Technion – Israel Institute of Technology

About: Technion – Israel Institute of Technology is a education organization based out in Haifa, Israel. It is known for research contribution in the topics: Population & Upper and lower bounds. The organization has 31714 authors who have published 79377 publications receiving 2603976 citations. The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.

A Dialectic Perspective on Innovation: Conflicting Demands, Multiple Pathways, and Ambidexterity

Abstract: Innovation, the development and intentional introduction of new and useful ideas by individuals, teams, and organizations, lies at the heart of human adaptation. Decades of research in different disciplines and at different organizational levels have produced a wealth of knowledge about how innovation emerges and the factors that facilitate and inhibit innovation. We propose that this knowledge needs integration. In an initial step toward this goal, we apply a dialectic perspective on innovation to overcome limitations of dichotomous reasoning and to gain a more valid account of innovation. We point out that individuals, teams, and organizations need to self-regulate and manage conflicting demands of innovation and that multiple pathways can lead to idea generation and innovation. By scrutinizing the current use of the concept of organizational ambidexterity and extending it to individuals and teams, we develop a framework to help guide and facilitate future research and practice. Readers expecting specific and universal prescriptions of how to innovate will be disappointed as current research does not allow such inferences. Rather, we think innovation research should focus on developing and testing principles of innovation management in addition to developing decision aids for organizational practice. To this end, we put forward key propositions and action principles of innovation management.

Degradation of Cdc25A by β-TrCP during S phase and in response to DNA damage

Abstract: The Cdc25A phosphatase is essential for cell-cycle progression because of its function in dephosphorylating cyclin-dependent kinases. In response to DNA damage or stalled replication, the ATM and ATR protein kinases activate the checkpoint kinases Chk1 and Chk2, which leads to hyperphosphorylation of Cdc25A. These events stimulate the ubiquitin-mediated proteolysis of Cdc25A and contribute to delaying cell-cycle progression, thereby preventing genomic instability. Here we report that beta-TrCP is the F-box protein that targets phosphorylated Cdc25A for degradation by the Skp1/Cul1/F-box protein complex. Downregulation of beta-TrCP1 and beta-TrCP2 expression by short interfering RNAs causes an accumulation of Cdc25A in cells progressing through S phase and prevents the degradation of Cdc25A induced by ionizing radiation, indicating that beta-TrCP may function in the intra-S-phase checkpoint. Consistent with this hypothesis, suppression of beta-TrCP expression results in radioresistant DNA synthesis in response to DNA damage--a phenotype indicative of a defect in the intra-S-phase checkpoint that is associated with an inability to regulate Cdc25A properly. Our results show that beta-TrCP has a crucial role in mediating the response to DNA damage through Cdc25A degradation.

A construction of a cipher from a single pseudorandom permutation

Abstract: We suggest a scheme for a block cipher which uses only one randomly chosen permutation,F. The key, consisting of two blocks,K 1 andK 2, is used in the following way. The message block is XORed withK 1 before applyingF, and the outcome is XORed withK 2, to produce the cryptogram block. We show that the resulting cipher is secure (when the permutation is random or pseudorandom). This removes the need to store, or generate a multitude of permutations.

Wikipedia-based semantic interpretation for natural language processing

Abstract: Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was based on purely statistical techniques that did not make use of background knowledge, on limited lexicographic knowledge bases such as WordNet, or on huge manual efforts such as the CYC project. Here we propose a novel method, called Explicit Semantic Analysis (ESA), for fine-grained semantic interpretation of unrestricted natural language texts. Our method represents meaning in a high-dimensional space of concepts derived from Wikipedia, the largest encyclopedia in existence. We explicitly represent the meaning of any text in terms of Wikipedia-based concepts. We evaluate the effectiveness of our method on text categorization and on computing the degree of semantic relatedness between fragments of natural language text. Using ESA results in significant improvements over the previous state of the art in both tasks. Importantly, due to the use of natural concepts, the ESA model is easy to explain to human users.