Performance Problems and Structural Retrofit Analysis of Existing BCTs

Automobile accident reports and full-scale crash tests of existing breakaway cable terminals (BCTs) indicated their poor performance during end-on impacts. This paper presents results of a feasibility study, which was conducted to identify problems with existing BCTs. The nonlinear, explicit, dynamic finite-element code LS-DYNA was used in the investigation of BCT design problems. Several problems were identified in the past during the full-scale crash tests. These problems became clearly visible when computational mechanics analyses were used. In addition to severe vehicle damage, vehicular impact induced dangerous, large deceleration peaks and uncontrolled vehicle trajectories. Analysis of actual crash tests and LS-DYNA data led to the conclusion that the terminal is too stiff along its longitudinal direction and fails to smoothly control dissipation of the vehicle kinetic energy. Therefore, the major objective of the research was to soften the existing system by weakening the rail in strategically located areas. The paper describes the design retrofit process, which was continuously guided by computational mechanics analyses. Specific retrofit recommendations emerged at the end of this process and they are described in the paper. Full-scale crash tests are recommended to confirm expected benefits of the proposed retrofit.     

Dopant profiling of focused ion beam milled semiconductors using off-axis electron holography; reducing artifacts,extending detection limits and reducing the effects of gallium implantation

Focused ion beam (FIB) milling is one of the few specimen preparation techniques that can be used to prepare parallel-sided specimens with nm-scale site specificity for examination using off-axis electron holography in the transmission electron microscope (TEM). However, FIB milling results in the implantation of Ga, the formation of amorphous surface layers and the introduction of defects deep into the specimens. Here we show that these effects can be reduced by lowering the operating voltage of the FIB and by annealing the specimens at low temperature. We also show that the electrically inactive thickness is dependent on both the operating voltage and type of ion used during FIB milling.     

Metallic nanobowls by galvanic replacement reaction on heterodimeric nanoparticles

Well-defined metallic nanobowls can be prepared by extending the concept of a protecting group to colloidal synthesis. Magnetic nanoparticles are employed as "protecting groups" during the galvanic replacement of silver with gold. The replacement reaction is accompanied by spontantous dissociation of the protecting groups, leaving behind metallic nanobowls.     

Transition metal ion capture using functional mesoporous carbon made with 1,10-phenanthroline

Functional mesoporous carbon has been built using 1,10-phenanthroline as the fundamental building block, resulting in a nanoporous, high surface area sorbent capable of selectively binding transition metal ions. This material had a specific surface area of 870 m²/g, an average pore size of about 30 Å, and contained as much as 8.2 wt% N. Under acidic conditions, where the 1,10-phenanthroline ligand is protonated, this material was found to be an effective anion exchange material for transition metal anions like ${\text{PdCl}}_4^{2-}$ and ${\text{H}}_2{\text{VO}}_4^{1-}$. 1,10-Phenanthroline functionalized mesoporous carbon (“Phen-FMC”) was found to have a high affinity for Cu(II), even down to a pH of 1. At pHs above 5, Phen-FMC was found to bind a variety of transition metal cations (e.g. Co(II), Ni(II), Zn(II), etc.) from filtered ground water, river water and seawater. Phen-FMC displayed rapid sorption kinetics with Co(II) in filtered river water, reaching equilibrium in less than an hour, and easily lowering the [Co(II)] to sub-ppb levels. Phen-FMC was found to be more effective for transition metal ion capture than ion-exchange resin or activated carbon.     

Performance Evaluation of Existing Bridge Fenders for Ship Impact

Bridge fender systems are used to guide vessels through navigational channels under bridges. They appear to be an attractive and inexpensive solution for protecting the integrity of bridge piers. However, until now the fenders have not been designed to withstand any specific lateral design force. Thus, their existing impact capacity is unknown. The paper presents results of the research project funded by the Florida Department of Transportation aimed at evaluating the crashworthiness of the system and developing possible retrofit recommendations. The research efforts concentrated on computational analysis of a Jumbo Hopper barge impacting a commonly constructed fender. LS-DYNA, a nonlinear explicit dynamic finite-element code, was used for analysis. Various initial velocities and impact angles were used to represent possible collision conditions. Computational analyses were adopted to assess the crashworthiness performance of the constructed fender system and to identify its weakest components for possible retrofit. It appears that such retrofits could further improve the energy absorbing capabilities of existing bridge fenders.     

The restricted influence of sparseness of coding on the capacity of familiarity discrimination networks

Much evidence indicates that the perirhinal cortex is involved in the familiarity discrimination aspect of recognition memory. It has been previously shown under selective conditions that neural networks performing familiarity discrimination can achieve very high storage capacity, being able to deal with many times more stimuli than associative memory networks can in associative recall. The capacity of associative memories for recall has been shown to be highly dependent on the sparseness of coding. However, previous work on the networks of Bogacz et al, Norman and O'Reilly and Sohal and Hasselmo that model familiarity discrimination in the perirhinal cortex has not investigated the effects of the sparseness of encoding on capacity. This paper explores how sparseness of coding influences the capacity of each of these published models and establishes that sparse coding influences the capacity of the different models in different ways. The capacity of the Bogacz et al model can be made independent of the sparseness of coding. Capacity increases as coding becomes sparser for a simplified version of the neocortical part of the Norman and O'Reilly model, whereas capacity decreases as coding becomes sparser for a simplified version of the Sohal and Hasselmo model. Thus in general, and in contrast to associative memory networks, sparse encoding results in little or no advantage for the capacity of familiarity discrimination networks. Hence it may be less important for coding to be sparse in the perirhinal cortex than it is in the hippocampus. Additionally, it is established that the capacities of the networks are strongly dependent on the precise form of the learning rules (synaptic plasticity) used in the network. This finding indicates that the precise characteristics of synaptic plastic changes in the real brain are likely to have major influences on storage capacity.     

Real-time guidewire simulation in complex vascular models

The base of all training in interventional radiology aims at the development of the core skills in manipulating the instruments. Computer simulators are emerging to help in this task. This paper extends our previous framework with more realistic instrument behaviour and more complex vascular models. The instrument is modelled as a hybrid mass–spring particle system while the vasculature is a triangulated surface mesh segmented from patient data sets. A specially designed commercial haptic device allows the trainee to use real instruments to guide the simulation through the vasculature selected from a database of 23 different patients. A new collision detection algorithm allows an efficient computation of the contacts, therefore leaving more time to deal with the collision response for a realistic simulation in real time. The behaviour of our simulated instruments has been visually compared with the real ones and assessed by experienced interventional radiologists. Preliminary results show close correlations and a realistic behaviour.

Cytochrome c Catalyzes the Hydrogen Peroxide‐Assisted Oxidative Desulfuration of 2‐Thiouridines in Transfer RNAs

The 5‐substituted 2‐thiouridines (R5S2Us) present in the first (wobble) position of the anticodon of transfer RNAs (tRNAs) contribute to accuracy in reading mRNA codons and tuning protein synthesis. Previously, we showed that, under oxidative stress conditions in vitro, R5S2Us were sensitive to hydrogen peroxide (H₂O₂) and that their oxidative desulfuration produced 5‐substituted uridines (R5Us) and 4‐pyrimidinone nucleosides (R5H2Us) at a ratio that depended on the pH and an R5 substituent. Here, we demonstrate that the desulfuration of 2‐thiouridines, either alone or within an RNA/tRNA chain, is catalyzed by cytochrome c (cyt c). Its kinetics are similar to those of Fenton‐type catalytic 2‐thiouridine (S2U) desulfuration. Cyt c/H₂O₂‐ and Fe^II‐mediated reactions deliver predominantly 4‐pyrimidinone nucleoside (H2U)‐type products. The pathway of the cyt c/H₂O₂‐peroxidase‐mediated S2U→H2U transformation through uridine sulfenic (U‐SOH), sulfinic (U‐SO₂H), and sulfonic (U‐SO₃H) intermediates is confirmed by LC–MS. The cyt c/H₂O₂‐mediated oxidative damage of S2U‐tRNA may have biological relevance through alteration of the cellular functions of transfer RNA.     

Tuning and implementation variants of discrete-time ADRC

Practical implementations of active disturbance rejection control (ADRC) will almost always take place in discretized form. Since applications may have quite different needs regarding their discrete-time controllers, this article summarizes and extends the available set of ADRC implementations to provide a suitable variant for as many as possible use cases. In doing so, the gap between quasi-continuous and discrete-time controller tuning is closed for applications with low sampling frequencies. The main contribution of this article is the derivation of three different discrete-time implementations of error-based ADRC. It is shown that these are almost one-to-one counterparts of existing output-based implementations, to the point where transfer functions and coefficients can be reused in unaltered form. In this way, error-based implementations become firmly rooted in the established landscape of discrete-time ADRC. Furthermore, it becomes possible to equip error-based variants with windup protection abilities known from output-based ADRC.