cssi/SciSciGPT-SciSciNet huggingface dataset:
Causal Multi-level Fairness

Algorithmic systems are known to impact marginalized groups severely, and more so, if all sources of bias are not considered. While work in algorithmic fairness to-date has primarily focused on addressing discrimination due to individually linked attributes, social science research elucidates how some properties we link to individuals can be conceptualized as having causes at macro (e.g. structural) levels, and it may be important to be fair to attributes at multiple levels. For example, instead of simply considering race as a causal, protected attribute of an individual, the cause may be distilled as perceived racial discrimination an individual experiences, which in turn can be affected by neighborhood-level factors. This multi-level conceptualization is relevant to questions of fairness, as it may not only be important to take into account if the individual belonged to another demographic group, but also if the individual received advantaged treatment at the macro-level. In this paper, we formalize the problem of multi-level fairness using tools from causal inference in a manner that allows one to assess and account for effects of sensitive attributes at multiple levels. We show importance of the problem by illustrating residual unfairness if macro-level sensitive attributes are not accounted for, or included without accounting for their multi-level nature. Further, in the context of a real-world task of predicting income based on macro and individual-level attributes, we demonstrate an approach for mitigating unfairness, a result of multi-level sensitive attributes.
Structure-guided microbial targeting of antistaphylococcal prodrugs

Carboxy ester prodrugs are widely employed to increase oral absorption and potency of phosphonate antibiotics. Prodrugging can mask problematic chemical features that prevent cellular uptake and may enable tissue specific compound delivery. However, many carboxy ester promoieties are rapidly hydrolyzed by serum esterases, limiting their therapeutic potential. While carboxy ester-based prodrug targeting is feasible, it has seen limited use in microbes as microbial esterase specific promoieties have not been described. Here we identify the bacterial esterases, GloB and FrmB, that activate carboxy ester prodrugs in Staphylococcus aureus. Additionally, we determine the substrate specificities for FrmB and GloB and demonstrate the structural basis of these preferences. Finally, we establish the carboxy ester substrate specificities of human and mouse sera, ultimately identifying several promoieties likely to be serum esterase-resistant and microbially labile. These studies will enable structure-guided design of anti-staphylococcal promoieties and expand the range of molecules to target staphylococcal pathogens.
An identity conflict perspective on female expatriate work adjustment

PurposeThis study aims to develop a model for female expatriate work adjustment from the identity conflict perspective.Design/methodology/approachThis is a theoretical paper that focuses on integrating the existing literature and proposing new constructive relationships.FindingsWe study female expatriates' adjustment processes in the work domain from the identity conflict perspective. Specifically, we categorize female expatriates' identities in the work domain into their gender identity and a work-related role identity cluster and propose that when gender identity is salient, unsupportive national and organizational cultures will lead to gender–work role identity conflicts and eventually result in maladjustment in the work domain.Originality/valueFirst, we suggest that female expatriates' work role identities can form a cluster that includes expatriate role, managerial role and occupational role identity. We further theorize how the gender role identity and the work-related role identity cluster of female expatriates interact to influence how they adjust to their work. Second, we explore two contingency factors – host organizational culture and host national culture–and explain how they influence the interaction between female expatriates' gender identity and work-related role identities. Finally, we introduce the concept of gender–work role identity conflict and theorize how it serves as the underlying mechanism linking female expatriate identity patterns and work adjustment.
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases

With the starting point that implicit human biases are reflected in the statistical regularities of language, it is possible to measure biases in English static word embeddings. State-of-the-art neural language models generate dynamic word embeddings dependent on the context in which the word appears. Current methods measure pre-defined social and intersectional biases that occur in contexts defined by sentence templates. Dispensing with templates, we introduce the Contextualized Embedding Association Test (CEAT), that can summarize the magnitude of overall bias in neural language models by incorporating a random-effects model. Experiments on social and intersectional biases show that CEAT finds evidence of all tested biases and provides comprehensive information on the variance of effect magnitudes of the same bias in different contexts. All the models trained on English corpora that we study contain biased representations. GPT-2 contains the smallest magnitude of overall bias followed by GPT, BERT, and then ELMo, negatively correlating with the contextualization levels of the models. Furthermore, we develop two methods, Intersectional Bias Detection (IBD) and Emergent Intersectional Bias Detection (EIBD), to automatically identify the intersectional biases and emergent intersectional biases from static word embeddings in addition to measuring them in contextualized word embeddings. We present the first algorithmic bias detection findings on how intersectional group members are strongly associated with unique emergent biases that do not overlap with the biases of their constituent minority identities. IBD achieves an accuracy of 81.6% and 82.7%, respectively, when detecting the intersectional biases of African American females and Mexican American females, where the random correct identification rates are 14.3% and 13.3%. EIBD reaches an accuracy of 84.7% and 65.3%, respectively, when detecting the emergent intersectional biases unique to African American females and Mexican American females, where the random correct identification rates are 9.2% and 6.1%. Our results indicate that intersectional biases associated with members of multiple minority groups, such as African American females and Mexican American females, have the highest magnitude across all neural language models.
Lineages of embryonic stem cells show non-Markovian state transitions

Pluripotent embryonic stem cells (ESCs) constitute the cell types of the adult vertebrate through a series of developmental state transitions. These states can be defined by expression levels of marker genes, such as Nanog and Sox2. In culture, ESCs reversibly transition between states. However, whether ESCs retain memory of their previous states or transition in a memoryless (Markovian) process remains relatively unknown. Here, we show some highly dynamic lineages of ESCs do not exhibit the Markovian property: their previous states and kin relations influence future choices. Unexpectedly, the distribution of lineages across their composition between states is constant over time, contrasting with the predictions of a Markov model. Additionally, highly dynamic ESC lineages show skewed cell fate distributions after retinoic acid differentiation. Together, these data suggest ESC lineage is an important variable governing future cell states, with implications for stem cell function and development.
Navigation using carrier Doppler shift from a LEO constellation: TRANSIT on steroids

A new global navigation concept is studied that relies on carrier Doppler shift measurements from a large LEO constellation. This system could provide an alternative to pseudorange-based GNSS. The concept uses a high-fidelity model of received carrier Doppler shift. This model is used in a point-solution batch filter that simultaneously estimates eight unknowns: the three position vector components, receiver clock offset, three velocity vector components, and receiver clock offset rate. The filter uses eight or more measured Doppler shifts in its least-squares fit. A generalized Geometric Dilution of Precision (GDOP) analysis indicates that absolute position accuracies on the order of 1-5 meters and absolute velocity accuracies on the order of 0.01 m/sec to 0.05 m/sec may be achievable if the range-rate precision of the Doppler shift measurements is 0.01 m/sec. These accuracies are comparable to current pseudorange-based GNSS. Clock offset accuracy is on the order of 0.0001 to 0.0010 sec 1-??.
Entity centric Feature Pooling for Complex Event Detection

In this paper, we propose an entity centric region of interest detection and visual-semantic pooling scheme for complex event detection in YouTube-like videos. Our method is based on the hypothesis that many YouTube-like videos involve people interacting with each other and objects in their vicinity. Based on this hypothesis, we first discover an Area of Interest (AoI) map in image keyframes and then use the AoI map for localized pooling of features. The AoI map is derived from image based saliency cues weighted by the actionable space of the person involved in the event. We extract the actionable space of the person based on human position and gaze based attention allocated per region. Based on the AoI map, we divide the image into disparate regions, pool features separately from each region and finally combine them into a single image signature. To this end, we show that our proposed semantically pooled image signature contains discriminative information that detects visual events favorably as compared to state of the art approaches.
Transfer learning for predicting virus-host protein interactions for novel virus sequences

Viruses such as SARS-CoV-2 infect the human body by forming interactions between virus proteins and human proteins. However, experimental methods to find protein interactions are inadequate: large scale experiments are noisy, and small scale experiments are slow and expensive. Inspired by the recent successes of deep neural networks, we hypothesize that deep learning methods are well-positioned to aid and augment biological experiments, hoping to help identify more accurate virus-host protein interaction maps. Moreover, computational methods can quickly adapt to predict how virus mutations change protein interactions with the host proteins. We propose DeepVHPPI, a novel deep learning framework combining a self-attention-based transformer architecture and a transfer learning training strategy to predict interactions between human proteins and virus proteins that have novel sequence patterns. We show that our approach outperforms the state-of-the-art methods significantly in predicting Virus-Human protein interactions for SARS-CoV-2, H1N1, and Ebola. In addition, we demonstrate how our framework can be used to predict and interpret the interactions of mutated SARS-CoV-2 Spike protein sequences. Availability: We make all of our data and code available on GitHub https://github.com/QData/DeepVHPPI.
Evaluation of the Feasibility and Perceived Value of Integrating Learn the Signs. Act Early. Developmental Monitoring Resources in Early Head Start

Many children with developmental disabilities are not identified before age 3 years of age, preventing them from being able to fully benefit from early intervention services. Early childhood educators, particularly those in Early Head Start (EHS) programs, are important partners in the early identification of children with developmental delays. Learn the Signs. Act Early. (LTSAE) is a program of the U.S. Centers for Disease Control and Prevention that provides free developmental monitoring resources to increase the early identification of children with developmental delays and disabilities. This paper presents findings from the first evaluation of the use of LTSAE resources in EHS, which was conducted across four states and 11 EHS programs from fall 2018 through spring 2019. Surveys (n = 448) and interviews (n = 39) with EHS management, staff, and parents indicated that LTSAE resources were valued and accepted, and their use in EHS considered feasible. Importantly, families and staff reported the LTSAE materials provided shared language to help them more effectively discuss development. These findings inform EHS and other early education programs that wish to enhance developmental monitoring, screening, and referral.
Algebraic characterizations of some relative notions of size

We obtain algebraic characterizations of relative notions of size in a discrete semigroup that generalize the usual combinatorial notions of syndetic, thick, and piecewise syndetic sets. “Filtered” syndetic and piecewise syndetic sets were defined and applied earlier by Shuungula et al. (Semigroup Forum 79:531–539, 2009). Other instances of these relative notions of size have appeared explicitly (and more often implicitly) in the literature related to the algebraic structure of the Stone–Cech compactification. Building on this prior work, we observe a natural duality and demonstrate how these notions of size may be composed to characterize previous notions of size (like piecewise syndetic sets) and serve as a convenient description for new notions of size.
Health benefits of local government sustainability efforts: A social cognitive perspective

Abstract Since climate change presents an unprecedented threat to public health, creating environmentally sustainable communi ties has become an important policy goal. Many local governments have voluntarily implemented sustainability practices to mitigate and adapt to climate change at community levels. Because of the potential benefits, scholars and practitioners are paying increasing attention to the sustainability practices of local government. This study provides evidence for their health benefits after analyzing data of more than 3000 older adults between 2012 and 2016. Our findings suggest that home weatherization assistance programs are associated with an increased likelihood that older adults will view life expectancy optimistically. Moreover, installing charging stations for electric vehicles is associated with increased physical activities. Our findings have important implications for local governments by linking climate change and community health issues.
Geobacter sulfurreducens inner membrane cytochrome CbcBA controls electron transfer and growth yield near the energetic limit of respiration.

Geobacter sulfurreducens utilizes extracellular electron acceptors such as Mn(IV), Fe(III), syntrophic partners, and electrodes that vary from +0.4 to -0.3 V versus standard hydrogen electrode (SHE), representing a potential energy span that should require a highly branched electron transfer chain. Here we describe CbcBA, a bc-type cytochrome essential near the thermodynamic limit of respiration when acetate is the electron donor. Mutants-lacking cbcBA ceased Fe(III) reduction at -0.21 V versus SHE, could not transfer electrons to electrodes between -0.21 and -0.28 V, and could not reduce the final 10%-35% of Fe(III) minerals. As redox potential decreased during Fe(III) reduction, cbcBA was induced with the aid of the regulator BccR to become one of the most highly expressed genes in G. sulfurreducens. Growth yield (CFU/mM Fe(II)) was 112% of WT in ∆cbcBA, and deletion of cbcL (an unrelated bc-cytochrome essential near -0.15 V) in ΔcbcBA increased yield to 220%. Together with ImcH, which is required at high redox potentials, CbcBA represents a third cytoplasmic membrane oxidoreductase in G. sulfurreducens. This expanding list shows how metal-reducing bacteria may constantly sense redox potential to adjust growth efficiency in changing environments.
Assured learning-enabled autonomy: A metacognitive reinforcement learning framework

Reinforcement learning (RL) agents with pre-specified reward functions cannot provide guaranteed safety across variety of circumstances that an uncertain system might encounter. To guarantee performance while assuring satisfaction of safety constraints across variety of circumstances, an assured autonomous control framework is presented in this paper by empowering RL algorithms with metacognitive learning capabilities. More specifically, adapting the reward function parameters of the RL agent is performed in a metacognitive decision-making layer to assure the feasibility of RL agent. That is, to assure that the learned policy by the RL agent satisfies safety constraints specified by signal temporal logic while achieving as much performance as possible. The metacognitive layer monitors any possible future safety violation under the actions of the RL agent and employs a higher-layer Bayesian RL algorithm to proactively adapt the reward function for the lower-layer RL agent. To minimize the higher-layer Bayesian RL intervention, a fitness function is leveraged by the metacognitive layer as a metric to evaluate success of the lower-layer RL agent in satisfaction of safety and liveness specifications, and the higher-layer Bayesian RL intervenes only if there is a risk of lower-layer RL failure. Finally, a simulation example is provided to validate the effectiveness of the proposed approach.
Intramolecular Charge Transfer in the Azathioprine Prodrug Quenches Intersystem Crossing to the Reactive Triplet State in 6-Mercaptopurine†.

The thiopurine prodrugs 6-mercaptopurine and azathioprine are among the world's essential medications for acute lymphoblastic leukemia, immunosuppression and several autoimmune conditions. Thiopurine prodrugs are efficient UVA absorbers and singlet oxygen generators and the long-term treatment with these prodrugs correlates with a high incidence of sunlight-induced skin cancer in patients. In this contribution, we show that the electronic relaxation mechanisms and photochemical properties of azathioprine are remarkably different from those of 6-mercaptopurine upon absorption of UVA radiation. UVA excitation of 6-mercaptopurine results in nearly 100% triplet yield and up to 30% singlet oxygen generation, whereas excitation of azathioprine with UVA leads to triplet yields of 15-3% depending on pH of the aqueous solution and <1% singlet oxygen generation. While photoexcitation of 6-mercaptopurine and other thiopurine prodrugs can facilitate oxidatively generated cell damage, azathioprine's poor photosensitization ability reveals the use of interchromophoric charge-transfer interactions for the molecular design of photostable prodrugs exhibiting a remarkable reduction in photocytotoxic side effects before drug metabolization.
Chen-Jiang decompositions for projective varieties, without Hodge modules

We give a new proof of a theorem by Pareschi, Popa and Schnell that the direct image of the canonical bundle of a smooth projective variety along a morphism to an abelian variety admits a Chen-Jiang decomposition, without using the theory of Hodge modules.
The Economics of Securities Regulation: A Survey

This paper reviews the academic literature that analyzes securities regulation from an economic perspective. It begins by describing the institutional foundations of securities law in the U.S. and distinguishing securities regulation from the private law of contracts, property, and fraud. Section 2 discusses the theoretical literature on mandatory versus voluntary disclosure in securities markets, focusing on information asymmetry and agency problems as justifications for mandatory disclosure. Section 3 surveys empirical work on the efficacy of actual mandatory disclosure rules. The remaining sections describe particular aspects of the U.S. regulatory system, including the regulation of public offerings, publicly-traded companies, trading markets, securities fraud, insider trading, market manipulation, and mutual funds and other collective investment vehicles, and surveys important theoretical and empirical work on each. The paper is intended to offer both institutional background and a summary of key research findings that may provide useful starting points for future research.
Sport Is for Everyone: A Legal Roadmap for Transgender Participation in Sport

Sport is a vehicle for social change and should be leveraged as such in 2021 and beyond to address matters of equality. In recent years, the public has paid greater attention to transgender athletes participating in sport at all levels—high school, collegiate, professional, and Olympic—despite the fact that transgender athletes have been competing in sports for decades. Backlash has arisen in general but also more specifically in response to several recent Supreme Court cases that have both solidified and extended rights of lesbian, gay, bisexual, transgender, and other gender and sexual minorities. In turn, state laws that seek to limit the rights of transgender students to participate in sports have been drafted around the country. To be sure, these laws are often built on erroneous data, a misunderstanding of facts, and ignorance, but their existence continues to fuel the public debate on whether transgender athletes should be allowed to participate based on their gender identity or their sex as determined at birth.
Logical Relations as Types: Proof-Relevant Parametricity for Program Modules

The theory of program modules is of interest to language designers not only for its practical importance to programming, but also because it lies at the nexus of three fundamental concerns in langu...
Dynamic Electrode-to-Image (DETI) mapping reveals the human brain's spatiotemporal code of visual information.

A number of neuroimaging techniques have been employed to understand how visual information is transformed along the visual pathway. Although each technique has spatial and temporal limitations, they can each provide important insights into the visual code. While the BOLD signal of fMRI can be quite informative, the visual code is not static and this can be obscured by fMRI’s poor temporal resolution. In this study, we leveraged the high temporal resolution of EEG to develop an encoding technique based on the distribution of responses generated by a population of real-world scenes. This approach maps neural signals to each pixel within a given image and reveals location-specific transformations of the visual code, providing a spatiotemporal signature for the image at each electrode. Our analyses of the mapping results revealed that scenes undergo a series of nonuniform transformations that prioritize different spatial frequencies at different regions of scenes over time. This mapping technique offers a potential avenue for future studies to explore how dynamic feedforward and recurrent processes inform and refine high-level representations of our visual world.
Caustics of Weakly Lagrangian Distributions

We study semiclassical sequences of distributions $$u_h$$ associated with a Lagrangian submanifold of phase space $$\mathcal {L}\subset T^*X$$ . If $$u_h$$ is a semiclassical Lagrangian distribution, which concentrates at a maximal rate on $$\mathcal {L},$$ then the asymptotics of $$u_h$$ are well understood by work of Arnol’d, provided $$\mathcal {L}$$ projects to X with a stable simple Lagrangian singularity. We establish sup-norm estimates on $$u_h$$ under much more general hypotheses on the rate at which it is concentrating on $$\mathcal {L}$$ (again assuming a stable simple projection). These estimates apply to sequences of eigenfunctions of integrable and KAM Hamiltonians.
Non-convergence of the spherical harmonic expansion of gravitational potential below the Brillouin sphere: The continuous case

For a singleton planet, P, with gravitational potential, V, we show that for each ɛ > 0, there exists a planet P′ with gravitational potential V′, with (P′, V′) “ɛ-close” to (P, V) (in an appropriate C0-sense), for which the spherical harmonic expansion of V′ does not extend more than a distance ɛ below the Brillouin sphere of P′.
Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning

This paper addresses outdoor terrain mapping using overhead images obtained from an unmanned aerial vehicle. Dense depth estimation from aerial images during flight is challenging. While feature-based localization and mapping techniques can deliver real-time odometry and sparse points reconstruction, a dense environment model is generally recovered offline with significant computation and storage. This paper develops a joint 2D-3D learning approach to reconstruct local meshes at each camera keyframe, which can be assembled into a global environment model. Each local mesh is initialized from sparse depth measurements. We associate image features with the mesh vertices through camera projection and apply graph convolution to refine the mesh vertices based on joint 2-D reprojected depth and 3-D mesh supervision. Quantitative and qualitative evaluations using real aerial images show the potential of our method to support environmental monitoring and surveillance applications.
Tailored generation of quantum states in an entangled spinor interferometer to overcome detection noise

We theoretically investigate how entangled atomic states generated via spin-changing collisions in a spinor Bose-Einstein condensate can be designed and controllably prepared for atom interferometry that is robust against common technical issues, such as limited detector resolution. We use analytic and numerical treatments of the spin-changing collision process to demonstrate that triggering the entangling collisions with a small classical seed rather than vacuum fluctuations leads to a more robust and superior sensitivity when technical noise is accounted for, despite the generated atomic state ideally featuring less metrologically useful entanglement. Our results are relevant for understanding how entangled atomic states are best designed and generated for use in quantum-enhanced matter-wave interferometry.
Characterizing partisan political narrative frameworks about COVID-19 on Twitter.

The COVID-19 pandemic is a global crisis that has been testing every society and exposing the critical role of local politics in crisis response. In the United States, there has been a strong partisan divide between the Democratic and Republican party's narratives about the pandemic which resulted in polarization of individual behaviors and divergent policy adoption across regions. As shown in this case, as well as in most major social issues, strongly polarized narrative frameworks facilitate such narratives. To understand polarization and other social chasms, it is critical to dissect these diverging narratives. Here, taking the Democratic and Republican political social media posts about the pandemic as a case study, we demonstrate that a combination of computational methods can provide useful insights into the different contexts, framing, and characters and relationships that construct their narrative frameworks which individual posts source from. Leveraging a dataset of tweets from the politicians in the U.S., including the ex-president, members of Congress, and state governors, we found that the Democrats' narrative tends to be more concerned with the pandemic as well as financial and social support, while the Republicans discuss more about other political entities such as China. We then perform an automatic framing analysis to characterize the ways in which they frame their narratives, where we found that the Democrats emphasize the government's role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses. Finally, we present a semantic role analysis that uncovers the important characters and relationships in their narratives as well as how they facilitate a membership categorization process. Our findings concretely expose the gaps in the "elusive consensus"" between the two parties. Our methodologies may be applied to computationally study narratives in various domains. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-021-00308-4."
A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods

The quality of a summarization evaluation metric is quantified by calculating the correlation between its scores and human annotations across a large number of summaries. Currently, it is not clear how precise these correlation estimates are, nor whether differences between two metrics' correlations reflects a true difference or if it is due to random chance. In this work, we address these two problems by proposing methods for calculating confidence intervals and running hypothesis tests for correlations using two resampling methods, bootstrapping and permutation. After evaluating which of the proposed methods is most appropriate for summarization through two simulation experiments, we analyze the results of applying these methods to several different automatic evaluation metrics across three sets of human annotations. We find that the confidence intervals are rather wide, demonstrating high uncertainty in how reliable automatic metrics truly are. Further, although many metrics fail to show statistical improvements over ROUGE, two recent works, QAEval and BERTScore, do in some evaluation settings.
Robust Auction Design in the Auto-bidding World

In classic auction theory, reserve prices are known to be effective for improving revenue for the auctioneer against quasi-linear utility maximizing bidders. The introduction of reserve prices, however, usually do not help improve total welfare of the auctioneer and the bidders. In this paper, we focus on value maximizing bidders with return on spend constraints -- a paradigm that has drawn considerable attention recently as more advertisers adopt auto-bidding algorithms in advertising platforms -- and show that the introduction of reserve prices has a novel impact on the market. Namely, by choosing reserve prices appropriately the auctioneer can improve not only the total revenue but also the total welfare. Our results also demonstrate that reserve prices are robust to bidder types, i.e., reserve prices work well for different bidder types, such as value maximizers and utility maximizers, without using bidder type information. We generalize these results for a variety of auction mechanisms such as VCG, GSP, and first-price auctions. Moreover, we show how to combine these results with additive boosts to improve the welfare of the outcomes of the auction further. Finally, we complement our theoretical observations with an empirical study confirming the effectiveness of these ideas using data from online advertising auctions.
Imaging the Maternal Rat Brain

This chapter discusses the technology and methods for performing imaging studies on awake dams during pup suckling. This unique experimental model allowed addressing three questions: Does pup suckling activate reward circuitry? Where is the cortical representation of nipple stimulation? What role does oxytocin (OT) play in suckling-induced brain activation? Technology and methods for imaging changes in brain activity in fully conscious rat dams in response to the onset of pup suckling involves a multiconcentric dual-coil, and small animal restrainer (insight neuroimaging systems), the basic configuration used for rat MR imaging. The BOLD fMRI signal is detected through the manipulation of precessing protons in the various brain tissue compartments when a subject is placed within an external magnetic field ( B 0 field provided by the MR scanner). Two radiofrequency coils, one for transmission and one for reception, facilitate the manipulation and detection of changes in proton resonant frequency, as an indirect measurement of the fMRI signal in vivo . Again, fMRI in conscious dams is ideally suited for providing an insight into this question of cortical representation of nipple stimulation during lactation. To address this issue, there is an imaging study using four stimulation conditions. In one condition, lactating dams were exposed to their pups for a 5-min stimulation period. In the second condition, a separate group of lactating dams were artificially suckled in the absence of pups. In the third condition, a separate group of lactating dams were exposed to gentle rubbing of the ventrum around the nipples with a flat edged wooden ruler. In the fourth condition, virgin females were exposed to this rubbing stimulus.
Partial G protein activation by fluorescent guanine nucleotide analogs. Evidence for a triphosphate-bound but inactive state

N-methyl-3'-O-anthranoyl (MANT) guanine nucleotide analogs are useful environmentally sensitive fluorescent probes for studying G protein mechanisms. Previously, we showed that MANT fluorescence intensity when bound to G protein was related to the degree of G protein activation where MANT-guanosine-5'-O-(3-thiotriphosphate) (mGTP gammaS) had the highest fluorescence followed by mGTP and mGDP, respectively (Remmers, A. E., Posner, R., and Neubig, R. R. (1994) J. Biol. Chem. 269, 13771-13778). To directly examine G protein conformations with nucleotide triphosphates bound, we synthesized several nonhydrolyzable MANT-labeled guanine nucleotides. The relative maximal fluorescence levels observed upon binding to recombinant myristoylated Goalpha (myrGoalpha) and myrGialpha1 were: mGTPgammaS > MANT-5'-guanylyl-imidodiphosphate > MANT-guanylyl-(beta,gamma-methylene)-diphosphonate > MANT-guanosine 5'-O-2-(thio)diphosphate. Using protection against tryptic digestion as a measure of the activated conformation, the ability of the MANT guanine nucleotides to maximally activate myrGo alpha correlated with maximal fluorescence. Biphasic dissociation kinetics were observed for all of the MANT guanine nucleotides. The data were consistent with the following model, [formula: see text] where G protein activation (G*-GXP) is determined by a conformational equilibrium between two triphosphate bound states as well as by the balance between binding and hydrolysis of the nucleotide triphosphate. Compared with myrGialpha1, maximal mGTP fluorescence was only 2-fold higher for the myrGialpha1 Q204L mutant, a mutant with greatly reduced GTPase activity, and only 24% that of mGTPgammaS, indicating that partial activation by mGTP was not just due to hydrolysis of mGTP. These results extend our previous conclusion that GTP analogs do not fully activate G protein.
Slow and Stopped Light in Coupled Resonator Systems

In the first part of this chapter, a theoretical overview is presented on the different approaches to the use of dynamic tuning for coherent optical pulse stopping and storage in coupled resonator systems, which are amenable to fabrication in on-chip devices such as photonic crystals. The use of such dynamic tuning overcomes the delay-bandwidth constraint of slow-light structures. The second part of this chapter presents a discussion on recent experimental work that has demonstrated the possibility of such dynamic tuning in on-chip systems.
Heat shock-induced prompt glycosylation. Identification of P-SG67 as calreticulin.

Abstract Acute heat shock initiates the phenomenon of "prompt" glycosylation, which is characterized by selective glycosylation of specific cellular proteins called the prompt stress glycoproteins (P-SG). Prompt glycosylation rapidly occurs even during short heating periods, e.g. 10 min at 45 degrees C, and is not affected by the presence of cycloheximide (Henle, K. J., Kaushal, G. P., Nagle, W. A., and Nolen, G. T. (1993) Exp. Cell Res. 207, 245-251). The major P-SG in Chinese hamster ovary cells, P-SG67, was characterized by an M(r) of 67,000 and a pI = 5.1. In the present study, we purified P-SG67 by sequential gel filtration, anion exchange, affinity chromatography with concanavalin A-Sepharose, and two-dimensional isoelectric focusing/SDS-polyacrylamide gel electrophoresis. The purified protein was digested and partially characterized by microsequencing of three major peptide fragments. The fragments, comprising a total of 46 amino acid residues, had an almost 100% sequence homology with calreticulin and partial homology with calnexin. Calcium binding studies with 45Ca2+ overlay confirmed that P-SG67 is a Ca(2+)-binding protein. These observations support the notion that P-SG67 is identical to calreticulin and that the glycosylation status of calreticulin can respond to environmental stress conditions.
Glutamate Receptor Activity Is Required for Normal Development of Tectal Cell Dendrites In Vivo

Glutamatergic retinotectal inputs mediated principally by NMDA receptors can be recorded from optic tectal neurons early during their morphological development in Xenopus tadpoles. As tectal cell dendrites elaborate, retinotectal synaptic responses acquire an AMPA receptor-mediated synaptic component, in addition to the NMDA component. Here, we tested whether glutamatergic activity was required for the elaboration of dendritic arbors in Xenopus optic tectal neurons. In vivo time-lapse imaging of single DiI-labeled neurons shows that the NMDA receptor antagonist APV (100 microM) blocked the early development of the tectal cell dendritic arbor, whereas the AMPA receptor antagonist CNQX (20 microM) or the sodium channel blocker TTX (1 microM) did not. The decreased dendritic development is attributable to failure to add new branches and extend preexisting branches. These observations indicate that NMDA-type glutamatergic activity promotes the initial development of the dendritic arbor. At later stages of tectal neuron development when AMPA receptor-mediated synaptic transmission is strong, both APV and CNQX decrease dendritic arbor branch length, consistent with a role for glutamatergic synaptic transmission in maintaining dendritic arbor structure. These results indicate that AMPA and NMDA receptors can differentially influence dendritic growth at different stages of neuronal development, in correlation with changes in the relative contribution of the receptor subtype to synaptic transmission.
Stable T-p53 complexes are not required for replication of simian virus 40 in culture or for enhanced phosphorylation of T antigen and p53.

Abstract We generated a number of simian virus 40 (SV40) mutants with single amino acid substitutions in T antigen between residues 388 and 411. All but one mutant (398LV) replicated like wild-type SV40 and gave rise to normal-size plaques. Three different mutations at residue 402 (Asp to Glu, Asn, or His) totally prevented the formation of stable complexes with the cellular protein p53 in monkey cells but had no effect on virus replication. Only one other mutation in this region, involving residue 401 (Met to Thr), slightly inhibited the formation of T-monkey p53 complexes. The three mutant T antigens with substitutions at residue 402 also formed no stable complexes with human p53 but generated low levels of complexes with mouse p53. These results indicate that residue 402 is critical for binding to monkey and human p53 proteins and is important for binding to mouse p53. We suggest that it is one of several points of contact. In cells infected with any one of the three residue 402 mutant viruses. T antigen and p53 became increasingly phosphorylated, as they were in cells infected with wild-type virus. Our data therefore show that stable T-p53 complexes are not required for replication of SV40 in culture or for enhanced phosphorylation of either protein.
Bloch radius, normal families and quasiregular mappings

Bloch’s Theorem is extended to K-quasiregular maps Rn → Sn, where Sn is the standard n-dimensional sphere. An example shows that Bloch’s constant actually depends on K for n ≥ 3. Let B(a, r) := {x ∈ Rn : |x − a| < r} be an open ball, 0 < r ≤ ∞. Consider an open discrete map f : B(0, r) → M where M is a Riemannian manifold of dimension n. For every x ∈ B(0, r) we define df (x) as the radius of the maximal open ball B ⊂ M centered at f(x), such that a continuous right inverse φ with the property φ(f(x)) = x exists in B. If there is no such ball df (x) = 0. The Bloch radius of f is defined as B(f) := sup x∈B(0,r) df (x). The cases of principal interest are M = Rn with the standard Euclidean metric |dx|, and M = Sn, the sphere with the standard spherical metric 2|dx|/(1 + |x|2), so that the diameter of the sphere in this metric is π. We denote the corresponding Bloch radii by Be(f) and Bs(f), respectively. Notice that Bs(f) ≤ 2Be(f), if we consider the push forward of the spherical metric to Rn via the stereographic projection. Notation B(f) will be used in statements which are true for both metrics. A family F of continuous maps B(0, r) → M is called normal if every sequence in F contains a subsequence which converges uniformly on compacta. In the case of compact M a family is normal if and only if its restriction to every compact in B(0, r) is equicontinuous [1]. The classical theorem of Bloch [3] can be stated as: ∗Supported by NSF grant DMS-9800084
Uranus and Neptune

Uranus and Neptune, were the first planets discovered by telescopic observation. They are of Jovian Planets similar size and much more massive than Earth (by factors of 14.5 and 17) but are still far less massive than Jupiter (by factors of 22 and 18). Both have deep atmospheres dominated by hydrogen, but unlike Jupiter and Saturn, most of their mass consists of rocky and icy components, which are in fluid form due to high interior temperatures. Both have ring systems, a diverse system of satellites, unusual tilted and offset magnetic fields, and similar atmospheric circulations. Their blue colors distinguish them from the pale tans of Jupiter and Saturn. But they also differ significantly from each other; they have very different obliquities (spin axis inclinations relative to their orbital planes), vastly different internal heat fluxes, and remarkably different weather patterns. These simularities and differences are discussed in detail in this article. Keywords: Uranus; Neptune; orbits; discovery; formation; interior structure; atmospheres; weather phenomena; satellite systems; rings; magnetic fields; magnetospheres
Particle Size Analysis in Food

Techniques are described for determining particle size in food dispersions involving food particles ranging in size from 0.1 to 1000 µm, where the presence of the particles confers special properties such as texture, appearance or flavor release. Those foods of plant origin that are cellular in nature are outside the scope of this article, as their structure is not under the control of the food manufacturer. The techniques described are used to a greater or lesser extent on foods, and they are all methods in use in other industrial sectors. The techniques are classified according to their underlying physical principle. Summary tables are provided to act as quick reference guides for a potential user of the technique. After the detailed descriptions, the final section groups those techniques relevant to a specific type of dispersion. The two most direct methods, microscopy and sieving, are discussed initially followed by three classes of optical technique, comparatively simple forward or back scattering, angular-dependent light scattering and dynamic light scattering. The next technique to be addressed is the electrical sensing zone originally developed by Coulter. Sedimentation techniques follow: gravitational sedimentation, centrifugal sedimentation and field-flow fractionation (FFF). All depend on the behavior of the particles in a force field that is balanced by viscous drag forces. The next two techniques are both acoustic in operation, either direct ultrasonic attenuation or electroacoustics. Finally, the novel applications based on nuclear magnetic resonance (NMR) are presented.
Externally mounted fibers for integrated optics interconnections.

A variety of input–output coupling problems remain central to the development of fiber and integrated optics communication systems. This paper discusses an externally mounted fiber consisting of a high index rectangular waveguide mounted on a larger low index support fiber. These fibers can be used to provide coupling between linear integrated optic guides and fibers or laser sources. Tapered (crossed-β) couplers are discussed in this context, and a simple expression for their coupling efficiency is presented. Externally mounted fibers have been fabricated, and experimental efficiencies of 70% for fiber–fiber and integrated optic linear waveguide–fiber coupling obtained.
Proximal Urinary Diversion in the Management of Posterior Urethral Valves: Is it Necessary?

AbstractPurpose: In infants with posterior urethral valves in whom renal function fails to normalize following decompression of the lower urinary tract supravesical urinary diversion is customarily recommended for presumed concomitant ureterovesical junction obstruction. We determined the true incidence of fixed or permanent ureterovesical junction obstruction and the renal prognosis for infants treated with proximal urinary diversion.Materials and Methods: We evaluated 26 patients with posterior urethral valves treated with supravesical urinary diversion. Mean gestational age at birth was 35 weeks (range 27 to 40). After initial decompression via an indwelling catheter for a median of 7 days (range 4 to 18) persistently high serum creatinine was present (median 2.5 mg./dl., range 1.9 to 3.5). One month after proximal urinary diversion median creatinine was 1.3 mg./dl. (range 0.5 to 2.8). At 1 year, median nadir creatinine was 1.0 mg./dl. (range 0.3 to 2.5). At reconstruction a Whitaker test in all 26 pat...
Propensity score analysis in the Genetic Analysis Workshop 17 simulated data set on independent individuals

Genetic Analysis Workshop 17 provided simulated phenotypes and exome sequence data for 697 independent individuals (209 case subjects and 488 control subjects). The disease liability in these data was influenced by multiple quantitative traits. We addressed the lack of statistical power in this small data set by limiting the genomic variants included in the study to those with potential disease-causing effect, thereby reducing the problem of multiple testing. After this adjustment, we could readily detect two common variants that were strongly associated with the quantitative trait Q1 (C13S523 and C13S522). However, we found no significant associations with the affected status or with any of the other quantitative traits, and the relationship between disease status and genomic variants remained obscure. To address the challenge of the multivariate phenotype, we used propensity scores to combine covariates with genetic risk factors into a single risk factor and created a new phenotype variable, the probability of being affected given the covariates. Using the propensity score as a quantitative trait in the case-control analysis, we again could identify the two common single-nucleotide polymorphisms (C13S523 and C13S522). In addition, this analysis captured the correlation between Q1 and the affected status and reduced the problem of multiple testing. Although the propensity score was useful for capturing and clarifying the genetic contributions of common variants to the disease phenotype and the mediating role of the quantitative trait Q1, the analysis did not increase power to detect rare variants.
Neurogenic bladder and chronic urinary retention associated with MDMA abuse.

Introduction The use of 3,4-methylenedioxymethamphetamine (MDMA, known as “ecstasy”), a synthetic amphetamine and “club drug,” has been associated with acute, transient urinary retention. We report a case of neurogenic bladder and chronic urinary retention associated with MDMA abuse.