A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018–June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0–100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription.

The protein interaction network of the inherited central nervous system diseases reveals new gene candidates for molecularly unclassified myelin disorders

Mutations in numerous genes cause the inherited disorders of the white matter in the central nervous system. Interestingly, all these mutations ultimately affect myelin, even though the corresponding proteins are involved in dissimilar functions. To address this system-level issue, we assembled the myelin disease network (MDN), in which each node represents a protein (either the mutated protein or one of its interactors), while each edge linking two nodes represents the physical interaction between the two proteins. Compared with control random networks, the MDN contains more pairs of disease proteins, whose members are linked either directly or via one intermediate protein. Then, we surmised that the interactions might not only cluster proteins into functionally homogenous and distinct modules but also link the modules together. This way, even gene mutations arising in functionally distinct modules might propagate their effects to the other modules, thus accounting for a similar pathological outcome. We found, however, that concerning the function the modules are neither homogeneous nor distinct, mostly because many proteins participate in more than one biological process. Rather, our analysis defines a region of the interactome, where different processes intersect. Finally, we propose that many non-disease proteins in the network might be candidates for molecularly unclassified myelin disorders.

An Improved ant based Algorithm and its Implementation for the Broken Edge Linking Problem

As a robust image processing technique, the broken edge linking technique is considered to be the complementary one to the edge detection technique. Here in case of the edge linking problem, we form closed contours by linking the broken edges. This action indeed needed to split the areas in the image into different parts known as segment. However the traditional edge linking technique is always succeeded by the traditional edge detection technique. The traditional edge linking technique, for all time, neglects some significant part of the boundaries to consider, as a result, appropriate and perfect solutions to the edge related linking problem cannot be reached always. With this article, we presented an improved method (technique) for the edge related linking difficulty (problem), which is actually the expansion of the original old Ant System (AS) algorithm. Here in the experiment, we mainly consider the two decisive and significant factors: first one is the length of the linking edge as well as second one is the grayscale visibility of the pixels, apart from an sobel edge binary image , so that the effective solution evaluation and enhancement of the overall performance can be achieved. The experiment showed the expected result, are presented herewith this to ensure the successfulness of the projected improved technique /algorithm.

The average weighted receiving time with weight-dependent walk on a family of double-weighted polymer networks

In this paper, a family of the double-weighted polymer networks is introduced depending on the number of copies [Formula: see text] and two weight factors [Formula: see text]. The double-weights represent the selected weights and the consumed weights, respectively. Denote by [Formula: see text] the selected weight connecting the nodes [Formula: see text] and [Formula: see text], and denote by [Formula: see text] the consumed weight connecting the nodes [Formula: see text] and [Formula: see text]. Let [Formula: see text] be related to the weight factor [Formula: see text], and let [Formula: see text] be related to the weight factors [Formula: see text]. Assuming that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the selected weight of edge linking them. The weighted time for two adjacency nodes is the consumed weight connecting the two nodes. The average weighted receiving time (AWRT) is defined on the double-weighted polymer networks. Our results show that in large network, the leading behaviors of AWRT for the double-weighted polymer networks follow distinct scalings, with the trapping efficiency associated with the network size [Formula: see text], the number of copies [Formula: see text], and two weight factors [Formula: see text]. We also found that the scalings of the AWRT with weight-dependent walk in double-weighted polymer networks is due to the use of the weight-dependent walk and the weighted time. The dominant reason is the range of each weight factor. To investigate the reason of the scalings, the AWRT for four cases are discussed.

AUTOMATED DETECTION OF LUNAR RIDGES BASED ON DEM DATA

<p><strong>Abstract.</strong> Wrinkle ridges are a common feature in the lunar maria and record subsequent contraction of mare infill. Automatic detection of wrinkle ridges is challenging because the ridges are of irregular shapes and many ridges have been eroded and/or degraded over time. The proposed method consists of the following steps. First, as the slope can reflect the gradient changes of the ridge rims to a certain extent, the slope map is generated and converted to a grayscale (0&amp;ndash;255) image. Then the phase symmetry of the slope map is calculated with filter wavelength and filter scales parameters, which reduce the regions into symmetry regions. Next, a regional threshold is applied to limit the ridge candidates. Candidates with values less than the threshold are rejected. Moreover, the images are processed using a series of morphological operations, such as close, open, edge linking and noise removal. Finally, after thresholding the ridge map can be obtained. An experiment was performed using Lunar Reconnaissance Orbiter Camera (LROC) WAC image and topographic data from LOLA, the results demonstrate promising performance with detection percentage from 73 to 90.</p>

On the C/edge linking mechanism. Evidence from Polish

The main aim of the paper is to examine Polish data from the perspective of Sigurðsson’s (2011, 2014) theory of C/edge linking. The crucial point of the theory lies in the hypothesis that phases are equipped with silent edge features which enable narrow syntax to link to context. All definite arguments, overt as well as null arguments, must be successfully C/edge linked, e.g. they have to match at least one feature in the broad C-domain. The present study focuses on utterances in Polish with direct object expressed as pronoun or null.The account proves successful in explaining some distributional patterns of null vs. pronoun objects in Polish. The Polish data investigated in this study indicates that the theory of silent edge linkers providing a communication channel for syntax and context is a step towards understanding the relation between syntax and pragmatics better.

SCALING OF THE AVERAGE RECEIVING TIME ON A FAMILY OF WEIGHTED HIERARCHICAL NETWORKS

In this paper, based on the un-weight hierarchical networks, a family of weighted hierarchical networks are introduced, the weight factor is denoted by [Formula: see text]. The weighted hierarchical networks depend on the number of nodes in complete bipartite graph, denoted by [Formula: see text], [Formula: see text] and [Formula: see text]. Assume that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the weight of edge linking them. We deduce the analytical expression of the average receiving time (ART). The obtained remarkable results display two conditions. In the large network, when [Formula: see text], the ART grows as a power-law function of the network size [Formula: see text] with the exponent, represented by [Formula: see text], [Formula: see text]. This means that the smaller the value of [Formula: see text], the more efficient the process of receiving information. When [Formula: see text], the ART grows with increasing order [Formula: see text] as [Formula: see text] or [Formula: see text].