Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Repetitive Transcranial Magnetic Stimulation at the Cerebellum on Working Memory

Transcranial magnetic stimulation is a widely used brain intervention technique in clinical settings. In recent years, the role of the cerebellum in learning and memory has become one of the hotspots in the field of cognitive neuroscience. In this study, we recruited 36 healthy college or graduate students as subjects and divided them into groups, with 10 to 14 subjects in each group. We performed 5 Hz and 20 Hz repeated transcranial magnetic stimulation and sham stimulation on the Crus II subregion of the cerebellum in different groups, then let them complete the 2-back working memory task before and after the stimulation. We simultaneously recorded the electroencephalogram in the experiment and analyzed the data. We found that after repeated transcranial magnetic stimulation of the cerebellum at 5 Hz and 20 Hz, the N170 and P300 event-related potential components in the prefrontal cortex showed significant differences compared to those in the sham stimulation group. Using phase-locked values to construct brain networks and conduct further analysis, we discovered that stimulation frequencies of 5 Hz and 20 Hz had significant effects on the local and global efficiency of brain networks in comparison to the sham stimulation group. The results showed that repeated transcranial magnetic stimulation on cerebellar targets can effectively affect the subjects’ working memory tasks. Repeated transcranial magnetic stimulation at 5 Hz and 20 Hz could enhance the excitatory responses of the frontal lobes. After stimulation at 5 Hz and 20 Hz, the efficiency of the brain network significantly improved.
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approved: Attila Altay Yavuz The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a research gap to create reproducible keys from image data. In this thesis, towards addressing aforementioned challenge, we developed a new image based reproducible key derivation mechanism, which leverages deep learning technique along side with fuzzy-extractor schemes to enable reproducible symmetric key creation from temporal visual environments. Our technique uses deep learning and fuzzyextractors as fundamental building blocks. Deep learning harnesses patterns in images to minimize the noise, and permit successful utilization of fuzzy-extractor schemes to handle errors by using error-correcting codes. Using these techniques together enables reproducible key generation. We also instantiated our technique to enable three potential use cases: i) Image entropy strengthened authentication, ii) image based password authenticated Diffie-Hellman, and iii) position based cryptography. Along side these potential use cases, we conducted a user study to assess the usability of the provided scheme. c ©Copyright by Gungor Basa December 2, 2016 All Rights Reserved
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approved: Kagan Tumer Auctions are used to solve resource allocation problem between many agents and many items in real-world settings. Unfortunately, in most cases, it is possible for selfish agents to manipulate the system for their own interest at the expense of the social welfare. Such manipulation can be prevented using the Vickrey-Clarke-Groves mechanism, which guarantees complete truthfulness from the agents, and therefore, preserve optimal social welfare. However, the Vickrey-Clarke-Groves mechanism is computationally expensive, mainly due to the search for the optimal allocation of items (the “Winner Determination Problem”). In this work, we propose the use of off-equilibrium incentives to approximate the VCG mechanism, where the agents use reinforcement learning using “difference rewards” to compute those incentives. In one round of the reinforcement learning the agents: (i) declare their preferences in terms of allocation; (ii) compute their reward using the difference reward; (iii) and update their Q-table and move toward system efficiency. We demonstrate theoretically the equivalence of the off-equilibrium incentives and the VCG mechanism, and empirically show that this approximation of VCG mechanism leads to desirable outcomes in a congestion game. c ©Copyright by Béatrice Moissinac November 22, 2013 All Rights Reserved Reinforcement Learning-based Off-Equilibrium Incentives to Approximate the VCG Mechanism
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approved: ___________________________________________________ Thinh Nguyen Since free riders in P2P network reduce the system‘s performance, how to maintain and encourage the nodes‘ cooperation is an important aspect of P2P related research. In this thesis, a P2P system is modeled based on two games: stag hunt game and snowdrift game. To relate the model to the real situation in P2P network, heterogeneous environment (e.g., different service capacity) for each node is considered. These P2P models reveal under which conditions nodes are cooperative, so they show how to maintain and improve the level of cooperation. Evolutionary game theory is employed to analyze the dynamic evolutionary process of the mechanism. Replicator dynamics is used to show what condition can increase the level of nodes‘ cooperation, theoretically and mathematically, and numerical results also are shown by simulation. These results suggest guidelines to design an efficient and fair P2P system. ©Copyright by Seungyun Cho December 3, 2010 All Rights Reserved Modeling and Dynamics Analysis of P2P Networks based on Evolutionary Games
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approved: Scott P. Sanner Social media sources such as Twitter represent a massively distributed social sensor over diverse topics ranging from social and political events to entertainment and sports news. However, due to the overwhelming volume of content, it can be difficult to identify novel and significant content within a broad topic in a timely fashion. To this end, this thesis proposes a scalable and practical method to automatically construct social sensors for generic topics. The concept of using social media as a sensor for detection of events and news has been proposed in the literature. However, we argue that most of these works do not focus on targeted content detection or they use very basic methods for collecting the topical data for further analysis. This demonstrates a gap in the use of social media as a sensor for high-quality topical content detection that we aim to address via machine learning. In this thesis, given minimal supervised training content from a user, we learn to identify topical tweets from millions of features capturing content, user and social interactions on Twitter. On a corpus of over 800 million English Tweets collected from the Twitter streaming API during 2013 and 2014 and learning for 10 diverse topics, we empirically show that our learned social sensor automatically generalizes to unseen future content with high ranking and precision scores. Furthermore, we provide an extensive analysis of features and feature types across different topics that reveals, for example, that (1) largely independent of topic, simple terms are the most informative feature followed by location features and that (2) the number of unique hashtags and tweets by a user correlates more with their informativeness than their follower or friend count. In summary, this work provides a novel, effective, and efficient way to learn topical social sensors requiring minimal user curation effort and offering strong generalization performance for identifying future topical content. c ©Copyright by Zahra Iman May 25, 2016 All Rights Reserved Learning Topical Social Media Sensors for Twitter
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approved:. Anna K. Hardin~ Traditional public health bacterial indicators of water quality and the Biolog® system were evaluated to compare their response to other indicators of stream condition with the state of Oregon and between ecoregions (Coast Range, Willamette Valley, Cascades, and Eastern Oregon). Forty-three randomly selected Oregon rivers were sampled during the summer low flow period in 1997 and 1998. Testing included heterotrophic plate counts (HPC), total coliforms, fecal coliforms, E. coli, and Biolog® GN plates. Statewide, HPC correlated strongly with physical habitat and chemistry indicators while fecal coliforms and E. coli were highly correlated only with the river chemistry indicators. Total coliform bacteria did not correlate with either of the above environmental indicators. Dividing the sites by ecoregion, Eastern Oregon was Redacted for Privacy characterized by high HPC, fecal coliforms, E. coli, nutrient loads, and indices of human disturbance, whereas the Cascades ecoregion had correspondingly low counts of these indicators. The Coast Range reflected statewide results and the Willamette Valley presented no consistent indicator pattern. Attempts to separate ecoregions with the Biolog system were not successful nor did a statistical pattern emerge between the first five principle components and the other environmental indicators. Our research has shown that traditional public health microbial indicators may, however, be useful in measuring the effects of anthropogenic stress over large spatial scales.
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approved: Sinisa Todorovic Given a video, we would like to recognize group activities, localize video parts where these activities occur, and detect actors involved in them. To this end, we propose a novel, mid-level feature, called control point, for representing group activities. The control points are aimed at summarizing visual cues, lifting from the noisy low-level features, and jointly providing visual evidence of actors and their group activity to higher-level inference algorithms. We formulate a generative model, called chains model, to organize a huge number of video features in an ensemble of chains of control points, representing a group activity. The chains may have arbitrary length, ideally, starting and ending at the beginning and end of the time interval occupied by the activity. We derive an efficient MAP inference, which is a new, EM-like algorithm that iterates two steps: warps the chains of control points to their expected locations so they can better summarize visual cues, and then maximizes their posterior probability. Our evaluation on benchmark UT-Human Interaction and Collective Activities datasets demonstrates that we outperform the sate of the art with reasonable running times.
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approved: Eric T. Walkingshaw Many applications require not only representing variability in software and data, but also computing with it. To do so efficiently requires variational data structures that make variability explicit in the underlying data and the operations used to manipulate it. Variational data structures have been developed ad hoc for many applications, but there is little general understanding of how to design them or what tradeoffs exist among them. In this thesis, we introduce the concept of holes to represent variational data structures of different sizes and shapes. Moreover, we strive for a more systematic exploration and analysis of a variational data structure. We want to know how different design decisions affect the performance and scalability of a variational data structure, and what properties of the underlying data and operation sequences need to be considered. Specifically, we study several alternative designs of a variational stack and analyze how these design decisions affect the performance of a variational stack with different usage profiles. We evaluate variational stacks in a real-world scenario: in the interpreter VarexJ when executing real software containing variability. Finally, we discuss different ways of representing variational priority queues and show how this affects the performance of the variational Dijkstra’s algorithm. c ©Copyright by Meng Meng September 22, 2017 All Rights Reserved Implementation Techniques for Variational Data Structures
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approved: _____________________________________________________________________ David C. Shaw Hemlock dwarf mistletoe (Arceuthobium tsugense subsp. tsugense) is an arboreal, hemiparasitic plant that principally parasitizes western hemlock (Tsuga heterophylla). Hemlock dwarf mistletoe exerts a profound influence on infected trees that can drastically change the structure of the tree crown due to reduced growth, top dieback, branch deformation and death, resulting in unique habitat structures, changed fire dynamics, and more severe drought impacts. Although dwarf mistletoe is important to tree crowns, most research has been from the ground or by felling trees. In this study, we climbed 16 western hemlock trees (age 97 – 321 years) across a gradient of infection (0 – 100% of branches infected) and measured occurrence of all dwarf mistletoe infections, branch and crown architecture, and dwarf mistletoe caused deformities. Sapwood area was measured at the top of buttressing or 1.37 m above the ground (f-diameter) and at base of live crown. To explore the impacts of increasing infection severity, over 25 different response variables were examined using linear and generalized linear models to estimate mean responses among the 16 western hemlocks. We developed three metrics of severity as explanatory variables for the models: total infection incidence, proportion of all live branches infected, and proportion of all live, infected branches with 33 percent or more foliage distal to infection. Many effects of dwarf mistletoe on crown structure appear subtle, except for deformations. Increasing severity led to crowns experiencing an apparent compaction, where crown volume was reduced while deformity volume increased, and crown volumes became increasingly comprised of deformities. A strong effect of dwarf mistletoe intensification is the reduction of branch foliage and an increase in the proportional amount of foliage distal to infections, and therefore a likely reduction in carbohydrates available to tree growth. Sapwood areas at f-diameter and at base of live crown were unrelated to all metrics of infection severity. Branch length and diameters were also unaffected by increasing infection severity despite heavily infected branches supporting 1 to 70 infections. This suggests infected trees compensate for the water and nutrient loss through changes to the crown architecture such as reduced foliage instead of through conductive tissues. Our results suggest shifts in crown structure reflect a shift in function, from prioritizing biomass production and growth, to tree survival. ©Copyright by Stephen John Calkins July 24, 2020 All Rights Reserved Transformation of Western Hemlock Tree Crowns by Dwarf Mistletoe by Stephen John Calkins
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approved: _ „ Tdfiy H. H. Chen This thesis reports a successful in vitro plant regeneration system for Iris germanica L.from cell suspension cultures. A series of experiments was conducted to systematically examine factors which critically affect induction of differentiated clumps from the suspension culture, as well as the induction of shoot and root regeneration from the clumps. A stable suspension culture was established from callus induced on leaf bases and was maintained by subculturing every 3 weeks. Suspension cultures were maintained in Murashige and Skoog (MS) medium (pH 5.9) supplemented with 290 mg-l" proline, 50 g-l" sucrose, 5.0 \iM 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.5 \xM. kinetin (Kin). Suspension-cultured cells were transferred to a shoot induction medium, MS basal medium supplemented with 10 mg-l" pantothenic acid, 4.5 mg-l" nicotinic acid, 1.9 mg-l" thiamin, 250 mg-l" casein hydrolysate, 250 mg-l" proline, 50 g-l' sucrose, 2.0 g-l" PhytagelTM (Sigma, St. Louis, MO), 0.5 \M. NAA (a-Naphthaleneacetic acid), and 12.5 pM Kin. Cell clusters differentiated and eventually developed into shoots in 5 weeks. At the suspension culture phase, the effects of plant growth regulators (2,4-D acid and Kin), length of culture period, and the size of multicellular aggregates on plant regeneration were examined. The highest regeneration efficiency was achieved when suspension cultures were grown in a liquid medium containing 5 ^M 2,4-D and 0.5 jxM Kin for 6 weeks, and the suspension cultures were then passed through a stainless steel sieve with pore size <280 jim in diameter. The screened cell fraction was inoculated onto an induction medium to induce plant regeneration. Various combinations of Kin and NAA were tested for their effects on the induction of differentiated cellular structures and subsequent development. The most regenerable clumps (66.7%) and (63.0%) developing into both shoots and roots simultaneously were produced on induciton medium with 2.5 or 12.5 \iM Kin with 0.5 |j.M NAA. Medium containing 1.25 ^M N^-benzyladenine (BA) were optimal for plant development from those regenerable clumps. Rooted plantlets were easily transplanted and acclimatized to soil mixtures in pots for greenhouse growth. This represents an efficient in vitro plant regeneration system for iris, allowing regeneration of a large number of morphologically normal plants. ©Copyright by Yuexin Wang May 20, 1998 All Rights Reserved PLANT REGENERATION FROM CELL SUSPENSION CULTURES OF IRIS (IRIS GERMANICA L. CV. 'SKATING PARTY')
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approved: ______________________________________________________ Margaret M. Burnett Software history and version control systems (VCS) are an important source of information for developers. This importance entails the need for a principled understanding of developers’ information seeking in VCS, both for improving existing tools as well as understanding requirements for new tools. However, it is only recently that researchers have started investigating how developers use VCS. In this thesis, we take a theory-based approach to understanding developers’ information seeking in VCS. Using the foundations of Information Foraging Theory (IFT), we analyze the data from a prior empirical study, to gain new perspectives into developers’ information seeking in VCS. Our results indicate that participants engaged in foraging behavior; therefore, tool builders can leverage IFT’s design insights and patterns to VCS design. Further, our results reveal that participants’ change-awareness foraging differed subtly from traditional foraging and calls for further investigation. Similarly, participants attempted to create commits that suited the needs of future foragers. However, balancing the tensions between different foraging activities or between different people (e.g., different commit size preferences) is a hard problem and presents an opportunity for further research at the intersection of IFT and software engineering. ©Copyright by Sruti Srinivasa Ragavan January 10, 2018 All Rights Reserved Version Control Systems: An Information Foraging Perspective by Sruti Srinivasa Ragavan
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approved: Sinisa Todorovic This thesis is about visual relationship detection. This is an important task in computer vision. The goal is to detect all visual relationships in a given image between objects. This thesis presents a new approach to this problem. Our approach does not use an object detector as a common pre-processing step of prior work. In this way, we overcome the limitation of large computational complexity when considering a large object categories. We focus on relationships that can be specified as triplets < subject, predicate, object >. Our approach has four modules including object pair detection, triplet proposal, imposing common-sense constraints and ranking. To boost the performance of our system, we use Message Passing on the triplet proposal module. Our evaluation shows effectiveness of our approach. We also discuss some improvements of our visual relationship detection system in the future. c ©Copyright by Khoi Nguyen September 19, 2017 All Rights Reserved Relational Networks for Visual Relationship Detection in Images
Effectiveness of influenza vaccination programme in preventing hospital admissions, Valencia, 2014/15 early results

Effectiveness of influenza vaccination programme in preventing hospital admissions, Valencia, 2014/15 early results 2 by J Puig-Barberà, A Mira-Iglesias, M Tortajada-Girbés, FX López-Labrador, A Belenguer-Varea, M Carballido-Fernández, E Carbonell-Franco, C Carratalá-Munuera, R Limón-Ramírez, J Mollar-Maseres, M del Carmen Otero-Reigada, G Schwarz-Chavarri, J Tuells, V Gil-Guillén, for the Valencia Hospital Network for the Study of Influenza and Respiratory Viruses Disease
Preserving biodiversity in saffron: the CROCUSBANK project and the world saffron and Crocus collection.

The loss of land surface dedicated to saffron cultivation in some areas of the world, particularly in the Mediterranean Basin countries (North and South banks), has resulted in a corresponding genetic erosion of this crop. Since saffron multiplies exclusively in a vegetative way, the preservation of the presumably scarce genetic diversity is highly valuable to carry out in any breeding programme. In 2005, the European Commission launched a programme for the conservation, characterisation, collection and utilisation of genetic resources in agriculture, AGRI GEN RES. A consortium of 14 groups of 9 countries, lead by the University of Castilla-La Mancha (Spain), presented the four-years project "Genetic Resources of Saffron and Allies (Crocus spp.): CROCUSBANK". The objective of this action is to create, characterise and exploit a worldwide germplasm collection in saffron and relatives. The mother-plant collection is located in the Bank of Plant Germplasm of Cuenca (CIA Albadalejito, Spain), where 384 accessions of saffron and wild crocuses are preserved, multiplied and partially characterised at the moment. In this paper, the curator of the collection, the manager and the coordinator of the CROCUSBANK Project, present the results in this field, after two years of activity.
On-site financial costs of soil erosion by runoff from the Mizewa catchment of the Blue Nile basin

This study was conducted in Mizewa watershed which is located in Blue Nile Basin (BNB) to estimate on-site financial cost of erosion in terms of yield reduction taking maize as representative crop. For this purpose, discharge measurement and runoff sampling was made during the rainy season of 2011 at the outlet of three sub watersheds within Mizewa catchment; lower Mizewa (MZ0), Upper Mizewa (MZ1) and Gindenewur (GN0). The samples were filtered to separate the sediment which was subsampled for determination of suspended sediment concentration (SSC), sediment fixed NO3 -, NH4 + and available phosphorous (P) contents. The filtered water was used to assess dissolved nitrate and dissolved phosphate. The on-site financial cost of erosion was estimated based on productivity change approach (PCA) focusing on available NP losses. The result revealed that the SSC and its NP content varied in space and time, in which higher and lower SSC occurred towards the beginning and end of the rainy season, respectively. The mean seasonal discharge was found to be 2.12±0.75, 1.49±0.52 and 0.57±0.20 m3/ sec at MZ0, MZ1 and GN0 stations in that order while the corresponding sediment concentration was 510±370 mg/l, 230±190 mg/l and 370±220 mg/l. This led to the total suspended sediment loss (SSL) of 4 ton/ha/year, 2 ton/ha/year and 3 ton/ha/year from the respective subwatersheds. The on-site financial cost due to N and P lost associated with SSL was estimated to be USD 200/ha, USD 186/ha and USD 227/ha from MZ0, MZ1 and GN0 watersheds, respectively. The study revealed that the economic impacts of soil erosion which is variable based on the characteristics of land resources and management practices are immense and deserve due attention. The result may help in sensitizing both farmers and decision-makers about the risk of soil erosion and in targeting management practices to overcome the challenges.