cssi/SciSciGPT-SciSciNet huggingface dataset:
Introducing Representations of Facial Affect in Automated Multimodal Deception Detection

Automated deception detection systems can enhance health, justice, and security in society by helping humans detect deceivers in high-stakes situations across medical and legal domains, among others. Existing machine learning approaches for deception detection have not leveraged dimensional representations of facial affect: valence and arousal. This paper presents a novel analysis of the discriminative power of facial affect for automated deception detection, along with interpretable features from visual, vocal, and verbal modalities. We used a video dataset of people communicating truthfully or deceptively in real-world, high-stakes courtroom situations. We leveraged recent advances in automated emotion recognition in-the-wild by implementing a state-of-the-art deep neural network trained on the Aff-Wild database to extract continuous representations of facial valence and facial arousal from speakers. We experimented with unimodal Support Vector Machines (SVM) and SVM-based multimodal fusion methods to identify effective features, modalities, and modeling approaches for detecting deception. Unimodal models trained on facial affect achieved an AUC of 80%, and facial affect contributed towards the highest-performing multimodal approach (adaptive boosting) that achieved an AUC of 91% when tested on speakers who were not part of training sets. This approach achieved a higher AUC than existing automated machine learning approaches that used interpretable visual, vocal, and verbal features to detect deception in this dataset, but did not use facial affect. Across all videos, deceptive and truthful speakers exhibited significant differences in facial valence and facial arousal, contributing computational support to existing psychological theories on relationships between affect and deception. The demonstrated importance of facial affect in our models informs and motivates the future development of automated, affect-aware machine learning approaches for modeling and detecting deception and other social behaviors in-the-wild.
Using Deep Space Climate Observatory Measurements to Study the Earth as an Exoplanet

Even though it was not designed as an exoplanetary research mission, the Deep Space Climate Observatory (DSCOVR) has been opportunistically used for a novel experiment, in which Earth serves as a proxy exoplanet. More than two years of DSCOVR Earth images were employed to produce time series of multi-wavelength, single-point light sources, in order to extract information on planetary rotation, cloud patterns, surface type, and orbit around the Sun. In what follows, we assume that these properties of the Earth are unknown, and instead attempt to derive them from first principles. These conclusions are then compared with known data about our planet. We also used the DSCOVR data to simulate phase angle changes, as well as the minimum data collection rate needed to determine the rotation period of an exoplanet. This innovative method of using the time evolution of a multi-wavelength, reflected single-point light source, can be deployed for retrieving a range of intrinsic properties of an exoplanet around a distant star.
Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human Reconstruction

We propose Geo-PIFu, a method to recover a 3D mesh from a monocular color image of a clothed person. Our method is based on a deep implicit function-based representation to learn latent voxel features using a structure-aware 3D U-Net, to constrain the model in two ways: first, to resolve feature ambiguities in query point encoding, second, to serve as a coarse human shape proxy to regularize the high-resolution mesh and encourage global shape regularity. We show that, by both encoding query points and constraining global shape using latent voxel features, the reconstruction we obtain for clothed human meshes exhibits less shape distortion and improved surface details compared to competing methods. We evaluate Geo-PIFu on a recent human mesh public dataset that is $10 \times$ larger than the private commercial dataset used in PIFu and previous derivative work. On average, we exceed the state of the art by $42.7\%$ reduction in Chamfer and Point-to-Surface Distances, and $19.4\%$ reduction in normal estimation errors.
Using secondary Upsilon invariants to rule out stable equivalence of knot complexes

Two Heegaard Floer knot complexes are called stably equivalent if an acyclic complex can be added to each complex to make them filtered chain homotopy equivalent. Hom showed that if two knots are concordant, then their knot complexes are stably equivalent. Invariants of stable equivalence include the concordance invariants $\tau$, $\varepsilon$, and $\Upsilon$. Feller and Krcatovich gave a relationship between the Upsilon invariants of torus knots. We use secondary Upsilon invariants defined by Kim and Livingston to show that these relations do not extend to stable equivalence.
SLE and Virasoro Representations: Fusion

We continue the study of null-vector equations in relation with partition functions of (systems of) Schramm–Loewner Evolutions (SLEs) by considering the question of fusion. Starting from n commuting SLEs seeded at distinct points, the partition function satisfies n null-vector equations (at level 2). We show how to obtain higher level null-vector equations by coalescing the seeds one by one. As an example, we extend Schramm’s formula (for the position of a marked bulk point relatively to a chordal SLE trace) to an arbitrary number of SLE strands. The argument combines input from representation theory—the study of Verma modules for the Virasoro algebra—with regularity estimates, themselves based on hypoellipticity and stochastic flow arguments.
Optimization and abstraction: a synergistic approach for analyzing neural network robustness

In recent years, the notion of local robustness (or robustness for short) has emerged as a desirable property of deep neural networks. Intuitively, robustness means that small perturbations to an input do not cause the network to perform misclassifications. In this paper, we present a novel algorithm for verifying robustness properties of neural networks. Our method synergistically combines gradient-based optimization methods for counterexample search with abstraction-based proof search to obtain a sound and (δ -)complete decision procedure. Our method also employs a data-driven approach to learn a verification policy that guides abstract interpretation during proof search. We have implemented the proposed approach in a tool called Charon and experimentally evaluated it on hundreds of benchmarks. Our experiments show that the proposed approach significantly outperforms three state-of-the-art tools, namely AI^2, Reluplex, and Reluval.
Cardinal interpolation with general multiquadrics: convergence rates

This article pertains to interpolation of Sobolev functions at shrinking lattices $h\mathbb {Z}^{d}$ from L p shift-invariant spaces associated with cardinal functions related to general multiquadrics, ϕ α, c (x) := (|x|2 + c 2) α . The relation between the shift-invariant spaces generated by the cardinal functions and those generated by the multiquadrics themselves is considered. Additionally, L p error estimates in terms of the dilation h are considered for the associated cardinal interpolation scheme. This analysis expands the range of α values which were previously known to give such convergence rates (i.e. O(h k ) for functions with derivatives of order up to k in L p , $1<p<\infty $ ). Additionally, the analysis here demonstrates that some known best approximation rates for multiquadric approximation are obtained by their cardinal interpolants.
New Constraints on Gliese 876—Exemplar of Mean-motion Resonance

Gliese 876 harbors one of the most dynamically rich and well-studied exoplanetary systems. The nearby M4V dwarf hosts four known planets, the outer three of which are trapped in a Laplace mean-motion resonance. A thorough characterization of the complex resonant perturbations exhibited by the orbiting planets, and the chaotic dynamics therein, is key to a complete picture of the system's formation and evolutionary history. Here we present a reanalysis of the system using six years of new radial velocity (RV) data from four instruments. This new data augments and more than doubles the size of the decades-long collection of existing velocity measurements. We provide updated estimates of the system parameters by employing a computationally efficient Wisdom-Holman N-body symplectic integrator, coupled with a Gaussian Process (GP) regression model to account for correlated stellar noise. Experiments with synthetic RV data show that the dynamical characterization of the system can differ depending on whether a white noise or correlated noise model is adopted. Despite there being a region of stability for an additional planet in the resonant chain, we find no evidence for one. Our new parameter estimates place the system even deeper into resonance than previously thought and suggest that the system might be in a low energy, quasi-regular double apsidal corotation resonance. This result and others will be used in a subsequent study on the primordial migration processes responsible for the formation of the resonant chain.
Long-period Giant Companions to Three Compact, Multiplanet Systems

Understanding the relationship between long-period giant planets and multiple smaller short-period planets is critical for formulating a complete picture of planet formation. This work characterizes three such systems. We present Kepler-65, a system with an eccentric (e=0.28+/-0.07) giant planet companion discovered via radial velocities (RVs) exterior to a compact, multiply-transiting system of sub-Neptune planets. We also use precision RVs to improve mass and radius constraints on two other systems with similar architectures, Kepler-25 and Kepler-68. In Kepler-68 we propose a second exterior giant planet candidate. Finally, we consider the implications of these systems for planet formation models, particularly that the moderate eccentricity in Kepler-65's exterior giant planet did not disrupt its inner system.
Non-Trivial Checks of Novel Consistency Relations

Single-field perturbations satisfy an infinite number of consistency relations constraining the squeezed limit of correlation functions at each order in the soft momentum. These can be understood as Ward identities for an infinite set of residual global symmetries, or equivalently as Slavnov-Taylor identities for spatial diffeomorphisms. In this paper, we perform a number of novel, non-trivial checks of the identities in the context of single field inflationary models with arbitrary sound speed. We focus for concreteness on identities involving 3-point functions with a soft external mode, and consider all possible scalar and tensor combinations for the hard-momentum modes. In all these cases, we check the consistency relations up to and including cubic order in the soft momentum. For this purpose, we compute for the first time the 3-point functions involving 2 scalars and 1 tensor, as well as 2 tensors and 1 scalar, for arbitrary sound speed.
Cognitive Connectivity Resilience in Multi-Layer Remotely Deployed Mobile Internet of Things

Enabling the Internet of things in remote areas without traditional communication infrastructure requires a multi-layer network architecture. The devices in the overlay network are required to provide coverage to the underlay devices as well as to remain connected to other overlay devices. The coordination, planning, and design of such two-layer heterogeneous networks is an important problem to address. Moreover, the mobility of the nodes and their vulnerability to adversaries pose new challenges to the connectivity. For instance, the connectivity of devices can be affected by changes in the network, e.g., the mobility of the underlay devices or the unavailability of overlay devices due to failure or adversarial attacks. To this end, this work proposes a feedback based adaptive, self-configurable, and resilient framework for the overlay network that cognitively adapts to the changes in the network to provide reliable connectivity between spatially dispersed smart devices. Our results show that if sufficient overlay devices are available, the framework leads to a connected configuration that ensures a high coverage of the mobile underlay network. Moreover, the framework can actively reconfigure itself in the event of varying levels of device failure.
Efficiency of particle trapping in the outer regions of protoplanetary disks

We investigate the strength of axisymmetric local pressure maxima (zonal flows) in the outer regions of protoplanetary disks, where ambipolar diffusion reduces turbulent stresses driven by the magnetorotational instability. Using local numerical simulations we show that in the absence of net vertical magnetic fields, the strength of turbulence in the ambipolar dominated region of the disk is low and any zonal flows that are present are weak. For net fields strong enough to yield observed protostellar accretion rates, however, zonal flows with a density amplitude of 10%-20% are formed. These strengths are comparable to those seen in simulations of ideal MHD disk turbulence. We investigate whether these zonal flows are able to reverse the inward radial drift of solids, leading to prolonged and enhanced concentration as a prelude to planetesimal formation. For commonly assumed mean surface density profiles (surface density Σ∝r –1/2 or steeper) we find that the predicted perturbations to the background disk profile do not correspond to local pressure maxima. This is a consequence of radial width of the simulated zonal flows, which is larger than was assumed in prior analytic models of particle trapping. These larger scale flows would only trap particles for higher amplitude fluctuations than observed. We conclude that zonal flows are likely to be present in the outer regions of protoplanetary disks and are potentially large enough to be observable, but are unlikely to lead to strong particle trapping.
Ensuring Fairness Beyond the Training Data

We initiate the study of fair classifiers that are robust to perturbations in the training distribution. Despite recent progress, the literature on fairness has largely ignored the design of fair and robust classifiers. In this work, we develop classifiers that are fair not only with respect to the training distribution, but also for a class of distributions that are weighted perturbations of the training samples. We formulate a min-max objective function whose goal is to minimize a distributionally robust training loss, and at the same time, find a classifier that is fair with respect to a class of distributions. We first reduce this problem to finding a fair classifier that is robust with respect to the class of distributions. Based on online learning algorithm, we develop an iterative algorithm that provably converges to such a fair and robust solution. Experiments on standard machine learning fairness datasets suggest that, compared to the state-of-the-art fair classifiers, our classifier retains fairness guarantees and test accuracy for a large class of perturbations on the test set. Furthermore, our experiments show that there is an inherent trade-off between fairness robustness and accuracy of such classifiers.
Topology of nuclear reaction networks of interest for astrophysics

Our understanding of the observed elemental abundance in the universe, stemming from nuclear reactions during the big bang or from nucleosynthesis within stellar environments, requires theoretical analyses based on multidimensional nucleosynthesis calculations involving hundreds of nuclei connected via thousands of nuclear processes. Up to recently, full nucleosynthesis network calculations remained computationally expensive and prohibitive. A recent publication by a Chinese group led by YuGang Ma [1] has proved that advanced computational algorithms developed in the last decade for the purpose of studying complex networks are paving the way to finally accomplish this ultimate goal of nuclear astrophysics.
Finding the Homology of Decision Boundaries with Active Learning

Accurately and efficiently characterizing the decision boundary of classifiers is important for problems related to model selection and meta-learning. Inspired by topological data analysis, the characterization of decision boundaries using their homology has recently emerged as a general and powerful tool. In this paper, we propose an active learning algorithm to recover the homology of decision boundaries. Our algorithm sequentially and adaptively selects which samples it requires the labels of. We theoretically analyze the proposed framework and show that the query complexity of our active learning algorithm depends naturally on the intrinsic complexity of the underlying manifold. We demonstrate the effectiveness of our framework in selecting best-performing machine learning models for datasets just using their respective homological summaries. Experiments on several standard datasets show the sample complexity improvement in recovering the homology and demonstrate the practical utility of the framework for model selection. Source code for our algorithms and experimental results is available at this https URL.
Twisted Alexander polynomials and representation shifts

For any knot, the following are equivalent. (1) The infinite cyclic cover has uncountably many finite covers; (2) there exists a finite-image representation of the knot group for which the twisted Alexander polynomial vanishes; (3) the knot group admits a finite-image representation such that the image of the fundamental group of an incompressible Seifert surface is a proper subgroup of the image of the commutator subgroup of the knot group.
Examples of non-rigid CAT(0) groups from the category of knot groups

The CAT(0) condition is a geometric notion of nonpositive curvature similar to the definition of Gromov i–hyperbolicity. A proper geodesic space X is called CAT(0) if it has the property that geodesic triangles in X are “no fatter” than geodesic triangles in Euclidean space (a precise definition is given by M R Bridson and A Haefliger in [4, Chapter II.1]). The visual or ideal boundary of X , denoted @X , is the collection of endpoints of geodesic rays emanating from a chosen basepoint endowed with the cone topology. It is well-known that @X is well-defined and independent of choice of basepoint and that X [ @X is a Z–set compactification for X . A group G is called CAT(0) if it acts geometrically (ie properly discontinuously and cocompactly by isometries) on some CAT(0) space X . In this setup we call X a CAT(0) G –space and @X a CAT(0) boundary of G . We say that a CAT(0) group G is rigid if it has only one topologically distinct boundary.
Structured variable selection in support vector machines

When applying the support vector machine (SVM) to high- dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The lasso and other variable selection techniques have been successfully used in the SVM to perform automatic variable selection. In some problems, there is a natural hierarchical structure among the variables. Thus, in or- der to have an interpretable SVM classifier, it is important to respect the heredity principle when enforcing the sparsity in the SVM. Many variable selection methods, however, do not respect the heredity principle. In this paper we enforce both sparsity and the heredity principle in the SVM by using the so-called structured variable selection (SVS) framework originally proposed in (20). We minimize the empirical hinge loss under a set of linear inequality constraints and a lasso-type penalty. The solution always obeys the desired heredity principle and enjoys sparsity. The new SVM classi- fier can be efficiently fitted, because the optimization problem is a linear program. Another contribution of this work is to present a nonparametric extension of the SVS framework, and we propose nonparametric heredity SVMs. Simulated and real data are used to illustrate the merits of the proposed method.
Application of Bruggeman and Maxwell Garnett homogenization formalisms to random composite materials containing dimers

The homogenization of a composite material comprising three isotropic dielectric materials was investigated. The component materials were randomly distributed as spherical particles, with the particles of two of the component materials being coupled to form dimers. The Bruggeman and Maxwell Garnett formalisms were developed to estimate the permittivity dyadic of the homogenized composite material (HCM), under the quasi-electrostatic approximation. Both randomly oriented and identically oriented dimers were accommodated; in the former case the HCM is isotropic, whereas in the latter case the HCM is uniaxial. Representative numerical results for composite materials containing dielectric–dielectric dimers demonstrate close agreement between the estimates delivered by the Bruggeman and Maxwell Garnett formalisms. For composite materials containing metal–dielectric dimers and metal–metal dimers with moderate degrees of dissipation, the estimates of the two formalisms are in broad agreement, provided that the d...
On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses

Investment in brighter sources and larger detectors has resulted in an explosive rise in the data collected at synchrotron facilities. Currently, human experts extract scientific information from these data, but they cannot keep pace with the rate of data collection. Here, we present three on-the-fly approaches—attribute extraction, nearest-neighbor distance, and cluster analysis—to quickly segment x-ray diffraction (XRD) data into groups with similar XRD profiles. An expert can then analyze representative spectra from each group in detail with much reduced time, but without loss of scientific insights. On-the-fly segmentation would, therefore, result in accelerated scientific productivity.
An Extension to the Theory of Controlled Lagrangians Using the Helmholtz Conditions

The Helmholtz conditions are necessary and sufficient conditions for a system of second-order differential equations to be variational, that is, equivalent to a system of Euler–Lagrange equations for a regular Lagrangian. On the other hand, matching conditions are sufficient conditions for a class of controlled systems to be variational for a Lagrangian function of a prescribed type, known as the controlled Lagrangian. Using the Helmholtz conditions, we are able to recover the matching conditions from Bloch et al. (IEEE Trans Autom Control 45(12):2253–2270, 2000). Furthermore, we can derive new matching conditions for a particular class of mechanical systems. It turns out that for this class of systems we obtain feedback controls that only depend on the configuration variables. We test this new strategy for the inverted pendulum on a cart and for the inverted pendulum on an incline.
The Lyman Continuum Polarization Rise in the QSO PG 1222+228

Some QSOs show an abrupt, strong rise in polarization at rest wavelength ~750 A. If this arises in the atmosphere of an accretion disk around a supermassive black hole, it may have diagnostic value. In PG 1222+228, the polarization rise occurs at the wavelength of a sharp drop in flux. We examine and reject interpretations of this feature involving a high-velocity outflow. The observations agree with a model involving several intervening Lyman limit systems, two of which happen to coincide with the Lyman continuum polarization rise. After correction for the Lyman limit absorption, the continuum shortward of 912 A is consistent with a typical power-law slope, α ≈ -1.8. This violates the apparent pattern for the Lyman limit polarization rises to occur only in "candidate Lyman edge QSOs." The corrected, polarized flux rises strongly at the wavelength of the polarization rise, resembling the case of PG 1630+377. The rise in polarized flux places especially stringent requirements on models.
Retinal OCT Denoising with Pseudo-Multimodal Fusion Network

Optical coherence tomography (OCT) is a prevalent imaging technique for retina. However, it is affected by multiplicative speckle noise that can degrade the visibility of essential anatomical structures, including blood vessels and tissue layers. Although averaging repeated B-scan frames can significantly improve the signal-to-noise-ratio (SNR), this requires longer acquisition time, which can introduce motion artifacts and cause discomfort to patients. In this study, we propose a learning-based method that exploits information from the single-frame noisy B-scan and a pseudo-modality that is created with the aid of the self-fusion method. The pseudo-modality provides good SNR for layers that are barely perceptible in the noisy B-scan but can over-smooth fine features such as small vessels. By using a fusion network, desired features from each modality can be combined, and the weight of their contribution is adjustable. Evaluated by intensity-based and structural metrics, the result shows that our method can effectively suppress the speckle noise and enhance the contrast between retina layers while the overall structure and small blood vessels are preserved. Compared to the single modality network, our method improves the structural similarity with low noise B-scan from \(0.559\pm 0.033\) to \(0.576\pm 0.031\).
How well do platelets prevent bleeding

Prophylactic platelet transfusions are used to reduce the risk of spontaneous bleeding in patients with treatment- or disease-related severe thrombocytopenia. A prophylactic platelet-transfusion threshold of <10 × 103/µL has been shown to be safe in stable hematology/oncology patients. A higher threshold and/or larger or more frequent platelet doses may be appropriate for patients with clinical features associated with an increased risk of bleeding such as high fevers, sepsis, disseminated intravascular coagulation, anticoagulation therapy, or splenomegaly. Unique factors in the outpatient setting may support the use of a higher platelet-transfusion threshold and/or dose of platelets. A prophylactic platelet-transfusion strategy has been shown to be associated with a lower risk of bleeding compared with no prophylaxis in adult patients receiving chemotherapy but not for autologous transplant recipients. Despite the use of prophylactic platelet transfusions, a high incidence (50% to 70%) of spontaneous bleeding remains. Using a higher threshold or larger doses of platelets does not change this risk. New approaches to reduce the risk of spontaneous bleeding, including antifibrinolytic therapy, are currently under study.
Learning Exceptions in Phonological Alternations.

The present study explores learning phonological alternations that contain exceptions. Participants were exposed to a back/round vowel harmony pattern in which a regular suffix obeyed a vowel harmo...
Multivariate Alexander quandles, II. The involutory medial quandle of a link (corrected)

Joyce showed that for a classical knot K, the involutory medial quandle IMQ(K) is isomorphic to the core quandle of the homology group H1(X2), where X2 is the cyclic double cover of &#x1d54a;3, branched ov...
Asymptotic dimension of minor-closed families and beyond

The asymptotic dimension of metric spaces is an important notion in geometric group theory introduced by Gromov. The metric spaces considered in this paper are the ones whose underlying spaces are the vertex-sets of graphs and whose metrics are the distance functions in graphs. A standard compactness argument shows that it suffices to consider the asymptotic dimension of classes of finite graphs. In this paper we prove that the asymptotic dimension of any proper minor-closed family, any class of graphs of bounded tree-width, and any class of graphs of bounded layered tree-width are at most 2, 1, and 2, respectively. The first result solves a question of Fujiwara and Papasoglu; the second and third results solve a number of questions of Bonamy, Bousquet, Esperet, Groenland, Pirot and Scott. These bounds for asymptotic dimension are optimal and improve a number of results in the literature. Our proofs can be transformed into linear or quadratic time algorithms for finding coverings witnessing the asymptotic dimension which is equivalent to finding weak diameter colorings for graphs. The key ingredient of our proof is a unified machinery about the asymptotic dimension of classes of graphs that have tree-decompositions of bounded adhesion over hereditary classes with known asymptotic dimension, which might be of independent interest.
Duality defect of the monster CFT

We show that the fermionization of the Monster CFT with respect to $\mathbb{Z}_{2A}$ is the tensor product of a free fermion and the Baby Monster CFT. The chiral fermion parity of the free fermion implies that the Monster CFT is self-dual under the $\mathbb{Z}_{2A}$ orbifold, i.e. it enjoys the Kramers-Wannier duality. The Kramers-Wannier duality defect extends the Monster group to a larger category of topological defect lines that contains an Ising subcategory. We introduce the defect McKay-Thompson series defined as the Monster partition function twisted by the duality defect, and find that the coefficients can be decomposed into the dimensions of the (projective) irreducible representations of the Baby Monster group. We further prove that the defect McKay-Thompson series is invariant under the genus-zero congruence subgroup $16D^0$ of $PSL(2,\mathbb{Z})$.
Driving energetically unfavorable dehydrogenation dynamics with plasmonics

Nanoparticle surface structure and geometry generally dictate where chemical transformations occur, with higher chemical activity at sites with lower activation energies. Here, we show how optical excitation of plasmons enables spatially modified phase transformations, activating otherwise energetically unfavorable sites. We have designed a crossed-bar Au-PdH x antenna-reactor system that localizes electromagnetic enhancement away from the innately reactive PdH x nanorod tips. Using optically coupled in situ environmental transmission electron microscopy, we track the dehydrogenation of individual antenna-reactor pairs with varying optical illumination intensity, wavelength, and hydrogen pressure. Our in situ experiments show that plasmons enable new catalytic sites, including dehydrogenation at the nanorod faces. Molecular dynamics simulations confirm that these new nucleation sites are energetically unfavorable in equilibrium and only accessible through tailored plasmonic excitation.
Compact Dual-Band Multi-Focal Diffractive Lenses

We design, fabricate, and characterize multifunctional and compact diffractive microlenses with sub-wavelength thickness and the capability to simultaneously focus visible and near-infrared spectral bands at two different focal positions with 24% and 15% measured focusing efficiency, respectively. Our technology utilizes high-index and low-loss sputtered hydrogenated amorphous Si, enabling a sub-wavelength thickness of only 235nm. Moreover, the proposed flat lens concept is polarization insensitive and can be readily designed to operate across any desired wavelength regime. Imaging under broadband illumination with independent focal planes for two targeted spectral bands is experimentally demonstrated, enabling the encoding of the depth information of a sample into different spectral images. In addition, with a small footprint of only 100$\mu$m and a minimum feature size of 400nm, the proposed multifunctional and compact diffractive microlenses can be readily integrated with vertical detector arrays to simultaneously concentrate and spectrally select electromagnetic radiation. This provides novel opportunities for spectroscopic and multispectral imaging systems with advanced detector architectures.
Instance segmentation for whole slide imaging: end-to-end or detect-then-segment.

Purpose: Automatic instance segmentation of glomeruli within kidney whole slide imaging (WSI) is essential for clinical research in renal pathology. In computer vision, the end-to-end instance segmentation methods (e.g., Mask-RCNN) have shown their advantages relative to detect-then-segment approaches by performing complementary detection and segmentation tasks simultaneously. As a result, the end-to-end Mask-RCNN approach has been the de facto standard method in recent glomerular segmentation studies, where downsampling and patch-based techniques are used to properly evaluate the high-resolution images from WSI (e.g., > 10,000 × 10,000 pixels on 40 × ). However, in high-resolution WSI, a single glomerulus itself can be more than 1000 × 1000 pixels in original resolution which yields significant information loss when the corresponding features maps are downsampled to the 28 × 28 resolution via the end-to-end Mask-RCNN pipeline. Approach: We assess if the end-to-end instance segmentation framework is optimal for high-resolution WSI objects by comparing Mask-RCNN with our proposed detect-then-segment framework. Beyond such a comparison, we also comprehensively evaluate the performance of our detect-then-segment pipeline through: (1) two of the most prevalent segmentation backbones (U-Net and DeepLab_v3); (2) six different image resolutions ( 512 × 512 , 256 × 256 , 128 × 128 , 64 × 64 , 32 × 32 , and 28 × 28 ); and (3) two different color spaces (RGB and LAB). Results: Our detect-then-segment pipeline, with the DeepLab_v3 segmentation framework operating on previously detected glomeruli of 512 × 512 resolution, achieved a 0.953 Dice similarity coefficient (DSC), compared with a 0.902 DSC from the end-to-end Mask-RCNN pipeline. Further, we found that neither RGB nor LAB color spaces yield better performance when compared against each other in the context of a detect-then-segment framework. Conclusions: The detect-then-segment pipeline achieved better segmentation performance compared with the end-to-end method. Our study provides an extensive quantitative reference for other researchers to select the optimized and most accurate segmentation approach for glomeruli, or other biological objects of similar character, on high-resolution WSI.
Twistronics: a turning point in 2D quantum materials

Moir\'e superlattices - periodic orbital overlaps and lattice-reconstruction between sites of high atomic registry in vertically-stacked 2D layered materials - are quantum-active interfaces where non-trivial quantum phases on novel phenomena can emerge from geometric arrangements of 2D materials, which are not intrinsic to the parent materials. Unexpected distortions in band-structure and topology lead to long-range correlations, charge-ordering, and several other fascinating quantum phenomena hidden within the physical space between the (similar or dissimilar) parent materials. Stacking, twisting, gate-modulating, and optically-exciting these superlattices open up a new field for seamlessly exploring physics from the weak to strong correlations limit within a many-body and topological framework. It is impossible to capture it all, and the aim of this review is to highlight some of the important recent developments in synthesis, experiments, and potential applications of these materials.
Khintchine-type theorems for values of subhomogeneous functions at integer points

This work has been motivated by recent papers that quantify the density of values of generic quadratic forms and other polynomials at integer points, in particular ones that use Rogers’ second moment estimates. In this paper, we establish such results in a very general framework. Given any subhomogeneous function (a notion to be defined) $$f: \mathbb {R}^n \rightarrow \mathbb {R}$$ , we derive a necessary and sufficient condition on the approximating function $$\psi $$ for guaranteeing that a generic element $$f\circ g$$ in the G-orbit of f is $$\psi $$ -approximable; that is, $$|f\circ g(\mathbf {v})| \le \psi (\Vert \mathbf {v}\Vert )$$ for infinitely many $$\mathbf {v}\in \mathbb {Z}^n.$$ We also deduce a sufficient condition in the case of uniform approximation. Here G can be any closed subgroup of $$\mathrm {ASL}_n(\mathbb {R})$$ satisfying certain axioms that allow for the use of Rogers-type estimates.
Improving innovation and performance in professional service outsourcing - an empirical study in emerging market

This study investigates how a professional service provider's external integration with global clients and internal integration across various functional units impact its innovation and performance under various external environmental uncertainties. Drawing on the theory of organisational learning and dynamic capabilities, a conceptual framework is proposed and tested empirically by using survey data from Indian-based professional service providers. This study contributes to the much-needed efforts in studying professional service outsourcing and provides helpful managerial guidelines to both professional service providers and global clients regarding how to properly manage outsourcing activities to achieve expected benefits.
Are Remittances Insurance? Evidence from Rainfall Shocks in the Philippines

Several facts motivate this study. First, life in developing countries is prone to many kinds of risk, such as crop and income loss due to natural disasters (weather, insect infestations, and fire) and civil conflict. Second, international migration and remittance flows are substantial and growing. Between 1965 and 2000, individuals living outside their country of birth grew from 2.2 to 2.9 percent of the world population, totaling 175 million people in 2000. The remittances that these migrants send to their countries of origin are an important but poorly understood type of international financial flow. This article examines a mechanism for coping with shocks ex post on which previous micro-level studies have not focused: remittances from family members overseas. At the international level, it is commonly posited that remittance flows from overseas buffer economic shocks in migrants' home countries, but there have been relatively few empirical tests of this claim with micro-level household data. Related research on the role of domestic migration in pooling risk within extended families includes Lucas and Stark (1985), Rosenzweig and Stark (1989), and Paulson (2000).
The pros and cons of regulating corporate reporting: A critical review of the arguments

Abstract In this paper, we distil essential insights about the regulation of financial reporting from the academic literature. The key objective is to synthesise extant theory to provide a basis for evaluating implications of pressures on the regulation of financial accounting following the recent financial crisis. We succinctly lay out arguments put forth both for and against the regulation of corporate disclosure and standard‐setting. We then examine current developments suggesting that accounting standard‐setting is at risk of becoming entangled in a web of political forces with potentially significant consequences. The crisis has brought into sharp focus the reality that the regulation of corporate reporting is just one piece of a larger regulatory configuration, and that forces are at play that would subjugate accounting standard‐setting to broader regulatory demands. Recent actions by the European Commission relating to IFRS 9 and proposed legislation in the US Congress to create a systemic risk cou...
Investing in the ‘New Economy’: Mutual Fund Performance and the Nature of the Firm

Although stock returns of intangibles-intensive firms tend to exceed physical assets-intensive firms, risk-adjusted returns of actively managed mutual funds significantly decrease (increase) with their portfolios’ exposure to intangibles-intensive (physical assets-intensive) firms. Fund managers tend to exhibit skill when they focus on difficult-to-value (e.g., small) firms, except when the firms are intangibles-intensive. In sum, the worst-performing funds are in areas of the market that seem to offer ample opportunities for professional investors due to exacerbated mispricing. The negative impact of investments in intangibles-intensive firms on fund performance appears to be driven by extrapolation bias and decreases with learning from experience.
The Independent Effects of Savings Accounts in Children's Names on Their Savings Outcomes in Young Adulthood

A question of interest in children’s savings research asks whether there are unique effects on children’s later savings when savings accounts are opened in their names earlier in life, either independently from and or simultaneously with accounts in which parents save on children’s behalf. Using longitudinal data from the Panel Study of Income Dynamics, this study created a combined measure of children’s (ages 12–19) and parents’ savings account ownership to predict savings outcomes in young adulthood (ages 20–25). All possible combinations of children’s and parents’ account ownership were significantly related to young adults’ savings account ownership; however, only children’s savings account ownership was significantly related to savings accumulation. Implications for the independent effects of savings accounts in children’s names are discussed.
Joint ownership and alienability

Most legal traditions view individual ownership as paradigmatic. Yet most property is jointly owned. This paper analyzes how joint ownership affects alienability by focusing on two fundamental issues raised by joint ownership—the nature of the class of those who may benefit from a joint asset and the nature of the process for making decisions about such an asset. I identify four possible ways to resolve these issues. These possibilities coincide with the four general approaches by which joint property has been held over time and across legal traditions. This four-fold categorization and the different effect each has on alienability is used to analyze a broad array of laws and practices, ranging from Hindu inheritance law to the Uniform Partnership Act to the growing shareholder democracy movement.
Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing

Over the past 3 decades, the U.S. Temporary Help Services (THS) industry grew five times more rapidly than overall employment. Contemporaneously, courts in 46 states adopted exceptions to the common law doctrine of employment at will that limited employers’ discretion to terminate workers and opened them to litigation. This article assesses the contribution of “unjust dismissal” doctrine to THS employment specifically, and outsourcing more generally, finding that it is substantial—explaining 20% of the growth of THS between 1973 and 1995 and contributing 500,000 additional outsourced workers in 2000. States with smaller declines in unionization also saw substantially more THS growth.
Special Court for Sierra Leone: Decisions on the Recusal of Judges Robertson and Winter

This article examines two motions for recusal of Appeals Chamber judges in the Special Cout for Sierra Leone. In early March 2004, defendants before the Special Court alleged to be key figures in the Revolutionary United Front (RUF) succeeded in removing the President of the Special Court, Judge Geoffrey Robertson QC, from hearing their cases. This may also have led to Robertson's removal by his fellow judges as President of the Court. In the aftermath, a motion was unsuccessfully brought to remove Judge Winter from hearing an interlocutory motion on child soldiers in another case. This article summarizes those events, identifies serious issues of judicial propriety that they raise and comments on their implications for international criminal law.
The value of banking relationships during a financial crisis: Evidence from failures of Japanese banks

Abstract Previous literature suggests that banking relationships can enhance the value of client firms in the presence of asymmetric information problems. Hence, severance of banking ties due to a bank failure can have adverse consequences for the clients of the failed bank. In this paper, we provide evidence on the value of banking relationships by examining the impact of three large bank failures in Japan on their clients and the clients of surviving banks. We find that, as in previous studies, the market value of customers of the failed banks is adversely affected on the date of the failure announcements. In addition, the effects are related to the financial characteristics of both the client firms and their primary banks. Firms that have greater access to alternative sources of funding experience a less severe adverse impact from bank failure announcements. Similarly, clients of banks that are more profitable, better capitalized, and have lower loan loss reserves suffer less from the failure announcements. However, we also find that these effects are not significantly different from the effects experienced by all firms in the economy. That is, the bank failures represent “bad news” for all firms in the economy, not just for the customers of the failed banks.
Experimental Outlook for the Pentaquark

A critical look is taken at both positive and null evidence for the Θ+ pentaquark. Potential problems with experiments will be discussed and the question of what conclusion can be drawn from both the positive and the null results is examined. First the question of existence of the Θ+ pentaquark is considered, followed by a discussion of new experiments that are either planned or in progress to answer questions about its mass, width and isospin. Finally, indirect evidence for the parity of the Θ+ is examined, and suggestions for experiments to measure its parity directly are given.
Using MOEAs to Outperform Stock Benchmarks in the Presence of Typical Investment Constraints

Portfolio managers are typically constrained by turnover limits, minimum and maximum stock positions, cardinality, a target market capitalization and sometimes the need to hew to a style (such as growth or value). In addition, portfolio managers often use multifactor stock models to choose stocks based upon their respective fundamental data. We use multi-objective evolutionary algorithms (MOEAs) to satisfy the above real-world constraints. The portfolios generated consistently outperform typical performance benchmarks and have statistically significant asset selection.
Hierarchy and Heterogeneity: How to Read a Statute in a Lower Court

Is statutory interpretation an activity that all courts should perform the same way? Courts and commentators implicitly so conclude. I believe that conclusion is wrong. Statutory interpretation is a court-specific activity that should differ according to the institutional circumstances of the interpreting court. The U.S. Supreme Court is not the model all other courts should emulate. I identify three kinds of institutional differences between courts that bear on which interpretive methods are appropriate: (1) the court’s place in the hierarchical structure of appellate review, (2) the court’s technical capacity and resources, and (3) the court’s democratic pedigree, particularly as reflected in methods of judicial selection. Attending to these institutional factors would yield insights for both judicial practice and academic theory. In terms of prescriptions for courts, the differences justify a heterogeneous regime in which courts at different levels of the judicial hierarchy use somewhat different interpretive methods. But even apart from my specific recommendations, the larger point is that scholars need a normative account of what lower-court statutory interpretation should look like. Such a normative framework would help us evaluate the lower courts’ output (which is becoming the subject of an important and growing body of descriptive work) and determine which of the Supreme Court’s practices should – and should not – be followed in the lower courts.