Miracle-dz/UniFAR-FTUs huggingface dataset:
A Pooled Analysis of Thyroid Cancer Incidence Following Radiotherapy for Childhood Cancer

Childhood cancer five-year survival now exceeds 70–80%. Childhood exposure to radiation is a known thyroid carcinogen; however, data are limited for the evaluation of radiation dose-response at high doses, modifiers of the dose-response relationship and joint effects of radiotherapy and chemotherapy. To address these issues, we pooled two cohort and two nested case-control studies of childhood cancer survivors including 16,757 patients, with 187 developing primary thyroid cancer. Relative risks (RR) with 95% confidence intervals (CI) for thyroid cancer by treatment with alkylating agents, anthracyclines or bleomycin were 3.25 (0.9–14.9), 4.5 (1.4–17.8) and 3.2 (0.8–10.4), respectively, in patients without radiotherapy, and declined with greater radiation dose (RR trends, P = 0.02, 0.12 and 0.01, respectively). Radiation dose-related RRs increased approximately linearly for <10 Gy, leveled off at 10–15-fold for 10–30 Gy and then declined, but remained elevated for doses >50 Gy. The fitted RR at 10 Gy was 13.7 (95% CI: 8.0–24.0). Dose-related excess RRs increased with decreasing age at exposure (P < 0.01), but did not vary with attained age or time-since-exposure, remaining elevated 25+ years after exposure. Gender and number of treatments did not modify radiation effects. Thyroid cancer risks remained elevated many decades following radiotherapy, highlighting the need for continued follow up of childhood cancer survivors.
Beyond the text: construction and analysis of multi-modal linguistic corpora

This paper addresses some of the linguistic and technological procedures and requirements of the next generation of tools for the analysis of spoken linguistic corpora. It reports on preliminary developments of an ESRC funded interdisciplinary project at the University of Nottingham. It specifically focuses on key methodological and technical issues related to the mark-up, coding and representation of multi-modal communication data. The paper builds on traditional approaches in the area of spoken corpus linguistics, which use multi-million word databases of textual renderings of naturally occurring conversation with the aim of identifying recurring patterns of lexical and grammatical patterns within sequences of interactions. The identification, classification and representation of accompanying gestural elements are explored in relation to the expression of active listenership.
Detection of cerebral ischemia using the power spectrum of the pulse wave measured by near-infrared spectroscopy

Abstract. The diagnosis and medical treatment of cerebral ischemia are becoming more important due to the increase in the prevalence of cerebrovascular disease. However, conventional methods of evaluating cerebral perfusion have several drawbacks: they are invasive, require physical restraint, and the equipment is not portable, which makes repeated measurements at the bedside difficult. An alternative method is developed using near-infrared spectroscopy (NIRS). NIRS signals are measured at 44 positions (22 on each side) on the fronto-temporal areas in 20 patients with cerebral ischemia. In order to extract the pulse-wave component, the raw total hemoglobin data recorded from each position are band-pass filtered (0.8 to 2.0 Hz) and subjected to a fast Fourier transform to obtain the power spectrum of the pulse wave. The ischemic region is determined by single-photon emission computed tomography. The pulse-wave power in the ischemic region is compared with that in the symmetrical region on the contralateral side. In 17 cases (85%), the pulse-wave power on the ischemic side is significantly lower than that on the contralateral side, which indicates that the transmission of the pulse wave is attenuated in the region with reduced blood flow. Pulse-wave power might be useful as a noninvasive marker of cerebral ischemia.
Automatic segmentation and recognition of human activities from observation based on semantic reasoning

Automatically segmenting and recognizing human activities from observations typically requires a very complex and sophisticated perception algorithm. Such systems would be unlikely implemented on-line into a physical system, such as a robot, due to the pre-processing step(s) that those vision systems usually demand. In this work, we present and demonstrate that with an appropriate semantic representation of the activity, and without such complex perception systems, it is sufficient to infer human activities from videos. First, we will present a method to extract the semantic rules based on three simple hand motions, i.e. move, not move and tool use. Additionally, the information of the object properties either ObjectActedOn or ObjectInHand are used. Such properties encapsulate the information of the current context. The above data is used to train a decision tree to obtain the semantic rules employed by a reasoning engine. This means, we extract lower-level information from videos and we reason about the intended human behaviors (high-level). The advantage of the abstract representation is that it allows to obtain more generic models out of human behaviors, even when the information is obtained from different scenarios. The results show that our system correctly segments and recognizes human behaviors with an accuracy of 85%. Another important aspect of our system is its scalability and adaptability toward new activities, which can be learned on-demand. Our system has been fully implemented on a humanoid robot, the iCub to experimentally validate the performance and the robustness of our system during on-line execution of the robot.
Evaluation of different biological data and computational classification methods for use in protein interaction prediction

Protein–protein interactions play a key role in many biological systems. High‐throughput methods can directly detect the set of interacting proteins in yeast, but the results are often incomplete and exhibit high false‐positive and false‐negative rates. Recently, many different research groups independently suggested using supervised learning methods to integrate direct and indirect biological data sources for the protein interaction prediction task. However, the data sources, approaches, and implementations varied. Furthermore, the protein interaction prediction task itself can be subdivided into prediction of (1) physical interaction, (2) co‐complex relationship, and (3) pathway co‐membership. To investigate systematically the utility of different data sources and the way the data is encoded as features for predicting each of these types of protein interactions, we assembled a large set of biological features and varied their encoding for use in each of the three prediction tasks. Six different classifiers were used to assess the accuracy in predicting interactions, Random Forest (RF), RF similarity‐based k‐Nearest‐Neighbor, Naïve Bayes, Decision Tree, Logistic Regression, and Support Vector Machine. For all classifiers, the three prediction tasks had different success rates, and co‐complex prediction appears to be an easier task than the other two. Independently of prediction task, however, the RF classifier consistently ranked as one of the top two classifiers for all combinations of feature sets. Therefore, we used this classifier to study the importance of different biological datasets. First, we used the splitting function of the RF tree structure, the Gini index, to estimate feature importance. Second, we determined classification accuracy when only the top‐ranking features were used as an input in the classifier. We find that the importance of different features depends on the specific prediction task and the way they are encoded. Strikingly, gene expression is consistently the most important feature for all three prediction tasks, while the protein interactions identified using the yeast‐2‐hybrid system were not among the top‐ranking features under any condition. Proteins 2006. © 2006 Wiley‐Liss, Inc.
Interference-Aware Component Scheduling for Reducing Tail Latency in Cloud Interactive Services

Large-scale interactive services usually divide requests into multiple sub-requests and distribute them to a large number of server components for parallel execution. Hence the tail latency (i.e. The slowest component's latency) of these components determines the overall service latency. On a cloud platform, each component shares and competes node resources such as caches and I/O bandwidths with its co-located jobs, hence inevitably suffering from their performance interference. In this paper, we study the short-running jobs in a 12k-node Google cluster to illustrate the dynamic resource demands of these jobs, resulting in both individual components' latency variability over time and across different nodes and hence posing a major challenge to maintain low tail latency. Given this motivation, this paper introduces a dynamic and interference-aware scheduler for large-scale, parallel cloud services. At each scheduling interval, it collects workload and resource contention information of a running service, and predicts both the component latency on different nodes and the overall service performance. Based on the predicted performance, the scheduler identifies straggling components and conducts near-optimal component-node allocations to adapt to the changing workloads and performance interferences. We demonstrate that, using realistic workloads, the proposed approach achieves significant reductions in tail latency compared to the basic approach without scheduling.
Adrenocortical suppression blocks the memory-enhancing effects of amphetamine and epinephrine.

This study examined glucocorticoid-adrenergic interactions in modulating acquisition and memory storage for inhibitory avoidance training. Systemically (s.c.) administered amphetamine (1 mg/kg), but not epinephrine (0.1 mg/kg) or the peripherally acting amphetamine derivative 4-OH amphetamine (2 mg/kg), given to rats shortly before training facilitated acquisition performance in a continuous multiple-trial inhibitory avoidance (CMIA) task. Adrenocortical suppression with the 11beta-hydroxylase inhibitor metyrapone (50 mg/kg; s.c.), given to rats 90 min before training, did not block the effect of amphetamine and did not affect acquisition performance of otherwise untreated animals. Retention of CMIA and one-trial inhibitory avoidance was enhanced by either pre- or posttraining injections of amphetamine as well as 4-OH amphetamine and epinephrine. The finding that injections of amphetamine and epinephrine have comparable effects on memory is consistent with the view that amphetamine may modulate memory storage, at least in part, by inducing the release of epinephrine from the adrenal medulla. Metyrapone pretreatment blocked the memory-enhancing effects of amphetamine, 4-OH amphetamine, and epinephrine but did not affect retention performance of otherwise untreated animals. Posttraining injections of different doses of epinephrine (ranging from 0.0001 to 1.0 mg/kg) produced a dose-dependent memory enhancement for inhibitory avoidance training and metyrapone blocked the memory-enhancing effects of all these doses. These findings provide further evidence that the sympathoadrenal and adrenocortical systems are intimately coupled during processes of memory storage.
Experiments on sublimation and contact forces of water ice particles and their application on planet formation

To date, the most accepted planet formation’s model is the so called “Nebular Hypothesis”. It proposes that planets are formed in a nebular region which remains orbiting around stars before they enter in the main sequence stage. This nebula, made of gas and dust, is called “Protoplanetary Disc” (PPD) due to its flat and symmetrical shape. Sub-micrometre particles’ aggregation is the main growth mechanism during the first planet formation phase in the disc. Contact forces between the constituents of solid aggregates determine the outcome of collisional events which occur in the disc. Icy grains are very abundant in regions where water condensates into solid state (regions situated beyond the so called “Snowline”). It implies that water ice is a fundamental ingredient during the planetesimal formation process. In this thesis, experiments on ice coagulation, sublimation and fragmentation are carried out in order to compare the obtained results with the existing theories. It is shown that sublimation of relatively large icy aggregates (∼ 1 metre) close to the snowline cause their fragmentation and the subsequent concentration of solids inthis region, boosting planetesimal formation. Making use of a “Temperature Gradient Force Microscope” (TGFM), critical forces between water ice particles are determined. This setup allows to establish an upper limit of variables related to contact physics like rolling and twisting torques. When the radius of the contact surface formed between two ice grains is ≲ 1 nm, actual theories are not able to predict the experimental observations. The variation of water ice’s surface energy may cause a reduction of the difference rate between experimental results and theoretical predictions. However, the development of a new model at such small scales may solve the issues presented in this thesis.
GPU-Based Interactive Volume Visualization From High-Order Finite Element Fields

This paper describes a new volume rendering system for spectral/hp finite-element methods that is both accurate and interactive. Even though high-order finite element methods are commonly used by scientists and engineers, there are few visualization methods designed to display this data directly. Consequently, visualizations of high-order data are generally created by first sampling the high-order field onto a regular grid and then generating the visualization via traditional methods based on linear interpolation. This approach, however, introduces error into the visualization pipeline and requires the user to balance image quality, interactivity, and resource consumption. We first show that evaluation of the volume rendering integral, when applied to the composition of piecewisesmooth transfer functions with the high-order scalar field, typically exhibits second-order convergence for a wide range of high-order quadrature schemes, and has worst case first-order convergence. This result provides bounds on the ability to achieve high-order convergence to the volume rendering integral. We then develop an algorithm for optimized evaluation of the volume rendering integral, based on the categorization of each ray according to the local behavior of the field and transfer function. We demonstrate the effectiveness of our system by running performance benchmarks on several high-order fluid-flow simulations.
Towards Scientific Workflows and Computer Simulation as a Method in Digital Humanities

This paper presents ongoing work on investigating text mining by scientific workflows and hypotheses testing by computer simulation as new digital methods in the digital humanities and particularly in the literary studies. In the course of the eXplore! project, the methods are developed for analyzing autobio-graphic texts and particularly for investigating the diaries of Klaus Mann, a famous German writer, with regards to the influences on the writer’s literary productivity. Text mining is used to build up a data basis for an agent-based model that can be used in simulation studies to answer what-if-questions about a writer’s creative writing processes. A further focus is put on the reusability of these methods to facilitate an application beyond the project’s pilot study. For this purpose, we model and apply scientific work-flows, populate a repository of proven workflows, and investigate an approach to reuse assistance by case-based reasoning.
Preparation of Iron Carbides Formed by Iron Oxalate Carburization for Fischer–Tropsch Synthesis

Different iron carbides were synthesized from the iron oxalate precursor by varying the CO carburization temperature between 320 and 450 °C. These iron carbides were applied to the high-temperature Fischer–Tropsch synthesis (FTS) without in situ activation treatment directly. The iron oxalate as a precursor was prepared using a solid-state reaction treatment at room temperature. Pure Fe5C2 was formed at a carburization temperature of 320 C, whereas pure Fe3C was formed at 450 °C. Interestingly, at intermediate carburization temperatures (350–375 °C), these two phases coexisted at the same time although in different proportions, and 360 °C was the transition temperature at which the iron carbide phase transformed from the Fe5C2 phase to the Fe3C phase. The results showed that CO conversions and products selectivity were affected by both the iron carbide phases and the surface carbon layer. CO conversion was higher (75–96%) when Fe5C2 was the dominant iron carbide. The selectivity to C5+ products was higher when Fe3C was alone, while the light olefins selectivity was higher when the two components (Fe5C2 and Fe3C phases) co-existed, but the quantity of Fe3C was small.
Simultaneous outlier detection and variable selection via difference-based regression model and stochastic search variable selection

In this article, we suggest the following approaches to simultaneous variable selection and outlier detection. First, we determine possible candidates for outliers using properties of an intercept estimator in a difference-based regression model, and the information of outliers is reflected in the multiple regression model adding mean shift parameters. Second, we select the best model from the model including the outlier candidates as predictors using stochastic search variable selection. Finally, we evaluate our method using simulations and real data analysis to yield promising results. In addition, we need to develop our method to make robust estimates. We will also to the nonparametric regression model for simultaneous outlier detection and variable selection.
Evaluation of the Efficacy of a Field Isolate of Eimeria Oocysts Immunization in Two Breeds of Chickens - Demystifying use of Coccidiosis Vaccines

Immunization efficacy of a field isolate of unattenuated sporulated Eimeria oocysts in broiler and Nigerian indigenous chickens (NIC) was investigated. Both breeds of birds were grouped and inoculated with varying dose levels (750, 1500 and 3000) of the oocysts per bird. Â The immunizing infections were truncated with an anticoccidial drug following detection of patency evident by presence of Eimeria oocysts in the faeces of inoculated birds on day 4 of inoculation. Â Immunized birds were then given challenged infections of 10,000 oocysts of the same Eimeria isolate per bird and an additional group that did not receive the immunizing infections was also challenged with 10,000 oocysts to serve as the unimmunized-challenged control while another group remained as uninfected-unchallenged control. Â Immunized birds were found to be protected against the challenge infections evident by having significantly less severe gross lesion scores (0 to 1) in contrast to the unimmunized-challenged control birds (which had lesion scores of 2 to 4 and 1 to 2 in broiler and indigenous chickens respectively). Â The infection was more severe in broiler chickens in contrast to the indigenous chickens judged by more severe lesion scores and significantly higher oocysts counts in the broilers. Â Broilers also had significantly lower PCV (P < 0.05) in comparison to their indigenous counterparts. Â Infected birds generally suffered infections more in contrast to the uninfected control birds judged by the significantly higher body weights and PCV of the uninfected birds (P < 0.05). Â The results showed that the protection of birds against coccidiosis by immunization with the Eimeria isolate is feasible and this can therefore serve as a premise for the recommendation of immunization against coccidioisis in eastern Nigeria where the practice is extremely low or unknown by poultry farmers and hardly recommended to poultry producers by veterinarians and their allies in spite of the endemicty and severity of the disease in the area. Â All the dose levels tried in this study were protective with no obvious differences between the dose levels and we recommended the use of 750 oocysts of such isolates to minimize the risk clinical coccidiosis. Local isolates of Eimeria would also have the added advantage in that they are likely to contain multiple Eimeria species that could provide full protection against the entire spectrum of Eimeria that occur in the area. Â Â
Real-time Passive Acoustic 3D Tracking of Deep Diving Cetacean by Small Non-uniform Mobile Surface Antenna

Detecting and localizing the echolocation clicks of sperm whales provides insight into their diving behavior, but existing methods are limited in range, imprecise, or costly. In this work, we demonstrate that we can obtain a high definition 3D track of deep diving cetaceans from a five-channel, small-aperture hydrophone array on a moving autonomous surface vehicle (ASV), enabled by the vessel’s hydrodynamic quality and a high recording sample rate. Real-time processing is achieved by splitting our non-uniform array into two parts for time delay of arrival estimation. Resulting 3D tracks depict the behavior of the cetacean in the abyss (−1.2 km), with one position per second. This high resolution allows us to observe a correlation between the repetition rate of the predator’s biosonar and the tortuosity of its track. Our proposed mobile observatory may offer new insights about whale behavior and its foraging success close to vessel traffic.
Secretory granules are recaptured largely intact after stimulated exocytosis in cultured endocrine cells

Classical cell biology teaches that exocytosis causes the membrane of exocytic vesicles to disperse into the cell surface and that a cell must later retrieve by molecular sorting whatever membrane components it wishes to keep inside. We have tested whether this view applies to secretory granules in intact PC-12 cells. Three granule proteins were labeled with fluorescent proteins in different colors, and two-color evanescent-field microscopy was used to view single granules during and after exocytosis. Whereas neuro-peptide Y was lost from granules in seconds, tissue plasminogen activator (tPA) and the membrane protein phogrin remained at the granule site for over 1 min, thus providing markers for postexocytic granules. When tPA was imaged simultaneously with cyan fluorescent protein (CFP) as a cytosolic marker, the volume occupied by the granule appeared as a dark spot where it excluded CFP. The spot remained even after tPA reported exocytosis, indicating that granules failed to flatten into the cell surface. Phogrin was labeled with GFP at its luminal end and used to sense the pH in granules. When exocytosis caused the acidic granule interior to neutralize, GFP–phogrin at first brightened and later dimmed again as the interior separated from the extracellular space and reacidified. Reacidification and dimming could be reversed by application of NH4Cl. We conclude that most granules reseal in <10 s after releasing cargo, and that these empty or partially empty granules are recaptured otherwise intact.