Interactions between molecules and nanostructures using quartz crystal microbalance

The understanding of protein behaviour at the nanoscale is critical for the development of new therapies and biosensing. The assembly of peptides for new therapies are performed on the surface of a biosensor and because of the rough nature of this sample, the characterisation is usually performed on a separate substrate that will provide a higher contrast with a different technique. The ideal scenario is for the same surface to be used in both sensing and characterisation stages. For biosensing, the rough nature of the surface could increase the range of mass measurement for biosensors with micro and nanoscale surfaces. Additionally, the interaction of proteins with nanostructures open the possibility of altering the dynamics of protein adsorption. These changes could be translated to different mechanical properties of the sensed protein. Furthermore, the induced conformational change might allow for a permanent attachment of the protein, increasing the limit of detection of a biosensor. However, the behaviour of proteins with nanoscale features is not well understood. Therefore, the fabrication of nanostructured surfaces along with eliminating such features on QCM biosensors for sensing and characterisation of proteins is pursued in this dissertation. Multiple novel methods of nanofabrication on top of QCM gold electrodes were created using ZnO nanowires (Chapter 1), gold nanoparticles (Chapter 2), and e-beam lithography (Chapter 5). These techniques were further optimised to obtain simple protocols to be followed by any user. Subsequently, optimal surfaces were used for protein adsorption and their results show less protein adsorption than the expected by the area increase of the features (50-70%), suggesting protein conformational changes (spreading) upon binding. The observation of protein conformational changes on nanostructures suggested that the roughness of standard gold QCM electrodes might also play a role in protein adsorption. A novel fabrication process is developed for the transfer of an atomically flat surface of gold onto a QCM Au electrode, the pressure-forming template stripped (PTS) technique. In Chapter 3, the PTS method is presented with the crucial parameters for obtaining an atomically flat gold surface on QCM resonators and their optimisation to obtain a roughness of 0.35 nm ± 0.05 root mean square and a required thickness of 100 nm of Au QCM electrodes. Furthermore, the QCM with PTS electrodes (PTS QCM) is used to adsorb model protein bovine serum albumin (BSA). This is compared against resonators with a standard electrode roughness from different companies, and against resonators build in-house with higher roughness than commercial samples. It is showed by both QCM mass monitoring and AFM of the same PTS QCM sample that BSA adsorption of BSA occurs in a self-assemble like manner, a tightly packed monolayer. More BSA areal mass is adsorbed on PTS QCM (15%) and high roughness QCM (17%) resonators than QCM samples with standard roughness. In contrast with standard QCM, high roughness QCM resonators induce aggregates on the surface increasing the mass adsorbed and obtaining similar areal mass to the tightly packed adsorption on PTS QCM devices.CONACyT (Mexico), SEP (Mexico), Cambridge Trust, Fitzwilliam College

Research Advances on Financial Inclusion: A Bibliometric Analysis

With intensifying competition in the financial system, new strategic applications are constantly being devised in the search for greater efficiency. In consequence, decisions are commonly based on locating and retaining market segments with high added value, and those which fail to supply the profitability required by the market are “excluded”. The aim of this study is to analyse the research advances made in the field of financial inclusion and the main lines of investigation currently being addressed by means of a bibliometric analysis. Among the scientific community, there is growing interest in this study area. The most assiduous in this respect are SA Asongu (the most productive author), Enterprise Development and Microfinance (the journal that has published the most articles in this field), Makerere University, Uganda (the most productive institution) and India (the country where most recent studies have taken place). Foreseeably inspiring future research, there is currently great interest in developing a more accessible financial system, especially through the use of digital money (Fintech) as an instrument to promote financial inclusion. For all this, a line of research is proposed that also includes the proposals from the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals

Cultural Sustainability in University Students’ Flamenco Music Event Attendance: A Neural Networks Approach

University students consume live music; however, almost 40% declare that they have never attended a flamenco show, an intangible heritage of humankind. Numerous studies have shown that cultural capital and socioeconomic profile, among other factors, are variables that influence cultural consumption, and therefore, cultural sustainability. Considering the relationship between several variables, this paper pursues a double objective. On the one hand, identifying the factors that influence attendance at flamenco shows, and on the other, proposing a predictive model that quantifies the likelihood of an individual attending a flamenco show. To this end, we analyse flamenco consumption by means of a survey conducted on 452 university students, using Multilayer Perceptrom (a non-parametric model), a methodology based on an artificial neural network. Our results confirm the importance of cultural capital, as well as personal and external factors, among other. The findings of this research work are of potential interest for management and planning of cultural events, as well as to promote cultural sustainability

A credit scoring model for institutions of microfinance under the Basil II normative

El crecimiento de los microcréditos a nivel mundial, junto con la normativa internacional sobre requerimientos de capital (Basilea II), están impulsando a las instituciones de microfinanzas (IMFs) a una mayor competencia con las entidades bancarias por este segmento de negocio. La banca tradicionalmente ha contado con adecuados modelos de credit scoring para analizar el riesgo de incumplimiento, pero esto no ha sido así en las IMFs supervisadas. El objetivo de esta investigación es diseñar un modelo de credit scoring para una institución sometida a supervisión y especializada en microcréditos, como es la Entidad de Desarrollo de la Pequeña y Micro Empresa (Edpyme) del sistema financiero del Perú. El resultado de la investigación muestra la metodología y fases necesarias para diseñar el modelo, así como el proceso de valoración y validación para que pueda ser aplicado en el área de negocio, especialmente para establecer la política de tasas de interés con clientes. Por último, también se muestra cómo puede utilizarse el modelo para desarrollar una gestión del riesgo de crédito en el marco de los métodos IRB de Basilea II.------------------------------------------------------------The growth of microcredit worldwide along with international rules on capital requirements (Basel II) are increasing the competition between microfinance institutions (MFIs) and banks for this business segment. The bank system traditionally has relied on adequate credit scoring models to analyze the risk of payment failures, but this has not been the case in supervised MFIs. The objective of this research is to design a credit scoring model for any institution subjected to supervision and specialized in microcredit as the Development Agency for Small and Micro Enterprise (Entidad de Desarrollo de la Pequeña y Micro Empresa - Edpyme) of the financial system in Peru. The results of this research includes a methodology and the steps needed to design the model, and the assessment and validation process that can be applied in the business area, in particular, to establish an interest rate policy with customers. Eventually, the paper also explains how the model can be used to develop credit risk management under the Basel II IRB approaches.Publicad

A CREDIT SCORING MODEL FOR INSTITUTIONS OF MICROFINANCE UNDER THE BASEL II NORMATIVE

The growth of microcredit worldwide along with international rules on capital requirements (Basel II) are increasing the competition between microfinance institutions (MFIs) and banks for this business segment. The bank system traditionally has relied on adequate credit scoring models to analyze the risk of payment failures, but this has not been the case in supervised MFIs. The objective of this research is to design a credit scoring model for any institution subjected to supervision and specialized in microcredit as the Development Agency for Small and Micro Enterprise (Entidad de Desarrollo de la Pequeña y Micro Empresa - Edpyme) of the financial system in Peru. The results of this research includes a methodology and the steps needed to design the model, and the assessment and validation process that can be applied in the business area, in particular, to establish an interest rate policy with customers. Eventually, the paper also explains how the model can be used to develop credit risk management under the Basel II IRB approaches.Microcredit; institutions of microfinance; Basel II; credit scoring; Logit; IRB

Predicting Big Data Adoption in Companies With an Explanatory and Predictive Model

The purpose of this paper is to identify the factors that affect the intention to use Big Data Applications in companies. Research into Big Data usage intention and adoption is scarce and much less from the perspective of the use of these techniques in companies. That is why this research focuses on analyzing the adoption of Big Data Applications by companies. Further to a review of the literature, it is proposed to use a UTAUT model as a starting model with the update and incorporation of other variables such as resistance to use and perceived risk, and then to perform a neural network to predict this adoption. With respect to this non-parametric technique, we found that the multilayer perceptron model (MLP) for the use of Big Data Applications in companies obtains higher AUC values, and a better confusion matrix. This paper is a pioneering study using this hybrid methodology on the intention to use Big Data Applications. The result of this research has important implications for the theory and practice of adopting Big Data Applications

Analyzing political and systemic determinants of financial risk in local governments

Studies have shown that political variables can infl uence the volume of government debt and have recommended investigating the joint effects of diverse factors on the risk of local government default. Considering the relation between economic management and political constraints, this paper examines the joint infl uence of political and systemic factors on the risk of loan default by Spanish local governments. To do so, we analyze 148 city councils for the period 2006-2011, using a logit model with panel data and an artifi cial neural network. The empirical results indicate that the fi nancial risk of local governments is affected both by political factors specifi c to each case and, simultaneously, by systemic variables for the country. Specifi cally, political variables such as the mayor not having economics-related university studies, the under-representation of female councilors in the municipal corporation, municipal government by a party with a progressive ideology, and ideological alignment between the municipal and the regional government are all associated with greater fi nancial risk. Moreover, rising national unemployment, an increased sovereign risk premium, the impact of the electoral cycle, and that of declining economic growth are all factors that may increase the risk of default. The fi ndings presented are of great potential interest for governments, managers, national and international fi scal authorities, fi nancial regulators, and citizens at large, because an understanding of the signifi cance of these variables can help authorities make appropriate decisions to prevent and/or overcome problems related to municipal insolvency

Ultra-flat Gold QCM Electrodes Fabricated with Pressure Forming Template Stripping for Protein Studies at the Nanoscale

Single-molecule imaging of proteins using atomic force microscopy (AFM) is crucially dependent on protein attachment to ultra-flat substrates. The technique of template stripping (TS), which can be used to create large areas of atomically flat gold, has been used to great effect for this purpose. However, this approach requires an epoxy which can swell in solution, causing surface roughening and substantially increasing the thickness of any sample, preventing its use on acoustic resonators in liquid. Diffusion bonding techniques should circumvent this problem but cannot be used on samples containing patterned features with mismatched heights due to cracking and poor transfer. Here, we describe a new technique called pressure forming template stripping (PTS) which permits an ultra-flat (0.35 ± 0.05 nm root-mean-square roughness) layer of gold to be transferred to the surface of a patterned substrate at low temperature and pressure. We demonstrate this technique by modifying a quartz crystal microbalance (QCM) sensor to contain an ultra-flat gold surface. Standard QCM chips have substantial roughness, preventing AFM imaging of proteins on the surface after measurement. With our approach there is no need to run samples in parallel: the modified QCM chip is flat enough to permit high-contrast AFM imaging after adsorption studies have been conducted. The PTS-QCM chips are then used to demonstrate adsorption of bovine serum albumin in comparison to rough QCM chips. The ability to attach thin layers of ultra-flat metals to surfaces of heterogeneous nature without epoxy will have many applications in diverse fields where there is a requirement to observe nanoscale phenomena with multiple techniques, including surface and interfacial science, optics, and biosensing

Un modelo de Credit Scoring para instituciones de microfinanzas en el marco de Basilea II

The growth of microcredit worldwide along with international rules on capital requirements (Basel II) are increasing the competition between microfinance institutions (MFIs) and banks for this business segment. The bank system traditionally has relied on adequate credit scoring models to analyze the risk of payment failures, but this has not been the case in supervised MFIs. The objective of this research is to design a credit scoring model for any institution subjected to supervision and specialized in microcredit as the Development Agency for Small and Micro Enterprise (Entidad de Desarrollo de la Pequeña y Micro Empresa - Edpyme) of the financial system in Peru. The results of this research includes a methodology and the steps needed to design the model, and the assessment and validation process that can be applied in the business area, in particular, to establish an interest rate policy with customers. Eventually, the paper also explains how the model can be used to develop credit risk management under the Basel II IRB approaches.El crecimiento de los microcréditos a nivel mundial junto con la normativa internacional sobre requerimientos de capital (Basilea II) están impulsando a las instituciones de microfinanzas (IMFs) a una mayor competencia con las entidades bancarias por este segmento de negocio. La banca tradicionalmente ha contado con adecuados modelos de credit scoring para analizar el riesgo de incumplimiento pero esto no ha sido así en las IMFs supervisadas. El objetivo de esta investigación es diseñar un modelo de credit scoring para una institución sometida a supervisión y especializada en microcréditos como es la Entidad de Desarrollo de la Pequeña y Micro Empresa (Edpyme) del sistema financiero del Perú. El resultado de la investigación muestra la metodología y fases necesarias para diseñar el modelo así como el proceso de valoración y validación para que pueda ser aplicado en el área de negocio especialmente para establecer la política de tasas de interés con clientes. Por último también se muestra cómo puede utilizarse el modelo para desarrollar una gestión del riesgo de crédito en el marco de los métodos IRB de Basilea II

Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study

Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack of research, nothing is known about whether non-financial information and non-parametric statistical techniques improve the predictive capacity of these models. Therefore, this paper provides an innovative financial distress model specifically designed for microenterprise startups via support vector machines (SVMs) that employs financial, non-financial, and macroeconomic variables. Based on a sample of almost 5,500 micro-entrepreneurs from a Peruvian Microfinance Institution (MFI), our findings show that the introduction of non-financial information related to the zone in which the entrepreneurs live and situate their business, the duration of the MFI-entrepre-neur relationship, the number of loans granted by the MFI in the last year, the loan destination, and the opinion of experts on the probability that microenterprise start-ups may experience financial problems, significantly increases the accuracy performance of our financial distress model. Furthermore, the results reveal that the models that use SVMs outperform those which employ traditional logistic regression (LR) analysis.A pesar del destacado papel que desempeña el microemprendimiento en el desarrollo económico y de la alta tasa de quiebra que tienen las nuevas microempresas en sus primeros años de vida, muy pocos estúdios han diseñado un modelo para detectar las dificultades financieras de los microemprendedores Además, debido a la ausencia de investigaciones, no se conoce nada acerca de si la información no financiera y las técnicas estadísticas no paramétricas mejoran la capacidad predictiva de estos modelos. Por tanto, este artículo proporciona un innovador modelo para detectar las dificultades financieras específicamente diseñado para las microempresas de nueva creación mediante el uso de máquinas de soporte vectorial (MSV) y empleando variables financieras, no financieras y macroeconómicas. Basados en una muestra de casi 5.500 de una Institución Mi-crofinanciera (IMF) peruana, nuestros hallazgos muestran que la introducción de información no financiera relacionada con la zona en la que el emprendedor vive y localiza su negocio, la duración de la relación IMF-emprendedor, el número de préstamos concedidos por la IMF en el último año, el destino del préstamo y la opinión de los expertos sobre la probabilidad de que la nueva microempresa experimente problemas financieros, aumentan de manera significativa la precisión de nuestro modelo de detección de dificultades financieras. Además, los resultados revelan que los modelos construidos usando MVS superan los obtenidos por aquellos modelos que emplean el tradicional análisis de regresión logística.Apesar do destacado papel que o microempreendimento desempenha no desenvolvimento económico e da alta taxa de falências que as novas microempresas têm nos seus primeiros anos de vida, poucos estudos têm projetado um modelo para detectar as dificuldades financeiras dos microempreendedores. Além disso, devido à ausência de pesquisas, não se sabe nada sobre se a informação não financeira e as técnicas estatísticas não paramétricas melhoram a capacidade preditiva destes modelos. Portanto, este artigo proporciona um inovador modelo para detectar as dificuldades financeiras especificamente projetado para as microempresas de criação recente mediante o uso de máquinas de vetores suportes (MVS) e utilizando variáveis financeiras, não financeiras e macroeconómicas Baseados em uma amostra de quase 5.500 microempresas de uma micro-insti-tuição financeira (IMF) peruana, encontramos que a introdução de informação não financeira relacionada com a região na qual o empreendedor mora e localiza o seu negócio, a duração da relação IMF- empreendedor, o número de empréstimos concedidos pela IMF no último ano, a destinação do empréstimo e a opinião dos peritos sobre a probabilidade de a nova microempresa ter problemas financeiros aumentam significativamente a precisão do nosso modelo de detecção de dificuldades financeiras. Além do mais, os resultados revelam que os modelos construídos utilizando MVS ultrapassam os obtidos por aqueles modelos que utilizam a tradicional análise de regressão logística