An ant colony optimization algorithm for DNA sequencing by hybridization

The reconstruction of DNA sequences from DNA fragments is one of the most challenging problems in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. Several metaheuristics such as tabu search and evolutionary algorithms have been applied to this problem. However, the performance of existing metaheuristics is often inferior to the performance of recently proposed constructive heuristics. On the basis of these new heuristics we develop an ant colony optimization algorithm for DNA sequencing by hybridization. An important feature of this algorithm is the implementation in a so-called multi-level framework. The computational results show that our algorithm is currently a state-of-the-art method for the tackled problem.     

A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.     

Using visual and text features for direct marketing on multimedia messaging services domain

Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.

Malicious uses of blockchains by malware: from the analysis to Smart-Zephyrus

The permanent availability and relative obscurity of blockchains is the perfect ground for using them for malicious purposes. However, the use of blockchains by malwares has not been characterized yet. This paper analyses the current state of the art in this area. One of the lessons learned is that covert communications for malware have received little attention. To foster further defence-oriented research, a novel mechanism (dubbed Smart-Zephyrus) is built leveraging smart contracts written in Solidity. Our results show that it is possible to hide 4 Kb of secret in 41 s. While being expensive (around USD 1.82 per bit), the provided stealthiness might be worth the price for attackers.

     

Indirect Exciton–Phonon Dynamics in MoS2 Revealed by Ultrafast Electron Diffraction

Transition metal dichalcogenides layered nano-crystals are emerging as promising candidates for next-generation optoelectronic and quantum devices. In such systems, the interaction between excitonic states and atomic vibrations is crucial for many fundamental properties, such as carrier mobilities, quantum coherence loss, and heat dissipation. In particular, to fully exploit their valley-selective excitations, one has to understand the many-body exciton physics of zone-edge states. So far, theoretical and experimental studies have mainly focused on the exciton–phonon dynamics in high-energy direct excitons involving zone-center phonons. Here, ultrafast electron diffraction and ab initio calculations are used to investigate the many-body structural dynamics following nearly- resonant excitation of low-energy indirect excitons in MoS₂. By exploiting the large momentum carried by scattered electrons, the excitation of in-plane K- and Q- phonon modes are identified with 𝑬^′ symmetry as key for the stabilization of indirect excitons generated via near-infrared light at 1.55 eV, and light is shed on the role of phonon anharmonicity and the ensuing structural evolution of the MoS₂ crystal lattice. The results highlight the strong selectivity of phononic excitations directly associated with the specific indirect- exciton nature of the wavelength-dependent electronic transitions triggered in the system.     

Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation

The proposed European Artificial Intelligence Act (AIA) is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can (and should) be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the conformity assessments that providers of high-risk AI systems are expected to conduct, and the post-market monitoring plans that providers must establish to document the performance of high-risk AI systems throughout their lifetimes. We argue that the AIA can be interpreted as a proposal to establish a Europe-wide ecosystem for conducting AI auditing, albeit in other words. Our analysis offers two main contributions. First, by describing the enforcement mechanisms included in the AIA in terminology borrowed from existing literature on AI auditing, we help providers of AI systems understand how they can prove adherence to the requirements set out in the AIA in practice. Second, by examining the AIA from an auditing perspective, we seek to provide transferable lessons from previous research about how to refine further the regulatory approach outlined in the AIA. We conclude by highlighting seven aspects of the AIA where amendments (or simply clarifications) would be helpful. These include, above all, the need to translate vague concepts into verifiable criteria and to strengthen the institutional safeguards concerning conformity assessments based on internal checks.

     

Sorafenib delivery nanoplatform based on superparamagnetic iron oxide nanoparticles magnetically targets hepatocellular carcinoma

Currently,sorafenib is the only systemic therapy capable of increasing overall survival of hepatocellular carcinoma patients.Unfortunately,its side effects,particularly its overall toxicity,limit the therapeutic response that can be achieved.Superparamagnetic iron oxide nanoparticles (SPIONs) are very attractive for drug delivery because they can be targeted to specific sites in the body through application of a magnetic field,thus improving intratumoral accumulation and reducing adverse effects.Here,nanoformulations based on polyethylene glycol modified phospholipid micelles,loaded with both SPIONs and sorafenib,were successfully prepared and thoroughly investigated by complementary techniques.This nanovector system provided effective drug delivery,had an average hydrodynamic diameter of about 125 nm,had good stability in aqueous medium,and allowed controlled drug loading.Magnetic analysis allowed accurate determination of the amount of SPIONs embedded in each micelle.An in vitro system was designed to test whether the SPION micelles can be efficiently held using a magnetic field under typical flow conditions found in the human liver.Human hepatocellular carcinoma (HepG2) cells were selected as an in vitro system to evaluate tumor cell targeting efficacy of the superparamagnetic micelles loaded with sorafenib.These experiments demonstrated that this delivery platform is able to enhance sorafenib's antitumor effectiveness by magnetic targeting.The magnetic nanovectors described here represent promising candidates for targeting specific hepatic tumor sites,where selective release of sorafenib can improve its efficacy and safety profile.     

Nanowire encapsulation with polymer for electrical isolation and enhanced optical properties

Light management and electrical isolation are essential for the majority of optoelectronic nanowire (NW) devices.Here,we present a cost-effective technique,based on vapor-phase deposition of parylene-C and subsequent annealing,that provides conformal encapsulation,anti-reflective coating,improved optical properties,and electrical insulation for GaAs nanowires.The process presented allows facile encapsulation and insulation that is suitable for any nanowire structure.In particular,the parylene-C encapsulation functions as an efficient antireflection coating for the nanowires,with reflectivity down to ＜1％ in the visible spectrum.Furthermore,the parylene-C coating increases photoluminescence intensity,suggesting improved light guiding to the NWs.Finally,based on this process,a NW LED was fabricated,which showed good diode performance and a clear electroluminescence signal.We believe the process can expand the fabrication possibilities and improve the performance of optoelectronic nanowire devices.