nils-herrmann/clean_scirepeval huggingface dataset:
Deep Class Aware Denoising

The increasing demand for high image quality in mobile devices brings forth the need for better computational enhancement techniques, and image denoising in particular. At the same time, the images captured by these devices can be categorized into a small set of semantic classes. However simple, this observation has not been exploited in image denoising until now. In this paper, we demonstrate how the reconstruction quality improves when a denoiser is aware of the type of content in the image. To this end, we first propose a new fully convolutional deep neural network architecture which is simple yet powerful as it achieves state-of-the-art performance even without being class-aware. We further show that a significant boost in performance of up to 0.4 dB PSNR can be achieved by making our network class-aware, namely, by fine-tuning it for images belonging to a specific semantic class. Relying on the hugely successful existing image classifiers, this research advocates for using a class-aware approach in all image enhancement tasks.
MSClique: Multiple Structure Discovery through the Maximum Weighted Clique Problem

We present a novel approach for feature correspondence and multiple structure discovery in computer vision. In contrast to existing methods, we exploit the fact that point-sets on the same structure usually lie close to each other, thus forming clusters in the image. Given a pair of input images, we initially extract points of interest and extract hierarchical representations by agglomerative clustering. We use the maximum weighted clique problem to find the set of corresponding clusters with maximum number of inliers representing the multiple structures at the correct scales. Our method is parameter-free and only needs two sets of points along with their tentative correspondences, thus being extremely easy to use. We demonstrate the effectiveness of our method in multiple-structure fitting experiments in both publicly available and in-house datasets. As shown in the experiments, our approach finds a higher number of structures containing fewer outliers compared to state-of-the-art methods.
Fast and accurate analysis of scanning slotted waveguide arrays

An iterative procedure is presented for a fast and accurate analysis of scanning slotted waveguide arrays including the effects of mutual couplings and their dependence on the scanning angle. The analysis takes also into account the input transitions from the feeding network; each slotted waveguide being excited either at one end or at the centre. The procedure is applied to the simple case of a linear array of four slots, for which a full-wave analysis could be carried out for comparison. The proposed method is shown to provide excellent agreement with the full-wave computation still requiring extremely short computation times.
The Potential of Neuromarketing as a Marketing Tool

In recent years, the emerging field of neuromarketing, which makes use of brain research in a managerial context, has gained increasing popularity in the academic literature as well as the practical world. Therefore, the purpose of the present paper is to evaluate upon the influence of neuromarketing tools on traditional marketing inputs in order to complete the understanding of consumer behavior. Yet, no available neuromarketing study provided an detailed overview of neuromarketing‘s influence on traditional marketing inputs while considering technical as well as ethical issues. The article uses the approach of an in-depth literature review in order to do so. The increased use of neuromarketing techniques for the evaluation of customer preferences and decision-making processes is considered to be an advantage for customers and marketers simultaneously. EEG, fMRI and MEG rank among the most appropriate technicalities in the area of neuroscience. However, critics emphasize the restriction of the consumer‘s free will and their reduced ability to make individual decisions in their buying behavior due to neuromarketing‘s implementation. After an evaluation of Outside reflexes, input-/Output models and Inside reflexes to analyze brain activities, the current paper evaluates upon the influence of neuromarketing on different relevant marketing inputs, followed by the consideration of its ethical defensibleness. The results indicate that neuromarketing is associated to have a high influence on consumer buying behavior, advertising, pricing, distribution of products, branding and decision-making as marketing inputs. Therefore, neuromarketing may be considered to be a remarkable extension in the research of human behavior and the brain as the ―black box‖ which can positively contribute to its practical applicableness.  Efthymios Constantinides
Expertness based cooperative Q-learning

By using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rules for unseen situations. These benefits would be gained if the learning agent can extract proper rules from the other agents' knowledge for its own requirements. One possible way to do this is to have the learner assign some expertness values (intelligence level values) to the other agents and use their knowledge accordingly. Some criteria to measure the expertness of the reinforcement learning agents are introduced. Also, a new cooperative learning method, called weighted strategy sharing (WSS) is presented. In this method, each agent measures the expertness of its teammates and assigns a weight to their knowledge and learns from them accordingly. The presented methods are tested on two Hunter-Prey systems. We consider that the agents are all learning from each other and compare them with those who cooperate only with the more expert ones. Also, the effect of communication noise, as a source of uncertainty, on the cooperative learning method is studied. Moreover, the Q-table of one of the cooperative agents is changed randomly and its effects on the presented methods are examined.
Dysfunction of ventral striatal reward prediction in schizophrenia

Negative symptoms may be associated with dysfunction of the brain reward system in schizophrenia. We used functional magnetic resonance imaging (fMRI) to assess the BOLD response in the ventral striatum of unmedicated schizophrenics during presentation of reward-indicating and loss-indicating stimuli.



A total of 10 schizophrenic men (7 never medicated, 3 unmedicated for at least 2 years) and 10 age-matched healthy male volunteers participated in an incentive monetary delay task, in which visual cues predicted that a rapid response to a subsequent target stimulus would result either in monetary gain or loss or would have no consequence.



Compared to healthy controls, unmedicated schizophrenics showed reduced ventral striatal activation during the presentation of reward-indicating cues. Decreased activation of the left ventral striatum was inversely correlated with the severity of negative (and trendwise positive) symptoms.



Reduced activation in one of the central areas of the brain reward system, the ventral striatum, was correlated with the severity of negative symptoms in medication-free schizophrenics. In unmedicated schizophrenic patients, a high striatal dopamine turnover may increase the "noise" in the reward system, thus interfering with the neuronal processing of reward-predicting cues by phasic dopamine release. This, in turn, may contribute to negative symptoms as such as anhedonia, apathy, and loss of drive and motivation.
Generating Sentence Planning Variations for Story Telling

There has been a recent explosion in applications for dialogue interaction ranging from direction-giving and tourist information to interactive story systems. Yet the natural language generation (NLG) component for many of these systems remains largely handcrafted. This limitation greatly restricts the range of applications; it also means that it is impossible to take advantage of recent work in expressive and statistical language generation that can dynamically and automatically produce a large number of variations of given content. We propose that a solution to this problem lies in new methods for developing language generation resources. We describe the ES-TRANSLATOR, a computational language generator that has previously been applied only to fables, and quantitatively evaluate the domain independence of the EST by applying it to personal narratives from weblogs. We then take advantage of recent work on language generation to create a parameterized sentence planner for story generation that provides aggregation operations, variations in discourse and in point of view. Finally, we present a user evaluation of different personal narrative retellings.
Hypothesis Only Baselines in Natural Language Inference

We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI). Especially when an NLI dataset assumes inference is occurring based purely on the relationship between a context and a hypothesis, it follows that assessing entailment relations while ignoring the provided context is a degenerate solution. Yet, through experiments on ten distinct NLI datasets, we find that this approach, which we refer to as a hypothesis-only model, is able to significantly outperform a majorityclass baseline across a number of NLI datasets. Our analysis suggests that statistical irregularities may allow a model to perform NLI in some datasets beyond what should be achievable without access to the context.
Genotyping by Sequencing for SNP-Based Linkage Analysis and Identification of QTLs Linked to Fruit Quality Traits in Japanese Plum (Prunus salicina Lindl.)

Marker-assisted selection (MAS) in stone fruit (Prunus species) breeding is currently difficult to achieve due to the polygenic nature of the most relevant agronomic traits linked to fruit quality. Genotyping by sequencing (GBS), however, provides a large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from a reference genome. In this study, GBS was used to genotype 272 seedlings of three F1 Japanese plum (Prunus salicina Lindl) progenies derived from crossing "98-99" (as a common female parent) with "Angeleno," "September King," and "September Queen" as male parents. Raw sequences were aligned to the Peach genome v1, and 42,909 filtered SNPs were obtained after sequence alignment. In addition, 153 seedlings from the "98-99" × "Angeleno" cross were used to develop a genetic map for each parent. A total of 981 SNPs were mapped (479 for "98-99" and 502 for "Angeleno"), covering a genetic distance of 688.8 and 647.03 cM, respectively. Fifty five seedlings from this progeny were phenotyped for different fruit quality traits including ripening time, fruit weight, fruit shape, chlorophyll index, skin color, flesh color, over color, firmness, and soluble solids content in the years 2015 and 2016. Linkage-based QTL analysis allowed the identification of genomic regions significantly associated with ripening time (LG4 of both parents and both phenotyping years), fruit skin color (LG3 and LG4 of both parents and both years), chlorophyll degradation index (LG3 of both parents in 2015) and fruit weight (LG7 of both parents in 2016). These results represent a promising situation for GBS in the identification of SNP variants associated to fruit quality traits, potentially applicable in breeding programs through MAS, in a highly heterozygous crop species such as Japanese plum.
How do you feel? Interoception: the sense of the physiological condition of the body

As humans, we perceive feelings from our bodies that relate our state of well-being, our energy and stress levels, our mood and disposition. How do we have these feelings? What neural processes do they represent? Recent functional anatomical work has detailed an afferent neural system in primates and in humans that represents all aspects of the physiological condition of the physical body. This system constitutes a representation of 'the material me', and might provide a foundation for subjective feelings, emotion and self-awareness.
Applying the design structure matrix to system decomposition and integration problems: a review and new directions

Systems engineering of products, processes, and organizations requires tools and techniques for system decomposition and integration. A design structure matrix (DSM) provides a simple, compact, and visual representation of a complex system that supports innovative solutions to decomposition and integration problems. The advantages of DSMsvis-à-visalternative system representation and analysis techniques have led to their increasing use in a variety of contexts, including product development, project planning, project management, systems engineering, and organization design. This paper reviews two types of DSMs, static and time-based DSMs, and four DSM applications: 1) Component-Basedor Architecture DSM, useful for modeling system component relationships and facilitating appropriate architectural decomposition strategies; 2) Team-Basedor Organization DSM, beneficial for designing integrated organization structures that account for team interactions; 3)Activity-Basedor Schedule DSM, advantageous for modeling the information flow among process activities; and 4)Parameter-Based(or low-level schedule)DSM, effective for integrating low-level design processes based on physical design parameter relationships. A discussion of each application is accompanied by an industrial example. The review leads to conclusions regarding the benefits of DSMs in practice and barriers to their use. The paper also discusses research directions and new DSM applications, both of which may be approached with a perspective on the four types of DSMs and their relationships.
A comparison between Chinese and Caucasian head shapes.

Univariate anthropometric data have long documented a difference in head shape proportion between Chinese and Caucasian populations. This difference has made it impossible to create eyewear, helmets and facemasks that fit both groups well. However, it has been unknown to what extend and precisely how the two populations differ from each other in form. In this study, we applied geometric morphometrics to dense surface data to quantify and characterize the shape differences using a large data set from two recent 3D anthropometric surveys, one in North America and Europe, and one in China. The comparison showed the significant variations between head shapes of the two groups and results demonstrated that Chinese heads were rounder than Caucasian counterparts, with a flatter back and forehead. The quantitative measurements and analyses of these shape differences may be applied in many fields, including anthropometrics, product design, cranial surgery and cranial therapy.
Functional Neuroanatomy of Emotion: A Meta-Analysis of Emotion Activation Studies in PET and fMRI

Neuroimagingstudies with positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have begun to describe the functional neuroanatomy of emotion. Taken separately, specific studies vary in task dimensions and in type(s) of emotion studied and are limited by statistical power and sensitivity. By examining findings across studies, we sought to determine if common or segregated patterns of activations exist across various emotional tasks. We reviewed 55 PET and fMRI activation studies (yielding 761 individual peaks) which investigated emotion in healthy subjects. Peak activation coordinates were transformed into a standard space and plotted onto canonical 3-D brain renderings. We divided the brain into 20 nonoverlapping regions, and characterized each region by its responsiveness across individual emotions (positive, negative, happiness, fear, anger, sadness, disgust), to different induction methods (visual, auditory, recall/imagery), and in emotional tasks with and without cognitive demand. Our review yielded the following summary observations: (1) The medial prefrontal cortex had a general role in emotional processing; (2) fear specifically engaged the amygdala; (3) sadness was associated with activity in the subcallosal cingulate; (4) emotional induction by visual stimuli activated the occipital cortex and the amygdala; (5) induction by emotional recall/imagery recruited the anterior cingulate and insula; (6) emotional tasks with cognitive demand also involved the anterior cingulate and insula. This review provides a critical comparison of findings across individual studies and suggests that separate brain regions are involved in different aspects of emotion.
On the Efficiency of Far-Field Wireless Power Transfer

Far-field wireless power transfer (WPT) is a promising technique to resolve the painstaking power-charging problem inherent in various wireless terminals. This paper investigates the power transfer efficiency of the WPT segment in future communication systems in support of simultaneous power and data transfer, by means of analytically computing the time-average output direct current (DC) power at user equipments (UEs). In order to investigate the effect of channel variety among UEs on the average output DC power, different policies for the scheduling of the power transfer among the users are implemented and compared in two scenarios: homogeneous, whereby users are symmetric and experience similar path loss, and heterogeneous, whereby users are asymmetric and exhibit different path losses. Specifically, if opportunistic scheduling is performed among N symmetric/asymmetric UEs, the power scaling laws are attained by using extreme value theory and reveal that the gain in power transfer efficiency is lnN if UEs are symmetric whereas the gain is N if UEs are asymmetric, compared with that of conventional round-robin scheduling. Thus, the channel variety among UEs inherent to the wireless environment can be exploited by opportunistic scheduling to significantly improve the power transfer efficiency when designing future wireless communication systems in support of simultaneous power and data transfer.
A Four-Switch Single-Stage Single-Phase Buck–Boost Inverter

This paper proposes a single-phase, single-stage buck–boost inverter for photovoltaic (PV) systems. The presented topology has one common terminal in input and output ports which eliminates common mode leakage current problem in the grid-connected PV applications. Although it uses four switches, its operation is bimodal and only two switches receive high-frequency pulse width modulation signals in each mode. Its principle of operation is described in detail with the help of equivalent circuits. Its dynamic model is presented, based on which a bimodal controller is designed. Experimental results, in stand-alone and grid-connected mode, obtained with a 300-W laboratory prototype are presented to validate its performance.
Effectiveness of Structured Teaching Program on Knowledge , Attitude and Management Strategies Among Teachers of Primary School toward Children with Attention Deficit Hyperactivity Disorders .

Children with ADHD often experience problems in interpersonal and academic relationships and achievements, which are typically suffer serious problems for themselves and those care for them (involve their teachers)  The study aimed at assessing the knowledge, attitude and behavior strategies among teachers of governmental primary school , evaluate the effectiveness of a of structured teaching program on knowledge, attitude and behavior strategies among teachers of governmental primary school.  Quasi-experimental design (one group pre –posttest group) was utilized in this study.  The present study was conducted at the west Qaluibya primary schools. Sample: Convenience purposive sample consisted of 60 teachers of primary schools were participated from 5 primary schools.  Three tools were used to collect the data for the current study, first, socio demographic data sheet. Second, teachers’ knowledge scale, teachers’ attitude scale, and Third, behaviors management strategies scale. A structured teaching program design to improve teacher’s knowledge and change attitude and behaviors management strategies toward children with attention deficit hyperactivity disorder(ADHD). This program was implemented over 15 sessions, three sessions per week(session every other day) and each session for about 4560 minutes. Pre-and post-assessment were carried out for the same group (selfcontrol group).  The current study results revealedl significant positive effects of structure program regarding teachers’ knowledge, attitude and behavior management strategies regarding children with ADHD. Some demographic variables as ages, educational qualifications, and Years of teaching Experience had a significant Positive correlation with post assessment teachers’ knowledge.  the study concluded that a Structured Teaching Program was effective with teachers of selected primary schools on improving their knowledge, change attitude and behavior management strategies into more positively one. The study recommended the need to implement this program at others primary schools in different setting for further benefits.
CONCEPT LEVEL NAVAL SURFACE COMBATANT DESIGN IN THE AXIOMATIC APPROACH TO DESIGN FRAMEWORK LCDR

The design of ships is an inherently complex process. This complexity is significantly increased when the particular ship being designed is a naval surface combatant. Naval combatant designers, or more appropriately, design teams, must not only address the factors common to all seagoing vessels such as hull form, propulsion, and maneuverability, but additionally must consider the selection, placement, and interaction of sophisticated weapons systems and sensors. The ship design process is traditionally viewed as a highly coupled collection of interrelated physical attributes often determined in an ad hoc fashion. Therefore, lack of understanding and documenting the design progression frequently necessitates modification of a completely developed, functionally acceptable portion of the ship because of its adverse effect on other functionally unrelated parameters. This paper proposes a methodology based on axiomatic design principles that strives to eliminate the currently accepted iterative nature of concept level ship design. By implementing this approach, the ship design process follows a repeatable structured format in which functional relationships between physical parameters are mapped, documented, and controlled. The AAD method is applied to a ship synthesis model, and a new ship design process is defined and coded to illustrate the utility of the method.