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We describe an inexpensive and accessible instructional setup which explores ion trapping with a planar linear ion trap. The planar trap is constructed using standard printed circuit board manufacturing and is designed to trap macroscopic charged particles in air. Trapping, shuttling, and splitting is demonstrated to students using these particles, visible to the naked eye. Students have control over trap voltages and can compare properties of particle motion to an analytic model of the trap using a computer vision program for particle tracking. Learning outcomes include understanding the design considerations for planar RF traps, mechanisms underpinning ion ejection, the physics of micromotion, and methods of data analysis using standard computer vision libraries., Comment: 22 pages, 5 figures

Perfect colouring of isonemal fabrics by thin and thick striping of warp and weft with more than two colours is examined where the cells with warps and wefts of the same colour do not appear along diagonal lines (not twilly redundancy). In species 33 to 39, all fabrics of specific orders (linear periods) can be perfectly coloured by thin striping with satin redundancy. In fewer species, all fabrics of specific orders can be perfectly coloured by thick striping in two different ways with doubled satin redundancy. The isonemal fabric 6-1-1 can be used as a redundancy configuration. All these colourings allow the coloured weaving of flat tori and -- a few of them -- cubes.

We investigate and simulate signal amplification in a transmission line (TL) with time-modulated characteristic impedance Zo. Periodically varying $Z_o$ is achieved by loading TL with a sinusoidally time-modulated capacitor (TMC). For a detailed study, three models are considered: a lossless L-C TL lumped model loaded with shunt infinite quality factor (Q) TMC, a TL loaded with a shunt infinite Q TMC, and finite Q TMC. By solving the eigenvalue problem in all models, dispersion diagrams (DD) are plotted with a created momentum band gap (MBG) at a modulation frequency double the signal frequency. Within MBG, only imaginary frequencies are found and correlated to MBG width and signal growth level. Using Harmonics Balance (HB) and Transient Simulation (TS), signal amplification is confirmed, and the obtained results are consistent with the DD outcomes. In the second model, the effect of TL length on amplification is investigated and explained by studying the unit cell's Bloch impedance. The loss effect is considered by adding a series resistance (Rc) to the third model's TMC (finite Q). Decreasing amplification levels, confirmed by circuit modeling, due to the increase of Rc value is explained by studying real and imaginary DDs and the attenuation constant.

Understanding and mitigating optical loss is critical to the development of high-performance photonic integrated circuits (PICs). Especially in high refractive index contrast compound semiconductor (III-V) PICs, surface absorption and scattering can be a significant loss mechanism, and needs to be suppressed. Here, we quantify the optical propagation loss due to surface state absorption in a suspended GaAs photonic integrated circuits (PIC) platform, probe its origins using X-ray photoemission spectroscopy (XPS) and spectroscopic ellipsometry (SE), and show that it can be mitigated by surface passivation using alumina ($Al_{2}O_{3}$). We also explore potential routes towards achieving passive device performance comparable to state-of-the-art silicon PICs, Comment: 8 pages, 8 figures, Comments welcome !!! v2: fixed typo in equation 1, minor edits in text

AI tools increasingly shape how we discover, make and experience music. While these tools can have the potential to empower creativity, they may fundamentally redefine relationships between stakeholders, to the benefit of some and the detriment of others. In this position paper, we argue that these tools will fundamentally reshape our music culture, with profound effects (for better and for worse) on creators, consumers and the commercial enterprises that often connect them. By paying careful attention to emerging Music AI technologies and developments in other creative domains and understanding the implications, people working in this space could decrease the possible negative impacts on the practice, consumption and meaning of music. Given that many of these technologies are already available, there is some urgency in conducting analyses of these technologies now. It is important that people developing and working with these tools address these issues now to help guide their evolution to be equitable and empower creativity. We identify some potential risks and opportunities associated with existing and forthcoming AI tools for music, though more work is needed to identify concrete actions which leverage the opportunities while mitigating risks., Comment: Presented at Cultures in AI/AI in Culture workshop at NeurIPS 2022

Bayesian methods are increasingly being applied to parameterize mechanistic process models used in environmental prediction and forecasting. In particular, models describing ecosystem dynamics with multiple states that are linear and autoregressive at each step in time can be treated as statistical state space models. In this paper we examine this subset of ecosystem models, giving closed form Gibbs sampling updates for latent states and process precision parameters when process and observation errors are normally distributed. We use simulated data from an example model (DALECev) to assess the performance of parameter estimation and identifiability under scenarios of gaps in observations. We show that process precision estimates become unreliable as temporal gaps between observed state data increase. To improve estimates, particularly precisions, we introduce a method of tuning the timestep of the latent states to leverage higher-frequency driver information. Further, we show that data cloning is a suitable method for assessing parameter identifiability in this class of models. Overall, our study helps inform the application of state space models to ecological forecasting applications where 1) data are not available for all states and transfers at the operational timestep for the ecosystem model and 2) process uncertainty estimation is desired.

Objective: Sleep related respiratory abnormalities are typically detected using polysomnography. There is a need in general medicine and critical care for a more convenient method to automatically detect sleep apnea from a simple, easy-to-wear device. The objective is to automatically detect abnormal respiration and estimate the Apnea-Hypopnea-Index (AHI) with a wearable respiratory device, compared to an SpO2 signal or polysomnography using a large (n = 412) dataset serving as ground truth. Methods: Simultaneously recorded polysomnographic (PSG) and wearable respiratory effort data were used to train and evaluate models in a cross-validation fashion. Time domain and complexity features were extracted, important features were identified, and a random forest model employed to detect events and predict AHI. Four models were trained: one each using the respiratory features only, a feature from the SpO2 (%)-signal only, and two additional models that use the respiratory features and the SpO2 (%)-feature, one allowing a time lag of 30 seconds between the two signals. Results: Event-based classification resulted in areas under the receiver operating characteristic curves of 0.94, 0.86, 0.82, and areas under the precision-recall curves of 0.48, 0.32, 0.51 for the models using respiration and SpO2, respiration-only, and SpO2-only respectively. Correlation between expert-labelled and predicted AHI was 0.96, 0.78, and 0.93, respectively. Conclusions: A wearable respiratory effort signal with or without SpO2 predicted AHI accurately. Given the large dataset and rigorous testing design, we expect our models are generalizable to evaluating respiration in a variety of environments, such as at home and in critical care., Comment: Co-First Authors: Wolfgang Ganglberger, Abigail A. Bucklin Co-Senior Authors: Robert J. Thomas, M. Brandon Westover

The gold standard to assess respiration during sleep is polysomnography; a technique that is burdensome, expensive (both in analysis time and measurement costs), and difficult to repeat. Automation of respiratory analysis can improve test efficiency and enable accessible implementation opportunities worldwide. Using 9,656 polysomnography recordings from the Massachusetts General Hospital (MGH), we trained a neural network (WaveNet) based on a single respiratory effort belt to detect obstructive apnea, central apnea, hypopnea and respiratory-effort related arousals. Performance evaluation included event-based and recording-based metrics - using an apnea-hypopnea index analysis. The model was further evaluated on a public dataset, the Sleep-Heart-Health-Study-1, containing 8,455 polysomnographic recordings. For binary apnea event detection in the MGH dataset, the neural network obtained an accuracy of 95%, an apnea-hypopnea index $r^2$ of 0.89 and area under the curve for the receiver operating characteristics curve and precision-recall curve of 0.93 and 0.74, respectively. For the multiclass task, we obtained varying performances: 81% of all labeled central apneas were correctly classified, whereas this metric was 46% for obstructive apneas, 29% for respiratory effort related arousals and 16% for hypopneas. The majority of false predictions were misclassifications as another type of respiratory event. Our fully automated method can detect respiratory events and assess the apnea-hypopnea index with sufficient accuracy for clinical utilization. Differentiation of event types is more difficult and may reflect in part the complexity of human respiratory output and some degree of arbitrariness in the clinical thresholds and criteria used during manual annotation., Comment: 11 pages, 6 figures, 6 tables, \c{opyright}2020 IEEE

Objective Brain Age Index (BAI), calculated from sleep electroencephalography (EEG), has been proposed as a biomarker of brain health. This study quantifies night-to-night variability of BAI and establishes probability thresholds for inferring underlying brain pathology based on a patient's BAI. Methods 86 patients with multiple nights of consecutive EEG recordings were selected from Epilepsy Monitoring Unit patients whose EEGs reported as being within normal limits. BAI was calculated for each 12-hour segment of patient data using a previously described algorithm, and night-to-night variability in BAI was measured. Results The within-patient night-to-night standard deviation in BAI was 7.5 years. Estimates of BAI derived by averaging over 2, 3, and 4 nights had standard deviations of 4.7, 3.7, and 3.0 years, respectively. Conclusions Averaging BAI over n nights reduces night-to-night variability of BAI by a factor of the square root of n, rendering BAI more suitable as a biomarker of brain health at the individual level. Significance With increasing ease of EEG acquisition including wearable technology, BAI has the potential to track brain health and detect deviations from normal physiologic function. In a clinical setting, BAI could be used to identify patients who should undergo further investigation or monitoring., Comment: 18 pages, 6 figures, 2 tables

Study Objective: Sleep is reflected not only in the electroencephalogram but also in heart rhythms and breathing patterns. Therefore, we hypothesize that it is possible to accurately stage sleep based on the electrocardiogram (ECG) and respiratory signals. Methods: Using a dataset including 8,682 polysomnographs, we develop deep neural networks to stage sleep from ECG and respiratory signals. Five deep neural networks consisting of convolutional networks and long short-term memory networks are trained to stage sleep using heart and breathing, including the timing of R peaks from ECG, abdominal and chest respiratory effort, and the combinations of these signals. Results: ECG in combination with the abdominal respiratory effort achieve the best performance for staging all five sleep stages with a Cohen's kappa of 0.600 (95% confidence interval 0.599 -- 0.602); and 0.762 (0.760 -- 0.763) for discriminating awake vs. rapid eye movement vs. non-rapid eye movement sleep. The performance is better for young participants and for those with a low apnea-hypopnea index, while it is robust for commonly used outpatient medications. Conclusions: Our results validate that ECG and respiratory effort provide substantial information about sleep stages in a large population. It opens new possibilities in sleep research and applications where electroencephalography is not readily available or may be infeasible, such as in critically ill patients., Comment: Contains supplementary material at the end. Sleep 2019

The human electroencephalogram (EEG) of sleep undergoes profound changes with age. These changes can be conceptualized as "brain age", which can be compared to an age norm to reflect the deviation from normal aging process. Here, we develop an interpretable machine learning model to predict brain age based on two large sleep EEG datasets: the Massachusetts General Hospital sleep lab dataset (MGH, N = 2,621) covering age 18 to 80; and the Sleep Hearth Health Study (SHHS, N = 3,520) covering age 40 to 80. The model obtains a mean absolute deviation of 8.1 years between brain age and chronological age in the healthy participants in the MGH dataset. As validation, we analyze a subset of SHHS containing longitudinal EEGs 5 years apart, which shows a 5.5 years difference in brain age. Participants with neurological and psychiatric diseases, as well as diabetes and hypertension medications show an older brain age compared to chronological age. The findings raise the prospect of using sleep EEG as a biomarker for healthy brain aging.

This paper investigates the problem of generation and load settings in a synthetic power grid modeling of high-voltage transmission network, considering both electrical parameters and topology measures. Our previous study indicated that the relative location of generation and load buses in a realistic grid are not random but correlated. And an entropy based optimization approach has been proposed to determine a set of correlated siting for generation and load buses in a synthetic grid modeling. Using the exponential distribution of individual generation capacity or load settings in a grid, and the non-trivial correlation between the generation capacity or load setting and the nodal degree of a generation or load bus we develop an approach to generate a statistically correct random set of generation capacities and load settings, and then assign them to each generation or load bus in a grid.

The multi-configurational self-consistent field theory is considered the standard starting point for almost all multireference approaches required for strongly-correlated molecular problems. The limitation of the approach is generally given by the number of strongly-correlated orbitals in the molecule, as its cost will grow exponentially with this number. We present a new multi-configurational self-consistent field approach, wherein linear determinant coefficients of a multi-configurational wavefunction are optimized via the stochastic full configuration interaction quantum Monte Carlo technique at greatly reduced computational cost, with non-linear orbital rotation parameters updated variationally based on this sampled wavefunction. This extends this approach to strongly-correlated systems with far larger active spaces than it is possible to treat by conventional means. By comparison with this traditional approach, we demonstrate that the introduction of stochastic noise in both the determinant amplitudes and the gradient and Hessian of the orbital rotations does not preclude robust and reliable convergence of the orbital optimization. It can even improve the ability to avoid convergence to local minima in the orbital space, and therefore aid in finding variationally lower-energy solutions. We consider the effect on the convergence of the orbitals as the number of walkers and the sampling time within the active space increases, as well as the effect on the final energy and error. The scope of the new protocol is demonstrated with a study of the increasingly strongly correlated electronic structure in a series of polycyclic aromatic hydrocarbons, up to the large coronene molecule in a complete active space of 24 pi electrons in 24 orbitals, requiring only modest computational resources.

The time-temperature response of porcine tissue to laser radiation exposure is investigated as a function of wavelength. We experimentally measure the thermal response of tissue to laser radiation ranging in wavelength from 1100 nm to 1550 nm. The experimental data were compared to simulations performed using thermal modeling software. Based on these simulations, and the corresponding experimental data, damage thresholds as a function of wavelength were estimated. This data can be used to help optimize the design of optical imaging systems, particularly those being used for biomedical imaging.

Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, "replica" ensemble of walkers, whose population evolves in imaginary time independently from the first, and which entails only modest additional computational overheads. The matrices obtained from this approach are shown to be representative of full configuration-interaction quality, and hence provide a realistic opportunity to achieve high-quality results for a range of properties whose operators do not necessarily commute with the hamiltonian. A density-matrix formulated quasi-variational energy estimator having been already proposed and investigated, the present work extends the scope of the theory to take in studies of analytic nuclear forces, molecular dipole moments and polarisabilities, with extensive comparison to exact results where possible. These new results confirm the suitability of the sampling technique and, where sufficiently large basis sets are available, achieve close agreement with experimental values, expanding the scope of the method to new areas of investigation., Comment: 11 pages

Currently, no light source exists which is both narrow-band and speckle-free with sufficient brightness for full-field imaging applications. Light emitting diodes (LEDs) are excellent spatially incoherent sources, but are tens of nanometers broad. Lasers on the other hand can produce very narrow-band light, but suffer from high spatial coherence which leads to speckle patterns which distort the image. Here we propose the use of random Raman laser emission as a new kind of light source capable of providing short-pulsed narrow-band speckle-free illumination for imaging applications.

The short-term forecasting of real-time locational marginal price (LMP) and network congestion is considered from a system operator perspective. A new probabilistic forecasting technique is proposed based on a multiparametric programming formulation that partitions the uncertainty parameter space into critical regions from which the conditional probability distribution of the real-time LMP/congestion is obtained. The proposed method incorporates load/generation forecast, time varying operation constraints, and contingency models. By shifting the computation cost associated with multiparametric programs offline, the online computation cost is significantly reduced. An online simulation technique by generating critical regions dynamically is also proposed, which results in several orders of magnitude improvement in the computational cost over standard Monte Carlo methods.

Perfect colouring of isonemal fabrics by thin striping of warp and weft with more than two colours is examined. Examples of thin striping in all possible species with no redundancy and with redundant cells arranged as twills are given. Colouring woven flat tori is discussed., Comment: 50 figures

Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system parameters. Such information is difficult to acquire in practice. The subspace methods presented in this paper, on the other hand, learn the system operating subspace from measurements and launch attacks accordingly. Conditions for the existence of an unobservable subspace attack are obtained under the full and partial measurement models. Using the estimated system subspace, two attack strategies are presented. The first strategy aims to affect the system state directly by hiding the attack vector in the system subspace. The second strategy misleads the bad data detection mechanism so that data not under attack are removed. Performance of these attacks are evaluated using the IEEE 14-bus network and the IEEE 118-bus network., Comment: 12 pages

A new mechanism aimed at misleading a power system control center about the source of a data attack is proposed. As a man-in-the-middle state attack, a data framing attack is proposed to exploit the bad data detection and identification mechanisms currently in use at most control centers. In particular, the proposed attack frames meters that are providing correct data as sources of bad data such that the control center will remove useful measurements that would otherwise be used by the state estimator. The optimal design of a data framing attack is formulated as a quadratically constrained quadratic program (QCQP). It is shown that the proposed attack is capable of perturbing the power system state estimate by an arbitrary degree controlling only half of a critical set of measurements that are needed to make a system unobservable. Implications of this attack on power system operations are discussed, and the attack performance is evaluated using benchmark systems., Comment: To appear in IEEE Journal on Selected Areas in Communications: Special series on Smart Grid Communications, 2014

Propagation of light in a highly scattering medium is among the most fascinating optical effect that everyone experiences on an everyday basis and possesses a number of fundamental problems which have yet to be solved. Conventional wisdom suggests that non-linear effects do not play a significant role because the diffusive nature of scattering acts to spread the intensity, dramatically weakening these effects. We demonstrate the first experimental evidence of lasing on a Raman transition in a bulk three-dimensional random media. From a practical standpoint, Raman transitions allow for spectroscopic analysis of the chemical makeup of the sample. A random Raman laser could serve as a bright Raman source allowing for remote, chemically specific, identification of powders and aerosols. Fundamentally, the first demonstration of this new light source opens up an entire new field of study into non-linear light propagation in turbid media, with the most notable application related to non-invasive biomedical imaging.

The problem of characterizing impacts of data quality on real-time locational marginal price (LMP) is considered. Because the real-time LMP is computed from the estimated network topology and system state, bad data that cause errors in topology processing and state estimation affect real-time LMP. It is shown that the power system state space is partitioned into price regions of convex polytopes. Under different bad data models, the worst case impacts of bad data on real-time LMP are analyzed. Numerical simulations are used to illustrate worst case performance for IEEE-14 and IEEE-118 networks., Comment: Compared to the first version, the authors added in Section IV-E details about the computational issue of the proposed analysis

There has been recent literature discussion on the origin and severity of the `sign problem' in full configuration interaction quantum Monte Carlo (FCIQMC) and its `initiator' adaptation (i-FCIQMC), methods of interest and potential because they allow for exact (FCI) ground-state solutions to be obtained often at a much reduced computational cost. In this study we aim to use a simple order parameter, describing the `sign structure' of the stochastic wavefunction representation, to empirically characterise the fundamentally different collective behaviour of the walker population in both methods., Comment: 5 pages, 6 figs

The role of ionic interactions between sodium dodecyl sulfate, SDS, and sapphire surfaces have been studied using specular neutron reflection to determine the structure and composition of adsorbed surfactant layers. Increasing the pH of the solution from 3 to 9 reduces the adsorption by reversing the charge of the alumina. This occurs at lower pH for the R-plane (1 -1 0 2) than the C-plane (0 0 0 1), corresponding to the different points of zero charge. The largest surface excess is about 6.5 micromol m-2, the thickness of the adsorbed layer is about 24 Angstrom and it contains roughly 20% water. The hydrocarbon tails of the surfactant molecules clearly interpenetrate rather than form an ordered bilayer. The structure is similar in either pure water or in 0.1 M NaCl when the surfactant is at the respective critical micelle concentration. Different structures were seen with lithium and cesium dodecyl sulfate. The CsDS forms dense layers with little or no hydration and a surface excess of about 10.5 micromol m-2. The metal cation strongly influences the hydration of the adsorbed surfactant. An overall picture of 'flattened micelles' for the structure of the adsorbed layer is observed

At present, the power grid has tight control over its dispatchable generation capacity but a very coarse control on the demand. Energy consumers are shielded from making price-aware decisions, which degrades the efficiency of the market. This state of affairs tends to favor fossil fuel generation over renewable sources. Because of the technological difficulties of storing electric energy, the quest for mechanisms that would make the demand for electricity controllable on a day-to-day basis is gaining prominence. The goal of this paper is to provide one such mechanisms, which we call Digital Direct Load Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle individual requests for energy and digitize them so that they can be automatically scheduled in a cellular architecture. Specifically, rather than storing energy or interrupting the job of appliances, we choose to hold requests for energy in queues and optimize the service time of individual appliances belonging to a broad class which we refer to as "deferrable loads". The function of each neighborhood scheduler is to optimize the time at which these appliances start to function. This process is intended to shape the aggregate load profile of the neighborhood so as to optimize an objective function which incorporates the spot price of energy, and also allows distributed energy resources to supply part of the generation dynamically., Comment: Accepted by the IEEE journal of Selected Areas in Communications (JSAC): Smart Grid Communications series, to appear

Perfect colouring of isonemal fabrics by thick striping of warp and weft and the closely related topic of isonemal prefabrics that fall apart are reconsidered and their relation further explored. The catalogue of isonemal prefabrics of genus V that fall apart is extended to order 20 with designs that can be used to weave cubes with colour symmetry as well as weaving symmetry., Comment: 50 diagrams

Perfect colouring of isonemal fabrics by thin striping of warp and weft and the closely related topic of isonemal prefabrics that fall apart are reconsidered and their relation further explored. The catalogue of isonemal prefabrics that fall apart is extended to order 20 for those of even genus., Comment: 25 pages, 20 figures

The time dependence of device performance has been measured for photocells using blends containing the conjugated polymer, poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) with two different functionalized C60 electron acceptor molecules: commercially available [6,6]-phenyl C61 butyric acid methyl ester (PCBM) or [6,6]-phenyl C61 butyric acid octadecyl ester (PCBOD) produced in this laboratory. Performance was characterized by the short-circuit current output of the devices, with the time dependence of PCBM samples typically degrading exponentially. Variations in the characteristic lifetime of the devices were observed to depend on the molar fraction of the electron acceptor molecules (calculated with respect to the MEH-PPV monomer fraction). In comparison to the PCBM samples, the stability of the PCBOD blends was significantly enhanced, with a one or two order of magnitude improvement. Corresponding spectroscopic data with similar time evolution as the transport measurements suggests an independent means for determining and understanding degradation mechanisms., Comment: accepted for publication in Solar Energy Materials and Solar Cells

The Galaxy And Mass Assembly (GAMA) project is the latest in a tradition of large galaxy redshift surveys, and is now underway on the 3.9m Anglo-Australian Telescope at Siding Spring Observatory. GAMA is designed to map extragalactic structures on scales of 1kpc - 1Mpc in complete detail to a redshift of z~0.2, and to trace the distribution of luminous galaxies out to z~0.5. The principal science aim is to test the standard hierarchical structure formation paradigm of Cold Dark Matter (CDM) on scales of galaxy groups, pairs, discs, bulges and bars. We will measure (1) the Dark Matter Halo Mass Function (as inferred from galaxy group velocity dispersions); (2) baryonic processes, such as star formation and galaxy formation efficiency (as derived from Galaxy Stellar Mass Functions); and (3) the evolution of galaxy merger rates (via galaxy close pairs and galaxy asymmetries). Additionally, GAMA will form the central part of a new galaxy database, which aims to contain 275,000 galaxies with multi-wavelength coverage from coordinated observations with the latest international ground- and space-based facilities: GALEX, VST, VISTA, WISE, HERSCHEL, GMRT and ASKAP. Together, these data will provide increased depth (over 2 magnitudes), doubled spatial resolution (0.7"), and significantly extended wavelength coverage (UV through Far-IR to radio) over the main SDSS spectroscopic survey for five regions, each of around 50 deg^2. This database will permit detailed investigations of the structural, chemical, and dynamical properties of all galaxy types, across all environments, and over a 5 billion year timeline., Comment: GAMA overview which appeared in the October 2009 issue of Astronomy & Geophysics, ref: Astron.Geophys. 50 (2009) 5.12

In the spirit of educational reform, this paper discusses school restructuring and proposes a model for making education more responsive to the needs of urban youth by fostering competence built upon unique cultural resources and individual skills already possessed. The proposed project would target the middle school, which is considered an ideal starting place for structuring change because it is at this level that the gains of the elementary school are thought to be lost. The following structural changes are proposed: (1) redesign of the self-contained classroom; (2) professional diversification through the use of teachers as craftsmen, specialists, and artists; (3) the use of teaching teams; (4) the incorporation of group processing and problem-solving skills for both students and teachers; (5) a less hierarchical management structure; and (6) increased monitoring of performance through the use of advanced technologies. The three instructional strategies being considered are teacher-assisted instruction, team-assisted instruction, and computer-assisted instruction. The effectiveness of these strategies will be related to the core subjects of reading, mathematics, and science to assess academic achievement. (Contains 22 references.) (LL)

This study sought to determine whether school boards from central region states with aggressive legislative education reform initiatives differ from school boards from nonreform states. Reform states, defined as states that have enacted statewide choice legislation, included Ohio, Minnesota, and Iowa. Nonreform states were Wisconsin, Michigan, Indiana, Illinois, and Missouri. The study described school board members based on the perceptions of school board presidents and explained differences between school board presidents from reform and nonreform states based on common legally mandated learning areas, sources of learning, group dimensions, and other demographics. The study found that school boards from reform and nonreform states do not differ with respect to learning, group relations, educational reform, district wealth, district size, or school board size. School board members learned to do their jobs primarily from the district superintendent or on the job. School board presidents were interested more in learning how to do their jobs and the impact of reform than they were about group relations. Recommendations are provided for school board members, superintendents, legislators, and other school personnel. (Contains 23 references.) (JDD)

We describe a simple variant of the interpolated Markov model with non-emitting state transitions and prove that it is strictly more powerful than any Markov model. More importantly, the non-emitting model outperforms the classic interpolated model on the natural language texts under a wide range of experimental conditions, with only a modest increase in computational requirements. The non-emitting model is also much less prone to overfitting. Keywords: Markov model, interpolated Markov model, hidden Markov model, mixture modeling, non-emitting state transitions, state-conditional interpolation, statistical language model, discrete time series, Brown corpus, Wall Street Journal., Comment: http://www.cs.princeton.edu/~ristad/papers/pu-544-97.ps.gz

A statistical language model assigns probability to strings of arbitrary length. Unfortunately, it is not possible to gather reliable statistics on strings of arbitrary length from a finite corpus. Therefore, a statistical language model must decide that each symbol in a string depends on at most a small, finite number of other symbols in the string. In this report we propose a new way to model conditional independence in Markov models. The central feature of our nonuniform Markov model is that it makes predictions of varying lengths using contexts of varying lengths. Experiments on the Wall Street Journal reveal that the nonuniform model performs slightly better than the classic interpolated Markov model. This result is somewhat remarkable because both models contain identical numbers of parameters whose values are estimated in a similar manner. The only difference between the two models is how they combine the statistics of longer and shorter strings. Keywords: nonuniform Markov model, interpolated Markov model, conditional independence, statistical language model, discrete time series., Comment: 17 pages

We introduce three new techniques for statistical language models: extension modeling, nonmonotonic contexts, and the divergence heuristic. Together these techniques result in language models that have few states, even fewer parameters, and low message entropies. For example, our techniques achieve a message entropy of 1.97 bits/char on the Brown corpus using only 89,325 parameters. In contrast, the character 4-gram model requires more than 250 times as many parameters in order to achieve a message entropy of only 2.47 bits/char. The fact that our model performs significantly better while using vastly fewer parameters indicates that it is a better probability model of natural language text., Comment: 8 pages, to appear in Proc. ACL 1995

Risk mitigation tests have been conducted by the NASA Glenn Research Center and The Aerospace Corporation in support of the DART Mission. The tests focused on NEXT performance characterizations intended to ensure its operations and characteristics are compatible with the DART mission operations, and to assist in the definition of the propulsion system. Tests were performed at the Aerospace Corporation and they involved: flow sensitivity-analyses, steady-state performance characterizations, and measurements of thruster erosion. The tests also involved defining, demonstrating, verifying, and evaluating the start-up sequences and a beam current regulation algorithm consistent with DART mission requirements. It was found that NEXT thruster operations are compatible with the proposed relaxation of flow control ranges for ignition and for steady-state operation.

A system integration test has been performed utilizing a prototype model NEXT ion thruster, an engineering model power processing unit, and a laboratory model command and data handling system. The objectives of the test were to: a) verify that the integrated system meets performance requirements, b) demonstrate that the integrated system is functional across the anticipated thermal, power processor, and Xe propellant ranges for the DART mission, and to c) evaluate fault detection and operation of the command and data handling system. Measurements made during this test included: thruster performance, PPU input voltages, PPU electrical and thermal telemetry, software states, and fault flags. Additionally, a far-field electrostatic probe diagnostic was used to infer relative changes in the thrust vector across the various propellant flow splits. This manuscript presents the results of these tests, which include integrated ion propulsion system demonstrations of performance, details on the execution of DART flight algorithms, and software fault handling.

A system integration test has been performed utilizing a prototype model NEXT ion thruster, an engineering model power processing unit, and a laboratory model command and data handling system. The objectives of the test were to: a) verify that the integrated system meets performance requirements, b) demonstrate that the integrated system is functional across the anticipated thermal, power processor, and Xe propellant ranges for the DART mission, and to c) evaluate fault detection and operation of the command and data handling system. Measurements made during this test included: thruster performance, PPU input voltages, PPU electrical and thermal telemetry, software states, and fault flags. Additionally, a far-field electrostatic probe diagnostic was used to infer relative changes in the thrust vector across the various propellant flow splits. This manuscript presents the results of these tests, which include integrated ion propulsion system demonstrations of performance, details on the execution of DART flight algorithms, and software fault handling.

A diagnostic has been designed and fabricated to verify the thrust vector requirement for the Advanced Electric Propulsion System (AEPS) Hall Effect Rocket with Magnetic Shielding (HERMeS) thruster. This diagnostic will be used to verify that the propulsion system thrust vector offset from the mounting surface normal vector does not exceed 1.5 degrees over the entire throttling range and over the course of 23,000 hours of thruster testing. The diagnostic will also not violate the thruster's required voltage standoff capability in the presence of carbon backsputter by being minimally intrusive and not significantly adding to the facility backsputtered rate. Based on these requirements, an appropriate diagnostic design was determined to comprise of an array of 23 Faraday probes swept through the plume in an arc 1m from the thruster to map the beam current density. The beam current density centroid of the plume is assumed to track the thrust vector within an acceptable level of uncertainty. Additionally, a reference system, including optical alignment to the mounting surface normal vector and tilt sensors, was devised to periodically calibrate the probe position and motion throughout the long duration wear test campaign. Initial measurements of the thruster plume have been acquired to demonstrate the diagnostics functionality, verify procedures, and assess any necessary improvements prior to implementation of the diagnostic during the AEPS Engineering Development Unit (EDU) long duration wear test. To illustrate the merits of differing approaches to thrust vector determination for different classes of electric propulsion thrusters, NASA's Evolutionary Xenon Thruster-Commercial (NEXT-C) thrust vector diagnostic design details and recent data are also discussed (Appendix A).