Field ionization electrodes Patent

Electrodes having array of small surfaces for field ionizatio

Positron Emission Tomography Score Has Greater Prognostic Significance Than Pretreatment Risk Stratification in Early-Stage Hodgkin Lymphoma in the UK RAPID Study.

PURPOSE: Accurate stratification of patients is an important goal in Hodgkin lymphoma (HL), but the role of pretreatment clinical risk stratification in the context of positron emission tomography (PET) -adapted treatment is unclear. We performed a subsidiary analysis of the RAPID trial to assess the prognostic value of pretreatment risk factors and PET score in determining outcomes. PATIENTS AND METHODS: Patients with stage IA to IIA HL and no mediastinal bulk underwent PET assessment after three cycles of doxorubicin, bleomycin, vinblastine, and dacarbazine; 143 PET-positive patients (PET score, 3 to 5) received a fourth doxorubicin, bleomycin, vinblastine, and dacarbazine cycle and involved-field radiotherapy, and 419 patients in complete metabolic remission were randomly assigned to receive involved-field radiotherapy (n = 208) or no additional treatment (n = 211). Cox regression was used to investigate the association between PET score and pretreatment risk factors with HL-specific event-free survival (EFS). RESULTS: High PET score was associated with inferior EFS, before (P .4). CONCLUSION: In RAPID, a positive PET scan did not carry uniform prognostic weight; only a PET score of 5 was associated with inferior outcomes. This suggests that in future trials involving patients without B symptoms or mediastinal bulk, a score of 5 rather than a positive PET result should be used to guide treatment escalation in early-stage HL

Credimus

We believe that economic design and computational complexity---while already important to each other---should become even more important to each other with each passing year. But for that to happen, experts in on the one hand such areas as social choice, economics, and political science and on the other hand computational complexity will have to better understand each other's worldviews. This article, written by two complexity theorists who also work in computational social choice theory, focuses on one direction of that process by presenting a brief overview of how most computational complexity theorists view the world. Although our immediate motivation is to make the lens through which complexity theorists see the world be better understood by those in the social sciences, we also feel that even within computer science it is very important for nontheoreticians to understand how theoreticians think, just as it is equally important within computer science for theoreticians to understand how nontheoreticians think

Randomisation and Derandomisation in Descriptive Complexity Theory

We study probabilistic complexity classes and questions of derandomisation from a logical point of view. For each logic L we introduce a new logic BPL, bounded error probabilistic L, which is defined from L in a similar way as the complexity class BPP, bounded error probabilistic polynomial time, is defined from PTIME. Our main focus lies on questions of derandomisation, and we prove that there is a query which is definable in BPFO, the probabilistic version of first-order logic, but not in Cinf, finite variable infinitary logic with counting. This implies that many of the standard logics of finite model theory, like transitive closure logic and fixed-point logic, both with and without counting, cannot be derandomised. Similarly, we present a query on ordered structures which is definable in BPFO but not in monadic second-order logic, and a query on additive structures which is definable in BPFO but not in FO. The latter of these queries shows that certain uniform variants of AC0 (bounded-depth polynomial sized circuits) cannot be derandomised. These results are in contrast to the general belief that most standard complexity classes can be derandomised. Finally, we note that BPIFP+C, the probabilistic version of fixed-point logic with counting, captures the complexity class BPP, even on unordered structures

On Second-Order Monadic Monoidal and Groupoidal Quantifiers

We study logics defined in terms of second-order monadic monoidal and groupoidal quantifiers. These are generalized quantifiers defined by monoid and groupoid word-problems, equivalently, by regular and context-free languages. We give a computational classification of the expressive power of these logics over strings with varying built-in predicates. In particular, we show that ATIME(n) can be logically characterized in terms of second-order monadic monoidal quantifiers

Investigation of initiation of gigantic jets connecting thunderclouds to the ionosphere

The initiation of giant electrical discharges called as "gigantic jets" connecting thunderclouds to the ionosphere is investigated by numerical simulation method in this paper. Using similarity relations, the triggering conditions of streamer formation in laboratory situations are extended to form a criterion of initiation of gigantic jets. The energy source causing a gigantic jet is considered due to the quasi-electrostatic field generated by thunderclouds. The electron dynamics from ionization threshold to streamer initiation are simulated by the Monte Carlo technique. It is found that gigantic jets are initiated at a height of ~18-24 km. This is in agreement with the observations. The method presented in this paper could be also applied to the analysis of the initiation of other discharges such as blue jets and red sprites.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL

What's in a grade? The multidimensional nature of what teacher-assigned grades assess in high school

Historically, teacher-assigned grades have been seen as unreliable subjective measures of academic knowledge, since grades and standardized tests have traditionally correlated at about the 0.5 to 0.6 level, and thus explain about 25–35% of each other. However, emerging literature indicates that grades may be a multidimensional assessment of both student academic knowledge and a student's ability to negotiate the social processes of schooling, such as behavior, participation, and effort. This study analyzed the high school transcript component of the Education Longitudinal Study of 2002 (ELS:2002) using multidimensional scaling (MDS) to describe the relationships between core subject grades, non-core subject grades, and standardized test scores in mathematics and reading. The results indicate that when accounting for the academic knowledge component assessed through standardized tests, teacher-assigned grades may be a useful assessment of a student's ability at the non-cognitive aspects of school. Implications for practice, research, and policy are discussed

Human astrocytes and microglia show augmented ingestion of synapses in Alzheimer's disease via MFG-E8

Synapse loss correlates with cognitive decline in Alzheimer's disease (AD). Data from mouse models suggests microglia are important for synapse degeneration, but direct human evidence for any glial involvement in synapse removal in human AD remains to be established. Here we observe astrocytes and microglia from human brains contain greater amounts of synaptic protein in AD compared with non-disease controls, and that proximity to amyloid-β plaques and the APOE4 risk gene exacerbate this effect. In culture, mouse and human astrocytes and primary mouse and human microglia phagocytose AD patient-derived synapses more than synapses from controls. Inhibiting interactions of MFG-E8 rescues the elevated engulfment of AD synapses by astrocytes and microglia without affecting control synapse uptake. Thus, AD promotes increased synapse ingestion by human glial cells at least in part via an MFG-E8 opsonophagocytic mechanism with potential for targeted therapeutic manipulation.</p

Forced Moves or Good Tricks in Design Space? Landmarks in the Evolution of Neural Mechanisms for Action Selection

This review considers some important landmarks in animal evolution, asking to what extent specialized action-selection mechanisms play a role in the functional architecture of different nervous system plans, and looking for “forced moves” or “good tricks” (see Dennett, D., 1995, Darwin’s Dangerous Idea, Penguin Books, London) that could possibly transfer to the design of robot control systems. A key conclusion is that while cnidarians (e.g. jellyfish) appear to have discovered some good tricks for the design of behavior-based control systems—largely lacking specialized selection mechanisms—the emergence of bilaterians may have forced the evolution of a central ganglion, or “archaic brain”, whose main function is to resolve conflicts between peripheral systems. Whilst vertebrates have many interesting selection substrates it is likely that here too the evolution of centralized structures such as the medial reticular formation and the basal ganglia may have been a forced move because of the need to limit connection costs as brains increased in size