cssi/SciSciGPT-SciSciNet huggingface dataset:
Learning Interpretable Feature Context Effects in Discrete Choice

Individuals are constantly making choices---purchasing products, consuming Web content, making social connections---so understanding what contributes to these decisions is crucial in many settings. A major interest is understanding context effects, which occur when the set of available options itself affects an individual's relative preferences. These violate traditional rationality assumptions but are commonly observed in human behavior. At the same time, identifying context effects from choice data remains a challenge; existing models posit a specific context effect a priori and then measure its effect from (often effect-targeting) data. Here, we develop discrete choice models that capture a broad range of context effects, which are learned from choice data rather than baked into the model. Our models yield intuitive, interpretable, and statistically testable context effects, all while being simple to train. We evaluate our model on several empirical choice datasets, discovering, e.g., that people are more willing to book higher-priced hotels when presented with options that are on sale. We also provide the first analysis of context effects in online social network growth, finding that users forming connections place relatively more emphasis on shared neighbors when popular users are an option.
Joint association and classification analysis of multi-view data.

Multi-view data, which is matched sets of measurements on the same subjects, have become increasingly common with advances in multi-omics technology. Often, it is of interest to find associations between the views that are related to the intrinsic class memberships. Existing association methods cannot directly incorporate class information, while existing classification methods do not take into account between-views associations. In this work, we propose a framework for Joint Association and Classification Analysis of multi-view data (JACA). Our goal is not to merely improve the misclassification rates, but to provide a latent representation of high-dimensional data that is both relevant for the subtype discrimination and coherent across the views. We motivate the methodology by establishing a connection between canonical correlation analysis and discriminant analysis. We also establish the estimation consistency of JACA in high-dimensional settings. A distinct advantage of JACA is that it can be applied to the multi-view data with block-missing structure, that is to cases where a subset of views or class labels is missing for some subjects. The application of JACA to quantify the associations between RNAseq and miRNA views with respect to consensus molecular subtypes in colorectal cancer data from The Cancer Genome Atlas project leads to improved misclassification rates and stronger found associations compared to existing methods.
Evoking highly focal percepts in the fingertips through targeted stimulation of sulcal regions of the brain for sensory restoration.

Abstract Background Paralysis and neuropathy, affecting millions of people worldwide, can be accompanied by significant loss of somatosensation. With tactile sensation being central to achieving dexterous movement, brain-computer interface (BCI) researchers have used intracortical and cortical surface electrical stimulation to restore somatotopically-relevant sensation to the hand. However, these approaches are restricted to stimulating the gyral areas of the brain. Since representation of distal regions of the hand extends into the sulcal regions of human primary somatosensory cortex (S1), it has been challenging to evoke sensory percepts localized to the fingertips. Objective/hypothesis Targeted stimulation of sulcal regions of S1, using stereoelectroencephalography (SEEG) depth electrodes, can evoke focal sensory percepts in the fingertips. Methods Two participants with intractable epilepsy received cortical stimulation both at the gyri via high-density electrocorticography (HD-ECoG) grids and in the sulci via SEEG depth electrode leads. We characterized the evoked sensory percepts localized to the hand. Results We show that highly focal percepts can be evoked in the fingertips of the hand through sulcal stimulation. fMRI, myelin content, and cortical thickness maps from the Human Connectome Project elucidated specific cortical areas and sub-regions within S1 that evoked these focal percepts. Within-participant comparisons showed that percepts evoked by sulcal stimulation via SEEG electrodes were significantly more focal (80% less area; p = 0.02) and localized to the fingertips more often, than by gyral stimulation via HD-ECoG electrodes. Finally, sulcal locations with consistent modulation of high-frequency neural activity during mechanical tactile stimulation of the fingertips showed the same somatotopic correspondence as cortical stimulation. Conclusions Our findings indicate minimally invasive sulcal stimulation via SEEG electrodes could be a clinically viable approach to restoring sensation.
Angular Momentum of Fission Fragments from Microscopic Theory

During nuclear fission, a heavy nucleus splits into two rotating fragments. The associated angular momentum is large, yet the mechanism of its generation and its dependence on the mass of fragments remain poorly understood. In this Letter, we provide the first microscopic calculations of angular momentum distributions in fission fragments for a wide range of fragment masses. For the benchmark case of $^{239}$Pu($n_{\text{th}}$,f), we find that the angular momentum of the fragments is largely determined by the nuclear shell structure and deformation, and that the heavy fragments therefore typically carry less angular momentum than their light partners. We use the fission model $\tt{FREYA}$ to simulate the emission of neutrons and photons from the fragments. The dependence of the angular momenta on fragment mass after the emission of neutrons and statistical photons is linear for the heavy fragments and either constant or weakly linear for the light fragments, consistent with the universal sawtooth pattern suggested by recent experimental data. Finally, we observe that using microscopic angular momentum distributions modifies the number of emitted photons significantly.
Estimation of high-dimensional seemingly unrelated regression models

In this paper, we investigate seemingly unrelated regression (SUR) models that allow the number of equations (N) to be large, and to be comparable to the number of the observations in each equation (T). It is well known in the literature that the conventional SUR estimator, for example, the generalized least squares (GLS) estimator of Zellner (1962) does not perform well. As the main contribution of the paper, we propose a new feasible GLS estimator called the feasible graphical lasso (FGLasso) estimator. For a feasible implementation of the GLS estimator, we use the graphical lasso estimation of the precision matrix (the inverse of the covariance matrix of the equation system errors) assuming that the underlying unknown precision matrix is sparse. We derive asymptotic theories of the new estimator and investigate its finite sample properties via Monte-Carlo simulations.
Robust a-posteriori error estimates for weak Galerkin method for the convection-diffusion problem

Abstract We present a robust a posteriori error estimator for a weak Galerkin finite element method applied to stationary convection-diffusion equations in the convection-dominated regime. The estimator provides global upper and lower bounds of the error and is robust in the sense that upper and lower bounds are uniformly bounded with respect to the diffusion coefficient. The weak Galerkin method we use was developed by Lin, Ye, Zhang, and Zhu (2018) for the convection-diffusion problem without assuming any additional conditions on the convection coefficient and, has a simple formulation. The motivation for our work comes from the fact that while this method performs very well in the strongly convection-dominated regime, it continues to exhibit poor behavior in the intermediate regime. In this proposed work we show that by relying on adaptively refined meshes based on a posteriori residual-type estimator, we can retrieve the optimal order of convergence for all the regimes not just for the strongly convection-dominated regime. Results of the numerical experiments are presented to illustrate the performance of the error estimator.
Personalized Priority Policies in Call Centers Using Past Customer Interaction Information

To increase revenue or improve customer service, companies are increasingly personalizing their product or service offerings based on their customers' history of interactions. In this paper, we sho...
Want To Reduce Labeling Cost? GPT-3 Can Help

Data annotation is a time-consuming and labor-intensive process for many NLP tasks. Although there exist various methods to produce pseudo data labels, they are often task-specific and require a decent amount of labeled data to start with. Recently, the immense language model GPT-3 with 170 billion parameters has achieved tremendous improvement across many few-shot learning tasks. In this paper, we explore ways to leverage GPT-3 as a low-cost data labeler to train other models. We find that to make the downstream model achieve the same performance on a variety of NLU and NLG tasks, it costs 50% to 96% less to use labels from GPT-3 than using labels from humans. Furthermore, we propose a novel framework of combining pseudo labels from GPT-3 with human labels, which leads to even better performance. These results present a cost-effective data labeling methodology that is generalizable to many practical applications.
The Milky Way, Coming into Focus: Precision Astrometry Probes its Evolution, and its Dark Matter

Abstract The growing trove of precision astrometric observations from the Gaia space telescope and other surveys is revealing the structure and dynamics of the Milky Way in ever more exquisite detail. We summarize the current status of our understanding of the structure and the characteristics of the Milky Way, and we review the emerging picture: the Milky Way is evolving through interactions with the massive satellite galaxies that stud its volume, with evidence pointing to a cataclysmic past. It is also woven with stellar streams, and observations of streams, satellites, and field stars offer new constraints on its dark matter, both on its spatial distribution and its fundamental nature. The recent years have brought much focus to the study of dwarf galaxies found within our Galaxy’s halo and their internal matter distributions. In this review, we focus on the predictions of the cold dark matter paradigm at small mass scales through precision astrometric measurements, and we summarize the modern consensus on the extent to which small-scale probes are consistent with this paradigm. We note the discovery prospects of these studies, and also how they intertwine with probes of the dynamics and evolution of the Milky Way in various and distinct ways.
Relevance-guided Supervision for OpenQA with ColBERT

Systems for Open-Domain Question Answering (OpenQA) generally depend on a retriever for finding candidate passages in a large corpus and a reader for extracting answers from those passages. In much recent work, the retriever is a learned component that uses coarse-grained vector representations of questions and passages. We argue that this modeling choice is insufficiently expressive for dealing with the complexity of natural language questions. To address this, we define ColBERT-QA, which adapts the scalable neural retrieval model ColBERT to OpenQA. ColBERT creates fine-grained interactions between questions and passages. We propose an efficient weak supervision strategy that iteratively uses ColBERT to create its own training data. This greatly improves OpenQA retrieval on Natural Questions, SQuAD, and TriviaQA, and the resulting system attains state-of-the-art extractive OpenQA performance on all three datasets.
Single-virus content-mixing assay reveals cholesterol-enhanced influenza membrane fusion efficiency.

Abstract In order to infect a cell, enveloped viruses must first undergo membrane fusion, which proceeds through a hemifusion intermediate, followed by the formation of a fusion pore through which the viral genome is transferred to a target cell. Single-virus fusion studies to elucidate the dynamics of content mixing typically require extensive fluorescent labeling of viral contents. The labeling process must be optimized depending on the virus identity and strain and can potentially be perturbative to viral fusion behavior. Here, we introduce a single-virus assay where content-labeled vesicles are bound to unlabeled influenza A virus (IAV) to eliminate the problematic step of content-labeling virions. We use fluorescence microscopy to observe individual, pH-triggered content mixing and content loss events between IAV and target vesicles of varying cholesterol compositions. We show that target membrane cholesterol increases the efficiency of IAV content mixing and decreases the fraction of content mixing events that result in content loss. These results are consistent with previous findings that cholesterol stabilizes pore formation in IAV entry and limits leakage following pore formation. We also show that content loss due to hemagglutinin fusion peptide engagement with the target membrane is independent of composition. This approach is a promising strategy for studying the single-virus content mixing kinetics of other enveloped viruses.
Learning swimming escape patterns for larval fish under energy constraints

This study explores escape motions employed by larval fish using two-dimensional simulations. We demonstrate how a deep reinforcement learning framework, discovers swimming escape motions, not previously obtained through direct optimization, under various energy constraints. The study serves to showcase the richness of flow physics that can be discovered through the use of artificial intelligence.
Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas.

Summary Deconstructing tissue-specific effects of genes and variants on proliferation is critical to understanding cellular transformation and systematically selecting cancer therapeutics. This requires scalable methods for multiplexed genetic screens tracking fitness across time, across lineages, and in a suitable niche, since physiological cues influence functional differences. Towards this, we present an approach, coupling single-cell cancer driver screens in teratomas with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serial reinjection. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. Additionally, mutant MEK1S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful platform for multi-lineage longitudinal study of oncogenesis.
Inverse design of grating couplers using the policy gradient method from reinforcement learning

We present a proof-of-concept technique for the inverse design of electromagnetic devices motivated by the policy gradient method in reinforcement learning, named PHORCED (PHotonic Optimization using REINFORCE Criteria for Enhanced Design). This technique uses a probabilistic generative neural network interfaced with an electromagnetic solver to assist in the design of photonic devices, such as grating couplers. We show that PHORCED obtains better performing grating coupler designs than local gradient-based inverse design via the adjoint method, while potentially providing faster convergence over competing state-of-the-art generative methods. Furthermore, we implement transfer learning with PHORCED, demonstrating that a neural network trained to optimize 8$^\circ$ grating couplers can then be re-trained on grating couplers with alternate scattering angles while requiring >$10\times$ fewer simulations than control cases.
Organizational Characteristics Associated with High Performance in Medicare's Comprehensive End-Stage Renal Disease Care Initiative

Background and objectives Medicare plans to extend financial structures tested through the Comprehensive End-Stage Renal Disease Care (CEC) Initiative-an alternative payment model for maintenance dialysis providers-to promote high-value care for beneficiaries with kidney failure. The End-Stage Renal Disease Seamless Care Organizations (ESCOs) that formed under the CEC Initiative varied greatly in their ability to generate cost savings and improve patient health outcomes. This study examined whether organizational or community characteristics were associated with ESCOs' performance. Design, setting, participants, & measurements We used a retrospective pooled cross-sectional analysis of all 37 ESCOs participating in the CEC Initiative during 2015-2018 (n=87 ESCO-years). Key exposures included ESCO characteristics: number of dialysis facilities, number and types of physicians, and years of CEC Initiative experience. Outcomes of interest included were above versus below median gross financial savings (2.4%) and standardized mortality ratio (0.93). We analyzed unadjusted differences between high- and low-performing ESCOs and then used multivariable logistic regression to construct average marginal effect estimates for parameters of interest. Results Above-median gross savings were obtained by 23 (52%) ESCOs with no program experience, 14 (32%) organizations with 1 year of experience, and seven (16%) organizations with 2 years of experience. The adjusted likelihoods of achieving above-median gross savings were 23 (95% confidence interval, 8 to 37) and 48 (95% confidence interval, 24 to 68) percentage points higher for ESCOs with 1 or 2 years of program experience, respectively (versus none). The adjusted likelihood of achieving above-median gross savings was 1.7 (95% confidence interval, -3 to -1) percentage points lower with each additional affiliated dialysis facility. Adjusted mortality rates were lower for ESCOs located in areas with higher socioeconomic status. Conclusions Smaller ESCOs, organizations with more experience in the CEC Initiative, and those located in more affluent areas performed better under the CEC Initiative.
Necessity, Importance, and the Nature of Law

This paper, prepared for a conference on jurisprudential methodology in Girona, Spain, starts with the observation that much of contemporary jurisprudence focuses on conceptual analysis, and on the properties that are necessary (or essential) to the concept of law. This enterprise is thought to advance our “understanding” of the “nature” of law, and indeed it has. But if we define the “nature of law” as other than synonymous with “concept of law,” or if we substitute words like “character” or “tenor” for “nature,” we may discover that there are features that are not necessary to law, but which overwhelmingly exist in actual legal systems, and which are more concentrated in legal systems than in other social structures and institutions. Moreover, we may discover that the identification and philosophical analysis of such features—probabilistically concentrated in law but not necessary to it—can also advance our understanding. As a result, defining jurisprudence (or the philosophy of law) as limited to general jurisprudence and as limited to the search for features that are necessary to law wherever and whenever it exists may turn out to hinder rather than advance our understanding of law as it is lived and experienced. Most contemporary practitioners of analytic general jurisprudence seek to identify and explain those features of law that are both necessary and important for legality, but by examining features that are important but not necessary we may learn much about law that an existing but unfortunate common definition of jurisprudence impedes.
Exchange bias without directional anisotropy in permalloy/CoO bilayers

We utilize transverse ac susceptibility measurements to characterize magnetic anisotropy in archetypal exchange-bias bilayers of ferromagnet permalloy (Py) and antiferromagnet CoO. Unidirectional anisotropy is observed for thin Py but becomes negligible at larger Py thicknesses, even though the directional asymmetry of the magnetic hysteresis loop remains significant. Additional magnetoresistance measurements, magneto-optical imaging, as well as micromagnetic simulations show that these surprising behaviors are likely associated with asymmetry of spin-flop distribution created in CoO during Py magnetization reversal, which facilitates the rotation of the latter back into its field-cooled direction. Our findings suggest possibilities for efficient realization of multistable nanomagnetic systems for neuromorphic applications
The telomere regulatory gene POT1 responds to stress and predicts performance in nature: Implications for telomeres and life history evolution.

Telomeres are emerging as correlates of fitness-related traits and may be important mediators of ecologically relevant variation in life history strategies. Growing evidence suggests that telomere dynamics can be more predictive of performance than length itself, but very little work considers how telomere regulatory mechanisms respond to environmental challenges or influence performance in nature. Here, we combine observational and experimental data sets from free-living tree swallows (Tachycineta bicolor) to assess how performance is predicted by the telomere regulatory gene POT1, which encodes a shelterin protein that sterically blocks telomerase from repairing the telomere. First, we show that lower POT1 gene expression in the blood was associated with higher female quality, that is, earlier breeding and heavier body mass. We next challenged mothers with an immune stressor (lipopolysaccharide injection) that led to "sickness" in mothers and 24 h of food restriction in their offspring. While POT1 did not respond to maternal injection, females with lower constitutive POT1 gene expression were better able to maintain feeding rates following treatment. Maternal injection also generated a 1-day stressor for chicks, which responded with lower POT1 gene expression and elongated telomeres. Other putatively stress-responsive mechanisms (i.e., glucocorticoids, antioxidants) showed marginal responses in stress-exposed chicks. Model comparisons indicated that POT1 mRNA abundance was a largely better predictor of performance than telomere dynamics, indicating that telomere regulators may be powerful modulators of variation in life history strategies.
Implicit Integration for Articulated Bodies with Contact via the Nonconvex Maximal Dissipation Principle

We present non-convex maximal dissipation principle (NMDP), a time integration scheme for articulated bodies with simultaneous contacts. Our scheme resolves contact forces via the maximal dissipation principle (MDP). Whereas prior MDP solvers assume linearized dynamics and integrate using the forward multistep scheme, we consider the coupled system of nonlinear Newton-Euler dynamics and MDP and integrate using the backward integration scheme. We show that the coupled system of equations can be solved efficiently using a novel projected gradient method with guaranteed convergence. We evaluate our method by predicting several locomotion trajectories for a quadruped robot. The results show that our NMDP scheme has several desirable properties including: (1) generalization to novel contact models; (2) stability under large timestep sizes; (3) consistent trajectory generation under varying timestep sizes.
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias

The generalization mystery of overparametrized deep nets has motivated efforts to understand how gradient descent (GD) converges to low-loss solutions that generalize well. Real-life neural networks are initialized from small random values and trained with cross-entropy loss for classification (unlike the "lazy" or "NTK" regime of training where analysis was more successful), and a recent sequence of results (Lyu and Li, 2020; Chizat and Bach, 2020; Ji and Telgarsky, 2020) provide theoretical evidence that GD may converge to the "max-margin" solution with zero loss, which presumably generalizes well. However, the global optimality of margin is proved only in some settings where neural nets are infinitely or exponentially wide. The current paper is able to establish this global optimality for two-layer Leaky ReLU nets trained with gradient flow on linearly separable and symmetric data, regardless of the width. The analysis also gives some theoretical justification for recent empirical findings (Kalimeris et al., 2019) on the so-called simplicity bias of GD towards linear or other "simple" classes of solutions, especially early in training. On the pessimistic side, the paper suggests that such results are fragile. A simple data manipulation can make gradient flow converge to a linear classifier with suboptimal margin.
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning

Semi-supervised learning (SSL) algorithms have had great success in recent years in limited labeled data regimes. However, the current state-of-the-art SSL algorithms are computationally expensive and entail significant compute time and energy requirements. This can prove to be a huge limitation for many smaller companies and academic groups. Our main insight is that training on a subset of unlabeled data instead of entire unlabeled data enables the current SSL algorithms to converge faster, thereby reducing the computational costs significantly. In this work, we propose RETRIEVE, a coreset selection framework for efficient and robust semi-supervised learning. RETRIEVE selects the coreset by solving a mixed discrete-continuous bi-level optimization problem such that the selected coreset minimizes the labeled set loss. We use a one-step gradient approximation and show that the discrete optimization problem is approximately submodular, thereby enabling simple greedy algorithms to obtain the coreset. We empirically demonstrate on several real-world datasets that existing SSL algorithms like VAT, Mean-Teacher, FixMatch, when used with RETRIEVE, achieve a) faster training times, b) better performance when unlabeled data consists of Out-of-Distribution(OOD) data and imbalance. More specifically, we show that with minimal accuracy degradation, RETRIEVE achieves a speedup of around 3X in the traditional SSL setting and achieves a speedup of 5X compared to state-of-the-art (SOTA) robust SSL algorithms in the case of imbalance and OOD data.
ReasonBERT: Pre-trained to Reason with Distant Supervision

We present ReasonBert, a pre-training method that augments language models with the ability to reason over long-range relations and multiple, possibly hybrid contexts. Unlike existing pre-training methods that only harvest learning signals from local contexts of naturally occurring texts, we propose a generalized notion of distant supervision to automatically connect multiple pieces of text and tables to create pre-training examples that require long-range reasoning. Different types of reasoning are simulated, including intersecting multiple pieces of evidence, bridging from one piece of evidence to another, and detecting unanswerable cases. We conduct a comprehensive evaluation on a variety of extractive question answering datasets ranging from single-hop to multi-hop and from text-only to table-only to hybrid that require various reasoning capabilities and show that ReasonBert achieves remarkable improvement over an array of strong baselines. Few-shot experiments further demonstrate that our pre-training method substantially improves sample efficiency.
Functional Multi-Omics Reveals Genetic and Pharmacologic Regulation of Surface CD38 in Multiple Myeloma

CD38 is a surface ectoenzyme expressed at high levels on myeloma plasma cells and is the target for the monoclonal antibodies (mAbs) daratumumab and isatuximab. CD38 density on tumor cells is an important determinant of mAb efficacy, and CD38 loss after mAb treatment may play a role in resistance. Several small molecules have been found to increase tumor surface CD38, with the goal of boosting mAb efficacy in a co-treatment strategy. Here we sought to extend our currently limited insight into CD38 surface expression by using a multi-omics approach. Genome-wide CRISPR-interference screens integrated with patient-centered epigenetic analysis confirmed known regulators of CD38, such as RARA, while revealing XBP1 and SPI1 as other key transcription factors governing surface CD38 levels. CD38 knockdown followed by cell surface proteomics demonstrated no significant remodeling of the myeloma 9surfaceome9 after genetically-induced loss of this antigen. Integrated transcriptome and surface proteome data confirmed high specificity of all-trans retinoic acid in upregulating CD38 in contrast to broader effects of azacytidine and panobinostat. Finally, unbiased phosphoproteomics identified inhibition of MAP kinase pathway signaling in tumor cells after daratumumab treatment. Our work provides a resource to design strategies to enhance efficacy of CD38-targeting immunotherapies in myeloma.
The Disease-Associated Proteins Drosophila Nab2 and Ataxin-2 Interact with Shared RNAs and Coregulate Neuronal Morphology

Nab2 encodes the Drosophila melanogaster member of a conserved family of zinc finger polyadenosine RNA-binding proteins (RBPs) linked to multiple steps in post-transcriptional regulation. Mutation of the Nab2 human ortholog ZC3H14 gives rise to an autosomal recessive intellectual disability but understanding of Nab2/ZC3H14 function in metazoan nervous systems is limited, in part because no comprehensive identification of metazoan Nab2/ZC3H14-associated RNA transcripts has yet been conducted. Moreover, many Nab2/ZC3H14 functional protein partnerships remain unidentified. Here, we present evidence that Nab2 genetically interacts with Ataxin-2 (Atx2), which encodes a neuronal translational regulator, and that these factors coordinately regulate neuronal morphology, circadian behavior, and adult viability. We then present the first high-throughput identifications of Nab2- and Atx2-associated RNAs in Drosophila brain neurons using RNA immunoprecipitation-sequencing (RIP-Seq). Critically, the RNA interactomes of each RBP overlap, and Nab2 exhibits high specificity in its RNA associations in neurons in vivo, associating with a small fraction of all polyadenylated RNAs. The identities of shared associated transcripts (e.g., drk, me31B, stai) and of transcripts specific to Nab2 or Atx2 (e.g., Arpc2 and tea) promise insight into neuronal functions of, and genetic interactions between, each RBP. Consistent with prior biochemical studies, Nab2-associated neuronal RNAs are overrepresented for internal A-rich motifs, suggesting these sequences may partially mediate Nab2 target selection. These data support a model where Nab2 functionally opposes Atx2 in neurons, demonstrate Nab2 shares associated neuronal RNAs with Atx2, and reveal Drosophila Nab2 associates with a more specific subset of polyadenylated mRNAs than its polyadenosine affinity alone may suggest.
A novel aperture isolation circuit for use in phased array systems

A novel electronically controlled matching network has been demonstrated as an aperture isolation circuit. This approach offers smaller size, lower weight, and potentially lower cost than circulators. An X-band MMIC (monolithic microwave integrated circuit) realization of this circuit has comparable loss to a circulator. An S-band hybrid realization demonstrated reductions in insertion loss of up to 2.3 dB for antenna VSWRs (voltage standing wave ratios) of up to 5:1 lying within a 100 degrees sector on the Smith chart. One disadvantage of this approach is that it increases the complexity of controlling and calibrating the module. >
Distributionally robust portfolio optimization with linearized STARR performance measure

We study the distributionally robust linearized stable tail adjusted return ratio (DRLSTARR) portfolio optimization problem, in which the objective is to maximize the worst-case linearized stable tail adjusted return ratio (LSTARR) performance measure under data-driven Wasserstein ambiguity. We consider two types of imperfectly known uncertainties, named uncertain probabilities and continuum of realizations, associated with the losses of assets. We account for two typical combinatorial trading constraints, called buy-in threshold and diversification constraints, to reflect stock market restrictions. Leveraging conic duality theory to tackle the distributionally robust worst-case expectation, the proposed problems are reformulated into mixed-integer linear programming problems. We carry out a series of empirical tests to illustrate the scalability and effectiveness of the proposed solution framework, and to evaluate the performance of the DRLSTARR-constructed portfolios. The cross-validation results obtained using a rolling-horizon procedure show the superior out-of-sample performance of the DRLSTARR portfolios under the uncertain continuum of realizations.
Functional and Pragmatic Directions in Aphasia Therapy

Publisher Summary This chapter focuses on the functional and pragmatic directions in aphasia therapy. In the science of aphasia a shift is evident as well. The emphasis on the characterization of language solely in terms of semantics and syntax began to lean toward language use and language in context. Models of aphasia that incorporate social elements as vital signs of a living, growing scientific and clinical discipline are increasingly apparent. The medical model of the assessment, diagnosis, and treatment of the acute phase of aphasia is no longer as appropriate as earlier translated. Certainly aphasia is associated with certain unalienable medical conditions and constructs, and these should neither be ignored nor abandoned. But aphasia is also social. It is based on communicating, interacting with others, and living in a societal context. Traditionally, language analysis, particularly in aphasia, had been largely word and sentence based. Increasingly, glimmers of interest began emerging on such seemingly “unique” language uses as conversation, discourse styles, social interaction, and even participation in language events in the real word context. Fitting well into social models of aphasia is the recently articulated Life Participation Approach to Aphasia (LPAA). The statement issued by the LPAA Project group is intended to have an impact on assessment, intervention, policy making, advocacy, and research in aphasia. The life participation approach to aphasia is conceived foremost as a consumer-driven movement that has intended to broaden and focus the goals of aphasia treatment. Pragmatic and life participation approaches to aphasia research and intervention are closely tied to the concepts of chronicity and quality of life.
Patient- and treatment-specific predictors of genitourinary function after high-dose-rate monotherapy for favorable prostate cancer.

Abstract Purpose High-dose-rate (HDR) brachytherapy alone is an effective treatment option for patients with early-stage prostate cancer. The purpose of this study was to quantify patient-reported short- and long-term toxicity and quality of life (QOL) after HDR monotherapy. Methods and Materials Thirty-nine consecutive men between May 2001 and January 2012 were identified for this analysis. All patients underwent definitive HDR monotherapy for favorable prostate cancer to a total dose of 3150 cGy in three fractions, 3800 cGy in four fractions, or 3850 in five fractions. Patient-reported genitourinary function was assessed before HDR, during an acute period after treatment (within 90 days of HDR), and on long-term followup using the American Urological Association International Prostate Symptom Score, a urinary QOL Likert questionnaire, and the Sexual Health Inventory for Men questionnaire. Regression analyses were performed using the ordinary least squares method. Results With median followup of 57 months, biochemical progression-free survival was 100%. There were no grade ≥3 toxicities. Dose to the urethra and bladder, as well as prostate size and intraprostatic urethra length were predictive for short-term changes in QOL. Advanced patient age was predictive for worse sexual function on both acute and long-term followup. Conclusions Toxicity after HDR monotherapy for prostate cancer is acceptable. Patients with larger prostates, longer intraprostatic urethras, and greater doses to the bladder and urethra may experience worse acute urinary QOL. Older patients may experience greater impairment in sexual function in the short and long terms.
How do "Resource Bundles" Develop and Change in New Ventures? A Dynamic Model and Longitudinal Exploration

According to recent studies applying Resource-Based Theory [RBT] to entrepreneurial firms (e.g. Chandler & Hanks, 1994; Brush & Greene, 1996), in the early stages of new venture development it is t...
Displacement Control of Elastic Structures: Integral Control with a Robustness Property

The issue of design of feedback controllers for elastic structures is addressed, where the objective is accurate and robust displacement control of the structure. Motivation for the work arises from study of control of multi-story buildings as part of the pseudo-dynamic-test method. If the force actuators have "fast" dynamics suitable control may be achieved by feedback of structural displacements and velocities, usilng a PID type controller logic. If the force actuators have "slow" dynamics it is suggested that structural accelerations also be fed back to the controller. Locations of the assigned closed loop poles are specified which guarantee robustness to variations in the actuator time constant and to uncertainties in the structural stiffness. Simplifying assumptions are made so that results are obtained using elementary arguments.
Supply Chain Coordination

Supply chain coordination is among the central issues in supply chain management. A supply chain is coordinated if all supply chain members adopt the actions that optimize the entire system's performance. However, in most cases, supply chain firms are independent, self-interested entities that may deviate from the system-optimal actions. This article provides an introductory review on how firms can use various contractual schemes to achieve supply chain coordination. Discussions on additional issues and potential research directions are also provided. Keywords: supply chains; incentives; coordination; channels; contracts; newsvendor; inventory management
ON THE NATURE OF COPPER IN ASCORBATE OXIDASE. I. THE VALENCE STATE OF COPPER IN THE DENATURED AND NATIVE ENZYME.

Abstract 1. 1. The valency state of Cu in the enzyme ascorbate oxidase ( l -ascorbate: O 2 oxidoreductase, EC 1.10.3.3) has been determined by liberating the copper from the enzyme in the presence of valence-specific Cu-chelating agents. The procedures were designed to prevent electronic changes in the copper valency as a result of enzyme denaturation during the assay process. 2. 2. By means of the two Cu(I)-specific reagents, cuproine and bathocuproine, it has been found that the prosthetic copper in ascorbate oxidase exists in a mixed valency state, corresponding to 25% Cu(I) and 75% Cu(II). This ratio of 1:3 corresponds to 2 atoms of Cu(I) and 6 atoms of Cu(II) per enzyme molecule. 3. 3. This same ratio was found for the mixed valency state in the denatured enzyme when the Cu(I) reagent, bathocuproine, and the Cu(II) reagent, cuprizone, were used simultaneously. 4. 4. Neither bathocuproine nor cuprizone reacted directly with the native enzyme at physiological pH 7.2.
Glutathione Levels and Susceptibility to Chemically Induced Injury in Two Human Prostate Cancer Cell Lines

More aggressive prostate cancer cells (PCCs) are often resistant to chemotherapy. Differences exist in redox status and mitochondrial metabolism that may help explain this phenomenon. Two human PCC lines, PC-3 cells (more aggressive) and LNCaP cells (less aggressive), were compared with regard to cellular glutathione (GSH) levels, susceptibility to either oxidants or GSH depletors, and expression of several proteins involved in apoptosis and stress response to test the hypothesis that more aggressive PCCs exhibit higher GSH concentrations and are relatively resistant to cytotoxicity. PC-3 cells exhibited 4.2-fold higher GSH concentration than LNCaP cells but only modest differences in acute cytotoxicity were observed at certain time points. However, only LNCaP cells underwent diamide-induced apoptosis. PC-3 cells exhibited higher levels of Bax and caspase-8 cleavage product but lower levels of Bcl-2 than LNCaP cells. However, LNCaP cells exhibited higher expression of Fas receptor (FasR) but also higher levels of several stress response and antioxidant proteins than PC-3 cells. LNCaP cells also exhibited higher levels of several mitochondrial antioxidant systems, suggesting a compensatory response. Thus, significant differences in redox status and expression of proteins involved in apoptosis and stress response may contribute to PCC aggressiveness.
Socioeconomic Rights and Refugee Status: Deepening the Dialogue Between Human Rights and Refugee Law

Over the past two decades, international human rights law has provided an increasingly useful framework for interpreting key criteria of the definition of a refugee. A human rights-based approach to analyzing refugee status helps to increase consistency and uniformity in decision making by state parties regarding who qualifies for international protection.Michelle Foster's book, International Refugee Law and Socio-economic Rights: Refuge from Deprivation (Cambridge U. Press 2007), comes at a critical time, not only because of increasing acceptance of the connection between refugee law and human rights law and significant developments in the current understanding of economic and social rights, but also because more asylum applicants are articulating the aspects of their claims involving socioeconomic deprivation. All jurisdictions, including the United States, now recognize that socioeconomic harm can rise to the level of persecution, but inconsistencies and insecurities still obstruct attempts at coherent analysis. Foster's meticulous research, sober reasoning, and original analysis may encourage additional scholarship on these pressing issues and lead to a more sophisticated understanding of both the refugee definition and the substantive content of economic and social rights. The proper adjudication of socioeconomic claims will likely play a vital role in challenging the lingering, dominant orthodoxy of civil and political rights, help coalesce the relationship between human rights and refugee law, and promote the development of refugee law, with some coherency, as a body of law.
Basic Chemistry of Botulinum Neurotoxins Relevant to Vaccines, Diagnostics, and Countermeasures

Botulinum neurotoxins (BoNTs) produced by the Clostridium family of bacteria are the deadliest of all naturally occurring toxins and are listed as the highest risk biothreat agents by the Centers for Disease Control and Prevention (CDC). They are the causative agents of botulism, a severe neuroparalytic disease which can be fatal in the absence of medical care. While the natural cases of botulism are rare, by virtue of their extreme toxicity, easy production, and dissemination, BoNTs could potentially be employed as biowarfare agents and hence pose great threat to national security and public health. Nevertheless, the ability of these toxins to disrupt neurotransmission has been put to good use, and this potentially lethal toxin is now being used therapeutically in an ever expanding list of medical disorders and cosmetic treatments. A combination of features including neuronal target sites, efficient cellular entry, and unique enzymatic activity contributes to the extreme toxicity of BoNTs. Botulinum neurotoxins have a multi-domain structure with each domain contributing to a specific role in the toxin action. Recent advancements in deciphering the molecular mechanism of action of BoNTs and their structure-function relationship have facilitated a greater understanding of the potential use of individual domains of the toxin in the development of potent antidotes against botulism. Numerous biodefense efforts have been directed toward the development of improved technologies for botulism detection/diagnosisandfor developing effective countermeasures, including vaccines, peptides, and small-molecule inhibitors.
Citizen Input and Aging Policy The Case of Florida

This research assesses the relevance of citizen input to support for age-related policy among local public officials. Viewed in terms of the manner in which citizens and public officials characteri...
Effects of ganglioside treatments on lesion-induced behavioral impairments and sprouting in the CNS.

Recent findings suggest that exogenous gangliosides improve recovery of a learned behavior (alternation in a T-maze) which is thought to be related to sprouting after lesions of the entorhinal cortex. In the present investigation, we studied an unlearned behavior (the open-field hyperactivity resulting from bilateral entorhinal lesions) to evaluate whether ganglioside treatments reduce the severity of initial postlesion impairments or improve recovery. We also examined whether the treatments enhance the sprouting of septodentate fibers which parallels the recovery of open-field activity. The typical behavioral changes induced by bilateral entorhinal lesions include hyperactivity, reduced habituation of activity, and a gradual time-dependent return toward control levels. We found that rats treated with total brain gangliosides (30 mg/kg) showed a smaller lesion-induced increase, consistently lower levels, and greater within-session habituation of activity than did saline-treated counterparts. Control rats treated with gangliosides did not exhibit a reduction in activity, suggesting that the effect was on lesion-induced hyperactivity rather than on activity, per se. Ganglioside-treated rats showed a slight, but consistently smaller lesion-induced sprouting response by the septodentate pathway than did untreated counterparts at all postlesion intervals examined (3, 5, 7, and 10 days). The present findings indicate that ganglioside treatments reduce the severity of the initial behavioral effects after entorhinal lesions without enhancing the sprouting by septodentate fibers.
Gene-modified PA1-STK cells home to tumor sites in patients with malignant pleural mesothelioma.

Abstract Background . Malignant mesothelioma is an uncommon but lethal cancer of increasing incidence, particularly among patients with a history of exposure to asbestos. Although numerous treatments have been employed, including chemotherapy, radiation therapy, surgical resection, and combinations of the above, no satisfactory treatment yet exists, and affected patients will die of this disease, usually within 12 months. Gene-based therapies constitute a new approach that offers hope of improved control of these tumors while being associated with less morbidity than conventional chemotherapeutic or surgical regimens. We demonstrated that PA1-STK cells home in vivo to mesothelioma deposits, a phenomenon that is required for optimal exertion of this therapeutic concept. Methods . Gene-modified ovarian cancer cells expressing the thymidine-kinase gene (PA1-STK) were radiolabeled with 99 Tc and infused into the pleural space of 4 patients with malignant pleural mesothelioma, then scanned to determine distribution of the cells. Results . PA1-STK cells recognized and adhered preferentially to mesothelioma lining the chest wall. Conclusions . Cell-based "suicide gene" therapy utilizing the "bystander effect" with the gene-modified ovarian cancer cell line PA1-STK is feasible in human pleural mesothelioma. We have shown that this trafficking and homing of the therapeutic cells to the intrapleural tumor sites, a requirement for success with this novel therapeutic concept, is also valid in humans.