Hebrew College collection, 1928-1996

Louis Hurwich, then superintendent of the Bureau of Jewish Education of Boston, founded Hebrew Teacher’s College in 1921. Hurwich was concerned about Jewish teachers leaving the field of Jewish education for other professions and sought an educational system that promoted Hebrew literacy at all levels. Hebrew Teacher’s College was also responsible for maintaining Hebrew High School (Prozdor), located at 14 Crawford Street in Roxbury, Massachusetts. Those students who graduated from the high school could matriculate to Hebrew Teacher’s College without having to take an exam. In 1943, the high school offered Talmud classes in addition to its regular curriculum, with studies in the Bible, Hebrew, Jewish History, and codes and customs. In 2002, the College moved to its current location in Newton, Massachusetts. One year later, it opened its Rabbinical School. This collection contains brochures, catalogs, commencement addresses, event fliers, invitations, pamphlets and publications.

Temple Mishkan Tefila Boston, Massachusetts collection, 1922-1996

Congregation Mishkan Tefila was founded in 1858 as Mishkan Israel, and is considered to be the oldest conservative synagogue in New England. Its founding members were East Prussian Jews who separated from Ohabei Shalom, which was predominately Polish at the time. In 1894, Mishkan Israel and another conservative synagogue, Shaarei Tefila, merged to form Congregation Mishkan Tefila. The synagogue moved its religious school to Walnut Street in Newton in 1955, and began planning for a new building in Chestnut Hill on Hammond Pond Parkway. The groundbreaking ceremony was on November 13, 1955. In 1958, services were held for the first time in the new synagogue building. This collection contains plays, annual reports, programs for events and dinners, and newsletters.

Rosalie Unger Collection 1856-1990

Two letters to Rosalie Unger in Oppeln (today Opole, Poland) from Adolf Heilborn and Berta Neustadt (née Fraenkel); and one letter to Max Neustadt from Leopold Rosenbaum (all photocopies). Also included is an explanatory letter from Harvey P, Newton.

Tax compliance and psychic costs: Behavioral experimental evidence using a physiological marker

Although paying taxes is a key element of a well-functioning society, there is still limited understanding as to why people actually pay their taxes. Models emphasizing that taxpayers make strategic, financially motivated compliance decisions seemingly assume an overly restrictive view of human nature. Law abidance may be more accurately explained by social norms, a concept that has gained growing importance as research attempts to understand the tax compliance puzzle. This study analyzes the influence of psychic stress generated by the possibility of breaking social norms in the tax compliance context. We measure psychic stress using heart rate variability (HRV), which captures the psychobiological or neural equivalents of psychic stress that may arise from the contemplation of real or imagined actions, producing immediate physiologic discomfort. The results of our laboratory experiments provide empirical evidence of a positive correlation between psychic stress and tax compliance, thus underscoring the importance of moral sentiments for tax compliance. We also identify three distinct types of individuals who differ in their levels of psychic stress, tax morale, and tax compliance.

Pseudo-time marching schemes for inverse problems in structural health assessment and medical imaging

We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.

ANC schemes for the enhancement of EEG signals in the presence of EOG artifacts

One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

Studies of solar and stellar flares using multi-instrument data

Solar flares were first observed by plain eye in white light by William Carrington in England in 1859. Since then these eruptions in the solar corona have intrigued scientists. It is known that flares influence the space weather experienced by the planets in a multitude of ways, for example by causing aurora borealis. Understanding flares is at the epicentre of human survival in space, as astronauts cannot survive the highly energetic particles associated with large flares in high doses without contracting serious radiation disease symptoms, unless they shield themselves effectively during space missions. Flares may be at the epicentre of man s survival in the past as well: it has been suggested that giant flares might have played a role in exterminating many of the large species on Earth, including dinosaurs. Having said that prebiotic synthesis studies have shown lightning to be a decisive requirement for amino acid synthesis on the primordial Earth. Increased lightning activity could be attributed to space weather, and flares. This thesis studies flares in two ways: in the spectral and the spatial domain. We have extracted solar spectra using three different instruments, namely GOES (Geostationary Operational Environmental Satellite), RHESSI (Reuven Ramaty High Energy Solar Spectroscopic Imager) and XSM (X-ray Solar Monitor) for the same flares. The GOES spectra are low resolution obtained with a gas proportional counter, the RHESSI spectra are higher resolution obtained with Germanium detectors and the XSM spectra are very high resolution observed with a silicon detector. It turns out that the detector technology and response influence the spectra we see substantially, and are important to understanding what conclusions to draw from the data. With imaging data, there was not such a luxury of choice available. We used RHESSI imaging data to observe the spatial size of solar flares. In the present work the focus was primarily on current solar flares. However, we did make use of our improved understanding of solar flares to observe young suns in NGC 2547. The same techniques used with solar monitors were applied with XMM-Newton, a stellar X-ray monitor, and coupled with ground based Halpha observations these techniques yielded estimates for flare parameters in young suns. The material in this thesis is therefore structured from technology to application, covering the full processing path from raw data and detector responses to concrete physical parameter results, such as the first measurement of the length of plasma flare loops in young suns.

The psychometric properties of the Kessler Psychological Distress Scale (K6) in a general population sample of adolescents

The 6-item Kessler Psychological Distress Scale (K6; Kessler et al., 2002) is a screener for psychological distress that has robust psychometric properties among adults. Given that a significant proportion of adolescents experience mental illness, there is a need for measures that accurately and reliably screen for mental disorders in this age group. This study examined the psychometric properties of the K6 in a large general population sample of adolescents (N = 4,434; mean age = 13.5 years; 44.6% male). Factor analyses were conducted to examine the dimensionality of the K6 in adolescents and to investigate sex-based measurement invariance. This study also evaluated the K6 as a predictor of scores on the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). The K6 demonstrated high levels of internal consistency, with the 6 items loading primarily on 1 factor. Consistent with previous research, females reported higher mean levels of psychological distress when compared with males. The identification of sex-based measurement noninvariance in the item thresholds indicated that these mean differences most likely represented reporting bias in the K6 items rather than true differences in the underlying psychological distress construct. The K6 was a fair to good predictor of abnormal scores on the SDQ, but predictive utility was relatively low among males. Future research needs to focus on refining and augmenting the K6 scale to maximize its utility in adolescents. (PsycINFO Database Record (c) 2015 APA, all rights reserved)

How Can Sustainable Agricultural Systems Promote Food Security in a Changing Climate?

A theoretical framework of the link between climate change, rural development, sustainable agriculture, poverty, and food security is presented. Some options to respond to climate change are described. Current knowledge and potential effects on agricultural productivity is discussed. Necessary conditions for successful adaptation includes secured property rights to land, institutions that make market access possible and credit possibilities. The options of mitigation and enhanced adaptive capacity and the requirements for their implementation are discussed.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

New computational approaches for wrinkled and slack membranes

The static response of thin, wrinkled membranes is studied using both a tension field approximation based on plane stress conditions and a 3D nonlinear elasticityformulation, discretized through 8-noded Cosserat point elements. While the tension field approach only obtains the wrinkled/slack regions and at best a measure of the extent of wrinkliness, the 3D elasticity solution provides, in principle, the deformed shape of a wrinkled/slack membrane. However, since membranes barely resist compression, the discretized and linearized system equations via both the approaches are ill-conditioned and solutions could thus be sensitive to discretizations errors as well as other sources of noises/imperfections. We propose a regularized, pseudo-dynamical recursion scheme that provides a sequence of updates, which are almost insensitive to theregularizing term as well as the time step size used for integrating the pseudo-dynamical form. This is borne out through several numerical examples wherein the relative performance of the proposed recursion scheme vis-a-vis a regularized Newton strategy is compared. The pseudo-time marching strategy, when implemented using 3D Cosserat point elements, also provides a computationally cheaper, numerically accurate and simpler alternative to that using geometrically exact shell theories for computing large deformations of membranes in the presence of wrinkles. (C) 2010 Elsevier Ltd. All rights reserved.

Impact of agricultural market liberalization on food security in developing countries : a comparative study of Kenya and Zambia

This research investigates the impacts of agricultural market liberalization on food security in developing countries and it evaluates the supply perspective of food security. This research theme is applied on the agricultural sector in Kenya and in Zambia by studying the role policies played in the maize sub-sector. An evaluation of selected policies introduced at the beginning of the 1980s is made, as well as an assessment of whether those policies influenced maize output. A theoretical model of agricultural production is then formulated to reflect cereal production in a developing country setting. This study begins with a review of the general framework and the aims of the structural adjustment programs and proceeds to their application in the maize sector in Kenya and Zambia. A literature review of the supply and demand synthesis of food security is presented with examples from various developing countries. Contrary to previous studies on food security, this study assesses two countries with divergent economic orientations. Agricultural sector response to economic and institutional policies in different settings is also evaluated. Finally, a dynamic time series econometric model is applied to assess the effects of policy on maize output. The empirical findings suggest a weak policy influence on maize output, but the precipitation and acreage variables stand out as core determinants of maize output. The policy dimension of acreage and how markets influence it is not discussed at length in this study. Due to weak land rights and tenure structures in these countries, the direct impact of policy change on land markets cannot be precisely measured. Recurring government intervention during the structural policy implementation period impeded efficient functioning of input and output markets, particularly in Zambia. Input and output prices of maize and fertilizer responded more strongly in Kenya than in Zambia, where the state often ceded to public pressure by revoking pertinent policy measures. These policy interpretations are based on the response of policy variables which are more responsive in Kenya than in Zambia. According the obtained regression results, agricultural markets in general, and the maize sub-sector in particular, responded more positively to implemented policies in Kenya, than in Zambia, which supported a more socialist economic system. It is observed in these results that in order for policies to be effective, sector and regional dimensions need to be considered. The regional and sector dimensions were not taken into account in the formulation and implementation of structural adjustment policies in the 1980s. It can be noted that countries with vibrant economic structures and institutions fared better than those which had a firm, socially founded system.

On numerical implementation of an isotropic elastic-viscoplastic constitutive model for bulk metallic glasses

An efficient algorithm within the finite deformation framework is developed for finite element implementation of a recently proposed isotropic, Mohr-Coulomb type material model, which captures the elastic-viscoplastic, pressure sensitive and plastically dilatant response of bulk metallic glasses. The constitutive equations are first reformulated and implemented using an implicit numerical integration procedure based on the backward Euler method. The resulting system of nonlinear algebraic equations is solved by the Newton-Raphson procedure. This is achieved by developing the principal space return mapping technique for the present model which involves simultaneous shearing and dilatation on multiple potential slip systems. The complete stress update algorithm is presented and the expressions for viscoplastic consistent tangent moduli are derived. The stress update scheme and the viscoplastic consistent tangent are implemented in the commercial finite element code ABAQUS/Standard. The accuracy and performance of the numerical implementation are verified by considering several benchmark examples, which includes a simulation of multiple shear bands in a 3D prismatic bar under uniaxial compression.