A HYBRID DEEP LEARNING APPROACH FOR SENTIMENT ANALYSIS IN PRODUCT REVIEWS

Product reviews play a crucial role in providing valuable insights to consumers and producers. Analyzing the vast amount of data generated around a product, such as posts, comments, and views, can be challenging for business intelligence purposes. Sentiment analysis of this content helps both consumers and producers gain a better understanding of the market status, enabling them to make informed decisions. In this study, we propose a novel hybrid approach based on deep neural networks (DNNs) for sentiment analysis in product reviews, focusing on the classification of sentiments expressed. Our approach utilizes the recursive neural network (RNN) algorithm for sentiment classification. To address the imbalanced distribution of positive and negative samples in social network data, we employ a resampling technique that balances the dataset by increasing samples from the minority class and decreasing samples from the majority class. We evaluate our approach using Amazon data, comprising four product categories: clothing, cars, luxury goods, and household appliances. Experimental results demonstrate that our proposed approach performs well in sentiment analysis for product reviews, particularly in the context of digital marketing. Furthermore, the attention-based RNN algorithm outperforms the baseline RNN by approximately 5%. Notably, the study reveals consumer sentiment variations across different products, particularly in relation to appearance and price aspects

Catalytically active nickel (110) surfaces in the growth of carbon tubular structures

M.S.Z. L. Wan

Catalytically active nickel {110} surfaces in growth of carbon tubular structures

©2000 American Institute of Physics. The electronic version of this article is the complete one and can be found online at: : http://link.aip.org/link/?APPLAB/76/1255/1DOI:10.1063/1.126001Recent interest in the growth of aligned carbon nanotube films using transition metal catalysts has led to questions concerning the growth mechanism involved. In our experiment carbon tubules grown using Ni catalysts exhibit a preferred orientation relative to the catalytically active surfaces of Ni. The axial directions of the tubular structure are mainly parallel to the 110 and 042 directions of Ni. The faceted shape of the Ni particles determines the intrinsic structure of the tubules. A mechanism involving spiral growth is proposed to explain the nucleation and growth of such tubules

Study on Brittleness Characteristics and Fracturing Crack Propagation Law of Deep Thin-Layer Tight Sandstone in Longdong, Changqing

Tight-sandstone oil and gas resources are the key areas of unconventional oil and gas resources exploration and development. Because tight-sandstone reservoirs usually have the characteristics of a low porosity and ultralow permeability, large-scale hydraulic fracturing is often required to form artificial fractures with a high conductivity to achieve efficient development. The brittleness of rock is the key mechanical factor for whether fracturing can form a complex fracture network. Previous scholars have carried out a lot of research on the brittleness characteristics of conglomerate and shale reservoirs, but there are few studies on the brittleness characteristics of sandstone with different types and different coring angles in tight-sandstone reservoirs and the fracture propagation law of sandstone with different brittleness characteristics. Based on this, this paper carried out a systematic triaxial compression and hydraulic fracturing experiment on the tight sandstone of Shan 1 and He 8 in the Longdong area of the Changqing oilfield. Combined with CT scanning cracks, the brittleness characteristics and fracturing crack propagation law of different types and different coring angles of sandstone under formation-confining pressure were clarified. The results show that there are great differences between different types of sandstone in the yield stage and the failure stage. The sandstone with a quartz content of 100% has the highest peak strength and a strong brittleness. Sandstones with a high content of natural fractures and dolomite have a lower peak strength and a weaker brittleness. There are also differences in the peak strength and fracture morphology of sandstone with different coring angles due to geological heterogeneity. The sandstone with a comprehensive brittleness index of 70.30 produces a more complex fracture network during triaxial compression and hydraulic fracturing than the sandstone with a comprehensive brittleness index of 14.15. The research results have important guiding significance for on-site fracturing construction of tight-sandstone reservoirs

Ultra-low Loading of Au Clusters on Nickel Nitride Efficiently Boosts Photocatalytic Hydrogen Production with Titanium Dioxide

Platinum (Pt) is a widely used co-catalyst with excellent performance for photocatalytic hydrogen evolution. However, it is not suitable for industrial production because of its prohibitive cost. Currently, there are two means to overcome this challenge. One is to, find alternative cocatalysts for Pt. The other is to develop ultrasmall of noble metal clusters, which reduces the amount of noble metal loading required. This reduces the loading amount of noble metals and improves their atomic efficiency. In this work, we have integrated both these approaches to generate a non-noble metal co-catalyst nickel nitride (Ni3N) and Au clusters (Au-c). The composite cocatalyst (Ni3N-Au-c) thus obtained promotes photocatalytic hydrogen production of TiO2. The (Ni3N-Au-c-TiO2) composite with an ultralow amount of Au-c (0.00025 wt%) shows photocatalytic hydrogen production rates that are even higher than that of Pt-TiO2. The loading requirement of noble metal is reduced by 99.95 wt% compared to the optimal load of Pt; further indicating the cost efficiency possible through this method

Chromium-titanium nitride as an efficient co-catalyst for photocatalytic hydrogen production

Transition metal nitrides (TMNs) are emerging as a feasible alternative to noble metal co-catalysts in photocatalytic hydrogen production. Considering the recent prospects created by multicomponent systems, it is reasonable to investigate multi-component TMNs for photocatalytic hydrogen production. Herein, in an effort in that direction, ternary chromium-titanium nitride (Cr0.5Ti0.5N) nanoparticles have been synthesized by a solid-solid phase separation method, resulting in highly efficient co-catalysts for promoting photocatalytic hydrogen production of semiconductors under visible light irradiation. Both experimental results and density functional theory (DFT) calculations demonstrate that ternary Cr0.5Ti0.5N offers a comprehensive advantage by boosting the photo-induced charge carrier separation and migration, improving the reaction kinetics as compared to those of TiN and CrN. Therefore, the optimal Cr0.5Ti0.5N-based sample exhibits the highest photocatalytic hydrogen evolution rate of 2.44 mmol g(-1)h(-1), and has similar to 120 times better kinetics than the reference pure CdS sample. In fact, this result even surpasses that of Pt-based nanocomposites (2.06 mmol g(-1)h(-1))

Ni-Mo ternary nitrides based one-dimensional hierarchical structures for efficient hydrogen evolution

Ni-Mo ternary nitrides based one-dimensional hierarchical structures for efficient hydrogen evolutio

Investigation of the electrocatalytic mechanisms of urea oxidation reaction on the surface of transition metal oxides

Urea oxidation reaction (UOR) has been widely considered as an alternative anodic reaction to water oxidation for the green production of hydrogen fuel. Due to the high catalytic activity of transition metal oxides towards UOR, various strategies have been developed to improve their syntheses and catalytic properties. However, little is known about the underlying mechanisms of UOR on catalyst surface. In this work, three transition metal oxides, including NiO, Co3O4, and Fe2O3 are investigated as model catalysts. Through analyzing the electrochemical properties by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and operando Raman spectroscopy, it is revealed that NiO has a unique high catalytic activity towards UOR due to simultaneous formation of a thin layer of oxyhydroxide species above 1.40 V vs. RHE in alkaline media. In addition, density functional theory (DFT) calculations further suggest that the adsorption of urea molecules is largely affected by surface interactions resulting in different space configurations, which impose large influences on the consecutive deprotonation and NN formation processes. Overall, results of this work point to the subtle adsorption − kinetics relationship in UOR and highlight the importance of the interfacial electronic interactions on catalyst surface

Systematic Identification of the RNA-Binding Protein STAU2 as a Key Regulator of Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a highly aggressive cancer. RNA-binding proteins (RBPs) regulate highly dynamic post-transcriptional processes and perform very important biological functions. Although over 1900 RBPs have been identified, most are considered markers of tumor progression, and further information on their general role in PAAD is not known. Here, we report a bioinformatics analysis that identified five hub RBPs and produced a high-value prognostic model based on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Among these, the prognostic signature of the double-stranded RNA binding protein Staufen double-stranded RNA (STAU2) was identified. Firstly, we found that it is a highly expressed critical regulator of PAAD associated with poor clinical outcomes. Accordingly, the knockdown of STAU2 led to a profound decrease in PAAD cell growth, migration, and invasion and induced apoptosis of PAAD cells. Furthermore, through multiple omics analyses, we identified the key target genes of STAU2: Palladin cytoskeletal associated protein (PALLD), Heterogeneous nuclear ribonucleoprotein U (HNRNPU), SERPINE1 mRNA Binding Protein 1 (SERBP1), and DEAD-box polypeptide 3, X-Linked (DDX3X). Finally, we found that a high expression level of STAU2 not only helps PAAD evade the immune response but is also related to chemotherapy drug sensitivity, which implies that STAU2 could serve as a potential target for combinatorial therapy. These findings uncovered a novel role for STAU2 in PAAD aggression and resistance, suggesting that it probably represents a novel therapeutic and drug development target