Miracle-dz/UniFAR-FTUs huggingface dataset:
Unveiling phase transitions with machine learning

The classification of phase transitions is a central and challenging task in condensed matter physics. Typically, it relies on the identification of order parameters and the analysis of singularities in the free energy and its derivatives. Here, we propose an alternative framework to identify quantum phase transitions, employing both unsupervised and supervised machine learning techniques. Using the axial next-nearest neighbor Ising (ANNNI) model as a benchmark, we show how unsupervised learning can detect three phases (ferromagnetic, paramagnetic, and a cluster of the antiphase with the floating phase) as well as two distinct regions within the paramagnetic phase. Employing supervised learning we show that transfer learning becomes possible: a machine trained only with nearest-neighbour interactions can learn to identify a new type of phase occurring when next-nearest-neighbour interactions are introduced. All our results rely on few and low dimensional input data (up to twelve lattice sites), thus providing a computational friendly and general framework for the study of phase transitions in many-body systems.
Habitat: A Platform for Embodied AI Research

We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3D simulation. Specifically, Habitat consists of: (i) Habitat-Sim: a flexible, high-performance 3D simulator with configurable agents, sensors, and generic 3D dataset handling. Habitat-Sim is fast -- when rendering a scene from Matterport3D, it achieves several thousand frames per second (fps) running single-threaded, and can reach over 10,000 fps multi-process on a single GPU. (ii) Habitat-API: a modular high-level library for end-to-end development of embodied AI algorithms -- defining tasks (e.g., navigation, instruction following, question answering), configuring, training, and benchmarking embodied agents. These large-scale engineering contributions enable us to answer scientific questions requiring experiments that were till now impracticable or 'merely' impractical. Specifically, in the context of point-goal navigation: (1) we revisit the comparison between learning and SLAM approaches from two recent works and find evidence for the opposite conclusion -- that learning outperforms SLAM if scaled to an order of magnitude more experience than previous investigations, and (2) we conduct the first cross-dataset generalization experiments {train, test} x {Matterport3D, Gibson} for multiple sensors {blind, RGB, RGBD, D} and find that only agents with depth (D) sensors generalize across datasets. We hope that our open-source platform and these findings will advance research in embodied AI.
A regression discontinuity design for ordinal running variables: Evaluating central bank purchases of corporate bonds

Regression discontinuity (RD) is a widely used quasi-experimental design for causal inference. In the standard RD, the assignment to treatment is determined by a continuous pretreatment variable (i.e., running variable) falling above or below a pre-fixed threshold. In the case of the corporate sector purchase programme (CSPP) of the European Central Bank, which involves large-scale purchases of securities issued by corporations in the euro area, such a threshold can be defined in terms of an ordinal running variable. This feature poses challenges to RD estimation due to the lack of a meaningful measure of distance. To evaluate such program, this paper proposes an RD approach for ordinal running variables under the local randomization framework. The proposal first estimates an ordered probit model for the ordinal running variable. The estimated probability of being assigned to treatment is then adopted as a latent continuous running variable and used to identify a covariate-balanced subsample around the threshold. Assuming local unconfoundedness of the treatment in the subsample, an estimate of the effect of the program is obtained by employing a weighted estimator of the average treatment effect. Two weighting estimators---overlap weights and ATT weights---as well as their augmented versions are considered. We apply the method to evaluate the causal effect of the CSPP and find a statistically significant and negative effect on corporate bond spreads at issuance.
Physiological and molecular responses to ocean acidification among strains of a model diatom

Differential responses of diatoms, an important group of marine primary producers to ocean acidification, have been well documented. However, studies so far are based on limited representative strains from key species. Investigation of strain level responses will help us better understand the contrasting discrepancy in diatom responses to ocean acidification. Here, we selected four strains of the model diatom Phaeodactylum tricornutum isolated from different regions of the global ocean, representing all genotypes based on internal transcribed spacer 2 sequences, and investigated strain‐specific responses to ocean acidification. In response to ocean acidification, changes in carbon metabolism varied among strains, although no significant effects of ocean acidification on growth rates or pigments were observed in any strains. The expression of genes encoding plasma membrane bicarbonate transporters was downregulated in strain Pt4, reflecting a potential decrease in active HCO3− uptake, which was not observed in the other strains. Reduction of CO2 concentrating mechanism efficiency was also indicated by the regulated expression of genes encoding carbonic anhydrases that catalyze the interconversion of HCO3− and CO2 in the pyrenoids and pyrenoid‐penetrating thylakoid, which exhibited different patterns among the strains. Under ocean acidification conditions, C4‐like metabolism appeared to redistribute carbon flux to gluconeogenesis in strain Pt1, and lipid synthesis in strains Pt8 and Pt11, rather than participating in net photosynthetic carbon fixation. These variations were incompletely correlated with phylogenetic relationship in different strains, implying that the habitat‐adapted imprints of the different strains could also be responsible for their differential responses to ocean acidification.
Comment on "Experimental Evidence for a State-Point-Dependent Density-Scaling Exponent of Liquid Dynamics".

Recently Sanz et al. [A. Sanz, T. Hecksher, H.W. Hansen, J.C. Dyre, K. Niss, and U.R. Pedersen, Phys. Rev. Lett. 122, 055501 (2019). ] reported that the scaling exponent gamma for tetramethyl-tetraphenyl-trisiloxane (DC704) varied with temperature; i.e., was not a material constant. Such a finding is at odds with previously published results on this compound and on more than 100 other liquids and polymers. The result of Sanz et al. comes from their measurement of a pressure dependence of the relaxation time at low temperature that becomes weaker with increasing pressure. Such a result is unphysical and contrary to the behavior of all known liquids. We re-measured this pressure dependence for DC704 and find it to be linear over the studied range. Thus, the conclusion of Sans et al. is incorrect; gamma for DC704 is state-point independent, in accord with other simple liquids and polymers.
Camera Adversarial Transfer for Unsupervised Person Re-Identification

Unsupervised person re-identification (Re-ID) methods consist of training with a carefully labeled source dataset, followed by generalization to an unlabeled target dataset, i.e. person-identity information is unavailable. Inspired by domain adaptation techniques, these methods avoid a costly, tedious and often unaffordable labeling process. This paper investigates the use of camera-index information, namely which camera captured which image, for unsupervised person Re-ID. More precisely, inspired by domain adaptation adversarial approaches, we develop an adversarial framework in which the output of the feature extractor should be useful for person Re-ID and in the same time should fool a camera discriminator. We refer to the proposed method as camera adversarial transfer (CAT). We evaluate adversarial variants and, alongside, the camera robustness achieved for each variant. We report cross-dataset ReID performance and we compare the variants of our method with several state-of-the-art methods, thus showing the interest of exploiting camera-index information within an adversarial framework for the unsupervised person Re-ID.
Revealing the interior of black holes out of equilibrium in the Sachdev-Ye-Kitaev model

The Sachdev-Ye-Kitaev (SYK) model can be used to describe black holes (BHs) in two-dimensional nearly anti--de Sitter gravity. We show that when such BHs are perturbed by a time-dependent negative-energy perturbation, their interior can be partially revealed. In the SYK model, a partial measurement of the state of the Majorana fermion pairs allows one to construct a matching time-dependent negative-energy perturbation of the BH geometry that shifts the state of the BH away from its equilibrium state. Kourkoulou and Maldacena showed that, if the perturbation is strong enough, the interior can be fully exposed and the BH disappears. Here, we show that when the perturbation is weaker than the threshold for full exposure, it effectively moves the horizon of the BH inwards, thus partially exposing the interior of the BH and leaving behind a smaller BH. The exposure is in proportion to the number of measured Majorana pairs and so also in proportion to the magnitude of the energy of the perturbation. From the boundary, the partial measurement is perceived as a burst of radiation whose strength and duration are proportional to the number of measured Majorana pairs.
Impact of polarization observables and 
Bc→τν
 on new physics explanations of the 
b→cτν
 anomaly

The combined analysis of the BABAR, Belle, and LHCb data on B→Dτν, B→D∗τν and Bc→J/Ψτν decay observables shows evidence of physics beyond the Standard Model (SM). In this article, we study all the one- and two-dimensional scenarios which can be generated by adding a single new particle to the SM. We put special emphasis on the model-discriminating power of FL(D∗) and of the τ polarizations, and especially on the constraint from the branching fraction BR(Bc→τν). We critically review this constraint and do not support the aggressive limit of BR(Bc→τν)<10% used in some analyses. While the impact of FL(D∗) is currently still limited, the BR(Bc→τν) constraint has a significant impact: depending on whether one uses a limit of 60%, 30% or 10%, the pull for new physics (NP) in scalar operators changes drastically. More specifically, for a conservative 60% limit a scenario with scalar operators gives the best fit to data, while for an aggressive 10% limit this scenario is strongly disfavored and the best fit is obtained in a scenario in which only a left-handed vector operator is generated. We find a sum rule for the branching ratios of B→Dτν, B→D∗τν and Λb→Λcτν which holds for any NP contribution to the Wilson coefficients. This sum rule entails an enhancement of BR(Λb→Λcτν) over its SM prediction by (24±6)% for the current R(D(*)) data.
Cosmological simulations of dwarfs: the need for ISM physics beyond SN feedback alone

The dominant feedback mechanism in low mass haloes is usually assumed to take the form of massive stars exploding as supernovae (SNe). We perform very high resolution cosmological zoom-in simulations of five dwarf galaxies to z = 4 with our mechanical SN feedback model. This delivers the correct amount of momentum corresponding to the stage of the SN remnant evolution resolved, and has been shown to lead to realistic dwarf properties in isolated simulations. We find that in 4 out of our 5 simulated cosmological dwarfs, SN feedback has insufficient impact resulting in excessive stellar masses, extremely compact sizes and central super-solar stellar metallicities. The failure of the SN feedback in our dwarfs is physical in nature within our model and is the result of the build up of very dense gas in the early universe due to mergers and cosmic inflows prior to the first SN occurring. We demonstrate that our results are insensitive to resolution (provided that it is high enough), details of the (spatially uniform) UV background and reasonable alterations within our star formation prescription. We therefore conclude that the ability of SNe to regulate dwarf galaxy properties is dependent on other physical processes, such as turbulent pressure support, clustering and runaway of SN progenitors and other sources of stellar feedback.
New Methods to Study the Behavior of Molecularly Imprinted Polymers in Aprotic Solvents

This work presents three new experimental methods for studying molecular imprinting. The electric conductivity measurements of the pre-polymerization mixture of amine templates in an aprotic solvent provide evidence of ionic dissociation of the pre-polymerization complexes. The displacement measurement of the template propranolol from its molecularly imprinted polymer (MIP) using a quaternary ammonium ion in toluene, shows that this MIP behaves as an ion exchanger even in a non-polar solvent. The same experiment also shows that template binding to the MIP from toluene involves ionic interaction. The third experimental method introduced here serves to study the models of template binding on MIPs. To this end the binding isotherm of propranolol (PR) has been measured on a polymer mixture consisting of non-imprinted control polymer (NIP) and a stronger binding acidic polymer, respectively. All three methods are suitable for studying several other imprinting systems.
Reconfigurable Shape Memory and Self-Welding Properties of Epoxy Phenolic Novolac/Cashew Nut Shell Liquid Composites Reinforced with Carbon Nanotubes

Conventional shape memory polymers (SMPs) can memorize their permanent shapes. However, these SMPs cannot reconfigure their original shape to obtain a desirable geometry owing to permanent chemically or physically crosslinked networks. To overcome this limitation, novel SMPs that can be reconfigured via bond exchange reactions (BERs) have been developed. In this study, polymer composites consisting of epoxy phenolic novolac (EPN) and bio-based cashew nut shell liquid (CNSL) reinforced by multi-walled carbon nanotubes (CNTs) were prepared. The obtained composites exhibited shape memory and self-welding properties, and their shapes could be reconfigured via BERs. Their shape memory mechanisms were investigated using variable-temperature Fourier transform infrared spectroscopy and dynamic mechanical analysis. The EPN/CNSL composite containing 0.3 wt % CNTs showed the highest shape fixity and shape recovery ratio. Furthermore, shape memory behavior induced by irradiation of near-infrared (NIR) light was also observed. All samples showed high shape recovery ratios of nearly 100% over five cycles, and increasing the CNT content shortened the recovery time remarkably. The ability of shape reconfiguration and stress relaxation affected the photo-induced shape memory properties of reshaped samples. Additionally, the self-welding properties were also influenced by stress relaxation. The hindrance of stress relaxation caused by the CNTs resulted in a decrease in adhesive fracture energy (Gc). However, the Gc values of EPN/CNSL composites were comparable to those of epoxy vitrimers. These results revealed that the material design concepts of thermal- and photo-induced shape memory, shape reconfiguration, and self-welding were combined in the EPN/CNSL composites, which could be feasible method for advanced smart material applications.
Effect of an Atmospheric Pressure Plasma Jet on the Structure and Physicochemical Properties of Waxy and Normal Maize Starch

In present study, a novel physical modification of waxy maize starch (WMS) and normal maize starch (NMS) was investigated by using an atmospheric pressure plasma jet (APPJ) treatment. The effect on the structure and physicochemical properties of both starches was demonstrated by treatment with a 5% starch suspension (w/w) with APPJ for short periods of time (1, 3, 5, or 7 min). The pH of WMS and NMS was decreased after APPJ treatment from 5.42 to 4.94, and 5.09 to 4.75, respectively. The water-binding capacity (WBC) (WMS: 105.19%–131.27%, NMS: 83.56%–95.61%) and swelling volume (SV) (WMS: 2.96 g/mL–3.33 g/mL, NMS: 2.75 g/mL–3.05 g/mL) of the starches were obviously increased by APPJ treatment. The surfaces of starch granules were wrecked, due to plasma etching. No changes in the crystalline types of both starches were observed. However, the relative crystallinities (RCs) of WMS and NMS were reduced from 46.7% to 42.0%, and 40.1% to 35.7%, respectively. Moreover, the short-range molecular orders of both starches were slightly reduced. In addition, APPJ treatment resulted in lower gelatinization temperature and enthalpies. Therefore, APPJ provides a mild and green approach to starch modification, showing great potential for applications in the food and non-food industry.
Thermal Degradation and Flame Retardant Mechanism of the Rigid Polyurethane Foam Including Functionalized Graphene Oxide

A flame retardant rigid polyurethane foam (RPUF) system containing functionalized graphene oxide (fGO), expandable graphite (EG), and dimethyl methyl phosphonate (DMMP) was prepared and investigated. The results show that the limiting oxygen index (LOI) of the flame-retardant-polyurethane-fGO (FRPU/fGO) composites reached 28.1% and UL-94 V-0 rating by adding only 0.25 g fGO. The thermal degradation of FRPU samples was studied using thermogravimetric analysis (TG) and the Fourier transform infrared (FT-IR) analysis. The activation energies (Ea) for the main stage of thermal degradation were obtained using the Kissinger equation. It was found that the fGO can considerably increase the thermal stability and decrease the flammability of RPUF. Additionally, the Ea of FRPU/fGO reached 191 kJ·mol−1, which was 61 kJ·mol−1 higher than that of the pure RPUF (130 kJ·mol−1). Moreover, scanning electron microscopy (SEM) results showed that fGO strengthened the compactness and the strength of the “vermicular” intumescent char layer improved the insulation capability of the char layer to gas and heat.
Study of theThermo-/pH-Sensitivity of Stereo-Controlled Poly(N-isopropylacrylamide-co-IAM) Copolymers via RAFT Polymerization

In this work, a smart copolymer, Poly(nipam-co-IAM) was synthesized by copolymerization of N-isopropylacrylamide (nipam) and itaconamic acid (IAM) through reversible addition-fragmentation chain-transfer (RAFT) polymerization. Poly(nipam-co-IAM) has been studied previously synthesized via radical polymerization without stereo-control, and this work used cumyl dithiobenzoate and Ytterbium(III) trifluoromethanesulfonate as RAFT and stereo-control agents, respectively. The stereo-control result in this work shows that tacticity affects the lower critical solution temperature (LCST) and/or the profile of phase separation of Poly(nipam-co-IAM). In the pH 7 and pH 10 buffer solutions, the P(nipam-co-IAM) copolymer solutions showed soluble–insoluble–soluble transitions, i.e., both LCST and upper critical solution temperature (UCST) transitions, which had not been found previously, and the insoluble to soluble transition (redissolved behavior) occurred at a relatively low temperature. The insoluble to soluble transition of P(nipam-co-IAM) in alkaline solution occurred at a temperature of less than 45 °C. However, the redissolved behavior of P(nipam-co-IAM) was found only in the pH 7 and pH 10 buffer solutions and this redissolved behavior was more prominent for the atactic copolymers than in the isotactic-rich ones. In addition, the LCST results under our experimental range of meso content did not show a significant difference between the isotactic-rich and the atactic P(nipam-co-IAM). Further study on the soluble-insoluble-soluble (S-I-S) transition and the application thereof for P(nipam-co-IAM) copolymers will be conducted.
Highly Selective Copper Ion Imprinted Clay/Polymer Nanocomposites Prepared by Visible Light Initiated Radical Photopolymerization

There is an urgent demand worldwide for the development of highly selective adsorbents and sensors of heavy metal ions and other organic pollutants. Within these environmental and public health frameworks, we are combining the salient features of clays and chelatant polymers to design selective metal ion adsorbents. Towards this end, the ion imprinting approach has been used to develop a novel nanohybrid material for the selective separation of Cu2+ ions in an aqueous solution. The Cu2+-imprinted polymer/montmorillonite (IIP/Mt) and non-imprinted polymer/montmorillonite (NIP/Mt) nanocomposites were prepared by a radical photopolymerization process in visible light. The ion imprinting step was indeed important as the recognition of copper ions by IIP/Mt was significantly superior to that of NIP/Mt, i.e., the reference nanocomposite synthesized in the same way but in the absence of Cu2+ ions. The adsorption process as batch study was investigated under the experimental condition affecting same parameters such as contact time, concentration of metal ions, and pH. The adsorption capacity of Cu2+ ions is maximized at pH 5. Removal of Cu2+ ion achieved equilibrium within 15 min; the results obtained were found to be fitted by the pseudo-second-order kinetics model. The equilibrium process was well described by the Langmuir isothermal model and the maximum adsorption capacity was found to be 23.6 mg/g. This is the first report on the design of imprinted polymer nanocomposites using Type II radical initiators under visible light in the presence of clay intercalated with hydrogen donor diazonium. The method is original, simple and efficient; it opens up new horizons in the general domain of clay/polymer nanocomposites.
Intrinsic Fluorescence of PAMAM Dendrimers—Quenching Studies

Intrinsic, non-traditional fluorescence of polyamidoamine (PAMAM) dendrimers that do not possess classical fluorophores has been attracting considerable interest for the last decade. Many hypotheses regarding the source of the fluorescence have appeared, but some of them are still disputable. In order to shed new light on the nature of the phenomenon, we applied quenchers that are normally used to study intrinsic fluorescence of proteins (i.e., KI, CsCl, and acrylamide). KI and acrylamide efficiently quenched steady state fluorescence of PAMAM G2, PAMAM G3, and PAMAM G4 dendrimers. Stern-Volmer plots exhibited a downward curvature that has been elucidated by heterogenous emission. We assume that there are two distinct fluorescent moieties in the dendrimer structure that are characterized by different accessibility to the quenchers.