors: pre-operative serum prealbumin &lt; 0.15 g/L (OR = 3.519, 95% CI 1.167-10.613), CRP on POD-7 (OR = 1.013, 95% CI 1.001-1.026), vascular reconstruction (OR = 9.897, 95% CI 2.405-40.733), soft pancreatic texture (OR = 5.243, 95% CI 1.628-16.885), and a main pancreatic duct diameter ≤3 mm (OR = 3.462, 95% CI 1.049-11.423), all associated with unplanned reoperation within 30 days post-LPD (all P &lt; 0.05).ConclusionPostoperative bleeding is the primary cause of unplanned reoperations after LPD. Independent risk factors, confirmed by multivariate analysis, include low pre-operative serum prealbumin, elevated CRP on POD-7, vascular reconstruction, soft pancreatic texture, and a main pancreatic duct diameter of ≤3 mm. Comprehensive peri-operative management focusing on these risk factors can reduce the likelihood of unplanned reoperations and improve patient outcomes

Impact of natural and socio-economic factors on varicella incidence in children in Shanghai, 2013-2022

BackgroundSince varicella is already known to be a globally distributed disease, the focus should be more on its transmissibility or disease burden. The incidence of varicella is affected by natural and socio-economic factors. However, it is unclear how these factors synergetically impact the dynamics of varicella transmission and control.MethodsWe conducted a retrospective analysis of varicella cases in children aged 0–17 years from 2013 to 2022 in Jiading District, Shanghai, China. First, we evaluated demographic characteristics, epidemiological trends of varicella. And then, we explored the impact of two-dose varicella vaccine (VarV) program on varicella incidence using interrupted time-series analyses, and assessed the influence of natural and socio-economic factors using principal component analysis and multivariate regression. Spatial analysis was conducted to compare varicella epidemiology.ResultsOur analysis includes 6,482 reported varicella cases, with a higher incidence observed among males (58.67%). Regional differences were noted, with the highest incidence in the western region and the lowest in the central region. Before the implementation of the two-dose VarV program, varicella incidence increased by 0.28 cases per 100,000 per month. Following the two-dose VarV program’s introduction, the incidence rate decreased by 0.49 cases per 100,000 per month, with an impressive 79.10% reduction in the annual average incidence among children aged 4–6 years. By analyzing the impact of demographic characteristics, healthcare capacity, economic level, air pollutants, and meteorological factors on the incidence of varicella, we found that the child population ratio and VarV program were most strongly associated with varicella incidence.ConclusionThe study underscores the importance of sustained monitoring of child population ratio and VarV program to reduce varicella transmission and protect vulnerable groups