Miracle-dz/UniFAR-FTUs huggingface dataset:
Amortized Projection Optimization for Sliced Wasserstein Generative Models

Seeking informative projecting directions has been an important task in utilizing sliced Wasserstein distance in applications. However, finding these directions usually requires an iterative optimization procedure over the space of projecting directions, which is computationally expensive. Moreover, the computational issue is even more severe in deep learning applications, where computing the distance between two mini-batch probability measures is repeated several times. This nested loop has been one of the main challenges that prevent the usage of sliced Wasserstein distances based on good projections in practice. To address this challenge, we propose to utilize the learning-to-optimize technique or amortized optimization to predict the informative direction of any given two mini-batch probability measures. To the best of our knowledge, this is the first work that bridges amortized optimization and sliced Wasserstein generative models. In particular, we derive linear amortized models, generalized linear amortized models, and non-linear amortized models which are corresponding to three types of novel mini-batch losses, named amortized sliced Wasserstein. We demonstrate the favorable performance of the proposed sliced losses in deep generative modeling on standard benchmark datasets.
Classical mass inflation versus semiclassical inner horizon inflation

We analyse the geometry of a spherically symmetric black hole with an inner and outer apparent horizon which is perturbed by spherical null shells of matter. On a classical level we observe that the mass inﬂation instability is triggered, resulting in a growth of curvature and an inward displacement of the inner horizon. We study in detail the inner structure of the mass-inﬂated region and compare it with previous results obtained for the case in which the perturbing matter content has a continuous distribution. We then perform an approximate calculation of the renormalised stress-energy tensor of a quantum ﬁeld in the vicinity of the inner horizon, and analyse the semiclassical backreaction on this region of the geometry. We ﬁnd that the classical tendency for this horizon to move inward due to mass inﬂation is challenged and potentially overcome by a semiclassical tendency for it to inﬂate outward.
Eﬃciency of higher-order algorithms for minimizing general composite optimization

Composite minimization involves a collection of functions which are aggregated in a nonsmooth manner. It covers, as a particular case, optimization problems with functional constraints, minimization of max-type functions, and simple composite minimization problems, where the objective function has a nonsmooth component. We design a higher-order majorization algorithmic framework for fully composite problems (possibly nonconvex). Our framework replaces each com-ponent with a higher-order surrogate such that the corresponding error function has a higher-order Lipschitz continuous derivative. We present convergence guarantees for our method for composite optimization problems with (non)convex and (non)smooth objective function. In particular, we prove stationary point convergence guarantees for general nonconvex (possibly nonsmooth) problems and under Kurdyka-Lojasiewicz (KL) property of the objective function we derive improved rates depending on the KL parameter. For convex (possibly nonsmooth) problems we also provide sublinear convergence rates.
Gating-Induced Mott Transition in NiS$_2$

NiS$_2$ has been widely regarded as a model system to study the bandwidth-controlled Mott transition, as enabled by isovalent Se chemical substitution on the S sites. Motivated by advances in electrolyte gating, we theoretically investigate the filling-controlled Mott transition induced by gating, which has the advantage of avoiding dopant disorder and stoichiometric changes. We use combined Density Functional Theory (DFT) and Dynamical Mean Field Theory (DMFT) to study such a filling-controlled transition and compare it with the case of bandwidth control. We draw a temperature-filling phase diagram and find that the Mott-insulator to metal transition occurs with modest added electron concentrations, well within the capabilities of existing electrolyte gating experiments. We find that there is significant incoherent weight at the Fermi level in the metallic phase when the transition is induced by gating. In contrast, the spectral weight remains rather coherent in the case of the bandwidth-controlled transition.
A Robust and Statistically Efficient Maximum-Likelihood Method for DOA Estimation Using Sparse Linear Arrays

The recent trend of research on direction-of-arrival estimation is to localize more uncorrelated sources than sensors by using a proper sparse linear array (SLA) at the cost of robustness to source correlations even in the regime of less sources than sensors. This article is devoted to proposing one algorithm that can simultaneously tackle two challenging scenarios: 1) more uncorrelated sources than sensors and 2) highly correlated or coherent sources. In order to statistically efficiently localize a maximal number of uncorrelated sources, we use the stochastic maximum likelihood (SML) criterion and propose an effective algorithm based on elegant problem reformulations and the alternating direction method of multipliers (ADMM). Moreover, we prove that the SML is robust to source correlations under mild conditions, though it is derived under the assumption of uncorrelated sources. The proposed algorithm is usable for arbitrary SLAs (e.g., minimum redundancy arrays, nested arrays, and coprime arrays) and is named as maximum-likelihood estimation via sequential ADMM (MESA). Extensive numerical results are provided that collaborate our analysis and demonstrate the statistical efficiency and robustness of MESA against state-of-the-art algorithms. Our results also imply that it is possible to localize more sources than sensors in the presence of high source correlations.
Preprocessing Reward Functions for Interpretability

In many real-world applications, the reward function is too complex to be manually specified. In such cases, reward functions must instead be learned from human feedback. Since the learned reward may fail to represent user preferences, it is important to be able to validate the learned reward function prior to deployment. One promising approach is to apply interpretability tools to the reward function to spot potential deviations from the user's intention. Existing work has applied general-purpose interpretability tools to understand learned reward functions. We propose exploiting the intrinsic structure of reward functions by first preprocessing them into simpler but equivalent reward functions, which are then visualized. We introduce a general framework for such reward preprocessing and propose concrete preprocessing algorithms. Our empirical evaluation shows that preprocessed rewards are often significantly easier to understand than the original reward.
A Dichotomy in Consistent Query Answering for Primary Keys and Unary Foreign Keys

Since 2005, significant progress has been made in the problem of Consistent Query Answering (CQA) with respect to primary keys. In this problem, the input is a database instance that may violate one or more primary key constraints. A repair is defined as a maximal subinstance that satisfies all primary keys. Given a Boolean query q, the question then is whether q holds true in every repair. So far, theoretical research in this field has not addressed the combination of primary key and foreign key constraints, despite the importance of referential integrity in database systems. This paper addresses the problem of CQA with respect to both primary keys and foreign keys. In this setting, it is natural to adopt the notion of symmetric-difference repairs, because foreign keys can be repaired by inserting new tuples. We consider the case where foreign keys are unary, and queries are conjunctive queries without self-joins. In this setting, we characterize the boundary between those CQA problems that admit a consistent first-order rewriting, and those that do not.
A Comparative Survey of Deep Active Learning

While deep learning (DL) is data-hungry and usually relies on extensive labeled data to deliver good performance, Active Learning (AL) reduces labeling costs by selecting a small proportion of samples from unlabeled data for labeling and training. Therefore, Deep Active Learning (DAL) has risen as a feasible solution for maximizing model performance under a limited labeling cost/budget in recent years. Although abundant methods of DAL have been developed and various literature reviews conducted, the performance evaluation of DAL methods under fair comparison settings is not yet available. Our work intends to fill this gap. In this work, We construct a DAL toolkit, DeepAL+, by re-implementing 19 highly-cited DAL methods. We survey and categorize DAL-related works and construct comparative experiments across frequently used datasets and DAL algorithms. Additionally, we explore some factors (e.g., batch size, number of epochs in the training process) that influence the efficacy of DAL, which provides better references for researchers to design their DAL experiments or carry out DAL-related applications.
Opportunistic Qualitative Planning in Stochastic Systems with Preferences over Temporal Logic Objectives

—Preferences play a key role in determining what goals/constraints to satisfy when not all constraints can be satisﬁed simultaneously. In this work, we study preference- based planning in a stochastic system modeled as a Markov decision process, subject to a possible incomplete preference over temporally extended goals. Our contributions are three folds: First, we introduce a preference language to specify preferences over temporally extended goals. Second, we deﬁne a novel automata-theoretic model to represent the preorder induced by given preference relation. The automata representation of preferences enables us to develop a preference- based planning algorithm for stochastic systems. Finally, we show how to synthesize opportunistic strategies that achieves an outcome that improves upon the current satisﬁable outcome, with positive probability or with probability one, in a stochastic system. We illustrate our solution approaches using a robot motion planning example.
On extremes of random clusters and marked renewal cluster processes

Abstract This article describes the limiting distribution of the extremes of observations that arrive in clusters. We start by studying the tail behaviour of an individual cluster, and then we apply the developed theory to determine the limiting distribution of $\max\{X_j\,:\, j=0,\ldots, K(t)\}$ , where K(t) is the number of independent and identically distributed observations $(X_j)$ arriving up to the time t according to a general marked renewal cluster process. The results are illustrated in the context of some commonly used Poisson cluster models such as the marked Hawkes process.
Personality and Strategy in Agriculture

Our fundamental aim in this study was to determine whether locus of control influences producers’ strategies and business performance. If traits such as locus of control do influence producers’ behaviour in terms of choice of farm strategy, then extension programs promoting improved farm business management techniques may need to incorporate educational elements to influence producers’ perceptions of control. The data used in the study were obtained from a mail questionnaire that was distributed to primary producers in the wheat-sheep zone of south-east Australia during the summer of 2001. We identified statistically significant relationships among producers’ locus of control, their farm strategies and farm business performance. In summary we found that producers with a strongly internal locus of control were More likely than other producers to adopt a prospective farm strategy. • • • • Less likely than other producers to experience low financial performance. Conversely we found that producers with a strongly external locus of control were: More likely than other producers to adopt a defensive farm strategy. More likely than other producers to experience low financial performance. These findings raise two key implications for the design of extension programs. The first key implication is that those producers most in need of upgrading their business skills may be the least likely to take advantage of extension programs offering such training. The second key implication is that the inclusion of activities aimed at increasing the internality of producers’ locus of control is likely to increase the adoption of new skills and ideas among primary producers.
Effectively leveraging Multi-modal Features for Movie Genre Classification

Movie genre classification has been widely studied in recent years due to its various applications in video editing, summarization, and recommendation. Prior work has typically addressed this task by predicting genres based solely on the visual content. As a result, predictions from these methods often perform poorly for genres such as documentary or musical, since non-visual modalities like audio or language play an important role in correctly classifying these genres. In addition, the analysis of long videos at frame level is always associated with high computational cost and makes the prediction less efficient. To address these two issues, we propose a Multi-Modal approach leveraging shot information, MMShot, to classify video genres in an efficient and effective way. We evaluate our method on MovieNet and Condensed Movies for genre classification, achieving 17% ~ 21% improvement on mean Average Precision (mAP) over the state-of-the-art. Extensive experiments are conducted to demonstrate the ability of MMShot for long video analysis and uncover the correlations between genres and multiple movie elements. We also demonstrate our approach's ability to generalize by evaluating the scene boundary detection task, achieving 1.1% improvement on Average Precision (AP) over the state-of-the-art.
leT and the Quality of Teaching: Some Hungarian Results of the OEeD leT Project

The educational research institute of OECD, CERI, commissioned an extensive study to investigate if and how ICT resulted in changes in the quality of learning. Between 1999 and 2002, a network of National Research Experts was set up who co-ordinate research in their countries and discuss the centrally developed tests, questionnaires and study outlines that were intended to capture similarities and differences of educational ICT policy in the countries concerned. The primary goal of the studies reported here was to understand how ICT can relate to educational innovation. The present paper discusses results related to teacher competence, performance and motivation in the use of ICT in the 'model schools' of Hungary that proved to be especially effective in ICT use. Diffusion process. Who were the early/late adopters of both the innovation and ICT? What incentives existed for adoption? Which organisational structures or processes were particularly important facilitators of change or barriers to it? Role of leadership. Who directed the innovation? Did the role or manner of leadership change over the adoption period? Importance of staff training: methods of achieving staff competence in using ICT and integrating it into the curriculum.
Analysis of calcium dynamics for dim-light responses in rod and cone photoreceptors

Rod and cone photoreceptors in the retina of vertebrate eyes are fundamental sensory neurons underlying vision. They use a sophisticated signal transduction pathway consisting of a series of biochemical processes to convert the absorption of light into an electrical current response. Several of these processes are modulated by feedback that depends on the intracellular Ca2+ concentration. In this work we use a representative phototransduction model to study how changing the Ca2+ kinetics by fast buffering affects sensitivity and dynamics of the light response in mouse rod and cone photoreceptors. We derive analytic results for dim-light stimulations that provide quantitative and conceptual insight. We show that flash responses are monophasic with low buffering, and the change in the Ca2+ concentration occurs in proportion to the current. If the amount of fast buffering is increased, the Ca2+ kinetics becomes slowed down and delayed with respect to the current, and biphasic responses emerge (damped oscillations). This shows that a biphasic response is not necessarily a manifestation of slow buffering reactions. A phase space analysis shows that the emergence of biphasic responses depends on the ratio between the effective rate μca that controls the Ca2+ kinetics, and the dark turnover rate of cyclic GMP βd. We further investigate how the light response is altered by modifying the extracellular Ca2+ concentration. In summary, we provide a comprehensive quantitative analysis that precisely links the dynamics of Ca2+ concentration to the observed current response.
A nuclear receptor facilitates differentiation of human PSCs into more mature hepatocytes

The capacity to generate functional hepatocytes from renewable human pluripotent stem cells (hPSCs) could address limited supplies of primary human hepatocytes. However, hepatocytes differentiated from hPSCs in vitro are functionally immature. To understand mechanisms regulating maturation of in vitro derived hepatocytes, we developed a 3D spheroid differentiation system and compared gene regulatory elements in uncultured human primary hepatocytes with those in hepatocytes that were differentiated in 2D or 3D conditions from human PSCs by RNA-seq, ATAC-seq, and H3K27Ac ChIP-seq. Three-dimensional differentiation improved enhancer activity and expression of transcription factor ONECUT1, but was insufficient to upregulate human-specific mature hepatocytes marker gene CYP3A4 or super-enhancer regulated transcription factor gene NFIC. Regulome comparisons showed reduced enrichment of thyroid receptor THRB motifs in accessible chromatin and in active enhancers without reduced transcription of THRB, suggesting the regulation at the level of THRB ligands in PSC-differentiated hepatocytes. Addition of thyroid hormone T3 to the PSC-differentiated hepatocytes increased CYP3A4 expression. T3 increased binding of THRB to the CYP3A4 proximal enhancer and restored the super-enhancer status and gene expression of NFIC and reduced expression of AFP. The resultant hPSC-hepatocytes showed gene expression, epigenetic status and super-enhancer landscape closer to primary hepatocytes and activated regulatory regions including non-coding SNPs associated with liver-related diseases. Transplanting the 3D PSC-hepatocytes into immunocompromised mice resulted in engraftment of human hepatocytes in the mouse liver parenchyma without disrupting normal liver histology at 6 months after transplantation. This work provides insights into the functions of nuclear receptor THRB and highlights the importance of the environmental factors-nuclear receptors axis in regulating maturation of human PSC-differentiated cell types.
SPACA6 structure reveals a conserved superfamily of gamete fusion-associated proteins

SPACA6 is a sperm-expressed surface protein that is critical for gamete fusion during mammalian sexual reproduction. Despite this fundamental role, little is known about how SPACA6 specifically functions. We elucidated the crystal structure of SPACA6 at 2.2-Å resolution, revealing a two-domain protein containing a four-helix bundle and Ig-like β-sandwich connected via a quasi-flexible linker. Based on the structural analysis, we propose SPACA6 is a founding member of a superfamily of gamete fusion-associated proteins, herein dubbed the IST superfamily. The IST superfamily is defined structurally by its distorted four-helix bundle and a pair of disulfide-bonded CXXC motifs. A structure-based search of the AlphaFold human proteome identified more protein members to this superfamily; remarkably, many of these proteins are linked to gamete fusion. The SPACA6 structure and its connection to other IST-superfamily members provide a missing link in our knowledge of mammalian gamete fusion. Significance Statement SPACA6 is a human sperm protein vital for the fusion of gametes, though its exact function remains a mystery. We present the first solved structure of SPACA6: a two-domain fold comprised of an Ig-like domain and a distorted four-helix bundle. Dali searches of the PDB and AlphaFold reveal a family of structurally related proteins, several of which are also known to play a role in gamete fusion; as such, SPACA6 is a founding member of a conserved protein superfamily, dubbed the IST superfamily. Evolutionary analysis to ascertain functionally relevant structural elements in SPACA6 show a conservation of flexibility between the two domains and several conserved surfaces that could function as protein-protein interfaces.
Efficient rescue of a newly classified Ebinur lake orthobunyavirus with GFP reporter and its application in rapid antiviral screening

Orthobunyaviruses have been reported to cause severe diseases in humans or animals, posing a threat to human health and social economy. Ebinur lake virus (EBIV) is a newly classified orthobunyavirus, which needs further intensive study and therapies to cope with its potential infection risk to human and animals. Here, through the reverse genetics system, the recombinant EBIV of wild type (rEBIV/WT) and NP-conjugated-eGFP (rEBIV/eGFP/S) were rescued for the application of the rapid antiviral drug screening. The eGFP fluorescence signal of the rEBIV/eGFP/S was stable in the process of successive passage in BHK-21 cells (over 10 passages) and this recombinant virus could replicate in various cell lines. Compared to the wild type EBIV, the rEBIV/eGFP/S caused the smaller plaques and its peak titers were lower, suggesting attenuation due to the eGFP insertion. Through the high-content screening (HCS) system, ribavirin showed an inhibitory effect on the rEBIV/eGFP/S with an EC50 of 21.91 μM, while favipiravir did not inhibit, even at high concentrations. In addition, five of ninety-six natural compounds had antiviral against EBIV. The robust reverse genetics system for EBIV will facilitate investigation into replication and assembly mechanisms and assist drug and vaccine development.