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Anne Dreller shows that data sharing offers great opportunities and huge value creation potential for the business world. Despite many opportunities that data sharing promises, the business world has not fully operationalized this fact yet, due to various existing challenges. Thus, an exemplary, future-oriented, and platform-based data sharing business model is developed for the startup Quemey. This business model is also equipped with prioritized implementation advice, including measures like focusing on strong values for all platform participants, growing their business into a powerful monopolist position, and eliminating barriers of technological, contractual and legal or data privacy uncertainties.
ICT has traditionally been a hostile territory for women. In information societies, this implies a drastic reduction in opportunities and autonomy for women. In emergent economies, the situation is even worse due to women’s subordinate status in society and little research regarding the intersection between gender and the digital divide. Such is the case in Latin America. In light of this, the purpose of this essay is to introduce a first comprehensive review of the few studies made in Latin America, against the background of the history of women’s digital exclusion. Based on a review of literature, we identify the main causes for women’s digital exclusion in the region and talk about the prospects for development of gender policies in the BRICS countries (Brazil, Russia, India, China and South Africa). We conclude that what this group of countries may achieve in regard to gender equality, will mark the future of the world. The aim of this essay is to make a call for the creation of inter - national research networks and propose the BRICS as host for these efforts, as they combine characteristics that will make them leaders of change in vast regions.
Scientific or statistical research has long been the domain of dedicated programming languages such as R, SPSS or SAS. A few years other competitors entered the arena, among them Python with its powerful SciPy package. The following article introduces SciPy by applying a small subset of its functionality to a well-known dataset.
Text is one of the key sources of information for social sciences and humanities which, with the rise and development of computational technologies, has been mostly available via digital libraries, archives and websites. It enables researchers to increasingly deal with large scale text corpora that require the use of advanced software tools to process them and extract information. Computational linguistics - a discipline that has emerged on the border of computer science, linguistics and statistics - has achieved certain results in automated text analysis and information extraction, e.g., tools for part-of-speech tagging, grammar parsing, semantic role labelling, sentiment analysis and anaphora resolution have been developed and successfully used in many scientific projects. However, there still exists a gap between technology available and the needs of social sciences: named entity recognizers are incapable of identifying actors, sentiment analysis just provides the overall mood of an expression but is not able to identify the evaluation of information by the utterer, topic modeling tools can only assign a topic to a document, but fall short of measuring its frame.
The design of an efficient digital circuit in term of low-power has become a very challenging issue. For this reason, low-power digital circuit design is a topic addressed in electrical and computer engineering curricula, but it also requires practical experiments in a laboratory. This PhD research investigates a novel approach, the low-power design laboratory system by developing a new technical and pedagogical system. The low-power design laboratory system is composed of two types of laboratories: the on-site (hands-on) laboratory and the remote laboratory. It has been developed at the Bonn-Rhine-Sieg University of Applied Sciences to teach low-power techniques in the laboratory. Additionally, this thesis contributes a suggestion on how the learning objectives can be complemented by developing a remote system in order to improve the teaching process of the low-power digital circuit design. This laboratory system enables online experiments that can be performed using physical instruments and obtaining real data via the internet. The laboratory experiments use a Field Programmable Gate Array (FPGA) as a design platform for circuit implementation by students and use image processing as an application for teaching low-power techniques.
This thesis presents the instructions for the low-power design experiments which use a top-down hierarchical design methodology. The engineering student designs his/her algorithm with a high level of abstraction and the experimental results are obtained and measured at a low level (hardware) so that more information is available to correctly estimate the power dissipation such as specification, latency, thermal effect, and technology used. Power dissipation of the digital system is influenced by specification, design, technology used, as well as operating temperature. Digital circuit designers can observe the most influential factors in power dissipation during the laboratory exercises in the on-site system and then use the remote system to supplement investigating the other factors. Furthermore, the remote system has obvious benefits such as developing learning outcomes, facilitating new teaching methods, reducing costs and maintenance, cost-saving by reducing the numbers of instructors, saving instructor time and simplifying their tasks, facilitating equipment sharing, improving reliability, and finally providing flexibility of usage the laboratories.
Social Assistance
(2018)
If the first Sustainable Development Goal (SDG) to “End poverty in all its forms everywhere” is to be taken seriously, most low- and middle-income countries face a huge challenge. An estimated 1 billion people have indeed escaped extreme poverty since the early 1990s, and the global poverty rate fell from 35% in 1990 to 10.7% in 2013, but the absolute number of people living below the international poverty line of $1.90 at purchasing power parity has hardly changed. Countries in Asia contributed greatly to the overall decline in poverty rates: from 2012 to 2013, over 100 million people in Asia left extreme poverty behind, notably in India, Indonesia, and the People’s Republic of China (PRC) (World Bank 2016). Yet the living standards of those still below that line have hardly improved (Ravallion 2016). The achievement of the first SDG requires additional efforts at global and national levels, particularly on policies that address chronic poverty traps and that improve the outcomes of poor and vulnerable populations.
Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL-negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/- mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch towards increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.
For the last 20 years, solid-phase microextraction (SPME) in headspace (HS) mode has been used as a valuable sample preparation technique for identifying degradation products in polymers and the determination of residual monomers and other light-boiling substances in polymeric materials. For more than 10 years, our laboratory has been involved in projects focused on the application of HS-SPME-gas chromatography–mass spectrometry (GC–MS) for the characterization of polymeric materials from many branches of manufacturing and building industries. This article describes the application of this technique for identifying volatile organic compounds (VOCs), additives, and degradation products in industrial rubber, car labeling reflection foil, and bone cement materials. The obtained analytical results were then used for troubleshooting and remedial action of the technological processes as well as for the health protection of producers and users.
For many different applications, current information about the bandwidth-related metrics of the utilized connection is very useful as they directly impact the performance of throughput sensitive applications such as streaming servers, IPTV and VoIP applications. In literature, several tools have been proposed to estimate major bandwidth-related metrics such as capacity, available bandwidth and achievable throughput. The vast majority of these tools fall into one of Packet Pair (PP), Variable Packet Size (VPS), Self-Loading of Periodic Streams (SLoPS) or Throughput approaches. In this study, seven popular bandwidth estimation tools including nettimer, pathrate, pathchar, pchar, clink, pathload and iperf belonging to these four well-known estimation techniques are presented and experimentally evaluated in a controlled testbed environment. Differently from the rest of studies in literature, all tools have been uniformly classified and evaluated according to an objective and sophisticated classification and evaluation scheme. The performance comparison of the tools incorporates not only the estimation accuracy but also the probing time and overhead caused.
Persons with disabilities have much lower employment rates than the population as a whole and are at a significantly higher risk of living in poverty (OECD, 2011, pp. 50-56 and WHO, 2011, pp. 237-239). However, many of the barriers people with disabilities face, with regards to labor market reintegration, are in fact avoidable. There has for quite some time been evidence that differences in employment and wages, between disabled and non-disabled workers, can only to a limited extent be explained by differences in human capital endowments and productivity (Kidd, Sloane, & Ferko, 2000). Instead, factors such as the absence of access to education and training, and the lack of financial assistance provided are actually significant drivers of labor market exclusion (OECD, 2009, p.15; WHO, 2011, p.239).
Pyrolysis–Gas Chromatography
(2018)
The methodology of analytical pyrolysis-GC/MS has been known for several years, but is seldom used in research laboratories and process control in the chemical industry. This is due to the relative difficulty of interpreting the identified pyrolysis products as well as the variety of them. This book contains full identification of several classes of polymers/copolymers and biopolymers that can be very helpful to the user. In addition, the practical applications can encourage analytical chemists and engineers to use the techniques explored in this volume.
The structure and the functions of various types of pyrolyzers and the results of the pyrolysis–gas chromatographic–mass spectrometric identification of synthetic polymers/copolymers and biopolymers at 700°C are described. Practical applications of these techniques are also included, detailing the analysis of microplastics, failure analysis in the automotive industry and solutions for technological problems.
This work discusses how to use OSM for robotic applications and aims at starting a discussion between the OSM and the robotics community. OSM contains much topological and semantic information that can be directly used in robotics and offers various advantages: 1) Standardized format with existing tooling. 2) The graph structure allows to compose the OSM models with domain-specific semantics by adding custom nodes, relations, and key-value pairs. 3) Information about many places is already available and can be used by robots since it is driven by a community effort.
Friction effects impose a requirement for the supplementary amount of torque to be produced in actuators for a robot to move, which in turn increases energy consumption. We cannot eliminate friction, but we can optimize motions to make them more energy efficient, by considering friction effects in motion computations. Optimizing motions means computing efficient joint torques/accelerations based on different friction torques imposed in each joint. Existing friction forces can be used for supporting certain types of arm motions, e.g standing still.
Reducing energy consumption of robot's arms will provide many benefits, such as longer battery life of mobile robots, reducing heat in motor systems, etc.
The aim of this project is extending an already available constrained hybrid dynamic solver, by including static friction effects in the computations of energy optimal motions. When the algorithm is extended to account for static friction factors, a convex optimization (maximization) problem must be solved.
The author of this hybrid dynamic solver has briefly outlined the approach for including static friction forces in computations of motions, but without providing a detailed derivation of the approach and elaboration that will show its correctness. Additionally, the author has outlined the idea for improving the computational efficiency of the approach, but without providing its derivation.
In this project, the proposed approach for extending the originally formulated algorithm has been completely derived and evaluated in order to show its feasibility. The evaluation is conducted in simulation environment with one DOF robot arm, and it shows correct results from the computation of motions. Furthermore, this project presents the derivation of the outlined method for improving the computational efficiency of the extended solver.
This Handbook of Applied Marketing and Personnel Services is part of the project "German-African University Partnership Platform for the Development of Entrepreneurship and SMEs", financed by the German Federal Ministry of Economic Cooperation and Development (BMZ) and the German Academic Exchange Service (DAAD), and jointly conducted by Bonn-Rhein-Sieg University of Applied Sciences, University of Cape Coast in Ghana and University of Nairobi in Kenya.
According to the International Union of Pure and Applied Chemistry (IUPAC) recommendation, analytical pyrolysis (Py) is defined as the characterization in an inert atmosphere of a material or a chemical process by a chemical degradation reaction(s) induced by thermal energy [1]. Thermal degradation under controlled conditions is often used as a part of an analytical procedure, either to render a sample into a suitable form for subsequent analysis by gas chromatography (GC), mass spectrometry (MS), gas chromatography coupled with the mass spectrometry (GC/MS), with the Fourier-transform infrared spectroscopy (GC/FTIR), or by direct monitoring as an analytical technique in its own right [2].
Gas chromatography (GC) is a type of chromatography. According to the International Union of Pure and Applied Chemistry (IUPAC) recommendation, gas chromatography is defined as a separation technique in which the mobile phase is a gas. Gas chromatography is always carried out in a column [1]. GC is a separation and detection method for sample mixtures, whose components can be volatilized without thermal decomposition.
This policy brief investigates the costs of child poverty in the Balkans, including deprivation in terms of education, health, and social mobility. It then lays out the potential of social protection, most notably in terms of building resilence and fostering development. Set against recent case studies from around the world, including Cambodia and Uganda, the brief gives policy recommendations on various critical issues including transfer schemes, transformative measures, and (alternative) care for children with disabilities.
Speech understanding is a fundamental feature for many applications focused on human-robot interaction. Although many techniques and several services for speech recognition and natural language understanding have been developed in the last years, specific implementation and validation on domestic service robots have not been performed. In this paper, we describe the implementation and the results of a functional benchmark for speech understanding in service robotics that has been developed and tested in the context of different robot competitions: RoboCup@Home, RoCKIn@Home and within the European Robotics League on Service Robots. Different approaches used by the teams in the competitions are presented and the evaluation results obtained in the competitions are discussed.
Welcome to the first edition of the Handbook for Applied Teaching and Learning designed primarily for educators, administrators, and students interested in applied teaching and entrepreneurial education. This handbook documents some of the outcomes of a very fruitful German-African collaboration among higher education institutions in the field of entrepreneurial education which was funded by the German Academic Exchange Service (DAAD) and the German Ministry of Economic Cooperation and Development (BMZ).
The epithelial sodium channel (ENaC) is a critical regulator of vertebrate electrolyte homeostasis. ENaC is the only constitutively open ion channel in the degenerin/ENaC protein family, and its expression, membrane abundance, and open probability therefore are tightly controlled. The canonical ENaC is composed of three subunits (, , and ), but a fourth -subunit may replace and form atypical -ENaCs. Using Xenopus laevis as a model, here we found that mRNAs of the - and -subunits are differentially expressed in different tissues and that -ENaC predominantly is present in the urogenital tract. Using whole-cell and single-channel electrophysiology of oocytes expressing Xenopus - or -ENaC, we demonstrate that the presence of the -subunit enhances the amount of current generated by ENaC due to an increased open probability, but also changes current into a transient form. Activity of canonical ENaCs is critically dependent on proteolytic processing of the - and -subunits, and immunoblotting with epitope-tagged ENaC subunits indicated that, unlike -ENaC, the -subunit does not undergo proteolytic maturation by the endogenous protease furin. Furthermore, currents generated by -ENaC were insensitive to activation by extracellular chymotrypsin, and presence of the -subunit prevented cleavage of -ENaC at the cell surface. Our findings suggest that subunit composition constitutes an additional level of ENaC regulation, and we propose that the Xenopus -ENaC subunit represents a functional example that demonstrates the importance of proteolytic maturation during ENaC evolution.
Evolutionary conservation of the antimicrobial function of mucus: a first defence against infection
(2018)
Mucus layers often provide a unique and multi-functional hydrogel interface between the epithelial cells of organisms and their external environment. Mucus has exceptional properties including elasticity, changeable rheology and an ability to self-repair by reannealing, and is therefore an ideal medium for trapping and immobilising pathogens and serving as a barrier to microbial infection. The ability to produce a functional surface mucosa was an important evolutionary step, which evolved first in the Cnidaria, which includes corals, and the Ctenophora. This allowed the exclusion of non-commensal microbes and the subsequent development of the mucus-lined digestive cavity seen in higher metazoans. The fundamental architecture of the constituent glycoprotein mucins is also evolutionarily conserved. Although an understanding of the biochemical interactions between bacteria and the mucus layer are important to the goal of developing new antimicrobial strategies, they remain relatively poorly understood. This review summarises the physicochemical properties and evolutionary importance of mucus, which make it so successful in the prevention of bacterial infection. In addition, the strategies developed by bacteria to counteract the mucus layer are also explored.
This paper describes a dynamic, model-based approach for estimating intensities of 22 out of 44 different basic facial muscle movements. These movements are defined as Action Units (AU) in the Facial Action Coding System (FACS) [1]. The maximum facial shape deformations that can be caused by the 22 AUs are represented as vectors in an anatomically based, deformable, point-based face model. The amount of deformation along these vectors represent the AU intensities, and its valid range is [0, 1]. An Extended Kalman Filter (EKF) with state constraints is used to estimate the AU intensities. The focus of this paper is on the modeling of constraints in order to impose the anatomically valid AU intensity range of [0, 1]. Two process models are considered, namely constant velocity and driven mass-spring-damper. The results show the temporal smoothing and disambiguation effect of the constrained EKF approach, when compared to the frame-by-frame model fitting approach ‘Regularized Landmark Mean-Shift (RLMS)’ [2]. This effect led to more than 35% increase in performance on a database of posed facial expressions.
Towards explaining deep learning networks to distinguish facial expressions of pain and emotions
(2018)
Deep learning networks are successfully used for object and face recognition in images and videos. In order to be able to apply such networks in practice, for example in hospitals as a pain recognition tool, the current procedures are only suitable to a limited extent. The advantage of deep learning methods is that they can learn complex non-linear relationships between raw data and target classes without limiting themselves to a set of hand-crafted features provided by humans. However, the disadvantage is that due to the complexity of these networks, it is not possible to interpret the knowledge that is stored inside the network. It is a black-box learning procedure. Explainable Artificial Intelligence (AI) approaches mitigate this problem by extracting explanations for decisions and representing them in a human-interpretable form. The aim of this paper is to investigate the explainable AI method Layer-wise Relevance Propagation (LRP) and apply it to explain how a deep learning network distinguishes facial expressions of pain from facial expressions of emotions such as happiness and disgust.
In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.
Conclusion
(2018)
There is a paradigm shift from traditional content-based education and training to competencybased and practice-oriented training. This shift has occurred because practice-oriented teaching has been found to produce a training outcome that is industry focused, generating the relevant occupational standards. Competency-based training program often comprises of modules broken into segments called learning outcomes. These learning outcomes are based on criteria set by industry and assessment is designed to ensure students become competent in their respective areas of specialization.
Maintaining orientation in an environment with non-Earth gravity (1 g) is critical for an astronaut's operational performance. Such environments present a number of complexities for balance and motion. For example, when an astronaut tilts due to ascending or descending an inclined plane on the moon, the gravity vector will be tilted correctly, but the magnitude will be different from on earth. If this results in a mis-perceived tilt, then that may lead to postural and perceptual errors, such as mis-perceiving the orientation of oneself or the ground plane and corresponding errors in task judgment.
Motion capture, often abbreviated mocap, generally aims at recording any kind of motion -- be it from a person or an object -- and to transform it to a computer-readable format. Especially the data recorded from (professional and non-professional) human actors are typically used for analysis in e.g. medicine, sport sciences, or biomechanics for evaluation of human motion across various factors. Motion capture is also widely used in the entertainment industry: In video games and films realistic motion sequences and animations are generated through data-driven motion synthesis based on recorded motion (capture) data.
Although the amount of publicly available full-body-motion capture data is growing, the research community still lacks a comparable corpus of specialty motion data such as, e.g. prehensile movements for everyday actions. On the one hand, such data can be used to enrich (hand-over animation) full-body motion capture data - usually captured without hand motion data due to the drastic dimensional difference in articulation detail. On the other hand, it provides means to classify and analyse prehensile movements with or without respect to the concrete object manipulated and to transfer the acquired knowledge to other fields of research (e.g. from 'pure' motion analysis to robotics or biomechanics).
Therefore, the objective of this motion capture database is to provide well-documented, free motion capture data for research purposes.
The presented database GraspDB14 in sum contains over 2000 prehensile movements of ten different non-professional actors interacting with 15 different objects. Each grasp was realised five times by each actor. The motions are systematically named containing an (anonymous) identifier for each actor as well as one for the object grasped or interacted with.
The data were recorded as joint angles (and raw 8-bit sensor data) which can be transformed into positional 3D data (3D trajectories of each joint).
In this document, we provide a detailed description on the GraspDB14-database as well as on its creation (for reproducibility).
Chapter 2 gives a brief overview of motion capture techniques, freely available motion capture databases for both, full body motions and hand motions, and a short section on how such data is made useful and re-used. Chapter 3 describes the database recording process and details the recording setup and the recorded scenarios. It includes a list of objects and performed types of interaction. Chapter 4 covers used file formats, contents, and naming patterns. We provide various tools for parsing, conversion, and visualisation of the recorded motion sequences and document their usage in chapter 5.
Smallholder farmers as a backbone for the implementation of the Sustainable Development Goals
(2018)
Multidisciplinary, multicultural, and multitasking has taken center stage in the global educational debate. Globalization and improvement in communication have affected the way organisations operate and hence influenced whom they hire. Today, it is common practice to work with people from diverse backgrounds and it requires competencies that go beyond general project management. Intercultural awareness, networking in different global communities, and learning to develop specific communication strategies for different stakeholders is all part of the package of skills and competencies that are required in today's interconnected world. This has indirect implication on the nature of skills and competencies institutions/universities must equip their students with to enable them to compete successfully in the working world.
The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.
In the context of the Franco-German research project Re(h)strain, this work focuses on a global system analysis integrating both safety and security analysis of international and/or urban railway stations. The Re(h)strain project focuses on terrorist attacks on high speed train systems and investigates prevention and mitigation measures to reduce the overall vulnerability and strengthen the system resilience. One main criterion regarding public transport issues is the number of passengers. For example, the railway station of Paris “Gare du Nord” deals with a bigger number of passengers than the biggest airport in the world (SNCF open Data 2014), the Atlanta airport, but in terms of passengers, it is only around the 23rd rank railway station in the world. Due to the enormous mass of people, this leads to the system approach of breaking out the station into several classes of zones, e.g. entrance, main hall, quays, trains, etc. All classes are analysed considering state-of-the-art parameters, like targets attractiveness, feasibility of attack, possible damage, possible mitigation and defences. Then, safety incidence of security defence is discussed in order to refine security requirement with regard to the considered zone. Finally, global requirements of security defence correlated to the corresponding class of zones are proposed.
3-Hydroxy-3-methylglutaryl-coenzyme A lyase (HMGCL, HMGCL) deficiency is a rare inborn error of ketogenesis. Even if the ketogenic enzyme is fully disrupted, an elevated signal for the ketone body acetoacetic acid is a frequent observation in the analysis of urinary organic acids, at least if derivatization is performed by methylation. We provide an explanation for this phenomenon and trace it back to degradation of the derivatized 3-hydroxy-3-methylglutaric acid and high temperature of the injector of the gas chromatograph.
Amino acids perform multiple essential physiological roles in humans, and accordingly, their importance to health has been the subject of extensive attention. In this special issue of the Journal of Nutrition and Metabolism, we focus on the various inborn errors of amino acid metabolism, their diagnostic challenges, new treatment approaches, and recent advances in patient monitoring as well as clinical outcomes.
This policy brief is part of a wider research project entitled ‘Building the Economic Case for Investments in Social Protection’. The research aims at demonstrating the potential impacts of social protection on inclusive growth. The project is a collaborative effort between the Maastricht Graduate School of Governance at the University of Maastricht and United Nations University-MERIT, NL; the Global Development Institute at the University of Manchester, UK; the School of Social Science at the University of Makerere, Uganda; and the Expanding Social Protection Programme of the Ugandan Ministry of Gender, Labour and Social Development. This project is part of the research agenda of the Knowledge Platform Inclusive Development Policies and funded by the Ministry of Foreign Affairs of the Netherlands through the NWO-WOTRO programme.