Effects of seeds treated with cobalt nanoparticles on germination, growth, yield and quality of soybean cultivar DT12

Seed treatment using metallic nanoparticles to stimulate germination and improve crop yields has been published and widely applied in agriculture production. To assess the safety of such methods on plants, the effectiveness and safety of the treatment of soybean Glycine max L. DT12 seeds with cobalt nanoparticles (nCo) before sowing were investigated. Seeds of soybean cultivar DT12 were treated with nCo at two different concentrations (0.165 and 1.65 mg/kg seed) before sowing. Germination rate, growth speed, soybean yield and bean nutrient components were examined throughout a season. Results implied that at a concentration of 0.165 mg/kg, nCo significantly increased germination rates, plant heights, total pods per plant, number of pods having 3 seeds, and crop productivity compared to both the control and seeds treated with a highter concentration of 16.5 mg per kg of seed. However, no significant differences were found between treatments in terms of growth level and seed nutrient contents, including moisture, ash content, mineral (K, Mg and Fe) and crude protein components. In seeds treated with higher concentration, the Ca content was dramatically lower than that of the control and seeds treated with a low concentration, but bean quality was not affected. This study contributes to the effective and sustainable application of nanomaterials in Vietnamese agriculture.

Depth of powers of edge ideals of Cohen-Macaulay trees

Let $I$ be the edge ideal of a Cohen-Macaulay tree of dimension $d$ over a polynomial ring $S = \mathrm{k}[x_1,\ldots,x_{d},y_1,\ldots,y_d]$. We prove that for all $t \ge 1$, $$\operatorname{depth} (S/I^t) = \operatorname{max} \{d -t + 1, 1 \}.$

Authenticating Operation-based History in Collaborative Systems

International audienceWithin last years multi-synchronous collaborative editing systems became widely used. Multi-synchronous collaboration maintains multiple, simultaneous streams of activity which continually diverge and synchronized. These streams of activity are represented by means of logs of operations, i.e. user modifications. A malicious user might tamper his log of operations. At the moment of synchronization with other streams, the tampered log might generate wrong results. In this paper, we propose a solution relying on hash-chain based authenticators for authenticating logs that ensure the authenticity, the integrity of logs, and the user accountability. We present algorithms to construct authenticators and verify logs. We prove their correctness and provide theoretical and practical evaluations

Log Auditing for Trust Assessment in Peer-to-Peer Collaboration

International audienceIn order to overcome the disadvantages of a central authority, a tendency is to move towards a peer-to-peer collaboration where control over data is given to users who can decide with whom they want to share their private data. In this peer-to-peer collaboration it is very difficult to ensure that after data is shared with other peers, these peers will not misbehave and violate data privacy. In this paper, we propose a mechanism that addresses the issue of data privacy violation by auditing the collaboration logs. In our approach, trust values between users are adjusted according to their previous activities on the shared data. Users share their private data by specifying some obligations the receivers are expected to follow. We log modifications done by users as well as the obligations and use a log-auditing mechanism to detect users who misbehaved. We adjust their associated trust values by using any existing decentralized trust model

A Log Auditing Approach for Trust Management in Peer-to-Peer Collaboration

Nowadays we are faced with an increasing popularity of social software including wikis, blogs, micro-blogs and online social networks such as Facebook and MySpace. Unfortunately, the mostly used social services are centralized and personal information is stored at a single vendor. This results in potential privacy problems as users do not have much control over how their private data is disseminated. To overcome this limitation, some recent approaches envisioned replacing the single authority centralization of services by a peer-to-peer trust-based approach where users can decide with whom they want to share their private data. In this peer-to-peer collaboration it is very difficult to ensure that after data is shared with other peers, these peers will not misbehave and violate data privacy. In this paper we propose a mechanism that addresses the issue of data privacy violation due to data disclosure to malicious peers. In our approach trust values between users are adjusted according to their previous activities on the shared data. Users share their private data by specifying some obligations the receivers must follow. We log modifications done by users on the shared data as well as the obligations that must be followed when data is shared. By a log-auditing mechanism we detect users that misbehaved and we adjust their associated trust values by using any existing decentralized trust model.Depuis quelques années nous assistons à une explosion de la popularité des logiciels sociaux comme les wikis, les blogs, les micro-blogs ou encore les réseaux sociaux tels que Facebook et MySpace. Malheureusement, les plus usités de ces services reposent tous sur un contrôle centralisé ; les données d'un utilisateur se retrouvant centralisées chez un seul fournisseur de service. Cela engendre indéniablement un problème de confidentialité puisque les utilisateurs n'ont plus le contrôle sur la manière dont leurs propres données sont diffusées. Afin de surpasser ces limitations, plusieurs approches récentes proposent de remplacer le contrôle centralisé de ces services par des approches pair-à-pair reposant sur des mécanismes de confiance où chaque usager décide avec qui il souhaite partager ces données personnelles. Toutefois, dans ce genre de collaboration, il est très difficile de s'assurer qu'une fois une donnée partagée avec des pairs, celle-ci ne soit pas divulguée à d'autres pairs non autorisés. Dans cet article, nous proposons un mécanisme qui permet de circonscrire les problèmes de violation de confidentialité liés à la divulgation de données par des pairs malicieux. Dans notre approche, les indices de confiance entre les usagers sont ajustés selon le comportement passé des usagers vis-à-vis des données partagées. Lorsqu'un usager partage des données, il impose aux autres usagers des obligations qu'ils doivent respecter. Chaque modification sur une donnée partagée effectuée par un usager et chaque obligation est répertoriée dans un journal. En réalisant un audit de ce journal, notre approche détecte les usagers qui se sont mal-comportés et ajuste en conséquence leurs indices de confiance

DoubleEcho: Mitigating Context-Manipulation Attacks in Copresence Verification

Copresence verification based on context can improve usability and strengthen security of many authentication and access control systems. By sensing and comparing their surroundings, two or more devices can tell whether they are copresent and use this information to make access control decisions. To the best of our knowledge, all context-based copresence verification mechanisms to date are susceptible to context-manipulation attacks. In such attacks, a distributed adversary replicates the same context at the (different) locations of the victim devices, and induces them to believe that they are copresent. In this paper we propose DoubleEcho, a context-based copresence verification technique that leverages acoustic Room Impulse Response (RIR) to mitigate context-manipulation attacks. In DoubleEcho, one device emits a wide-band audible chirp and all participating devices record reflections of the chirp from the surrounding environment. Since RIR is, by its very nature, dependent on the physical surroundings, it constitutes a unique location signature that is hard for an adversary to replicate. We evaluate DoubleEcho by collecting RIR data with various mobile devices and in a range of different locations. We show that DoubleEcho mitigates context-manipulation attacks whereas all other approaches to date are entirely vulnerable to such attacks. DoubleEcho detects copresence (or lack thereof) in roughly 2 seconds and works on commodity devices

A CONTRACT-EXTENDED PUSH-PULL-CLONE MODEL FOR MULTI-SYNCHRONOUS COLLABORATION

International audienceIn multi-synchronous collaboration users replicate shared data, modify it and redistribute modified versions of this data without the need of a central authority. However, in this model, no usage restriction mechanism was proposed to control what users can do with the data after it has been released to them. In this paper, we extend the multisynchronous collaboration model with contracts that express usage restrictions and that are checked a posteriori by users when they receive the modified data. We propose a merging algorithm that deals not only with changes on data but also with contracts. A log auditing protocol is used to detect users who do not respect contracts and to adjust user trust levels. Our contract-based model was implemented and evaluated by using PeerSim simulator