nils-herrmann/clean_scirepeval huggingface dataset:
Wide phenotypic variability in families with holoprosencephaly and a sonic hedgehog mutation

Mutations in the human sonic hedgehog gene ( SHH) are the most frequent cause of autosomal dominant inherited holoprosencephaly (HPE), a complex brain malformation resulting from incomplete cleavage of the developing forebrain into two separate hemispheres and ventricles. Here we report the clinical and molecular findings in five unrelated patients with HPE and their relatives with an identified SHH mutation. Three new and one previously reported SHH mutations were identified, a fifth proband was found to carry a reciprocal subtelomeric rearrangement involving the SHH locus in 7q36. An extremely wide intrafamilial phenotypic variability was observed, ranging from the classical phenotype with alobar HPE accompanied by typical severe craniofacial abnormalities to very mild clinical signs of choanal stenosis or solitary median maxillary central incisor (SMMCI) only. Two families were initially ascertained because of microcephaly in combination with developmental delay and/or mental retardation and SMMCI, the latter being a frequent finding in patients with an identified SHH mutation. In other affected family members a delay in speech acquisition and learning disabilities were the leading clinical signs.  mutational analysis of the sonic hedgehog gene should not only be considered in patients presenting with the classical holoprosencephaly phenotype but also in those with two or more clinical signs of the wide phenotypic spectrum of associated abnormalities, especially in combination with a positive family history.
Alpha particle and neutron-induced soft error rates and scaling trends in SRAM

We performed underground real-time tests to obtain alpha particle-induced soft error rates (α-SER) with high accuracies for SRAMs with 180 nm – 90 nm technologies and studied the scaling trend of α-SERs. In order to estimate the maximum permissive rate of alpha emission from package resin, the α-SER was compared to the neutron-induced soft error rate (n-SER) obtained from accelerated tests. We found that as devices are scaled down, the α-SER increased while the n-SER slightly decreased, and that the α-SER could be greater than the n-SER in 90 nm technology even when the ultra-low-alpha (ULA) grade, with the alpha emission rate ≫ 1 × 10<sup>−3</sup> cm<sup>−2</sup>h<sup>−1</sup>, was used for package resin. We also performed computer simulations to estimate scaling trends of both α-SER and n-SER up to 45 nm technologies, and noticed that the α-SER decreased from 65 nm technology while the n-SER increased from 45 nm technology due to direct ionization from the protons generated in the n + Si nuclear reaction.
The Bayesian brain: Phantom percepts resolve sensory uncertainty

Phantom perceptions arise almost universally in people who sustain sensory deafferentation, and in multiple sensory domains. The question arises 'why' the brain creates these false percepts in the absence of an external stimulus? The model proposed answers this question by stating that our brain works in a Bayesian way, and that its main function is to reduce environmental uncertainty, based on the free-energy principle, which has been proposed as a universal principle governing adaptive brain function and structure. The Bayesian brain can be conceptualized as a probability machine that constantly makes predictions about the world and then updates them based on what it receives from the senses. The free-energy principle states that the brain must minimize its Shannonian free-energy, i.e. must reduce by the process of perception its uncertainty (its prediction errors) about its environment. As completely predictable stimuli do not reduce uncertainty, they are not worthwhile of conscious processing. Unpredictable things on the other hand are not to be ignored, because it is crucial to experience them to update our understanding of the environment. Deafferentation leads to topographically restricted prediction errors based on temporal or spatial incongruity. This leads to an increase in topographically restricted uncertainty, which should be adaptively addressed by plastic repair mechanisms in the respective sensory cortex or via (para)hippocampal involvement. Neuroanatomically, filling in as a compensation for missing information also activates the anterior cingulate and insula, areas also involved in salience, stress and essential for stimulus detection. Associated with sensory cortex hyperactivity and decreased inhibition or map plasticity this will result in the perception of the false information created by the deafferented sensory areas, as a way to reduce increased topographically restricted uncertainty associated with the deafferentation. In conclusion, the Bayesian updating of knowledge via active sensory exploration of the environment, driven by the Shannonian free-energy principle, provides an explanation for the generation of phantom percepts, as a way to reduce uncertainty, to make sense of the world.
Wearable Vibrotactile Haptic Device for Stiffness Discrimination during Virtual Interactions

In this paper, we discuss the development of cost effective, wireless, and wearable vibrotactile haptic device for stiffness perception during an interaction with virtual objects. Our experimental setup consists of haptic device with five vibrotactile actuators, virtual reality environment tailored in Unity 3D integrating the Oculus Rift Head Mounted Display (HMD) and the Leap Motion controller. The virtual environment is able to capture touch inputs from users. Interaction forces are then rendered at 500 Hz and fed back to the wearable setup stimulating fingertips with ERM vibrotactile actuators. Amplitude and frequency of vibrations are modulated proportionally to the interaction force to simulate the stiffness of a virtual object. A quantitative and qualitative study is done to compare the discrimination of stiffness on virtual linear spring in three sensory modalities: visual only feedback, tactile only feedback, and their combination. A common psychophysics method called the Two Alternative Forced Choice (2AFC) approach is used for quantitative analysis using Just Noticeable Difference (JND) and Weber Fractions (WF). According to the psychometric experiment result, average Weber fraction values of 0.39 for visual only feedback was improved to 0.25 by adding the tactile feedback.
An Internet computing model for ensuring continuity of healthcare

The lack of an integrated medical information service model has been considered as a main issue in ensuring the continuity of healthcare from doctors, healthcare professionals to patients; the resultant unavailable, inaccurate, or unconformable healthcare information services have been recognized as main causes to the annual millions of medication errors. This paper proposes an Internet computing model aimed at providing an affordable, interoperable, ease of integration, and systematic approach to the development of a medical information service network to enable the delivery of continuity of healthcare. Web services, wireless, and advanced automatic identification technologies are fully integrated in the proposed service model. Some preliminary research results are presented.
Men’s Experiences of the Criminal Justice System Following Female Perpetrated Intimate Partner Violence

The current study aimed to explore men’s experience of the UK Criminal Justice System (CJS) following female-perpetrated intimate partner violence (IPV). Unstructured face-to-face and Skype interviews were conducted with six men aged between 40–65 years. Interviews were transcribed and analysed using interpretative phenomenological analysis (IPA). Due to the method of analysis and the sensitive nature of the research, the researcher engaged in a process of reflexivity. Four main themes were identified, including ‘Guilty until Proven Innocent: Victim Cast as Perpetrator;’ ‘Masculine Identity;’ ‘Psychological Impact’ and ‘Light at the End of the Tunnel.’ Themes were discussed and illustrated with direct quotes drawn from the transcripts. Directions for future research, criminal justice interventions, and therapeutic interventions were discussed.
Sentiment Learning on Product Reviews via Sentiment Ontology Tree

Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierarchical relationships of products attributes is not fully utilized. (2) Reviews or sentences mentioning several attributes associated with complicated sentiments are not dealt with very well. In this paper, we propose a novel HL-SOT approach to labeling a product’s attributes and their associated sentiments in product reviews by a Hierarchical Learning (HL) process with a defined Sentiment Ontology Tree (SOT). The empirical analysis against a humanlabeled data set demonstrates promising and reasonable performance of the proposed HL-SOT approach. While this paper is mainly on sentiment analysis on reviews of one product, our proposed HLSOT approach is easily generalized to labeling a mix of reviews of more than one products.
Generalization in Interactive Networks: The Benefits of Inhibitory Competition and Hebbian Learning

Computational models in cognitive neuroscience should ideally use biological properties and powerful computational principles to produce behavior consistent with psychological findings. Error-driven backpropagation is computationally powerful and has proven useful for modeling a range of psychological data but is not biologically plausible. Several approaches to implementing backpropagation in a biologically plausible fashion converge on the idea of using bid irectional activation propagation in interactive networks to convey error signals. This article demonstrates two main points about these error-driven interactive networks: (1) they generalize poorly due to attractor dynamics that interfere with the network's ability to produce novel combinatorial representations systematically in response to novel inputs, and (2) this generalization problem can be remedied by adding two widely used mechanistic principles, inhibitory competition and Hebbian learning, that can be independently motivated for a variety of biological, psychological, and computational reasons. Simulations using the Leabra algorithm, which combines the generalized recirculation (GeneRec), biologically plausible, error-driven learning algorithm with inhibitory competition and Hebbian learning, show that these mechanisms can result in good generalization in interactive networks. These results support the general conclusion that cognitive neuroscience models that incorporate the core mechanistic principles of interactivity, inhibitory competition, and error-driven and Hebbian learning satisfy a wider range of biological, psychological, and computational constraints than models employing a subset of these principles.
Satisficing Awakens : Models to Mitigate Uncertainty

Satisficing, as an approach to decision-making under uncertainty, aims at achieving solutions that satisfy the problem’s constraints as well as possible. Mathematical optimization problems that are related to this form of decision-making include the P-model of Charnes and Cooper (1963), where satisficing is the objective, as well as chance-constrained and robust optimization problems, where satisficing is articulated in the constraints. In this paper, we first propose the R-model, where satisficing is the objective, and where the problem consists in finding the most “robust” solution, feasible in the problem’s constraints when uncertain outcomes arise over a maximally sized uncertainty set. We then study the key features of satisficing decision making that are associated with these problems and provide the complete functional characterization of a satisficing decision criterion. As a consequence, we are able to provide the most general framework of a satisficing model, termed the S-model, which seeks to maximize a satisficing decision criterion in its objective, and the corresponding satisficing-constrained optimization problem that generalizes robust optimization and chance-constrained optimization problems. Next, we focus on a tractable probabilistic S-model, termed the T-model whose objective is a lower bound of the P-model. We show that when probability densities of the uncertainties are log-concave, the T-model can admit a tractable concave objective function. In the case of discrete probability distributions, the T-model is a linear mixed integer program of moderate dimensions. We also show how the T-model can be extended to multi-stage decision-making and present the conditions under which the problem is computationally tractable. Our computational experiments on a stochastic maximum coverage problem strongly suggest that the T-model solutions can be highly effective, thus allaying misconceptions of having to pay a high price for the satisficing models in terms of solution conservativeness.
Encoding of emotional memories depends on amygdala and hippocampus and their interactions

We have studied patients with variable degrees of left hippocampal and amygdala pathology who performed a verbal encoding task during functional magnetic resonance imaging (fMRI) to assess the impact of pathology on emotional-memory performance and encoding-evoked activity. The severity of left hippocampal pathology predicted memory performance for neutral and emotional items alike, whereas the severity of amygdala pathology predicted memory performance for emotional items alone. Encoding-related hippocampal activity for successfully remembered emotional items correlated with the degree of left amygdala pathology. Conversely, amygdala-evoked activity with respect to subsequently remembered emotional items correlated with the degree of left hippocampal pathology. Our data indicate a reciprocal dependence between amygdala and hippocampus during the encoding of emotional memories.
Automation: What It Means to Us Around the World

The meaning of the term automation is reviewed through its definition and related definitions, historical evolution, technological progress, benefits and risks, and domains and levels of applications. A survey of 331 people around the world adds insights to the current meaning of automation to people, with regard to: What is your definition of automation? Where did you encounter automation first in your life? and What is the most important contribution of automation to society? The survey respondents include 12 main aspects of the definition in their responses; 62 main types of first automation encounter; and 37 types of impacts, mostly benefits but also two benefit–risks combinations: replacing humans, and humans’ inability to complete tasks by themselves. The most exciting contribution of automation found in the survey was to encourage/inspire creative work; inspire newer solutions. Minor variations were found in different regions of the world. Responses about the first automation encounter are somewhat related to the age of the respondent, e.g., pneumatic versus digital control, and to urban versus farming childhood environment. The chapter concludes with several emerging trends in bioinspired automation, collaborative control and automation, and risks to anticipate and eliminate.
The Influence Of Personality And Organizational Culture On Employee Performance Through Organizational Citizenship Behavior

This study is aimed to determine the effect of the employee’s personality and organizational culture toward the employee’s performance through the BPR OCB throughout the Gianyar district of Bali province. This study used a quantitative approach to test the hypotheses by the sampling technique proportional simple random sampling of the 105 respondents who are employees not the leader of BPR in Gianyar Bali, the data collecting used in this study is a questionnaire. The data analysis technique used SEM analysis. The results showed that the employee’s personality and organizational culture have an indirect effect on employee performance through OCB of all of BPR in Gianyar Bali.
Avoiding common pitfalls in qualitative data collection and transcription.

The subjective nature of qualitative research necessitates scrupulous scientific methods to ensure valid results. Although qualitative methods such as grounded theory, phenomenology, and ethnography yield rich data, consumers of research need to be able to trust the findings reported in such studies. Researchers are responsible for establishing the trustworthiness of qualitative research through a variety of ways. Specific challenges faced in the field can seriously threaten the dependability of the data. However, by minimizing potential errors that can occur when doing fieldwork, researchers can increase the trustworthiness of the study. The purpose of this article is to present three of the pitfalls that can occur in qualitative research during data collection and transcription: equipment failure, environmental hazards, and transcription errors. Specific strategies to minimize the risk for avoidable errors will be discussed.
Sex differences in response to children ’ s toys in nonhuman primates ( Cercopithecus aethiops sabaeus )

Sex differences in children’s toy preferences are thought by many to arise from gender socialization. However, evidence from patients with endocrine disorders suggests that biological factors during early development (e.g., levels of androgens) are influential. In this study, we found that vervet monkeys (Cercopithecus aethiops sabaeus) show sex differences in toy preferences similar to those documented previously in children. The percent of contact time with toys typically preferred by boys (a car and a ball) was greater in male vervets (n = 33) than in female vervets (n = 30) (P < .05), whereas the percent of contact time with toys typically preferred by girls (a doll and a pot) was greater in female vervets than in male vervets (P < .01). In contrast, contact time with toys preferred equally by boys and girls (a picture book and a stuffed dog) was comparable in male and female vervets. The results suggest that sexually differentiated object preferences arose early in human evolution, prior to the emergence of a distinct hominid lineage. This implies that sexually dimorphic preferences for features (e.g., color, shape, movement) may have evolved from differential selection pressures based on the different behavioral roles of males and females, and that evolved object feature preferences may contribute to present day sexually dimorphic toy preferences in children. D 2002 Elsevier Science Inc. All rights reserved.
A probabilistic model for food image recognition in restaurants

A large amount of food photos are taken in restaurants for diverse reasons. This dish recognition problem is very challenging, due to different cuisines, cooking styles and the intrinsic difficulty of modeling food from its visual appearance. Contextual knowledge is crucial to improve recognition in such scenario. In particular, geocontext has been widely exploited for outdoor landmark recognition. Similarly, we exploit knowledge about menus and geolocation of restaurants and test images. We first adapt a framework based on discarding unlikely categories located far from the test image. Then we reformulate the problem using a probabilistic model connecting dishes, restaurants and geolocations. We apply that model in three different tasks: dish recognition, restaurant recognition and geolocation refinement. Experiments on a dataset including 187 restaurants and 701 dishes show that combining multiple evidences (visual, geolocation, and external knowledge) can boost the performance in all tasks.
Object figure-ground segmentation using zero-shot learning

We consider the problem of object figure-ground segmentation when the object categories are not available during training (i.e. zero-shot). During training, we learn standard segmentation models for a handful of object categories (called “source objects”) using existing semantic segmentation datasets. During testing, we are given images of objects (called “target objects”) that are unseen during training. Our goal is to segment the target objects from the background. Our method learns to transfer the knowledge from the source objects to the target objects. Our experimental results demonstrate the effectiveness of our approach.
Preparation and magnetic properties of nano size nickel ferrite particles using hydrothermal method

Nickel ferrite, a kind of soft magnetic materials is one of the most attracting class of materials due to its interesting and important properties and has many technical applications, such as in catalysis, sensors and so on. In this paper the synthesis of NiFe2O4 nanoparticles by the hydrothermal method is reported and the inhibition of surfactant (Glycerol or Sodium dodecyl sulfate) on the particles growth is investigated.



For investigation of the inhibition effect of surfactant on NiFe2O4 particles growth, the samples were prepared in presence of Glycerol and Sodium dodecyl sulfate. The X-ray powder diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), vibrating sample magnetometer (VSM) and inductively coupled plasma atomic emission spectrometer (ICP-AES) techniques were used to characterize the samples.



The results of XRD and ICP-AES show that the products were pure NiFe2O4 and also nanoparticles grow with increasing the temperature, while surfactant prevents the particle growth under the same condition. The average particle size was determined from the Scherrer's equation and TEM micrographs and found to be in the range of 50-60 nm that decreased up to 10-15 nm in presence of surfactant. The FT-IR results show two absorption bands near to 603 and 490 cm-1 for the tetrahedral and octahedral sites respectively. Furthermore, the saturated magnetization and coercivity of NiFe2O4 nanoparticles were in the range of 39.60 emu/g and 15.67 Qe that decreased for samples prepared in presence of surfactant. As well as, the nanoparticles exhibited a superparamagnetic behavior at room temperature.



Nanosized nickel ferrite particles were synthesized with and without surfactant assisted hydrothermal methods. The results show that with increasing of temperature, the crystallinity of nanoparticles is increased. In the presence of surfactants, the crystallinity of NiFe2O4 nanoparticles decreased in comparison with surfactant- free prepared samples. All of the nickel ferrite nanoparticles were superparamagnetic at room temperature.
Aesthetic preformed paediatric crowns: systematic review.

Different aesthetic preformed crowns (APC) are proposed to restore decayed and damaged primary teeth because the stainless steel crowns (SSCs) do not satisfy parents concerned about aesthetic.



The objective was to evaluate the clinical effectiveness of all types of APC for restoring primary teeth compared with conventional filling materials or other types of crowns.



Relevant articles were searched in electronic databases of PubMed via MEDLINE and the Cochrane central register of controlled trials. Two review authors independently assessed the risk of bias in the included articles and extracted data.



From 555 potentially eligible articles, seven relevant articles were included. The overall risk of bias was high for all the studies. SCCs cannot be replaced by APC, such as the open-faced SSCs and the pre-veneered SCCs, for restoring badly decayed primary molars. Zircon crowns were assessed only in primary incisors and compared with pre-veneered SCCs and resin composite strip crowns. After a follow-up of only 6 months, Zircon crowns gave significantly better results than the others with regard to gingival health and crown fractures.



Due to the small number of RCTs on this topic and their risk of bias, future RCTs should be carried out in primary teeth.