Experimental modelling of free-surface dry granular flows under a centrifugal acceleration field

We investigate the dynamics of granular flows under the action of a centrifugal acceleration field. The granular flows consist of a monodisperse set of glass beads flowing down an inclined plane. The experiments are performed at variable slope angles \(\zeta \) and equivalent centrifugal accelerations \(a_\text {cf}\equiv Ng\). We study the effect of this parameters on the superficial flow velocity u and flow height h. Two trends are observed, by increasing \(\zeta \) and \(a_\text {cf}\), u increases proportionally, and h decreases asymptotically until a constant height. This relation is analysed in terms of the system potential and kinetic energy, leading to the estimation of equivalent impact forces one order of magnitude larger than those observed in small scale 1g laboratory experiments, with the possibility to reach higher forces by increasing N. Finally, considering the trend of u and h, our results suggest a scaling principle of inertial velocity proportional to \(\sqrt{N}\).     

Bandwidth selection in kernel density estimation for interval-grouped data

When interval-grouped data are available, the classical Parzen–Rosenblatt kernel density estimator has to be modified to get a computable and useful approach in this context. The new nonparametric grouped data estimator needs of the choice of a smoothing parameter. In this paper, two different bandwidth selectors for this estimator are analyzed. A plug-in bandwidth selector is proposed and its relative rate of convergence obtained. Additionally, a bootstrap algorithm to select the bandwidth in this framework is designed. This method is easy to implement and does not require Monte Carlo. Both proposals are compared through simulations in different scenarios. It is observed that when the sample size is medium or large and grouping is not heavy, both bandwidth selection methods have a similar and good performance. However, when the sample size is large and under heavy grouping scenarios, the bootstrap bandwidth selector leads to better results.     

Colloidal Quantum Dot Infrared Lasers Featuring Sub-Single-Exciton Threshold and Very High Gain

The use of colloidal quantum dots (CQDs) as a gain medium in infrared laser devices has been underpinned by the need for high pumping intensities, very short gain lifetimes, and low gain coefficients. Here, PbS/PbSSe core/alloyed-shell CQDs are employed as an infrared gain medium that results in highly suppressed Auger recombination with a lifetime of 485 ps, lowering the amplified spontaneous emission (ASE) threshold down to 300 µJ cm⁻², and showing a record high net modal gain coefficient of 2180 cm⁻¹. By doping these engineered core/shell CQDs up to nearly filling the first excited state, a significant reduction of optical gain threshold is demonstrated, measured by transient absorption, to an average-exciton population-per-dot 〈N^th〉_g of 0.45 due to bleaching of the ground state absorption. This in turn have led to a fivefold reduction in ASE threshold at 〈N^th〉_ASE = 0.70 excitons-per-dot, associated with a gain lifetime of 280 ps. Finally, these heterostructured QDs are used to achieve near-infrared lasing at 1670 nm at a pump fluences corresponding to sub-single-exciton-per-dot threshold (〈N^th〉_Las = 0.87). This work brings infrared CQD lasing thresholds on par to their visible counterparts, and paves the way toward solution-processed infrared laser diodes.     

An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL)

Diabetes therapy management in AAL environments, such as old people and diabetes patients homes, is a very difficult task since many factors affect a patient’s blood sugar levels. Factors such as illness, treatments, physical and psychological stress, physical activity, drugs, intravenous fluids and change in the meal plan cause unpredictable and potentially dangerous fluctuations in blood sugar levels. Right now, operations related to dosage are based on insulin infusion protocol boards, which are provided by physicians to the patients. These boards are not considering very influential factors such as glycemic index from the diet, consequently patients need to estimate the dosage leading to dose error, which culminates in hyperglycemia and hypoglycemia episode. Therefore, right insulin infusion calculation needs to be supported by the next generation of personal-care devices. For this reason, a personal device has been developed to assist and consider more factors in the insulin therapy dosage calculation. The proposed solution is based on Internet of things in order to, on the one hand, support a patient’s profile management architecture based on personal RFID cards and, on the other hand, provide global connectivity between the developed patient’s personal device based on 6LoWPAN, nurses/physicians desktop application to manage personal health cards, glycemic index information system, and patient’s web portal. This solution has been evaluated by a multidisciplinary group formed by patients, physicians, and nurses.     

Development of an automated platform for high-throughput P1-phage transduction of Escherichia coli

Synthetic biology depends on the ability to rapidly produce strains with improved phenotypes but is limited by the ability to rapidly produce strain collections with directed mutations. Here, we present a system capable of overcoming this limitation through automated P1-phage transductions of Escherichia coli. By combining the Keio collection of single-gene deletion E. coli mutants with P1-phage, it is possible to generate an engineered host-strain collection consisting of every possible gene deletion mutant. This strategy was tested by transducing 355 genetic markers from the Keio collection into five different host strains, and it achieved a 98% success rate. This method offers an improved mechanism for rapidly engineering collections of microbes and provides one method for rapidly deploying a broader synthetic biology effort.     

Differential evolution for solving the mobile location management

In this work we present two new approaches to solve the location management problem, respectively, based on the location areas and the reporting cells strategies. The location management problem corresponds to the management of the network configuration with the objective of minimizing the costs involved. We use the differential evolution algorithm to find the best configuration for the location areas and the reporting cells strategies, which principally considers the location update and paging costs. With this work we want to define the best values to the differential evolution configuration, using test networks and also realistic networks, as well as compare our results with the ones obtained by other authors. These two new approaches applied to this problem have given us very good results, when compared with those obtained by other authors.     

Efficient hardware architecture for the AES-CCM protocol of the IEEE 802.11i standard

Applications of wireless communications networks are emerging continuously. To offer a good level of security in these applications, new standards for wireless communications propose solutions based on cryptographic algorithms working on special modes of operation. This work presents a custom hardware architecture for the AES-CCM protocol (AES-CCMP) which is the basis for the security architecture of the IEEE 802.11i standard. AES-CCMP is based on the AES-CCM algorithm that performs the Advanced Encryption Standard (AES) in CTR with CBC-MAC mode (CCM mode), plus specialized data formatting modules, providing different security services through iterative and complex operations. Results of implementing the proposed architecture targeting FPGA devices are presented and discussed. A comparison against similar works shows significant improvements in terms of both throughput and efficiency.