Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping of peatlands in the forested landscape of Sweden using lidar-based terrain indices

Abstract. Globally, northern peatlands are major carbon deposits with important implications for the climate system. It is therefore crucial to understand their spatial occurrence, especially in the context of peatland degradation by land cover change and climate change. This study was aimed at mapping peatlands in the forested landscape of Sweden by modelling soil data against lidar-based terrain indices. Machine learning methods were used to produce nationwide raster maps at 10 m spatial resolution indicating the presence or not of peatlands. Four different definitions of peatlands were examined: 30, 40, 50 and 100 cm thickness of the organic horizon. Depending on peatland definition, testing with a hold-out dataset indicated an accuracy of 0.89–0.91 and Matthew's correlation coefficient of 0.79–0.81. The final maps showed a national forest peatland extent of 60 292–71 996 km2, estimates which are in the range of previous studies employing traditional soil maps. In conclusion, these results emphasize the possibilities of mapping boreal peatlands with lidar-based terrain indices. The final peatland maps are publicly available at https://doi.org/10.17043/rimondini-2023-peatlands-2 (Rimondini et al., 2023) and may be employed for spatial planning, estimating carbon stocks and evaluating climate change mitigation strategies.
High Minimum Wages and the Monopsony Puzzle cover

We present the first causal analysis of recent large minimum wage increases, focusing on 47 larger U.S. counties that reached $15 or more by 2022q1. Using stacked county-level synthetic control estimators, we find substantial pay growth, no disemployment effects and reduced wage inequality. Our novel procedure ameliorates pandemic-related bias. We pose and address a monopsony puzzle: Researchers often invoke monopsony to explain absent negative employment effects, yet the model generally predicts positive employment effects. When we reduce selection and attenuation biases—by excluding areas with local minimum wages and high-wage counties—we find large, significant positive employment effects. JEL codes: B41, J23, J24, J31, J38, J42
DECODING COLONY SIZE OF AMAZONIAN STINGLESS BEES THROUGH INTRINSIC PARAMETERS

1. Stingless bees live in populous colonies that vary in size from a few hundred individuals to tens of thousands, although information on actual colony size is limited. Determining colony sizes using easily measurable biological parameters are important steps to understanding their life histories and ease their utilization and keeping. The objectives of this study were to determine the colony size of ﬁve Amazonian stingless bee species ( Melipona ﬂavolineat a, Melipona fasciculata , Scaptotrigona aﬀ. postica , Frieseomelitta longipes and Plebeia minima ), and to identify biological parameters that covary with colony size. 2. The number of brood cells, adult bees, and food stocks were counted under laboratory conditions, alongside ﬁeld assessments of egg-laying rate and external activity of adult workers. To identify covariates of colony size, the number of adult bees was regressed against the number of brood cells, egg-laying rate, external activity of adult workers, and food stocks, and the best Candidate models were ranked using the Akaike Information Criterion. 3. Mean ( ± s.d.) adult population sizes were: 1,046 ± 185 in M. ﬂavolineata ; 593 ± 300 in M. fasciculata ; 7,404 ± 1,391 in S. aﬀ. postica ; 2,425 ± 1,000 in F. longipes ; and 405 ± 254 in P. minima . We showed that the external activity is the biological parameter, after the number of brood cells, that presents the best relationship with the number of adult bees, which can be easily evaluated in the ﬁeld.
Buying from a Group

A buyer trades with a group of sellers whose heterogeneous willingness to trade is private information. She must trade with all sellers or none and must oﬀer sellers identical terms of trade. We characterize the optimal mechanism: trade occurs if and only if the buyer’s beneﬁt of trade exceeds a weighted average of sellers’ virtual values. These weights are endogenous, with sellers who are ex ante less inclined to trade being given greater inﬂu-ence. This mechanism always outperforms posted-price mechanisms, using the entire proﬁle of sellers’ values to set the terms of trade. An extension characterizes the entire Pareto frontier
Transformation of dense shelf water cascade to supercritical 1 turbidity currents: Impact on seabed geomorphology and 2 implication for climate change

13 Dense shelf water cascades (DSWC) are ubiquitous on continental margins worldwide. 14 They could transform into turbidity currents, shape the seabed physiography, and 15 influence sediment, organic carbon, and pollutants that transfer from the shelf to the 16 basin floor. However, there is still a lack of knowledge regarding how DSWC transforms 17 into turbidity currents, and how DSWC interacts with the seabed. The Central Region 18 of the offshore Gippsland Basin, located on the southeast Australian margin, is 19 seasonally impacted by DSWC (named the Bass Cascade Current; BCC) formed in the 20 Bass Strait. We observed complex seabed morphologies and highly diverse 21 sedimentary processes in this area using high-resolution multibeam bathymetry, 22 seismic reflection, and core description data. Observed sedimentary structures include 23 sediment waves, erosional scours, cyclic steps, submarine channels, longitudinal 24 furrows, submarine landslides and gullies. We ascribe this complexity to a dynamic 25 interaction between BCC, and Westerly wind-associated Ekman transport flow, and 26 strong waves. We found that the along-shelf transported BCC can interact with the 27 submarine landslides and generate supercritical turbidity currents transporting 28 downslope for more than 80 km. We reveal that climate change could significantly 29 impact the
Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks

Deep Neural Networks are known to be brittle to even minor distribution shifts compared to the training distribution. While one line of work has demonstrated that Simplicity Bias (SB) of DNNs – bias towards learning only the simplest features – is a key reason for this brittleness, another recent line of work has surprisingly found that diverse/ complex features are indeed learned by the backbone, and their brittleness is due to the linear classification head relying primarily on the simplest features. To bridge the gap between these two lines of work, we first hypothesize and verify that while SB may not altogether preclude learning complex features, it amplifies simpler features over complex ones. Namely, simple features are replicated several times in the learned representations while complex features might not be replicated. This phenomenon, we term Feature Replication Hypothesis, coupled with the Implicit Bias of SGD to converge to maximum margin solutions in the feature space, leads the models to rely mostly on the simple features for classification. To mitigate this bias, we propose Feature Reconstruction Regularizer (FRR) to ensure that the learned features can be reconstructed back from the logits. The use of FRR in linear layer training (FRR-L) encourages the use of more diverse features for classification. We further propose to finetune the full network by freezing the weights of the linear layer trained using FRR-L, to refine the learned features, making them more suitable for classification. Using this simple solution, we demonstrate up to 15% gains in OOD accuracy on the recently introduced semi-synthetic datasets with extreme distribution shifts. Moreover, we demonstrate noteworthy gains over existing SOTA methods on the standard OOD benchmark DomainBed as well.
Zugspitze ozone 1970–2020: the role of stratosphere–troposphere transport

Abstract. The pronounced increase in ozone observed at the Alpine station Zugspitze (2962 ma.s.l.) since the 1970s has been ascribed to an increase in stratospheric air descending to the Alps. In this paper, we present a reanalysis of the data from for both ozone (1978 to 2011) and carbon monoxide (1990–2011), which has been extended until 2020 by the data from the Global Atmosphere Watch site at the Umweltforschungsstation Schneefernerhaus (UFS; 2671 ma.s.l. – above sea level), which is located just below the Zugspitze summit. For ozone between 1970 and 1977, a constant annual average of 36.25 ppb (parts per billion) was assumed to have been obtained by extrapolation. The analysis is based on data filtering, utilizing the isotope 7Be (measured between 1970 and 2006) and relative humidity (1970 to 2011; UFS from 2002 to 2020). We estimate both the influence of stratospheric intrusions directly descending to the northern rim of the Alps from the full data filtering and the aged (“indirect”) intrusions from applying a relationship between ozone and the 7Be data. The evaluated total stratospheric contribution to the annual average ozone rises roughly from 12 ppb in 1970 to 24 ppb in 2003. It turns out that the increase in the stratospheric influence is particularly strong in winter. A lowering in positive trend is seen afterwards, with a delay of roughly 1 decade after the beginning of the decrease in the solar irradiation. The air masses hitting the Zugspitze summit became drier until 2003, and we see the growing stratospheric contribution as being an important factor for this drying. Both an increase in the lower-stratospheric ozone and the growing thickness of the intruding layers departing downward from just above the tropopause must be taken into consideration. Carbon monoxide in the intrusions did not change much during the full measurement period from 1990 to 2020, with a slight increase until 2005. This is remarkable since, for air outside intrusions, a decrease by approximately 44 % was found, indicating a substantial improvement in the tropospheric air quality.
Two-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms

This article considers a two-stage assembly scheduling problem (TSASP) with batch setup times, time-dependent deterioration, and preventive maintenance activities (PMAs). The objective of this problem is to simultaneously determine the optimal component-manufacturing sequence (CMS), product-assembly sequence (PAS), number of setups, and number and position of PMAs (PPMA). First, to determine the optimal solution, a novel mixed integer linear programming model (MILP) for the proposed problem is derived. Then, a standard genetic algorithm (SGA), hybrid genetic algorithm (HGA), standard harmony search (SHS), hybrid harmony search (HHS), and harmony-search-based evolutionary algorithm (HSEA) were proposed owing to the intractability of the optimal solution for large-scale problems. SGA and SHS provide a chromosome to represent a complete solution including three decisions (CMS, PAS, and PPMA). HGA, HHS, and HSEA provide a chromosome to represent a partial solution including PAS. CMS and PPMA are found by an effective local search heuristic based on the partial solution. A computational experiment is then conducted to evaluate the impacts of the factors on the performance of the proposed algorithms.
Global existence and asymptotic behavior to the solutions of 1-D Lyumkis energy transport model for semiconductors

The global existence and asymptotic behavior of smooth solutions to the initial-boundary value problem for the 1-D Lyumkis energy transport model in semiconductor science is studied. When the boundary is insulated, the smooth solution of the problem converges to a stationary solution of the drift diffusion equations, exponentially fast as t —> oo.
Improved catalog of NOx point source emissions (version 2)

Abstract. We present an updated (v2) catalog of NOx emissions from point sources as derived from TROPOspheric Monitoring Instrument (TROPOMI) measurements of NO2 (Products Algorithm Laboratory (PAL) product) combined with wind fields from ERA5. Compared to version 1 of the catalog (Beirle et al., 2021), several improvements have been introduced to the algorithm. Most importantly, several corrections are applied, accounting for the effects of plume height on satellite sensitivity, 3D topographic effects, and the chemical loss of NOx, resulting in considerably higher and more accurate NOx emissions. In addition, error estimates are provided for each point source, taking into account the uncertainties of the individual retrieval steps. The v2 catalog is based on a fully automated iterative detection algorithm of point sources worldwide. It lists 1139 locations that have been found to be significant NOx sources. The majority of these locations match power plants listed in the Global Power Plant Database (GPPD). Other NOx point sources correspond to cement plants, metal smelters, industrial areas, or medium-sized cities. The emissions listed in v2 of the catalog show good agreement (within 20 % on average) to emissions reported by the German Environment Agency (Umweltbundesamt, UBA) as well as the United States Environmental Protection Agency (EPA). The data are publicly available at https://doi.org/10.26050/WDCC/No_xPointEmissionsV2 (Beirle et al., 2023).
Confidence as an Arbiter of Attentional Allocation During Learning in Multidimensional Environments

1 Reinforcement learning algorithms are notoriously inefficient in high-dimensional environments, and yet people manage to solve these complex problems with ease. One way in which our brains are thought to make such high-dimensional problems tractable is by using selective attention to reduce the dimensionality to only those features that are relevant for the task. Prior work has demonstrated that in rewardbased learning, there is a bi-directional relationship between learning and attention, but how the brain decides where to employ attention over the course of learning is debated. Drawing on ideas from theoretical and experimental work, we propose that internal confidence computations may arbitrate between different attention strategies. To test this hypothesis, we used a high-dimensional reinforcement learning task in which efficient learning and concomitant maximization of reward requires narrowing of subjects’ attention to the relevant dimension. Our results demonstrate a clear link between confidence and the breadth of attention during learning. We also incorporated our hypotheses into two novel computational models that predict trial-by-trial attention during the task. While neither of our models performed better than the value-based model to which we compared them, our results do not disprove the idea that confidence modulates the distribution of attention during learning. Rather, they suggest that models which allocate attention purely based on value miss an important component of how subjects actually distribute their attention, and that more thought needs to be given to the role of confidence, as well as perseverance and hypothesis-testing. This section contains text that is based closely on, or identical to, text found in my junior paper (2017). iii
Diseases associated with loneliness in the elderly: a social challenge

: Objective: Identify pathologies in the elderly associated with loneliness. Methodology: Secondary research, integrative review type, structured according to Crossetti’s consensus. Results: After applying descriptors and search strategies, a total of 4,011 articles were identified, after applying filters, inclusion, and exclusion criteria, 27 articles were selected; from these articles 17 corresponded to WoS, 9 to BVS and 1 to PubMed. Conclusions: The association between loneliness and cognitive impairment, decreased physical fitness, Alzheimer's disease and cardiovascular events is highlighted. It is necessary to establish public policies to prepare people for their future aging process.
Understanding High Schools’ Effects on Longer-Term Outcomes

Improving education and labor market outcomes for low-income students is critical for advancing socioeconomic mobility in the United States. We explore how Massachusetts public high schools affect the longer-term outcomes of low-income students, using detailed longitudinal data. We estimate school value-added impacts on four-year college graduation and earnings. Similar students who attend schools at the 80th percentile of the distribution are 6 percentage points more likely to graduate from a four-year college and earn 13% (or $3,600) more annually at age 30 compared to peers who attend schools at the 20th percentile. We consider how school effectiveness across a range of short-term measures relates to longer-run impacts. Schools that improve students’ test scores and college aspirations improve longer-run outcomes more.
The VLA-COSMOS 3 GHz Large Project: AGN and host-galaxy properties out to z less than or similar to 6

We explore the multiwavelength properties of AGN host galaxies for different classes of radio-selected AGN out to z ≲ 6 via a multiwavelength analysis of about 7700 radio sources in the COSMOS field. The sources were selected with the Very Large Array (VLA) at 3 GHz (10 cm) within the VLA–COSMOS 3 GHz Large Project, and cross-matched with multiwavelength ancillary data. This is the largest sample of high-redshift (z ≲ 6) radio sources with exquisite photometric coverage and redshift measurements available. We constructed a sample of moderate-to-high radiative luminosity AGN (HLAGN) via spectral energy distribution decomposition combined with standard X-ray and mid-infrared diagnostics. Within the remainder of the sample we further identified low-to-moderate radiative luminosity AGN (MLAGN) via excess in radio emission relative to the star formation rates in their host galaxies. We show that at each redshift our HLAGN havesystematically higher radiative luminosities than MLAGN and that their AGN power occurs predominantly in radiative form, while MLAGN display a substantial mechanical AGN luminosity component. We found significant differences in the host properties of the two AGN classes, as a function of redshift. At z 1.5, we observed a reversal in the behaviour of the stellar mass distributions with the HLAGN populating the higher stellar mass tail. We interpret this finding as a possible hint of the downsizing of galaxies hosting HLAGN, with the most massive galaxies triggering AGN activity earlier than less massive galaxies, and then fading to MLAGN at lower redshifts. Our conclusion is that HLAGN and MLAGN samples trace two distinct galaxy and AGN populations in a wide range of redshifts, possibly resembling the radio AGN types often referred to as radiative- and jet-mode (or high- and low-excitation), respectively, whose properties might depend on the different availability of cold gas supplies.
Error analysis and Cramer–Rao bound for convolutional beamspace

—The MSE performance and Cramer–Rao Bound (CRB) for a recently proposed beamspace method, called convolutional beamspace (CBS), are studied. Beamspace processing for DOA estimation offers lower computational complexity and higher DOA resolution. However, traditional beamspace methods do not retain the Vandermonde structure of uniform linear array output, so additional preparation is required to apply root-MUSIC. CBS preserves the Vandermonde structure by using digital filtering. CBS also offers smaller estimation errors for correlated sources. In this paper, we analyze the MSE performance of CBS when MUSIC or root-MUSIC is used. The variance is derived from the asymptotic probability distribution of the eigenvectors of an average finite-snapshot covariance matrix. Meanwhile, the bias due to the filtered stopband sources is given by a first-order perturbation analysis. Known advantages of CBS are confirmed by the MSE analysis. For example, CBS yields smaller MSE for correlated sources than element-space. Moreover, the CRB is also derived. Conventionally, the CRB is a lower bound for unbiased estimators. A lower bound on the variances of the biased CBS estimator is obtained and shown to be well approximated by the classical CRB for unbiased estimators. Two forms of CRB expressions are derived, and they offer different insights as explained in the paper. All the results also apply to element-space since element-space is a special case of CBS. Finally, the theoretical results are verified by simulations.
Commitment Profiles of Restaurant Employees: A Person-Centered Approach with Multigroup Structural Equation Modeling

Person-centered approaches assume that a respective sample might reflect multiple subpopulations characterized by different sets of parameters. Three hospitality employee cohorts with different workplace profiles were hypothesized based on the levels of organizational commitment and predictive outcomes. The hypotheses were tested among subgroup populations using applied latent profile analyses and multigroup structural equation modeling (MSEM) procedures. The sample (n=160) differentiated between two restaurant types. The construct validity of the extracted latent profiles was verified by plotted Euclidean Distances and multivariate analysis of covariance. Next, cross-restaurant comparisons using MSEM provided the richer interpretations between subgroups and their relations. The analyses confirmed a model with four latent profiles. Further analysis using MSEM presented theoretical coherent patterns of predictor differences between full- and quick-service restaurant employees in terms of their intrinsic motivation and organizational-based self-esteem. Practical implications of implementing a person-centered approach to the study of restaurant employees and future directions are discussed.
In the footsteps of Copernicus: Padua and Uppsala

For over half a millennium the life and work of the Polish astronomer and mathematician Nicolaus Copernicus has been described and discussed in countless publications. And yet there are some aspects of his life, as well as the whereabouts of his remains that are relatively unknown to the general public. One of the less explored episodes is the period Copernicus spent at Padua University in Italy. Another that deserves more recognition is the recent detective story, involving work at the University of Uppsala in Sweden to identify his genetic material, permitting the deﬁnitive location of his grave. In this article we intend to shed light on these less familiar facts about Copernicus, hoping that the reader will be enticed to visit those two amazing historical cities: Padua and Uppsala.
Attitude Motion of Cylindrical Space Debris during Its Removal by Ion Beam

The paper is devoted to the problem of space debris mitigation. Contactless method of the space debris deorbiting is considered. It is assumed that ion thrusters on the active spacecraft create the ion flow, which blows the debris and slows it down. The objectives of this work are the development of mathematical models and the research of space debris motion under the action of the ion flow. It is supposed that the space debris is a rigid body of a cylindrical shape. Calculation of ion beam force and torque was performed for a self-similar model of plasma plume expansion using the hypothesis of ion fully diffused reflection from a surface. A mathematical model describing plane motions of the cylindrical space debris under the influence of gravity gradient torque and the ion flux was constructed. It was shown that motion of the space debris around its center of mass has a significant effect on its removal time. Phase portraits, describing the motion of the space debris relative to its center of mass, were constructed. Comparison of the descent times in different motion modes was carried out. The results can be used to create new effective systems of large space debris removal.