Generalized Firefly Algorithm for Optimal Transmit Beamforming

This paper proposes a generalized Firefly Algorithm (FA) to solve an optimization framework having objective function and constraints as multivariate functions of independent optimization variables. Four representative examples of how the proposed generalized FA can be adopted to solve downlink beamforming problems are shown for a classic transmit beamforming, cognitive beamforming, reconfigurable-intelligent-surfaces-aided (RIS-aided) transmit beamforming, and RIS-aided wireless power transfer (WPT). Complexity analyzes indicate that in large-antenna regimes the proposed FA approaches require less computational complexity than their corresponding interior point methods (IPMs) do, yet demand a higher complexity than the iterative and the successive convex approximation (SCA) approaches do. Simulation results reveal that the proposed FA attains the same global optimal solution as that of the IPM for an optimization problem in cognitive beamforming. On the other hand, the proposed FA approaches outperform the iterative, IPM and SCA in terms of obtaining better solution for optimization problems, respectively, for a classic transmit beamforming, RIS-aided transmit beamforming and RIS-aided WPT

The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance

The stock market is a crucial component of the financial market, playing a vital role in wealth accumulation for investors, financing costs for listed companies, and the stable development of the national macroeconomy. Significant fluctuations in the stock market can damage the interests of stock investors and cause an imbalance in the industrial structure, which can interfere with the macro level development of the national economy. The prediction of stock price trends is a popular research topic in academia. Predicting the three trends of stock pricesrising, sideways, and falling can assist investors in making informed decisions about buying, holding, or selling stocks. Establishing an effective forecasting model for predicting these trends is of substantial practical importance. This paper evaluates the predictive performance of random forest models combined with artificial intelligence on a test set of four stocks using optimal parameters. The evaluation considers both predictive accuracy and time efficiency.Comment: 10 pages, 8 figure

AI-Driven Anonymization: Protecting Personal Data Privacy While Leveraging Machine Learning

The development of artificial intelligence has significantly transformed people's lives. However, it has also posed a significant threat to privacy and security, with numerous instances of personal information being exposed online and reports of criminal attacks and theft. Consequently, the need to achieve intelligent protection of personal information through machine learning algorithms has become a paramount concern. Artificial intelligence leverages advanced algorithms and technologies to effectively encrypt and anonymize personal data, enabling valuable data analysis and utilization while safeguarding privacy. This paper focuses on personal data privacy protection and the promotion of anonymity as its core research objectives. It achieves personal data privacy protection and detection through the use of machine learning's differential privacy protection algorithm. The paper also addresses existing challenges in machine learning related to privacy and personal data protection, offers improvement suggestions, and analyzes factors impacting datasets to enable timely personal data privacy detection and protection.Comment: 9 pages, 6 figure

Nurr1 regulates Top IIβ and functions in axon genesis of mesencephalic dopaminergic neurons

<p>Abstract</p> <p>Background</p> <p>NURR1 (also named as NR4A2) is a member of the steroid/thyroid hormone receptor family, which can bind to DNA and modulate expression of target genes. Previous studies have shown that NURR1 is essential for the nigral dopaminergic neuron phenotype and function maintenance, and the defects of the gene are possibly associated with Parkinson's disease (PD).</p> <p>Results</p> <p>In this study, we used new born <it>Nurr1 </it>knock-out mice combined with Affymetrix genechip technology and real time polymerase chain reaction (PCR) to identify <it>Nurr1 </it>regulated genes, which led to the discovery of several transcripts differentially expressed in the nigro-striatal pathway of <it>Nurr1 </it>knock-out mice. We found that an axon genesis gene called <it>Topoisomerase IIβ </it>(<it>Top IIβ</it>) was down-regulated in <it>Nurr1 </it>knock-out mice and we identified two functional NURR1 binding sites in the proximal <it>Top IIβ </it>promoter. While in <it>Top IIβ </it>null mice, we saw a significant loss of dopaminergic neurons in the substantial nigra and lack of neurites along the nigro-striatal pathway. Using specific TOP II antagonist ICRF-193 or <it>Top IIβ </it>siRNA in the primary cultures of ventral mesencephalic (VM) neurons, we documented that suppression of TOP IIβ expression resulted in VM neurites shortening and growth cones collapsing. Furthermore, microinjection of ICRF-193 into the mouse medial forebrain bundle (MFB) led to the loss of nigro-striatal projection.</p> <p>Conclusion</p> <p>Taken together, our findings suggest that <it>Top IIβ </it>might be a down-stream target of <it>Nurr1</it>, which might influence the processes of axon genesis in dopaminergic neurons via the regulation of TOP IIβ expression. The <it>Nurr1-Top IIβ </it>interaction may shed light on the pathologic role of <it>Nurr1 </it>defect in the nigro-striatal pathway deficiency associated with PD.</p

(E)-3-[2,5-Dioxo-3-(propan-2-yl­idene)pyrrolidin-1-yl]acrylic acid

The title compound, C10H11NO4, was extracted from a culture broth of Penicillium verruculosum YL-52. The mol­ecular structure is essentially planar, with an r.m.s. deviation of 0.01342 (2) Å for the non-H atoms. In the crystal structure, adjacent mol­ecules are connected into a centrosymmetric dimer through a pair of O—H⋯O hydrogen bonds. The dimers are further extended into a chain by weak C—H⋯O hydrogen bonds

Investigation of the Interaction between Nafion Ionomer and Surface Functionalized Carbon Black Using Both Ultrasmall Angle X-ray Scattering and Cryo-TEM

In making a catalyst ink, the interactions between Nafion ionomer and catalyst support are the key factors that directly affect both ionic conductivity and electronic conductivity of the catalyst layer in a membrane electrode assembly. One of the major aims of this investigation is to understand the behavior of the catalyst support, Vulcan XC-72 (XC-72) aggregates, in the existence of the Nafion ionomer in a catalyst ink to fill the knowledge gap of the interaction of these components. The dispersion of catalyst ink depends not only on the solvent but also on the interaction of Nafion and carbon particles in the ink. The interaction of Nafion ionomer particles and XC-72 catalyst aggregates in liquid media was studied using ultrasmall-angle X-ray scattering and cryogenic TEM techniques. Carbon black (XC-72) and functionalized carbon black systems were introduced to study the interaction behaviors. A multiple curve fitting was used to extract the particle size and size distribution from scattering data. The results suggest that the particle size and size distribution of each system changed significantly in Nafion + XC-72 system, Nafion + NH2-XC72 system, and Nafion + SO3H-XC-72 system, which indicates that an interaction among these components (i.e., ionomer particles and XC-72 aggregates) exists. The cryogenic TEM, which allows for the observation the size of particles in a liquid, was used to validate the scattering results and shows excellent agreement

Molluscicidal efficacies of different formulations of niclosamide: result of meta-analysis of Chinese literature

The control efforts on Oncomelania hupensis, the intermediate snail host of Schistosoma japonicum, cannot be easily excluded from the integrated approach of schistosomiasis control in China. Application of chemical compounds, molluscicides, in snail habitats is a common method for snail control in addition to environmental modification. We conducted a systematic review and meta-analysis to assess the molluscicidal effects of the currently recommended 50% niclosamide ethanolamine salt wettable powder and a new 4% niclosamide ethanolamine salt powder developed by Chinese researchers. Literature was searched from three Chinese databases, i.e. Chinese Biomedical Database, VIP Database and Wanfang Database, on field mollusciciding trials of niclosamide in China (from January 1, 1990 to April 1, 2010). Molluscicidal effects on reduction of snail population of the 50% or 4% niclosamide formulations in field trial were evaluated 3 days, 7 days or 15 days post-application. Out of 90 publications, 20 papers were eventually selected for analysis. Publication bias and heterogeneity tests indicated that no publication bias existed but heterogeneity between studies was present. Meta-analysis in a random effect model showed that the snail mortality of 3, 7 and 15 days after spraying the 50% niclosamide ethanolamine salt wettable powder were 77% [95%CI: 0.68-0.86], 83% [95%CI: 0.77-0.89], and 88% [95%CI: 0.82-0.92], respectively. For the 4% niclosamide ethanolamine salt powder, the snail mortality after 3, 7 and 15 days were 81% [95%CI: 0.65-0.93], 90% [95%CI: 0.83-0.95] and 94% [95%CI: 0.91-0.97], respectively. Both are good enough to be used as molluscicides integrated with a schistosomiasis control programme. The 4% niclosamide ethanolamine salt powder can be applied in the field without water supply as the surrogate of the current widely used 50% niclosamide ethanolamine salt wettable powder. However, to consolidate the schistosomiasis control achievement gained, it is necessary to continuously perform mollusciciding more than twice annually in the field

Polybenzimidazole (PBI) Functionalized Nanographene as Highly Stable Catalyst Support for Polymer Electrolyte Membrane Fuel Cells (PEMFCs)

Nanoscale graphenes were used as cathode catalyst supports in proton exchange membrane fuel cells (PEMFCs). Surface-initiated polymerization that covalently bonds polybenzimidazole (PBI) polymer on the surface of graphene supports enables the uniform distribution of the Pt nanoparticles, as well as allows the sealing of the unterminated carbon bonds usually present on the edge of graphene from the chemical reduction of graphene oxide. The nanographene effectively shortens the length of channels and pores for O2 diffusion/water dissipation and significantly increases the primary pore volume. Further addition of p-phenyl sulfonic functional graphitic carbon particles as spacers, increases the specific volume of the secondary pores and greatly improves O2 mass transport within the catalyst layers. The developed composite cathode catalyst of Pt/PBI-nanographene (50 wt%) + SO3H-graphitic carbon black demonstrates a higher beginning of life (BOL) PEMFC performance as compared to both Pt/PBI-nanographene (50 wt%) and Pt/PBI-graphene (50 wt%) + SO3H-graphitic carbon black (GCB). Accelerated stress tests show excellent support durability compared to that of traditional Pt/Vulcan XC72 catalysts, when subjected to 10,000 cycles from 1.0 V to 1.5 V. This study suggests the promise of using PBI-nanographene + SO3H-GCB hybrid supports in fuel cells to achieve the 2020 DOE targets for transportation applications