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Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue.We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses. 

Context.Dark gamma-ray bursts (GRBs) constitute a significant fraction of the GRB population. In this paper, we present a multi-wavelength analysis (both prompt emission and afterglow) of an intense (3.98  ×  10⁻⁵erg cm⁻²usingFermi-Gamma-Ray Burst Monitor) two-episodic GRB 150309A observed early on until ∼114 days post burst. Despite the strong gamma-ray emission, no optical afterglow was detected for this burst. However, we discovered near-infrared (NIR) afterglow (K_S-band), ∼5.2 h post burst, with the CIRCE instrument mounted at the 10.4 m Gran Telescopio Canarias (hereafter, GTC). Aims.We aim to examine the characteristics of GRB 150309A as a dark burst and to constrain other properties using multi-wavelength observations. Methods.We usedFermiobservations of GRB 150309A to understand the prompt emission mechanisms and jet composition. We performed early optical observations using the BOOTES robotic telescope and late-time afterglow observations using the GTC. A potential faint host galaxy was also detected in the optical wavelength using the GTC. We modelled the potential host galaxy of GRB 150309A in order to explore the environment of the burst. Results.The time-resolved spectral analysis ofFermidata indicates a hybrid jet composition consisting of a matter-dominated fireball and magnetic-dominated Poynting flux. The GTC observations of the afterglow revealed that the counterpart of GRB 150309A was very red, withH − K_S > 2.1 mag (95% confidence). The red counterpart was not discovered in any bluer filters ofSwiftUVOT/BOOTES, which would be indicative of a high redshift origin. Therefore we discarded this possibility based on multiple arguments, such as spectral analysis of the X-ray afterglow constrainz < 4.15 and a moderate redshift value obtained using the spectral energy distribution (SED) modelling of the potential galaxy. The broadband (X-ray to NIR bands) afterglow SED implies a very dusty host galaxy with a deeply embedded GRB (suggestingA_V ≳ 35 mag). Conclusions.The environment of GRB 150309A demands a high extinction towards the line of sight. Demanding dust obscuration is the most probable origin of optical darkness as well as the very red afterglow of GRB 150309A. This result establishes GRB 150309A as the most extinguished GRB known to date. 

Exploding and vanishing gradient are both major problems often faced when an artificial neural network is trained with gradient descent. Inspired by the ubiquity and robustness of nonlinear oscillations in biological neural systems, we investigate the properties of their artificial counterpart, the stable limit cycle neural networks. Using a continuous time dynamical system interpretation of neural networks and backpropagation, we show that stable limit cycle neural networks have non-exploding gradients, and at least one effective non-vanishing gradient dimension. We conjecture that limit cycles can support the learning of long temporal dependence in both biological and artificial neural networks. 

Abstract On 11 September 2021, two small thunderstorms developed over the Telescope Array Surface Detector (TASD) that produced an unprecedented number of six downward terrestrial gamma ray flashes (TGFs) within one‐hour timeframe. The TGFs occurred during the initial stage of negative cloud‐to‐ground flashes whose return strokes had increasingly large peak currents up to 223 kA, 147 GeV energy deposit in up to 25 1.2 km‐spaced surface detectors, and intermittent bursts of gamma‐rays with total durations up to 717 s. The analyses are based on observations recorded by the TASD network, complemented by data from a 3D lightning mapping array, broadband VHF interferometer, fast electric field change sensor, high‐speed video camera, and the National Lightning Detection Network. The TGFs of the final two flashes had gamma fluences of and 8, logarithmically bridging the gap between previous TASD and satellite‐based detections. The observations further emphasize the similarity between upward and downward TGF varieties, suggesting a common mechanism for their production. 

Abstract Optical emissions associated with Terrestrial Gamma ray Flashes (TGFs) have recently become important subjects in space‐based and ground‐based observations as they can help us understand how TGFs are produced during thunderstorms. In this paper, we present the first time‐resolved leader spectra of the optical component associated with a downward TGF. The TGF was observed by the Telescope Array Surface Detector (TASD) simultaneously with other lightning detectors, including a Lightning Mapping Array (LMA), an INTerFerometer (INTF), a Fast Antenna (FA), and a spectroscopic system. The spectroscopic system recorded leader spectra at 29,900 frames per second (33.44 s time resolution), covering a spectral range from 400 to 900 nm, with 2.1 nm per pixel. The recordings of the leader spectra began 11.7 ms before the kA return stroke and at a height of 2.37 km above the ground. These spectra reveal that optical emissions of singly ionized nitrogen and oxygen occur between 167 s before and 267 s after the TGF detection, while optical emissions of neutrals (H I, 656 nm; N I, 744 nm, and O I, 777 nm) occur right at the moment of the detection. The time‐dependent spectra reveal differences in the optical emissions of lightning leaders with and without downward TGFs. 

To understand the complex nonlinear dynamics of neural circuits, we fit a structured state-space model called tree-structured recurrent switching linear dynamical system (TrSLDS) to noisy high-dimensional neural time series. TrSLDS is a multi-scale hierarchical generative model for the state-space dynamics where each node of the latent tree captures locally linear dynamics. TrSLDS can be learned efficiently and in a fully Bayesian manner using Gibbs sampling. We showcase TrSLDS' potential of inferring low-dimensional interpretable dynamical systems on a variety of examples. 

Abstract Despite the f₀(980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$) meson, a tetraquark ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$) exotic state, a kaon-antikaon ($${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$) molecule, or a quark-antiquark-gluon ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$) hybrid. This paper reports strong evidence that the f₀(980) state is an ordinary$${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$meson, inferred from the scaling of elliptic anisotropies (v₂) with the number of constituent quarks (n_q), as empirically established using conventional hadrons in relativistic heavy ion collisions. The f₀(980) state is reconstructed via its dominant decay channel f₀(980) →π⁺π⁻, in proton-lead collisions recorded by the CMS experiment at the LHC, and itsv₂is measured as a function of transverse momentum (p_T). It is found that then_q= 2 ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$state) hypothesis is favored overn_q= 4 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$or$${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$states) by 7.7, 6.3, or 3.1 standard deviations in thep_T< 10, 8, or 6 GeV/cranges, respectively, and overn_q= 3 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$hybrid state) by 3.5 standard deviations in thep_T< 8 GeV/crange. This result represents the first determination of the quark content of the f₀(980) state, made possible by using a novel approach, and paves the way for similar studies of other exotic hadron candidates. 

A first search for beyond the standard model physics in jet multiplicity patterns of multilepton events is presented, using a data sample corresponding to an integrated luminosity of $138{\mathrm{fb}}^{-1}$of 13 TeV proton-proton collisions recorded by the CMS detector at the LHC. The search uses observed jet multiplicity distributions in one-, two-, and four-lepton events to explore possible enhancements in jet production rate in three-lepton events with and without bottom quarks. The data are found to be consistent with the standard model expectation. The results are interpreted in terms of supersymmetric production of electroweak chargino-neutralino superpartners with cascade decays terminating in prompt hadronic $R$-parity violating interactions.