Comparison of quantum mechanical and classical trajectory calculations of cross sections for ion-atom impact ionization of negative - and positive -ions for heavy ion fusion applications

Stripping cross sections in nitrogen have been calculated using the classical trajectory approximation and the Born approximation of quantum mechanics for the outer shell electrons of 3.2GeV I$^{-}$ and Cs$^{+}$ ions. A large difference in cross section, up to a factor of six, calculated in quantum mechanics and classical mechanics, has been obtained. Because at such high velocities the Born approximation is well validated, the classical trajectory approach fails to correctly predict the stripping cross sections at high energies for electron orbitals with low ionization potential.Comment: submitted to Phys. Rev.

Cisplatin-induced emesis: systematic review and meta-analysis of the ferret model and the effects of 5-HT3 receptor antagonists

PURPOSE: The ferret cisplatin emesis model has been used for ~30 years and enabled identification of clinically used anti-emetics. We provide an objective assessment of this model including efficacy of 5-HT(3) receptor antagonists to assess its translational validity. METHODS: A systematic review identified available evidence and was used to perform meta-analyses. RESULTS: Of 182 potentially relevant publications, 115 reported cisplatin-induced emesis in ferrets and 68 were included in the analysis. The majority (n = 53) used a 10 mg kg(−1) dose to induce acute emesis, which peaked after 2 h. More recent studies (n = 11) also used 5 mg kg(−1), which induced a biphasic response peaking at 12 h and 48 h. Overall, 5-HT(3) receptor antagonists reduced cisplatin (5 mg kg(−1)) emesis by 68% (45–91%) during the acute phase (day 1) and by 67% (48–86%) and 53% (38–68%, all P < 0.001), during the delayed phase (days 2, 3). In an analysis focused on the acute phase, the efficacy of ondansetron was dependent on the dosage and observation period but not on the dose of cisplatin. CONCLUSION: Our analysis enabled novel findings to be extracted from the literature including factors which may impact on the applicability of preclinical results to humans. It reveals that the efficacy of ondansetron is similar against low and high doses of cisplatin. Additionally, we showed that 5-HT(3) receptor antagonists have a similar efficacy during acute and delayed emesis, which provides a novel insight into the pharmacology of delayed emesis in the ferret

Artificial intelligence methods for security and cyber security systems

This research is in threat analysis and countermeasures employing Artificial Intelligence (AI) methods within the civilian domain, where safety and mission-critical aspects are essential. AI has challenges of repeatable determinism and decision explanation. This research proposed methods for dense and convolutional networks that provided repeatable determinism. In dense networks, the proposed alternative method had an equal performance with more structured learnt weights. The proposed method also had earlier learning and higher accuracy in the Convolutional networks. When demonstrated in colour image classification, the accuracy improved in the first epoch to 67%, from 29% in the existing scheme. Examined in transferred learning with the Fast Sign Gradient Method (FSGM) as an analytical method to control distortion of dissimilarity, a finding was that the proposed method had more significant retention of the learnt model, with 31% accuracy instead of 9%. The research also proposed a threat analysis method with set-mappings and first principle analytical steps applied to a Symbolic AI method using an algebraic expert system with virtualized neurons. The neural expert system method demonstrated the infilling of parameters by calculating beamwidths with variations in the uncertainty of the antenna type. When combined with a proposed formula extraction method, it provides the potential for machine learning of new rules as a Neuro-Symbolic AI method. The proposed method uses extra weights allocated to neuron input value ranges as activation strengths. The method simplifies the learnt representation reducing model depth, thus with less significant dropout potential. Finally, an image classification method for emitter identification is proposed with a synthetic dataset generation method and shows the accurate identification between fourteen radar emission modes with high ambiguity between them (and achieved 99.8% accuracy). That method would be a mechanism to recognize non-threat civil radars aimed at threat alert when deviations from those civilian emitters are detected

Drag Reduction by Polymers in Wall Bounded Turbulence

We address the mechanism of drag reduction by polymers in turbulent wall bounded flows. On the basis of the equations of fluid mechanics we present a quantitative derivation of the "maximum drag reduction (MDR) asymptote" which is the maximum drag reduction attained by polymers. Based on Newtonian information only we prove the existence of drag reduction, and with one experimental parameter we reach a quantitative agreement with the experimental measurements.Comment: 4 pages, 1 fig., included, PRL, submitte

Rethinking place and the social work office in the delivery of children's social work services

Limited attention has been given to the concept of place in social work research and practice. This paper draws on the national evaluation of social work practices (SWPs) in England undertaken between 2009 and 2012. SWPs were pilot organisations providing independent social work services for children in out-of-home care in five sites. One factor distinguishing some of these pilots was their attention to place. The evaluation employed a mixed methods approach and we use data from interviews with 121 children and young people in out-of-home care, 19 birth parents and 31 interviews with SWP staff which explored their views and experiences of the SWP offices. Children and young people were alert to the stigma which could attach to social work premises and appreciated offices which were planned and furnished to appear less institutional and more ‘normal’. Daily interactions with staff which conveyed a sense of recognition and value to service users also contributed to a view of some SWP offices as accessible and welcoming places. Both children and parents appreciated offices that provided fun activities that positioned them as active rather than passive. Staff valued opportunities for influencing planning decisions about offices and place was seen to confer a value on them as well as on service users. However, not all the SWPs were able to achieve these aspects of place, and engaging children and families in place was less likely when the service user population was widely dispersed. Recognising the importance of place and how place is constructed through relationships between people as well as through the physical environment appeared to be key to creating offices that combated the stigma attached to out-of-home care. Those leading and managing children’s services should explore ways of involving local communities in planning social work offices and turn attention to making these offices accessible, welcoming, places

Gaussian process for interpreting pulsed eddy current signals for ferromagnetic pipe profiling

© 2014 IEEE. This paper describes a Gaussian Process based machine learning technique to estimate the remaining volume of cast iron in ageing water pipes. The method utilizes time domain signals produced by a commercially available pulsed Eddy current sensor. Data produced by the sensor are used to train a Gaussian Process model and perform inference of the remaining metal volume. The Gaussian Process model was learned using sensor data obtained from cast iron calibration plates of various thicknesses. Results produced by the Gaussian Process model were validated against the remaining wall thickness acquired using a high resolution laser scanner after the pipes were sandblasted to remove corrosion. The evaluation shows agreement between model outputs and ground truth. The paper concludes by discussing the implications or results and how the proposed method can potentially advance the current technological setup by facilitating real time pipe profiling

Interdisciplinary Psychology and Law Training in Family and Child Mediation: An Empirical Study of the Effects on Law Student Mediators

There is growing interest in interdisciplinary training programs for law students. The goal of these programs is to prepare law students for the real world interdisciplinary settings they will face in their careers. However, there exists little research to provide evidence of the utility of such training. This study examined the effectiveness of an interdisciplinary psychology and law training program on law students using a multi-method approach (i.e., knowledge tests and focus group discussion). Findings suggest that interdisciplinary training of law students increased law students’ knowledge of law and psychology, was enjoyed by law students, and had a beneficial impact on law students’ educational experience