Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing EEG neuroimaging with machine learning

Neuroimaging techniques can give novel insights into the nature of human cognition. We do not wish only to label patterns of activity as potentially associated with a cognitive process, but also to probe this in detail, so as to better examine how it may inform mechanistic theories of cognition. A possible approach towards this goal is to extend EEG ‘brain-computer interface’ (BCI) tools – where motor movement intent is classified from brain activity – to also investigate visual cognition experiments. We hypothesised that, building on BCI techniques, information from visual object tasks could be classified from EEG data. This could allow novel experimental designs to probe visual information processing in the brain. This can be tested and falsified by application of machine learning algorithms to EEG data from a visual experiment, and quantified by scoring the accuracy at which trials can be correctly classified. Further, we hypothesise that ICA can be used for source-separation of EEG data to produce putative activity patterns associated with visual process mechanisms. Detailed profiling of these ICA sources could be informative to the nature of visual cognition in a way that is not accessible through other means. While ICA has been used previously in removing ’noise’ from EEG data, profiling the relation of common ICA sources to cognitive processing appears less well explored. This can be tested and falsified by using ICA sources as training data for the machine learning, and quantified by scoring the accuracy at which trials can be correctly classified using this data, while also comparing this with the equivalent EEG data. We find that machine learning techniques can classify the presence or absence of visual stimuli at 85% accuracy (0.65 AUC) using a single optimised channel of EEG data, and this improves to 87% (0.7 AUC) using data from an equivalent single ICA source. We identify data from this ICA source at time period around 75–125 ms post-stimuli presentation as greatly more informative in decoding the trial label. The most informative ICA source is located in the central occipital region and typically has prominent 10-12Hz synchrony and a -5 μV ERP dip at around 100ms. This appears to be the best predictor of trial identity in our experiment. With these findings, we then explore further experimental designs to investigate ongoing visual attention and perception, attempting online classification of vision using these techniques and IC sources. We discuss how these relate to standard EEG landmarks such as the N170 and P300, and compare their use. With this thesis, we explore this methodology of quantifying EEG neuroimaging data with machine learning separation and classification and discuss how this can be used to investigate visual cognition. We hope the greater information from EEG analyses with predictive power of each ICA source quantified by machine learning might give insight and constraints for macro level models of visual cognition.
Low power, current mode CMOS circuits for synthesis of arbitrary nonlinear functions

Low voltage CMOS circuits, operating in current mode, that exhibit piecewise transfer characteristics are presented. These circuits can be used for the synthesis of arbitrary piecewise transfer functions. Several circuits were developed. Nonlinear functions were synthesized with several approaches and results were compared using the Monte Carlo simulation of PSPICE software. The best results were obtained with double break point circuits. These circuits can be supplied with less than 1V.
An “inline” quasi-elliptic substrate integrated waveguide filter with high stopband rejection

In this paper, a fourth-order single-layered substrate integrated waveguide (SIW) quasi-elliptic filter with inline resonator arrangement is proposed. Transmission zeros (TZs) are introduced by the cross-coupling between higher/lower order modes in the SIW cavities to realize the quasi-elliptic function response and high stopband rejection of the filter. Measured results show that the 3 dB bandwidth of the filter is from 19.65 to 20.15 GHz, or 2.5% fractional bandwidth. The passband return loss is better than 20 dB, and the minimum insertion loss is 2.9 dB. Good agreement between the simulated and measured results is obtained. By using the proposed filter structure, four TZs are introduced, and high selectivity and high stopband rejection are obtained.
Mathematisches Forschungsinstitut Oberwolfach Enumerative Combinatorics

Enumerative Combinatorics focusses on the exact and asymp-totic counting of combinatorial objects. It is strongly connected to the proba-bilistic analysis of large combinatorial structures and has fruitful connections to several disciplines, including statistical physics, algebraic combinatorics, graph theory and computer science. This workshop brought together experts from all these various fields, including also computer algebra, with the goal of promoting cooperation and interaction among researchers with largely varying backgrounds.
Comparison of the sedative properties of CNS 7056, midazolam, and propofol in sheep.

BACKGROUND CNS 7056 is an esterase-metabolized benzodiazepine sedative currently under development. Its short duration of action would suggest a clinical role similar to midazolam or propofol. METHODS The effect of a range of doses of CNS 7056, midazolam, and propofol on depth of sedation, the respiratory system, and the cardiovascular system was studied in chronically instrumented sheep (n=5 or 6). The low, medium, and high doses of CNS 7056, midazolam, and propofol were 0.37, 0.74, and 1.47 mg kg(-1); 0.05, 0.1, and 0.2 mg kg(-1); and 1, 2, and 4 mg kg(-1), respectively. RESULTS CNS 7056 produced substantial sedation with rapid onset and offset for all doses, with duration rather than depth of sedation increasing with the dose. The lower doses of midazolam had minimal sedative effect; increasing the dose produced variable but longer term sedation. Sedation from propofol was comparable with that of CNS 7056 for the medium and high doses only. The high doses produced approximately 20 min of sedation. All three drugs produced dose-dependent respiratory (e.g. reductions in arterial oxygen tension) and cardiovascular depression (e.g. reductions in mean arterial pressure). For CNS 7056, midazolam, and propofol, the magnitude of the cardiovascular and respiratory depression was proportional to the depth of sedation achieved for any given drug or dose. For all three drugs, the respiratory and cardiovascular depression was not of sufficient magnitude to endanger the animals. CONCLUSIONS CNS 7056 is a powerful and short-acting anaesthetic in sheep with respiratory and cardiovascular effects consistent with its sedative/anaesthetic qualities.
THE DIDJERIDU AND THE VOCAL TRACT

The Australian didjeridu is a deceptively simple instrument acoustically but, because it is closely coupled to the playerOs vocal tract without an intervening mouthpiece, a skilled player can produce a wide variety of striking musical effects. Measurements and supporting theory elucidate the roles of passive instrument acoustics, lip motion, controllable vocal tract resonances, and active vocalisation.
Supervisory control of theme park vehicles

High-tech companies are often challenged to increase quality and functionality of products. However, this often results in increasing development costs and longer time-to-market. As a consequence, there is a need for new engineering processes. Supervisory control theory (SCT) can be used to synthesize control systems from the formal models of system components and requirements. As a result, expectations are that SCT enhances the engineering process.
Understanding How the New HyperFlex Architecture Enables Next-Generation High-Performance Systems

© 2015 Altera Corporation. A NIOS, QUARTUS and STRAT Trademark Office and in othe their respective holders as de products to current specificat products and services at any t of any information, product, advised to obtain the latest ve for products or services. 101 Innovation Drive San Jose, CA 95134 www.altera. com Understanding How the New HyperFlex Architecture Enables Next-Generation HighPerformance Systems by Mike Hutton, Architect, IC Design Engineering
Functional Relations of Cerebellar Modules of the Cat

The cerebellum consists of parasagittal zones that define fundamental modules of neural processing. Each zone receives input from a distinct subdivision of the inferior olive (IO)—activity in one olivary subdivision will affect activity in one cerebellar module. To define functions of the cerebellar modules, we inactivated specific olivary subdivisions in six male cats with a glutamate receptor blocker. Olivary inactivation eliminates Purkinje cell complex spikes, which results in a high rate of Purkinje cell simple spike discharge. The increased simple spike discharge inhibits output from connected regions of the cerebellar nuclei. After inactivation, behavior was evaluated during a reach-to-grasp task and during locomotion. Inactivation of each subdivision produced unique behavioral deficits. Performance of the reach-to-grasp task was affected by inactivation of the rostral dorsal accessory olive (rDAO) and the rostral medial accessory olive (rMAO) and, possibly, the principal olive. rDAO inactivation produced paw drag during locomotion and a deficit in grasping the handle during the reach-to-grasp task. rMAO inactivation caused the cats to reach under the handle and produced severe limb drag during locomotion. Inactivation of the dorsal medial cell column, cell group β, or caudal medial accessory olive produced little deficit in the reach-to-grasp task, but each produced a different deficit during locomotion. In all cases, the cats appeared to have intact sensation, good spatial awareness, and no change of affect. Normal cerebellar function requires low rates of IO discharge, and each cerebellar module has a specific and unique function in sensory–motor integration.
A patient previously treated with ALK inhibitors for central nervous system lesions from ALK rearranged lung cancer: a case report

Background Patients with anaplastic lymphoma kinase (ALK)-rearranged non-small-cell lung cancer (NSCLC) are now preferentially treated with tyrosine kinase inhibitors (TKIs). However, patients treated with ALK inhibitors end up with acquired resistance. Case presentation We present a patient with recurrent ALK-rearranged NSCLC that developed multiple brain metastases and meningitis carcinomatosa after sequential treatment with several lines of cytotoxic chemotherapy, crizotinib, and alectinib. After the patient underwent retreatment with crizotinib as salvage therapy because of poor performance status, the intracranial metastatic foci and meningeal thickening were shrank within 1 week. Conclusion Our experience with this case suggests that alectinib may restore sensitivity to crizotinib or amplified pathway such as MET which bestowed alectinib resistance was inhibited with crizotinib.
Affect Detection from Social Contexts Using Commonsense Knowledge Representations

In the past years, an important volume of research in Natural Language Processing has concentrated on the development of automatic systems to deal with affect in text. In spite of this interest, the performance of the approaches is still very low. An explanation to this fact is that emotion is most of the times not expressed through specific words, but by evoking situations that have an affective meaning. Dealing with this phenomenon requires automatic systems to have "knowledge"on the situation, the concepts it describes and their interaction. This necessity motivated us to develop the EmotiNet knowledgebase - a resource for the detection of emotion from text based on commonsense knowledge on concepts, their interaction and their affective consequence. In this article, we present an overview of the process undergone to build EmotiNet, propose methods to extend the knowledge it contains and analyze the performance of implicit affect detection using this resource. Additionally, we compare the results obtained with EmotiNet to the use of well-established methods for affect detection. The results of our extensive evaluations show that the approach using EmotiNet is appropriate for capturing and storing the structure of implicitly expressed affect, that the knowledge it contains can be easily extended to improve the results of this task and that methods employing EmotiNet obtain better results than existing methods for emotion detection.
Diagnostics for respondent‐driven sampling

Respondent‐driven sampling (RDS) is a widely used method for sampling from hard‐to‐reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference.
Storage and Reuse of Each Student's Personalized Documents Using a Non-structured Database

Personalization in e-Learning systems is becoming increasingly important. However, most personalization research is focused on user groups with information collected from registration data and logs. We propose a method for the storage and reuse of each student's personalized documents in an e-Learning system using a non-structured database like MongoDB. We create a document, which is serviced to the user as a short exam, and focus on analyzing the document itself using feedback from the user. Furthermore, we develop a system that automatically assembles test questions from a set of examples. We discuss how to store and reuse the documents and automatically assemble test questions, which are restructured for each user. Lastly, we discuss about how to combine each examples using user feedback.
Tissue plasminogen activator in central nervous system physiology and pathology

Summary Although conventionally associated with fibrin clot degradation, recent work has uncovered new functions for the tissue plasminogen activator (tPA)/plasminogen cascade in central nervous system physiology and pathology. This extracellular proteolytic cascade has been shown to have roles in learning and memory, stress, neuronal degeneration, addiction and Alzheimer’s disease. The current review considers the different ways tPA functions in the brain.
Designing Simulated Context-Aware Telephone in Pervasive Spaces

Personal context information is important to enable context-aware applications in pervasive spaces. As privacy, many investigators have pointed out that it must be in the controllable state by using personal privacy policy. The long term objective of this research was to extract privacy policy from personal context information database with machine learning method. A context-aware telephone system was designed to collect data, learn policy and examine the accuracy of policy. In the step of PDA simulation, the results showed that the method was possible to make suitable decision for telephone communication in consideration of privacy protection. In order to further validate the proposed privacy protection method, the pervasive space was designed and implemented to get more real data about using context-aware telephone. At the step of pervasive space simulation, we design and code the prototype of context-aware telephone system from the view of software engineering.
Geographical Region Mapping Scheme Based on Musical Preferences

Many countries and cities in the world tend to have different types of preferred or popular music, such as pop, K-pop, and reggae. Music-related applications utilize geographical proximity for evaluating the similarity of music preferences between two regions. Sometimes, this can lead to incorrect results due to other factors such as culture and religion. To solve this problem, in this paper, we propose a scheme for constructing a music map in which regions are positioned close to one another depending on the similarity of the musical preferences of their populations. That is, countries or cities in a traditional map are rearranged in the music map such that regions with similar musical preferences are close to one another. To do this, we collect users’ music play history and extract popular artists and tag information from the collected data. Similarities among regions are calculated using the tags and their frequencies. And then, an iterative algorithm for rearranging the regions into a music map is applied. We present a method for constructing the music map along with some experimental results.
Hidden Correlation Discovery : Towards the Automation of an Analysis System

IT Analytics company, Sumerian Ltd, has undertaken a 2-year project to automate and embed statistical techniques into its processes. Their current automated processes rely on correlation to highlight relationships between metric pairs. It is proposed that the nature of the data often obscures instances of high correlation, and that these may be revealed through the use of clustering analysis. Clustering analysis is a technique for dividing datasets into groups so that similar items are together and those displaying differences are separated. Like many data analysis methodologies, such techniques are often better suited to theoretical situations and are ill-equipped to perform well against the real-world situation of 'messy', massive-scale data. This project therefore aims to adapt simple clustering techniques to improve on the processes at Sumerian, by investigating different algorithms aimed at uncovering hidden correlation patterns within their datasets. Using the well-known k-means clustering algorithm as a starting point and baseline, we will attempt to find: highly-correlated subsets of any metric-pair without any categorical information; correlation in certain 'windows' of time within the data; and differences in the patterns of correlation between peak and other processing periods. Investigations into these developments will take in Hill Climbing and Genetic Algorithms. Overall, no single solution was found to fully meet the company's needs, but several avenues of future research have been uncovered, and recommendations are made on how to continue with the work. 3 Acknowledgements Huge thanks must go to my supervisor, Professor David Corne, for his support and guidance throughout both this and the wider KTP project, which would not have been remotely successful without his participation and encouragement. I would also like to thank Sumerian for allowing me to use my work with them as the basis for this dissertation, and particularly Chris Playford and George Theologou for rescuing me from total isolation during the work! I, Sarah Little, confirm that this work submitted for assessment is my own and is expressed in my words. Any uses made within it of the words of other authors in any form e.g. ideas, equations, figures, text, tables, programs are properly acknowledged at any point of their use. A list of the references employed is included.
Fisher choice may increase prevalence of green turtle fibropapillomatosis disease

Disease in wildlife populations is often controlled through culling. But when healthy individuals are removed and diseased individuals are left in the population, it is anticipated that prevalence of disease increases. Although this scenario is presumably common in exploited populations where infected individuals are less marketable, it is not widely reported in the literature. We describe this scenario in a marine turtle fishery in the Turks and Caicos Islands (TCI), where green turtles are harvested for local consumption. During a two-year period, we recorded the occurrence of fibropapillomatosis (FP) disease in green turtles (Chelonia mydas) captured during in-water surveys and compared it with that of turtles landed in the fishery. 13.4% (n=32) of turtles captured during in-water surveys showed externally visible signs of FP. FP occurred at specific geographic locations where fishing also occurred. Despite the disease being prevalent in the size classes selected by fishers, FP was not present in any animals landed by the fishery (n=162). The majority (61%) of fishers interviewed expressed that they had caught turtles with FP. Yet, 82% of those that had caught turtles with the disease chose to return their catch to the sea, selectively harvesting healthy turtles and leaving those with the disease in the population. Our study illustrates that fisher choice may increase the prevalence of FP disease and highlights the importance of this widely neglected driver in the disease dynamics of exploited wildlife populations.
DNA methyltransferase inhibitors-state of the art.

BACKGROUND DNA methylation is the addition of a methyl group to the 5 position of cytosine. It is an epigenetic process with several effects, including chromatin structure modulation, transcriptional repression and the suppression of transposable elements. In malignancy, methylation patterns change, resulting in global hypomethylation with regional hypermethylation. This can lead to genetic instability and the repression of tumor suppressor genes. DESIGN A review of the DNA methyltransferase inhibitor literature was conducted. RESULTS DNA methylation inhibitors have demonstrated the ability to inhibit hypermethylation, restore suppressor gene expression and exert antitumor effects in in vitro and in vivo laboratory models. Four inhibitors, which are analogs of the nucleoside deoxycitidine, have been clinically tested: 5-azacytidine, 5-aza-2'-deoxycytidine, 1-beta-D-arabinofuranosyl-5-azacytosine and dihydro-5-azacytidine. The first two have demonstrated encouraging antileukemic activity but little activity in solid tumors, while the latter two are no longer under study due to lack of efficacy. A fifth agent, MG98, is an antisense oligodeoxynucleotide directed against the 3' untranslated region of the DNA methyltransferase-1 enzyme mRNA, and is now under phase II study. CONCLUSIONS While some positive clinical results with DNA methyltransferase inhibitors have been seen, a definitive clinical role for these agents will most likely require combination therapy, and good phase III studies are needed.