Basing cryptographic protocols on tamper-evident seals

In this article, we attempt to formally study two very intuitive physical models: sealed envelopes and locked boxes, often used as illustrations for common cryptographic operations. We relax the security properties usually required from locked boxes [such as in bit-commitment (BC) protocols] and require only that a broken lock or torn envelope be identifiable to the original sender. Unlike the completely impregnable locked box, this functionality may be achievable in real life, where containers having this property are called “tamper-evident seals”. Another physical object with this property is the “scratch-off card”, often used in lottery tickets. We consider three variations of tamper-evident seals, and show that under some conditions they can be used to implement oblivious transfer, BC and coin flipping (CF). We also show a separation between the three models. One of our results is a strongly fair CF protocol with bias bounded by O(1/r) (where r is the number of rounds); this was a stepping stone towards achieving such a protocol in the standard model (in subsequent work).     

Elucidating the Response of Crop Plants towards Individual,Combined and Sequentially Occurring Abiotic Stresses

In nature, plants are exposed to an ever-changing environment with increasing frequencies of multiple abiotic stresses. These abiotic stresses act either in combination or sequentially, thereby driving vegetation dynamics and limiting plant growth and productivity worldwide. Plants’ responses against these combined and sequential stresses clearly differ from that triggered by an individual stress. Until now, experimental studies were mainly focused on plant responses to individual stress, but have overlooked the complex stress response generated in plants against combined or sequential abiotic stresses, as well as their interaction with each other. However, recent studies have demonstrated that the combined and sequential abiotic stresses overlap with respect to the central nodes of their interacting signaling pathways, and their impact cannot be modelled by swimming in an individual extreme event. Taken together, deciphering the regulatory networks operative between various abiotic stresses in agronomically important crops will contribute towards designing strategies for the development of plants with tolerance to multiple stress combinations. This review provides a brief overview of the recent developments in the interactive effects of combined and sequentially occurring stresses on crop plants. We believe that this study may improve our understanding of the molecular and physiological mechanisms in untangling the combined stress tolerance in plants, and may also provide a promising venue for agronomists, physiologists, as well as molecular biologists.     

Regulatory Changes Affecting the Production and Use of Fats and Oils: Focus on Partially Hydrogenated Oils

Partially hydrogenated oils (PHO), the products of incomplete catalytic hydrogenation of food oils, have been widely employed by the food industry for more than a century. Their exceptional stability and technologic characteristics made them the preferred choice for the production of several food products including margarines, bakery goods, and frying oils. Some of these highly prized characteristics were provided by the high content in trans fatty acids (TFA), defined as fatty acids with one or more isolated double bond in trans configuration. The discovery of negative health effects associated with dietary intake of TFA triggered world-wide a wave of regulatory actions aimed to curb their consumption. PHO became the main target of most campaigns aimed to reduce consumption of TFA, and their fortune in the food industry progressively faded. At the 2017, AOCS Annual Meeting in Orlando, a group of experts from regulatory agencies and industry from North America and Europe met to discuss the current status of government regulations and industry adaptations regarding the productions and use of PHO. The discussion was enriched by including the impact on fats and oils production of the 2016 amendment of the Toxic Substances Control Act of 1976 (TSCA). The present publication may not include all regulatory changes that took place after this symposium, in 2017.     

“Designer” scaffolds for tissue engineering and regeneration

Tissue engineering entails the in vitro or in vivo generation of replacement tissues from cells with the aid of supporting scaffolds and stimulating biomolecules, in order to provide biological substitutes for restoration and maintenance of human tissue functions. In this review, we summarize the main classes of degradable polymeric scaffolds, natural and synthetic ones, and the evolution made in this field from adaptation of materials in clinical use to the fabrication of “designer” scaffolds.     

Enantiomeric Control of Intrinsically Chiral Nanocrystals

The chiral aspect of inorganic crystals that crystallize in chiral space groups has been largely ignored until recently, partly due to difficulties in characterizing the chiroptical properties of bulk crystals, and also due to the difficulty in separating (sub)micrometer-scale chiral crystal enantiomers. In recent years, the colloidal synthesis of intrinsically chiral nanocrystals (NCs) of several chiral inorganic compounds with significant enantiomeric excess has been demonstrated. This is achieved through the use of chiral molecular ligands, which bind to the atomic/ionic components of the crystals, preferentially forming one crystal enantiomorph. Here, recent progress on several aspects of these NCs is described, including the connection between ligand structure and its ability to direct NC handedness, chiral amplification in the synthesis leading to enantiopure NC samples, spontaneous symmetry breaking, the formation of NCs with chiral shapes, the connection between lattice and shape chirality and mixed contributions of atomic-scale and shape chirality to the chiroptical properties.     

Anytime similarity measures for faster alignment

Image alignment refers to finding the best transformation from a fixed reference image to a new image of a scene. This process is often optimizing a similarity measure between images, computed based on the image data. However, in time-critical applications state-of-the-art methods for computing similarity are too slow. Instead of using all the image data to compute similarity, one could use only a subset of pixels to improve the speed, but often this comes at the cost of reduced accuracy. These kinds of tradeoffs between the amount of computation and the accuracy of the result have been addressed in the field of real-time artificial intelligence as deliberation control problems. We propose that the optimization of a similarity measure is a natural application domain for deliberation control using the anytime algorithm framework. In this paper, we present anytime versions for the computation of two common image similarity measures: mean squared difference and mutual information. Off-line, we learn a performance profile specific to each measure, which is then used on-line to select the appropriate amount of pixels to process at each optimization step. When tested against existing techniques, our method achieves comparable quality and robustness with significantly less computation.     

Collaboration within large groups in the classroom

The purpose of this paper is to show how a large group of students can work collaboratively in a synchronous way within the classroom using the cheapest possible technological support. Making use of the features of Single Display Groupware and of Multiple Mice we propose a computer-supported collaborative learning approach for big groups within the classroom. The approach uses a multiple classification matrix and our application was built for language-learning (in this case Spanish). The basic collaboration mechanism that the approach is based upon is “silent collaboration,” in which students—through suggestions and exchanges—must compare their ideas to those of their classmates. An exploratory experimental study was performed along with a quantitative and qualitative study that analyzed ease of use of the software, described how the conditions for collaborative learning were achieved, evaluated the achievements in learning under the defined language objectives, and analyzed the impact of silent and spoken collaboration. Our initial findings are that silent collaboration proved to be an effective mechanism to achieve learning in large groups in the classroom.     

Unsupervised named-entity extraction from the Web: An experimental study

The KnowItAll system aims to automate the tedious process of extracting large collections of facts (e.g., names of scientists or politicians) from the Web in an unsupervised, domain-independent, and scalable manner. The paper presents an overview of KnowItAll's novel architecture and design principles, emphasizing its distinctive ability to extract information without any hand-labeled training examples. In its first major run, KnowItAll extracted over 50,000 class instances, but suggested a challenge: How can we improve KnowItAll's recall and extraction rate without sacrificing precision?This paper presents three distinct ways to address this challenge and evaluates their performance. Pattern Learning learns domain-specific extraction rules, which enable additional extractions. Subclass Extraction automatically identifies sub-classes in order to boost recall (e.g., “chemist” and “biologist” are identified as sub-classes of “scientist”). List Extraction locates lists of class instances, learns a “wrapper” for each list, and extracts elements of each list. Since each method bootstraps from KnowItAll's domain-independent methods, the methods also obviate hand-labeled training examples. The paper reports on experiments, focused on building lists of named entities, that measure the relative efficacy of each method and demonstrate their synergy. In concert, our methods gave KnowItAll a 4-fold to 8-fold increase in recall at precision of 0.90, and discovered over 10,000 cities missing from the Tipster Gazetteer.     

Automatic inference of complex affective states

Affective states and their non-verbal expressions are an important aspect of human reasoning, communication and social life. Automated recognition of affective states can be integrated into a wide variety of applications for various fields. Therefore, it is of interest to design systems that can infer the affective states of speakers from the non-verbal expressions in speech, occurring in real scenarios. This paper presents such a system and the framework for its design and validation. The framework defines a representation method that comprises a set of affective-state groups or archetypes that often appear in everyday life. The inference system is designed to infer combinations of affective states that can occur simultaneously and whose level of expression can change over time. The framework considers also the validation and generalisation of the system. The system was built of 36 independent pair-wise comparison machines, with average accuracy (tenfold cross-validation) of 75%. The accumulated inference system yielded total accuracy of 83% and recognised combinations for different nuances within the affective-state groups. In addition to the ability to recognise these affective-state groups, the inference system was applied to characterisation of a very large variety of affective state concepts (549 concepts) as combinations of the affective-state groups. The system was also applied to annotation of affective states that were naturally evoked during sustained human–computer interactions and multi-modal analysis of the interactions, to new speakers and to a different language, with no additional training. The system provides a powerful tool for recognition, characterisation, annotation (interpretation) and analysis of affective states. In addition, the results inferred from speech in both English and Hebrew, indicate that the vocal expressions of complex affective states such as thinking, certainty and interest transcend language boundaries.