cssi/SciSciGPT-SciSciNet huggingface dataset:
Forecasting the Remaining Duration of an Ongoing Solar Flare

The solar X-ray irradiance is significantly heightened during the course of a solar flare, which can cause radio blackouts due to ionization of the atoms in the ionosphere. As the duration of a sol...
Robust Control Co-Design with Receding-Horizon MPC

Control co-design (CCD) is a technique for improving the closed-loop performance of systems through the coordinated design of both plant parameters and an optimal control policy. While model predictive control (MPC) is an attractive control strategy for many systems, embedding it within a CCD algorithm presents challenges because obtaining a closed-form solution for this receding-horizon optimization strategy is often not feasible. This paper meets that challenge by including a robust MPC formulation within the inner loop of a CCD algorithm. As exemplified by application to an aircraft thermal management system, the proposed algorithm closely matches the plant design of an open-loop benchmark. However, unlike the open-loop approach, the proposed algorithm can leverage MPC control variables designed a priori to achieve robust online operation under disturbance profiles that differ from those used for design.
A Fulton–Hansen theorem for almost homogeneous spaces

We prove a generalization of the Fulton–Hansen connectedness theorem, where $${\mathbb {P}}^n$$ is replaced by a normal variety on which an algebraic group acts with a dense orbit.
Predicting critical state after COVID-19 diagnosis: model development using a large US electronic health record dataset

As the COVID-19 pandemic is challenging healthcare systems worldwide, early identification of patients with a high risk of complication is crucial. We present a prognostic model predicting critical state within 28 days following COVID-19 diagnosis trained on data from US electronic health records (IBM Explorys), including demographics, comorbidities, symptoms, and hospitalization. Out of 15753 COVID-19 patients, 2050 went into critical state or deceased. Non-random train-test splits by time were repeated 100 times and led to a ROC AUC of 0.861 [0.838, 0.883] and a precision-recall AUC of 0.434 [0.414, 0.485] (median and interquartile range). The interpretability analysis confirmed evidence on major risk factors (e.g., older age, higher BMI, male gender, diabetes, and cardiovascular disease) in an efficient way compared to clinical studies, demonstrating the model validity. Such personalized predictions could enable fine-graded risk stratification for optimized care management.
Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.
The Vietoris functor and modal operators on rings of continuous functions

Abstract We introduce an endofunctor H on the category bal of bounded archimedean l-algebras and show that there is a dual adjunction between the category Alg ( H ) of algebras for H and the category Coalg ( V ) of coalgebras for the Vietoris endofunctor V on the category of compact Hausdorff spaces. We prove that Gelfand duality lifts to a dual equivalence between Coalg ( V ) and the full reflective subcategory Alg u ( H ) of Alg ( H ) . We provide an alternate view of Alg u ( H ) by introducing an endofunctor H u on the full reflective subcategory of bal consisting of uniformly complete objects of bal and showing that Alg ( H u ) is isomorphic to Alg u ( H ) . On the one hand, these results generalize those of [1] , [19] for the category of coalgebras of the Vietoris endofunctor on the category of Stone spaces. On the other hand, they provide an alternate, more categorical proof of a recent result of [6] .
Rigidity, Graphs and Hausdorff Dimension

A set of \(k+1\) points in Euclidean space is called a \((k+1)\)-point configuration. Two configurations are congruent if they are equal up to an affine isometry. Given a compact subset E of \(\mathbb R^d\), \(d\ge 2\) of Hausdorff dimension greater than \(d-\frac{1}{k+1}\) we prove that the Lebesgue measure of noncongruent \((k+1)\)-point configurations in E is positive, for \(k>d\), complementing the results of [11] for \(k\le d\).
Nonlinear waveform distortion: Assessment and detection of clipping on speech data and systems

Abstract Speech, speaker, and language systems have traditionally relied on carefully collected speech material for training acoustic models. There is an enormous amount of freely accessible audio content. A major challenge, however, is that such data is not professionally recorded, and therefore may contain a wide diversity of background noise, nonlinear distortions, or other unknown environmental or technology-based contamination or mismatch. There is a crucial need for automatic analysis to screen such unknown datasets before acoustic model development training, or to perform input audio purity screening prior to classification. In this study, we propose a waveform based clipping detection algorithm for naturalistic audio streams and examine the impact of clipping at different severities on speech quality measurements and automatic speaker recognition systems. We use the TIMIT and NIST SRE08 corpora as case studies. The results show, as expected, that clipping introduces a nonlinear distortion into clean speech data, which reduces speech quality and performance for speaker recognition. We also investigate what degree of clipping can be present to sustain effective speech system performance. The proposed detection system, which will be released, could contribute to massive new audio collections for speech and language technology development (e.g. Google Audioset ( Gemmeke et al., 2017 ), CRSS-UTDallas Apollo Fearless-Steps ( Yu et al., 2014 ) (19,000 h naturalistic audio from NASA Apollo missions)).
A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation

In “A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation,” Luo and Larson propose a novel repeated route-then-schedule algorithm...
The Role of Timing and Management's Remediation Actions in Preventing Failed Remediation of Material Weaknesses in Internal Controls†

Prior research finds that signals of remediation of internal control weaknesses do not guarantee that all weaknesses are fully resolved. However, why certain remediation strategies fail is unclear. This study examines how remediation timing and actions affect the likelihood of a failed remediation. I find that the likelihood of a failed remediation is decreasing in both the time a company takes to remediate and in the extent of remediation actions employed. Importantly, this study documents that disclosures of material changes in internal control provide information useful in assessing the likelihood of a failed remediation, as well as evidence that prompt remediation does not necessarily result in a successful remediation. Moreover, I find that there are consequences to remediation failures in the form of a higher likelihood of management and board turnover. Finally, I find evidence that economic benefits of remediation found in prior research may be understated. This study can provide stakeholders with insights into how the nature, extent, and timing of a remediation strategy can reduce the likelihood of a failed remediation.
Experiences in LP-IoT: EnviSense Deployment of Remotely Reprogrammable Environmental Sensors

The advent of Low Power Wide Area Networks (LPWAN) has improved the feasibility of wireless sensor networks for environmental sensing across wide areas. We have built EnviSense, an ultra-low power environmental sensing system, and deployed over a dozen of them across two locations in Northern California for hydrological monitoring applications with the U.S. Geological Survey (USGS). This paper details our experiences with the design and implementation of this system across two years, including six months of continuous measurement in the field. We describe the lessons learned for deployment planning, remote device management and programming, and system co-design with a domain-expert from the USGS.
Flow-loss: learning cardinality estimates that matter

Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make mistakes, the goal should be to improve the estimates that make the biggest difference to an optimizer. We introduce a new loss function, Flow-Loss, that explicitly optimizes for better query plans by approximating the optimizer's cost model and dynamic programming search algorithm with analytical functions. At the heart of Flow-Loss is a reduction of query optimization to a flow routing problem on a certain plan graph in which paths correspond to different query plans. To evaluate our approach, we introduce the Cardinality Estimation Benchmark, which contains the ground truth cardinalities for sub-plans of over 16K queries from 21 templates with up to 15 joins. We show that across different architectures and databases, a model trained with Flow-Loss improves the cost of plans (using the PostgreSQL cost model) and query runtimes despite having worse estimation accuracy than a model trained with Q-Error. When the test set queries closely match the training queries, both models improve performance significantly over PostgreSQL and are close to the optimal performance (using true cardinalities). However, the Q-Error trained model degrades significantly when evaluated on queries that are slightly different (e.g., similar but not identical query templates), while the Flow-Loss trained model generalizes better to such situations. For example, the Flow-Loss model achieves up to 1.5x better runtimes on unseen templates compared to the Q-Error model, despite leveraging the same model architecture and training data.
Sector Bias and the Credibility of Performance Information: An Experimental Study of Elder Care Provision

Reporting government performance to the public is generally understood as a tool for improving accountability and transparency. However, evidence has shown that citizens’ anti public sector bias may discount good performance of public organizations. Using an experimental study of nursing homes in the US, this study fills four gaps in the literature: 1) the need to include nonprofit organizations rather than just public and private organizations, 2) consideration of the credibility of the source of performance information, 3) the use of existing less ambiguous performance metrics, and 4) the willingness to use organizational services as a performance dimension. Our results show that the public has a general but modest anti-for-profit sector bias in nursing home care (nonprofits are perceived the most positively). Sector biases generally disappear when commonly used government performance data are presented. Also, the credibility of the source matters, and respondents’ willingness to use organizational services is more sensitive to both sector bias and performance information than other performance measures such as effectiveness, efficiency, red tape or equity. The paper concludes with a discussion of the implications of this study for democratic accountability.
Minimum-Distortion Embedding

We consider the vector embedding problem. We are given a finite set of items, with the goal of assigning a representative vector to each one, possibly under some constraints (such as the collection of vectors being standardized, i.e., have zero mean and unit covariance). We are given data indicating that some pairs of items are similar, and optionally, some other pairs are dissimilar. For pairs of similar items, we want the corresponding vectors to be near each other, and for dissimilar pairs, we want the corresponding vectors to not be near each other, measured in Euclidean distance. We formalize this by introducing distortion functions, defined for some pairs of the items. Our goal is to choose an embedding that minimizes the total distortion, subject to the constraints. We call this the minimum-distortion embedding (MDE) problem. The MDE framework is simple but general. It includes a wide variety of embedding methods, such as spectral embedding, principal component analysis, multidimensional scaling, dimensionality reduction methods (like Isomap and UMAP), force-directed layout, and others. It also includes new embeddings, and provides principled ways of validating historical and new embeddings alike. We develop a projected quasi-Newton method that approximately solves MDE problems and scales to large data sets. We implement this method in PyMDE, an open-source Python package. In PyMDE, users can select from a library of distortion functions and constraints or specify custom ones, making it easy to rapidly experiment with different embeddings. Our software scales to data sets with millions of items and tens of millions of distortion functions. To demonstrate our method, we compute embeddings for several real-world data sets, including images, an academic co-author network, US county demographic data, and single-cell mRNA transcriptomes.
Stimulated radiation from axion cluster evolution in static spacetimes

If their number density is high enough, clusters of axions can decay to photons via stimulated emission. We study both the special and general relativistic corrections to lasing in such dense axion clusters as they evolve in static spacetimes. Our main results are rate equations for the evolution of axion and photon number densities that include these corrections. We use Schwarzschild spacetime as a detailed example.
Smooth bubbling geometries without supersymmetry

We construct the first smooth bubbling geometries using the Weyl formalism. The solutions are obtained from Einstein theory coupled to a two-form gauge field in six dimensions with two compact directions. We classify the charged Weyl solutions in this framework. Smooth solutions consist of a chain of Kaluza-Klein bubbles that can be neutral or wrapped by electromagnetic fluxes, and are free of curvature and conical singularities. We discuss how such topological structures are prevented from gravitational collapse without struts. When embedded in type IIB, the class of solutions describes D1-D5-KKm solutions in the non-BPS regime, and the smooth bubbling solutions have the same conserved charges as a static four-dimensional non-extremal Cvetic-Youm black hole.
Quantification and image-derived phenotyping of retinal ganglion cell nuclei in the nee mouse model of congenital glaucoma.

Abstract The nee mouse model exhibits characteristic features of congenital glaucoma, a common cause of childhood blindness. The current study of nee mice had two components. First, the time course of neurodegeneration in nee retinal flat-mounts was studied over time using a retinal ganglion cell (RGC)-marker, BRN3A; a pan-nuclear marker, TO-PRO-3; and H&E staining. Based on segmentation of nuclei using ImageJ and RetFM-J, this analysis identified a rapid loss of BRN3A+ nuclei from 4 to 15 weeks of age, with the first statistically significant difference in average density compared to age-matched controls detected in 8-week-old cohorts (49% reduction in nee). Consistent with a model of glaucoma, no reductions in BRN3A− nuclei were detected, but the combined analysis indicated that some RGCs lost BRN3A marker expression prior to actual cell loss. These results have a practical application in the design of experiments using nee mice to study mechanisms or potential therapies for congenital glaucoma. The second component of the study pertains to a discovery-based analysis of the large amount of image data with 748,782 segmented retinal nuclei. Using the automatedly collected region of interest feature data captured by ImageJ, we tested whether RGC density of glaucomatous mice was significantly correlated to average nuclear area, perimeter, Feret diameter, or MinFeret diameter. These results pointed to two events influencing nuclear size. For variations in RGC density above approximately 3000 nuclei/mm2 apparent spreading was observed, in which BRN3A− nuclei—regardless of genotype—became slightly larger as RGC density decreased. This same spreading occurred in BRN3A+ nuclei of wild-type mice. For variation in RGC density below 3000 nuclei/mm2, which only occurred in glaucomatous nee mutants, BRN3A+ nuclei became smaller as disease was progressively severe. These observations have relevance to defining RGCs of relatively higher sensitivity to glaucomatous cell death and the nuclear dynamics occurring during their demise.
The Constitution and Takings of Private Property

Lewis Evans and Neil Quigley argue in “Compensation for Takings of Private Property Rights and the Rule of Law” that New Zealand should affirm, either in the New Zealand Bill of Rights Act 1990 or in some other statute, a generic right to compensation for the taking of private property for public purposes. This paper argues that the enactment of such a right would be a mistake, for three reasons. First, no sound evidence has been presented that property rights in New Zealand are especially insecure. Evans and Quigley give a series of examples of alleged abuse of property rights, but this paper argues that many of these examples are not, as Evans and Quigley argue, either rule of law breaches or inefficient. Secondly, a generic right to compensation for takings would undermine reliance on existing property rights, and so would hurt rather than secure the rule of law. In jurisdictions that have affirmed a right to compensation for takings of property, imprecision about the limits of the right (particularly the distinction between general regulation and regulatory expropriation) is rife and significant. The uncertainty inherent in takings jurisprudence would be exacerbated by Evans and Quigley’s conception of takings, because their view of what constitutes a taking is extremely broad compared to existing constitutional principle and international precedent. Thirdly, there is no convincing evidence that a generic right to compensation for takings would cause rather than harm economic growth. The evidence and theory that developed economies can improve economic growth by increasing private property right protections is mixed. Even against the criterion of improving certainty of private property rights, a generic right to compensation for takings would be counterproductive and inferior to focusing attention on refining specific statutory regimes to protect private property.
VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning.

Recent advances in bioimaging have provided scientists a superior high spatial-temporal resolution to observe dynamics of living cells as 3D volumetric videos. Unfortunately, the 3D biomedical video analysis is lagging, impeded by resource insensitive human curation using off-the-shelf 3D analytic tools. Herein, biologists often need to discard a considerable amount of rich 3D spatial information by compromising on 2D analysis via maximum intensity projection. Recently, pixel embedding based cell instance segmentation and tracking provided a neat and generalizable computing paradigm for understanding cellular dynamics. In this work, we propose a novel spatial-temporal voxel-embedding (VoxelEmbed) based learning method to perform simultaneous cell instance segmenting and tracking on 3D volumetric video sequences. Our contribution is in four-fold: (1) The proposed voxel embedding generalizes the pixel embedding with 3D context information; (2) Present a simple multi-stream learning approach that allows effective spatial-temporal embedding; (3) Accomplished an end-to-end framework for one-stage 3D cell instance segmentation and tracking without heavy parameter tuning; (4) The proposed 3D quantification is memory efficient via a single GPU with 12 GB memory. We evaluate our VoxelEmbed method on four 3D datasets (with different cell types) from the ISBI Cell Tracking Challenge. The proposed VoxelEmbed method achieved consistent superior overall performance (OP) on two densely annotated datasets. The performance is also competitive on two sparsely annotated cohorts with 20.6\(\%\) and 2\(\%\) of data-set having segmentation annotations. The results demonstrate that the VoxelEmbed method is a generalizable and memory-efficient solution.
Developmental Regulation of Homeostatic Plasticity in Mouse Primary Visual Cortex.

Homeostatic plasticity maintains network stability by adjusting excitation, inhibition, or the intrinsic excitability of neurons, but the developmental regulation and coordination of these distinct forms of homeostatic plasticity remains poorly understood. A major contributor to this information gap is the lack of a uniform paradigm for chronically manipulating activity at different developmental stages. To overcome this limitation, we utilized Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) to directly suppress neuronal activity in layer (L) 2/3 of mouse primary visual cortex (V1) of either sex at two important developmental timepoints: the classic visual system critical period (CP, P24-29), and adulthood (P45-55). We show that 24 hours of DREADD-mediated activity suppression simultaneously induces excitatory synaptic scaling up and intrinsic homeostatic plasticity in L2/3 pyramidal neurons during the CP, consistent with previous observations using prolonged visual deprivation. Importantly, manipulations known to block these forms of homeostatic plasticity when induced pharmacologically or via visual deprivation also prevented DREADD-induced homeostatic plasticity. We next used the same paradigm to suppress activity in adult animals. Surprisingly, while excitatory synaptic scaling persisted into adulthood, intrinsic homeostatic plasticity was completely absent. Finally, we found that homeostatic changes in quantal inhibitory input onto L2/3 pyramidal neurons were absent during the CP but present in adults. Thus, the same population of neurons can express distinct sets of homeostatic plasticity mechanisms at different development stages. Our findings suggest that homeostatic forms of plasticity can be recruited in a modular manner according to the evolving needs of a developing neural circuit.Significance statement:Developing brain circuits are subject to dramatic changes in inputs that could destabilize activity if left uncompensated. This compensation is achieved through a set of homeostatic plasticity mechanisms that provide slow, negative feedback adjustments to excitability. Given that circuits are subject to very different destabilizing forces during distinct developmental stages, the forms of homeostatic plasticity present in the network must be tuned to these evolving needs. Here we developed a method to induce comparable homeostatic compensation during distinct developmental windows, and found that neurons in the juvenile and mature brain engage strikingly different forms of homeostatic plasticity. Thus, homeostatic mechanisms can be recruited in a modular manner according to the developmental needs of the circuit.
He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics

We investigate how well BERT performs on predicting factuality in several existing English datasets, encompassing various linguistic constructions. Although BERT obtains a strong performance on most datasets, it does so by exploiting common surface patterns that correlate with certain factuality labels, and it fails on instances where pragmatic reasoning is necessary. Contrary to what the high performance suggests, we are still far from having a robust system for factuality prediction.
Neural network-based order parameter for phase transitions and its applications in high-entropy alloys

Phase transition is one of the most important phenomena in nature and plays a central role in materials design. All phase transitions are characterized by suitable order parameters, including the order–disorder phase transition. However, finding a representative order parameter for complex systems is non-trivial, such as for high-entropy alloys. Given the strength of dimensionality reduction of a variational autoencoder (VAE), we introduce a VAE-based order parameter. We propose that the Manhattan distance in the VAE latent space can serve as a generic order parameter for order–disorder phase transitions. The physical properties of our order parameter are quantitatively interpreted and demonstrated by multiple refractory high-entropy alloys. Using this order parameter, a generally applicable alloy design concept is proposed by mimicking the natural mixing process of elements. Our physically interpretable VAE-based order parameter provides a computational technique for understanding chemical ordering in alloys, which can facilitate the development of rational alloy design strategies. A variational autoencoder-based order parameter is proposed and demonstrated on various high-entropy alloys, providing a computational technique for understanding chemical ordering in alloys. Ultimately, this has the potential to facilitate the development of rational alloy design strategies.
Sequential Equilibrium in Games of Imperfect Recall

Although the definition of sequential equilibrium can be applied without change to games of imperfect recall, doing so leads to arguably inappropriate results. We redefine sequential equilibrium so that the definition agrees with the standard definition in games of perfect recall while still giving reasonable results in games of imperfect recall. The definition can be viewed as trying to capture a notion of ex ante sequential equilibrium. The picture here is that players choose their strategies before the game starts and are committed to it, but they choose it in such a way that it remains optimal even off the equilibrium path. A notion of interim sequential equilibrium is also considered.
Predicting What You Already Know Helps: Provable Self-Supervised Learning

Self-supervised representation learning solves auxiliary prediction tasks (known as pretext tasks), that do not require labeled data, to learn semantic representations. These pretext tasks are created solely using the input features, such as predicting a missing image patch, recovering the color channels of an image from context, or predicting missing words, yet predicting this \textit{known} information helps in learning representations effective for downstream prediction tasks. This paper posits a mechanism based on approximate conditional independence to formalize how solving certain pretext tasks can learn representations that provably decrease the sample complexity of downstream supervised tasks. Formally, we quantify how the approximate independence between the components of the pretext task (conditional on the label and latent variables) allows us to learn representations that can solve the downstream task with drastically reduced sample complexity by just training a linear layer on top of the learned representation.
Data-driven geometric system identification for shape-underactuated dissipative systems.

Systems whose movement is highly dissipative provide an opportunity to both identify models easily and quickly optimize motions. Geometric mechanics provides means for reduction of the dynamics by environmental homogeneity, while the dissipative nature minimizes the role of second order (inertial) features in the dynamics. Here we extend the tools of geometric system identification to ``Shape-Underactuated Dissipative Systems (SUDS)'' -- systems whose motions are more dissipative than inertial, but whose actuation is restricted to a subset of the body shape coordinates. Many animal motions are SUDS, including micro-swimmers such as nematodes and flagellated bacteria, and granular locomotors such as snakes and lizards. Many soft robots are also SUDS, particularly those robots using highly damped series elastic actuators. Whether involved in locomotion or manipulation, these robots are often used to interface less rigidly with the environment. We motivate the use of SUDS models, and validate their ability to predict motion of a variety of simulated viscous swimming platforms. For a large class of SUDS, we show how the shape velocity actuation inputs can be directly converted into torque inputs suggesting that systems with soft pneumatic actuators or dielectric elastomers can be modeled with the tools presented. Based on fundamental assumptions in the physics, we show how our model complexity scales linearly with the number of passive shape coordinates. This offers a large reduction on the number of trials needed to identify the system model from experimental data, and may reduce overfitting. The sample efficiency of our method suggests its use in modeling, control, and optimization in robotics, and as a tool for the study of organismal motion in friction dominated regimes.
Evaluating the advantage of adaptive strategies for quantum channel distinguishability

Quantum strategies are a generalization of quantum channels, allowing for multiple interactions over multiple rounds. Here, the authors expand the resource theory of asymmetric distinguishability to quantum strategies. They find that adaptive, sequential strategies may offer an advantage over parallel ones in the discrimination of amplitude damping channels.
On the Origins of Lagrangian Hydrodynamic Methods

The intent of this paper is to discuss the history and origins of Lagrangian hydrodynamic methods for simulating shock driven flows. The majority of the pioneering research occurred within the Manhattan Project. A range of Lagrangian hydrodynamic schemes were created between 1943 and 1948 by John von Neumann, Rudolf Peierls, Tony Skyrme, and Robert Richtmyer. These schemes varied significantly from each other; however, they all used a staggered-grid and finite difference approximations of the derivatives in the governing equations, where the first scheme was by von Neumann. These ground-breaking schemes were principally published in Los Alamos laboratory reports that were eventually declassified many decades after authorship, which motivates us to document the work and describe the accompanying history in a paper that is accessible to the broader scientific community. Furthermore, we seek to correct historical omissions on the pivotal contributions made by Peierls and Skyrme to creating robust Lagrangian hydrodynamic methods for simulating shock driven flows. Understanding the history of Lagrangian hydrodynamic methods can help explain the origins of many modern schemes and may inspire the pursuit of new schemes.
F-IDEs with Features and VCs Designed to Assist Human Reasoning When Verification Fails

This paper summarizes our efforts to aid human reasoning when verification fails through the use of two distinct Formalization Integrated Development Environments (F-IDEs) that we have developed. Both environments are modular and facilitate reasoning about the full behavior of object-based code. The first environment, referred to as the web-IDE, has been used for several years to teach aspects of formal specification and verification, including why and where verification conditions (VCs) arise and how to use them when verification fails. The second F-IDE, RESOLVE Studio, remains experimental, but is a more fully-fledged environment backed by a sequent-based VC generator that produces VCs with fewer extraneous givens. While the environments and VC generation techniques are necessarily language specific, the principles of alternative VC generation methods, F-IDE features, and observations about their impact on novices and experienced users are more generally applicable.
Quantile Inverse Optimization: Improving Stability in Inverse Linear Programming

Although inverse linear programming (LP) has received increasing attention as a technique to identify an LP that can reproduce observed decisions that are originally from a complex system, the perf...
Analysis of mass-action systems by split network translation

We introduce the notion of corresponding a chemical reaction network to a split network translation, and use this novel process to extend the scope of existing network-based theory for characterizing the steady state set of mass-action systems. In the process of network splitting, the reactions of a network are divided into subnetworks, called slices, in such a way that, when summed across the slices, the stoichiometry of each reaction sums to that of the original network. This can produce a network with more desirable structural properties, such as weak reversibility and a lower deficiency, which can then be used to establish steady state properties of the original mass-action system such as multistationarity and absolute concentration robustness. We also present a computational implementation utilizing mixed-integer linear programming for determining whether a given chemical reaction network has a weakly reversible split network translation.
Physiologically Based Modeling of the Effect of Physiological and Anthropometric Variability on Indocyanine Green Based Liver Function Tests

Accurate evaluation of liver function is a central task in hepatology. Dynamic liver function tests (DLFT) based on the time-dependent elimination of a test substance provide an important tool for such a functional assessment. These tests are used in the diagnosis and monitoring of liver disease as well as in the planning of hepatobiliary surgery. A key challenge in the evaluation of liver function with DLFTs is the large inter-individual variability. Indocyanine green (ICG) is a widely applied test compound used for the evaluation of liver function. After an intravenous administration, pharmacokinetic (PK) parameters are calculated from the plasma disappearance curve of ICG which provide an estimate of liver function. The hepatic elimination of ICG is affected by physiological factors such as hepatic blood flow or binding of ICG to plasma proteins, anthropometric factors such as body weight, age, and sex, or the protein amount of the organic anion-transporting polypeptide 1B3 (OATP1B3) mediating the hepatic uptake of ICG. Being able to account for and better understand these various sources of inter-individual variability would allow to improve the power of ICG based DLFTs and move towards an individualized evaluation of liver function. Within this work we systematically analyzed the effect of various factors on ICG elimination by the means of computational modeling. For the analysis, a recently developed and validated physiologically based pharmacokinetics (PBPK) model of ICG distribution and hepatic elimination was utilized. Key results are (i) a systematic analysis of the variability in ICG elimination due to hepatic blood flow, cardiac output, OATP1B3 abundance, liver volume, body weight and plasma bilirubin level; (ii) the evaluation of the inter-individual variability in ICG elimination via a large \emph{in silico} cohort of n=100000 subjects based on the NHANES cohort with special focus on stratification by age, sex, and body weight; (iii) the evaluation of the effect of various degrees of cirrhosis on variability in ICG elimination. The presented results are an important step towards individualizing liver function tests by elucidating the effects of confounding physiological and anthropometric parameters in the evaluation of liver function via ICG.
Bromo(crotyl)(cyclopentadienyl)(nitrosyl)molybdenum

[133684-62-5] C9H12BrMoNO (MW 326.04) InChI = 1S/C5H5.C4H7.BrH.Mo.NO/c1-2-4-5-3-1;1-3-4-2;;;1-2/h1-5H;3-4H,1H2,2H3;1H;;/q;;;2*+1/p-1 InChIKey = SSVKDUPGRFDGND-UHFFFAOYSA-M (reagent for stereocontrolled synthesis of β-methyl homoallyl alcohols via crotyl addition to aldehydes) Physical Data: mp ∼150 °C (with dec). Solubility: sol most polar organic solvents; very sol methylene chloride. Form Supplied in: orange crystals; currently no commercial source. Handling, Storage, and Precautions: indefinitely stable at rt under nitrogen or argon. The crystals can be handled in air for short periods with no significant decomposition.
ADFET-a simple inexpensive power device

A new high-voltage power device, termed the ADFET for alloyed drain power MOSFET, provides an economical alternative to conventional power MOSFETs (epi-FETs) for many applications. Possessing qualities mid-way between a non-punchthrough (NPT) IGBT and an epitaxial power MOSFET, 1200 V ADFETs have on-voltages about half that of 1200 V epi-FETs and fall times of /spl sim/90 nsec. In addition, ADFET costs are dramatically lower than epi-FETs, not just because lower on-voltages reduce die sizes, but also because the floatzone (FZ) starting material is much less expensive than thick epitaxial layers. This paper discusses fabrication of the ADFET, provides actual 1200 V TO-220 device data with direct comparison to non-punchthrough IGBT and epitaxial power MOSFET data, and reviews MEDICI modeling performed to elucidate mechanisms.
Characterization of the products of DNA-directed DNA polymerases in oncogenic RNA viruses.

Several RNA tumour viruses contain an enzyme that synthesizes a DNA–RNA hybrid using the single stranded viral RNA as template. Hybridization experiments confirm that the DNA strand is complementary to the viral RNA.
Restoration of edges under Poisson noise using convex constraints with application to confocal microscopy

A new algorithm is presented which uses maximum likelihood (ML) estimation and convex constraints to restore edge information in a robust and accurate way for microscope images. The convex constraints are spatially variant bounds on the image intensities and the directions of gradients, and they are extracted from an image restored with strong smoothing constraints. The high resolution estimate is obtained by maximizing the ML objective under the convex constraints and relaxed smoothing, using conjugate gradient and constrained optimization techniques. Relaxed smoothing allows edges in the final estimate, while the bound constraints preserve the robustness of the estimate. The convex constraints can be considered as a generalization of the positivity constraint which has been widely used in image restoration. The method does not impose any constraints on the profile of the edges, and it compares favorably with first order Bayesian methods which are frequently used for edge enhanced restoration in medical imaging. The performance of the method is demonstrated by restoring an image obtained from a confocal microscope.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Cytosine Catalysis of Nitrosative Guanine Deamination and Interstrand Cross-Link Formation

Effects are discussed of the anisotropic DNA environment on nitrosative guanine deamination based on results of an ab initio study of the aggregate 3 formed by guaninediazonium ion 1 and cytosine 2. Within 3, the protonation of 2 by 1 is fast and exothermic and forms 6, an aggregate between betaine 4 (2-diazonium-9H-purin-6-olate) and cytosinium ion 5. Electronic structure analysis of 4 shows that this betaine is not mesoionic; only the negative charge is delocalized in the π-system while the positive charge resides in the σ-system. Potential energy surface exploration shows that both dediazoniation and ring-opening of betaine 4 in aggregate 6 are fast and exothermic and lead irreversibly to E-11, the aggregate between (E)-5-cyanoimino-4-oxomethylene-4,5-dihydroimidazole E-10 and 5. The computed pair binding energies for 3, 6, and E-11 greatly exceed the GC pair binding energy. While 1 can be a highly reactive intermediate in reactions of the “free nucleobase” (or its nucleoside and nucleotide), the cyano...
In vitro release and permeation of levobunolol from various transdermal formulations

Abstract Levobunolol (LB) is a potent β-blocker with proven antihypertensive activity. However, it has a short biological half-life and requires frequent dosing. To overcome these problems, the feasibility of systemic delivery of LB via the transdermal route was explored. A series of in vitro skin permeation studies of the drug were conducted at 37°C across hairless mouse skin. It was found that the skin permeation potential of LB free base was much higher than that of its hydrochloride salt. Release of LB from different systems showed a characteristic matrix diffusion-controlled Q vs t 1 2 linear relationship, whereas skin permeation profiles from all those systems showed a membrane permeation-controlled Q vs t linear relationship. The in vitro skin permeation flux values ranged from 1.09 to 60.92 μg/cm2 per h depending upon the system at a 5% (w/w) loading dose of LB base. Azone showed a skin permeation enhancing effect on LB at a 10% (w/w) concentration. The flux value obtained from an indirect in vivo method using a polyacrylate patch showed an excellent in vitro/in vivo correlation.
Lateral mobility of integral membrane proteins is increased in spherocytic erythrocytes

Alterations of glycoprotein distribution and lateral mobility in cell membranes can provide transmembrane signals for several membrane-related phenomena. Control of the transmembranous events has been ascribed to interaction between submembranous protein matrices (or 'cytoskeletons') and membrane glycoproteins. A consequence of such interaction would be differential inhibition of protein lateral diffusion in biological membranes. Measurements of the lateral diffusion coefficients of membrane proteins, in fact, have generally yielded values much less than were predicted for unhindered diffusion in a fluid bilayer. The mouse spherocytic erythrocyte, which lacks the major components of the normal erythrocyte membrane matrix (composed of spectrin, actin, bands 4.1 and 4.9 (ref. 16), in the nomenclature of Fairbanks et al.), provides a unique system for a direct evaluation of the effect of the matrix on protein lateral mobility. After using a modification of the technique of fluorescence redistribution after photobleaching (FRAP), we report here that membrane proteins diffuse about 50 times faster in spherocytic than in normal mouse erythrocytes.
Components and control of ribonucleotide reductase system of the rat.

Abstract The components of ribonucleotide reductase system of the Novikoff rat tumor are thioredoxin, thioredoxin reductase, and two components of ribonucleoside diphosphate reductase designated P1 and P2. Brief summaries are given of published (or submitted) purifications and descriptions of thioredoxin and thioredoxin reductase. A partial purification of P1 and P2 is described. Factors influencing the amount and activity of ribonucleotide reductase are discussed.
Enzymic hydrolysis of phosphonate esters

Summary Enzymes capable of hydrolyzing the 4-nitrophenyl monoester of phenylphosphonic acid, which has no isosteric analog in nature, to 4-nitrophenol and phenylphosphonate have been detected in plants, animals, and microorganisms. The mucosa of vertebrate small intestine is an especially rich source of this activity, which is also present in commercial preparations of alkaline phosphatase. Small but clear-cut differences in the properties of this enzyme and alkaline phosphatase suggest that the two activities do not reside in the same protein.
Effect of Seed Development Stage on Sphingolipid and Phospholipid Contents in Soybean Seeds

Glucosylceramide (GlcCer) and ceramide (Cer) are the predominant sphingolipids (SL) in soybeans. They have been recognized as functional components in plants and may have health benefits for humans. The objective of this study was to evaluate the changes in SL and phospholipid (PL) contents that occurred during seed development. Soybean seeds of three cultivars (IA1008, IA1010, and IA1014) were harvested at 5-day intervals from 28 days after flowering (DAF) to 68 DAF (mature seed). SL and PL contents of seeds were quantified using high-performance liquid chromatography (HPLC) with an evaporative light scattering detector (ELSD). SL and PL contents decreased significantly during seed development. Averaged across cultivars, Cer content on a dry weight basis decreased from 51.4 nmol/g at 28 DAF to 22.2 nmol/g at 68 DAF, whereas GlcCer content decreased from 522.8 nmol/g at 28 DAF to 135.8 nmol/g at 68 DAF. PL percentage of the total lipid decreased from 9.1% at 28 DAF to 3.5% at 68 DAF.
Interstitial pneumonitis associated with neoadjuvant leuprolide and nilutamide for prostate cancer

Nilutamide is a new synthetic nonsteroidal antiandrogen. Most clinical studies of nilutamide have evaluated its efficacy in the treatment of advanced prostate adenocarcinoma as monotherapy, or in combination with orchiectomy or a luteinizing hormone-releasing hormone agonist.1 Adverse reactions associated with nilutamide include gastrointestinal disturbances, problems with light to dark adaptation, alcohol intolerance and, rarely, interstitial pneumonitis.1 To our knowledge nilutamide induced interstitial pneumonitis during neoadjuvant hormone therapy has not been reported. We report a case of interstitial pneumonitis after neoadjuvant nilutamide and leuprolide for prostate cancer.
Microprecision interferometer test bed: first stabilized stellar fringes

This paper presents initial results that demonstrate the end-to-end operation of the Micro- Precision Interferometer (MPI) testbed. The testbed is a full-scale model of a future space- based interferometer, containing all the spacecraft and support systems necessary to perform an astrometric measurement. The primary objective of the testbed is to provide an end-to-end problem to evaluate and integrate new interferometer technologies, such as vibration isolation, structural quieting, active optics, and metrology systems. This paper shows initial testbed functionality in terms of the ultimate performance metric: stabilization of stellar fringes (from a pseudo star). The present incarnation of the evolving testbed uses a fringe tracker and pointing control subsystem to stabilize the fringe position to the 72 nm (RMS) level in the presence of the ambient laboratory seismic noise environment which is a factor of 10 higher than that expected on-orbit. These encouraging preliminary results confirm that the MPI testbed provides an essential link between the extensive ongoing ground-based interferometer technology development activities and the technology needs of future spaceborne interferometers.