STUDY ON OPTIMAL COMBINATION SETTLEMENT PREDICTION MODEL BASED ON LOGISTIC CURVE AND GOMPERTZ CURVE

The Logistic and Gompertz embankment settlement prediction models have poor prediction accuracy for the late settlement of high-filled soil. This study proposes a combination of the two models based on their common characteristics and individuality, and their respective advantages and specific limitations. The minimum logarithmic error square sum of the combined model was used as the objective function to solve the optimal weighting coefficient. The optimal weighted geometric mean combination prediction model was deduced, to improve the confidence of the prediction accuracy of the settlement of high-filled soil. By fitting and analysing the measured settlement data of the engineered high-filled soil with each prediction model, the feasibility of the proposed optimal combination prediction model in the settlement prediction of high-filled soil was tested. It was found that the proposed optimal combination forecasting model was more accurate and adaptable compared to any single model, and was more reliable. Therefore, the proposed combination forecasting model could be used as an effective method to predict the settlement of high-filled soil in the later stages of settlement

Distributed optimization for multi-agent systems with communication delays and external disturbances under a directed network

This article studies the distributed optimization problem for multi-agent systems with communication delays and external disturbances in a directed network. Firstly, a distributed optimization algorithm is proposed based on the internal model principle in which the internal model term can effectively compensate for external environmental disturbances. Secondly, the relationship between the optimal solution and the equilibrium point of the system is discussed through the properties of the Laplacian matrix and graph theory. Some sufficient conditions are derived by using the Lyapunov–Razumikhin theory, which ensures all agents asymptotically reach the optimal value of the distributed optimization problem. Moreover, an aperiodic sampled-data control protocol is proposed, which can be well transformed into the proposed time-varying delay protocol and analyzed by using the Lyapunov–Razumikhin theory. Finally, an example is given to verify the effectiveness of the results

Group Network Hawkes Process

In this work, we study the event occurrences of individuals interacting in a network. To characterize the dynamic interactions among the individuals, we propose a group network Hawkes process (GNHP) model whose network structure is observed and fixed. In particular, we introduce a latent group structure among individuals to account for the heterogeneous user-specific characteristics. A maximum likelihood approach is proposed to simultaneously cluster individuals in the network and estimate model parameters. A fast EM algorithm is subsequently developed by utilizing the branching representation of the proposed GNHP model. Theoretical properties of the resulting estimators of group memberships and model parameters are investigated under both settings when the number of latent groups $G$ is over-specified or correctly specified. A data-driven criterion that can consistently identify the true $G$ under mild conditions is derived. Extensive simulation studies and an application to a data set collected from Sina Weibo are used to illustrate the effectiveness of the proposed methodology.Comment: 35 page

Modeling Social Media User Content Generation Using Interpretable Point Process Models

In this article, we study the activity patterns of modern social media users on platforms such as Twitter and Facebook. To characterize the complex patterns we observe in users' interactions with social media, we describe a new class of point process models. The components in the model have straightforward interpretations and can thus provide meaningful insights into user activity patterns. A composite likelihood approach and a composite EM estimation procedure are developed to overcome the challenges that arise in parameter estimation. Using the proposed method, we analyze Donald Trump's Twitter data and study if and how his tweeting behavior evolved before, during and after the presidential campaign. Additionally, we analyze a large-scale social media data from Sina Weibo and identify interesting groups of users with distinct behaviors; in this analysis, we also discuss the effect of social ties on a user's online content generating behavior

The clinicopathological factors associated with disease progression in Luminal a breast cancer and characteristics of metastasis: A retrospective study from a single center in China

Background/Aim: This study investigated the clinicopathological factors associated with outcomes in patients with Luminal A breast cancer. Patients and Methods: Retrospective analysis of the association of clinicopathological factors and breast cancer outcome in 421 patients with newly diagnosed Luminal-A breast cancer that were enrolled from January 2008 to December 2014. Clinicopathological data were analyzed to validate the relationship with disease free survival (DFS) and overall survival (OS). Kaplan-Meier curves and log-rank tests were used to analyze the value of clinicopathological factors (tumor size, node status and lymphovascular invasion), and subsequent Cox regression analysis revealed significant prognostic factors. Results: With a median of 61 months follow up, the 5-year DFS and 5-year OS rate were 98.3% and 99.3%. Cox multivariate regression analysis showed that clinical anatomic stage, tumor size, status of lymph nodes, lymphovascular invasion and systemic treatment are strong prognostic factors for clinical outcome in patients with Luminal-A breast cancer. Of all 413 patients with stage I-III breast cancer, 14 presented with metastasis (3.4%) during the follow up. Bone (6/14, 42.9%) was the most common site of metastasis followed by liver (5/14, 35.7%) and lung (4/14, 28.6%). The median survival time after metastasis was 20.4 months. Of all the sites of distant metastasis, liver metastasis was the only factor that affected survival time after metastasis (χ2=6.263, p=0.012). Conclusion: Patients with Luminal A breast cancer have excellent outcomes. Liver metastasis is an important factor compressing the survival time after distant metastasis presents

A Wheat Cinnamyl Alcohol Dehydrogenase TaCAD12 Contributes to Host Resistance to the Sharp Eyespot Disease

peer reviewedSharp eyespot, caused mainly by the necrotrophic fungus Rhizoctonia cerealis, is a destructive disease in hexaploid wheat (Triticum aestivum L.). In Arabidopsis, certain cinnamyl alcohol dehydrogenases (CADs) have been implicated in monolignol biosynthesis and in defense response to bacterial pathogen infection. However, little is known about CADs in wheat defense responses to necrotrophic or soil-borne pathogens. In this study, we isolate a wheat CAD gene TaCAD12 in response to R. cerealis infection through microarray-based comparative transcriptomics, and study the enzyme activity and defense role of TaCAD12 in wheat. The transcriptional levels of TaCAD12 in sharp eyespot-resistant wheat lines were significantly higher compared with those in susceptible wheat lines. The sequence and phylogenetic analyses revealed that TaCAD12 belongs to IV group in CAD family. The biochemical assay proved that TaCAD12 protein is an authentic CAD enzyme and possesses catalytic efficiencies toward both coniferyl aldehyde and sinapyl aldehyde. Knock-down of TaCAD12 transcript significantly repressed resistance of the gene-silenced wheat plants to sharp eyespot caused by R. cerealis, whereas TaCAD12 overexpression markedly enhanced resistance of the transgenic wheat lines to sharp eyespot. Furthermore, certain defense genes (Defensin, PR10, PR17c, and Chitinase1) and monolignol biosynthesis-related genes (TaCAD1, TaCCR, and TaCOMT1) were up-regulated in the TaCAD12-overexpressing wheat plants but down-regulated in TaCAD12-silencing plants. These results suggest that TaCAD12 positively contributes to resistance against sharp eyespot through regulation of the expression of certain defense genes and monolignol biosynthesis-related genes in wheat.Nationa l“KeySci-Tech” Projec

AceGPT, Localizing Large Language Models in Arabic

This paper explores the imperative need and methodology for developing a localized Large Language Model (LLM) tailored for Arabic, a language with unique cultural characteristics that are not adequately addressed by current mainstream models like ChatGPT. Key concerns additionally arise when considering cultural sensitivity and local values. To this end, the paper outlines a packaged solution, including further pre-training with Arabic texts, supervised fine-tuning (SFT) using native Arabic instructions and GPT-4 responses in Arabic, and reinforcement learning with AI feedback (RLAIF) using a reward model that is sensitive to local culture and values. The objective is to train culturally aware and value-aligned Arabic LLMs that can serve the diverse application-specific needs of Arabic-speaking communities. Extensive evaluations demonstrated that the resulting LLM called `AceGPT' is the SOTA open Arabic LLM in various benchmarks, including instruction-following benchmark (i.e., Arabic Vicuna-80 and Arabic AlpacaEval), knowledge benchmark (i.e., Arabic MMLU and EXAMs), as well as the newly-proposed Arabic cultural \& value alignment benchmark. Notably, AceGPT outperforms ChatGPT in the popular Vicuna-80 benchmark when evaluated with GPT-4, despite the benchmark's limited scale. % Natural Language Understanding (NLU) benchmark (i.e., ALUE) Codes, data, and models are in https://github.com/FreedomIntelligence/AceGPT.Comment: https://github.com/FreedomIntelligence/AceGP

Purification and Characterization of Two New Allergens from the Venom of Vespa magnifica

Due to poor diagnostic facilities and a lack of medical alertness, allergy to Vespa wasps may be underestimated. Few allergens have been identified from Vespa wasps

Development of a candidate reference material for adventitious virus detection in vaccine and biologicals manufacturing by deep sequencing.

Unbiased deep sequencing offers the potential for improved adventitious virus screening in vaccines and biotherapeutics. Successful implementation of such assays will require appropriate control materials to confirm assay performance and sensitivity. A common reference material containing 25 target viruses was produced and 16 laboratories were invited to process it using their preferred adventitious virus detection assay. Fifteen laboratories returned results, obtained using a wide range of wet-lab and informatics methods. Six of 25 target viruses were detected by all laboratories, with the remaining viruses detected by 4-14 laboratories. Six non-target viruses were detected by three or more laboratories. The study demonstrated that a wide range of methods are currently used for adventitious virus detection screening in biological products by deep sequencing and that they can yield significantly different results. This underscores the need for common reference materials to ensure satisfactory assay performance and enable comparisons between laboratories

Mouse RC/BTB2, a Member of the RCC1 Superfamily, Localizes to Spermatid Acrosomal Vesicles

Mouse RC/BTB2 is an unstudied protein of the RCC1 (Regulator of Chromosome Condensation) superfamily. Because of the significant remodeling of chromatin that occurs during spermiogenesis, we characterized the expression and localization of mouse RC/BTB2 in the testis and male germ cells. The Rc/btb2 gene yields two major transcripts: 2.3 kb Rc/btb2-s, present in most somatic tissues examined; and 2.5 kb Rc/btb2-t, which contains a unique non-translated exon in its 5′-UTR that is only detected in the testis. During the first wave of spermatogenesis, Rc/btb2-t mRNA is expressed from day 8 after birth, reaching highest levels of expression at day 30 after birth. The full-length protein contains three RCC1 domains in the N-terminus, and a BTB domain in the C-terminus. In the testis, the protein is detectable from day 12, but is progressively up-regulated to day 30 and day 42 after birth. In spermatids, some of the protein co-localizes with acrosomal markers sp56 and peanut lectin, indicating that it is an acrosomal protein. A GFP-tagged RCC1 domain is present throughout the cytoplasm of transfected CHO cells. However, both GFP-tagged, full-length RC/BTB2 and a GFP-tagged BTB domain localize to vesicles in close proximity to the nuclear membrane, suggesting that the BTB domain might play a role in mediating full-length RC/BTB2 localization. Since RCC1 domains associate with Ran, a small GTPase that regulates molecular trafficking, it is possible that RC/BTB2 plays a role in transporting proteins during acrosome formation