Decision-Making and the Newsvendor Problem – An Experimental Study

This paper investigates repetitive purchase decisions of perishable items in the face of uncertain demand (the newsvendor problem). The experimental design includes: high, or low profit levels; and uniform, or normal demand distributions. The results show that in all cases both learning and convergence occur and are effected by: (1) the mean demand; (2) the order-size of the maximal expected profit; and (3) the demand level of the immediately preceding round. In all cases of the experimental design, the purchase order converges to a value between the mean demand and the quantity for maximizing the expected profit.Inventory, Learning, Behavior, Management, Optimization

EFAB: Batch Production of Functional, Fully-Dense Metal Parts with Micron-Scale Features

EFAB (Electrochemical FABrication) is a new SFF process with the potential to economically fabricate prototypes or mass production quantities of functional, mesoscale-microscale parts and mechanisms. EFAB generates an entire layer simultaneously-versus serially, as with most SFF. Based on electrodeposition, EFAB allows ultra-thin layers (2-10 microns, or even submicron) that minimize stairsteps, and generates a net-shape, fully-dense metal structure that can be homogeneous and isotropic. Minimum feature width is approximately 25 microns, and can be reduced further. EFAB can be used to manufacture micromachines and microelectromechanical systems (MEMS), offering significant advantages over current processes: e.g., true 3-D geometry, IC compatibility, low capital investment, and process automation.Mechanical Engineerin

University vs. Society in a Period of Nation Building: The Hebrew University in Pre-State Israel

This article examines the process by which the Hebrew University of Jerusalem was established, from 1925-1948, during the period of the British Mandate in Palestine. It finds that the World Zionist Organization was deeply involved in this project, viewing a university as an important building block in the creation of a Jewish nationality in the Land of Israel. But alongside this Zionist role, Jewish communities around the world, particularly in Europe and the United States, also played an important academic and financial role in the establishment of the Hebrew University. This study reveals that, in contrast to the common pattern of close cooperation that is characteristic of relations between academic institutions and cohering national elites, the Hebrew University consistently pursued an academic policy that generated acute tension vis-à-vis the political leadership in Jewish Palestine. The University deliberately nurtured an elitist policy while rejecting attempts to make it service the general public needs, as defined by the local political leadership. Rather, the University saw its central role as being a “university for the dispersed nation,” that is, a university for all of the Jewish people.Cet article examine le processus au cours duquel l’Université hébraïque de Jérusalem fut établie de 1925 à 1948, alors que la Palestine était sous mandat britannique. Il montre que la World Zionist Organization fut profondément impliquée dans le projet, considérant l’université comme une importante composante de la création d’une nation juive en terre d’Israël. Mais à côté de ce rôle sioniste, les communautés juives du monde entier, particulièrement celles d’Europe et des États-Unis, jouèrent aussi un rôle académique et financier important dans l’établissement de l’Université hébraïque. Cette étude montre que, par opposition au modèle habituel de l’étroite coopération qui caractérise les relations entre les institutions académiques et les élites nationales unies, l’Université hébraïque poursuivit immanquablement une politique académique qui généra une vive tension au sein de la direction politique de la Palestine juive. L’Université alimenta délibérément une politique élitiste tout en rejetant les tentatives de la mettre au service de l’intérêt public général, comme il avait été décidé par la direction politique locale. Au lieu de cela, l’Université se considéra comme « une université de la diaspora », soit une université pour tout le peuple juif

The immune-body cytokine network defines a social architecture of cell interactions

BACKGROUND: Three networks of intercellular communication can be associated with cytokine secretion; one limited to cells of the immune system (immune cells), one limited to parenchymal cells of organs and tissues (body cells), and one involving interactions between immune and body cells (immune-body interface). These cytokine connections determine the inflammatory response to injury and subsequent healing as well as the biologic consequences of the adaptive immune response to antigens. We informatically probed the cytokine database to uncover the underlying network architecture of the three networks. RESULTS: We now report that the three cytokine networks are among the densest of complex networks yet studied, and each features a characteristic profile of specific three-cell motifs. Some legitimate cytokine connections are shunned (anti-motifs). Certain immune cells can be paired by their input-output positions in a cytokine architecture tree of five tiers: macrophages (MΦ) and B cells (BC) comprise the first tier; the second tier is formed by T helper 1 (Th1) and T helper 2 (Th2) cells; the third tier includes dendritic cells (DC), mast cells (MAST), Natural Killer T cells (NK-T) and others; the fourth tier is formed by neutrophils (NEUT) and Natural Killer cells (NK); and the Cytotoxic T cell (CTL) stand alone as a fifth tier. The three-cell cytokine motif architecture of immune system cells places the immune system in a super-family that includes social networks and the World Wide Web. Body cells are less clearly stratified, although cells involved in wound healing and angiogenesis are most highly interconnected with immune cells. CONCLUSION: Cytokine network architecture creates an innate cell-communication platform that organizes the biologic outcome of antigen recognition and inflammation. Informatics sheds new light on immune-body systems organization. REVIEWERS: This article was reviewed by Neil Greenspan, Matthias von Herrath and Anne Cooke

Neuronvisio: A Graphical User Interface with 3D Capabilities for NEURON

The NEURON simulation environment is a commonly used tool to perform electrical simulation of neurons and neuronal networks. The NEURON User Interface, based on the now discontinued InterViews library, provides some limited facilities to explore models and to plot their simulation results. Other limitations include the inability to generate a three-dimensional visualization, no standard mean to save the results of simulations, or to store the model geometry within the results. Neuronvisio (http://neuronvisio.org) aims to address these deficiencies through a set of well designed python APIs and provides an improved UI, allowing users to explore and interact with the model. Neuronvisio also facilitates access to previously published models, allowing users to browse, download, and locally run NEURON models stored in ModelDB. Neuronvisio uses the matplotlib library to plot simulation results and uses the HDF standard format to store simulation results. Neuronvisio can be viewed as an extension of NEURON, facilitating typical user workflows such as model browsing, selection, download, compilation, and simulation. The 3D viewer simplifies the exploration of complex model structure, while matplotlib permits the plotting of high-quality graphs. The newly introduced ability of saving numerical results allows users to perform additional analysis on their previous simulations

A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators

Classical streaming algorithms operate under the (not always reasonable) assumption that the input stream is fixed in advance. Recently, there is a growing interest in designing robust streaming algorithms that provide provable guarantees even when the input stream is chosen adaptively as the execution progresses. We propose a new framework for robust streaming that combines techniques from two recently suggested frameworks by Hassidim et al. [NeurIPS 2020] and by Woodruff and Zhou [FOCS 2021]. These recently suggested frameworks rely on very different ideas, each with its own strengths and weaknesses. We combine these two frameworks into a single hybrid framework that obtains the "best of both worlds", thereby solving a question left open by Woodruff and Zhou

Generalized Private Selection and Testing with High Confidence

Composition theorems are general and powerful tools that facilitate privacy accounting across multiple data accesses from per-access privacy bounds. However they often result in weaker bounds compared with end-to-end analysis. Two popular tools that mitigate that are the exponential mechanism (or report noisy max) and the sparse vector technique, generalized in a recent private selection framework by Liu and Talwar (STOC 2019). In this work, we propose a flexible framework of private selection and testing that generalizes the one proposed by Liu and Talwar, supporting a wide range of applications. We apply our framework to solve several fundamental tasks, including query releasing, top-k selection, and stable selection, with improved confidence-accuracy tradeoffs. Additionally, for online settings, we apply our private testing to design a mechanism for adaptive query releasing, which improves the sample complexity dependence on the confidence parameter for the celebrated private multiplicative weights algorithm of Hardt and Rothblum (FOCS 2010)

NERetrieve: Dataset for Next Generation Named Entity Recognition and Retrieval

Recognizing entities in texts is a central need in many information-seeking scenarios, and indeed, Named Entity Recognition (NER) is arguably one of the most successful examples of a widely adopted NLP task and corresponding NLP technology. Recent advances in large language models (LLMs) appear to provide effective solutions (also) for NER tasks that were traditionally handled with dedicated models, often matching or surpassing the abilities of the dedicated models. Should NER be considered a solved problem? We argue to the contrary: the capabilities provided by LLMs are not the end of NER research, but rather an exciting beginning. They allow taking NER to the next level, tackling increasingly more useful, and increasingly more challenging, variants. We present three variants of the NER task, together with a dataset to support them. The first is a move towards more fine-grained -- and intersectional -- entity types. The second is a move towards zero-shot recognition and extraction of these fine-grained types based on entity-type labels. The third, and most challenging, is the move from the recognition setup to a novel retrieval setup, where the query is a zero-shot entity type, and the expected result is all the sentences from a large, pre-indexed corpus that contain entities of these types, and their corresponding spans. We show that all of these are far from being solved. We provide a large, silver-annotated corpus of 4 million paragraphs covering 500 entity types, to facilitate research towards all of these three goals.Comment: Findings of EMNLP 202