Metabolic attributes, yield and stability of milk in Jersey cows fed diets containing sodium citrate and sodium bicarbonate

The objective of this work was to evaluate the inclusion of sodium citrate and sodium bicarbonate in the diet of lactating Jersey cows, and its effects on the metabolic attributes, productivity and stability of milk. We evaluated urinary pH, levels of glucose and urea in blood, body weight, body condition score, milk yield, milk stability (ethanol test), and milk physicochemical properties of 17 cows fed diets containing sodium citrate (100 g per cow per day), sodium bicarbonate (40 g per cow per day) or no additives. Assessments were made at the 28th and 44th days. Supply of sodium citrate or bicarbonate has no influence on the metabolic attributes, productivity, body weight, and body condition score of the cows, neither on the composition and stability of milk.

Robust Detection of Incumbents in Cognitive Radio Networks Using Groups

Cognitive radio is a wireless technology aimed at improvingthe efficiency use of the radio-electric spectrum, thus facilitating a reductionin the load on the free frequency bands. Cognitive radio networkscan scan the spectrum and adapt their parameters to operate in the unoccupiedbands. To avoid interfering with licensed users operating on a givenchannel, the networks need to be highly sensitive, which is achieved byusing cooperative sensing methods. Current cooperative sensing methodsare not robust enough against occasional or continuous attacks. This articleoutlines a Group Fusion method that takes into account the behavior ofusers over the short and long term. On fusing the data, the method is basedon giving more weight to user groups that are more unanimous in their decisions.Simulations have been performed in a dynamic environment withinterferences. Results prove that when attackers are present (both reiterativeor sporadic), the proposed Group Fusion method has superior sensingcapability than other methods.

Recipients' Anonymity in Multihop Ad-hoc Networks

Multihop ad-hoc networks have a dynamic topology. Retrieving a route towards a remote peer requires the execution of a recipient lookup, which can publicly reveal sensitive information about him. Within this context, we propose an efficient, practical and scalable solution to guaranteethe anonymity of recipients' nodes in ad-hoc networks.

Anonymous Routing Protocol in decentralized networks

Peer-reviewed

Fully Distributed Cooperative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio networks (CRN) sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to force a wrong decision. Providing security to the sensing process is also complex, as it usually involves introducing limitations to the CRN applications. The most common limitation is the need for a static trusted node that is able to authenticate and merge the reports of all CRN nodes. This paper overcomes this limitation by presenting a protocol that is suitable for fully distributed scenarios, where there is no static trusted node.

A Secure and Anonymous Cooperative Sensing Protocol for Cognitive Radio Networks

Spectrum is an essential resource for the provision of mobile services. In order to control and delimit its use, governmental agencies set up regulatory policies. Unfortunately, such policies have led to a deficiency of spectrum as only few frequency bands are left unlicensed, and these are used for the majority of new emerging wireless applications. One promising way to alleviate the spectrum shortage problem is adopting a spectrum sharing paradigm in which frequency bands are used opportunistically. Cognitive radio is the key technology to enable this shift of paradigm.Cognitive radio networks are self-organized systems in which devices cooperate to use those spectrum ranges that are not occupied by licensed users. They carry out spectrum sensing in order to detect vacant channels that can be used for communication. Even though spectrum sensing is an active area of research, an important issue remains unsolved: the secure authentication of sensing reports. Not providing security enables the input of false data in the system thus empowering false results. This paper presents a distributed protocol based on wireless physical layer security, symmetric cryptography and one-way functions that allows determining a final sensing decision from multiple sources in a quick and secure way, as well as it preserves users¿ privacy.

A Secure Cooperative Sensing Protocol for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancyand manage themselves to operate in unused bands without disturbing licensed users. Spectrum sensing is more accurate if jointly performed by several reliable nodes. Even though cooperative sensing is an active area of research, the secureauthentication of local sensing reports remains unsolved, thus empowering false results. This paper presents a distributed protocol based on digital signatures and hash functions, and ananalysis of its security features. The system allows determining a final sensing decision from multiple sources in a quick and secure way.

On an IDS Model for Mobile Ad Hoc Networks

Manet security has a lot of open issues. Due to its character-istics, this kind of network needs preventive and corrective protection. Inthis paper, we focus on corrective protection proposing an anomaly IDSmodel for Manet. The design and development of the IDS are consideredin our 3 main stages: normal behavior construction, anomaly detectionand model update. A parametrical mixture model is used for behav-ior modeling from reference data. The associated Bayesian classi¯cationleads to the detection algorithm. MIB variables are used to provide IDSneeded information. Experiments of DoS and scanner attacks validatingthe model are presented as well.

Developmental and metabolic brain alterations in rats exposed to bisphenol A during gestation and lactation.

In recent years, considerable research has focused on the biological effect of endocrine-disrupting chemicals. Bisphenol A (BPA) has been implicated as an endocrine-disrupting chemical (EDC) due to its ability to mimic the action of endogenous estrogenic hormones. The aim of this study was to assess the effect of perinatal exposure to BPA on cerebral structural development and metabolism after birth. BPA (1mg/l) was administered in the drinking water of pregnant dams from day 6 of gestation until pup weaning. At postnatal day 20, in vivo metabolite concentrations in the rat pup hippocampus were measured using high field proton magnetic resonance spectroscopy. Further, brain was assessed histologically for growth, gross morphology, glial and neuronal development and extent of myelination. Localized proton magnetic resonance spectroscopy ((1)H MRS) showed in the BPA-exposed rat a significant increase in glutamate concentration in the hippocampus as well as in the Glu/Asp ratio. Interestingly these two metabolites are metabolically linked together in the malate-aspartate metabolic shuttle. Quantitative histological analysis revealed that the density of NeuN-positive neurons in the hippocampus was decreased in the BPA-treated offspring when compared to controls. Conversely, the density of GFAP-positive astrocytes in the cingulum was increased in BPA-treated offspring. In conclusion, exposure to low-dose BPA during gestation and lactation leads to significant changes in the Glu/Asp ratio in the hippocampus, which may reflect impaired mitochondrial function and also result in neuronal and glial developmental alterations.

Fructose and metabolic diseases: new findings, new questions.

There has been much concern regarding the role of dietary fructose in the development of metabolic diseases. This concern arises from the continuous increase in fructose (and total added caloric sweeteners consumption) in recent decades, and from the increased use of high-fructose corn syrup (HFCS) as a sweetener. A large body of evidence shows that a high-fructose diet leads to the development of obesity, diabetes, and dyslipidemia in rodents. In humans, fructose has long been known to increase plasma triglyceride concentrations. In addition, when ingested in large amounts as part of a hypercaloric diet, it can cause hepatic insulin resistance, increased total and visceral fat mass, and accumulation of ectopic fat in the liver and skeletal muscle. These early effects may be instrumental in causing, in the long run, the development of the metabolic syndrome. There is however only limited evidence that fructose per se, when consumed in moderate amounts, has deleterious effects. Several effects of a high-fructose diet in humans can be observed with high-fat or high-glucose diets as well, suggesting that an excess caloric intake may be the main factor involved in the development of the metabolic syndrome. The major source of fructose in our diet is with sweetened beverages (and with other products in which caloric sweeteners have been added). The progressive replacement of sucrose by HFCS is however unlikely to be directly involved in the epidemy of metabolic disease, because HFCS appears to have basically the same metabolic effects as sucrose. Consumption of sweetened beverages is however clearly associated with excess calorie intake, and an increased risk of diabetes and cardiovascular diseases through an increase in body weight. This has led to the recommendation to limit the daily intake of sugar calories.

Reconstruction of networks from their betweenness centrality

In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.

Joint physical-MAC layer design of the broadcast channel protocol in adhoc networks

Broadcast transmission mode in ad hoc networks is critical to manage multihop routing or providing medium accesscontrol (MAC)-layer fairness. In this paper, it is shown that ahigher capacity to exchange information among neighbors may beobtained through a physical-MAC cross-layer design of the broadcastprotocol exploiting signal separation principles. Coherentdetection and separation of contending nodes is possible throughtraining sequences which are selected at random from a reducedset. Guidelines for the design of this set are derived for a lowimpact on the network performance and the receiver complexity.

Sindrome metabolica e rischio di tumore mammario. [Metabolic syndrome and the risk of breast cancer].

Metabolic syndrome has been associated with an increased risk of various cancers. A multicenter study conducted in Italy and Switzerland on 3,869 cases of breast cancer in post-menopause reported a relative risk of 1.75 in women with the metabolic syndrome, confirming the results of other smaller epidemiological studies.

Input diffusion and the evolution of production networks

What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.