Miracle-dz/UniFAR-FTUs huggingface dataset:
iSORT: An Integrative Method for Reconstructing Spatial Organization of Cells using Transfer Learning

Understanding the cellular spatial organization is a paramountly important direction of exploring the intricate functionalities of tissues and organs. However, conventional single-cell RNA sequencing (scRNA-seq) technologies often lose cells’ spatial information. Recent spatial transcriptomics (ST) techniques aim to preserve locations but easily come with either low resolution or high costs. Here, we introduce iSORT (an integrative method for reconstructing Spatial ORganization of cells via Transfer learning), which can recover the spatial organization of large-scale multi-source scRNA-seq dataset with only one ST reference. iSORT employs a transfer learning approach to assign coordinates for each single cell with scRNA-seq. iSORT also integrates multiple ST tissue slices as references to enhance accuracy and capture multi-slice biological heterogeneity. Furthermore, iSORT conduces to the precise identification of spatially variable genes (SVGs). We demonstrated the effectiveness of iSORT by applying it to four benchmark datasets, including those from Drosophila embryo, mouse embryo, mouse brain, and human brain tissues, and by a comparative analysis with five other algorithms as well. Additionally, we collected scRNA-seq data from the patients with atherosclerosis to reconstruct the structure of arteries for the first time, using ST data from other individuals as references. Atherosclerosis-related SVGs were identified and verified by the gene set enrichment analysis. As a promising tool, iSORT provides deep insights into the single-cell omics data analysis and biomedical research.
EXCRETE enables deep proteomics of the microbial extracellular environment

Extracellular proteins play a significant role in shaping microbial communities which, in turn, can impact ecosystem function, human health, and biotechnological processes. Yet, for many ubiquitous microbes, there is limited knowledge regarding the identity and function of secreted proteins. Here, we introduce EXCRETE (enhanced exoproteome characterization by mass spectrometry), a workflow that enables comprehensive description of microbial exoproteomes from minimal starting material. Using cyanobacteria as a case study, we benchmark EXCRETE and show a significant increase over current methods in the identification of extracellular proteins. Subsequently, we show that EXCRETE can be miniaturized and adapted to a 96-well high-throughput format. Application of EXCRETE to cyanobacteria from different habitats (Synechocystis sp. PCC 6803, Synechococcus sp. PCC 11901, and Nostoc punctiforme PCC 73102), and in different cultivation conditions, identified up to 85% of all predicted secreted proteins. Finally, functional analysis reveals that cell envelope maintenance and nutrient acquisition are central functions of the cyanobacterial secretome. Collectively, these findings challenge the general belief that cyanobacteria lack secretory proteins and point to a functional conservation of the secretome across freshwater, marine, and terrestrial species.
Robust badlands thalwegs network extraction from DTM for topological characterisation

This paper presents methods to extract badlands thalwegs network from regular grid DTM by combining a terrain morphology indices to a drainage algorithm. The computation of a continuous vector network will permit the study of the badlands spatial patterns. Thess methods aim at delineating a thalweg only where the DTM denotes a significant curvature with respect to DTM accuracy. It relies on three major steps. Firstly, discontinuous concave areas are detected from the DTM using morphological criteria; the plan curvature and the convergence index . Secondly, the concave convergence areas are connected using a drainage algorithm which provides continuous and tree-structured thick scheme. We assume that these areas present physical significance and corresponds to a gully floor area. Finally, the thick path is reduced to its main curve and vectorised to obtain a thalwegs network. The methods are applied on both virtual and actual cases DTM. The actual case is a LiDAR DTM of Draix Badlands (French Alps). The obtained networks are quantitatively compared both to the one obtained with usual drainage area criteria and to a reference network. The networks comparison shows the great potential of the converge index based method for thalweg network extraction.
Annual seasonality in Sentinel-1 signal for forest mapping and forest type classification

ABSTRACT The Sentinel-1 satellites provide the formerly unprecedented combination of high spatial and temporal resolution of dual polarization synthetic aperture radar data. The availability of dense time series enables the derivation and analysis of temporally filtered annual backscatter signals. The study concentrates on the use of Sentinel-1 seasonal backscatter signatures for forest area estimation and forest type classification. A classification method based on time series similarity measures is introduced and tested in three test areas covered by various forest types including broadleaf temperate, boreal and montane forests. The results are compared with two European-wide Copernicus high resolution layers, namely forest type and tree cover density (TCD). The correspondence of forest/non-forest maps and TCD is high in all test areas, with overall accuracies for forest/non-forest classification between 86% and 91% and Pearson correlation coefficients for TCD between 0.68 and 0.74. The forest type classification (non-forest, coniferous and broadleaf forest classes) provides best results in temperate forests with an overall accuracy of 85%; in boreal forest, the accuracy decreases to only 65%. Generally, the method provides reliable results for forest area estimation, including regions where methods based on static parameters are often problematic (mountainous areas), and it enables forest type classification in temperate forests.
Which are the best cities for psychology research worldwide? A map visualizing city ratios of observed and expected numbers of highly-cited papers

We present scientometric results about world-wide centers of excellence in psychology. Based on Web of Science data, domain-specific excellence can be identified for cities where highly cited papers are published. Data refer to all psychology articles published in 2007 which are documented in the Social Science Citation Index and to their citation frequencies from 2007 to May 2011. Visualized are 214 cities with an article output of at least 50 in 2007. Statistical z tests are used for the evaluation of the degree to which an observed number of top-cited papers (top-10%) for a city differs from the number expected on the basis of randomness in the selection of papers. Map visualizing city ratios on significant differences between observed and expected numbers of highly-cited papers point at excellence centers in cities at the East and West Coast of the United States as well as in Great Britain, Germany, the Netherlands, Ireland, Belgium, Sweden, Finland, Australia, and Taiwan. Furthermore, positive but non-significant differences in favor of high citation rates are documented for some cities in the United States, Great Britain, the Netherlands, the Scandinavian and the German-speaking countries, Belgium, France, Spain, Israel, South Korea, and China. Scientometric results show convincingly that highly-cited psychological research articles come from the Anglo-American countries and some of the non-English European countries in which the number of English-language publications has increased during the last decades.
A Joint Framework for Disparity and Surface Normal Estimation

: This paper deals with the stereo matching problem, while moving away from the traditional fronto-parallel assumption. We propose an algorithm that provides disparities in accordance with the surface properties of the scene under consideration. To do so, we carry out cooperatively both disparity and surface normal estimations by setting the two tasks in a uniﬁed Markovian framework. A novel joint probabilistic model is deﬁned through two Markov Random Fields (MRF) to favor both intra ﬁeld (within neighboring disparities and neighboring normals) and inter ﬁeld (between disparities and normals) consistency. Geometric contextual information is introduced in the pair-wise Markovian regularizing term used in both MRFs. Segmentation and plane ﬁtting procedures, usually performed as ﬁnal steps to increase the quality results are here explicitly used in one of the MRF data terms. We then design an appropriate alternating maximization procedure based on standard Belief Propagation. We illustrate the performance of our approach on synthetic and real data. The results obtained are comparable to the state-of-the-art and show improvement in many cases.
How reliable are data on arboreal ant (Hymenoptera: Formicidae) communities collected by insecticidal fogging?

Insecticidal fogging has proven to be an efficient method for sampling arboreal arthropods in tropical lowland rain forests. By exact positioning of the collecting funnels beneath the tree and by excluding arthropods from higher canopy levels, fogging can be a precise tool to collect for example ant communities in a tree-species specific way. Such clearly defined communities form a good model system for community analysis. Analysis, however, requires knowledge about how representative communities were sampled from the trees. In order to assess this, ant nests were located in the trees the day before fogging. For that purpose ants were attracted to bait (pieces of tuna and sugar-water) placed on all branches in the trees. Pursuing the ants from the baits made it easy to localize the ants' nests in the trees and to get information on the relative size of the colonies. Comparing these results with those obtained by fogging showed that fogging does not always describe abundance hierarchies correctly and that different species could be numerically dominant at the bait compared to the fogging samples. Particularly, abundances of stem-nesting species are underestimated indicating the necessity to correct ant abundances for a specific community-level analysis.
Evaluation of the possible role of prostaglandin F 2 α in laminitis induced in horses by nasogastric administration of black walnut heartwood extract

I n horses, the pathogenesis of laminitis is multifactorial and involves perturbations in metabolic, enzymatic, inflammatory, and vascular homeostasis within the laminar dermis. 1–3 Eicosanoids are lipid-derived mediators that are widely distributed in mammalian tissues 4 and have wide-ranging biological actions with respect to inflammatory and cardiovascular regulation. 5–7
Enhancing Operational Deliberation in a Refinement Acting Engine with Continuous Planning

Recent technological developments in robotics and artificial intelligence may enable the deployment of robots in many aspects of our lives. As the complexity of robotic platforms increases, deliberation algorithms need to be improved, in particular to handle an increasing number of agents, to manage complex goals and tasks, and to evolve in more open environments in which unforeseen events should be dealt with autonomously. Among the deliberation functionalities deployed to provide the best level of autonomy: planning, monitoring, learning, observing, we focus here on acting. We present OMPAS, a refinement-based acting engine that executes high-level tasks by refining them into a set of lower-level tasks and commands. OMPAS uses a custom Lisp dialect (SOMPAS) to define the behavior of the robotic agent. SOMPAS provides primitives to handle concurrency and resources, and allows the synthesis of planning models, thanks to the restricted core language, and the explicit identification of acting decisions. The engine has been extended to deploy a continuous planning module, using the synthesized models, to look ahead and guide the decisions of the acting system in order to e.g., avoid deadlock, or optimize the completion of several parallel tasks. We provide an evaluation of the over-all approach on the control of a fleet of robots in a simulated logistic platform.
Enhancement in selectivity of trivalent Am over Cm by modulating donor centres of aza-macrocyclic ligands: An implication of their differences in bonding

: Efficient management of the high-level liquid waste (HLW) generated during the reprocessing of nuclear fuel involves mutual separation and transmutation of the minor actinides like Am and Cm, which are chemically very similar. In the present work, an in-silico analysis of the bonding of Am(III) and Cm(III) ions with donor center modulated azacrown based ligand, i.e., a ligand formed by replacing the four ‘O’s of the azacrown macrocycle in N,N’ -bis[(6-carboxy-2-pyridyl)-methyl]-1,10-diaza-18-crown-6 (L1) with four ‘S’s (L2) is carried out using relativistic density functional theory to develop a deeper understanding of the impact of both, soft donors as well as the cavity effects on the separation of these metal ions. The subtle differences in the bonding is brought about by the covalent interaction of the metal and the aza-macrocyclic O and S donors. The electron donation from the ligand is mostly accepted in the metal 6d orbitals and minimally to the 5f orbitals. But the f-orbital participation plays the crucial role in bringing about the subtle difference in the bonding between Am(III) and Cm(III) ions with the ligands. The trivalent Cm ion with half-filled initial f 7 configuration shows resistance in participating in bonding as was observed from NPA, QTAIM, NBO and DOS analyses. Whereas, the Am(III) ions having f 6 configuration are eager to accept f-electrons to achieve the stable half-filled configuration. The energetics elucidated that both L1 and L2 ligands are Am selective. But the extraction capacity and selectivity is higher for the L2 ligand. The Am selectivity can be attributed to the significant covalent interaction of S donors which have better electron donating capacity (than O) to the electron deficient Am(III) ion. This study is anticipated to throw some light on the implication of the bonding features on their separation.
Edinburgh Research Explorer Inclusive agro-industrial development and sectoral systems of innovation

The agro-industries are widely viewed as important to inclusive industrial development due to their relatively low entry barriers and acessibility to small ﬁ rms. However, the agro-industries are more technologically complex than commonly assumed. Small and young ﬁ rms face challenges acquiring capabilities to compete e ﬀ ectively. The paper explores how di ﬀ ering sectoral systems of innovation (SSI) shape patterns of inclusion and exclusion in the agro-industries, and the factors shaping this. It analyses two contrasting South African agro-industrial sectors, maize processing and fresh citrus. It proposes a partial conceptualization of ‘ inclusive ’ SSIs (ISSIs) as sectoral con ﬁ gurations of actors and institutions that lower entry barriers and narrow capability gaps between small ﬁ rms and dominant incumbents at the technological frontier. It argues that ISSIs rely on institutions that coordinate innovation-related activities in a manner bene ﬁ tting small ﬁ rms and new entrants, by aiding the broad di ﬀ usion of relevant technology and capabilities. Alongside state agencies, business associations can play an important role in this regard. It identi ﬁ es the characteristics of state-business relations and inter-ﬁ rm dynamics of competition and collective action as important underlying determinants of ISSIs. Thus, the paper highlights the need for attention to sector-level political economy in understanding the diverse outcomes of SSIs.
Spectral Eﬀiciency of CDMA Downlink Cellular Networks with Matched Filter

In this contribution, the performance of a downlink code division multiple access (CDMA) system with orthogonal spreading and multicell interference is analyzed. A useful framework is provided in order to determine the optimal base station coverage for wireless frequency selective channels with dense networks where each user is equipped with a matched ﬁlter. Using asymptotic arguments, explicit expressions of the spectral e ﬃ ciency are obtained and provide a simple expression of the network spectral e ﬃ - ciency based only on a few meaningful parameters. Contrarily to a common misconception which asserts that to increase spectral e ﬃ ciency in a CDMA network, one has to increase the number of cells, we show that, depending on the path loss and the fading channel statistics, the code orthogonal gain (due to the synchronization of all the users at the base station) can compensate and even compete in some cases with the drawbacks due to intercell interference. The results are especially realistic and useful for the design of dense networks.
How much are individuals willing to pay to offset their carbon footprint? The role of information disclosure and social norms

This paper examines individuals' willingness to pay (WTP) to offset their carbon footprint in response to receiving information about (i) the size of their own carbon footprint, and (ii) further receiving in addition information about the difference between their carbon footprint and the target footprint, i.e. per-capita GHG emissions compatible with the 1.5°C target. The analysis employs a demographically representative survey among the adult population in Germany, which includes a comprehensive online carbon footprint calculator and randomized information treatments. The findings from estimating double hurdle models suggest that disclosing information about the size of the individual carbon footprint increases average WTP by about one third. Providing this information appears to affect the intensive margin but not the extensive margin. In comparison, providing information about the size of their carbon footprint together with information about the difference between their carbon footprint and the target footprint does not appear to affect individuals' WTP. Further, the WTP is related with income, gender, age, education, carbon literacy, the belief that carbon offsetting is effective, and with environmental preferences. In comparison, the findings provide no statistically significant evidence that the WTP is associated with the size of the individual carbon footprint, and whether participants consider their carbon footprint to be higher or lower than the carbon footprint of the average adult in the population.
Efficiency in rice cultivation in north-western region of Bangladesh

Meeting the increasing demand for food grains requires almost a parallel growth in food grain production, either by increasing the utilization of inputs or by effectively organizing the management of production. The main objective of the present study was to identify and analyze the possibilities for improving productivity of rice by increasing the productive efficiency of rice farmers under both flood-prone and flood free environments in Bangladesh. The study employed mainly farm level cross sectional data collected from 298 farm households in three districts of Bangladesh. The stochastic frontier production function has been employed to measure the efficiency and to identify the cause of inefficiency in the production processes. Estimates of yield functions revealed that, among the biophysical factors, land type
PDSim: Simulate Plans

This paper presents new additions and improvements to the Planning Domain Simulation (PDSim) project. PDSim is a plugin for the Unity game engine to simulate planning domains and plans. PDSim uses a novel way to translate the output of a planner to 2D or 3D animations and effects. Using these visualisation techniques, PDSim aims to help users evaluate the quality of a plan and improve domain and problem modelling. In this system demonstration, we present the structure and operation of the PDSim interface by illustrating how to set up a new simulation for planning problems, and how the user interface can be used for creating animations.
Force Partitioning Analysis of Vortex-Induced Vibrations of Wind Turbine Tower Sections

Vortex-Induced Vibrations (VIV) of wind turbine towers during installation is an aero-structural problem of significant practical relevance. Vibrations may happen in the tower structure, especially when the rotor-nacelle assembly is not yet attached to the tower or if the rotor blades are not yet connected to the tower-nacelle assembly. The complexity of aeroelastic phenomena involved in VIV makes the modeling and analysis challenging. Therefore, the aim of the current research is to investigate the fundamental mechanisms causing the onset and sustenance of vortex-induced vibrations. To gain more under-5 standing of the nature of vibrations, a methodology is established that distinguishes different components of the forces at play. This approach allows identifying how various force components impact the oscillation of a rigid body. The method is executed using the OpenFOAM open-source software. Numerical simulations are conducted on a two-dimensional smooth cylinder at both subcritical and supercritical Reynolds numbers to establish a correlation between wind turbine tower vibrations and the force mechanism. The analysis involves performing Unsteady Reynolds-Averaged Navier Stokes (URANS) simulations us-10 ing the modified pimpleFoam solver with the k-ω SST turbulence model. Both fixed and free-vibrating cases are studied for smooth cylinders. For the high Reynolds number cases, a setup matching the tower top segment of the IEA 15MW reference wind turbine was chosen. Studying the flow around a cylinder at a subcritical Reynolds number reveals that the primary force involved is the vorticity force. The combined force due to viscosity, added mass, and vorticity contributes most to the overall force. For a freely vibrating cylinder with a single degree of freedom in the cross-flow direction, the analysis indicates that the 15 force component associated with the cylinder’s motion is crucial and significantly affects the total force. Moreover, analysing the energy transfer between the fluid and the structure, a positive energy contribution by the vorticity-induced force is observed on or before the dominant Strouhal velocity. This confirms observations at low Reynolds numbers in the literature that the vortex shedding predominantly contributes to the initiation of oscillations during VIV. The kinematic force contributes to the energy transfer of the system, but the mean energy transfer per cycle is negligible.
Proceedings of the Annual Meeting of the Cognitive Science Society

A key property of human cognition is its ability to generate novel predictions about unfamiliar situations by completing a partially-specified relation or an analogy. Here, we present a computational model capable of producing generative inferences from relations and analogs. This model, BART-Gen, operates on explicit representations of relations learned by BART ( Bayesian Analogy with Relational Transformations ), to achieve two related forms of generative inference: reasoning from a single relation, and reasoning from an analog. In the first form, a reasoner completes a partially-specified instance of a stated relation (e.g., robin is a type of ____ ). In the second, a reasoner completes a target analog based on a stated source analog (e.g., sedan:car :: robin:____ ). We compare the performance of BART-Gen with that of BERT, a popular model for Natural Language Processing (NLP) that is trained on sentence completion tasks and that does not rely on explicit representations of relations. Across simulations and human experiments, we show that BART-Gen produces more human-like responses for generative inferences from relations and analogs than does the NLP model. These results demonstrate the essential role of explicit relation representations in human generative reasoning.