An automatic procedure for the synthesis and optimization of very low-frequency Gm–C integrators

Fully integrated low frequency filters are critical cells that should be carefully designed in order to avoid excessive area occupation. In this work we propose an automatic procedure capable of optimizing the design of G_m?CC integrators, which constitute the basis of a wide class of G_m?CC filters. The optimization target is minimizing the cell area with constraints on input range and low frequency noise. Lower and upper bounds can be fixed to most quantities and design parameters in order to avoid solutions that are not compatible with the physical limitations of the process. The program has been developed within the MATLAB^? platform, exploiting the optimization toolbox. The effect of several important design parameters on the optimization of low frequency integrators has been investigated using the proposed routine. The strong interaction between noise and low frequency constraints has been demonstrated, showing the impressive impact of strict noise specifications on the occupied area. The actual effectiveness of parameters such as the current division factor or approaches such as flicker noise rejection by means of chopper modulation has been investigated. Examples of integrator synthesis, performed using the proposed procedure configured with the parameters of a commercial CMOS process, are presented. The consistence between the characteristics of the cells and the initial specifications has been checked using electrical simulations showing a maximum discrepancy with the initial specifications of nearly 80%. A semi-manual method to refine the synthesized cells and improve the accuracy is proposed.     

New Approach to Water Distribution Network Calibration

A new approach is proposed for calibrating hydraulic network models. This procedure uses a nonlinear optimization algorithm along with a standard, off-the-shelf, network solver. Pipe roughness is adjusted until simulation results agree with the values observed in the field. To achieve realistic calibrated roughness values, the objective is to minimize the sum of the squares of the differences between the calibrated and initial pipe roughness estimates, under a set of constraints determined from a sensitivity matrix. The algorithm is applied to a sample network, and the resulting calibrated network is tested under different loading conditions.     

Compensation for decreased expression of B7 molecules on Leishmania infantum-infected canine macrophages results in restoration of parasite-specific T-cell proliferation and gamma interferon production

Infection of humans and dogs by Leishmania infantum may result in visceral leishmaniasis, which is characterized by impaired T-cell-mediated immune responses to parasite antigens. Dogs are natural hosts of Leishmania parasites and play an important role in the transmission of the parasites to humans. In an effort to characterize the immune response in dogs infected with this intracellular pathogen, we examined how infection with L. infantum affects canine macrophages and the consequences for T-cell activation in vitro. We showed that the proliferation of T-cell lines to cognate antigen decreases to background levels when infected autologous monocyte-derived macrophages are used as antigen-presenting cells (APC). The observed reduction of antigen-specific T-cell proliferation was shown to be dependent on the parasite load and to require cell-to-cell interaction of T cells with the infected APC. In addition, we observed a decreased expression of costimulatory B7 molecules on infected monocyte-derived macrophages. The expression of other surface molecules involved in T-cell activation, such as major histocompatibility complex class I and class II, on these cells did not change upon infection, whereas the expression of intracellular adhesion molecule 1 was marginally increased. Compensation for the decreased expression of B7 molecules by the addition of B7-transfected cells resulted in the restoration of cell proliferation and gamma interferon (IFN-gamma) production by a Leishmania-specific T-cell line. These results showed that for the activation of parasite-specific canine T cells producing IFN-gamma, which are most likely involved in protective immunity, sufficient expression of B7 molecules on infected macrophages is required. Provision of costimulatory molecules may be an approach for immunotherapy of leishmaniaisis as well as for vaccine development.     

Disaster-survivable cloud-network mapping

Cloud-computing services are provided to consumers through a network of servers and network equipment. Cloud-network (CN) providers virtualize resources [e.g., virtual machine (VM) and virtual network (VN)] for efficient and secure resource allocation. Disasters are one of the worst threats for CNs as they can cause massive disruptions and CN disconnection. A disaster may also induce post-disaster correlated, cascading failures which can disconnect more CNs. Survivable virtual-network embedding (SVNE) approaches have been studied to protect VNs against single physical-link/-node and dual physical-link failures in communication infrastructure, but massive disruptions due to a disaster and their consequences can make SVNE approaches insufficient to guarantee cloud-computing survivability. In this work, we study the problem of survivable CN mapping from disaster. We consider risk assessment, VM backup location, and post-disaster survivability to reduce the risk of failure and probability of CN disconnection and the penalty paid by operators due to loss of capacity. We formulate the proposed approach as an integer linear program and study two scenarios: a natural disaster, e.g., earthquake and a human-made disaster, e.g., weapons-of-mass-destruction attack. Our illustrative examples show that our approach reduces the risk of CN disconnection and penalty up to 90 % compared with a baseline CN mapping approach and increases the CN survivability up to 100 % in both scenarios.     

Provisioning of dynamic traffic in mixed-line-rate optical networks with launch power determination

In mixed-line-rate (MLR) networks, different line rates on different wavelengths can coexist on the same fiber. MLR architectures can be built over transparent optical networks, where the transmitted signals remain in the optical domain along the entire path. Along the transparent optical path, a signal experiences various physical layer impairments (PLIs), and its quality degrades as it travels through each optical component. One of the major factors that affect the transmission quality is the launch power of the optical signal. The power must be large enough to ensure noise resiliency at the receiver, but it must be below the limit where fiber nonlinearities distort the signal. Moreover, high launch power is disruptive not only for the actual lightpath itself but also for neighboring lightpaths, and this effect is particularly critical in MLR networks since advanced modulation techniques used for high line rates are highly susceptible to PLIs. In this study, we investigate the problem of determining the appropriate launch power for provisioning of dynamic connection requests in MLR networks. By setting the appropriate launch power for each connection, we aim to maximize the number of established connections. We propose two different heuristics to determine the appropriate launch power of a lightpath. Worst-case best-case average (WBA) is based on optical reach of signal in a transparent optical network. In impairment-aware launch power determination (I-ALPD), current state of the network and impairments are evaluated to determine the launch power. The proposed approaches are practical and can adapt to the needs of network operators. Simulation results show that the performances of the proposed approaches show better results than the existing schemes in terms of blocking probability and bandwidth blocking ratio.     

Disaster-aware service provisioning with manycasting in cloud networks

Cloud services delivered by high-capacity optical datacenter networks are subject to disasters which may cause large-area failures, leading to huge data loss. Survivable service provisioning is crucial to minimize the effects of network/datacenter failures and maintain critical services in case of a disaster. We propose a novel disaster-aware service-provisioning scheme that multiplexes service over multiple paths destined to multiple servers/datacenters with manycasting. Our scheme maintains some bandwidth (i.e., degraded service) after a disaster failure vs. no service at all. We formulate this problem into a mathematical model which turns out to be an Integer Linear Program (ILP), and we provide heuristic optimization approaches as ILP is intractable for large problem instances. Numerical examples show that exploiting manycasting by intelligently selecting destinations in a risk-aware manner for service provisioning offers high level of survivability against link and node failures that may be caused by disasters and post-disaster failures at no extra cost compared to the other survivable schemes.     

A rapid spectroscopic method to detect the fraudulent treatment of tuna fish with carbon monoxide

Carbon monoxide (CO) can be used to treat fresh meat and fish in order to retain its ‘fresh’ red colour appearance for a longer period of time. In fact, upon aging, myoglobin is oxidized to met-myoglobin with the concomitant blue-shift and broadening of the Soret maximum, which brings about a change in the colour of the fish, revealing that it is no longer fresh. The use of carbon monoxide, which reacts with the oxy-myoglobin to form a fairly stable cherry red carboxy-myoglobin complex may mask spoilage, because the CO-complex can be stable beyond the microbiological shelf life of the meat. The presence of CO in tuna fish has been investigated by optical spectroscopy as the formation of the CO adduct can be easily detected by the combined analysis of electronic absorption spectra in their normal and second derivative modes, monitoring the intense Soret band at 420 nm. The presence of met- and oxy-myoglobin can obscure the presence of small amounts of the CO adduct; however, it can be revealed by chemically reducing the met- and oxy-forms to the deoxy-form in an anaerobic environment. This spectroscopic method provides a qualitatively rapid laboratory screening procedure for food control to unmask the presence of CO in frozen or fresh fish.