cssi/SciSciGPT-SciSciNet huggingface dataset:
Heat Transfer Limitations in Hydrogen Production via Steam Reformation: The Effect of Reactor Geometry

Author(s): Vernon, David R.; Davieau, David D.; Dudgeon, Bryce A.; Erickson, Paul A. | Abstract: Proceedings of the ASME 4th International Conference on Fuel Cell Science, Engineering and Technology, Irvine, CA, June 19 - 21, 2006Hydrogen can be produced in a variety of methods including steam-reformation of hydrocarbon fuels. In past studies the quasi non-dimensional space velocity parameter (inverse residence time) has been shown to be insufficient in accurately predicting fuel conversion in hydrocarbon-steam reformation. Heat transfer limitations have been manifest with reactors of different geometries. In order to achieve ideal fuel conversion, the heat transfer limitations and the changes of these limitations with respect to geometry must be considered in the reactor design. In this investigation, axial and radial temperature profiles are presented from reactors of different aspect ratios while holding space velocity constant. Using both the temperature profile information as well as the traditional space velocity limitations one may be able to develop an optimal reactor design.
Low-pressure cesium and potassium diode pumped alkali lasers: pros and cons

This paper presents the results of our experiments on a comparative study of cesium and potassium diode pumped alkali lasers (DPALs) aimed to determine which of these two lasers has more potential to scale to high powers. For both lasers, we have chosen a “low-pressure DPAL approach,” which uses buffer gas pressure of about 1 atm for spin-orbit mixing of the excited states of alkali atoms to provide population inversion in the gain medium. The goal of this study was to determine power-limiting effects, which affect the performance of these DPALs, and find out how these limiting effects can be mitigated. We studied the performance of both lasers in CW and pulsed modes using both static and flowing gain medium and pump with different pulse duration. We observed output power degradation in time from the initial value to the level corresponding to the CW mode of operation. As a result of this study, some essential positive and negative features of both DPALs were revealed, which should be taken into account for power-scaling experiments.
Building Resource Adaptive Software Systems (BRASS): Objectives and System Evaluation

As modern software systems continue inexorably to increase in complexity and capability, users have become accustomed to periodic cycles of updating and upgrading to avoid obsolescence---if at some cost in terms of frustration. In the case of the U.S. military, having access to well-functioning software systems and underlying content is critical to national security, but updates are no less problematic than among civilian users and often demand considerable time and expense. To address these challenges, DARPA has announced a new four-year research project to investigate the fundamental computational and algorithmic requirements necessary for software systems and data to remain robust and functional in excess of 100 years. The Building Resource Adaptive Software Systems, or BRASS, program seeks to realize foundational advances in the design and implementation of long-lived software systems that can dynamically adapt to changes in the resources they depend upon and environments in which they operate. [1] MIT Lincoln Laboratory will provide the test framework and evaluation of proposed software tools in support of this revolutionary vision
Carbon efficiency of US colleges and universities: a nonparametric assessment

ABSTRACTUnder the American College and University Presidents’ Climate Commitment (ACUPCC), institutes of higher education have pledged to pursue a goal of carbon neutrality. We utilize emissions reported under the ACUPCC agreement and a nonparametric data envelopment analysis approach in order to evaluate the relative performance of signatories to the agreement in terms of producing teaching and research with the least greenhouse gas emissions. We find that while many signatory institutions are now producing their desirable outputs relatively efficiently in terms of carbon emissions, there still exists considerable variation in efficiency and potential for improvement. Results of a second stage efficiency change analysis shows evidence of both movement towards the efficiency frontier since signing, and some movement of the frontier itself, though this evidence comes primarily from teaching-focused institutions.
Two ways to auction off an uncertain good

An auction framework is examined where each seller is uncertain about whether or not he will have a good available to sell. A timely example includes the auctioning off of radio spectrum by licensed primary users to unlicensed secondary users. A licensed primary user may not use the spectrum all of the time, but may not know in advance whether or not he will need the spectrum himself and thus whether or not he will have spectrum bandwidth available to rent out. We consider two types of auctions: an ex-post auction which takes place after each seller learns about the availability of the good and an ex-ante auction which takes place before each seller learns about availability. The expected payoffs to buyers, sellers, and to society are then compared. The ex-ante auction can cause buyers to bid on multiple expected units to ensure that they end up with at least one actual unit. Such over purchasing can create a loss to society. Sellers will prefer the ex-post auction since if fewer units are actually available to sell, then they can be sold at a higher price. Whereas in the ex-ante auction all sellers have one expected unit available to sell which results in a lower price. However, if high value buyers are common, then a buyer may prefer the ex-ante auction as it can be easier to win an expected unit than an ex-post actual unit. In contrast, if a buyer has a high valuation and if high value buyers are uncommon, then he may prefer the ex-post auction since he has a strong chance to win an actual unit.
Habits vs Environment: What Really Causes Asthma?

Despite considerable number of studies on risk factors for asthma onset, very little is known about their relative importance. To have a full picture of these factors, both categories, personal and environmental data, have to be taken into account simultaneously, which is missing in previous studies. We propose a framework to rank the risk factors from heterogeneous data sources of the two categories. Established on top of EventShop and Personal EventShop, this framework extracts about 400 features, and analyzes them by employing a gradient boosting tree. The features come from sources including personal profile and life-event data, and environmental data on air pollution, weather and PM2.5 emission sources. The top ranked risk factors derived from our framework agree well with the general medical consensus. Thus, our framework is a reliable approach, and the discovered rankings of relative importance of risk factors can provide insights for the prevention of asthma.
Temporal Frequency of Soil Test Information Effects on Returns to Potassium Fertilization in Cotton Production

Little research exists on the optimal temporal frequency between soil tests, given empirical data on potassium (K) carryover and its interaction with cotton yield. We evaluate how decreasing the temporal frequency between obtaining K soil test information affects the net present value (NPV) of cotton production. Monte Carlo simulation was used to determine NPV for cotton production using five soil test schedules ranging from soil testing annually to every fifth year. NPV of returns to K was maximized at 2/ac. per year greater than annual soil testing.
Bayesian estimation of a decision using information theory

The problem of modeling the revision of the information of a decision maker based on the information of the expert sources is considered. The basic model assumes that the information of the decision maker and expert sources is in the form of the probability mass functions. The modeling approach is Bayesian estimation, which relies on Kullback entropy and Shannon entropy for information measurement, and produces a unique solution. Modeling of the problem not only considers information about the statistical dependence of the expert sources, but also uses information to measure the quality and importance of the individual expert sources in the form of rank ordering. The outcome shows that the effects of the dependence and rank ordering of the expert sources on the final decision cannot be isolated, In a special case where this isolation is possible, the effect of rank ordering decreases with the increase in the value of the correlation coefficient from -1 to +1, and the effect of the correlation never exceeds the effect of rank ordering. Sensitivity analysis is performed to explore other properties of the model related to the influence of the decision maker and expert sources. Extensions of the basic modeling to group decision making, group consensus, and mean value information are presented.
Inactivation of DFR (Dihydroflavonol 4-reductase) Gene Transcription Results in Blockage of Anthocyanin Production in Yellow Onions (Allium cepa)

Anthocyanin, one of the flavonoids, is a primary determinant of red color in onions. Inheritance studies indicate that a single gene determines the color difference between yellow and red onions. In order to establish which gene might be responsible for this color difference, full-length cDNAs of five structural genes: chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS), and flavonol synthase (FLS) were cloned using degenerate PCR and RACE (Rapid Amplification of cDNA Ends). RT-PCR was carried out for these five genes to examine differential expression between yellow and red colored bulbs. Accumulation of the DFR gene transcript only occurred in red onions. In F3 populations which originated from the cross between yellow and red parents, DFR transcript was detected only in red F3 lines. To design molecular markers for selection of yellow and red DFR alleles, the DFR gene was sequenced from genomic DNA isolated from both types of onions. The genomic DNA sequence revealed the DFR gene consists of six exons and five introns. A PCR-RFLP marker was designed based on 2% polymorphic nucleotide sequence of the DFR gene between yellow and red onions. The co-segregation of markers and red color were observed in F2 segregating populations, supporting the conclusion that color difference in red and yellow onions is likely to be due to the lack of an active DFR gene.
Ligand-Controlled Diastereoselective 1,3-Dipolar Cycloadditions of Azomethine Ylides with Methacrylonitrile

Copper-catalyzed reactions of glycine ester arylimines and methacrylonitrile provide selective access to either the endo or exo pyrrolidine cycloadducts. DFT calculations have elucidated the origins of ligand-controlled diastereoselectivity.
Accounting Conservatism, Aggregation, and Information Quality†

This paper demonstrates that conservative aggregation in accounting often improves the overall quality of information produced, and therefore enhances the welfare of accounting information users. We study the optimal accounting policy when a rm can control the quality of accounting information through costly and noncontractible action. In our model, the accounting system not only a¤ects the quality of reported information ex post, but also the quality of information generation ex ante. It is shown that the desirable accounting has two key features: (i) the accounting report aggregates, rather than reports directly, the underlying information; and (ii) the accounting has a conservative bias. By invoking conservative aggregation, which serves as a commitment to an apparently ine¢ cient accounting scheme given the ex post information quality, rms are induced to spend more e¤ort controlling information quality. In equilibrium, the level of conservatism might even increase with the opportunity loss associated with being overly prudent. JEL Classi cation: D81; M41; M48 We are grateful to two anonymous referees and the editor for valuable comments. We also wish to thank Gary Biddle, Qi Chen, Sunil Dutta, Jennifer Francis, Edward Riedl, Jim Wahlen, Yun Zhang, and participants at the 2005 UNC-Duke Fall Camp and the 2006 HKUST Summer Camp for comments and suggestions. yUniversity of California at Berkeley, fan@haas.berkeley.edu zUniversity of California at Berkeley, xzhang@haas.berkeley.edu
Structure and electronic spectra of purine-methyl viologen charge transfer complexes.

The structure and properties of the electron donor–acceptor complexes formed between methyl viologen and purine nucleosides and nucleotides in water and the solid state have been investigated using a combination of experimental and theoretical methods. Solution studies were performed using UV–vis and 1H NMR spectroscopy. Theoretical calculations were performed within the framework of density functional theory (DFT). Energy decomposition analysis indicates that dispersion and induction (charge-transfer) interactions dominate the total binding energy, whereas electrostatic interactions are largely repulsive. The appearance of charge transfer bands in the absorption spectra of the complexes are well-described by time-dependent DFT and are further explained in terms of the redox properties of purine monomers and solvation effects. Crystal structures are reported for complexes of methyl viologen with the purines 2′-deoxyguanosine 3′-monophosphate (DAD′DAD′ type) and 7-deazaguanosine (DAD′ADAD′ type). Compariso...
Gold network structures in rhombohedral and monoclinic Sr2Au6(Au,T)3 (T = Zn, Ga). A transition via relaxation.

Quantitative syntheses, structure determinations and interpretations, and band calculations are reported for the nonstoichiometric rhombohedral (R3c) and monoclinic (C2/c) Sr2Au6(Au3–xTx) (T = Zn, Ga) compounds. Several different compositions of the two Sr phases were similarly refined from single crystal X-ray diffraction data as R3c: a ≈ 8.43 A, c ≈ 21.85 A, Z = 6 and C2/c: a ≈ 14.70 A, b ≈ 8.47 A, c ≈ 8.70 A, β ≈ 123.2°, Z = 4. The R3c Zn phase is stable in the composition region x ∼ 2.5–2.9 whereas its C2/c neighbor is the major product at x ∼ 2.2–2.3. Gallium versions of both were also identified. Both R3c and C2/c structural types contain hexagonal-diamond-like gold superlattices stuffed with strings of interstitial Sr and disordered triangular (Au,T)3 units. The latter space group is a maximal, nonisomorphic subgroup of the former, and the decrease in interstitial radius from Ba to Sr (∼0.08 A experimentally) evidently drives the symmetry reduction, relaxation, and small distortions, principall...
Novel Roles for Peroxynitrite in Angiotensin II and CaMKII Signaling.

Ca2+/calmodulin-dependent protein kinase II (CaMKII) oxidation controls excitability and viability. While hydrogen peroxide (H2O2) affects Ca2+-activated CaMKII in vitro, Angiotensin II (Ang II)-induced CaMKIIδ signaling in cardiomyocytes is Ca2+ independent and requires NADPH oxidase-derived superoxide, but not its dismutation product H2O2. To better define the biological regulation of CaMKII activation and signaling by Ang II, we evaluated the potential for peroxynitrite (ONOO−) to mediate CaMKII activation and downstream Kv4.3 channel mRNA destabilization by Ang II. In vitro experiments show that ONOO− oxidizes and modestly activates pure CaMKII in the absence of Ca2+/CaM. Remarkably, this apokinase stimulation persists after mutating known oxidation targets (M281, M282, C290), suggesting a novel mechanism for increasing baseline Ca2+-independent CaMKII activity. The role of ONOO− in cardiac and neuronal responses to Ang II was then tested by scavenging ONOO− and preventing its formation by inhibiting nitric oxide synthase. Both treatments blocked Ang II effects on Kv4.3, tyrosine nitration and CaMKIIδ oxidation and activation. Together, these data show that ONOO− participates in Ang II-CaMKII signaling. The requirement for ONOO− in transducing Ang II signaling identifies ONOO−, which has been viewed as a reactive damaging byproduct of superoxide and nitric oxide, as a mediator of GPCR-CaMKII signaling.
Evaluation of Multiplanar Reconstruction in CT Recognition of Lumbar Disk Disease

Axial computed tomographic (CT) images were compared with sagittal and coronal reformations and myelograms in 60 patients to evaluate the diagnostic usefulness of multiplanar reconstructions for the recognition of lumbar disk disease. The axial CT scans were most sensitive and specific. The sagittal scans were helpful in evaluating the neural foramina, the size of the disk bulge into the spinal canal, especially at L5–51, and patients with spondylolisthesis. The coronal images were the least informative, although they contributed to the evaluation of lumbar nerve roots. The myelograms and the sagittal images were equally useful in the detection of herniated disk, but axial scans were superior to either. It was concluded that reformatted sagittal and coronal images are not required if all axial images are normal. However, when uncertainty exists or complex anatomy is being evaluated, reformatted images may be helpful, particularly for reassurance.
On the zero-divisor-cup-length of spaces of oriented isometry classes of planar polygons

Abstract Using information about the rational cohomology ring of the space M ( l 1 , … , l n ) of oriented isometry classes of planar n-gons with the specified side lengths, we obtain bounds for the zero-divisor-cup-length (zcl) of these spaces, which provide lower bounds for their topological complexity (TC). In many cases our result about the cohomology ring is complete and we determine the precise zcl. We find that there will usually be a significant gap between the bounds for TC implied by zcl and dimensional considerations.
Treatment of Parasitic Infections

This article provides an extensive table of drugs and dosages for treatment of parasitic infections, listing the treatment regimen most commonly used. This is followed by a list of the recommended drugs, their preparations, toxicity, contraindications, and precautions.
Designed sampling from large databases for controlled trials

ABSTRACTControlled trials are ubiquitously used to investigate the effect of a medical treatment. The trial outcome can be dependent on a set of patient covariates. Traditional approaches have relied primarily on randomized patient sampling and allocation to treatment and control groups. However, when covariate data for a large set of patients are available and the dependence of the outcome on the covariates is of interest, one can potentially design treatment/control groups that provide better estimates of the covariate-dependent effects of the treatment or provide similarly accurate estimates with a smaller trial cohort size. In this article, we develop an approach that uses optimal Design Of Experiments (DOE) concepts to select the patients for the treatment and control groups upfront, based on their covariate values, in a manner that optimizes the information content in the data. For the optimal treatment and control groups selection, we develop simple guidelines and an optimization algorithm that ach...
Interpenetrating Three-Dimensional Diamondoid Lattices and Antiferromagnetic Ordering (Tc = 73 K) of MnII(CN)2

Thermolysis of either the 3-D, bridged-layered [NEt4]MnII3(CN)7 or 2-D, layered [NEt4]2MnII3(CN)8 forms MnII(CN)2. Rietveld analysis of the high-resolution synchrotron powder X-ray diffraction data determined that MnII(CN)2 is cubic [a = 6.1488(3) A] (space group = Pn3m) consisting of two independent, interpenetrating networks having the topology of the diamond lattice. Each tetrahedrally coordinated MnII is bonded to four orientationally disordered cyanide ligands. MnII(CN)2 magnetically orders as an antiferromagnet with a Tc = 73 K determined from the peak in d(χT)/dT. Exchange coupling estimated via the mean field Heisenberg model from the transition temperature (J/kB = −4.4 K) and low temperature magnetic susceptibility of the ordered phase (J/kB = −7.2 K) indicate that MnII(CN)2 experiences weak antiferromagnetic coupling. The discrepancy between those estimates is presumably due to local anisotropy at the MnII sites arising from the CN orientational disorder or interactions between the interpenetra...
West Nile fever and West Nile encephalitis

West Nile virus is a mosquito-borne flavivirus, and maintained in mosquito-bird cycle in nature. Humans are a dead-end host in West Nile virus infection. Symptoms are developed in approximately 20% of West Nile virus-infected humans. Encephalitis and meningitis are developed in about 1 out of 150 infected humans, especially in elderly populations. It has recently been reported that West Nile virus causes polio-like, acute flaccid paralysis and polyneuritis. These symptoms occur in patients without central nervous system symptoms as well as in those with encephalitis. Thus, West Nile virus causes various types of illness in humans. West Nile virus has not entered Japan yet. However, West Nile virus should be considered to be one of the causative agents for patient with a febrile illness, meningitis, encephalitis or acute flaccid paralysis who came back from West Nile endemic or epidemic areas of the world.
Competition alters tree growth responses to climate at individual and stand scales

Understanding how climate affects tree growth is essential for assessing climate change impacts on forests but can be confounded by effects of competition, which strongly influences tree responses to climate. We characterized the joint influences of tree size, competition, and climate on diameter growth using hierarchical Bayesian methods applied to permanent sample plot data from the montane forests of Mount Rainier National Park, Washington State, USA, which are mostly comprised of Abies amabilis Douglas ex Forbes, Tsuga heterophylla (Raf.) Sarg., Pseudotsuga menziesii (Mirb.) Franco, and Thuja plicata Donn ex D. Don. Individual growth was sensitive to climate under low but not high competition, likely because tree ability to increase growth under more favorable climates (generally greater energy availability) was constrained by competition, with important variation among species. Thus, climate change will likely increase individual growth most in uncrowded stands with lower competition. However, crowde...
Predictive Modeling of Anatomy with Genetic and Clinical Data.

We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. Such predictive modeling promises to facilitate novel analyses in both voxel-level studies and longitudinal biomarker evaluation. We capture anatomical change through a combination of population-wide regression and a non-parametric model of the subject’s health based on individual genetic and clinical indicators. In contrast to classical correlation and longitudinal analysis, we focus on predicting new observations from a single subject observation. We demonstrate prediction of follow-up anatomical scans in the ADNI cohort, and illustrate a novel analysis approach that compares a patient’s scans to the predicted subject-specific healthy anatomical trajectory.
Consumers or Citizens? Whose Voice Will Healthwatch Represent and Will It Matter?; Comment on “Challenges Facing Healthwatch, a New Consumer Champion in England”

Efforts to achieve effective and meaningful patient and public involvement (PPI) in healthcare have existed for nearly a century, albeit with limited success. This brief commentary discusses a recent paper by Carter and Martin exploring the “Challenges Facing Healthwatch, a New Consumer Champion in England,” and places these challenges in the context of the broader struggle to give a voice to healthcare consumers and citizens. With an overview of what can go right and—perhaps more importantly—what can go wrong, the question remains: will Healthwatch—and other PPI efforts in healthcare—represent the voice of consumers or citizens and will it matter?
Economics of Variable Rate Planting for Corn

This analysis works out the economic implications for variable rate seeding of the corn population response curves estimated by Pioneer Hi-Bred agronomists. Examples are developed for various mixes of low, medium and high yield potential soil, as well as for a range of seed costs and variable rate equipment costs. The strategies analyzed were: variable rate planting using agronomic recommendations for each yield potential zone, variable rate planting using an economic decision rule for each yield potential zone, an information strategy which sets the uniform planting rate at the highest population indicated by agronomic recommendations for any part of the field and a second information strategy which uses an economic decision rule for the whole field based on potential in each yield zone. The economic decision rule sets the value of additional yield produced by adding a few more plants equal to the cost of planting a few extra seeds. Major assumptions of the analysis include: only corn is considered for variable rate planting, 1000 acres of corn are planted annually, the yield potential zones are small, irregularly shaped and interspersed so that changing population by field is ineffective, the zones are accurately mapped and corn price at harvest is $3/bu. The analysis does not include risk, alternative uses for low yield potential soil or the benefits of variable rate planting other than seed cost savings and matching population to the yield potential of the soil. The general conclusion is that variable rate seeding has profit potential only for farmers with some low yield potential land (<100 bu./a). Farmers with mix of medium and high potential land are better off with uniform rate seeding. The surprise is that variable rate seeding is potentially profitable when the proportion of low yield land is small. In the example, the farm with 10% low yield potential soil shows positive returns to variable rate planting. The results are not particularly sensitive to seed cost or variable rate investment cost.
The Influences of the Atlantic Multidecadal Oscillation on the Mean Strength of the North Pacific Subtropical High during Boreal Winter

AbstractThe Atlantic multidecadal oscillation (AMO) has been shown to be capable of exerting significant influences on the Pacific climate. In this study, the authors analyze reanalysis datasets and conduct forced and coupled experiments with an atmospheric general circulation model (AGCM) to explain why the winter North Pacific subtropical high strengthens and expands northwestward during the positive phase of the AMO. The results show that the tropical Atlantic warming associated with the positive AMO phase leads to a westward displacement of the Pacific Walker circulation and a cooling of the tropical Pacific Ocean, thereby inducing anomalous descending motion over the central tropical Pacific. The descending motion then excites a stationary Rossby wave pattern that extends northward to produce a nearly barotropic anticyclone over the North Pacific. A diagnosis based on the quasigeostrophic vertical velocity equation reveals that the stationary wave pattern also results in enhanced subsidence over the ...
Periodic Orbit-Attitude Solutions in the Planar Elliptic Restricted Three-Body Problem

The pitch motion of spacecraft in the planar elliptic restricted three-body system is studied. Previous studies laid the foundation for spacecraft stability analysis with a small perturbation to th...
Circuit breaker and transformer inspection and maintenance: probabilistic models

Circuit breakers and transformers are two of the most common components in the power system. Catastrophic failure of these components will result in high cost associated with the loss of load and component replacement. Preventive maintenance may reduce these costs by extending the components' lifetime and increasing availability. However, too much maintenance may be costly while too little maintenance may result in catastrophic failure. Probabilistic models that will include the effects of maintenance on reliability are needed to perform cost benefit analysis and arrive at an optimal maintenance strategy. A probabilistic maintenance model introduced earlier for power transformer is proposed for circuit breaker uses in this paper. The model is based on data coming from a study of deterioration process, maintenance tasks, and inspection tests for circuit breakers.
Dual origins of measured phase-amplitude coupling reveal distinct neural mechanisms underlying episodic memory in the human cortex

Phase-amplitude coupling (PAC) is hypothesized to coordinate neural activity, but its role in successful memory formation in the human cortex is unknown. Measures of PAC are difficult to interpret, however. Both increases and decreases in PAC have been linked to memory encoding, and PAC may arise due to different neural mechanisms. Here, we use a waveform analysis to examine PAC in the human cortex as participants with intracranial electrodes performed a paired associates memory task. We found that successful memory formation exhibited significant decreases in left temporal lobe and prefrontal cortical PAC, and these two regions exhibited changes in PAC within different frequency bands. Two underlying neural mechanisms, nested oscillations and sharp waveforms, were responsible for the changes in these regions. Our data therefore suggest that decreases in measured cortical PAC during episodic memory reflect two distinct underlying mechanisms that are anatomically segregated in the human brain.
Incentives to tax foreign investors

This paper shows that a small country can have an incentive to tax inbound FDI even in a setting with perfect competition and free entry that is compatible with the Diamond–Mirrlees (Am Econ Rev 61(1):8–27, 1971) framework. While firms make no aggregate profits worldwide due to free entry in this setting, they make taxable profits in foreign production locations because their costs are partly incurred in their home countries. These profits are not perfectly mobile because firm productivity varies across locations. Consequently, the host country does not bear the entire burden of a tax on foreign firms, giving rise to an incentive to tax foreign investors. The standard zero optimal tax result can be recovered in this model under an apportionment system that ensures zero economic profits in each location.
On the period of the periodic orbits of the restricted three body problem

We will show that the period T of a closed orbit of the planar circular restricted three body problem (viewed on rotating coordinates) depends on the region it encloses. Roughly speaking, we show that, $$2 T=k\pi +\int _\Omega g$$ where k is an integer, $$\Omega $$ is the region enclosed by the periodic orbit and $$g:{\mathbb {R}}^2\rightarrow {\mathbb {R}}$$ is a function that only depends on the constant C known as the Jacobian constant; it does not depend on $$\Omega $$ . This theorem has a Keplerian flavor in the sense that it relates the period with the space “swept” by the orbit. As an application we prove that there is a neighborhood around $$L_4$$ such that every periodic solution contained in this neighborhood must move clockwise. The same result holds true for $$L_5$$ .
On Scheduling Redundant Requests With Cancellation Overheads

Reducing latency in distributed computing and data storage systems is gaining increasing importance. Several empirical works have reported on the efficacy of scheduling redundant requests in such systems. That is, one may reduce job latency by: 1) scheduling the same job at more than one server and 2) waiting only until the fastest of them responds. Several theoretical models have been proposed to explain the power of using redundant requests, and all of the existing results rely heavily on a common assumption: all redundant requests of a job can be immediately cancelled as soon as one of them is completed. We study how one should schedule redundant requests when such assumption does not hold. This is of great importance in practice, since cancellation of running jobs typically incurs non-negligible delays. In order to bridge the gap between the existing models and practice, we propose a new queueing model that captures such cancellation delays. We then find how one can schedule redundant requests to achieve the optimal average job latency under the new model. Our results show that even with a small cancellation overhead, the actual optimal scheduling policy differs significantly from the optimal scheduling policy when the overhead is zero. Furthermore, we study optimal dynamic scheduling policies, which appropriately schedule redundant requests based on the number of jobs in the system. Our analysis reveals that for the two-server case, the optimal dynamic scheduler can achieve 7%–16% lower average job latency, compared with the optimal static scheduler.
Search for Neutrinoless Double Beta Decay in Xenon 136 with the Enriched Xenon Observatory (EXO)

resolved a puzzling mismatch between theory and a published limit [2]. Here we report on a search for neutrinoless double-beta decay of 136Xe with EXO-200 [3]. No signal is observed for a 136Xe exposure of 26.3 kg-yr, with a background of ∼ 1.5× 10−3 kg(enrLXe)−1yr−1keV−1 in the ±1σ region of interest. This sets a lower limit on the half-life of the neutrinoless double-beta decay T 0νββ 1/2 ( 136Xe) > 1.6 × 1025 yr (90% CL), corresponding to effective Majorana masses of
Structure and Spectroscopy of Transcurium Nuclei

The stability of the superheavy elements depends on the shell corrections which are governed by the single-particle spectra. Ideally one would like to experimentally determine the single-particle levels in the superheavy nuclei but the production of only a few atoms of these nuclides precludes such measurements. One therefore has to identify single-particle levels in the heaviest nuclei which are available in at least nanoCurie amounts. They have studied the structure of such heavy nuclei in the Z=98 region and identified many single-particle states. In particular, they have studied the structure of {sup 251}Cf and {sup 249}Bk by measuring the radiations emitted in the {alpha} decay of {sup 255}Fm and {sup 253}Es. These single-particle spectra can be used to test theoretical models for superheavy elements.
A computer architecture for intelligent machines

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems. >
Slow entropy for some smooth flows on surfaces

We study slow entropy in some classes of smooth mixing flows on surfaces. The flows we study can be represented as special flows over irrational rotations and under roof functions which are C2 everywhere except one point (singularity). If the singularity is logarithmic asymmetric (Arnol’d flows), we show that in the scale an(t) = n(log n)t slow entropy equals 1 (the speed of orbit growth is n log n) for a.e. irrational α. If the singularity is of power type (x−γ, γ ∈ (0, 1)) (Kochergin flows), we show that in the scale an(t) = nt slow entropy equals 1 + γ for a.e. α. We show moreover that for local rank one flows, slow entropy equals 0 in the n(log n)t scale and is at most 1 for scale nt. As a consequence we get that a.e. Arnol’d and a.e Kochergin flow is never of local rank one.
SenseGen: A deep learning architecture for synthetic sensor data generation

Our ability to synthesize sensory data that preserves specific statistical properties of the real data has had tremendous implications on data privacy and big data analytics. The synthetic data can be used as a substitute for selective real data segments - that are sensitive to the user - thus protecting privacy and resulting in improved analytics. However, increasingly adversarial roles taken by data recipients such as mobile apps, or other cloud-based analytics services, mandate that the synthetic data, in addition to preserving statistical properties, should also be “difficult” to distinguish from the real data. Typically, visual inspection has been used as a test to distinguish between datasets. But more recently, sophisticated classifier models (discriminators), corresponding to a set of events, have also been employed to distinguish between synthesized and real data. The model operates on both datasets and the respective event outputs are compared for consistency. Prior work on data synthesis have often focussed on classifiers that are built for features explicitly preserved by the synthetic data. This suggests that an adversary can build classifiers that can exploit a potentially disjoint set of features for differentiating between the two datasets. In this paper, we take a step towards generating sensory data that can pass a deep learning based discriminator model test, and make two specific contributions: first, we present a deep learning based architecture for synthesizing sensory data. This architecture comprises of a generator model, which is a stack of multiple Long-Short-Term-Memory (LSTM) networks and a Mixture Density Network (MDN); second, we use another LSTM network based discriminator model for distinguishing between the true and the synthesized data. Using a dataset of accelerometer traces, collected using smartphones of users doing their daily activities, we show that the deep learning based discriminator model can only distinguish between the real and synthesized traces with an accuracy in the neighborhood of 50%.
Minimizing the Age of Information in broadcast wireless networks

We consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients. The Age of Information (AoI), namely the amount of time that elapsed since the most recently delivered packet was generated, captures the freshness of the information. We formulate a discrete-time decision problem to find a scheduling policy that minimizes the expected weighted sum AoI of the clients in the network. To the best of our knowledge, this is the first work to provide a scheduling policy that optimizes AoI in a wireless network with unreliable channels. The results are twofold: first, we show that a Greedy Policy, which transmits the packet with highest current age, is optimal for the case of symmetric networks. Then, for the general network case, we establish that the problem is indexable and obtain the Whittle Index in closed-form. Numerical results are presented to demonstrate the performance of the policies.
STAGED BILATERAL TOTAL KNEE ARTHROPLASTY: WHEN IS THE SECOND KNEE SAFE TO BE REPLACED?

Background There are several surgical options available for patients with bilateral knee osteoarthritis including simultaneous bilateral TKA (BTKA) and staged approach. The appropriate and safe time interval between two stages is still controversial. The preset systematic review aims to determine the optimal time interval between two stages of BTKA. Methods Pubmed database was searched from 1979 to 2013 for English-language studies that compared the outcomes of each surgical approach. Comparison was carried out on unilateral TKA and two-staged BTKA as well as on different time intervals in two-staged BTKA. Results Eighteen studies that enrolled patients underwent TKA either unilaterally or bilaterally in one-stage and two-stage were enrolled in this systematic review. Statistically significant difference was observed in cardiac complications (OR= 1.15, 95% CI: 1.01–1.31; P=0.03) and wound complications (OR=1.18, 95% CI: 1.07–1.3; P<0.000) following two-staged BTKA compared with unilateral TKA. There observed significant differences in favor of bilateral two-stage TKA regarding other complications including mortality (OR=0.82, 95% CI: 0.7–0.95; P<0.00), PE (OR=0.71, 95% CI: 0.64–0.78; P<0.00), knee infection (OR=0.5, 95% CI: 0.45–0.55; P<0.00) and knee revision (OR=0.42, 95% CI: 0.37–0.48; P<0.00). Increasing time interval between two stages of TKA to more than 90 days, showed a lower risk for urinary (OR=0.12, 95% CI: 0.02–0.72; P=0.02) and respiratory (OR=0.05, 95% CI: 0–0.94; P=0.04) complications. Conclusion The main finding of this study was that time interval of more than 90 days between two stages of BTKA may be associated with less complication rate, specially of urinary and respiratory system.
Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.
Partial-State Stabilization and Optimal Feedback Control for Stochastic Dynamical Systems

In this paper, we develop a unified framework to address the problem of optimal nonlinear feedback control for partial stability and partial-state stabilization of stochastic dynamical systems. Partial asymptotic stability in probability of the closed-loop nonlinear system is guaranteed by means of a Lyapunov function that is positive definite and decrescent with respect to part of the system state which can clearly be seen to be the solution to the steady-state form of the stochastic Hamilton-Jacobi-Bellman equation, and hence, guaranteeing both partial stability in probability and optimality. The overall framework provides the foundation for extending optimal linear-quadratic stochastic controller synthesis to nonlinear-nonquadratic optimal partial-state stochastic stabilization. Connections to optimal linear and nonlinear regulation for linear and nonlinear time-varying stochastic systems with quadratic and nonlinear-nonquadratic cost functionals are also provided. Finally, we also develop optimal feedback controllers for affine stochastic nonlinear systems using an inverse optimality framework tailored to the partial-state stochastic stabilization problem and use this result to address polynomial and multilinear forms in the performance criterion.
Information theoretic validity of penalized likelihood

Building upon past work, which developed information theoretic notions of when a penalized likelihood procedure can be interpreted as codelengths arising from a two stage code and when the statistical risk of the procedure has a redundancy risk bound, we present new results and risk bounds showing that the l1 penalty in Gaussian Graphical Models fits the above story. We also show how twice the traditional l0 penalty times plus lower order terms which stay bounded on the whole parameter space has a conditional two stage description length interpretation and present risk bounds for this penalized likelihood procedure.
Are the Snapshot Difference Quotients Needed in the Proper Orthogonal Decomposition

This paper presents a theoretical and numerical investigation of the following practical question: Should the time difference quotients (DQs) of the snapshots be used to generate the proper orthogonal decomposition (POD) basis functions? The answer to this question is important, since some published numerical studies use the time DQs, whereas other numerical studies do not. The criterion used in this paper to answer this question is the optimality of the convergence rate of the error of the reduced order model with respect to the number of POD basis functions. Since to the best of our knowledge a definition of the optimality of the convergence rate is not available, we propose one in Definition 3.1 in this paper. Two cases are considered: the no_DQ case, in which the snapshot DQs are not used, and the DQ case, in which the snapshot DQs are used. For each case, two types of POD bases are used: the $L^2$-POD basis, in which the basis is generated in the $L^2$-norm, and the $H^1$-POD basis, in which the basi...
The Artisan and His Audience: Identification with Work and Price Setting in a Handicraft Cluster in Southern India:

Using ethnographic, experimental, and survey data from a handicraft cluster in southern India, this paper reports on a study of when and why people who identify with their work might sacrifice financial rewards in their economic decisions. Based on findings from ethnographic fieldwork, I hypothesize that the monetary value that individuals who identify with their work seek for their output depends on their audience: when they encounter discerning audiences, who are knowledgeable about and appreciative of their work, they underemphasize financial gains; transactions with non-discerning audiences, however, result in a focus on monetary rewards. I propose that the mechanism underlying this behavior is product attachment: people who identify with their work develop affection for the output of their labor and prefer to transact with audiences who will take care of their products beyond the point of sale, even if doing so results in lower monetary rewards. I substantiate this theory with a field experiment by d...
Resonant transition-based quantum computation

In this article we assess a novel quantum computation paradigm based on the resonant transition (RT) phenomenon commonly associated with atomic and molecular systems. We thoroughly analyze the intimate connections between the RT-based quantum computation and the well-established adiabatic quantum computation (AQC). Both quantum computing frameworks encode solutions to computational problems in the spectral properties of a Hamiltonian and rely on the quantum dynamics to obtain the desired output state. We discuss how one can adapt any adiabatic quantum algorithm to a corresponding RT version and the two approaches are limited by different aspects of Hamiltonians' spectra. The RT approach provides a compelling alternative to the AQC under various circumstances. To better illustrate the usefulness of the novel framework, we analyze the time complexity of an algorithm for 3-SAT problems and discuss straightforward methods to fine tune its efficiency.