Browsing by Author "Wu J"
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- ItemBasic Volcanic Elements of the Arxan-Chaihe Volcanic Field, Inner Mongolia, NE China(inTech Open: Rijeka, Croatia, 2020-10-30) Li B; Nemeth K; Palmer A; Wu J; Procter J; Liu JThe Arxan-Chaihe Volcanic Field, Inner Mongolia, NE China is a Pleistocene to Recent volcanic field still considered to be active. In this chapter we provide an update of current volcanological research conducted in the last four years to describe the volcanic architecture of the identified vents, their eruptive history and potential volcanic hazards. Here we provide an evidence-based summary of the most common volcanic eruption styles and types the field experienced in its evolution. The volcanic field is strongly controlled by older structural elements of the region. Hence most of the volcanoes of the field are fissure-controlled, fissure-aligned and erupted in Hawaiian to Strombolian-style creating lava spatter and scoria cone cone chains. One of the largest and most complex volcano of the field (Tongxin) experienced a violent phreatomagmatic explosive phase creating a maar in an intra-mountain basin, while the youngest known eruptions formed a triple vent set (Yanshan) that reached violent Strombolian phases and created an extensive ash and lapilli plains in the surrounding areas. This complex vent system also emitted voluminous lava flows that change the landscape by damming fluival networks, providing a volcanological paradise for the recently established Arxan UNESCO GLobal Geopark.
- ItemDL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning(BioMed Central Ltd, 2023-12) Wu J; Liu B; Zhang J; Wang Z; Li JPURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets. RESULTS: In this study, the paper introduces a novel deep learning framework, termed DL-PPI, for predicting PPIs based on sequence data. The proposed framework comprises two key components aimed at improving the accuracy of feature extraction from individual protein sequences and capturing relationships between proteins in unfamiliar datasets. 1. Protein Node Feature Extraction Module: To enhance the accuracy of feature extraction from individual protein sequences and facilitate the understanding of relationships between proteins in unknown datasets, the paper devised a novel protein node feature extraction module utilizing the Inception method. This module efficiently captures relevant patterns and representations within protein sequences, enabling more informative feature extraction. 2. Feature-Relational Reasoning Network (FRN): In the Global Feature Extraction module of our model, the paper developed a novel FRN that leveraged Graph Neural Networks to determine interactions between pairs of input proteins. The FRN effectively captures the underlying relational information between proteins, contributing to improved PPI predictions. DL-PPI framework demonstrates state-of-the-art performance in the realm of sequence-based PPI prediction.
- ItemDoes board diversity in industry-experience boost firm value? The role of corporate innovation(Elsevier, 2023-08-31) Huang P; Lu Y; Wu JPrevious studies examining board diversity disproportionately focus on directors' demographic features. In this paper, we construct a sophisticated measure of board diversity based on directors' industry-experience diversity (BIED) and examine its effect on firm value. Using a sample of S&P1500 firms, we find that higher BIED leads to higher firm value. This result survives both firm fixed effects and an instrumental variable approach, at least partially suggesting a causal relationship. We argue that a more diverse board brings more perspectives, viewpoints, knowledge and information to the firm, enhances directors’ capability of advising, and thus creates higher firm value. We further find one possible underlying economic mechanism through which BIED facilitates value creation. That is, BIED creates value by promoting corporate innovation. Overall, BIED constitutes a valuable corporate governance mechanism.
- ItemEntitlement-Based Access Control for Smart Cities Using Blockchain(MDPI (Basel, Switzerland), 2021-08-04) Sabrina F; Jang-Jaccard J; Dai H-N; Wu J; Wang HSmart cities use the Internet of Things (IoT) devices such as connected sensors, lights, and meters to collect and analyze data to improve infrastructure, public utilities, and services. However, the true potential of smart cities cannot be leveraged without addressing many security concerns. In particular, there is a significant challenge for provisioning a reliable access control solution to share IoT data among various users across organizations. We present a novel entitlement-based blockchain-enabled access control architecture that can be used for smart cities (and for any ap-plication domains that require large-scale IoT deployments). Our proposed entitlement-based access control model is flexible as it facilitates a resource owner to safely delegate access rights to any entities beyond the trust boundary of an organization. The detailed design and implementation on Ethereum blockchain along with a qualitative evaluation of the security and access control aspects of the proposed scheme are presented in the paper. The experimental results from private Ethereum test networks demonstrate that our proposal can be easily implemented with low latency. This validates that our proposal is applicable to use in the real world IoT environments.