Miraculous Survival 1939-1982

Description of war years in France and Spain, including experiences in internment camps, life in hiding, etc.; emigration to USA.

Joseph A. Rosen Papers 1921-1938

With few exceptions, the bulk of the collection pertains to the work of the Agro-Joint. Records of the Agro-Joint Director General. Agreements of the American Relief Administration (ARA) and the Joint Distribution Committee with the Soviet government, 1922-1923. Agreements between the Agro-Joint and the Soviet government, 1924, 1927, 1928. Agreements of the Agro-Joint and the American Society for Jewish Farm Settlements (ASJFS) with the Soviet government, 1929, 1930, 1933, 1938. Materials relating to relief work of the JDC within the framework of the American Relief Administration, 1922, including the appointment of J. Rosen as the JDC representative at the ARA. Statistics, reports, miscellaneous correspondence relating to JDC activities in Russia. Minutes, memos, reports, legal documents, certificate of incorporation, and general correspondence relating to the ASJFS, its formation, fund-raising activities, 1927-1939. Records of the Agro-Joint Main Office, Moscow. Annual and periodi c reports of the Agro-Joint including statistics, financial estimates, financial reports, analyses of expenditures, relating to Agro-Joint work, 1924-1937. General correspondence files: incoming and outgoing letters, reports, and memoranda. Materials relating to land surveys and allocations in the Crimea: statistics, surveys, memos, correspondence, relating to the Salsk district, Chernomor district, Changar peninsula, Azov, Kuban, Odessa district, Samara district, Povolzhe, Krivoy Rog, Kherson, The Far East, Siberia. Materials relating to contacts with KOMZET. Correspondence, minutes of KOMZET meetings, statistical information, reports. By-laws of the OZET (Obshchestvo po Zemleustroystvu Trudyachtchikhsya Evreev - Association For the Settlement of Toiling Jews On Land) and AGRO-KUSTBANK (Evreysky Agrarno-Kustarny Bank - Jewish Agricultural and House Workers Bank). Register of Agro-Joint assets transferred to KOMZET. Records of the Agro-Joint Agricultural Department. Materials

Graenum Berger papers, undated, (1825)-2002

Contains correspondence, minutes, reports, clippings, manuscripts, research materials, journal articles, photographs and publications; primarily relating to Berger's involvement with Ethiopian Jewry and his efforts to bring about their rescue through the organization he formed, the American Association for Ethiopian Jews. Also contains material from Berger's other interests- his writings, travels through the world and to Israel and Ethiopia, community affiliations, research in Black American Jews, profession as a Jewish social work executive, his commitment to Jewish causes and to Israel. There are also many personal and biographical materials from the numerous long-term friendships and associations he established.

Herbert B. Ehrmann papers, 1913-1970.

Contains correspondence, addresses and speeches, newspaper clippings, and published material relating primarily to Ehrmann's activity in the national and Boston chapter of the American Jewish Committee (1935-1970). Of special interest is material on the relation of the Committee to the American Jewish Conference (1943-1948), the relationship of American Jewry to the State of Israel, and the attitude of the Committee to the establishment of Israel. Also contains genealogical material, in German and in English, between Ehrmann and his relatives in Poland immediately prior World War II, and in Italy immediately after the war. Also contains letters and reports sent by Mrs. Sara Rosenfeld Ehrmann (b. 1895) by the American Jewish Joint Distribution Committee (JDC) and the United Jewish Appeal, dealing primarily with fund-raising matters.

Solis-Cohen family papers, 1808-1990.

Correspondence, diaries, acount books, pamphlets, and other personal and professional materials pertaining to Jacob da Silva Solis and his descendents.

Lewis Lichtenstein Strauss papers 1908-1973

Consists of correspondence, documents, speeches, reports and other writings, photographs, film and other records of Admiral Strauss' involvement with Jewish organizations and causes, as well as miscellaneous personal items.

Louis Kraft papers undated, 1914-1975.

Correspondence, memoranda, minutes, reports, official documents and other similar materials pertaining to Kraft's long career in Jewish Social Service at the JWB, the JDC and related organizations.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

Monte-Carlo estimation of time-dependent statistical characteristics of random dynamical systems

The problem of estimating the time-dependent statistical characteristics of a random dynamical system is studied under two different settings. In the first, the system dynamics is governed by a differential equation parameterized by a random parameter, while in the second, this is governed by a differential equation with an underlying parameter sequence characterized by a continuous time Markov chain. We propose, for the first time in the literature, stochastic approximation algorithms for estimating various time-dependent process characteristics of the system. In particular, we provide efficient estimators for quantities such as the mean, variance and distribution of the process at any given time as well as the joint distribution and the autocorrelation coefficient at different times. A novel aspect of our approach is that we assume that information on the parameter model (i.e., its distribution in the first case and transition probabilities of the Markov chain in the second) is not available in either case. This is unlike most other work in the literature that assumes availability of such information. Also, most of the prior work in the literature is geared towards analyzing the steady-state system behavior of the random dynamical system while our focus is on analyzing the time-dependent statistical characteristics which are in general difficult to obtain. We prove the almost sure convergence of our stochastic approximation scheme in each case to the true value of the quantity being estimated. We provide a general class of strongly consistent estimators for the aforementioned statistical quantities with regular sample average estimators being a specific instance of these. We also present an application of the proposed scheme on a widely used model in population biology. Numerical experiments in this framework show that the time-dependent process characteristics as obtained using our algorithm in each case exhibit excellent agreement with exact results. (C) 2010 Elsevier Inc. All rights reserved.

Linear Coding Schemes for the Distributed Computation of Subspaces

Let X-1,..., X-m be a set of m statistically dependent sources over the common alphabet F-q, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation setting in which the receiver is interested in the lossless computation of the elements of an s-dimensional subspace W spanned by the elements of the row vector X-1,..., X-m]Gamma in which the (m x s) matrix Gamma has rank s. A sequence of three increasingly refined approaches is presented, all based on linear encoders. The first approach uses a common matrix to encode all the sources and a Korner-Marton like receiver to directly compute W. The second improves upon the first by showing that it is often more efficient to compute a carefully chosen superspace U of W. The superspace is identified by showing that the joint distribution of the {X-i} induces a unique decomposition of the set of all linear combinations of the {X-i}, into a chain of subspaces identified by a normalized measure of entropy. This subspace chain also suggests a third approach, one that employs nested codes. For any joint distribution of the {X-i} and any W, the sum-rate of the nested code approach is no larger than that under the Slepian-Wolf (SW) approach. Under the SW approach, W is computed by first recovering each of the {X-i}. For a large class of joint distributions and subspaces W, the nested code approach is shown to improve upon SW. Additionally, a class of source distributions and subspaces are identified, for which the nested-code approach is sum-rate optimal.

Characterizing drought using the reliability-resilience-vulnerability concept

This study borrows the measures developed for the operation of water resources systems as a means of characterizing droughts in a given region. It is argued that the common approach of assessing drought using a univariate measure (severity or reliability) is inadequate as decision makers need assessment of the other facets considered here. It is proposed that the joint distribution of reliability, resilience, and vulnerability (referred to as RRV in a reservoir operation context), assessed using soil moisture data over the study region, be used to characterize droughts. Use is made of copulas to quantify the joint distribution between these variables. As reliability and resilience vary in a nonlinear but almost deterministic way, the joint probability distribution of only resilience and vulnerability is modeled. Recognizing the negative association between the two variables, a Plackett copula is used to formulate the joint distribution. The developed drought index, referred to as the drought management index (DMI), is able to differentiate the drought proneness of a given area when compared to other areas. An assessment of the sensitivity of the DMI to the length of the data segments used in evaluation indicates relative stability is achieved if the data segments are 5years or longer. The proposed approach is illustrated with reference to the Malaprabha River basin in India, using four adjoining Climate Prediction Center grid cells of soil moisture data that cover an area of approximately 12,000 km(2). (C) 2013 American Society of Civil Engineers.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Converses For Secret Key Agreement and Secure Computing

We consider information theoretic secret key (SK) agreement and secure function computation by multiple parties observing correlated data, with access to an interactive public communication channel. Our main result is an upper bound on the SK length, which is derived using a reduction of binary hypothesis testing to multiparty SK agreement. Building on this basic result, we derive new converses for multiparty SK agreement. Furthermore, we derive converse results for the oblivious transfer problem and the bit commitment problem by relating them to SK agreement. Finally, we derive a necessary condition for the feasibility of secure computation by trusted parties that seek to compute a function of their collective data, using an interactive public communication that by itself does not give away the value of the function. In many cases, we strengthen and improve upon previously known converse bounds. Our results are single-shot and use only the given joint distribution of the correlated observations. For the case when the correlated observations consist of independent and identically distributed (in time) sequences, we derive strong versions of previously known converses.

Full current statistics for a disordered open exclusion process

We consider the nonabelian sandpile model defined on directed trees by Ayyer et al. (2015 Commun. Math. Phys. 335 1065). and restrict it to the special case of a one-dimensional lattice of n sites which has open boundaries and disordered hopping rates. We focus on the joint distribution of the integrated currents across each bond simultaneously, and calculate its cumulant generating function exactly. Surprisingly, the process conditioned on seeing specified currents across each bond turns out to be a renormalised version of the same process. We also remark on a duality property of the large deviation function. Lastly, all eigenvalues and both Perron eigenvectors of the tilted generator are determined.