Evaluating traffic informers: Testing the behavioral and social-cognitive effects of an adolescent bicycle safety education program

AbstractIn The Netherlands, 12–24 years old are over-represented in the total number of traffic fatalities and injuries. In this study, the traffic informer program – designed to promote safe traffic behavior in the pre-driver population – was experimentally evaluated, with a specific focus on bicycle use. Students were subjected to graphic videos of traffic accidents and listened to a first-person narrative provided by a traffic accident victim. The influence of the program on concepts derived from the theory of planned behavior and protection motivation theory (attitudes, norms, self-efficacy, risk-perception, intention and behavior) was assessed. Students from various schools (N=1593;M age=15 years, SD=.84) participated in a quasi-experimental study, either in an experimental or a control group, completing self-report questionnaires one week prior to the program implementation and approximately one month after the program implementation. Mixed regression analyses showed significant positive and negative time×intervention interaction effects on attitude toward traffic violations, relative attitude toward traffic safety, and risk comparison, but not on intention and behavior. More research is needed to find effective behavioral change techniques (other than increasing risk awareness) for promoting safe traffic behavior in adolescents. Research is also needed to address how these can be translated into effective interventions and educational programs

Function Prediction

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. There are still huge gaps in understanding the molecular function of proteins. This raises the question on how we may predict protein function, when little to no knowledge from direct experiments is available. Protein function is a broad concept which spans different scales: from quantum scale effects for catalyzing enzymatic reactions, to phenotypes that manifest at the organism level. In fact, many of these functional scales are entirely different research areas. Here, we will consider prediction of a smaller range of functions, roughly spanning the protein residue-level up to the pathway level. We will give a conceptual overview of which functional aspects of proteins we can predict, which methods are currently available, and how well they work in practice.Comment: editorial responsability: K. Anton Feenstra, Sanne Abeln. This chapter is part of the book "Introduction to Protein Structural Bioinformatics". The Preface arXiv:1801.09442 contains links to all the (published) chapters. The update adds available arxiv hyperlinks for the chapter

Function Prediction

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. There are still huge gaps in understanding the molecular function of proteins. This raises the question on how we may predict protein function, when little to no knowledge from direct experiments is available. Protein function is a broad concept which spans different scales: from quantum scale effects for catalyzing enzymatic reactions, to phenotypes that manifest at the organism level. In fact, many of these functional scales are entirely different research areas. Here, we will consider prediction of a smaller range of functions, roughly spanning the protein residue-level up to the pathway level. We will give a conceptual overview of which functional aspects of proteins we can predict, which methods are currently available, and how well they work in practice

Strain in InP/ZnSe, S core/shell quantum dots from lattice mismatch and shell thickness : material stiffness influence

We investigate the buildup of strain in InP quantum dots with the addition of shells of the lower-lattice constant materials ZnSe and ZnS by Raman spectroscopy. Both materials induce compressive strain in the core, which increases with increasing shell volume. We observe a difference in the shell behavior between the two materials: the thickness-dependence points toward an influence of the material stiffness. ZnS has a larger Young's modulus and requires less material to develop stress on the InP lattice at the interface, while ZnSe requires several layers to form a stress-inducing lattice at the interface. This hints at the material stiffness being an additional parameter of relevance for designing strained core/shell quantum dots

Gate-Controlled Ionization and Screening of Cobalt Adatoms on a Graphene Surface

We describe scanning tunneling spectroscopy (STS) measurements performed on individual cobalt (Co) atoms deposited onto backgated graphene devices. We find that Co adatoms on graphene can be ionized by either the application of a global backgate voltage or by the application of a local electric field from a scanning tunneling microscope (STM) tip. Large screening clouds are observed to form around Co adatoms ionized in this way, and we observe that some intrinsic graphene defects display a similar behavior. Our results provide new insight into charged impurity scattering in graphene, as well as the possibility of using graphene devices as chemical sensors.Comment: 19 pages, 4 figure

Comparison of speech intelligibility in quiet and in noise after hearing aid fitting according to a purely prescriptive and a comparative fitting procedure

We compared two different types of hearing-aid fitting procedures in a double-blind randomized clinical study. Hearing aid fittings based on a purely prescriptive procedure (the NAL-RP formula) were compared to a comparative fitting procedure based on optimizing speech intelligibility scores. Main outcome measures were improvement of speech intelligibility scores in quiet and in noise. Data were related to the real-ear insertion responses that were measured after fitting. For analysis purposes subgroups were composed according to degree of hearing loss, characterized by unaided speech intelligibility in quiet, previous experience with hearing aids, unilateral or bilateral fittings and type of hearing aid. We found equal improvement of speech intelligibility in quiet, while fitting according to the prescriptive formula resulted in a somewhat better performance as expressed by the speech-to-noise ratio in comparison to the comparative procedure. Both procedures resulted in comparable real-ear insertion responses

Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index

A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex-and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value &lt;5 x 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 x 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index.</p