Gene therapy of inherited skin adhesion disorders: a critical overview

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A framework for allocating server time to spot and on-demand services in cloud computing

Cloud computing delivers value to users by facilitating their access to computing capacity in periods when their need arises. An approach is to provide both on-demand and spot services on shared servers. The former allows users to access servers on demand at a fixed price and users occupy different periods of servers. The latter allows users to bid for the remaining unoccupied periods via dynamic pricing; however, without appropriate design, such periods may be arbitrarily small since on-demand users arrive randomly. This is also the current service model adopted by Amazon Elastic Cloud Compute. In this paper, we provide the first integral framework for sharing the time of servers between on-demand and spot services while optimally pricing spot instances. It guarantees that on-demand users can get served quickly while spot users can stably utilize servers for a properly long period once accepted, which is a key feature to make both on-demand and spot services accessible. Simulation results show that, by complementing the on-demand market with a spot market, a cloud provider can improve revenue by up to 464.7%. The framework is designed under assumptions which are met in real environments. It is a new tool that cloud operators can use to quantify the advantage of a hybrid spot and on-demand service, eventually making the case for operating such service model in their own infrastructures

Acid gas removal from natural gas by water washing

Projections in the future energy scenario outline an important role played by fossil fuels to meet the increasing global energy demand. A “golden age” has been recently outlined for natural gas, in particular, as the fastest growing and the cleanest of all fossil fuels. Although natural gas is mostly considered to be a “clean” fuel with respect to the emission of pollutants from its combustion, the raw natural gas found in reservoir deposits is not free of contaminants. Among the others, hydrogen sulphide and carbon dioxide are two undesired compounds, which are responsible for the sour or acidic nature of natural gas and must be removed for operational and safety reasons. Acid gas treating is typically performed in facilities built at surface locations, mainly by means of chemical absorption into aqueous amine solutions. However, subsurface technologies may allow to possibly separate the gas undesired compounds directly downhole. The high pressure encountered in this environment makes the use of water as liquid absorbent worth considering. This work investigates the possibility of acid gas removal from natural gas by downhole water washing and presents a preliminary evaluation of the performances of the process, which is assumed to be carried out in the gas production casing that can be represented as a bubble column. A previously proposed correlation for the gas holdup in this type of contacting device operated counter-currently has been used to determine the volumetric mass transfer coefficient for design purposes, considering different raw gas flow rates and inlet acid gas concentrations. By solving a simplified model of a bubble column and by using water flow rates compatible with reinjection into the reservoir, it has been found that it is possible to reduce the H2S content from the inlet concentration to the commonly accepted value to meet pipeline specifications and, depending on the inlet CO2 concentration, to perform a bulk removal of it

Internet of things: Vision, applications and research challenges

The term “Internet-of-Things” is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internet-of-Things

Delocalized-localized transition in a semiconductor two-dimensional honeycomb lattice

We report the magneto-transport properties of a two-dimensional electron gas in a modulation-doped AlGaAs/GaAs heterostructure subjected to a lateral potential with honeycomb geometry. Periodic oscillations of the magneto-resistance and a delocalized-localized transition are shown by applying a gate voltage. We argue that electrons in such artificial-graphene lattices offer a promising approach for the simulation of quantum phases dictated by Coulomb interactions

Bone marrow transplantation as therapy for ataxia-telangiectasia: a systematic review

Ataxia-Telangiectasia (A-T) is a rare autosomal recessive disorder, first reported in 1926, caused by a deficiency of ATM (Ataxia-Telangiectasia Mutated) protein. The disease is characterized by progressive cerebellar neurodegeneration, immunodeficiency, leukemia, and lymphoma cancer predisposition. Immunoglobulin replacement, antioxidants, neuroprotective factors, growth, and anti-inflammatory hormones are commonly used for A-T treatment, but, to date, there is no known cure. Bone marrow transplantation (BMT) is a successful therapy for several forms of diseases and it is a valid approach for tumors, hemoglobinopathies, autoimmune diseases, inherited disorders of metabolism, and other pathologies. Some case reports of A-T patients have shown that BMT is becoming a good option, as a correct engraftment of healthy cells can restore some aspects of immunologic capacity. However, due to a high risk of mortality as a result of a clinical and cellular hypersensitivity to ionizing radiation and radiomimetic drugs, a specific non-myeloablative conditioning is required before BMT. Although BMT might be considered as one promising therapy for the treatment of immunological defects and cancer prevention in selected A-T patients, the therapy is currently not recommended or recognized and the eligibility of A-T patients for BMT is a point to deepen and deliberate

Ophthalmic manifestations of cat scratch disease

Cat scratch disease (CSD) is a worldwide distributed zoonosis caused by Bartonella henselae and other Bartonella spp. The reservoirs of Bartonella are domestic animals, especially cats, and the transmission to humans is thought to occur from a cat scratch or even through the cat flea Ctenocephalides felix. With more and more pet owners, the physicians should keep in mind signs and symptoms of CSD. A widespread infection may occur in 5-14% of cases, and ocular involvement, called ocular bartonellosis, is a quite common consequence of disseminated CSD. Although the most typical manifestations of ocular Bartonellosis are Parinaud's oculoglandular syndrome, neuroretinitis and retinochoroiditis, many other ophthalmic conditions have been reported. The diagnosis of CSD is often based on history of contact with a cat and high serum titers of immunoglobulin G antibodies against B. henselae. Polymerase chain reaction could be helpful for CSD diagnosis when serology is negative but clinical findings are suggestive for the disease. Multimodal imaging, including fundus autofluorescence, fluorescein and indocyanine green angiography, optical coherence tomography (OCT) and OCT angiography, can be used for diagnosis and monitoring of ocular Bartonellosis. Since CSD is more often a self-limited infection in immunocompetent individuals, no antibiotic treatment is usually needed. However, when a therapy is prescribed, doxycycline is the most used antibiotic. The aim of this article is to review the current literature relating to epidemiology, systemic and ocular manifestations, diagnosis, treatment and prognosis of bartonellosis, in order to give the ophthalmologists a useful tool for daily practice

Unusual sub-genus associations of fecal Prevotella and Bacteroides with specific dietary patterns

Background: Diet has a recognized effect in shaping gut microbiota. Many studies link an increase in Prevotella to high-fibre diet, while Bacteroides abundance is usually associated with the consumption of animal fat and protein-rich diets. Nevertheless, closely related species and strains may harbour different genetic pools; therefore, further studies should aim to understand whether species of the same genus are consistently linked to dietary patterns or equally responsive to diet variations. Here, we used oligotyping of 16S rRNA gene sequencing data to exploit the diversity within Prevotella and Bacteroides genera in faecal samples of omnivore and non-omnivore subjects from a previously studied cohort. Results: A great heterogeneity was found in oligotype composition. Nevertheless, different oligotypes within the same genus showed distinctive correlation patterns with dietary components and metabolome. We found that some Prevotella oligotypes are significantly associated with the plant-based diet but some are associated with animal-based nutrients, and the same applies to Bacteroides. Therefore, an indiscriminate association of Bacteroidetes genera with specific dietary patterns may lead to an oversimplified vision that does not take into account sub-genus diversity and the different possible responses to dietary components. Conclusions: We demonstrated that Prevotella and Bacteroides oligotypes show distinctive correlation patterns with dietary components and metabolome. These results substantiate a current oversimplification of diet-dependent microbe-host associations and highlighted that sub-genus differences must be taken into account when planning gut microbiota modulation for health benefits

Decentralized Self-adaptation in Large-scale Distributed Systems

The evolution of technology is leading to a world where computational systems are made of a huge number of components spread over a logical network: these components operate in a highly dynamic and unpredictable environment, joining or leaving the system and creating connections between them at runtime. This scenario poses new challenges to software engineers that have to design and implement such complex systems. We want to address this problem, designing and developing an infrastructure, GRU, that uses self-adaptive decentralized techniques to manage large-scale distributed systems. GRU will help developers to focus on the functional part of their application instead of the needed self-adaptive infrastructure. We aim to evaluate our project with concrete case studies, providing evidence on the validity of our approach, and with the feedback provided by developers that will test our system. We believe this approach can contribute to fill the gap between the theoretical study of self-adaptive systems and their application in a production context

A security-and quality-aware system architecture for Internet of Things

Internet of Things (IoT) is characterized, at the system level, by high diversity with respect to enabling technologies and supported services. IoT also assumes to deal with a huge amount of heterogeneous data generated by devices, transmitted by the underpinning infrastructure and processed to support value-added services. In order to provide users with valuable output, the IoT architecture should guarantee the suitability and trustworthiness of the processed data. This is a major requirement of such systems in order to guarantee robustness and reliability at the service level. In this paper, we introduce a novel IoT architecture able to support security, privacy and data quality guarantees, thereby effectively boosting the diffusion of IoT services