Tight Bounds for Maximal Identifiability of Failure Nodes in Boolean Network Tomography

We study maximal identifiability, a measure recently introduced in Boolean Network Tomography to characterize networks' capability to localize failure nodes in end-to-end path measurements. We prove tight upper and lower bounds on the maximal identifiability of failure nodes for specific classes of network topologies, such as trees and $d$-dimensional grids, in both directed and undirected cases. We prove that directed $d$-dimensional grids with support $n$ have maximal identifiability $d$ using $2d(n-1)+2$ monitors; and in the undirected case we show that $2d$ monitors suffice to get identifiability of $d-1$. We then study identifiability under embeddings: we establish relations between maximal identifiability, embeddability and graph dimension when network topologies are model as DAGs. Our results suggest the design of networks over $N$ nodes with maximal identifiability $\Omega(\log N)$ using $O(\log N)$ monitors and a heuristic to boost maximal identifiability on a given network by simulating $d$-dimensional grids. We provide positive evidence of this heuristic through data extracted by exact computation of maximal identifiability on examples of small real networks

Information technology application in medicine and nursing

The computers are the greatest human invention of the twentieth century. Their abilities to store، share and transmission of multimedia data are used in the business، entertainment، health and medicine. Telemedicine technology is one of the abilities that can cause medical information exchange will be at long distances. Telemedicine is using telecommunications and information technology to provide modern clinical services and remote data transfer to take care of patients. Objectives: This study was done aimed to review the remote treatment and care. This study was done using literature related to nursing and telemedicine in Latin and Farsi databases included Proquest، Science direct، Ovid، SID، IranMedex. Telemedicine and telenursing are included transfer of medical and nursing data، such as sound، images، and animated pictures. It is used in areas like management of chronic diseases، prevention of diseases، public health، routine consultation، education of patients and disaster controls. According to the function of this technology and easiness of performance it is expected that its application in medical science to spread quickly. Therefore it is necessary to develop health services in our country and take more attention. This article wants to introduce the fundamentals of telemedicine and telenursing. Obviously knowing the details of their applications need more review and study. Keywords: Telenursing, Telemedicine, Care, Treatmen

The Effect of Bubble making on the Procedural Pain of Injection in Thalasemic School- aged Children in Kerman Thalasemia Center

Introduction: Medical procedures are common sources of pain for children. Children with chronic illnesses experience an even greater number of painful procedures as part of their condition diagnosis, treatment, and monitoring. Several methods are reported for reducing the pain. Clinicians commonly used distraction methods for decreasing pain. However there is no consensus among them about what distraction method is better for reducing injection pain. Objective: This study carried out to assess the Effect of Bubble making on The Procedural Pain of Injection in Thalassemic School- aged Children in Kerman Thalasemia Center Method: The present study is a clinical trial. The research sample consists of 40 thalassemic children with 6-12 years old, who have registered in Kerman thalasemia center. The participants were randomly divided into two groups (control and experimental). In the experimental group, bubble making was performed. The data gathering instruments were included: demographic information questionnaire, the investigation scale of pain behavioral signs, numeric pain scale. The analysis of the data was carried out through descriptive and analytical statistics. Results: The data indicated that there was a significant difference between the average scores of pain in the two groups after injection (P<0.05) Conclusion: Based on the result of this study, the distraction (Bubble Making) can reduce the pain of injection procedures in children. Keywords: Pain, Bubble making, Distraction, School- aged Children, Thalasemi

Comparison between doxycycline–rifampin–amikacin and doxycycline–rifampin regimens in the treatment of brucellosis

SummaryBackgroundCombination drug therapy of brucellosis leads to recovery of symptoms, shortening of symptomatic interval, and decrease in morbidity rate, but single drug therapy is associated with more relapse episodes and a higher rate of drug resistance. Different drug combinations have been evaluated in the treatment of brucellosis. Considering the failure of treatment and relatively high rate of relapse of the disease with the World Health Organization's (WHO) recommended therapeutic regimen, we evaluated a new regimen that we assumed would increase the success of treatment and decrease the rate of relapse. In this study we compare the standard regimen of the WHO, doxycycline–rifampin (DR), to triple therapy with doxycycline–rifampin–amikacin (ADR).MethodsTwo hundred and twenty-eight consecutive patients with brucellosis, who attended Hamedan Sina Hospital between 1999 and 2001, whether seen as outpatients or as inpatients, were enrolled in the study. The participants were randomly allocated to the DR group (receiving doxycycline 100mg twice a day and rifampin 10mg/kg body weight/day every morning, both taken orally for eight weeks) or the ADR group (receiving doxycycline 100mg twice a day and rifampin 10mg/kg body weight/day every morning, both taken orally for eight weeks, plus 7.5mg/kg amikacin intramuscularly twice a day for seven days). The patients were checked for the relief of symptoms, drug side-effects, and relapse of disease during the treatment and follow-up.ResultsOf the 228 patients enrolled, eight were withdrawn – four patients from the DR group and four from the ADR group. Of the remaining 220 participants (110 in the ADR group and 110 in the DR group), 107 were male (48.6%) and 113 were female (51.4%). Mean age was 35.7±17 years in the ADR group and 37±18.4 years in the DR group (p=0.5). In the DR group, 97 (88.2%) and in the ADR group, 106 (96.4%) of the patients had relief of symptoms (a significant difference by Chi-square test (p=0.04)). After completion of treatment, and at the sixth month follow-up, nine (9.3%) patients in the DR group and six (5.7%) in the ADR group experienced a relapse of the disease, with no significant difference (p=0.4). Mild side-effects were found in only 10 patients, and none required discontinuation of the therapeutic regimen. Of these patients, four were from DR group and six from ADR group; no significant difference was observed (p=0.7).ConclusionsGiven the fact that the ADR regimen had a higher efficacy and more rapid action in terms of relief of symptoms compared to the DR regimen, and that no significant difference in drug side-effects and disease relapse existed in the patients of either group, adding amikacin to the DR standard treatment regimen seems beneficial

Bounds on the maximal number of corrupted nodes via Boolean Network Tomography

In this thesis we are concentrating on identifying defective items in larger sets which is a main problem with many applications in real life situations, e.g., fault diagnosis, medical screening and DNA screening. We consider the problem of localizing defective nodes in networks through an approach based on Boolean Network Tomography (BNT), which is grounded on inferring informations from the Boolean outcomes of end-to-end measurement paths. In particular, we focus on the following three: • Studying Maximal Identifiability, which was recently introduced in BNT to measure the maximal number of corrupted nodes which can be uniquely localized in sets of end-to-end measurement paths on networks; • Central role of Vertex-Connectivity in maximal identifiability; • Investigating identifiability conditions on the set of paths which guarantee discovering or counting unambiguously the defective nodes and contributing this problem both from a theoretical and applied perspective. We prove tight upper and lower bounds on the maximal identifiability for sets of end-to-end paths in network topologies obtained from trees and d-(dimensional) grids over n^d nodes. For trees (both directed and undirected) we show that the maximal identifiability is 1. For undirected d-grids we prove that, using only 2d monitors, maximal identifiability is at least d − 1 and at most d. In the directed case proving that the maximal identifiability is d and can be reached at the cost of placing 2d(n − 1) + 2 monitors on the d-grid. This monitor placement is optimal and adding more monitors will not increase the identifiability. We also study maximal identifiability for directed topologies under embeddings establishing new relations with embeddability, graph dimension and proving that under the operation of transitive closure maximal identifiability grows linearly. Our results suggest the design of networks over n nodes reaching maximal identifiability Ω(log n) using O(log n) monitors and an heuristic to boost maximal identifiability increasing the minimal degree of the network which we test experimentally. Moreover we prove tight bounds on the maximal identifiability first in a particular class of graphs, the Line of Sight networks and then slightly weaker bounds for arbitrary networks. Furthermore we initiate the study of maximal identifiability in random networks. We investigate two models: the classical Erdős-Rényi model, and that of Random Regular graphs. The proposed framework allows a probabilistic analysis of the identifiability in random networks giving a tradeoff between the number of monitors to place and the maximal identifiability. Further in this thesis, we work on the precise tradeoff between number of nodes and number of paths such that at most k nodes can be identified unambiguously. The answer to this problem is known only for k = 1 and we answer it for any k, setting a problem implicitly left open in previous works. We focus on upper and lower bounds on the number of unambiguously identifiable nodes, introducing new identifiability measures (Separability and Distinguishability) which strictly imply and are strictly implied by the notion of identifiability introduced in [39]. We utilize these new measures to design algorithmic heuristics to count failure nodes in a fine-grained way and further to prove the first complexity hardness results on the problem of identifying failure nodes in networks via BNT. At last but not least, we introduce a random model so as to achieve lower bounds on the number of unambiguously identifiable defective nodes. We use this model to approximate that number on real networks by a maximum likelihood estimate approach