Low-temperature isothermal Rankine cycle for desalination

In brackish groundwater desalination, high recovery ratio (of fresh water from saline feed) is desired to minimise concentrate reject. To this effect, previous studies have developed a batch reverse osmosis (RO) desalination system, DesaLink, which proposed to expand steam in a reciprocating piston cylinder and transmit the driving force through a linkage crank mechanism to pressurise batches of saline water (recirculating) in a water piston cylinder unto RO membranes. However, steam is largely disadvantaged at operation from low temperature (< 150oC) thermal sources; and organic working fluids are more viable, though, the obtainable thermal cycle efficiencies are generally low with low temperatures. Consequently, this thesis proposed to investigate the use of organic working fluid Rankine cycle (ORC) with isothermal expansion, to drive the DesaLink machine, at improved thermal efficiency from low temperature thermal sources. Following a review of the methods of achieving isothermal expansion, ‘liquid flooded expansion’ and ‘expansion chamber surface heating’ were identified as potential alternative methods. Preliminary experimental comparative analysis of variants of the heated expansion chamber technique of effecting isothermal expansion favoured a heated plain wall technique, and as such was adopted for further optimisation and development. Further, an optimised isothermal ORC engine was built and tested at < 95oC heat source temperature, with R245fa working fluid – which was selected from 16 working fluids that were analysed for isothermal operation. Upon satisfactory performance of the test engine, a larger (10 times) version was built and coupled to drive the DesaLink system. Operating the integrated ORC-RO DesaLink system, gave freshwater (approximately 500 ppm) production of about 12 litres per hour (from 4000 ppm feed water) at a recovery ratio of about 0.7 and specific energy consumption of 0.34 kWh/m3; and at a thermal efficiency of 7.7%. Theoretical models characterising the operation and performance of the integrated system was developed and utilised to access the potential field performance of the system, when powered by two different thermal energy sources – solar and industrial bakery waste heat – as case studies.

A multi-method approach for the assessment of composite indices and rankings

There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.

Property Exchange Rules Offer Tax Opportunities for Hotel Owners

One strategy often overlooked by hospitality owners in developing cost-saving strategies is the use of like-kind exchanges to acquire property. The author reviews some alternative methods of like-kind exchanges, which may not only provide new business opportunities for the hospitality owner, but lucrative tax benefits as well.

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.

Bioengineering strategies to improve functional qualities of nisin

The abuse of antibiotics and the emergence of multi-drug resistant bacterial strains have created the need to explore alternative methods of controlling microbial pathogens. The bacteriocin family of antimicrobial peptides has been proposed as one such alternative to classic antibiotics. Nisin A belongs to the subgroup of bacteriocins called the lantibiotics, which contain several unusual amino acids as a consequence of enzyme-mediated post-translational modifications. As nisin is produced by generally regarded as safe (GRAS) microorganisms, it could potentially be applied in a clinical setting. However, as lantibiotics are naturally produced in such small quantities, this can hinder their industrial potential. In order to overcome this, several approaches can be utilised. For example, given the gene encoded nature of lantibiotics, genetic engineering approaches can be implemented in order to yield variants with enhanced properties. Here, the use of mutagenesis-based strategies was employed to obtain a derivative of nisin with enhanced bioactivity in vitro. Investigations with purified peptide highlighted the enhanced specific activity of this variant, nisin M21V, against food-borne Listeria monocytogenes strains. Furthermore, this specific enhanced bioactivity was evident in a mouse model of listeriosis. Reductions in bioluminescence and microbial counts in organs from infected mice were observed following treatment with nisin M21V compared to that of wild-type nisin A. Peptide bioengineering approaches were also implemented to obtain additional novel derivatives of nisin. The generation of “S5X” and “S33X” banks (representing a change of natural serines at positions 5 and 33 to all possible alternative residues) by a combination of site-saturation and site-directed mutagenesis led to the identification of several derivatives exhibiting improved stability. This allowed the rational design of variants with enhanced stability compared to that of wild type nisin. Another means of tackling issues associated with lantibiotic yield is to combine lantibiotics with other antimicrobials. This could circumvent the need for enhanced production while also reducing concentrations of the peptide antimicrobials. We observed that combinations of nisin variants and low levels of plant essential oils (thymol, carvacrol, trans-cinnamaldehyde) significantly controlled Gram negative foodborne pathogens in in vitro assays compared to nisin A-essential oil combinations. This enhanced control was also evident in model food systems. Nisin variants used in conjunction with carvacrol significantly reduced numbers of E. coli O157:H7 in apple juice while a commercial nisin preparation used in combination with citric acid significantly controlled C. sakazakii in infant milk formula. It is noteworthy that while nisin is generally associated with Gram positive targets, upon combination with plant essential oils the spectrum of inhibition was broadened to Gram negative targets.

Molecular docking and geographical information systems as tools to assess the potential impact of veterinary medicines on non-target organisms and the environment

Veterinary medicines (VMs) from agricultural industry can enter the environment in a number of ways. This includes direct exposure through aquaculture, accidental spillage and disposal, and indirect entry by leaching from manure or runoff after treatment. Many compounds used in animal treatments have ecotoxic properties that may have chronic or sometimes lethal effects when they come into contact with non-target organisms. VMs enter the environment in mixtures, potentially having additive effects. Traditional ecotoxicology tests are used to determine the lethal and sometimes reproductive effects on freshwater and terrestrial organisms. However, organisms used in ecotoxicology tests can be unrepresentative of the populations that are likely to be exposed to the compound in the environment. Most often the tests are on single compound toxicity but mixture effects may be significant and should be included in ecotoxicology testing. This work investigates the use, measured environmental concentrations (MECs) and potential impact of sea lice treatments on salmon farms in Scotland. Alternative methods for ecotoxicology testing including mixture toxicity, and the use of in silico techniques to predict the chronic impact of VMs on different species of aquatic organisms were also investigated. The Scottish Environmental Protection Agency (SEPA) provided information on the use of five sea lice treatments from 2008-2011 on Scottish salmon farms. This information was combined with the recently available data on sediment MECs for the years 2009-2012 provided by SEPA using ArcGIS 10.1. In depth analysis of this data showed that from a total of 55 sites, 30 sites had a MEC higher than the maximum allowable concentration (MAC) as set out by SEPA for emamectin benzoate and 7 sites had a higher MEC than MAC for teflubenzuron. A number of sites that were up to 16 km away from the nearest salmon farm reported as using either emamectin benzoate or teflubenzuron measured positive for the two treatments. There was no relationship between current direction and the distribution of the sea lice treatments, nor was there any evidence for alternative sources of the compounds e.g. land treatments. The sites that had MECs higher than the MAC could pose a risk to non-target organisms and disrupt the species dynamics of the area. There was evidence that some marine protected sites might be at risk of exposure to these compounds. To complement this work, effects on acute mixture toxicity of the 5 sea lice treatments, plus one major metabolite 3-phenoxybenzoic acid (3PBA), were measured using an assay using the bioluminescent bacteria Aliivibrio fischeri. When exposed to the 5 sea lice treatments and 3PBA A. fischeri showed a response to 3PBA, emamectin benzoate and azamethiphos as well as combinations of the three. In order to establish any additive effect of the sea lice treatments, the efficacy of two mixture prediction equations, concentration addition (CA) and independent action ii(IA) were tested using the results from single compound dose response curves. In this instance IA was the more effective prediction method with a linear regression confidence interval of 82.6% compared with 22.6% of CA. In silico molecular docking was carried out to predict the chronic effects of 15 VMs (including the five used as sea lice control). Molecular docking has been proposed as an alternative screening method for the chronic effects of large animal treatments on non-target organisms. Oestrogen receptor alpha (ERα) of 7 non-target bony fish and the African clawed frog Xenopus laevis were modelled using SwissModel. These models were then ‘docked’ to oestradiol, the synthetic oestrogen ethinylestradiol, two known xenoestrogens dichlorodiphenyltrichloroethane (DDT) and bisphenol A (BPA), the antioestrogen breast cancer treatment tamoxifen and 15 VMs using Auto Dock 4. Based on the results of this work, four VMs were identified as being possible xenoestrogens or anti-oestrogens; these were cypermethrin, deltamethrin, fenbendazole and teflubenzuron. Further investigation, using in vitro assays, into these four VMs has been suggested as future work. A modified recombinant yeast oestrogen screen (YES) was attempted using the cDNA of the ERα of the zebrafish Danio rerio and the rainbow trout Oncorhynchus mykiss. Due to time and difficulties in cloning protocols this work was unable to be completed. Use of such in vitro assays would allow for further investigation of the highlighted VMs into their oestrogenic potential. In conclusion, VMs used as sea lice treatments, such as teflubenzuron and emamectin benzoate may be more persistent and have a wider range in the environment than previously thought. Mixtures of sea lice treatments have been found to persist together in the environment, and effects of these mixtures on the bacteria A. fischeri can be predicted using the IA equation. Finally, molecular docking may be a suitable tool to predict chronic endocrine disrupting effects and identify varying degrees of impact on the ERα of nine species of aquatic organisms.

How using Technology Enhanced Learning could help modernise traditional large group teaching or Lecturing.

The efficiency of lecturing or large group teaching has been called into question for many years. An abundance of literature details the components of effective teaching which are not provided in the traditional lecture setting, with many alternative methods of teaching recommended. However, with continued constraints on resources large group teaching is here to stay and student’s expect and are familiar with this method.

Technology Enhanced Learning may be the way forward, to prevent educators from “throwing out the baby with the bath water”. TEL could help Educator’s especially in the area of life sciences which is often taught by lectures to engage and involve students in their learning, provide feedback and incorporate the “quality” of small group teaching, case studies and Enquiry Based Learning into the large group setting thus promoting effective and deep learning.

Noise resilient discrete-time cross-relation sensor characterisation

In-situ characterisation of thermocouple sensors is a challenging problem. Recently the authors presented a blind characterisation technique based on the cross-relation method of blind identification. The method allows in-situ identification of two thermocouple probes, each with a different dynamic response, using only sampled sensor measurement data. While the technique offers certain advantages over alternative methods, including low estimation variance and the ability to compensate for noise induced bias, the robustness of the method is limited by the multimodal nature of the cost function. In this paper, a normalisation term is proposed which improves the convexity of
the cost function. Further, a normalisation and bias compensation hybrid approach is presented that exploits the advantages of both normalisation and bias compensation. It is found that the optimum of the hybrid cost function is less biased and more stable than when only normalisation is applied. All results were verified by simulation.

Effektiv lagerstyrning med AHP och tvådimensionell artikelklassificering : En fallstudie på Permobil AB, Timrå

Costs related to inventory are usually a significant amount of the company’s total assets. Despite this, companies in general don’t pay a lot of interest in it, even if the benefits from effective inventory are obvious when it comes to less tied up capital, increased customer satisfaction and better working environment. Permobil AB, Timrå is in an intense period when it comes to revenue and growth. The production unit is aiming for an increased output of 30 % in the next two years. To make this possible the company has to improve their way to distribute and handle material,The purpose of the study is to provide useful information and concrete proposals for action, so that the company can build a strategy for an effective and sustainable solution when it comes to inventory management. Alternative methods for making forecasts are suggested, in order to reach a more nuanced perception of different articles, and how they should be managed. Analytic Hierarchy Process (AHP) was used in order to give specially selected persons the chance to decide criteria for how the article should be valued. The criteria they agreed about were annual volume value, lead time, frequency rate and purchase price. The other method that was proposed was a two-dimensional model where annual volume value and frequency was the criteria that specified in which class an article should be placed. Both methods resulted in significant changes in comparison to the current solution. For the spare part inventory different forecast methods were tested and compared with the current solution. It turned out that the current forecast method performed worse than both moving average and exponential smoothing with trend. The small sample of ten random articles is not big enough to reject the current solution, but still the result is a reason enough, for the company to control the quality of the forecasts.

Desempenho de fosfitos de potássio no manejo de mofo branco em soja

Soybean plays an important role in the Brazilian agriculture being one of the products most exported by the country. Its yield may be affected by diseases such as white mold, caused by the fungus Sclerotinia sclerotiorum Lib. de Bary, which, under favorable field conditions prevents the crop of expressing all its productive potential. The fungus is cosmopolitan and infects more than 400 species of plants. This disease is difficult to control, and the use of chemicals has not been sufficient to avoid significant losses, thus, this products are expensive and may cause environmental damage. Alternative methods, such as foliar fertilizers based on potassium phosphite, can also be used in the management of this disease. In this context, this work aimed to study different sources of potassium phosphite and its effects in the control of white mold in soybeans, as well as the time of application in culture, its action in inducing plants defense responses and/or its influence over the seeds quality. The effect of phosphites, over the pathogen, was evaluated in vitro, on mycelial inhibition, the mass of dry mycelium and germination of sclerotia. In all tests, the following phosphites were utilized: Phosphite A (P2O5-40%; K2O-20% - 1 L/ha); Phosphite B (P2O5-40%; K2O-28% - 1 L/ha); Phosphite C (P2O5-40%; K2O-20% - 1 L/ha) e Phosphite D (P2O5-30%; K2O-20% - 2,4 L/ha). At the induction of resistance tests were evaluated the synthesis of phytoalexin in soybean cotyledons and the enzymes FAL and POX evaluated in seedlings in growing chamber, sprayed with phosphites and the fungicide fluazinam. Field experiment was carried out at Coronel Domingos Soares-PR, in the 2012/2013 season, in an area with natural infestation of the pathogen. Soybean cultivar BMX Active was no-till seeded with 0,5m between rows. The experimental was laid out as a factorial 5 x 4 scheme (treatment x application time). Phosphites sources were used, as described above, and water was sprayed in the control treatment. Treatments were applied at four different growth stages: V4, V4 + R1, R1 and R2 at the rates recommended by the manufacturer. Soybean yield components and seeds and health and physiological quality were evaluated after harvesting. None of the tested phosphites affected mycelial growth and sclerotia germination or influenced phytoalexin synthesis. Phosphites C and D stood out due to an increasing in the phenylalanine ammonia-lyase activity 48 hours after its inoculation. These same products also induced the synthesis and peroxidases and phosphite C kept the levels of this enzyme elevated up to 72 hours after inoculation. At the field trials, phosphites C and D stood out in the control of white mold. There was no significant interaction of potassium phosphite on physiological and sanitary quality of the seeds.

Desenvolvimento de metodologias alternativas para quantificação de micronutrientes em produtos de nutrição infantil

As farinhas infantis, alimentos que se destinam a recém-nascidos e crianças até à idade pré-escolar, devem satisfazer todas as necessidades nutricionais que se verificam durante o período de crescimento e desenvolvimentos físico e mental desta faixa etária. Desta forma, são frequentemente adicionadas prémisturas de vitaminas e minerais durante a sua produção (fortificação), de maneira a que a quantidade adicionada e a composição do produto final sejam concordantes com a legislação comunitária em vigor. A implementação, na linha de produção, de métodos alternativos de análise “amigos do ambiente” e passíveis de obter resultados rápidos acerca da composição nutricional dos produtos alimentares, mesmo antes destes serem embalados, permite reduções de tempo, custos e um melhor controlo do processo de produção. A espectroscopia FT-NIR e a espectroscopia de XRF são técnicas que permitem a quantificação de micronutrientes e possuem características fundamentais ao controlo rápido de processos. Neste trabalho foram desenvolvidos modelos de calibração para quantificação de zinco, por espectroscopia de XRF, em três receitas de pré-misturas de vitaminas e minerais. Construíram-se dois modelos de calibração, um com um R2 de 0,990 e um SEC de 26,624 mg/100g e outro com um R2 de 0,927 e um SEC de 18,838 mg/100g. Estes resultados indicam que os modelos de calibração construídos são adequados e podem ser usados na determinação rápida do teor de zinco em pré-misturas de vitaminas e minerais. Foram também verificadas as rectas de calibração existentes para quantificação de cálcio e ferro por espectroscopia de XRF e quantificação de vitamina C por espectroscopia FT-NIR para aplicação nas novas receitas de pré-misturas de vitaminas e minerais.

Forecasting exchange rates in the presence of instabilities

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

Sustainability of protein production by bioreactor processes using wind and solar power as energy sources

Food production account for significant share of global environmental impacts. Impacts are global warming, fresh water use, land use and some non-renewable substance consumption like phosphorous fertilizers. Because of non-sustainable food production, the world is heading to different crises. Both food- and freshwater crises and also land area and phosphorous fertilizer shortages are one of many challenges to overcome in near future. The major protein sources production amounts, their impacts on environment and uses are show in this thesis. In this thesis, a more sustainable than conventional way of biomass production for food use is introduced. These alternative production methods are photobioreactor process and syngas-based bioreactor process. The processes’ energy consumption and major inputs are viewed. Their environmental impacts are estimated. These estimations are the compared to conventional protein production’s impacts. The outcome of the research is that, the alternative methods can be more sustainable solutions for food production than conventional production. However, more research is needed to verify the exact impacts. Photobioreactor is more sustainable process than syngas-based bioreactor process, but it is more location depended and uses more land area than syngas-based process. In addition, the technology behind syngas-based application is still developing and it can be more efficient in the future.

Experiences of COPD patients with existing smoking cessation programs and their preferences for improvement - a qualitative analysis

BACKGROUND: Smoking is a major risk factor for chronic obstructive pulmonary disease (COPD). For current smokers who are diagnosed with COPD, their first treatment option is to stop smoking. Motivation is necessary for long-term smoking cessation; therefore, when designing smoking cessation programs, the patients' needs and preferences should be considered. We focused on COPD patients' experiences with existing smoking cessation programs and evaluated their preferences for the improvement of these programs. METHODS: We conducted 18 guideline-based interviews with COPD patients between April and June 2014 in Germany. Each patient with COPD, who was a current or past smoker and had made at least one attempt to quit smoking in the past 5 years, was included in the study. We audiotaped, verbatim transcribed, and evaluated the interviews, using content analysis. RESULTS: The patients had broad and different experiences with pharmaceutical, behavioral, and alternative approaches that supported or negatively influenced the smoking cessation process. Pharmaceuticals were viewed as an expensive alternative with many side effects although they helped to stop cravings for a few moments. Furthermore, the bad structure and impersonal content of the seminars for smoking cessation negatively influenced group cohesion, and therefore degrading the patients' motivation to stop smoking. Alternative methods, such as acupuncture and hypnosis were mostly ineffective in smoking cessation, but in some cases, served as motivational strategies. CONCLUSION: Negative experiences with smoking cessation were explained by the patients' lack of motivation or resolution. Other negative experiences, such as the structure of seminars for smoking cessation and the high price of pharmaceuticals should be addressed through policy changes to increase the patients' motivation to quit smoking.

Shortcuts to adiabaticity in the double well

123 p.