Information Technology Development Needs in Community Pharmacies : A Strategic Approach

In the context of health care, information technology (IT) has an important role in the operational infrastructure, ranging from business management to patient care. An essential part of the system is medication management in inpatient and outpatient care. Community pharmacists strategy has been to extend practice responsibilities beyond dispensing towards patient care services. Few studies have evaluated the strategic development of IT systems to support this vision. The objectives of this study were to assess and compare independent Finnish community pharmacy owners and staff pharmacists priorities concerning the content and structure of the next generation of community pharmacy IT systems, to explore international experts visions and strategic views on IT development needs in relation to services provided in community pharmacies, to identify IT innovations facilitating patient care services and to evaluate their development and implementation processes, and to assess community pharmacists readiness to adopt innovations. This study applied both qualitative and quantitative methods. A qualitative personal interview of 14 experts in community pharmacy services and related IT from eight countries and a national survey of Finnish community pharmacy owners (mail survey, response rate 53%, n=308), and of a representative sample of staff pharmacists (online survey, response rate 22%, n=373) were conducted. Finnish independent community pharmacy owners gave priority to logistical functions but also to those related to medication information and patient care. The managers and staff pharmacists have different views of the importance of IT features, reflecting their different professional duties in the community pharmacy. This indicates the need for involving different occupation groups in planning the new IT systems for community pharmacies. A majority of the international experts shared the vision of community pharmacy adopting a patient care orientation; supported by IT-based documentation, new technological solutions, access to information, and shared patient data. Community pharmacy IT innovations were rare, which is paradoxical because owners and staff pharmacists perception of their innovativeness was seen as being high. Community pharmacy IT systems development processes usually had not undergone systematic needs assessment research beforehand or evaluation after the implementation and were most often coordinated by national governments without subsequent commercialization. Specifically, community pharmacy IT developments lack research, organization, leadership and user involvement in the process. Those responsible for IT development in the community pharmacy sector should create long-term IT development strategies that are in line with community pharmacy service development strategies. This could provide systematic guidance for future projects to ensure that potential innovations are based on a sufficient understanding of pharmacy practice problems that they are intended to solve, and to encourage strong leadership in research, development of innovations so that community pharmacists potential innovativeness is used, and that professional needs and strategic priorities will be considered even if the development process is led by those outside the profession.

Proportioning of fly-ash cement concrete mixes

The accumulation of fly ash throughout the world is several million tons per day. The main problem with the usage of fly ash is the slow rate of strength gain, primarily due to slow pozzolanic reactions. Existing methods of proportioning fly ash concrete are lacking. These methods are involved and do not directly take into account the properties of the constituent materials. The Generalized Approach for Mix Proportioning developed at the Indian Institute of Science, Bangalore, is the basis for the development of the proposed method, which takes into account the characteristics of cement, fly ash, and aggregates. Based on the basic trial mix data obtained by using the American Concrete Institute (ACI 211.1-81) method, the proportions of fly-ash concrete mixes were arrived at using the Generalized Approach for Mix Proportioning. The method proposed was applied to and found applicable for fly-ash concretes using fly ashes from two different sources.

On the problem of spurious patterns in neural associative memory models

The problem of spurious patterns in neural associative memory models is discussed, Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out, A solution based on the notion of neural self-interaction with a suitably chosen magnitude is presented for the Hebb learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns, With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.

Optimal allocation of carbon credits to emitting agents in a carbon economy

Reduction of carbon emissions is of paramount importance in the context of global warming. Countries and global companies are now engaged in understanding systematic ways of achieving well defined emission targets. In fact, carbon credits have become significant and strategic instruments of finance for countries and global companies. In this paper, we formulate and suggest a solution to the carbon allocation problem, which involves determining a cost minimizing allocation of carbon credits among different emitting agents. We address this challenge in the context of a global company which is faced with the challenge of determining an allocation of carbon credit caps among its divisions in a cost effective way. The problem is formulated as a reverse auction problem where the company plays the role of a buyer or carbon planning authority and the different divisions within the company are the emitting agents that specify cost curves for carbon credit reductions. Two natural variants of the problem: (a) with unlimited budget and (b) with limited budget are considered. Suitable assumptions are made on the cost curves and in each of the two cases we show that the resulting problem formulation is a knapsack problem that can be solved optimally using a greedy heuristic. The solution of the allocation problem provides critical decision support to global companies engaged seriously in green programs.

Hardware implementation of 4x4 DCT/Quantization block using multiplication and error-free algorithm

The 4ÃÂ4 discrete cosine transform is one of the most important building blocks for the emerging video coding standard, viz. H.264. The conventional implementation does some approximation to the transform matrix elements to facilitate integer arithmetic, for which hardware is suitably prepared. Though the transform coding does not involve any multiplications, quantization process requires sixteen 16-bit multiplications. The algorithm used here eliminates the process of approximation in transform coding and multiplication in the quantization process, by usage of algebraic integer coding. We propose an area-efficient implementation of the transform and quantization blocks based on the algebraic integer coding. The designs were synthesized with 90 nm TSMC CMOS technology and were also implemented on a Xilinx FPGA. The gate counts and throughput achievable in this case are 7000 and 125 Msamples/sec.

On the Production of Anorexic Plan Diagrams

A "plan diagram" is a pictorial enumeration of the execution plan choices of a database query optimizer over the relational selectivity space. We have shown recently that, for industrial-strength database engines, these diagrams are often remarkably complex and dense, with a large number of plans covering the space. However, they can often be reduced to much simpler pictures, featuring significantly fewer plans, without materially affecting the query processing quality. Plan reduction has useful implications for the design and usage of query optimizers, including quantifying redundancy in the plan search space, enhancing useability of parametric query optimization, identifying error-resistant and least-expected-cost plans, and minimizing the overheads of multi-plan approaches. We investigate here the plan reduction issue from theoretical, statistical and empirical perspectives. Our analysis shows that optimal plan reduction, w.r.t. minimizing the number of plans, is an NP-hard problem in general, and remains so even for a storage-constrained variant. We then present a greedy reduction algorithm with tight and optimal performance guarantees, whose complexity scales linearly with the number of plans in the diagram for a given resolution. Next, we devise fast estimators for locating the best tradeoff between the reduction in plan cardinality and the impact on query processing quality. Finally, extensive experimentation with a suite of multi-dimensional TPCH-based query templates on industrial-strength optimizers demonstrates that complex plan diagrams easily reduce to "anorexic" (small absolute number of plans) levels incurring only marginal increases in the estimated query processing costs.

Online Handwriting Recognition of Tamil Script Using Fractal Geometry

We present a fractal coding method to recognize online handwritten Tamil characters and propose a novel technique to increase the efficiency in terms of time while coding and decoding. This technique exploits the redundancy in data, thereby achieving better compression and usage of lesser memory. It also reduces the encoding time and causes little distortion during reconstruction. Experiments have been conducted to use these fractal codes to classify the online handwritten Tamil characters from the IWFHR 2006 competition dataset. In one approach, we use fractal coding and decoding process. A recognition accuracy of 90% has been achieved by using DTW for distortion evaluation during classification and encoding processes as compared to 78% using nearest neighbor classifier. In other experiments, we use the fractal code, fractal dimensions and features derived from fractal codes as features in separate classifiers. While the fractal code is successful as a feature, the other two features are not able to capture the wide within-class variations.

Endurance of Nafion-composite membranes in PEFCs operating at elevated temperature under low relative-humidity

PEFCs employing Nafion-silica (Nafion-SiO2) and Nafion-mesoporous zirconium phosphate (Nafion-MZP) composite membranes are subjected to accelerated-durability test at 100 degrees C and 15% relative humidity (RH) at open-circuit voltage (OCV) for 50 h and performance compared with the PEFC employing pristine Nafion-1135 membrane. PEFCs with composite membranes sustain the operating voltage better with fluoride-ion-emission rate at least an order of magnitude lower than PEFC with pristine Nafion-1135 membrane. Reduced gas-crossover, fast fuel-cell-reaction kinetics and superior performance of the PEFCs with Nafion-SiO2 and Nafion-MZP composite membranes in relation to the PEFC with pristine Nafion-1135 membrane support the long-term operational usage of the former in PEFCs. An 8-cell PEFC stack employing Nafion-SiO2 composite membrane is also assembled and successfully operated at 60 degrees C without external humidification.

Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins

Abstract: Background: Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question "What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?" Results: A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex. Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors. Conclusions: The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Combining heterogeneous classifiers for relational databases

Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.

On the height of fall of dropping mass in SASW measurements for asphaltic road pavements

A number of spectral analysis of surface waves (SASW) tests were performed on asphaltic road pavements by dropping a metallic 6.5 kg sphere, from a height (H) ranging from 1 to 3 m. Various combinations of source to first receiver distance (S) and receiver spacing (X) were employed. By increasing the height of the fall of the dropping mass, the maximum wavelength (lambda(max)), up to which the shear wave velocity profile can be predicted with the usage of the SASW measurements, was found to increase continuously. The height of fall of the dropping mass also seems to affect the admissible range of the wavelength for given combinations of X and S. Irrespective of different chosen combinations of S, X and H, a unique combined dispersion curve was generated in all the cases for a given pavement site as long as the threshold minimum value of the coherence function is greater than 0.90.

Performance analysis of data and voice connections in a cognitive radio network

We study the performance of cognitive (secondary) users in a cognitive radio network which uses a channel whenever the primary users are not using the channel. The usage of the channel by the primary users is modelled by an ON-OFF renewal process. The cognitive users may be transmitting data using TCP connections and voice traffic. The voice traffic is given priority over the data traffic. We theoretically compute the mean delay of TCP and voice packets and also the mean throughput of the different TCP connections. We compare the theoretical results with simulations.

Ship-Mounted Real-Time Surface Observational System on board Indian Vessels for Validation and Refinement of Model Forcing Fields

A network of ship-mounted real-time Automatic Weather Stations integrated with Indian geosynchronous satellites Indian National Satellites (INSATs)] 3A and 3C, named Indian National Centre for Ocean Information Services Real-Time Automatic Weather Stations (I-RAWS), is established. The purpose of I-RAWS is to measure the surface meteorological-ocean parameters and transmit the data in real time in order to validate and refine the forcing parameters (obtained from different meteorological agencies) of the Indian Ocean Forecasting System (INDOFOS). Preliminary validation and intercomparison of analyzed products obtained from the National Centre for Medium Range Weather Forecasting and the European Centre for Medium-Range Weather Forecasts using the data collected from I-RAWS were carried out. This I-RAWS was mounted on board oceanographic research vessel Sagar Nidhi during a cruise across three oceanic regimes, namely, the tropical Indian Ocean, the extratropical Indian Ocean, and the Southern Ocean. The results obtained from such a validation and intercomparison, and its implications with special reference to the usage of atmospheric model data for forcing ocean model, are discussed in detail. It is noticed that the performance of analysis products from both atmospheric models is similar and good; however, European Centre for Medium-Range Weather Forecasts air temperature over the extratropical Indian Ocean and wind speed in the Southern Ocean are marginally better.

1.5 V battery driven reduced graphene oxide-silver nanostructure coated carbon foam (rGO-Ag-CF) for the purification of drinking water

A porous carbon foam (CF) electrode modified with a reduced graphene oxide-Ag (rGO-Ag) nanocomposite has been fabricated to purify water. It can perform as an antibacterial device by killing pathogenic microbes with the aid of a 1.5 V battery, with very little power consumption. The device is recycled ten times with good performance for long term usage. It is shown that the device may be implemented as a fast water purifier to deactivate the pathogens in drinking water.