nils-herrmann/clean_scirepeval huggingface dataset:
Detecting Neonatal Seizures With Computer Algorithms.
Venue: Journal of clinical neurophysiology official publication of the American Electroencephalographic Society

It is now generally accepted that EEG is the only reliable way to accurately detect newborn seizures and, as such, prolonged EEG monitoring is increasingly being adopted in neonatal intensive care units. Long EEG recordings may last from several hours to a few days. With neurophysiologists not always available to review the EEG during unsociable hours, there is a pressing need to develop a reliable and robust automatic seizure detection method a computer algorithm that can take the EEG signal, process it, and output information that supports clinical decision making. In this study, we review existing algorithms based on how the relevant seizure information is exploited. We start with commonly used methods to extract signatures from seizure signals that range from those that mimic the clinical neurophysiologist to those that exploit mathematical models of neonatal EEG generation. Commonly used classification methods are reviewed that are based on a set of rules and thresholds that are either heuristically tuned or automatically derived from the data. These are followed by techniques to use information about spatiotemporal seizure context. The usual errors in system design and validation are discussed. Current clinical decision support tools that have met regulatory requirements and are available to detect neonatal seizures are reviewed with progress and the outstanding challenges are outlined. This review discusses the current state of the art regarding automatic detection of neonatal seizures.
Functions and regulation of the Brr2 RNA helicase during splicing
Venue: Cell cycle

Pre mRNA splicing entails the stepwise assembly of an inactive spliceosome, its catalytic activation, splicing catalysis and spliceosome disassembly. Transitions in this reaction cycle are accompanied by compositional and conformational rearrangements of the underlying RNA protein interaction networks, which are driven and controlled by 8 conserved superfamily 2 RNA helicases. The Ski2 like helicase, Brr2, provides the key remodeling activity during spliceosome activation and is additionally implicated in the catalytic and disassembly phases of splicing, indicating that Brr2 needs to be tightly regulated during splicing. Recent structural and functional analyses have begun to unravel how Brr2 regulation is established via multiple layers of intra and inter molecular mechanisms. Brr2 has an unusual structure, including a long N terminal region and a catalytically inactive C terminal helicase cassette, which can auto inhibit and auto activate the enzyme, respectively. Both elements are essential, also serve as protein protein interaction devices and the N terminal region is required for stable Brr2 association with the tri snRNP, tri snRNP stability and retention of U5 and U6 snRNAs during spliceosome activation in vivo. Furthermore, a C terminal region of the Prp8 protein, comprising consecutive RNase H like and Jab1/MPN like domains, can both up and down regulate Brr2 activity. Biochemical studies revealed an intricate cross talk among the various cis and trans regulatory mechanisms. Comparison of isolated Brr2 to electron cryo microscopic structures of yeast and human U4/U6*U5 tri snRNPs and spliceosomes indicates how some of the regulatory elements exert their functions during splicing. The various modulatory mechanisms acting on Brr2 might be exploited to enhance splicing fidelity and to regulate alternative splicing.
The chloroplastic DEVH box RNA helicase INCREASED SIZE EXCLUSION LIMIT 2 involved in plasmodesmata regulation is required for group II intron splicing.
Venue: Plant, cell environment

INCREASED SIZE EXCLUSION LIMIT 2 (ISE2) encodes a putative DEVH box RNA helicase originally identified through a genetic screening for Arabidopsis mutants altered in plasmodesmata (PD) aperture. Depletion of ISE2 also affects chloroplasts activity, decreases accumulation of photosynthetic pigments and alters expression of photosynthetic genes. In this work, we show the chloroplast localization of ISE2 and decipher its role in plastidic RNA processing and, consequently, PD function. Group II intron containing RNAs from chloroplasts exhibit defective splicing in ise2 mutants and ISE2 silenced plants, compromising plastid viability. Furthermore, RNA immunoprecipitation suggests that ISE2 binds in vivo to several splicing regulated RNAs. Finally, we show that the chloroplast clpr2 mutant (defective in a subunit of a plastidic Clp protease) also exhibits abnormal PD function during embryogenesis, supporting the idea that chloroplast RNA processing is required to regulate cell cell communication in plants.
METU MMDS: An Intelligent Multimedia Database System for Multimodal Content Extraction and Querying
Venue: MMM

Managing a large volume of multimedia data, which contain various modalities (visual, audio, and text) reveals the need for a specialized multimedia database system (MMDS) to efficiently model, process, store and retrieve video shots based on their semantic content. This demo introduces METU MMDS, an intelligent MMDS which employs both machine learning and database techniques. The system extracts semantic content automatically by using visual, audio and textual data, stores the extracted content in an appropriate format and uses this content to efficiently retrieve video shots. The system architecture supports various multimedia query types including unimodal querying, multimodal querying, query by concept, query by example, and utilizes a multimedia index structure for efficiently querying multi dimensional multimedia data. We demonstrate METU MMDS for semantic data extraction from videos and complex multimedia querying by considering content and concept based queries containing all modalities.
False memories with age: Neural and cognitive underpinnings
Venue: Neuropsychologia

As we age we become increasingly susceptible to memory distortions and inaccuracies. Over the past decade numerous neuroimaging studies have attempted to illuminate the neural underpinnings of aging and false memory. Here we review these studies, and link their findings with those concerning the cognitive properties of age related changes in memory accuracy. Collectively this evidence points towards a prominent role for age related declines in medial temporal and prefrontal brain areas, and corresponding impairments in associative binding and strategic monitoring. A resulting cascade of cognitive changes contributes to the heightened vulnerability to false memories with age, including reduced recollective ability, a reliance on gist information and familiarity based monitoring mechanisms, as well as a reduced ability to inhibit irrelevant information and erroneous binding of features between memory traces. We consider both theoretical and applied implications of research on aging and false memories, as well as questions remaining to be addressed in future research.
How Fuzzy Trace Theory Predicts True and False Memories for Words, Sentences, and Narratives.
Venue: Journal of applied research in memory and cognition

Fuzzy trace theory posits independent verbatim and gist memory processes, a distinction that has implications for such applied topics as eyewitness testimony. This distinction between precise, literal verbatim memory and meaning based, intuitive gist accounts for memory paradoxes including dissociations between true and false memory, false memories outlasting true memories, and developmental increases in false memory. We provide an overview of fuzzy trace theory, and, using mathematical modeling, also present results demonstrating verbatim and gist memory in true and false recognition of narrative sentences and inferences. Results supported fuzzy trace theory's dual process view of memory: verbatim memory was relied on to reject meaning consistent, but unpresented, sentences (via recollection rejection) However, verbatim memory was often not retrieved, and gist memory supported acceptance of these sentences (via similarity judgment and phantom recollection) Thus, mathematical models of words can be extended to explain memory for complex stimuli, such as narratives, the kind of memory interrogated in law.
Semantic representations in the temporal pole predict false memories
Venue: Proceedings of the National Academy of Sciences

False memories can arise in daily life through a mixture of factors, including misinformation and prior conceptual knowledge. This can have serious consequences in settings, such as legal eyewitness testimony, which depend on the accuracy of memory. We investigated the brain basis of false memory with fMRI, and found that patterns of activity in the temporal pole region of the brain can predict false memories. Furthermore, we show that each individual has unique patterns of brain activation that can predict their own idiosyncratic set of false memory errors. Together, these results suggest that the temporal pole may be responsible for the conceptual component of illusory memories. Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.
Mindfulness and False Memories: The Impact of Mindfulness Practice on the DRM Paradigm
Venue: The Journal of psychology

Mindfulness practice is the cultivation of awareness to the present moment and has been shown in recent years to have beneficial effects on cognition. However, to date, the data regarding the impact of mindfulness on memory and specifically on memory distortions is scarce and incomplete. The present study was aimed to examine whether mindfulness practice would have an effect on true and false memories. To this end, the effect of mindfulness meditation practice on memory performance was examined in two experiments in which false memories were provoked using the Deese Roediger McDermott (DRM) paradigm (Roediger McDermott, 1995) In Experiment 1, college students were randomly divided into either a 5 week mindfulness practice group (n 29) or a waitlist control group (n 22) In Experiment 2, college students were randomly divided into either a brief mindfulness session (n 21) or a mind wandering control group (n 19) The results indicated that mindfulness increased the recognition of true memories with no effect on spontaneous false memories, yet increased the rate of provoked false memories. These findings are discussed in terms of memory sensitivity and response bias, and it is argued that mindfulness may have a lesser effect on encoding processes than previously suggested.
Arousal But Not Valence Reduces False Memories at Retrieval
Venue: PloS one

Mood affects both memory accuracy and memory distortions. However, some aspects of this relation are still poorly understood: (1) whether valence and arousal equally affect false memory production, and (2) whether retrieval related processes matter; the extant literature typically shows that mood influences memory performance when it is induced before encoding, leaving unsolved whether mood induced before retrieval also impacts memory. We examined how negative, positive, and neutral mood induced before retrieval affected inferential false memories and related subjective memory experiences. A recognition memory paradigm for photographs depicting script like events was employed. Results showed that individuals in both negative and positive moods similar in arousal levels correctly recognized more target events and endorsed fewer false memories (and these errors were linked to remember responses less frequently) compared to individuals in neutral mood. This suggests that arousal (but not valence) predicted memory performance; furthermore, we found that arousal ratings provided by participants were more adequate predictors of memory performance than their actual belonging to either positive, negative or neutral mood groups. These findings suggest that arousal has a primary role in affecting memory, and that mood exerts its power on true and false memory even when induced at retrieval.
Application of DSTATCOM for power quality improvement using isolated zig zag/star transformer under varying consumer load
Venue: 2016 International Conference on Electrical Power and Energy Systems (ICEPES)

The demand of non linear and dynamic load is increasing day to day causing severe power quality issues. This paper presents a novel control strategy by employing distributed static compensator (DSTATCOM) to mitigate power quality problems. The proposed controller is a combination of a DSTACOM consisting voltage source converter with zig zag/star transformer for optimizing DC link voltage. The DSTATCOM is realized by using IGBT based current controlled voltage source converter, which inject the reactive power. The neutral point for consumer load is provided by zig zag/star transformer which mitigates the harmonic current, provide the path for zero sequence current, provide isolation for power electronics devices and optimize the DC link voltage of DSTATCOM. Power balance theory (PBT) is employed for generating gating pulse of DSTATCOM under varying consumer load. This concept is demonstrated with various MATLAB/Simulink simulation studies. Finally a comparative analysis is carried out to show the effectivity of the proposed controller.
Early Antibody Lineage Diversification and Independent Limb Maturation Lead to Broad HIV 1 Neutralization Targeting the Env High Mannose Patch.
Venue: Immunity

The high mannose patch on HIV Env is a preferred target for broadly neutralizing antibodies (bnAbs) but to date, no vaccination regimen has elicited bnAbs against this region. Here, we present the development of a bnAb lineage targeting the high mannose patch in an HIV 1 subtype C infected donor from sub Saharan Africa. The Abs first acquired autologous neutralization, then gradually matured to achieve breadth. One Ab neutralized >47% of HIV 1 strains with only ~11% somatic hypermutation and no insertions or deletions. By sequencing autologous env, we determined key residues that triggered the lineage and participated in Ab Env coevolution. Next generation sequencing of the Ab repertoire showed an early expansive diversification of the lineage followed by independent maturation of individual limbs, several of them developing notable breadth and potency. Overall, the findings are encouraging from a vaccine standpoint and suggest immunization strategies mimicking the evolution of the entire high mannose patch and promoting maturation of multiple diverse Ab pathways.
Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance.
Venue: Cell metabolism

To investigate the biological processes that are altered in obese subjects, we generated cell specific integrated networks (INs) by merging genome scale metabolic, transcriptional regulatory and protein protein interaction networks. We performed genome wide transcriptomics analysis to determine the global gene expression changes in the liver and three adipose tissues from obese subjects undergoing bariatric surgery and integrated these data into the cell specific INs. We found dysregulations in mannose metabolism in obese subjects and validated our predictions by detecting mannose levels in the plasma of the lean and obese subjects. We observed significant correlations between plasma mannose levels, BMI, and insulin resistance (IR) We also measured plasma mannose levels of the subjects in two additional different cohorts and observed that an increased plasma mannose level was associated with IR and insulin secretion. We finally identified mannose as one of the best plasma metabolites in explaining the variance in obesity independent IR.
Coverage based Neural Machine Translation
Venue: ArXiv

Attention mechanism advanced state of the art neural machine translation (NMT) by jointly learning to align and translate. However, attentional NMT ignores past alignment information, which leads to over translation and undertranslation problems. In response to this problem, we maintain a coverage vector to keep track of the attention history. The coverage vector is fed to the attention model to help adjust the future attention, which guides NMT to pay more attention to the untranslated source words. Experiments show that coverage based NMT significantly improves both alignment and translation quality over NMT without coverage.
Effective Multicultural Supervision for a Culturally Diverse Country.

Living in a country based on the "salad bowl" of cultures philosophy, it is necessary for mental health professionals to be competent in providing effective counseling to heterogeneous clientele. Multicultural counseling ensures that professional counselors will deliver services matching the clients' needs, resulting in valuable treatment. Individuals wishing to become a counselor need guidance in multicultural counseling beyond the instruction given in a classroom. This can be accomplished during supervision from a multiculturally competent supervisor. Effective Multicultural Supervision for a Culturally Diverse Country As the population of the United States of America becomes increasingly diverse with more individuals immigrating to this country than ever before, the mental health field must be prepared to provide optimal services to this diverse population. According to the United States Census Bureau (2016) the estimated race of the population for 2014 was as follows: 62.1% would be identified as White, 17.4% identified as Hispanic or Latino, 13.2% identified as Black or African American, 5.4% identified as Asian, and the remaining 1.9% would be identified as Native Indian, Alaska Native, Native Hawaiian, other Pacific Islander, or being of two or more races. The Census Bureau (2016) also estimated that in 2014, females would comprise 50.8% of the population, whereas males would comprise 49.2% Approximately 23.1% of the 2014 population was estimated to be aged eighteen or younger, and 76.9% would be aged over nineteen (United States Census Bureau, 2016) Finally, the Census Bureau (2016) estimated that in 2014, 14.8% of the population would be considered to be living in poverty, with the medium household income to be $53,482. This exemplifies the salad bowl analogy often used to describe the United States because there is not a single type of American, but rather the country prides itself on a variety of individuals from diverse backgrounds (different races, ethnicities, religions, genders, education, ages, language, socioeconomic statuses, and sexual orientation) coming together to form the larger community. Therefore, mental health professionals in this country must be well versed in the various aspects of providing exceptional counseling to an assorted clientele. There is not a "one size fits all" counseling approach, and it is imperative that professional counselors adequately prepare to assist clients from heterogeneous backgrounds. This process, commonly referred to as multicultural counseling, occurs when two or more individuals from different cultures to come together during
Big Data Classification Using the SVM Classifiers with the Modified Particle Swarm Optimization and the SVM Ensembles

The problem with development of the support vector machine (SVM) classifiers using modified particle swarm optimization (PSO) algorithm and their ensembles has been considered. Solving this problem would allow fulfilling the high precision data classification, especially Big Data classification, with the acceptable time expenditures. The modified PSO algorithm conducts a simultaneous search of the type of kernel functions, the parameters of the kernel function and the value of the regularization parameter for the SVM classifier. The idea of particles' <regeneration> served as the basis for the modified PSO algorithm. In the implementation of this algorithm, some particles change the type of their kernel function to the one which corresponds to the particle with the best value of the classification accuracy. The offered PSO algorithm allows reducing the time expenditures for the developed SVM classifiers, which is very important for Big Data classification problem. In most cases such SVM classifier provides the high quality of data classification. In exceptional cases the SVM ensembles based on the decorrelation maximization algorithm for the different strategies of the decision making on the data classification and the majority vote rule can be used. Also, the two level SVM classifier has been offered. This classifier works as the group of the SVM classifiers at the first level and as the SVM classifier on the base of the modified PSO algorithm at the second level. The results of experimental studies confirm the efficiency of the offered approaches for Big Data classification.
Robust image registration with rotation, scale and translation using Best Buddies Pairs
Venue: 2016 International Joint Conference on Neural Networks (IJCNN)

Since the complex outliers caused by the background and non rigid deformation, image registration remains a challenging task. This paper proposes a new method for image registration, which is robust to the transformations with rotation, scale and translation. Our method is under the general Iterative Closet Point (ICP) framework which contains two main parts: finding the corresponding points and updating transformation parameters. In our method, to be robust to outliers, Best Buddies Pairs (BBPs) are used as similarity measure between two images to obtain the corresponding points. While, in order to be invariant to scale transformation, Scaling ICP is employed to update transformation parameters. Besides the image registration, we also apply the method for object tracking in video sequences. Experimental results demonstrate the effectiveness and efficiency of the proposed method.
A new canon? Contemporary Italian cinema and television and the role of quality in the Anglophone curriculum

ACADEMIC APPOINTMENTS The Ohio State University Professor of Italian, The Department of French and Italian, 2020 Associate Professor of Italian with tenure, The Department of French and Italian, 2014 20 Assistant Professor of Italian, The Department of French and Italian, 2007 2014 Core Faculty: The Film Studies Program Affiliate Faculty: The Department of Comparative Studies; The Department of Women's, Gender, and Sexuality Studies The University of Bologna Affiliate Faculty: Collegio dei Docenti del Dottorato in Arti visive, performative, mediali, 2019