An Integrated Assessment of the Impacts of Changing Climate Variability on Agricultural Productivity and Profitability in an Irrigated Mediterranean Catchment

Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ET_N), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ET_N may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.     

Using the Meteorological Information for the Regional Rainfall Frequency Analysis: An Application to Sicily

Regional frequency analysis is a useful tool for accurate estimation of precipitation quantiles than at-site frequency analysis, especially in the case of regions with a short rainfall time series. The use of meteorological information, combined with rainfall data analysis, could improve the selection of homogeneous regions. Starting from 1958, 198 meteorological configurations, related to extreme events, have been identified throughout the national territory of Italy. The reanalyzed meteorological data of the 40 Year Re-analysis Archive (ERA-40) of the European Centre for Medium-Range Weather Forecast (ECMWF) have been analyzed to identify homogeneous regions with respect to the Convective Available Potential Energy (CAPE), the Q vector Divergence (QD) and the Vertically Integrated Moisture Flux (VIMF). The latter index appears to be the better candidate for finding regional homogeneity inside areas where high frequency values of CAPE or QD are present. The paper presents an application based on the delimitation of homogeneous regions using climatic indexes for the island of Sicily. By applying the proposed methodology, seven homogeneous areas over Sicily were found. The consistency of the final results has been validated by using a coupled approach based on the Valuation of Floods in Italy procedure (VAPI) and on the heterogeneity test of Hosking and Wallis (Water Resour Res 29:271–281, 1993, 1997).     

Minimize the Maximum Duty in Multi-interface Networks

We consider devices equipped with multiple wired or wireless interfaces. By switching of various interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost. In this paper, we consider two basic networking problems in the field of multi-interface networks. The first one, known as the Coverage problem, requires to establish the connections defined by a network. The second one, known as Connectivity problem, requires to guarantee a connecting path between any pair of nodes of a network. Both are subject to the constraint of keeping as low as possible the maximum cost set of active interfaces at each single node. We study the problems of minimizing the maximum cost set of active interfaces among the nodes of the network in order to cover all the edges in the first case, or to ensure connectivity in the second case. We prove that the Coverage problem is NP-hard for any fixed Δ≥5 and k≥16, with Δ being the maximum degree, and k being the number of different interfaces among the network. We also show that, unless P=NP, the problem cannot be approximated within a factor of ηln?Δ, for a certain constant η. We then provide a general approximation algorithm which guarantees a factor of O((1+b)ln?Δ), with b being a parameter depending on the topology of the input graph. Interestingly, b can be bounded by a constant for many graph classes. Other approximation and exact algorithms for special cases are presented. Concerning the Connectivity problem, we prove that it is NP-hard for any fixed Δ≥3 and k≥10. Also for this problem, the inapproximability result holds, that is, unless P=NP, the problem cannot be approximated within a factor of ηln?Δ, for a certain constant η. We then provide approximation and exact algorithms for the general problem and for special cases, respectively.     

Robust model predictive control with guaranteed setpoint tracking

In this paper a novel robust model predictive control (RMPC) algorithm is proposed, which is guaranteed to stabilize any linear time-varying system in a given convex uncertainty region while respecting state and input constraints. Moreover, unlike most existing RMPC algorithms, the proposed algorithm is guaranteed to remove steady-state offset in the controlled variables for setpoints (possibly) different from the origin when the system is unknown linear time-invariant. The controller uses a dual-mode paradigm (linear control law plus free control moves to reach an appropriate invariant region), and the key step is the design of a robust linear state feedback controller with integral action and the construction of an appropriate polyhedral invariant region in which this controller is guaranteed to satisfy the process constraints. The proposed algorithm is efficient since the on-line implementation only requires one to solve a convex quadratic program with a number of decision variables that scale linearly with the control horizon. The main features of the new control algorithm are illustrated through an example of the temperature control of an open-loop unstable continuous stirred tank reactor.     

A taxonomy of novice user perception of error on the Web

Novice users face many challenges when browsing the Web. The goal of this experiment was to learn about how users perceive error situations when using the World Wide Web. Specifically, the goal was to learn which circumstances cause users to believe that an error has occurred. An exploratory experiment took place with 78 subjects who were novice users. In the experiment the subjects were asked to identify when they perceived that an error had occurred. The subjects reported a total of 219 error situations. These error situations were then classified by the researchers into the following four categories: user error, system error, situational error, and poor Web design. Based on the collected data, suggestions are presented for improving the usability of Web browsers and Web sites.     

NKG2C+ NK Cells for Immunotherapy of Glioblastoma Multiforme

In glioblastoma, non-classical human leucocyte antigen E (HLA-E) and HLA-G are frequently overexpressed. HLA-E loaded with peptides derived from HLA class I and from HLA-G contributes to inhibition of natural killer (NK) cells with expression of the inhibitory receptor CD94/NKG2A. We investigated whether NK cells expressing the activating CD94/NKG2C receptor counterpart were able to exert anti-glioma effects. NKG2C+ subsets were preferentially expanded by a feeder cell line engineered to express an artificial disulfide-stabilized trimeric HLA-E ligand (HLA-E*spG). NK cells expanded by a feeder cell line, which facilitates outgrowth of conventional NKG2A+, and fresh NK cells, were included for comparison. Expansion via the HLA-E*spG feeder cells selectively increased the fraction of NKG2C+ NK cells, which displayed a higher frequency of KIR2DL2/L3/S2 and CD16 when compared to expanded NKG2A+ NK cells. NKG2C+ NK cells exhibited increased cytotoxicity against K562 and KIR:HLA-matched and -mismatched primary glioblastoma multiforme (GBM) cells when compared to NKG2A+ NK cells and corresponding fresh NK cells. Cytotoxic responses of NKG2C+ NK cells were even more pronounced when utilizing target cells engineered with HLA-E*spG. These findings support the notion that NKG2C+ NK cells have potential therapeutic value for treating gliomas.     

A theory of ultimately periodic languages and automata with an application to time granularity

In this paper, we develop a theory of regular ω-languages that consist of ultimately periodic words only and we provide it with an automaton-based characterization. The resulting class of automata, called ultimately periodic automata (UPA), is a subclass of the class of Büchi automata and inherits some properties of automata over finite words (NFA). Taking advantage of the similarities among UPA, Büchi automata, and NFA, we devise efficient solutions to a number of basic problems for UPA, such as the inclusion, the equivalence, and the size optimization problems. The original motivation for developing a theory of ultimately periodic languages and automata was to represent and to reason about sets of time granularities in knowledge-based and database systems. In the last part of the paper, we show that UPA actually allow one to represent (possibly infinite) sets of granularities, instead of single ones, in a compact and suitable to algorithmic manipulation way. In particular, we describe an application of UPA to a concrete time granularity scenario taken from clinical medicine.     

The State of the Art of Piezo1 Channels in Skeletal Muscle Regeneration

Piezo1 channels are highly mechanically-activated cation channels that can sense and transduce the mechanical stimuli into physiological signals in different tissues including skeletal muscle. In this focused review, we summarize the emerging evidence of Piezo1 channel-mediated effects in the physiology of skeletal muscle, with a particular focus on the role of Piezo1 in controlling myogenic precursor activity and skeletal muscle regeneration and vascularization. The disclosed effects reported by pharmacological activation of Piezo1 channels with the selective agonist Yoda1 indicate a potential impact of Piezo1 channel activity in skeletal muscle regeneration, which is disrupted in various muscular pathological states. All findings reported so far agree with the idea that Piezo1 channels represent a novel, powerful molecular target to develop new therapeutic strategies for preventing or ameliorating skeletal muscle disorders characterized by an impairment of tissue regenerative potential.     

Lipidomic Approaches to Study HDL Metabolism in Patients with Central Obesity Diagnosed with Metabolic Syndrome

The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors characterised by central obesity, atherogenic dyslipidaemia, and changes in the circulating lipidome; the underlying mechanisms that lead to this lipid remodelling have only been partially elucidated. This study used an integrated “omics” approach (untargeted whole serum lipidomics, targeted proteomics, and lipoprotein lipidomics) to study lipoprotein remodelling and HDL composition in subjects with central obesity diagnosed with MetS (vs. controls). Compared with healthy subjects, MetS patients showed higher free fatty acids, diglycerides, phosphatidylcholines, and triglycerides, particularly those enriched in products of de novo lipogenesis. On the other hand, the “lysophosphatidylcholines to phosphatidylcholines” and “cholesteryl ester to free cholesterol” ratios were reduced, pointing to a lower activity of lecithin cholesterol acyltransferase (LCAT) in MetS; LCAT activity (directly measured and predicted by lipidomic ratios) was positively correlated with high-density lipoprotein cholesterol (HDL-C) and negatively correlated with body mass index (BMI) and insulin resistance. Moreover, many phosphatidylcholines and sphingomyelins were significantly lower in the HDL of MetS patients and strongly correlated with BMI and clinical metabolic parameters. These results suggest that MetS is associated with an impairment of phospholipid metabolism in HDL, partially led by LCAT, and associated with obesity and underlying insulin resistance. This study proposes a candidate strategy to use integrated “omics” approaches to gain mechanistic insights into lipoprotein remodelling, thus deepening the knowledge regarding the molecular basis of the association between MetS and atherosclerosis.