Medication -related adverse events in older people with dementia:causes and possible solutions

This submission for a PhD by previously published work is based upon six publications in peer reviewed journals, reflecting a 9-year research programme. My research has shown, in a coherent and original way, the difficulty in treating people with dementia with safe and effective medication whilst providing research-founded guidance to develop mechanisms to optimise medication choice and minimise iatrogenic events. A wide range of methods, including systematic reviews, meta-analysis, randomised controlled trials (RCTs), quantitative research and mixed methods were used to generate the data, which supported the exploration of three themes. The first theme, to understand the incidence and causes of medication errors in dementia services, identified that people with dementia may be more susceptible to medication-related iatrogenic disease partly due to inherent disease-related characteristics. One particular area of concern is the use of anti-psychotics to treat the Behavioural and Psychological Symptoms of Dementia (BPSD). The second and third themes, respectively, investigated a novel pharmacological and health services intervention to limit anti-psychotic usage. The second phase found that whilst the glutamate receptor blocker memantine showed some promise, further research was clearly required. The third phase found that anti-psychotic usage in dementia may be higher than official figures suggest and that medication review linking primary and secondary care can limit such usage. My work has been widely cited, reflecting a substantial contribution to the field, in terms of our understanding of the causes of, and possible solutions to limit, medication-related adverse events in people with dementia. More importantly, this work has already informed clinical practice, patients, carers and policy makers by its demonstrable impact on health policy. In particular my research has identified key lines of enquiry for future work and for the development of my own personal research programme to reduce the risk associated with medication in this vulnerable population.

Operational Rules for a Mixed Operator of the Erdélyi-Kober Type

2000 Mathematics Subject Classification: 26A33 (main), 44A40, 44A35, 33E30, 45J05, 45D05

Quasi-Regular Solutions for 3D Equations of Tricomi and Keldish Types

Цветан Д. Христов, Недю Ив. Попиванов, Манфред Шнайдер - Изучени са някои тримерни гранични задачи за уравнения от смесен тип. За уравнения от типа на Трикоми те са формулирани от М. Протер през 1952, като тримерни аналози на задачите на Дарбу или Коши–Гурса в равнината. Добре известно е, че новите задачи са некоректни. Ние формулираме нова гранична задача за уравнения от типа на Келдиш и даваме понятие за квазиругулярно решение на тази задача и на eдна от задачите на Протер. Намерени са достатъчни условия за единственост на такива решения.

Mixed spatial and nonspatial problems in location based services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

How effective are heuristic solutions for electricity planning in developing countries

Acknowledgement The first author would like to acknowledge the University of Aberdeen and the Henderson Economics Research Fund for funding his PhD studies in the period 2011-2014 which formed the basis for the research presented in this paper. The first author would also like to acknowledge the Macaulay Development Trust which funds his postdoctoral fellowship with The James Hutton Institute, Aberdeen, Scotland. The authors thank two anonymous referees for valuable comments and suggestions on earlier versions of this paper. All usual caveats apply

Sustainable solutions for the construction sector: integration of secondary raw materials in the production cycle of concrete

The construction industry is one of the largest consumers of raw materials and energy and one of the highest contributor to green-houses gases emissions. In order to become more sustainable it needs to reduce the use of both raw materials and energy, thus lim-iting its environmental impact. Developing novel technologies to integrate secondary raw materials (i.e. lightweight recycled aggre-gates and alkali activated “cementless” binders - geopolymers) in the production cycle of concrete is an all-inclusive solution to im-prove both sustainability and cost-efficiency of construction industry. SUS-CON “SUStainable, Innovative and Energy-Efficiency CONcrete, based on the integration of all-waste materials” is an European project (duration 2012-2015), which aim was the inte-gration of secondary raw materials in the production cycle of concrete, thus resulting in innovative, sustainable and cost-effective building solutions. This paper presents the main outcomes related to the successful scaling-up of SUS-CON concrete solutions in traditional production plants. Two European industrial concrete producers have been involved, to design and produce both pre-cast components (blocks and panels) and ready-mixed concrete. Recycled polyurethane foams and mixed plastics were used as aggre-gates, PFA (Pulverized Fuel Ash, a by-product of coal fuelled power plants) and GGBS (Ground Granulated Blast furnace Slag, a by-product of iron and steel industries) as binders. Eventually, the installation of SUS-CON concrete solutions on real buildings has been demonstrated, with the construction of three mock-ups located in Europe (Spain, Turkey and Romania)

Exact solutions to the short sea shipping distribution problem

Short sea shipping has several advantages over other means of transportation, recognized by EU members. The maritime transportation could be dealt like a combination of two well-known problems: the container stowage problem and routing planning problem. The integration of these two well-known problems results in a new problem CSSRP (Container stowage and ship routing problem) that is also an hard combinatorial optimization problem. The aim of this work is to solve the CSSRP using a mixed integer programming model. It is proved that regardless the complexity of this problem, optimal solutions could be achieved in a reduced computational time. For testing the mathematical model some problems based on real data were generated and a sensibility analysis was performed.

Exact solutions for the agricultural and the two-dimensional packing problems

Objectives and study method: The objective of this study is to develop exact algorithms that can be used as management tools for the agricultural production planning and to obtain exact solutions for two of the most well known twodimensional packing problems: the strip packing problem and the bin packing problem. For the agricultural production planning problem we propose a new hierarchical scheme of three stages to improve the current agricultural practices. The objective of the first stage is to delineate rectangular and homogeneous management zones into the farmer’s plots considering the physical and chemical soil properties. This is an important task because the soil properties directly affect the agricultural production planning. The methodology for this stage is based on a new method called “Positions and Covering” that first generates all the possible positions in which the plot can be delineated. Then, we use a mathematical model of linear programming to obtain the optimal physical and chemical management zone delineation of the plot. In the second stage the objective is to determine the optimal crop pattern that maximizes the farmer’s profit taken into account the previous management zones delineation. In this case, the crop pattern is affected by both management zones delineation, physical and chemical. A mixed integer linear programming is used to solve this stage. The objective of the last stage is to determine in real-time the amount of water to irrigate in each crop. This stage takes as input the solution of the crop planning stage, the atmospheric conditions (temperature, radiation, etc.), the humidity level in plots, and the physical management zones of plots, just to name a few. This procedure is made in real-time during each irrigation period. A linear programming is used to solve this problem. A breakthrough happen when we realize that we could propose some adaptations of the P&C methodology to obtain optimal solutions for the two-dimensional packing problem and the strip packing. We empirically show that our methodologies are efficient on instances based on real data for both problems: agricultural and two-dimensional packing problems. Contributions and conclusions: The exact algorithms showed in this study can be used in the making-decision support for agricultural planning and twodimensional packing problems. For the agricultural planning problem, we show that the implementation of the new hierarchical approach can improve the farmer profit between 5.27% until 8.21% through the optimization of the natural resources. An important characteristic of this problem is that the soil properties (physical and chemical) and the real-time factors (climate, humidity level, evapotranspiration, etc.) are incorporated. With respect to the two-dimensional packing problems, one of the main contributions of this study is the fact that we have demonstrate that many of the best solutions founded in literature by others approaches (heuristics approaches) are the optimal solutions. This is very important because some of these solutions were up to now not guarantee to be the optimal solutions.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Climate change adaptation solutions for the green sectors of selected zones in the MENA region

In this paper, we propose climate adaptation solutions for the green sectors in three different zones of MENA: Egypt’s Delta (irrigated), Karak, in the highlands of Jordan (rainfed), and Lebanon’s Orontes basin (mixed: rainfed-irrigated). We analysed land use and crop intensification, and calculated the economic productivity of water – a critical scarce resource in MENA. By integrating the results with evidence from literature on the potential impacts of climate change and socio-economic factors, we could identify vulnerability levels of the three regions and propose adaptation measures relying of the concept of the “food-water-energy nexus.” While the vulnerability levels are found to be high in the Delta (Egypt) and Karak (Jordan), mainly due to water scarcity and poor adaptive capacity, the vulnerability level is moderate in the Orontes zone (Lebanon) due to a diversified agricultural sector and good market development, coupled with moderate water scarcity. Proposed adaptation solutions range from measures to improve technical efficiency, to measures that encourage economically efficient allocation by use of market forces. For both cases, the development of market opportunities is emphasized to make the proposed measures attractive to farmers.

New dimeric supramolecular structure of mixed (phthalocyaninato)(porphyrinato)-europium(III) sandwiches : preparation and spectroscopic characteristics

The mixed double-decker Eu\[Pc(15C5)4](TPP) (1) was obtained by base-catalysed tetramerisation of 4,5-dicyanobenzo-15-crown-5 using the half-sandwich complex Eu(TPP)(acac) (acac = acetylacetonate), generated in situ, as the template. For comparative studies, the mixed triple-decker complexes Eu2\[Pc(15C5)4](TPP)2 (2) and Eu2\[Pc(15C5)4]2(TPP) (3) were also synthesised by the raise-by-one-story method. These mixed ring sandwich complexes were characterised by various spectroscopic methods. Up to four one-electron oxidations and two one-electron reductions were revealed by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). As shown by electronic absorption and infrared spectroscopy, supramolecular dimers (SM1 and SM3) were formed from the corresponding double-decker 1 and triple-decker 3 in the presence of potassium ions in MeOH/CHCl3.