We gratefully acknowledge Mr. Xiaomeng Wu and Ms. Yanan Hao for their help with art design, Mr. Shiren Tang for his help with embedded‑system design, Dr. Yuangao Qu for Raman spectroscopy, and the crews of the R/V Tan Suo Yi Hao, RV KEXUE, and HOV Fen Dou Zhe. In addition, we thank the Institutional Center for Shared Technologies and Facilities of IDSSE, CAS for providing essential experimental platforms and technical support that enabled the completion of this work. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is...

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PV systems require efficient maximum power tracking to operate under dynamic environmental conditions. Importance of PV systems The photovoltaic (PV) system stands out as one of the most critical renewable energy technologies because it directly converts sunlight to electric power with a high level of reliability and no negative environmental impact. The drive for clean and sustainable sources of energy globally and the dwindling supply of conventional fossil fuels has led to increased use of PV systems in residential, commercial, industrial and smart grid applications. Benefits of PV systems include little maintenance, scalability, silent operation and lower emissions of greenhouse gases. Improvements in power electronic converters, energy storage systems and intelligent maximum power point tracking (MPPT) techniques have greatly enhanced the efficiency and stabilization of PV generation under fluctuating environmental conditions such as partial shading, dust accumulation and temperature changes. Therefore, PV systems are critical facilitators of providing sustainable energy, reducing carbon footprints and moving towards the development of modern intelligent energy management systems. Need for MPPT Maximum Power Point Tracking (MPPT) is an important control method in photovoltaic (PV) systems to ensure that maximum available power is obtained during fluctuations in environmental conditions. The output characteristics of PV panels...

The technology could one day decode dreams—or reveal our most private thoughts.

Our approach for detecting optical skyrmions that are encoded in vectorial fields using diffractive neural networks is illustrated in Fig. 1. The overarching goal is to detect these skyrmions in an all-optical processing scheme that minimises electronic computational overhead while addressing the key challenge that topological numbers are not orthogonal. Concept of topological classifier Skyrmions are field configurations and, as illustrated in Fig. 1a, can be realised in paraxial optical fields using nonseparable vector beams of the form7, $$\left\vert {\psi }_{{\ell }_{12}}\right\rangle=\left\vert {\ell }_{1}\right\rangle \left\vert H\right\rangle+\exp (i\gamma )\left\vert {\ell }_{2}\right\rangle \left\vert V\right\rangle .$$ (1) Here, the first ket \((\left\vert {\ell }_{1(2)}\right\rangle )\) denotes the OAM degree of freedom, while the second ket \((\left\vert H(V)\right\rangle )\) denotes the polarisation degree of freedom of each photon in the field, while γ is a relative phase. In this work, we define the OAM eigenmodes using cylindrically symmetric Laguerre-Gaussian modes which can be expressed in polar coordinates \(\bar{r}=(r,\phi )\), \(\langle \bar{r}| \ell \rangle={{\mbox{LG}}}_{\ell }\left(\bar{r}\right)\propto {(\sqrt{2}r/w)}^{| \ell | }\exp (-{(r/w)}^{2})\exp (i\ell \phi )\) where ℓ is a topological index that is associated with an OAM of ℓℏ per photon. To reveal the topology, it is essential to represent the vector mode as a spin field,...

Prions are one of nature's cruelest tricks.

SNSやMQL5を見ていて思うことがあります。 それは「日本と海外のAIを用いたEA開発の違い」。 日本では「AI」をよく目にしますが、 MQL5では「Neural Network（NN）」をよく目にします。 具体的に言うと 日本のEA界隈では「AI・機械学習」というマーケティング上の言葉が先行しやすく、海外のEA開発者、とくにMQL5の技術コミュニティでは「Neural Network（ニ...

Countries all around the world have been severely affected by the novel coronavirus, popularly known as COVID-19, causing hundreds of thousands of unfortunate deaths without having found a widespread immunization method. It is extremely crucial for healthcare officials and the Governments of various countries to be able to differentiate the possible coronavirus strains to provide appropriate care and treatment. This paper proposes an effective way to set apart coronavirus strains into classes such as severe acute respiratory syndrome (SARS), acute respiratory distress syndrome (ARDS), and COVID-19 using machine learning algorithms and recurrent neural networks (RNN). Natural language processing (NLP) techniques were performed on textual clinical reports to structure the data and improve its usability for the model. Bag of words model and Term Frequency-Inverse Document Frequency (TF-IDF) vectorization were some of the few processes involved in extracting the prominent symptoms associated with each variant. The same has fed to various machine learning algorithms include multinomial naive Bayes (NB), logistic regression (LR), decision tree (DT), support vector machines (SVMs), and random forest (RF). Moreover, two more algorithms namely bagging, and gradient boost, are used for classification purposes. The reasons for choosing them are to observe their performance while classifying the proposed...