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The non-intrusive screening of shipping containers at national borders serves as a prominent and vital component in deterring and detecting the illicit transportation of radioactive and/or nuclear materials which could be used for malicious and highly damaging purposes. Screening systems for this purpose must be designed to efficiently detect and identify material that could be used to fabricate radiological dispersal or improvised nuclear explosive devices, while having minimal impact on the flow of cargo and also being affordable for widespread implementation. As part of current screening systems, shipping containers, offloaded from increasingly large cargo ships, are driven through radiation portal monitors comprising plastic scintillators for gamma detection and separate, typically 3He-based, neutron detectors. Such polyvinyl-toluene plastic-based scintillators enable screening systems to meet detection sensitivity standards owing to their economical manufacturing in large sizes, producing high-geometric-efficiency detectors. However, their poor energy resolution fundamentally limits the screening system to making binary “source” or “no source” decisions. To surpass the current capabilities, future generations of shipping container screening systems should be capable of rapid radionuclide identification, activity estimation and source localisation, without inhibiting container transportation. This review considers the physical properties of screening systems (including detector materials, sizes and positions) as well as the data collection and processing algorithms they employ to identify illicit radioactive or nuclear materials. The future aim is to surpass the current capabilities by developing advanced screening systems capable of characterising radioactive or nuclear materials that may be concealed within shipping containers.

Background: Step-downs are scheduled reductions in the rate of compensation paid to injured workers. Their primary purpose is to encourage return to work. Despite being widespread in Australia, we know of no evidence that they influence time spent off work. Using claims data from each Australian workers' compensation jurisdiction, we will examine whether step-downs affect the rate at which injured workers leave the compensation system. Methods: 1) Regression discontinuity Using the National Dataset for Compensation-based statistics, we will convert record-level claims data into benefit cessation rates, documenting the proportion of workers' compensation claims that remain in the system each day. Using a regression discontinuity (RD) design, we will test whether step-downs increased the benefit cessation rate within each jurisdiction. Analyses will be limited to claims lodged between July 2008 and June 2015 (allowing a minimum of two years of follow up; the data were last updated to June 2017). Where jurisdictions have changed either the step-down rate or initial rate of compensation, we will only include claims lodged after the latest implementation date to ensure consistency in exposure. We will also analyse Western Australia, which currently has no step-downs as a control. Claims with two weeks or fewer of compensated time loss will be excluded to account for employer excess in Victoria and South Australia, as will claims affected by the maximum wage replacement cap, which mitigate or preclude step-down effects. We will also conduct sensitivity analyses with a one-week delay as workers may not be aware of impending step-downs and only respond after receiving reduced compensation. RD analyses will be conducted in R using the rdd package. The package calculates optimal RD bandwidths (BW) using the Imbens-Kalyanaraman calculation, in addition to sensitivity analyses using half- and double-sized BWs. We have attached a proof of concept plot, based on analysis of the 13 week step-down in Victoria. We found no evidence of an effect: local average treatment effects (LATE): 0.44, p = .168 (half-BW: -0.20, p = .307; double-BW: 0.75, p = .173). 2) Meta-analyses We will conduct a meta-analysis of each RD model to derive a pooled effect estimate and determine the proportion of variance attributable to heterogeneity. If we find significant heterogeneity, we will look at several factors to determine those that affect step-down effects. We have identified the following possible factors to consider: timing of step-down, the magnitude of reduction (difference between pre- and post-step-down rate), and the pre step-down wage replacement rate. Meta-analyses will be conducted in R using the metafor package.

This Ph.D. dissertation examines the extent to which the personal characteristics of political leaders affect their political ambition and government formation processes. While the literature shows that government performance and issue preferences depend, to some extent, on leaders’ characteristics, such characteristics have received little scholarly attention in the context of government formation. The dissertation’s main argument is that leaders’ characteristics, especially gender, influence the creation of their preferences and attitudes during negotiations to obtain positions of power. Three empirical chapters test this using the case of Spanish local level politics. In the first chapter, I devise an original conjoint experiment and show that gender plays a role in predicting politicians preferences. They prefer women as government partners because they are perceived as reducers of the cost of communication and as more competent. In the second chapter, I leverage the as-if random assignment of a bargaining advantage in close local elections through a Regression Discontinuity Design. The results show that women are less likely to secure the mayoralty than men when they win elections by narrow margins, although their parties still manage to join governing coalitions. In the third chapter, to explore the mechanisms underlying of the other chapters’ results, I explore the attitudes and political ambitions of those who reach those top positions. This project proposes a new way of understanding government negotiations. Moreover, the results highlight the inequalities that certain social groups, such as women, face when attempting to occupy positions of leadership. Aquesta tesi doctoral estudia fins a quin punt les característiques personals dels líders polítics afecten la seva ambició política i els processos de formació de govern. Tot i que la literatura mostra que el rendiment del govern i les preferències depenen, fins a un cert punt, de les característiques dels líders, la formació dels governs és un aspecte que ha despertat menys interès acadèmic. L’argument principal de la tesi és que les característiques dels líders, especialment el gènere, influeixen en la creació de les seves preferències i actituds durant les negociacions per obtenir posicions de poder. Tres capítols empírics, els quals utilitzen el cas de la política local espanyola, ho avalen. En el primer capítol, elaboro un experiment conjoint original i demostro que el gènere juga un paper en predir les preferències dels polítics. Els líders prefereixen les dones com a sòcies de govern perquè se les percep com a facilitadores de la comunicació i són més competents. En el segon capítol, es posa el focus en l’assignació quasi aleatòria de tenir avantatge negociadora en eleccions locals mitjançant un disseny de regressió discontínua. La tesi mostra que les dones tenen menys probabilitats d’aconseguir l’alcaldia que els homes quan el resultat és ajustat, és a dir, guanyen les eleccions per marges estrets. Tanmateix, els seus partits aconsegueixen unir-se a coalicions de govern. En el tercer capítol, per explorar els mecanismes subjacents dels altres capítols, exploro les actituds i les ambicions polítiques d’aquells polítics que assoleixen posicions de poder superiors. Amb tot, la tesi doctoral proposa una nova manera d’entendre les negociacions governamentals. A més, els resultats posen de manifest les desigualtats a què s’enfronten determinats col·lectius socials, com les dones, a l’hora de formar part de càrrecs polítics de primera línia.

Rosai-Dorfman disease (RDD) is a rare, benign, non-Langerhans cells histiocytosis with massive lymphadenopathy of uncertain aetiology. It is commonly characterized by massive, painless, non-tender, bilateral cervical lymphadenopathy. Extra-nodal involvement is usually seen in 50% of patients, with the brain being affected in only 5% of cases, usually as dural-based lesions. Clinical presentation is heterogeneous and strongly dependent on the localization of the lesions. Although the histopathological findings are essential for the final diagnosis, brain magnetic resonance imaging (MRI) currently represents the first-line strategy for the detection of the lesions across the central nervous system (CNS); moreover, it may provide additional elements for the differential diagnosis versus other more common lesions. We performed a case-based literature review to highlight possible aetiologic and pathogenetic theories of this disease, along with imaging features of RDD, with a particular focus on the MRI characteristics of the CNS involvement (CNS-RDD). Finally, we provided a novel insight on the current therapeutic approaches, either surgical or medical.

International audience; For most software projects, the bug tracker is an essential tool. In open source development, this tool plays an even more central role as it is generally open to all users, who are encouraged to test the software and report bugs. Previous studies have highlighted the act of reporting a bug as a first step leading a user to become an active contributor.The impact of the bug reporting environment on the bug tracking activity is difficult to assess because of the lack of comparison points. In this paper, we take advantage of the switch, from Bugzilla to GitHub, of the bug tracker of Coq, a medium-sized open source project, to evaluate and interpret the impact that such a change can have.We first report on the switch itself, including the migration of preexisting issues. Then we analyze data from before and after the switch using a regression discontinuity design, an econometric methodology imported from quantitative policy analysis. We complete this quantitative analysis with qualitative data from interviews with developers.We show that the switch induces an increase in bug reporting, particularly from principal developers themselves, and more generally an increased engagement with the bug tracking platform, with more comments by developers and also more external commentators.

Frequent Itemset Mining is an important data mining task in real-world applications. Distributed parallel Apriori and FP-Growth algorithm is the most important algorithm that works on data mining for finding the frequent itemsets. Originally, Map-Reduce mining algorithm-based frequent itemsets on Hadoop were resolved. For handling the big data, Hadoop comes into the picture but the implementation of Hadoop does not reach the expectations for the parallel algorithm of distributed data mining because of its high I/O results in the transactional disk. According to research, Spark has an in-memory computation technique that gives faster results than Hadoop. It was mainly acceptable for parallel algorithms for handling the data. The algorithm working on multiple datasets for finding the frequent itemset to get accurate results for computation time. In this paper, we propose on parallel apriori and FP-growth algorithm to finding the frequent itemset on multiple datasets to get the mining itemsets using the Apache SPARK framework. Our experiment results depend on the support value to get accurate results.

The literature has documented a one-off drop in consumption at retirement in Italy. We show that respondents’ subjective evaluation of the minimum amount of money needed “to live comfortably but not in luxury” drops at retirement as well. This finding supports the idea that, even if expenditure falls at retirement, this may have the same effect on money needed, hence no effect on the marginal utility of consumption.

Traditional electron-transfer dissociation (ETD) experiments operate through a complex combination of hydrogen abundant and hydrogen deficient fragmentation pathways, yielding c and z ions, side-chain losses, and disulfide bond scission. Herein, a novel dissociation pathway is reported, yielding homolytic cleavage of carbon-iodine bonds via electronic excitation. This observation is very similar to photodissociation experiments where homolytic cleavage of carbon-iodine bonds has been utilized previously, but ETD activation can be performed without addition of a laser to the mass spectrometer. Both loss of iodine and loss of hydrogen iodide are observed, with the abundance of the latter product being greatly enhanced for some peptides after additional collisional activation. These observations suggest a novel ETD fragmentation pathway involving temporary storage of the electron in a charge-reduced arginine side chain. Subsequent collisional activation of the peptide radical produced by loss of HI yields spectra dominated by radical-directed dissociation, which can be usefully employed for identification of peptide isomers, including epimers. Graphical Abstract ᅟ.

Policymakers are concerned about potential underinvestment in lifelong learning. In this paper we study to what extent a tax deduction helps to stimulate post-initial training. Specifically, we employ a regression kink and regression discontinuity design as jumps in tax bracket rates generate exogenous variation in the effective costs of lifelong learning. Using high quality data on tax returns of the universe of Dutch taxpayers, we find that the tax deduction has heterogeneous effects on lifelong learning. Low-income singles show no response. For high-income singles we find an effect of 10% on the probability to use the tax deduction. Furthermore, ignoring shifting of expenses between partners leads to spurious large estimates for primary earners and spurious negative estimates for secondary earners.

Background 50% to 60% of the people who have recovered from the first episode of depression experience a relapse. The immune system of the people suffering from depression is in a permanent state of pathological pro-inflammatory readiness. There are some reports that depressive episodes cause sensitization of immune-inflammatory pathways and that staing of depression (e.g. number of depressive episodes) is correlated with immune-inflammatory markers. The main objective of the study was to delineate whether recurrent major depression (rDD) is characterized by alterations in selected immune-inflammatory biomarkers as compared with first episode of depression (ED-I), i.e. expression of mRNA and enzymatic activity of manganese superoxide dismutase (MnSOD, SOD-2), myeloperoxidase (MPO), inducible nitric oxide synthase (iNOS, NOS-2), and cyclooxygenase-2 (COX-2). Methods The study was carried out in a group of 131 patients: ED-I group – 42 patients, rDD group – 89 patients. Depression severity was assessed with the 17-item Hamilton Depression Rating Scale (HDRS). The number of depression episodes and the disease duration periods were recorded in each patient. For the patients, HDRS was administered at admission during the symptomatic phase, which would generally be either before or shortly after modification of the previous antidepressant drug regimen. Reassessment of the mental condition was conducted after 8 weeks of the pharmacological treatment also with the use of the HDRS scale. Results No significant statistical differences were found between the analysed groups as regards the intensity of depressive disorders. No differences in the expression of MnSOD, MPO, COX-2 and i-NOS genes on the level of both mRNA and protein were observed between both groups. No significant interrelation was noticed between the number of depression episodes experienced and the expression of selected genes on the mRNA level and protein level. Conclusions There is no significant difference in MnSOD, MPO, COX-2 and i-NOS between patients with recurrent depressive disorders and those in a first episode of depression. These findings suggest that these enzymes are trait markers of depression and are not related to staging of depression.

It is known that the largest developmental changes in the hippocampus take place during the prenatal period and during the first two years of postnatal life. Few studies have been conducted to address the normal developmental trajectory of the hippocampus during childhood. In this study shape analysis was applied to study the normal developing hippocampus in a group of 103 typically developing 6- to 10-year-old preadolescent children. The individual brain was normalized to a template, and then the hippocampus was manually segmented and further divided into the head, body, and tail sub-regions. Three different methods were applied for hippocampal shape analysis: radial distance mapping, surface-based template registration using the robust point matching (RPM) algorithm, and volume-based template registration using the Demons algorithm. All three methods show that the older children have bilateral expanded head segments compared to the younger children. The results analyzed based on radial distance to the centerline were consistent with those analyzed using template-based registration methods. In analyses stratified by sex, it was found that the age-associated anatomical changes were similar in boys and girls, but the age-association was strongest in girls. Total hippocampal volume and sub-regional volumes analyzed using manual segmentation did not show a significant age-association. Our results suggest that shape analysis is sensitive to detect sub-regional differences that are not revealed in volumetric analysis. The three methods presented in this study may be applied in future studies to investigate the normal developmental trajectory of the hippocampus in children. They may be further applied to detect early deviations from the normal developmental trajectory in young children for evaluating susceptibility for psychopathological disorders involving hippocampus. © 2013 ISDN.

The Internet Protocol Multimedia Subsystem (IMS) has been recognized as a common signaling architecture for providing next generation multimedia services. In order to enhance perceived service quality regardless of access network and device, IMS supports Quality of Service (QoS) negotiation and signaling. The IMS procedures used for that purpose are based on Session Initiation Protocol (SIP). Therefore, signaling performance of SIP plays an important role in affecting the overall Quality of Experience (QoE) in next generation networks. Although many standards to evaluate the performance of telephony signaling protocols have been proposed, none of the metrics address SIP. Recent research in this field has resulted in the definitions of a standard set of metrics for measuring the performance of end-to-end SIP for basic telephony service. This paper aims to provide an insight in the process of measuring and evaluating SIP performance metrics as defined in Internet Engineering Task Force (IETF) Request for Comments (RFC) 6076. The open source IMS platform is used as the test environment for the purpose of examining SIP performance metrics under different conditions. Presented results show the impact of SIP signaling performance on QoE for IMS-based telephony service.

TESATEX was developed to evaluate the source term generated by an open-air explosion with or without obstacles. It lies on deeply modified SARRIM and HOTSPOT models. TESATEX can take account of the wind field influenced by buildings. It was operated with Micro-SPRAY but could be run with any other dispersion model. Experimental validation of TESATEX and Micro-SPRAY was successfully carried out using ‘Double Tracks’ in-field test measurements. Applications of TESATEX – Micro- SWIFT-SPRAY modelling system are shown in the paper. Explosions of Radiological Dispersal Devices (RDD) or ‘dirty bombs’ have been simulated in Oklahoma City (downtown) and Paris (Concorde square district). The radiological pollutants dispersion is strongly influenced by the streets network and the initial cloud configuration. Dispersion results have been post-processed to assess the radiological impact of the considered hypothetical events.