cssi/SciSciGPT-SciSciNet huggingface dataset:
Cantharidin Biosynthesis and Function in Meloid Beetles

Publisher Summary Cantharidin, a teφenoid substance found in blister beetles, is among the most widely known insect natural products in the world. Its reputation derives principally from descriptions of its physiological activities, most notably as an aphrodisiac for humans and livestock, that are traced from oral history. Cantharidin is also the blistering agent that earned these bettles their common name. These diverse effects on humans are paralleled by activities that the beetles exploit in their reproduction and ecology. The chapter explores the latter perspective of cantharidin's role—the pheromonal and other adaptive functions of cantharidin in blister beetles. The chapter discusses the chemical and biosynthetic knowledge of cantharidin to build a foundation for understanding its ecological roles in blister beetles. The intriguing simplicity of the cantharidin structure belies not only the difficulties encountered establishing the details of its molecular structure but also the complexity of the metabolic process involved in its formation by blister beetles. Comparison of its structure to those of known metabolic origin readily suggests that this compound belongs to the terpenoid biosynthetic class of natural products.
Inositol polyphosphate 1-phosphatase from calf brain. Purification and inhibition by Li+, Ca2+, and Mn2+.

We recently identified an enzyme which we have designated inositol polyphosphate 1-phosphatase that hydrolyzes both inositol 1,3,4-trisphosphate (Ins-1,3,4-P3) and inositol 1,4-bisphosphate (Ins-1,4-P2), yielding inositol 3,4-bisphosphate and inositol 4-phosphate, respectively, as products (Inhorn, R. C., Bansal, V.S., and Majerus, P.W. (1987) Proc. Natl. Acad. Sci. U.S.A. 84, 2170-2174). We have now purified the inositol polyphosphate 1-phosphatase 3600-fold from calf brain supernatant. The purified enzyme has an apparent molecular mass of 44,000 daltons as determined by gel filtration and is free of other inositol phosphate phosphatase activities. The enzyme hydrolyzes Ins-1,4-P2 with an apparent Km of approximately 4-5 microM, while it degrades Ins-1,3,4-P3 with an apparent Km of approximately 20 microM. The enzyme hydrolyzes these substrates at approximately the same maximal velocity. Inositol polyphosphate 1-phosphatase shows a sigmoidal dependence upon magnesium ion, with 0.3 mM Mg2+ causing half-maximal stimulation. A Hill plot of the data is linear with a value of n = 1.9, suggesting that the enzyme binds magnesium cooperatively. Calcium and manganese inhibit enzyme activity, with 50% inhibition at approximately 6 microM. Lithium inhibits Ins-1,4-P2 hydrolysis uncompetitively with a Ki of approximately 6 mM. This mechanism of lithium inhibition is similar to that observed for the inositol monophosphate phosphatase (originally designated myo-inositol-1-phosphatase; Hallcher, L.M., and Sherman, W.R. (1980) J. Biol. Chem. 255, 10896-10901), suggesting that these two enzymes are related. Lithium also inhibits Ins-1,3,4-P3 hydrolysis with an estimated Ki of 0.5-1 mM.
Arbovirus Infections As Screening Tools for the Identification of Viral Immunomodulators and Host Antiviral Factors

RNA interference- and genome editing-based screening platforms have been widely used to identify host cell factors that restrict virus replication. However, these screens are typically conducted in cells that are naturally permissive to the viral pathogen under study. Therefore, the robust replication of viruses in control conditions may limit the dynamic range of these screens. Furthermore, these screens may be unable to easily identify cellular defense pathways that restrict virus replication if the virus is well-adapted to the host and capable of countering antiviral defenses. In this article, we describe a new paradigm for exploring virus-host interactions through the use of screens that center on naturally abortive infections by arboviruses such as vesicular stomatitis virus (VSV). Despite the ability of VSV to replicate in a wide range of dipteran insect and mammalian hosts, VSV undergoes a post-entry, abortive infection in a variety of cell lines derived from lepidopteran insects, such as the gypsy moth (Lymantria dispar). However, these abortive VSV infections can be "rescued" when host cell antiviral defenses are compromised. We describe how VSV strains encoding convenient reporter genes and restrictive L. dispar cell lines can be paired to set-up screens to identify host factors involved in arbovirus restriction. Furthermore, we also show the utility of these screening tools in the identification of virally encoded factors that rescue VSV replication during coinfection or through ectopic expression, including those encoded by mammalian viruses. The natural restriction of VSV replication in L. dispar cells provides a high signal-to-noise ratio when screening for the conditions that promote VSV rescue, thus enabling the use of simplistic luminescence- and fluorescence-based assays to monitor the changes in VSV replication. These methodologies are valuable for understanding the interplay between host antiviral responses and viral immune evasion factors.
Simple Simulation Model for Exploring the Effects of Solvent and Structure on Asphaltene Aggregation

Asphaltenes are operationally defined as the fraction of crude oil that is soluble in toluene but insoluble in n-heptane. According to the Yen-Mullins model, typical asphaltenes are relatively small molecules consisting of a single aromatic core flanked by aliphatic chains. The Yen-Mullins model posits that asphaltene aggregation proceeds via a hierarchical mechanism involving small nanoaggregates with stacked aromatic cores surrounded by a corona of aliphatic tails. In this work, we introduce a coarse-grained (CG) model for investigating the physical picture underlying the Yen-Mullins model and, more generally, the effects of the solvent character and molecular structure upon asphaltene self-assembly. By representing proposed asphaltenes in united atom detail, this CG model accurately describes their shape and conformational properties. Conversely, the CG model mimics varying solvent conditions by modulating the effective attraction between aliphatic and aromatic groups. Given the simplicity of this model, we performed long, replicate simulations of 147 different asphaltene solutions. As proposed by the Yen-Mullins model, island-type molecules readily form stacked aggregates under conditions that promote aromatic interactions. Interestingly, the onset of nanoaggregation appears to be insensitive to the aliphatic tails, although these tails may sterically stunt further growth of nanoaggregates. Consequently, nanoaggregates form more readily and grow larger under conditions that promote both aliphatic and aromatic interactions. In contrast, archipelago-type molecules also form large aggregates, but they do not demonstrate significant stacking interactions. Thus, the CG model reasonably describes the physical intuition of the Yen-Mullins picture and may prove to be useful for exploring later stages of asphaltene aggregation.
Stimulation of the Posterior Cingulate Cortex Impairs Episodic Memory Encoding

Neuroimaging experiments implicate the posterior cingulate cortex (PCC) in episodic memory processing, making it a potential target for responsive neuromodulation strategies outside of the hippocampal network. However, causal evidence for the role that PCC plays in memory encoding is lacking. In human female and male participants (N = 17) undergoing seizure mapping, we investigated functional properties of the PCC using deep brain stimulation (DBS) and stereotactic electroencephalography. We used a verbal free recall paradigm in which the PCC was stimulated during presentation of half of the study lists, whereas no stimulation was applied during presentation of the remaining lists. We investigated whether stimulation affected memory and modulated hippocampal activity. Results revealed four main findings. First, stimulation during episodic memory encoding impaired subsequent free recall, predominantly for items presented early in the study lists. Second, PCC stimulation increased hippocampal gamma-band power. Third, stimulation-induced hippocampal gamma power predicted the magnitude of memory impairment. Fourth, functional connectivity between the hippocampus and PCC predicted the strength of the stimulation effect on memory. Our findings offer causal evidence implicating the PCC in episodic memory encoding. Importantly, the results indicate that stimulation targeted outside of the temporal lobe can modulate hippocampal activity and impact behavior. Furthermore, measures of connectivity between brain regions within a functional network can be informative in predicting behavioral effects of stimulation. Our findings have significant implications for developing therapies to treat memory disorders and cognitive impairment using DBS.SIGNIFICANCE STATEMENT Cognitive impairment and memory loss are critical public health challenges. Deep brain stimulation (DBS) is a promising tool for developing strategies to ameliorate memory disorders by targeting brain regions involved in mnemonic processing. Using DBS, our study sheds light on the lesser-known role of the posterior cingulate cortex (PCC) in memory encoding. Stimulating the PCC during encoding impairs subsequent recall memory. The degree of impairment is predicted by stimulation-induced hippocampal gamma oscillations and functional connectivity between PCC and hippocampus. Our findings provide the first causal evidence implicating PCC in memory encoding and highlight the PCC as a favorable target for neuromodulation strategies using a priori connectivity measures to predict stimulation effects. This has significant implications for developing therapies for memory diseases.
When Leverage Ratio Meets Derivatives: Running Out Of Options?

This paper examines the impact of Basel III leverage ratio on the competitive landscape of US derivatives markets. Because the leverage ratio focuses on notional amounts and does not fully recognize offsetting positions and risk-mitigating collateral, it is more likely the binding constraint for derivatives. The leverage ratio also put heterogeneous constraints on different types of institutions and activities. Using daily positions of clearing members and their customers on SP (2) US banks lose market share to European banks; (3) banks' clearing activities shift away from customer accounts to house accounts; (4) low-delta options are affected most by the leverage ratio. All hypotheses are confirmed in the data. Short-dated US Treasury futures options, which receive zero exposure in the leverage ratio calculation, do not exhibit such behavior. Our evidence suggests that the leverage ratio requirement pushes derivatives activities toward less constrained institutions and market segments.
T and B lymphocytes in fibrosis and systemic sclerosis.

Purpose of reviewTo summarize recent advances in the understanding of the pathogenesis of autoimmune fibrotic diseases. These diseases include IgG4-related disease, systemic sclerosis and lupus nephritis.Recent findingsRecent studies indicate that a poorly studied subset of helper T cells, cytotoxic
Big Data in IoT

The Internet of Things is generating an enormous amount of data. Analyzing and managing that data requires programming and statistical approaches. Big Data technology operates on this massive data and pushes new products, applications, future research and developments to improve decision making. In this paper, we explore Big data in IoT driven technologies and the issue of the four V's in Big Data. This paper also highlights the importance of pre-processing, metadata, data storage formats, data management and how big data is closely associated with IoT technologies. Today, with the rapid growth of IoT, everything is connected. To stay ahead of demands, new technologies such as Cloud Computing and Edge Computing are transforming IoT organizations. This paper discusses in which layers edge computing operates in the IoT reference model to achieve low-latency and greater efficiency solutions. This paper also reviews the IoT reference model layers that are associated with cloud computing, the structure of cloud computing architecture, data acquisition and data cleaning. This paper also discusses on various cloud-based IoT platforms such as AWS, Google Cloud IoT, Microsoft Azure, and Cisco IoT Cloud. We examined the importance of Big Data visualization, gives insights on various visualization tools and techniques. Lastly, this paper also addresses various significant challenges of Big Data in IoT, security issues and future research directions.
Structure-guided discovery of a single-domain antibody agonist against human apelin receptor.

Developing antibody agonists targeting the human apelin receptor (APJ) is a promising therapeutic approach for the treatment of chronic heart failure. Here, we report the structure-guided discovery of a single-domain antibody (sdAb) agonist JN241-9, based on the cocrystal structure of APJ with an sdAb antagonist JN241, the first cocrystal structure of a class A G protein–coupled receptor (GPCR) with a functional antibody. As revealed by the structure, JN241 binds to the extracellular side of APJ, makes critical contacts with the second extracellular loop, and inserts the CDR3 into the ligand-binding pocket. We converted JN241 into a full agonist JN241-9 by inserting a tyrosine into the CDR3. Modeling and molecular dynamics simulation shed light on JN241-9–stimulated receptor activation, providing structural insights for finding agonistic antibodies against class A GPCRs.
Voltage Source Inverter Control in Peak Shaving Applications for Power Quality Enhancement

In this paper, a control scheme is developed for a Voltage Source Inverter (VSI) used in peak shaving applications. The developed control first allows the VSI to reduce the power consumption from the grid during peak demand. Secondly, the control strategy allows the VSI to mimic the Power Factor (PF) correction feature usually achieved by capacitor banks and, finally, inherits the capabilities of active harmonic filters to suppress the harmonic content in the line current. The proposed control strategy is developed using MATLAB/Simulink and validated experimentally with the VSI connected to the grid in parallel with non-linear loads. The control scheme was validated under two different operation scenarios: under high Total Harmonic Distortion (THD) and under low power factor conditions. The presented analysis highlights the overall power quality improvements attained from the control strategy when interfacing the VSI with the grid and the peak shaving system.
Long‐term oncologic outcomes of robotic and open pancreatectomy in a national cohort of pancreatic adenocarcinoma

Background Robotic pancreatectomy is gaining momentum; however, limited data exist on the long-term survival of this approach for pancreatic ductal adenocarcinoma (PDAC). The objective of this study is to compare the long-term oncologic outcomes of robotic pancreaticoduodenectomy (RPD) and robotic distal pancreatectomy (RDP) to open surgery in patients with PDAC. Study design Robotic and open pancreatectomy for stages I-III PDAC were obtained from the 2010 to 2016 National Cancer Database. Results We identified 17 831 pancreaticoduodenectomies and 2718 distal pancreatectomies of which 626 (4%) and 332 (12%) were robotic, respectively. There was no difference in median overall survival between RPD (22.0 months) and open pancreatoduodenectomy (21.8 months; logrank P = .755). The adjusted hazard ratio [HR] was 1.014 (95% confidence interval [CI]: 0.903-1.139). The median overall survival for RDP (35.3 months) was higher than open distal pancreatectomy (ODP) (24.9 months; logrank P = .001). The adjusted HR suggests a benefit to RDP compared to ODP (HR, 0.744; 95% CI: 0.632-0.868) CONCLUSION: In a national cohort of resected pancreatic adenocarcinoma, the robotic platform was associated with similar long-term survival for pancreaticoduodenectomy, but improved survival for distal pancreatectomy.
An Optimization-Based Iterative Learning Control Design Method for UAV's Trajectory Tracking.

This paper presents an iterative learning control (ILC) design method to improve the unmanned aerial vehicle's (UAV's) tracking performance. ILC is a feedforward control method that aims to improve the tracking performance through learning from errors over iterations in repetitively operated systems. The tracking errors from previous iterations are injected into a learning module, which includes a learning filter and a robust filter, to generate the learning signal and to improve the tracking performance of the current iteration. This paper presents a two-step optimization based design method for these filters. As to the learning filter design, we transform it into a feedback controller design problem for a purposely constructed system. The formulated controller design problem is solved based on H-infinity optimal control theory. After the learning filter is designed, the robust filter is obtained by solving an additional H-infinity optimization problem. Through the proposed two-step optimization-based filter design method, the system's stability is guaranteed and the learning performance is optimized. The proposed filter design method and the regarding ILC algorithm are applied to the UAV's trajectory tracking system and are validated by numerical studies based on Gazebo, one high-fidelity simulation platform for UAVs.
Bayesian inference of heterogeneous epidemic models: Application to COVID-19 spread accounting for long-term care facilities.

Abstract We propose a high dimensional Bayesian inference framework for learning heterogeneous dynamics of a COVID-19 model, with a specific application to the dynamics and severity of COVID-19 inside and outside long-term care (LTC) facilities. We develop a heterogeneous compartmental model that accounts for the heterogeneity of the time-varying spread and severity of COVID-19 inside and outside LTC facilities, which is characterized by time-dependent stochastic processes and time-independent parameters in ∼ 1500 dimensions after discretization . To infer these parameters, we use reported data on the number of confirmed, hospitalized, and deceased cases with suitable post-processing in both a deterministic inversion approach with appropriate regularization as a first step, followed by Bayesian inversion with proper prior distributions. To address the curse of dimensionality and the ill-posedness of the high-dimensional inference problem, we propose use of a dimension-independent projected Stein variational gradient descent method , and demonstrate the intrinsic low-dimensionality of the inverse problem . We present inference results with quantified uncertainties for both New Jersey and Texas, which experienced different epidemic phases and patterns. Moreover, we also present forecasting and validation results based on the empirical posterior samples of our inference for the future trajectory of COVID-19.
Where Do Peacekeepers Go When They Go?: Explaining the Spatial Heterogeneity of Peacekeeping Deployments

Recent developments in the availability of spatial data and the growing trend of spatial analysis in political science has given scholars the ability to account for local-level factors in the study of political violence and conflict management. In this paper, the authors contribute to this growing body of literature by employing geo-coded data to empirically explore a question central to the study of peacekeeping – when peacekeepers are authorized to enter a conflict, where do they go? In other words, what types of violence are peacekeeping forces most concerned with, and what geographic features might prevent or allow for the deployment of peacekeepers? Using the un mission in the Democratic Republic of the Congo, the authors find that peacekeeping forces were less concerned with non-state violence (rebels fighting rebels) and instead focused on government-rebel confrontations and those instances in which government or rebels attacked unarmed civilians. In addition, peacekeepers are shown to cluster around transportation networks, densely populated areas, surface-based resources, and international borders.
Periodic Advertising Pulsing in a Competitive Market

The question as to the optimality of advertising pulsing has attracted many researchers since first posed by Vidale and Wolfe (1957). In this paper we specify a market share model in which there are two advertising setting firms as well as a no purchase state. The framework is one of a first order Markov process with three states. When the second brand is eliminated the framework collapses to exactly the discrete analog of the Vidale and Wolfe model. The objective of both firms is to maximize profits and a Nash equilibrium is sought. We are able to demonstrate, for a diminishing returns advertising function that the optimal advertising strategy is pulsing. The frequency of the advertising pulse is shown to depend on the magnitude of the market share retention rate (state dependence); the higher it is the less frequent the advertising. We further find that the optimal advertising budgets do not remain the same when the frequency of pulsing changes. Finally, we show that it is optimal for both firms to advertise in-phase.
The Relationship Between Executive Functioning, Type 1 Diabetes Self-Management Behaviors, and Glycemic Control in Adolescents and Young Adults

Understanding barriers to self-management behaviors and glycemic stability may inform specific needs for behavior change in adolescents and young adults with type 1 diabetes (T1D). The current review aims to systematically synthesize the literature on the relationships between executive functioning, self-management, and A1C in adolescents and young adults with T1D. Fifteen studies were retained in the current review. Study quality assessment for the majority of the studies were “Fair” or “Good.” This review highlights several advances in research design, including use of longitudinal designs, data from multiple informants, and use of objective measures. Adolescents and young adults reported that more executive functioning weaknesses were related to decreased self-management behaviors and higher A1C. The current review demonstrated that self-perceived executive functioning weaknesses negatively impact self-management behaviors and A1C. Future research is needed to determine the utility of objective measures in assessing the relationships between executive functioning, T1D self-management, and A1C.
A Deep Learning Approach for Predicting Spatiotemporal Dynamics From Sparsely Observed Data

In this paper, we consider the problem of learning prediction models for spatiotemporal physical processes driven by unknown partial differential equations (PDEs). We propose a deep learning framework that learns the underlying dynamics and predicts its evolution using sparsely distributed data sites. Deep learning has shown promising results in modeling physical dynamics in recent years. However, most of the existing deep learning methods for modeling physical dynamics either focus on solving known PDEs or require data in a dense grid when the governing PDEs are unknown. In contrast, our method focuses on learning prediction models for unknown PDE-driven dynamics only from sparsely observed data. The proposed method is spatial dimension-independent and geometrically flexible. We demonstrate our method in the forecasting task for the two-dimensional wave equation and the Burgers-Fisher equation in multiple geometries with different boundary conditions, and the ten-dimensional heat equation.
Driving β2- While Suppressing α-Adrenergic Receptor Activity Suppresses Joint Pathology in Inflammatory Arthritis.

Objective Hypersympathetic activity is prominent in rheumatoid arthritis, and major life stressors precede onset in ~80% of patients. These findings and others support a link between stress, the sympathetic nervous system and disease onset and progression. Here, we extend previous research by evaluating how selective peripherally acting α/β2-adrenergic drugs affect joint destruction in adjuvant-induced arthritis. Methods Complete Freund's adjuvant induced inflammatory arthritis in male Lewis rats. Controls received no treatment. Arthritic rats then received vehicle or twice-daily treatment with the α-adrenergic antagonist, phentolamine (0.5 mg/day) and the β2-adrenergic agonist, terbutaline (1200 µg/day, collectively named SH1293) from day (D) of disease onset (D12) through acute (D21) and severe disease (D28). Disease progression was assessed in the hind limbs using dorsoplantar widths, X-ray analysis, micro-computed tomography, and routine histology on D14, D21, and D28 post-immunization. Results On D21, SH1293 significantly attenuated arthritis in the hind limbs, based on reduced lymphocytic infiltration, preservation of cartilage, and bone volume. Pannus formation and sympathetic nerve loss were not affected by SH1293. Bone area and osteoclast number revealed high- and low-treatment-responding groups. In high-responding rats, treatment with SH1293 significantly preserved bone area and decreased osteoclast number, data that correlated with drug-mediated joint preservation. SH1293 suppressed abnormal bone formation based on reduced production of osteophytes. On D28, the arthritic sparing effects of SH1293 on lymphocytic infiltration, cartilage and bone sparing were maintained at the expense of bone marrow adipocity. However, sympathetic nerves were retracted from the talocrural joint. Conclusion and significance Our findings support a significant delay in early arthritis progression by treatment with SH1293. Targeting sympathetic neurotransmission may provide a strategy to slow disease progression.
Optimal temperature sensor placement in buildings with buoyancy-driven natural ventilation using computational fluid dynamics and uncertainty quantification

Abstract Natural ventilation and cooling can significantly reduce building energy consumption, but inherent variability in the boundary and operating conditions makes robust design and operation a challenging task. Computational models can be leveraged to evaluate the effects of these uncertainties and support robust design; however, the model accuracy should be thoroughly assessed, ideally through validation with carefully designed full-scale measurements. This study presents a novel approach for using computational fluid dynamics (CFD) simulations with uncertainty quantification to optimize temperature sensor placement in buildings with buoyancy-driven natural ventilation, such that the measurements are representative of the volume-averaged temperature, while also supporting analysis of the spatial variability in the temperature field. The approach uses a polynomial chaos expansion method to quantify the effect of the variability in the boundary and initial conditions on the predicted buoyancy-driven flow and indoor temperature field. Results for an operational building that employs night-time cooling are analyzed to identify sensor locations that will support robust observation of the time series of the volume-averaged temperature and the temperature range. The approach is shown to significantly reduce the potential error between the temperature recorded at a random location and the true volume-average temperature, while also providing a representative measure of the temperature range in the building. The results indicate that this approach can also support identifying optimal locations for temperature sensors used for operational control.
Impact self-assembly of low-binder-content geopolymer parts

Abstract In the current study, we produce low-binder-content geopolymer parts through impact self-assembly. After sand (the filler) and a small amount of fly ash-alkaline activator mixture (the binder) are premixed, they are impacted by a hammer in a drop tower. The hammer mass is around 2∼5 kg and the drop distance is 0.2∼0.8 m. The flexural strength of the cured material is ∼5 MPa, comparable to typical portland cement. The key processing parameter is the impact momentum of the hammer. Repeated impact improves the microstructural uniformity. The low binder content helps minimize the materials cost, reduce the carbon emission, and lower the demand of class F fly ash.
Proteolytic fragments of phosphoinositide-specific phospholipase C-delta 1. Catalytic and membrane binding properties.

Abstract Active proteolytic fragments of phosphoinositide-specific phospholipase C-delta 1 (PLC-delta 1) were generated by trypsin digestion of the native protein. Brief proteolysis produced a 77-kDa fragment that contained the highly conserved X and Y regions but lacked the amino-terminal domain (amino acids 1-60). Prolonged digestion of PLC-delta 1 produced two fragments, one of 45 kDa that contained the entire X region and another of 32 kDa that consisted of the entire Y region and COOH-terminal domain. The 45- and 32-kDa fragments were isolated as an active heterodimeric complex. The 77-kDa fragment and the complex catalyzed calcium-dependent hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) in detergent/phospholipid mixed micelles. When compared with the native enzyme, both the 77-kDa fragment and the complex exhibited a reduced capacity to processively hydrolyze PIP2; increasing the mole fraction of PIP2 in the mixed micelle surface greatly increased the rate of PIP2 hydrolysis catalyzed by the native enzyme but not the fragments. Both fragments also exhibited a reduced affinity for substrate; the native enzyme bound to bilayer vesicles consisting of phosphatidylcholine and PIP2 with high affinity (Ka approximately 10(6) M-1), whereas the fragments bound weakly (Ka < 10(4) M-1). These results demonstrate that the X, Y, and COOH-terminal regions form a calcium-dependent catalytic core that is resistant to proteolysis. The amino-terminal domain appears to be essential for high affinity binding to PIP2 but not catalysis. These observations are consistent with the idea that the amino-terminal domain forms part of a PIP2 binding site, which anchors PLC-delta 1 to the membrane surface during processive hydrolysis of its substrate.
Processing of type 1 plasminogen activator inhibitor (PAI-1) into the regulated secretory pathway.

To understand the processing of type 1 plasminogen activator inhibitor (PAI-1) into the storage granules of platelets, we utilized a eukaryotic expression vector (pRC/CMV) to transfer the human cDNA for PAI-1 into AtT-20 cells, a mouse pituitary cell line known to sort proteins in a regulated fashion. Immunofluorescence staining of PAI-1-transfected AtT-20 clones revealed co-localization of PAI-1 with an endogenously produced and stored hormone (i.e. adrenocorticotropic hormone, ACTH). Stimulation of PAI-1-transfected AtT-20 cells with a secretagogue resulted in the release of both active PAI-1 and the latent form. In comparison, PAI-1-transfected Chinese hamster ovary cells (i.e. a nonpackaging cell line) did not release PAI-1 in response to a secretagogue and exhibited immunoreactivity for PAI-1 primarily confined to the Golgi region. Percoll density gradient fractionation of AtT-20 cells revealed a codistribution of PAI-1 and ACTH in cellular compartments of the same density. The half-life of PAI-1 activity at 37 degrees C was prolonged in intact granules (t1/2, 5 h) in comparison with its half-life in lysed granules (t1/2, 2 h). These studies demonstrate the presence of a new functional property associated with the PAI-1 molecule that directs this inhibitor into the storage secretory pathway.
Risk and Return Trade-Offs in Partnering Strategies between Co-ops and IOFs

Changes in grain handling technologies and favorable terms on rail services are encouraging construction of state of the art grain handling facilities. Given these are high fixed and low marginal cost operations that are becoming increasingly vertically interdependent, the investments have substantial risks and opportunities. Partnerships are being formed to capitalize construction of fixed assets, provide a means to share specialized services, or to facilitate acquisitions or mergers. Given the mixture of corporate structures in this industry, including investor owned (IOF) and cooperatives, partnership agreement terms must accommodate the interest of a variety of stakeholder types. The purpose of this paper is to develop a financial model to evaluate classes of these partnerships and then compare distributions of risk and returns to each partner. A stochastic simulation model, specified as being highly representative of some contemporary partnerships, was developed for these purposes. Alternative partnership terms are specified and evaluated.
Combinatorial markov random fields

A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatorial Markov random fields (Comrafs), which are Markov random fields where some of the nodes are combinatorial random variables. We argue that Comrafs are powerful models for unsupervised and semi-supervised learning. We put Comrafs in perspective by showing their relationship with several existing models. Since it can be problematic to apply existing inference techniques for graphical models to Comrafs, we design two simple and efficient inference algorithms specific for Comrafs, which are based on combinatorial optimization. We show that even such simple algorithms consistently and significantly outperform Latent Dirichlet Allocation (LDA) on a document clustering task. We then present Comraf models for semi-supervised clustering and transfer learning that demonstrate superior results in comparison to an existing semi-supervised scheme (constrained optimization).
A Proposal for Extensions of PEARL to Facilitate the Formulation of Hard Real-Time Applications

Zur Formulierung zuverlassiger Software fur zeitkritische Anwendungen fehlen in den verfugbaren Prozesprogrammiersprachen problemorientierte Sprachkonstruktionen zur Synchronisation, zur Ereignisuberwachung und zum Ausdruck des Zeitverhaltens. Die Sprache Pearl wird deshalb durch geeignete Erweiterungen, deren Syntax und Semantik beschrieben werden, entsprechend angepast. Weiterhin werden bisher noch nicht realisierte Betriebssystemdienste, die fur ein zuverlassiges und genau vorhersehbares Programmverhalten notwendig sind, und die sie steuernden Anweisungen diskutiert. Die Implementation solcher Elemente durfte ein wichtiger Schritt hin auf dem Wege zur Ermoglichung der sicherheitstechnischen Abnahme von Software sein.
The Power of Self-Promotion: Twitter Followers and Guaranteed Purses in Professional Boxing, 2011-2013

The social media phenomenon has provided tremendous opportunities for self-promotion. From global pop star, Psy, reaching over 1.2 billion YouTube viewers (as of this writing) with his smash hit, “Gangnam Style” to recent college graduates “getting themselves out there” in the job market via Linkedin and Monster, the opportunities for greater self-actualization for the upwardly-mobile appear endless. Professional boxers have been savvy to ride the social media gravy train through a number of outlets. This study will focus on professional boxers’ use of one of these outlets, Twitter, as a determinant of their guaranteed purse for fights taking place over the period 2011-2013. As only the third study to utilize a multivariate regression in modeling the determinants of real-world purse data for professional boxers (Balbien, J., Noll, R. & Quirk, J., 1981; Chaplin, 2012a), this study contributes to an underdeveloped segment (that of the economics of professional boxing) of the ever-expanding sports economics field and analyzes the link between social media popularity and sport-specific pay in a way heretofore unexplored.
Highlights of FSS and array research at the Ohio State University ElectroScience laboratory

Periodic structures can be of the passive type excited by an incident plane wave or they can be of the active type where each element is driven by individual generators. The first type may be used as a frequency selective surface, the second as a phased array. The underlying physics of the two cases are discussed.
Edge-preserving image coding based on local modeling of images

A coding scheme which encodes each contiguous block of an image based on its local structure is developed. Three different types of models are constructed to characterize the image patterns occurring most frequently in a small block. The average bit rate is reduced by making use of the special constraint among the pixels in an oriented model, where the intensity variation is along only one direction. Judging from the image quality around edges, the reconstructed images with a bit rate less than 0.68 bit/pixel are perceptually superior to those obtained by the block and truncation coding at a bit rate of 1.64 bits/pixel. The complexity of this algorithm increases linearly with the size of the block and the number of orientations considered, which is much lower than that of the standard vector quantization techniques. >
Robust scheduling to hedge against processing time uncertainty in single-stage production

Schedulers confronted with significant processing time uncertainty often discover that a schedule which is optimal with respect to a deterministic or stochastic scheduling model yields quite poor performance when evaluated relative to the actual processing times. In these environments, the notion of schedule robustness, i.e., determining the schedule with the best worst-case performance compared to the corresponding optimal solution over all potential realizations of job processing times, is a more appropriate guide to schedule selection. In this paper, we formalize the robust scheduling concept for scheduling situations with uncertain or variable processing times. To illustrate the development of solution approaches for a robust scheduling problem, we consider a single-machine environment where the performance criterion of interest is the total flow time over all jobs. We define two measures of schedule robustness, formulate the robust scheduling problem, establish its complexity, describe properties of the optimal schedule, and present exact and heuristic solution procedures. Extensive computational results are reported to demonstrate the efficiency and effectiveness of the proposed solution procedures.
Rayleigh backscattering in a fiber gyroscope with limited coherence sources

Noise due to temporal fluctuations of Rayleigh baekscattered light in fiber-optical gyroscopes is studied experimentally with various sources whose coherence length is less than the fiber length. The reduction of the coherent fraction of backscattered light and its fluctuation frequencies with reduced source coherence is demonstrated and fit to an analytical model. Measured backscatter parameters for the fiber and sources used are presented.
Pain-related depression of the mesolimbic dopamine system in rats: expression, blockade by analgesics, and role of endogenous κ-opioids

Pain is often associated with depression of behavior and mood, and relief of pain-related depression is a common goal of treatment. This study tested the hypothesis that pain-related behavioral depression is mediated by activation of endogenous κ-opioid systems and subsequent depression of mesolimbic dopamine release. Adult male Sprague–Dawley rats were implanted with electrodes targeting the medial forebrain bundle (for behavior studies of intracranial self-stimulation (ICSS)) or with cannulae for microdialysis measures of nucleus accumbens dopamine (NAc DA). Changes in ICSS and NAc DA were examined after treatment with a visceral noxious stimulus (intraperitoneal injection of dilute lactic acid) or an exogenous κ-agonist (U69593). Additional studies examined the sensitivity of acid and U69593 effects to blockade by two analgesics (the nonsteroidal antiinflammatory drug ketoprofen and the μ-opioid agonist morphine) or by the κ-antagonist norbinaltorphimine (norBNI). The effects of acid were also examined on mRNA expression for prodynorphin (PDYN) and κ-opioid receptors (KORs) in mesocorticolimbic brain regions. Both acid and U69593 depressed ICSS and extracellular levels of NAc DA. Pain-related acid effects were blocked by ketoprofen and morphine but not by norBNI. The U69593 effects were blocked by norBNI but not by ketoprofen, and were only attenuated by morphine. Acid did not significantly alter PDYN or KOR in NAc, but it produced a delayed increase in PDYN in prefrontal cortex. These results support a key role for the mesolimbic DA system, but a more nuanced role for endogenous κ-opioid systems, in mediating acute pain-related behavioral depression in rats.
Crystallization and X-ray structure of full-length recombinant human butyrylcholinesterase.

Human butyrylcholinesterase (BChE) has been shown to function as an endogenous scavenger of diverse poisons. BChE is a 340 kDa tetrameric glycoprotein that is present in human serum at a concentration of 5 mg l−1. The well documented therapeutic effects of BChE on cocaine toxicity and organophosphorus agent poisoning has increased the need for effective methods of producing recombinant therapeutic BChE. In order to be therapeutically useful, BChE must have a long circulatory residence time or associate as tetramers. Full-length recombinant BChE produced in Chinese hamster ovary (CHO) cells or human embryonic kidney cells has been shown to associate as monomers, with a shorter circulatory residence time than the naturally occurring tetrameric serum protein. Based on the preceding observation as well as the need to develop novel methodologies to facilitate the mass production of therapeutic recombinant BChE, studies have been initiated to determine the structural basis of tetramer formation. Towards these ends, full-length monomeric recombinant BChE has been crystallized for the first time. A 2.8 A X-ray structure was solved in space group P4212, with unit-cell parameters a = b = 156, c = 146 A.
Crystal Chemical Constraints on the Formation of Actinide Pyrochlores

The pyrochlore structure type, A1−2 B2O6Y0−1 Fd3m Z=8, is a common constituent of polyphase, crystalline waste forms. Naturally occurring minerals with the same structure often occur in the radiation damaged, electron-diffraction amorphous, “metamict” state; and therefore, a principal concern with phases of this structure type is the effect of alpha-recoil damage associated with the presence of actinides. In this paper we outline crystal chemical constraints on the formation of novel actinide pyrochlores.
An exploration and comparison of the worklife experiences of registered nurses and physicians with permanent physical and/or sensory disabilities.

Purpose To examine the worklife experiences of physicians, to further the exploration of the worklife experiences of nurses with disabilities, and to discover how the two healthcare professions compare with each other with regard to these experiences. Methods This study employed the research tradition of interpretive naturalistic inquiry and used constant comparative analysis to collect and analyze the data. Findings Despite the cultural and educational differences between physicians and RNs, their experiences as healthcare professionals with self-identified permanent physical and/or sensory disabilities were very similar. The research team identified five core themes. Conclusions Healthcare professionals, including staff and administrators, need to make an effort to retain employees as turnover and predicted shortages are likely to jeopardize the current healthcare system. Clinical relevance Modifications can be made within both professions to support people with disabilities and to enable them to contribute to their professions using their abilities to think critically, solve problems, and care for patients safely.
Earthquake physics and real-time seismology.

The past few decades have witnessed significant progress in our understanding of the physics and complexity of earthquakes. This has implications for hazard mitigation.
Online focus groups used as an accessible participatory research method

Participatory research methods are being used internationally to gather data on complex social, cultural, and political concerns that effect the use of technology [4]. Researchers have found it difficult to include people with disabilities in these studies [5, 6, 7]. The Accessible Learning Through Text-to-Speech Project will utilize online focus groups as a method of integrating people with disabilities into a participatory research project. The Alt-Learning Project will have three primary target populations; users of screen readers with vision, users of screen readers who are blind, and professionals responsible for the delivery of assistive technology. The online focus groups will allow the observation and collection of data as a participant would normally utilize their screen reader applications at home, school, or workplace.
Performance of all-NbN superconductive tunnel junctions as mixers at 205 GHz

Small-area (1x1 sq micron) high-current-density NbN-MgO-NbN tunnel junctions with I-V characteristics suitable for high frequency mixers were fabricated. These junctions are integrated with superconducting microstrip lines designed to resonate out the large junction capacitance. The mixer gain and noise performance were studied near 205 GHz as a function of the inductance provided by the microstrip. This has yielded values of junction capacitance of 85 fF/sq microns and magnetic penetration depth of 3800 angstroms. Mixer noise as low as 133 K has been obtained for properly tuned junctions. This is the best noise performance ever reported for an NbN SIS mixer.
Optimization and Control of Mechatronic Systems

This plenary talk gives an overview of our research in optimization and control of mechatronic systems. In the first part of the talk, a convex program known as semidefinite program (SDP) will be presented. An SDP is an optimization problem with a linear objective function, and constraints on the eigenvalues of a linear matrix-valued function of the optimization variables. Key practical features of the SDP will be reviewed using mathematical language common to most control and automation engineers. The value of utilizing semidefinite programming in several important engineering problems will be discussed. In particular, it will be shown how SDP has facilitated advancements in the following areas: the design of estimation and control algorithms with fixed point arithmetic, the design of control laws with multiple specifications, the analysis of vibrations in turbomachinery components, and the design of state estimation algorithms with probability constraints on the state trajectories. In the second part of this talk, a (virtually) model-free optimization algorithm for control known as extremum seeking control (ESC) will be described. The ESC is based on the gradient method of nonlinear programming. The effectiveness of ESC to identify and track operating points of maximum performance of complex nonlinear mechatronic systems will be illustrated using a thermoacoustic cooling process. This talk will conclude with a personal perspective of growth opportunities for higher education in mechatronics and automation, which was developed essentially during my recent tenure as Program Director for Control Systems at the National Science Foundation.
Internal motions in an alternating copolymer of ethylene and tetrafluoroethylene

Internal motions in an alternating copolymer of ethylene and tetrafluoroethylene were investigated by dynamic mechanical and dielectric measurements and by nuclear magnetic resonance. At 1 Hz the α, β, and γ relaxations were observed at 110, −25, and −120°C in a quenched sample. The activation energy was 76 kcal/mole for the α relaxation and 10.6 kcal/mole for the γ relaxation. These relaxations are attributed to the motion of long and short segments in the amorphous regions, respectively. The β relaxation, which was observed only in the dynamic mechanical experiments, appears to occur in the crystalline regions. The copolymer is isomeric with poly(vinylidene fluoride), but it has a higher melting point and a much lower dielectric loss.