nils-herrmann/clean_scirepeval huggingface dataset:
Mental fatigue, motivation and action monitoring

In this study we examined whether the effects of mental fatigue on behaviour are due to reduced action monitoring as indexed by the error related negativity (Ne/ERN), N2 and contingent negative variation (CNV) event-related potential (ERP) components. Therefore, we had subjects perform a task, which required a high degree of action monitoring, continuously for 2h. In addition we tried to relate the observed behavioural and electrophysiological changes to motivational processes and individual differences. Changes in task performance due to fatigue were accompanied by a decrease in Ne/ERN and N2 amplitude, reflecting impaired action monitoring, as well as a decrease in CNV amplitude which reflects reduced response preparation with increasing fatigue. Increasing the motivational level of our subjects resulted in changes in behaviour and brain activity that were different for individual subjects. Subjects that increased their performance accuracy displayed an increase in Ne/ERN amplitude, while subjects that increased their response speed displayed an increase in CNV amplitude. We will discuss the effects prolonged task performance on the behavioural and physiological indices of action monitoring, as well as the relationship between fatigue, motivation and individual differences.
Could mindfulness decrease anger, hostility, and aggression by decreasing rumination?

Research suggests that rumination increases anger and aggression. Mindfulness, or present-focused and intentional awareness, may counteract rumination. Using structural equation modeling, we examined the relations between mindfulness, rumination, and aggression. In a pair of studies, we found a pattern of correlations consistent with rumination partially mediating a causal link between mindfulness and hostility, anger, and verbal aggression. The pattern was not consistent with rumination mediating the association between mindfulness and physical aggression. Although it is impossible with the current nonexperimental data to test causal mediation, these correlations support the idea that mindfulness could reduce rumination, which in turn could reduce aggression. These results suggest that longitudinal work and experimental manipulations mindfulness would be worthwhile approaches for further study of rumination and aggression. We discuss possible implications of these results.
Modality specific assessment of video game player's experience using the Emotiv

A growing body of literature has emerged that focuses upon cognitive assessment of video game player experience. Given the growing popularity of video gaming and the increasing literature on cognitive aspects of video gamers, there is a growing need for novel approaches to assessment of the cognitive processes that occur while persons are immersed in video games. In this study, we assessed various stimulus modalities and gaming events using an off-the-shelf EEG devise. A significant difference was found among different stimulus modalities with increasingly difficult cognitive demands. Specifically, beta and gamma power were significantly increased during high intensity events when compared to low intensity gaming events. Our findings suggest that the Emotiv EEG can be used to differentiate between varying stimulus modalities and accompanying cognitive processes.
Conditional Risk of Relapse in Surveillance for Clinical Stage I Testicular Cancer.

Patients on surveillance for clinical stage I (CSI) testicular cancer are counseled regarding their baseline risk of relapse. The conditional risk of relapse (cRR), which provides prognostic information on patients who have survived for a period of time without relapse, have not been determined for CSI testicular cancer.



To determine cRR in CSI testicular cancer.



We reviewed 1239 patients with CSI testicular cancer managed with surveillance at a tertiary academic centre between 1980 and 2014.  cRR estimates were calculated using the Kaplan-Meier method. We stratified patients according to validated risk factors for relapse. We used linear regression to determine cRR trends over time.



At orchiectomy, the risk of relapse within 5 yr was 42.4%, 17.3%, 20.3%, and 12.2% among patients with high-risk nonseminomatous germ cell tumor (NSGCT), low-risk NSGCT, seminoma with tumor size ≥3cm, and seminoma with tumor size <3cm, respectively. However, for patients without relapse within the first 2 yr of follow-up, the corresponding risk of relapse within the next 5 yr in the groups was 0.0%, 1.0% (95% confidence interval [CI] 0.3-1.7%), 5.6% (95% CI 3.1-8.2%), and 3.9% (95% CI 1.4-6.4%). Over time, cRR decreased (p≤0.021) in all models. Limitations include changes to surveillance protocols over time and few late relapses.



After 2 yr, the risk of relapse on surveillance for CSI testicular cancer is very low. Consideration should be given to adapting surveillance protocols to individualized risk of relapse based on cRR as opposed to static protocols based on baseline factors. This strategy could reduce the intensity of follow-up for the majority of patients.



Our study is the first to provide data on the future risk of relapse during surveillance for clinical stage I testicular cancer, given a patient has been without relapse for a specified period of time.
An Overview of Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

OFDM (Orthogonal Frequency Division Multiplexing) has been widely adopted for high data rate wireless communication systems due to its advantages such as extraordinary spectral efficiency, robustness to channel fading and better QoS (Quality of Service) performance for multiple users. However, some challenging issues are still unresolved in OFDM systems. One of the issues is the high PAPR (peak-toaverage power ratio), which results in nonlinearity in power amplifiers, and causes out of band radiation and in band distortion. This paper reviews some conventional PAPR reduction techniques and their modifications to achieve better PAPR performance. Advantages and disadvantages of each technique are discussed in detail. And comparisons between different techniques are also presented. Finally, this paper makes a prospect forecast about the direction for further researches in the area of PAPR reduction for OFDM signals.
Applications of Mobius transform in image processing and cryptography

The evaluation results of the Mobius transforms of some often-used waveforms are applied in the image transform. And the method of modulation and demodulation in Chen-Mobius communication systems, which is quite different from the traditional one, is newly used. To make such a processing, the Chen-Mobius inverse transformed functions act as the “modulation” waveforms, and the receiving end coherently “demodulated” by the often-used digital waveforms. Then the image is partitioned in segmentations that are “modulated” and “demodulated” in different waveform sets. Therefore, it's another new method of image cryptography. In additional, the image transform is simulated by the MATLAB software on the computer and the results are discussed in some details.
A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks

This paper presents a novel mobility metric for mobile ad hoc networks (MANET) that is based on the ratio between the received power levels of successive transmissions measured at any node from all its neighboring nodes. This mobility metric is subsequently used as a basis for cluster formation which can be used for improving the scalability of services such as routing in such networks. We propose a distributed clustering algorithm, MOBIC, based on the use of this mobility metric for selection of clusterheads, and demonstrate that it leads to more stable cluster formation than the Lowest-ID clustering algorithm ( “least clusterhead change” ) which is a well known clustering algorithms for MANETs. We show reduction of as much as 33% in the number of clusterhead changes owing to the use of the proposed technique. In a MANET that uses scalable cluster-based services, the network performance metrics such as throughput and delay are tightly coupled with the frequency of cluster reorganization. Therefore, we believe that since using MOBIC results in a more stable configuration, it will directly lead to improvement of performance.
Highly Reproducible Perovskite Solar Cells with Average Efficiency of 18.3% and Best Efficiency of 19.7% Fabricated via Lewis Base Adduct of Lead(II) Iodide.

High efficiency perovskite solar cells were fabricated reproducibly via Lewis base adduct of lead(II) iodide. PbI2 was dissolved in N,N-dimethyformamide with equimolar N,N-dimethyl sulfoxide (DMSO) and CH3NH3I. Stretching vibration of S═O appeared at 1045 cm(-1) for bare DMSO, which was shifted to 1020 and 1015 cm(-1) upon reacting DMSO with PbI2 and PbI2 + CH3NH3I, respectively, indicative of forming the adduct of PbI2·DMSO and CH3NH3I·PbI2·DMSO due to interaction between Lewis base DMSO and/or iodide (I(-)) and Lewis acid PbI2. Spin-coating of a DMF solution containing PbI2, CH3NH3I, and DMSO (1:1:1 mol %) formed a transparent adduct film, which was converted to a dark brown film upon heating at low temperature of 65 °C for 1 min due to removal of the volatile DMSO from the adduct. The adduct-induced CH3NH3PbI3 exhibited high charge extraction characteristics with hole mobility as high as 3.9 × 10(-3) cm(2)/(V s) and slow recombination rate. Average power conversion efficiency (PCE) of 18.3% was achieved from 41 cells and the best PCE of 19.7% was attained via adduct approach.
Reducing the Cost of Implementing Error Correction Codes in Content Addressable Memories

Reliability is a major concern for memories. To ensure that errors do not affect the data stored in a memory, error correction codes (ECCs) are widely used in memories. ECCs introduce an overhead as some bits are added to each word to detect and correct errors. This increases the cost of the memory. Content addressable memories (CAMs) are a special type of memories in which the input is compared with the data stored, and if a match is found, the output is the address of that word. CAMs are used in many computing and networking applications. In this brief, the specific features of CAMs are used to reduce the cost of implementing ECCs. More precisely, the proposed technique eliminates the need to store the ECC bits for each word in the memory. This is done by embedding those bits into the address of the key. The main potential issue of the new scheme is that it restricts the addresses in which a new key can be stored. Therefore, it can occur that a new key cannot be added into the CAM when there are addresses that are not used. This issue is analyzed and evaluated showing that, for large CAMs, it would only occur when the CAM occupancy is close to 100%. Therefore, the proposed scheme can be used to effectively reduce the cost of implementing ECCs in CAMs.
Trait Anxiety Modulates the Neural Efficiency of Inhibitory Control

An impairment of attentional control in the face of threat-related distracters is well established for high-anxious individuals. Beyond that, it has been hypothesized that high trait anxiety more generally impairs the neural efficiency of cognitive processes requiring attentional control—even in the absence of threat-related stimuli. Here, we use fMRI to show that trait anxiety indeed modulates brain activation and functional connectivities between task-relevant brain regions in an affectively neutral Stroop task. In high-anxious individuals, dorsolateral pFC showed stronger task-related activation and reduced coupling with posterior lateral frontal regions, dorsal ACC, and a word-sensitive area in the left fusiform gyrus. These results support the assumption that a general (i.e., not threat-specific) impairment of attentional control leads to reduced neural processing efficiency in anxious individuals. The increased dorsolateral pFC activation is interpreted as an attempt to compensate for suboptimal connectivity within the cortical network subserving task performance.
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning

Driving Scene understanding is a key ingredient for intelligent transportation systems. To achieve systems that can operate in a complex physical and social environment, they need to understand and learn how humans drive and interact with traffic scenes. We present the Honda Research Institute Driving Dataset (HDD), a challenging dataset to enable research on learning driver behavior in real-life environments. The dataset includes 104 hours of real human driving in the San Francisco Bay Area collected using an instrumented vehicle equipped with different sensors. We provide a detailed analysis of HDD with a comparison to other driving datasets. A novel annotation methodology is introduced to enable research on driver behavior understanding from untrimmed data sequences. As the first step, baseline algorithms for driver behavior detection are trained and tested to demonstrate the feasibility of the proposed task.
An abstract framework for argumentation with structured arguments

An abstract framework for structured arguments is presented t hat instantiates Dung’s (1995) abstract argumentation frameworks. Arguments are defined as inference trees formed by applying two kinds of inference rules: strict and defeasible rules. This naturally leads to three ways of attacking an argument: attacking a premise, attacking a conclusion and attacking an inference. To resolve such attacks, preferences may be used, which leads to three corresponding kinds of defeat: un dermining, rebutting and undercutting defeat. The nature of the inference rules, the structure of the logic al language on which they operate and the origin of the preferences are, apart from some basic assumptions, lef t unspecified. The resulting framework integrates work of Pollock, Vreeswi jk and others on the structure of arguments and the nature of defeat, and extends it in several respects. Various rationality postulates are proven to be satisfied by the framework, and several existing approaches a re proven to be a special case of the framework, including assumption-based argumentation and DefLog.
Cellular DNA replicases: components and dynamics at the replication fork.

DNA replicases are multicomponent machines that have evolved clever strategies to perform their function. Although the structure of DNA is elegant in its simplicity, the job of duplicating it is far from simple. At the heart of the replicase machinery is a heteropentameric AAA+ clamp-loading machine that couples ATP hydrolysis to load circular clamp proteins onto DNA. The clamps encircle DNA and hold polymerases to the template for processive action. Clamp-loader and sliding clamp structures have been solved in both prokaryotic and eukaryotic systems. The heteropentameric clamp loaders are circular oligomers, reflecting the circular shape of their respective clamp substrates. Clamps and clamp loaders also function in other DNA metabolic processes, including repair, checkpoint mechanisms, and cell cycle progression. Twin polymerases and clamps coordinate their actions with a clamp loader and yet other proteins to form a replisome machine that advances the replication fork.
A survey on Data Mining Techniques for Crop Yield Prediction

This paper presents the various crop yield prediction methods using data mining techniques. Agricultural system is very complex since it deals with large data situation which comes from a number of factors. Crop yield prediction has been a topic of interest for producers, consultants, and agricultural related organizations. In this paper our focus is on the applications of data mining techniques in agricultural field. Different Data Mining techniques such as K-Means, K-Nearest Neighbor(KNN), Artificial Neural Networks(ANN) and Support Vector Machines(SVM) for very recent applications of data mining techniques in agriculture field. Data mining technology has received a great progress with the rapid development of computer science, artificial intelligence. Data Mining is an emerging research field in agriculture crop yield analysis.  Mining is the process of identifying the hidden patterns from large amount of data. Yield prediction is a very important agricultural problem that remains to be solved based on the available data. The problem of yield prediction can be solved by employing data mining techniques.
A comprehensive framework for modeling set-based business rules during conceptual database design

Business rules are the basis of any organization. From an information systems perspective, these business rules function as constraints on a database helping ensure that the structure and content of the real world—sometimes referred to as miniworld—is accurately incorporated into the database. It is important to elicit these rules during the analysis and design stage, since the captured rules are the basis for subsequent development of a business constraints repository. We present a taxonomy for set-based business rules, and describe an overarching framework for modeling rules that constrain the cardinality of sets. The proposed framework results in various types constraints, i.e., attribute, class, participation, projection, co-occurrence, appearance and overlapping, on a semantic model that supports abstractions like classification, generalization/specialization, aggregation and association. We formally define the syntax of our proposed framework in Backus-Naur Form and explicate the semantics using first-order logic. We describe partial ordering in the constraints and define the concept of metaconstraints, which can be used for automatic constraint consistency checking during the design stage itself. We demonstrate the practicality of our approach with a case study and show how our approach to modeling business rules seamlessly integrates into existing database design methodology. Via our proposed framework, we show how explicitly capturing data semantics will help bridge the semantic gap between the real world and its representation in an information system. r 2003
Canine substitution of a missing maxillary lateral incisor in an orthodontic retreatment case : long term follow up Case report

This case report describes the orthodontic re-treatment of a case with a severely compromised maxillary lateral incisor requiring removal and canine substitution. The treatment included creative asymmetric treatment mechanics and a careful management of anchorage.  Pre-treatment, post treatment and 5 years follow-up records are shown. The treatment outcomes proved to be stable at the follow-up with acceptable aesthetic and functional results.  Through careful management of anchorage it was possible to successfully use asymmetric treatment mechanics to achieve a good functional occlusion.  2016;  January 29, 2017;  2017 Lupini D, Lempert S, Cozzani M. Canine substitution of a missing maxillary lateral incisor in an orthodontic re-treatment case: long term follow up.  Missing maxillary lateral incisor 15 The clinical presentation of a patient missing one or both maxillary lateral incisors can vary and through careful planning and ingenuity the orthodontist can develop a plan that takes into account the patient’s unique findings. With multiple treatment options available it is best to have the patient’s pre-treatment expectations aligned with the doctor’s treatment goals to provide the best opportunity for patient satisfaction. The following case report shows the creative management of a severely compromised maxillary lateral incisor that had been subject to failed prior treatment attempts. Literature reports many cases of canine substitution of missing lateral incisor, but very few reports are associated with severe root resorption conditions. 8,9 Ultimately, this tooth required removal and canine substitution. Through asymmetric treatment mechanics it was possible to achieve a pleasing, functional smile and a satisfied patient.
Oromandibular Dystonia: A Case Report of the Lateral Pterygoid Muscle Involvement and Treatment with Botulinum Toxin A

The objective of the present case report is to punctuate the importance of individualized therapy procedures and the accurate diagnosis of the muscles involved in oromandibular dystonia and underline the role of electromyography (EMG). We report a woman who presented sustained jaw movement towards the left, severe difficulty in jaw opening and jaw protrusion. The patient was treated with injections of botulinum A toxin in lateral pterygoid, masseter, platysma, sternoclidomastoid, temporalis muscles with EMG guidance. She experienced an 80% reduction of her symptoms after the first injection. In jaw deviation dystonia symptoms impressively respond to botulinum toxin treatment of the pterygoid muscle. Individualized therapy procedures are necessitated.
Story extraction from the Web: A case study in security informatics

Open source intelligence is becoming more and more important in security-related applications. Effective extraction of valuable information from these intelligence sources so as to understand the content of intelligence is one of the central issues in security domain. To address this key problem, this paper studies how to extract domain events and generate story representation of the events. We implement a story extraction platform (SEP) which applies pattern matching to extract events from Web news and organizes events based on theme using narrative structure. We also design extraction rules, use domain-specific features and employ ontology to facilitate story extraction in SEP. The experimental results show the effectiveness of our system in security informatics.
Fractionation and purification of the enzymes stored in the latex of Carica papaya.

The latex of the tropical species Carica papaya is well known for being a rich source of the four cysteine endopeptidases papain, chymopapain, glycyl endopeptidase and caricain. Altogether, these enzymes are present in the laticifers at a concentration higher than 1 mM. The proteinases are synthesized as inactive precursors that convert into mature enzymes within 2 min after wounding the plant when the latex is abruptly expelled. Papaya latex also contains other enzymes as minor constituents. Several of these enzymes namely a class-II and a class-III chitinase, an inhibitor of serine proteinases and a glutaminyl cyclotransferase have already been purified up to apparent homogeneity and characterized. The presence of a beta-1,3-glucanase and of a cystatin is also suspected but they have not yet been isolated. Purification of these papaya enzymes calls on the use of ion-exchange supports (such as SP-Sepharose Fast Flow) and hydrophobic supports [such as Fractogel TSK Butyl 650(M), Fractogel EMD Propyl 650(S) or Thiophilic gels]. The use of covalent or affinity gels is recommended to provide preparations of cysteine endopeptidases with a high free thiol content (ideally 1 mol of essential free thiol function per mol of enzyme). The selective grafting of activated methoxypoly(ethylene glycol) chains (with M(r) of 5000) on the free thiol functions of the proteinases provides an interesting alternative to the use of covalent and affinity chromatographies especially in the case of enzymes such as chymopapain that contains, in its native state, two thiol functions.