Development of management accounting practices in energy operations in a forest industry Company

The aim of this master’s thesis was to map the management accounting processes and reporting of an internal service unit. The research was conducted in energy services in a forest industry company. Research questions and the results of the study are highly specific for the case unit although some generalizable features of management accounting in internal service units under shared services were searched. The research was carried out as a qualitative action research and a single case study. Internal benchmarking was used to find best practices from other units and to get a comprehensive understanding of the financial processes of the case company. Empirical data for the study was collected with participant observation, interviews of experts and by exploring internal company documents. A literature review was conducted to outline the subject and to support the study. Although the management accounting processes of the case unit were found to be on a good level, some improvement ideas were presented. Results of the research show that the needs of the customers are in the key role in the processes of an internal service unit. Management accounting and reporting need to support the company strategy and management decision-making. To evaluate the performance of the service unit both financial and non-financial measures are needed.

Development of procedures for the triazole fungicides determination in fruits and liquid samples using microextraction techniques and chromatographic separation

Agricultural crops can be damaged by funguses, insects, worms and other organisms that cause diseases and decrease the yield of production. The effect of these damaging agents can be reduced using pesticides. Among them, triazole compounds are effective substances against fungus; for example, Oidium. Nevertheless, it has been detected that the residues of these fungicides in foods as well as in derivate products can affect the health of the consumers. Therefore, the European Union has established several regulations fixing the maximum residue of pesticide levels in a wide range of foods trying to assure the consumer safety. Hence, it is very important to develop adequate methods to determine these pesticide compounds. In most cases, gas or liquid chromatographic (GC, LC) separations are used in the analysis of the samples. But firstly, it is necessary to use proper sample treatments in order to preconcentrate and isolate the target analytes. To reach this aim, microextraction techniques are very effective tools; because allow to do both preconcentration and extraction of the analytes in one simple step that considerably reduces the source of errors. With these objectives, two remarkable techniques have been widely used during the last years: solid phase microextraction (SPME) and liquid phase microextraction (LPME) with its different options. Both techniques that avoid the use or reduce the amount of toxic solvents are convenient coupled to chromatographic equipments providing good quantitative results in a wide number of matrices and compounds. In this work simple and reliable methods have been developed using SPME and ultrasound assisted emulsification microextraction (USAEME) coupled to GC or LC for triazole fungicides determination. The proposed methods allow confidently determine triazole concentrations of μg L‐1 order in different fruit samples. Chemometric tools have been used to accomplish successful determinations. Firstly, in the selection and optimization of the variables involved in the microextraction processes; and secondly, to overcome the problems related to the overlapping peaks. Different fractional factorial designs have been used for the screening of the experimental variables; and central composite designs have been carried out to get the best experimental conditions. Trying to solve the overlapping peak problems multivariate calibration methods have been used. Parallel Factor Analysis 2 (PARAFAC2), Multivariate Curve Resolution (MCR) and Parallel Factor Analysis with Linear Dependencies (PARALIND) have been proposed, the adequate algorithms have been used according to data characteristics, and the results have been compared. Because its occurrence in Basque Country and its relevance in the production of cider and txakoli regional wines the grape and apple samples were selected. These crops are often treated with triazole compounds trying to solve the problems caused by the funguses. The peel and pulp from grape and apple, their juices and some commercial products such as musts, juice and cider have been analysed showing the adequacy of the developed methods for the triazole determination in this kind of fruit samples.

Development of a cargo screening process simulator: a first approach

The efficiency of current cargo screening processes at sea and air ports is largely unknown as few benchmarks exists against which they could be measured. Some manufacturers provide benchmarks for individual sensors but we found no benchmarks that take a holistic view of the overall screening procedures and no benchmarks that take operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. Our aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximise detection rates. In this paper we present our ideas for developing such a system and highlight the research challenges we have identified. Then we introduce our first case study and report on the progress we have made so far.

Development of the Andalusian Registry of Patients Receiving Community Case Management, for the follow-up of people with complex chronic diseases.

Background: Complex chronic diseases are a challenge for the current configuration of Health services. Case management is a service frequently provided for people with chronic conditions and despite its effectiveness in many outcomes, such as mortality or readmissions, uncertainty remains about the most effective form of team organization, structures, and the nature of the interventions. Many processes and outcomes of case management for people with complex chronic conditions cannot be addressed with the information provided by electronic clinical records. Registries are frequently used to deal with this weakness. The aim of this study was to generate a registry-based information system of patients receiving case management to identify their clinical characteristics, their context of care, events identified during their follow-up, interventions developed by case managers, and services used. Methods and design: The study was divided into three phases, covering the detection of information needs, the design and its implementation in the healthcare system, using literature review and expert consensus methods to select variables that would be included in the registry. Objective: To describe the essential characteristics of the provision of ca re lo people who receive case management (structure, process and outcomes), with special emphasis on those with complex chronic diseases. Study population: Patients from any District of Primary Care, who initiate the utilization of case management services, to avoid information bias that may occur when including subjects who have already been received the service, and whose outcomes and characteristics could not be properly collected. Results: A total of 102 variables representing structure, processes and outcomes of case management were selected for their inclusion in the registry after the consensus phase. Total sample was composed of 427 patients, of which 211 (49.4%) were women and 216 (50.6%) were men. The average functional level (Barthel lndex) was 36.18 (SD 29.02), cognitive function (Pfeiffer) showed an average of 4.37 {SD 6.57), Chat1son Comorbidity lndex, obtained a mean of 3.03 (SD 2.7) and Social Support (Duke lndex) was 34.2 % (SD 17.57). More than half of patients include in the Registry, correspond lo immobilized or transitional care for patients discharged from hospital (66.5 %). The patient's educational level was low or very low (50.4%). Caregivers overstrain (Caregiver stress index), obtained an average value of 6.09% (SD 3.53). Only 1.2 % of patients had declared their advanced directives, 58.6 had not defined the tutelage and the vast majority lived at home 98.8 %. Regarding the major events recorded at RANGE Registry, 25.8 % of the selected patients died in the first three months, 8.2 % suffered a hospital admission at least once time, 2.3%, two times, and 1.2% three times, 7.5% suffered a fall, 8.7% had pressure ulcer, 4.7% had problems with medication, and 3.3 % were institutionalized. Stroke is the more prevalent health problem recorded (25.1%), followed by hypertension (11.1%) and COPD (11.1%). Patients registered by NCMs had as main processes diabetes (16.8%) and dementia (11.3 %). The most frequent nursing diagnoses referred to the self-care deficit in various activities of daily living. Regarding to nursing interventions, described by the Nursing Intervention Classification (NIC), dementia management is the most used intervention, followed by mutual goal setting, caregiver and emotional support. Conclusions: The patient profile who receive case management services is a chronic complex patient with severe dependence, cognitive impairment, normal social support, low educational level, health problems such as stroke, hypertension or COPD, diabetes or dementia, and has an informal caregiver. At the first follow up, mortality was 19.2%, and a discrete rate of readmissions and falls.

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

A Transcriptome Atlas of Physcomitrella patens Provides Insights into the Evolution and Development of Land Plants

Post-print version of the article.

Biodeterioration of easel paintings: development of new mitigation strategies

Easel paintings have undergone biodeterioration processes due to microbiological agents proliferation, particularly by development of fungal strains that are associated to biofilms formation and microstructure disintegration of these artworks, due to a wide diversity of available nutrients. Thus, mitigation strategies, using green and non-toxic biocides, which eliminate and prevent the microbiological contamination of these cultural assets are in progress.

Development of Glomerella leaf spot is enhanced in virus-infected Maxi Gala apples.

Apples are commercially grown in Brazil in a subtropical environment that favors the development of fungal diseases such as Glomerella leaf spot (GLS) caused mainly by Glomerella cingulata (anamorph Colletotrichum gloeosporioides). The main objective of this work was to evaluate the effect of mixed infections by Apple stem grooving virus (ASGV) and Apple stem pitting virus (ASPV) on the infection and the colonization processes of C. gloeosporiodes in cv. Maxi Gala plants. Leaves of 16-month-old potted plants were spray-inoculated and both the disease incidence and lesion count were monitored over time and leaf severity was assessed in the final evaluation using an image analysis tool. Results showed that initial infection estimated from a monomolecular model fitted to progress of lesion count was higher and the incubation period (time to reach 50% incidence) was on average 10 h shorter in virus-infected plants compared to non-infected plants. It is hypothesized that initial events such as conidial germination and fungal penetration into plant cells were facilitated by the presence of viral infection. Also, final GLS severity was significantly higher in the virus-infected plants. Mixed infections by ASGV/ASPV seemed to make apple leaves more susceptible to the initial infection and colonization by C. gloeosporioides.

Development of new immunochemical and spectroscopic analytical methods for the characterization and conservation of works of art

Cultural heritage is constituted by complex and heterogenous materials, such as paintings but also ancient remains. However, all ancient materials are exposed to external environment and their interaction produces different changes due to chemical, physical and biological phenomena. The organic fraction, especially the proteinaceous one, has a crucial role in all these materials: in archaeology proteins reveal human habits, in artworks they disclose technics and help for a correct restoration. For these reasons the development of methods that allow the preservation of the sample as much as possible and a deeper knowledge of the deterioration processes is fundamental. The research activities presented in this PhD thesis have been focused on the development of new immunochemical and spectroscopic approaches in order to detect and identify organic substances in artistic and archaeological samples. Organic components could be present in different cultural heritage materials as constituent element (e.g., binders in paintings, collagen in bones) and their knowledge is fundamental for a complete understanding of past life, degradation processes and appropriate restauration approaches. The combination of immunological approach with a chemiluminescence detection and Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry allowed a sensitive and selective localization of collagen and elements in ancient bones and teeth. Near-infrared spectrometer and hyper spectral imaging have been applied in combination with chemometric data analysis as non-destructive methods for bones prescreening for the localization of collagen. Moreover, an investigation of amino acids in enamel has been proposed, in order to clarify teeth biomolecules survival overtime through the optimization and application of High-Performance Liquid Chromatography on modern and ancient enamel powder. New portable biosensors were developed for ovalbumin identification in paintings, thanks to the combination between biocompatible Gellan gel and electro-immunochemical sensors, to extract and identify painting binders with the contact only between gel and painting and between gel and electrodes.

Noises: a Nuisance and a Resource. Development of New Decomposition Methods of Noisy Data

Noise is constant presence in measurements. Its origin is related to the microscopic properties of matter. Since the seminal work of Brown in 1828, the study of stochastic processes has gained an increasing interest with the development of new mathematical and analytical tools. In the last decades, the central role that noise plays in chemical and physiological processes has become recognized. The dual role of noise as nuisance/resource pushes towards the development of new decomposition techniques that divide a signal into its deterministic and stochastic components. In this thesis I show how methods based on Singular Spectrum Analysis have the right properties to fulfil the previously mentioned requirement. During my work I applied SSA to different signals of interest in chemistry: I developed a novel iterative procedure for the denoising of powder X-ray diffractograms; I “denoised” bi-dimensional images from experiments of electrochemiluminescence imaging of micro-beads obtaining new insight on ECL mechanism. I also used Principal Component Analysis to investigate the relationship between brain electrophysiological signals and voice emission.

Development of functional MRI protocols in the study of neurodegenerative diseases: MRI study in patients with REM sleep behavior disorder, idiopathic Parkinson's disease and multisystem atrophy

In the central nervous system, iron in several proteins is involved in many important processes: oxygen transportation, oxidative phosphorylation, mitochondrial respiration, myelin production, the synthesis and metabolism of neurotransmitters. Abnormal iron homoeostasis can induce cellular damage through hydroxyl radical production, which can cause the oxidation, modification of lipids, proteins, carbohydrates, and DNA, lead to neurotoxicity. Moreover increased levels of iron are harmful and iron accumulations are typical hallmarks of brain ageing and several neurodegenerative disorders particularly PD. Numerous studies on post mortem tissue report on an increased amount of total iron in the substantia nigra in patients with PD also supported by large body of in vivo findings from Magnetic Resonance Imaging (MRI) studies. The importance and approaches for in vivo brain iron assessment using multiparametric MRI is increased over last years. Quantitative MRI may provide useful biomarkers for brain integrity assessment in iron-related neurodegeneration. Particularly, a prominent change in iron- sensitive T2* MRI contrast within the sub areas of the SN overlapping with nigrosome 1 were shown to be a hallmark of Parkinson's Disease with high diagnostic accuracy. Moreover, differential diagnosis between Parkinson's Disease (PD) and atypical parkinsonian syndromes (APS) remains challenging, mainly in the early phases of the disease. Advanced brain MR imaging enables to detect the pathological changes of nigral and extranigral structures at the onset of clinical manifestations and during the course of the disease. The Nigrosome-1 (N1) is a substructure of the healthy Substantia Nigra pars compacta enriched by dopaminergic neurons; their loss in Parkinson’s disease and atypical parkinsonian syndromes is related to the iron accumulation. N1 changes are supportive MR biomarkers for diagnosis of these neurodegenerative disorders, but its detection is hard with conventional sequences, also using high field (3T) scanner. Quantitative susceptibility mapping (QSM), an iron-sensitive technique, enables the direct detection of Neurodegeneration

Historic and modern alloys: atmospheric corrosion and development of accelerated ageing methodologies

The atmospheric corrosion of modern and historic alloys used in cultural heritage has been investigated by applying specific accelerated ageing methods. Three main research lines were carried out, involving different materials. In the first part, the atmospheric corrosion of a modern Cu-3Si-1Mn bronze was investigated through accelerated ageing tests simulating outdoor runoff conditions. The corrosion processes were evaluated through different analyses, and the results obtained were compared to those of a traditional quaternary bronze. The second line was carried out to characterise historic aluminium alloys used in aeronautics to develop and apply innovative protection strategies for their conservation. Historic wrecks were identified and characterised through micro and macroscale observations. Moreover, accelerated ageing tests were performed on both historic and modern alloys to compare their behaviour and select the best modern substrate to be used for the development of effective coatings. The third research line aimed to develop accelerate sampling and ageing methods to investigate the role of particulate matter (PM) in the atmospheric corrosion of bronzes and metals in general. The first approach consisted in the fine-tuning of an efficient accelerated method for ambient PM sampling on bronze specimens followed by their accelerated ageing, in order to establish a correlation between the PM and the substrate’s corrosion. After the accelerated ageing of the specimens, the corrosion was evaluated by surface characterisation and correlated to the PM features. The second approach consisted in the development of a synthetic PM formulation and of an artificial deposition method, which was performed by spraying mixtures containing the main PM inorganic fractions on a G-85 bronze with an airbrush. The deposition efficiency was assessed, and the effect of synthetic PM on the bronze corrosion was evaluated. The results were compared to those obtained by ambient PM deposition.

Green approach to Palladium Cross-Coupling reactions and development of new methodologies based on highly abundant metals

Transition metal catalyzed cross-coupling reactions represent among the most versatile and useful tools in organic synthesis for the carbon-carbon (C-C) bond formation and have a prominent role in both the academic and pharmaceutical segments. Among them, palladium catalyzed cross-coupling reactions are currently the most versatile. In this thesis, the applications, impact and development of green palladium cross-coupling reactions are discussed. Specifically, we discuss the translation of the Twelve Principles of Green Chemistry and their applications in pharmaceutical organometallic chemistry to stimulate the development of cost-effective and sustainable catalytic processes for the synthesis of active pharmaceutical ingredients (API). The Heck-Cassar-Sonogashira (HCS) and the Suzuki-Miyaura (SM) protocols, using HEP/H2O as green mixture and sulfonated phosphine ligands, allowed to recycle and recover the catalyst, always guaranteeing high yields and fast conversion under mild conditions, with aryl iodides, bromides, triflates and chlorides. No catalyst leakage or metal contamination of the final product were observed during the HCS and SM reactions, respecting the very low limits for metal impurities in medicines established by the International Conference of Harmonization Guidelines Q3D (ICH Q3D). In addition, a deep understanding of the reaction mechanism is very important if the final target is to develop efficient protocols that can be applied at industrial level. Experimental and theoretical studies pointed out the presence of two catalytic cycles depending on the counterion, shedding light on the role of base in catalyst reduction and acetylene coordination in the HCS coupling. Finally, the development of a cross-coupling reaction to form aryldifluoronitriles in the presence of copper is discussed, highlighting the importance of inserting fluorine atoms within biological structures and the use of readily available metals such as copper as an alternative to palladium.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.

Development of molecular-level switches and implementation into novel nanostructures and smart materials

The work presented in this thesis deals with the design, synthesis and investigation of (supra)molecular switches, and their implementation into novel nanostructures and smart devices. Part A deals with investigation of fundamental properties of Donor Acceptor Stenhouse Adducts (DASAs) as well as their implementation into polymer matrices in order to construct novel smart materials. Part B deals with the implementation of azobenzene photoswitches into pseudorotaxanes and the investigation of the effect of light-driven isomerization on the self-assembly and disassembly processes.