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1. Two new hybrid species of Salvia (S. × karamanensis and S. × doganii) from Turkey: evidence from molecular and morphological studies

   Ferhat CELEP; Emma RADERS; Bryan T. DREW (January 2020, Turkish journal of botany)

   Salvia L. is an ideal exemplar to demonstrate prezygotic isolation mechanisms in sympatric populations due to their wellknown staminal lever mechanism. Mechanical, phenological, and ethological isolation mechanisms have been reported among sympatric species of Salvia. However, it has been shown that if closely related species are sympatric and flower at the same time, they can potentially hybridize. In this study, we describe two new hybrid species of Salvia (S. × karamanensis Celep & B.T.Drew, and S. × doganii Celep & B.T.Drew) from Turkey based on morphological and molecular evidence. Salvia × karamanensis (S. aucheri Benth. subsp. canescens (Boiss. & Heldr.) Celep, Kahraman & Doğan × S. heldreichiana Boiss. ex Benth.) is known from near Karaman city in the central Mediterranean region of Turkey, and S. × doganii (S. cyanescens Boiss. & Bal. × S. vermifolia Hedge & Hub.-Mor.) occurs near Sivas in central Anatolia, Turkey. Morphological comparisons between the hybrid species and their putative parents are given with notes on the International Union for Conservation of Nature (IUCN) red list categories, biogeography and ecology of the two hybrid species. 

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2. Dualities of 5d gauge theories from S-duality

   https://doi.org/10.1007/JHEP07(2020)012  

   Bhardwaj, Lakshya (July 2020, Journal of High Energy Physics)
3. S-Isomap++: Multi manifold learning from streaming data

   https://doi.org/10.1109/BigData.2017.8257987  

   Mahapatra, Suchismit; Chandola, Varun (December 2017, IEEE Bigdata 2017)

   Manifold learning based methods have been widely used for non-linear dimensionality reduction (NLDR). However, in many practical settings, the need to process streaming data is a challenge for such methods, owing to the high computational complexity involved. Moreover, most methods operate under the assumption that the input data is sampled from a single manifold, embedded in a high dimensional space. We propose a method for streaming NLDR when the observed data is either sampled from multiple manifolds or irregularly sampled from a single manifold. We show that existing NLDR methods, such as Isomap, fail in such situations, primarily because they rely on smoothness and continuity of the underlying manifold, which is violated in the scenarios explored in this paper. However, the proposed algorithm is able to learn effectively in presence of multiple, and potentially intersecting, manifolds, while allowing for the input data to arrive as a massive stream. 

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4. Understanding CO2-S Degassing from San Cristóbal Volcano

   León Jr, C.; Ding, S.; Plank, T.A. (October 2022, AGU Fall Meeting Abstracts)

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5. Spin‐s$$s$$ Dicke States and Their Preparation

   https://doi.org/10.1002/qute.202400057  

   Nepomechie, Rafael_I; Ravanini, Francesco; Raveh, David (September 2024, Advanced Quantum Technologies)

   Abstract The notion of spin‐ Dicke states is introduced, which are higher‐spin generalizations of usual (spin‐1/2) Dicke states. These multi‐qudit states can be expressed as superpositions of qudit Dicke states. They satisfy a recursion formula, which is used to formulate an efficient quantum circuit for their preparation, whose size scales as , where is the number of qudits and is the number of times the total spin‐lowering operator is applied to the highest‐weight state. The algorithm is deterministic and does not require ancillary qudits. 

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