Poverty mapping is increasingly important for monitoring Sustainable Development Goal 1 (SDG 1) of the United Nations 2030 Agenda, which aims to end poverty in all its forms everywhere. Yet timely and fine-resolution poverty estimation remains difficult because conventional census- and survey-based approaches are costly, infrequent, and often sparse precisely where deprivation is most severe. As poverty emerges from complex socioeconomic systems shaped by human mobility, social interactions, infrastructure, and economic activities, emerging computational methods and nontraditional data sources have created new opportunities for poverty estimation and mapping. At the intersection of statistical physics, complex systems science, and data science, these approaches enable poverty estimation at finer spatial and temporal resolutions. This review summarizes the main concepts of poverty and the principal frameworks used to measure it, and examines recent advances on poverty estimation and mapping using satellite imagery, mobile phone data, social media data, and multisource data fusion. The review also discusses persistent challenges related to representativeness, transferability across regions, interpretability, and uncertainty quantification. Finally, the review clarifies both the analytical promise and the practical limits of contemporary poverty mapping.
This study presents the synthesis, structural architecture, density functional theory (DFT) investigations, third-order nonlinear optical (NLO) properties, and biological evaluations of two organic–inorganic hybrid compounds based on the dicationic 1-(4-pyridyl)piperazine ligand: (C9H15N3)2+.HgCl42- (Compound I) and (C9H15N3)2+.CuCl42- (Compound II) Single-crystal X-ray diffraction reveals that both hybrid compounds assemble into robust 3D supramolecular networks governed by extensive ionic charge-assisted (N–H···Cl, C–H···Cl) hydrogen bonds. Hirshfeld surface analysis demonstrates that H···Cl (up to 37.1) and H···H contacts dominate the crystal packing. Quantum theory of atoms in molecules (QTAIM), non-covalent interaction (NCI) calculations and Time-dependent DFT (TD-DFT) validate the purely non-covalent character of these lattice-stabilizing interactions. Single-beam Z-scan measurements under continuous-wave excitation show that both complexes exhibit strong reverse saturable absorption (RSA) and thermal self-defocusing behavior. Compound II demonstrates a significantly enhanced third-order susceptibility χ3 = 1.899 × 10–5 compared to Compound I χ3= 1.25 × 10–5 driven by efficient dication-to-halometalate electronic coupling and LMCT interactions. Furthermore, Compound I exhibited pronounced antibacterial efficacy against Escherichia coli 19 mm and S. aureus 21 mm while Compound II demonstrated superior cytotoxic potency against MDA-MB-231 triple-negative breast cancer cells with an IC50 of 10.96 μg/mL (compared to 25.25 μg/mL for Compound I). These results highlight the dual potential of compound I and II in photonic devices and as next-generation anti-cancer therapeutics.
The rise of nationalist and populist candidates worldwide provides compelling evidence that parties win elections, not by appealing to voters' policy preferences alone, but rather by connecting those preferences to group identities. This state-of-the-field article argues that party scholars need to integrate constructivist insights from neighboring fields to better understand the role of group identities in party competition. We review recent demand- and supply-side studies on the role of group identities in elections and bring them into conversation with the literature on ethnic politics and nationalism and political economic models of identity politics. On this basis, we suggest a research agenda that models voters as having both policy preferences and desires for self-esteem and self-consistency, which are mediated by their identification with social groups. Voters want to benefit others they see as being similar to themselves, to raise the status of the groups they identify with, and to maintain self-consistency by narrowing the gap between themselves and members of groups with which they identify. Political parties strategically combine policy offers with group appeals to address - and shape - all these motivations. Shifting from a 'policy-only' towards a 'policy-cum-identity' paradigm will enable the field of party politics to better understand the dynamics of real-world electoral competition and to reconcile its models with the latest developments in the political theory of representation.
The Middle Permian reptile Eunotosaurus africanus is a key taxon for understanding reptile evolution because it has been proposed to be one of the earliest stem turtles, but it could alternatively represent an early sauropsid. Alternative evolutionary interpretations are based on morphological character observations, and comparative anatomy of previously undocumented body parts may yield novel character evidence. Based on a previously unreported specimen of Eunotosaurus africanus, we provide descriptions of its inner ear anatomy, which we compare to a diversity of amniotes including turtles, millerettids and novel segmentations of Youngina capensis and Champsosaurus lindoei. The inner ear of Eunotosaurus africanus has plesiomorphic neodiapsid inner ear features that contrast with turtle ear morphology, including a radius of curvature of the anterior semicircular canal (ASC) that is larger than that of the posterior semicircular canal (PSC), narrow intercanal angles, slender vertical semicircular canals, and a bend in the central section of the PSC. Eunotosaurus africanus shares with turtles a large common crus cross-section and a thickened lateral semicircular canal. We provide a landmark-based comparison of amniote labyrinth shapes, which shows principal differences in the semicircular canals of birds, mammals and turtles as end members of a gradient of semicircular canal geometries. Other extant amniote groups (crocodiles, lepidosaurs), fossil lineages (e.g. sauropterygians, captorhinids, millerettids, younginiforms, varanopids, Eunotosaurus africanus) and stem lineages of extant groups (e.g. pterosaurs, non-avian dinosaurs, phytosaurs, other extinct pseudosuchians, mosasaurs, 'pelycosaurs', dicynodonts) show semicircular canal geometries that are generally intermediate between extreme shapes of birds, mammals and turtles, so that the entire morphospace shows gradational morphologies. The observed variation provides evidence of convergent evolution of labyrinth features, but also suggests phylogenetic signal is widespread in labyrinth morphology and that bird, mammal, and turtle labyrinth shapes may have evolved from a plesiomorphic shape that was retained in many reptilian stem lineages.
Plasmonic metal nanoparticles have deeply impacted the spectroscopy field by enabling nanoscale concentration of light and powerful signal enhancement. However, their operation remains largely confined to the visible and near-infrared spectral ranges due to the poor stability and limited surface functionalization strategies of UV-active materials. Here, we establish a complete route for the fabrication of programmable UV-plasmonic nanoantennas based on rhodium nanocube dimers assembled on DNA origami scaffolds. We report on an effective surface ligand exchange protocol for functionalizing rhodium nanocubes with DNA strands enabling their assemble into dimers with a yield of 69%, and an interparticle distance of 10 nm. Thanks to the DNA origami, a single streptavidin protein is accurately positioned into the plasmonic nanogap, contrasting to other works relying only on random diffusion. In good agreement with numerical simulations, UV autofluorescence measurements on a single streptavidin indicate up to 22 & times; brightness enhancement factor with the average value of 6.6 & times;, shorter autofluorescence lifetimes, and over 10 & times; increase of the total photon budget. By pioneering a robust, versatile and selective strategy for constructing UV-resonant plasmonic nanoantennas, this work broadens the applications of plasmonics into the deep UV range and opens new opportunities for label-free spectroscopy of single proteins.
