Self‐Assembling,Bioinspired Wax Crystalline Surfaces with Time‐Dependent Wettability

One of the most fascinating properties of materials in nature is the superhydrophobic and self‐cleaning capabilities of different plant surfaces. This is usually achieved by the hydrophobic cuticles that are made of cutin and contain wax crystals both within them and on their surfaces. Here, bioinspired n‐hexatriacontane wax films are deposited via thermal evaporation and it is shown that the surface evolves in time via self‐assembly. This leads to a dramatic change in the wetting properties with a transition from hydrophobic to superhydrophobic characteristics, which takes place within several days at room temperature. This phenomenon is investigated and strain‐induced recrystallization is proposed to be the mechanism for it. This work could become the basis for the inspiration and production of tuned, time‐dependant, temperature‐sensitive, variable‐wettability surfaces.     

Sleeved co-clustering of lagged data

The paper focuses on mining clusters that are characterized by a lagged relationship between the data objects. We call such clusters lagged co-clusters. A lagged co-cluster of a matrix is a submatrix determined by a subset of rows and their corresponding lag over a subset of columns. Extracting such subsets may reveal an underlying governing regulatory mechanism. Such a regulatory mechanism is quite common in real-life settings. It appears in a variety of fields: meteorology, seismic activity, stock market behavior, neuronal brain activity, river flow, and navigation, but a limited list of examples. Mining such lagged co-clusters not only helps in understanding the relationship between objects in the domain, but assists in forecasting their future behavior. For most interesting variants of this problem, finding an optimal lagged co-cluster is NP-complete problem. We present a polynomial-time Monte-Carlo algorithm for mining lagged co-clusters. We prove that, with fixed probability, the algorithm mines a lagged co-cluster which encompasses the optimal lagged co-cluster by a maximum 2 ratio columns overhead and completely no rows overhead. Moreover, the algorithm handles noise, anti-correlations, missing values, and overlapping patterns. The algorithm is extensively evaluated using both artificial and real-world test environments. The first enable the evaluation of specific, isolated properties of the algorithm. The latter (river flow and topographic data) enable the evaluation of the algorithm to efficiently mine relevant and coherent lagged co-clusters in environments that are temporal, i.e., time reading data and non-temporal.     

Jitter-approximation tradeoff for periodic scheduling

We consider an asymmetric wireless communication setting, where a server periodically broadcasts data items to different mobile clients. The goal is to serve items into a prescribed rate, while minimizing the energy consumption of the mobile users. Abstractly, we are presented with a set of jobs, each with a known execution time and a requested period, and the task is to design a schedule for these jobs over a single shared resource without preemption. Given any solution schedule, its period approximation is the maximal factor by which the average period of a job in the schedule is blown up w.r.t. its requested period, and the jitter is roughly the maximal variability of times between two consecutive occurrences of the same job. Schedules with low jitter allow the mobile devices to save power by having their receivers switched off longer. In this paper we consider a scenario where clients may be willing to settle for non-optimal period approximation so that the jitter is improved. We present a parametric jitter-approximation tradeoff algorithm that allows us to choose various combinations between jitter optimality and period optimality for any given set of jobs. Zvika Brakerski was born in 1981. He received a masters’ degree from Tel-Aviv University in 2002 and is currently employed as an Electric Engineer. Boaz Patt-Shamir received his PhD from MIT in 1995. He was an assistant professor in Northeastern University until 1997, and then he joined the Dept. of Electrical Engineering in Tel Aviv University, where he directs the Computer Communication and Multimedia Laboratory. He held visiting positions at MIT, Boston University, Bellcore, and HP Labs.     

Arma spectral estimation based on partial autocorrelations — Part II: Statistical analysis

In a previous paper [1], a new algorithm for ARMA spectral estimation of stationary time series has been presented. The algorithm is based on nonlinear least squares fit of the sample partial autocorrelations to the partial autocorrelations generated by the assumed ARMA model. This paper explores the statistical properties of the above algorithm, including some numerical examples of the asymptotic variance of the estimated parameters, as compared to the Cramer-Rao bound. The results confirm the good performance of the algorithm and suggest an improvement in its implementation.     

MODELS FOR IMPROVED EFFECTIVENESS BASED ON DEA EFFICIENCY RESULTS

Following the characterization via Data Envelopment Analysis (DEA) of managerial units as efficient or inefficient, management will wish to increase profitability and/or control costs while becoming (or remaining) technically efficient in the DEA sense. This paper presents three families of models for achieving this and describes the managerial situations in which they are useful. The first addresses the management of an existing Decision Making Unit (DMU) and die second attempts to identify the desired “location” for a new DMU. The third addresses the aggregate of all DMUs, reallocating scarce resources among them for maximum overall organizational profitability and technical efficiency.     

Development of a sweet pepper harvesting robot

This paper presents the development, testing and validation of SWEEPER, a robot for harvesting sweet pepper fruit in greenhouses. The robotic system includes a six degrees of freedom industrial arm equipped with a specially designed end effector, RGB‐D camera, high‐end computer with graphics processing unit, programmable logic controllers, other electronic equipment, and a small container to store harvested fruit. All is mounted on a cart that autonomously drives on pipe rails and concrete floor in the end‐user environment. The overall operation of the harvesting robot is described along with details of the algorithms for fruit detection and localization, grasp pose estimation, and motion control. The main contributions of this paper are the integrated system design and its validation and extensive field testing in a commercial greenhouse for different varieties and growing conditions. A total of 262 fruits were involved in a 4‐week long testing period. The average cycle time to harvest a fruit was 24 s. Logistics took approximately 50% of this time (7.8 s for discharge of fruit and 4.7 s for platform movements). Laboratory experiments have proven that the cycle time can be reduced to 15 s by running the robot manipulator at a higher speed. The harvest success rates were 61% for the best fit crop conditions and 18% in current crop conditions. This reveals the importance of finding the best fit crop conditions and crop varieties for successful robotic harvesting. The SWEEPER robot is the first sweet pepper harvesting robot to demonstrate this kind of performance in a commercial greenhouse.     

Distributed discovery of large near-cliques

Given an undirected graph and 0 ￡ e ￡ 1{0\le\epsilon\le1}, a set of nodes is called an e{\epsilon}-near clique if all but an e{\epsilon} fraction of the pairs of nodes in the set have a link between them. In this paper we present a fast synchronous network algorithm that uses small messages and finds a near-clique. Specifically, we present a constant-time algorithm that finds, with constant probability of success, a linear size e{\epsilon}-near clique if there exists an e³{\epsilon^3}-near clique of linear size in the graph. The algorithm uses messages of O(log n) bits. The failure probability can be reduced to n ^−Ω(1) by increasing the time complexity by a logarithmic factor, and the algorithm also works if the graph contains a clique of size Ω(n/(log log n) ^α ) for some a ? (0,1){\alpha \in (0,1)}. Our approach is based on a new idea of adapting property testing algorithms to the distributed setting.     

Theoretical Cryptanalysis of the Klimov-Shamir Number Generator TF-1

The internal state of the Klimov-Shamir number generator TF-1 consists of four words of size w bits each, whereas its intended strength is 2^2w. We exploit an asymmetry in its output function to show that the internal state can be recovered after having 2^w outputs, using 2^1.5w operations. For w = 32 the attack is practical, but for their recommended w = 64 it is only of theoretical interest.     

Alleviation of Severe Skin Insults Following High-Dose Irradiation with Isolated Human Fetal Placental Stromal Cells

Skin exposure to high-dose irradiation, as commonly practiced in radiotherapy, affects the different skin layers, causing dry and wet desquamation, hyperkeratosis fibrosis, hard to heal wounds and alopecia and damaged hair follicles. Fetal tissue mesenchymal stromal cells (f-hPSC) were isolated from excised human fetal placental tissue, based on their direct migration from the tissue samples to the tissue dish. The current study follows earlier reports on for the mitigation of acute radiation syndrome following whole body high-dose exposure with remotely injected f-hPSC. Both the head only and a back skin flap of mice were irradiated with 16 &18 Gy, respectively, by 6MeV clinical linear accelerator electron beam. In both locations, the irradiated skin areas developed early and late radiation induced skin damages, including cutaneous fibrosis, lesions, scaring and severe hair follicle loss and reduced hair pigmentation. Injection of 2 × 10⁶ f-hPSC, 3 and 8 weeks following 16 Gy head irradiation, and 1 and 4 weeks following the 18 Gy back skin only irradiation, resulted in significantly faster healing of radiation induced damages, with reduction of wet desquamation as measured by surface moisture level and minor recovery of the skin viscoelasticity. Detailed histological morphometry showed a clear alleviation of radiation induced hyperkeratosis in f-hPSC treated mice, with significant regain of hair follicles density. Following 16 Gy head irradiation, the hair follicles density in the scalp skin was reduced significantly by almost a half relative to the controls. A nearly full recovery of hair density was found in the f-hPSC treated mice. In the 18 Gy irradiated back skin, the hair follicles density dropped in a late stage by ~70% relative to naïve controls. In irradiated f-hPSC treated mice, it was reduced by only ~30% and was significantly higher than the non-treated group. Our results suggest that local injections of xenogeneic f-hPSC could serve as a simple, safe and highly effective non-autologous pro-regenerative treatment for high-dose radiation induced skin insults. We expect that such treatment could also be applied for other irradiated organs.