Showing papers by "Max Planck Society published in 2022"

Fair Top-k Ranking with multiple protected groups

Abstract: Ranking items or people is a fundamental operation at the basis of several processes and services, not all of them happening online. Ranking is required for different tasks, including search, personalization, recommendation, and filtering. While traditionally ranking has been aimed solely at maximizing some global utility function, recently the awareness of potential discrimination for some of the elements to rank, has captured the attention of researchers, which have thus started devising ranking systems which are non-discriminatory or fair for the items being ranked. So far, researchers have mostly focused on group fairness, which is usually expressed in the form of constraints on the fraction of elements from some protected groups that should be included in the top- k positions, for any relevant k . These constraints are needed in order to correct implicit societal biases existing in the input data and reflected in the relevance or fitness score computed. In this article, we tackle the problem of selecting a subset of k individuals from a pool of n ≫ k candidates, maximizing global utility (i.e., selecting the “best” candidates) while respecting given group-fairness criteria. In particular, to tackle this Fair Top- k Ranking problem, we adopt a ranked group-fairness definition which extends the standard notion of group fairness based on protected groups, by ensuring that the proportion of protected candidates in every prefix of the top- k ranking remains statistically above, or indistinguishable from, a given minimum threshold. Our notion of utility requires, intuitively, that every individual included in the top- k should be more qualified than every candidate not included; and that for every pair of candidates in the top- k , the more qualified candidate should be ranked above. The main contribution of this paper is an algorithm for producing a fair top- k ranking that can be used when more than one protected group is present, which means that a statistical test based on a multinomial distribution needs to be used instead of one for a binomial distribution, as the original FA*IR algorithms does. This poses important technical challenges and increases both the space and time complexity of the re-ranking algorithm. Our experimental assessment on real-world datasets shows that our approach yields small distortions with respect to rankings that maximize utility without considering our fairness criteria.

Planar heterojunction boosts solar-driven photocatalytic performance and stability of halide perovskite solar photocatalyst cell

Abstract: The excellent optoelectronic properties of metal halide perovskites (MHPs) have been employed in various photocatalytic applications, but their poor water stability is considered as the main bottleneck for further development. Herein, we protect the light-absorbing CsPbBr3 MHP with a NiOx and TiO2 hole and electron extracting layer. This planar NiOx/CsPbBr3/TiO2 architecture can easily be fabricated through solution-processing. When applied to selective photocatalytic oxidation of benzyl alcohol, this system presents a 7-fold enhancement of photoactivity and an improved stability for over 90 h compared to CsPbBr3 counterpart. Interestingly, we find that trace amounts of water improve photoactivity. Through experimental and theoretical analyses, this improvement could be attributed to water-induced structural reorganization of MHP, leading to improved crystal quality and decreased effective masses of charge carriers. This work indicates planar heterojunction helps improve the photoactivity and stability of MHP photocatalyst, and our findings provide insights into the effect of water on MHPs.

What makes a megaplasmid

Abstract: Naturally occurring plasmids come in different sizes. The smallest are less than a kilobase of DNA, while the largest can be over three orders of magnitude larger. Historically, research has tended...

Facilitating the acidic oxygen reduction of Fe-N-C catalysts by fluorine-doping.

Abstract: As the alternatives to expensive Pt-based materials for the oxygen reduction reaction (ORR), iron/nitrogen co-doped carbon catalysts (FeNC) with dense FeNx active sites are promising candidates to promote the commercialization of proton exchange membrane fuel cells. Herein, we report a synthetic approach using perfluorotetradecanoic acid (PFTA)-modified metal–organic frameworks as precursors for the synthesis of fluorine-doped FeNC (F-FeNC) with improved ORR performance. The utilization of PFTA surfactants causes profound changes of the catalyst structure including F-doping into graphitic carbon, increased micropore surface area and Brunauer–Emmett–Teller (BET) surface area (up to 1085 m2 g−1), as well as dense FeNx sites. The F-FeNC catalyst exhibits an improved ORR activity with a high E1/2 of 0.83 V (VS. RHE) compared to the pristine FeNC material (E1/2 = 0.80 V). A fast decay occurs in the first 10 000 potential cycles for the F-FeNC catalyst, but high durability is still maintained up to another 50 000 cycles. Density functional theory calculations reveal that the strongly withdrawing fluorine atoms doped on the graphitic carbon can optimize the electronic structure of the FeNx active center and decrease the adsorption energy of ORR intermediates.

Searches for Gravitational Waves from Known Pulsars at Two Harmonics in the Second and Third LIGO-Virgo Observing Runs

Abstract: We present a targeted search for continuous gravitational waves (GWs) from 236 pulsars using data from the third observing run of LIGO and Virgo (O3) combined with data from the second observing run (O2). Searches were for emission from the $l=m=2$ mass quadrupole mode with a frequency at only twice the pulsar rotation frequency (single harmonic) and the $l=2, m=1,2$ modes with a frequency of both once and twice the rotation frequency (dual harmonic). No evidence of GWs was found so we present 95\% credible upper limits on the strain amplitudes $h_0$ for the single harmonic search along with limits on the pulsars' mass quadrupole moments $Q_{22}$ and ellipticities $\varepsilon$. Of the pulsars studied, 23 have strain amplitudes that are lower than the limits calculated from their electromagnetically measured spin-down rates. These pulsars include the millisecond pulsars J0437\textminus4715 and J0711\textminus6830 which have spin-down ratios of 0.87 and 0.57 respectively. For nine pulsars, their spin-down limits have been surpassed for the first time. For the Crab and Vela pulsars our limits are factors of $\sim 100$ and $\sim 20$ more constraining than their spin-down limits, respectively. For the dual harmonic searches, new limits are placed on the strain amplitudes $C_{21}$ and $C_{22}$. For 23 pulsars we also present limits on the emission amplitude assuming dipole radiation as predicted by Brans-Dicke theory.

Representative volume elements for matrix-inclusion composites - a computational study on the effects of an improper treatment of particles intersecting the boundary and the benefits of periodizing the ensemble

Abstract: We investigate volume-element sampling strategies for the stochastic homogenization of particle-reinforced composites and show, via computational experiments, that an improper treatment of particles intersecting the boundary of the computational cell may affect the accuracy of the computed effective properties. Motivated by recent results on a superior convergence rate of the systematic error for periodized ensembles compared to taking snapshots of ensembles, we conduct computational experiments for microstructures with circular, spherical and cylindrical inclusions and monitor the systematic errors in the effective thermal conductivity for snapshots of ensembles compared to working with microstructures sampled from periodized ensembles. We observe that the standard deviation of the apparent properties computed on microstructures sampled from the periodized ensembles decays at the scaling expected from the central limit theorem. In contrast, the standard deviation for the snapshot ensembles shows an inferior decay rate at high filler content. The latter effect is caused by additional long-range correlations that necessarily appear in particle-reinforced composites at high, industrially relevant, volume fractions. Periodized ensembles, however, appear to be less affected by these correlations. Our findings provide guidelines for working with digital volume images of material microstructures and the design of representative volume elements for computational homogenization.

Computer-aided molecular design of solvents for chemical separation processes

Abstract: Solvents are widely used in chemical industries, especially in various separation processes. As traditional trial-and-error solvent selection is time-consuming and expensive, model-based methods for solvent selection/design become important for efficient and sustainable chemical manufacturing. A lot of contributions have been made in this area in the past few decades. This article first reviews the prediction methods for solvent properties, including single molecular properties and mixture properties. Then, the solution strategies of solvent design problems are summarized, including generate-and-test, deterministic optimization, and stochastic optimization methods. Next, latest progresses of computer-aided solvent-process design in separation processes including liquid–liquid extraction, extractive distillation, gas absorption, and crystallization are reviewed. Finally, several remaining challenges and possible future directions for solvent design in separation processes are pointed out.

Self-organization of rectangular bipyramidal helical columns by supramolecular orientational memory epitaxially nucleated from a Frank-Kasper σ phase

Abstract: Programming living and soft complex matter via primary structure and self-organization represents the key methodology employed to design functions in biological and synthetic nanoscience. Memory effects have been used to create commercial technologies including liquid crystal displays and biomedical applications based on shape memory polymers. Supramolecular orientational memory (SOM), induced by an epitaxial nucleation mediated by the close contact spheres of cubic phases, emerged as a pathway to engineer complex nanoscale soft matter of helical columnar hexagonal arrays. SOM preserves the crystallographic directions of close contact supramolecular spheres from the 3D phase upon cooling to the columnar hexagonal periodic array. Despite the diversity of 3D periodic and quasiperiodic nanoarrays of supramolecular dendrimers, including Frank-Kasper and quasicrystal, all examples of SOM to date were mediated by Im3¯m (body-centered cubic, BCC) and Pm3¯n (Frank-Kasper A15) cubic phases. Expanding the scope of SOM to non-cubic arrays is expected to generate additional morphologies that were not yet available by any other methods. Here we demonstrate the SOM of a dendronized triphenylene that self-organizes into helical columnar hexagonal and tetragonal P4/mnm (Frank-Kasper σ) phases. Structural analysis of oriented fibers by X-ray diffraction reveals that helical columnar hexagonal domains self-organize an unusual rectangular bipyramidal morphology upon cooling from the σ phase. The discovery of SOM in a non-cubic Frank-Kasper phase indicates that this methodology may be expanded to other periodic and quasiperiodic nanoarrays organized from self-assembling dendrimers and, most probably, to other soft and living complex matter.

Deep Learning for Text Style Transfer: A Survey

Abstract: Abstract Text style transfer is an important task in natural language generation, which aims to control certain attributes in the generated text, such as politeness, emotion, humor, and many others. It has a long history in the field of natural language processing, and recently has re-gained significant attention thanks to the promising performance brought by deep neural models. In this article, we present a systematic survey of the research on neural text style transfer, spanning over 100 representative articles since the first neural text style transfer work in 2017. We discuss the task formulation, existing datasets and subtasks, evaluation, as well as the rich methodologies in the presence of parallel and non-parallel data. We also provide discussions on a variety of important topics regarding the future development of this task.1

The development of prosocial behavior-from sympathy to strategy.

Abstract: Children act prosocially already in their first years of life. Research has shown that this early prosociality is mostly motivated by sympathy for others, but that, over the course of development, children's prosocial behaviors become more varied, more selective, and more motivationally and cognitively complex. Here, we review recent evidence showing that starting at around age 5, children become gradually capable of strategically using prosocial acts as instrumental means to achieve ulterior goals such as to improve their reputation, to be chosen as social partners, to elicit reciprocity, and to navigate interpersonal obligations. Children's sympathy-based prosociality is thus being extended and reshaped into a behavioral repertoire that enables individuals to pursue and balance altruistic, mutualistic, and selfish motives.

Using large, publicly available datasets to study adolescent development: Opportunities and challenges

Abstract: Adolescence is a period of rapid change, with cognitive, mental wellbeing, environmental biological factors interacting to shape lifelong outcomes. Large, longitudinal phenotypically rich data sets available for reuse (secondary data) have revolutionized the way we study adolescence, allowing the field to examine these unfolding processes across hundreds or even thousands of individuals. Here, we outline the opportunities and challenges associated with such secondary data sets, provide an overview of particularly valuable resources available to the field, and recommend best practices to improve the rigor and transparency of analyses conducted on large, secondary data sets.