Miracle-dz/UniFAR-FTUs huggingface dataset:
Revealing the Phase Diagram of Kitaev Materials by Machine Learning: Cooperation and Competition between Spin Liquids

Kitaev materials are promising materials for hosting quantum spin liquids and investigating the interplay of topological and symmetry-breaking phases. We use an unsupervised and interpretable machine-learning method, the tensorial-kernel support vector machine, to study the classical honeycomb Kitaev-$\Gamma$ model in a magnetic field. Our machine learns the global phase diagram and the associated analytical order parameters, including several distinct spin liquids, two exotic $S_3$ magnets, and two modulated $S_3 \times Z_3$ magnets. We find that the extension of Kitaev spin liquids and a field-induced suppression of magnetic order already occur in the large-$S$ limit, implying that critical parts of the physics of Kitaev materials can be understood at the classical level. Moreover, the two $S_3 \times Z_3$ orders are induced by competition between Kitaev and $\Gamma$ spin liquids and feature a previously unknown type of spin-lattice entangled modulation, which requires a matrix description instead of scalar phase factors. Our work provides the first instance of a machine detecting new phases and paves the way towards the development of automated tools to explore unsolved problems in many-body physics.
Trophic implications of light reductions for Amphibolis Griffithii seagrass fauna

Numerous anthropogenic activities can significantly reduce the amount of light reaching seagrass habitats. Typically these result in morphological and physiological changes to the plant and associated algal epiphytes. However, the flow-on effects to seagrass dependent fauna induced by these disturbances has yet to be examined. This study investigated the effects of different intensity (High: ~92% and Moderate: ~84% reduction), duration (3, 6 and 9 months) and timing (post-winter and post-summer), of light reductions on the density and biomass of macroinvertebrate epifauna within an Amphibolis griffithii seagrass ecosystem, Western Australia. There were generally lower epifauna densities and biomass within shaded seagrass plots. When Moderate intensity shading was imposed at the end of winter, total density was 31% lower than in unshaded controls at three months and 78% at nine months. When High intensity shading was imposed, total density was 38% lower than in controls at three months and 89% by nine months. Although densities varied, similar magnitudes of decline occurred in Post-summer shaded treatments. Taxa-specific responses were variable in terms of time, rapidity and magnitude of response. Amphipod, isopod and gastropod densities generally declined in response to shading. Bivalve densities declined with shading Post-summer but not Post-winter. Ostracod densities had an inconsistent response to Moderate shading. Changes in epifaunal density were largely associated with declines in algal biomass, leaf variables and stem biomass, indicating food and habitat limitations. It is likely that the significant declines in epifauna observed in this experiment, would have flow-on consequences to higher trophic levels.
Energy transfer mechanisms and resolvent analysis in the cylinder wake

Energy transfer mechanisms for vortex shedding behind a 2D cylinder at a Reynolds number of Re=100 are investigated. We first characterize the energy balances achieved by the true cylinder flow---both for the flow as a whole and for each of its most energetic harmonic frequencies. It is found that viscous dissipation balances production when each is considered over the entire flow field and therefore that linear mechanisms achieve an energy balance on their own, thus respecting the Reynolds--Orr equation. Suitable energy conservation laws reveal that while nonlinear mechanisms neither produce nor consume energy overall, they nevertheless account for an important transfer of energy to higher frequencies. The energy balance for DNS is compared to that predicted by resolvent analysis. Although a suitable energy balance is achieved for each harmonic, resolvent analysis does not correctly model energy transfer between temporal frequencies. We further investigate the detailed roles of energy transfer from the viewpoint of nonlinear triadic interactions by considering a finite number of harmonic frequencies. It is shown that the nonlinearity plays a critical role in the redistribution of energy to higher harmonic frequencies. We observe not only an energy cascade from low frequencies to high frequencies, but also a considerable inverse cascade from high frequencies to low frequencies. The true nonlinear energy transfer mechanisms provide insight into closure models for improved resolvent-based predictions of harmonic modes in shear flows.
How Do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking

Attribution methods assess the contribution of inputs (e.g., words) to the model prediction. One way to do so is erasure: a subset of inputs is considered irrelevant if it can be removed without affecting the model prediction. Despite its conceptual simplicity, erasure is not commonly used in practice. First, the objective is generally intractable, and approximate search or leave-one-out estimates are typically used instead; both approximations may be inaccurate and remain very expensive with modern deep (e.g., BERT-based) NLP models. Second, the method is susceptible to the hindsight bias: the fact that a token can be dropped does not mean that the model `knows' it can be dropped. The resulting pruning is over-aggressive and does not reflect how the model arrives at the prediction. To deal with these two challenges, we introduce Differentiable Masking. DiffMask relies on learning sparse stochastic gates (i.e., masks) to completely mask-out subsets of the input while maintaining end-to-end differentiability. The decision to include or disregard an input token is made with a simple linear model based on intermediate hidden layers of the analyzed model. First, this makes the approach efficient at test time because we predict rather than search. Second, as with probing classifiers, this reveals what the network `knows' at the corresponding layers. This lets us not only plot attribution heatmaps but also analyze how decisions are formed across network layers. We use DiffMask to study BERT models on sentiment classification and question answering.
Bilateral Attention Network for RGB-D Salient Object Detection

RGB-D salient object detection (SOD) aims to segment the most attractive objects in a pair of cross-modal RGB and depth images. Currently, most existing RGB-D SOD methods focus on the foreground region when utilizing the depth images. However, the background also provides important information in traditional SOD methods for promising performance. To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task. Specifically, we introduce a Bilateral Attention Module (BAM) with a complementary attention mechanism: foreground-first (FF) attention and background-first (BF) attention. The FF attention focuses on the foreground region with a gradual refinement style, while the BF one recovers potentially useful salient information in the background region. Benefited from the proposed BAM module, our BiANet can capture more meaningful foreground and background cues, and shift more attention to refining the uncertain details between foreground and background regions. Additionally, we extend our BAM by leveraging the multi-scale techniques for better SOD performance. Extensive experiments on six benchmark datasets demonstrate that our BiANet outperforms other state-of-the-art RGB-D SOD methods in terms of objective metrics and subjective visual comparison. Our BiANet can run up to 80 fps on $224\times 224$ RGB-D images, with an NVIDIA GeForce RTX 2080Ti GPU. Comprehensive ablation studies also validate our contributions.
Aproveitamento e caracteristicas da gordura cavitaria do tambaqui, Colossoma macropomun, Cuvier 1818

O presente trabalho se refere a um estudo da gordura cavitaria do Colossoma macropomum, com relacao as caracteristicas fisicas e quimicas e seu potencial como gordura de cozinha. Este peixe de agua doce e conhecido na regiao amazonica com o nome de tambaqui. As amostras foram coletadas em quatro epocas: julho e outubro de 1977 e fevereiro e abril de 1978. Na ultima amostra foi de terminado tambem o conteudo de gordura muscular. Varia.s determinacoes fisicas e quimicas foram efetuadas dentre elas as mais significantes sao: indice de acidez 0,14 - 2,16; indice de Iodo 60,0 - 96,0; Ponto de fusao 27.5o - 45oC. A baixa acidez indicou que poderiamos suprimir a etapa de neutralizacao no processo de refinacao da gordura. O baixo indice de Iodo nos indica alta proporcao de acidos graxos saturados. A determinacao dos acidos graxos por cromatografia gasosa constatou alto teor de acidos graxos saturados (35.5 - 53.5i), que explica o estado semi-so1ido apresentado pela gordura. As analises revelaram que a gordura do tambaqui se assemelha mais a gordura e oleos vegetais e animais, do que oleos de peixe de agua salgada. Os acidos graxos tipicos de peixe de agua do mar eicosapentaenoioo (C20:5) e docosahexaenoico (C22:6) nao foram encontrados nas epocas estudadas.Observacao: O resumo, na integra, podera ser visualizado no texto completo da tese digital Abstract
Extreme statistics of anomalous subdiffusion following a fractional Fokker–Planck equation: subdiffusion is faster than normal diffusion

Anomalous subdiffusion characterizes transport in diverse physical systems and is especially prevalent inside biological cells. In cell biology, the prevailing model for chemical activation rates has recently changed from the first passage time (FPT) of a single searcher to the FPT of the fastest searcher out of many searchers to reach a target, which is called an extreme statistic or extreme FPT. In this paper, we investigate extreme statistics of searchers which move by anomalous subdiffusion. We model subdiffusion by a fractional Fokker–Planck equation involving the Riemann–Liouville fractional derivative. We prove an explicit and very general formula for every moment of subdiffusive extreme FPTs and approximate their full probability distribution. While the mean FPT of a single subdiffusive searcher is infinite, the fastest subdiffusive searcher out of many subdiffusive searchers typically has a finite mean FPT. In fact, we prove the counterintuitive result that extreme FPTs of subdiffusion are faster than extreme FPTs of normal diffusion. Mathematically, we employ a stochastic representation involving a random time change of a standard Ito drift–diffusion according to the trajectory of the first crossing time inverse of a Levy subordinator. A key step in our analysis is generalizing Varadhan’s formula from large deviation theory to the case of subdiffusion, which yields the short-time distribution of subdiffusion in terms of a certain geodesic distance.
Confinement-induced self-organization in growing bacterial colonies

How do bacterial colonies orient and navigate through a narrow channel? We investigate the emergence of global alignment in colonies of dividing rod-shaped cells under confinement. Using molecular dynamics simulations and continuous modeling, we demonstrate that geometrical anisotropies in the confining environment give rise to an imbalance in the normal stresses, which, in turn, drives a collective rearrangement of the cells. This behavior crucially relies on the colony’s solid-like mechanical response at short time scales and can be recovered within the framework of active hydrodynamics upon modeling bacterial colonies as growing viscoelastic gels characterized by Maxwell-like stress relaxation.
Effect of dietary γ-aminobutyric acid on performance parameters and some plasma metabolites in Cherry Valley ducks under high ambient temperature

Department of Animal Science, College of Animal Science and Technology, Shandong Agricultural University, Taian, Shandong, 271018, China; Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran; MSc Student in Animal Science, Department of Animal Science, College of Animal Science and Technology, Shandong Agricultural University, Taian, Shandong, 271018, China
Defeating stochasticity: coalescence time-scales of massive black holes in galaxy mergers

The coalescence of massive black hole binaries (BHBs) in galactic mergers is the primary source of gravitational waves (GWs) at low frequencies. Current estimates of GW detection rates for the Laser Interferometer Space Antenna and the Pulsar Timing Array vary by three orders of magnitude. To understand this variation, we simulate the merger of equal-mass, eccentric, galaxy pairs with central massive black holes and shallow inner density cusps. We model the formation and hardening of a central BHB using the fast multiple method as a force solver, which features a O(N) scaling with the number N of particles and obtains results equivalent to direct-summation simulations. At N ∼ 5 × 105, typical for contemporary studies, the eccentricity of the BHBs can vary significantly for different random realizations of the same initial condition, resulting in a substantial variation of the merger time-scale. This scatter owes to the stochasticity of stellar encounters with the BHB and decreases with increasing N. We estimate that N ∼ 107 within the stellar half-light radius suffices to reduce the scatter in the merger time-scale to ∼10 per cent. Our results suggest that at least some of the uncertainty in low-frequency GW rates owes to insufficient numerical resolution.
High-velocity Type Ia Supernova Has a Unique Host Environment

Ejecta velocity of Type Ia supernovae (SNe Ia) is one powerful tool to differentiate between progenitor scenarios and explosion mechanisms. Here we revisit the relation between photospheric Si ii λ6355 velocities (vSi ii) and host-galaxy properties with ∼280 SNe Ia. A more stringent criterion on the phase of SN spectra is adopted to classify SNe Ia in terms of their photospheric velocities. We find a significant trend that SNe Ia with faster Si ii λ6355 (high-vSi ii SNe Ia) tend to explode in massive environments, whereas their slower counterparts can be found in both lower-mass and massive environments. This trend is further supported by the direct measurements on host gas-phase metallicities. We suggest this relation is likely caused by at least two populations of SNe Ia. Since stars of higher metallicity (at a given mass) generally form less massive white dwarfs, our results support some theoretical models that high-vSi ii SNe Ia may originate from sub-Chandrasekhar class of explosions. Previous observations also showed some evidence that high-vSi ii SNe Ia could be related to the single degenerate systems. However, we find high-vSi ii SNe Ia do not come from particularly young populations. We conclude metallicity is likely the dominant factor in forming high-vSi ii SNe Ia. This also implies their potential evolution with redshift and impact on the precision of SN Ia cosmology.
Appliance Specific Feedback and Social Comparisons: Evidence From a Field Experiment on Electricity Saving

Feedback about individual electricity consumption relative to others in the population is widely used to steer behavior and reduce electricity consumption. This feedback usually informs households about their aggregate electricity consumption relative to others. While aggregate consumption feedback already translates into significant energy savings, it may leave potential savings untapped because households lack the knowledge where to save most efficiently. In this paper, we provide households with detailed feedback about their consumption of a specific high energy use appliance (air-conditioning) relative to other households. We thereby also exogenously vary a households' reference group about which they receive the appliance specific consumption information. We find that our appliance specific feedback is a powerful tool to curb electricity consumption. Households significantly reduce their average air-conditioning consumption by 17% in our treatment groups. Our effects are not driven by comparative feedback to specific reference groups. We interpret this as encouraging evidence to promote the use of appliance specific consumption feedback to realize electricity savings.
Towards optimal doubly robust estimation of heterogeneous causal effects

Heterogeneous effect estimation plays a crucial role in causal inference, with applications across medicine and social science. Many methods for estimating conditional average treatment effects (CATEs) have been proposed in recent years, but there are important theoretical gaps in understanding if and when such methods are optimal. This is especially true when the CATE has nontrivial structure (e.g., smoothness or sparsity). Our work contributes in several main ways. First, we study a two-stage doubly robust CATE estimator and give a generic model-free error bound, which, despite its generality, yields sharper results than those in the current literature. We apply the bound to derive error rates in nonparametric models with smoothness or sparsity, and give sufficient conditions for oracle efficiency. Underlying our error bound is a general oracle inequality for regression with estimated or imputed outcomes, which is of independent interest; this is the second main contribution. The third contribution is aimed at understanding the fundamental statistical limits of CATE estimation. To that end, we propose and study a local polynomial adaptation of double-residual regression. We show that this estimator can be oracle efficient under even weaker conditions, if used with a specialized form of sample splitting and careful choices of tuning parameters. These are the weakest conditions currently found in the literature, and we conjecture that they are minimal in a minimax sense. We go on to give error bounds in the non-trivial regime where oracle rates cannot be achieved. Some finite-sample properties are explored with simulations.
Cell fate specification and polarisation in mouse preimplantation epithelia

Understanding the establishment of polarity and the cell fate specification of epithelial cells is important for developmental biology, regenerative medicine and the study of cancer. In this thesis, models of pre-implantation epithelial development are used to investigate the relationship between these two processes. The trophoblast is an extraembryonic epithelial tissue which contributes to the placenta. Addition of BMP4 to mouse and human embryonic stem (mES) cells grown in culture has been suggested to induce differentiation of cells to the trophoblast lineage. The use of this differentiation method was investigated as a possible model of trophoblast polarisation and cell fate specification. Unfortunately, with the protocol and reagents available this model did not appear to physiologically recapitulate trophoblast development and was not reliable. The primitive endoderm is an epithelium which arises from the inner cell mass during mammalian pre-implantation development. It faces the blastocoel cavity and later gives rise to the extraembryonic parietal and visceral endoderm. When mES cells are grown in suspension they form aggregates of differentiating cells known as embryoid bodies. The outermost cell layer of an embryoid body is an epithelial cell type comparable to the primitive endoderm. Embryoid bodies were used here to study the polarisation and cell fate specification of the primitive endoderm. The outer cells of these embryoid bodies were found to gradually acquire the hallmarks of polarised epithelial cells and express markers of primitive endoderm cell fate. The acquisition of epithelial polarity occurred prior to the maximal expression of cell fate markers. Fgfr/Erk signalling is known to be required for specification of the primitive endoderm, but its role in polarisation of this tissue is less well understood. To investigate the function of this pathway in the primitive endoderm, embryoid bodies were cultured in the presence of a small molecule inhibitor of Mek. This inhibitor caused a loss of expression of markers of primitive endoderm cell fate and maintenance of the pluripotency marker Nanog. In addition, a mislocalisation of apico-basolateral markers and disruption of the epithelial barrier which normally blocks free diffusion across the epithelial cell layer occurred. Two inhibitors of the Fgf receptor elicited similar phenotypes, suggesting that Fgf receptor signalling promotes Erkmediated polarisation. This data shows that the formation of a polarised primitive endoderm layer in embryoid bodies requires the Fgfr/Erk signalling pathway.
Influence du poids sur l’activité de la polyarthrite rhumatoïde : étude prospective sur douze mois

Introduction : l’objectif de notre etude est d’evaluer l’influence du poids sur l’activite de la Polyarthrite Rhumatoide (PR) sur 12 mois. Methode : les patients ont ete selectionnes dans une cohorte monocentrique observationnelle prospective, suivie au CHU de Nice entre 2001 et 2017. Seules certaines donnees ont ete recueillies retrospectivement. Etaient inclus, les patients d’au moins 18 ans, traites par un DMARDS et/ou une biotherapie, respectant les criteres ACR / EULAR 2010 pour le diagnostic de la PR et presentant une PR active. La reponse clinique a ete evaluee apres 12 mois. Le critere principal d’efficacite etait une diminution du DAS 28 VS superieure ou egale a 1.2. Le critere secondaire etait la proportion de patients atteignant la remission clinique selon l’EULAR. Resultats : 307 patients sur les 425 screenes ont ete inclus. L’analyse multivariee a montre que seule la CRP etait un facteur predictif significatif de reponse au traitement (OR ajuste = 0.98 [0,95 ; 1,00] p = 0.034). L’etude des patients sous biotherapie a montre que les facteurs influencant la reponse therapeutique en analyse univariee etaient le sexe feminin (p = 0.047 ; OR = 0.45 [0,20 ; 0,97]) et la biotherapie, principalement le Tocilizumab (p=0.005 ; OR = 2.7 [1,37 ; 5,45]). Le poids ne semblait pas influencer la reponse therapeutique quel que soit le type de traitement (p = 0.136 chez les patients sans biotherapie, p = 0.724 avec biotherapie). Parmi les patients sous anti TNF alpha, il n’y avait pas de difference significative entre les differents types de traitement (p = 0.390). Conclusion : Dans notre etude, le poids n’influence pas l’activite de la PR et ne semble pas etre un facteur predictif de reponse au traitement.
Forest hydrology and catchment management: an Australian perspective

Within the discipline of forest science, both hydrology and catchment management have traditionally been recognised as key components. Scientifically, catchment research at locations such as Hubbard Brook, Coweeta and the Andrews site in the USA provided the format for methods and information required in understanding dynamics of forest systems. While information on the principles of hydrology from overseas was relatively easy to obtain, it was more difficult to obtain information specific to Australian conditions. In his book on forest hydrology, Leon Bren has tried to overcome some of these deficiencies by providing ‘a concise account of the discipline and findings of forest hydrology in Australia’ using his long experience at the Cropper Creek study area in north-eastern Victoria. The focus of the book is on hydrology, specifically in paired catchment studies, and steers away from the ecological and nutrient cycling components of catchment studies as has been reported in other books on forested catchments. A large proportion of the information is from Victoria and probably the title should have been ‘a south-eastern Australian perspective’.