nils-herrmann/clean_scirepeval huggingface dataset:
Inhibition protects acquired song segments during vocal learning in zebra finches
Venue: Science

Fixation on learned syllables Zebra finches learn their beautiful songs by listening to other zebra finches. Vallentin et al. observed zebra finch brains as learning proceeded, only to find that inhibition of the neuronal circuits was critical to fixating on learned sequences. For song syllables that have been adequately learned, the inhibitory neurons fired coherently. Song syllables not yet learned failed to produce this flag. Thus, it is the learning process that alters the neuronal circuits. The inhibitory neuronal firing, not the age of the bird, locks in the learning. Science, this issue p. 267 Songs that birds have already learned are preserved by inhibitory neurons that block further modifications. Vocal imitation involves incorporating instructive auditory information into relevant motor circuits through processes that are poorly understood. In zebra finches, we found that exposure to a tutor's song drives spiking activity within premotor neurons in the juvenile, whereas inhibition suppresses such responses upon learning in adulthood. We measured inhibitory currents evoked by the tutor song throughout development while simultaneously quantifying each bird's learning trajectory. Surprisingly, we found that the maturation of synaptic inhibition onto premotor neurons is correlated with learning but not age. We used synthetic tutoring to demonstrate that inhibition is selective for specific song elements that have already been learned and not those still in refinement. Our results suggest that structured inhibition plays a crucial role during song acquisition, enabling a piece by piece mastery of complex tasks.
Natural courtship song variation caused by an intronic retroelement in an ion channel gene
Venue: Nature

Animal species display enormous variation for innate behaviours, but little is known about how this diversity arose. Here, using an unbiased genetic approach, we map a courtship song difference between wild isolates of Drosophila simulans and Drosophila mauritiana to a 966 base pair region within the slowpoke (slo) locus, which encodes a calcium activated potassium channel. Using the reciprocal hemizygosity test, we confirm that slo is the causal locus and resolve the causal mutation to the evolutionarily recent insertion of a retroelement in a slo intron within D. simulans. Targeted deletion of this retroelement reverts the song phenotype and alters slo splicing. Like many ion channel genes, slo is expressed widely in the nervous system and influences a variety of behaviours; slo null males sing little song with severely disrupted features. By contrast, the natural variant of slo alters a specific component of courtship song, illustrating that regulatory evolution of a highly pleiotropic ion channel gene can cause modular changes in behaviour.
Auditory experience dependent cortical circuit shaping for memory formation in bird song learning
Venue: Nature communications

As in human speech acquisition, songbird vocal learning depends on early auditory experience. During development, juvenile songbirds listen to and form auditory memories of adult tutor songs, which they use to shape their own vocalizations in later sensorimotor learning. The higher level auditory cortex, called the caudomedial nidopallium (NCM) is a potential storage site for tutor song memory, but no direct electrophysiological evidence of tutor song memory has been found. Here, we identify the neuronal substrate for tutor song memory by recording single neuron activity in the NCM of behaving juvenile zebra finches. After tutor song experience, a small subset of NCM neurons exhibit highly selective auditory responses to the tutor song. Moreover, blockade of GABAergic inhibition, and sleep decrease their selectivity. Taken together, these results suggest that experience dependent recruitment of GABA mediated inhibition shapes auditory cortical circuits, leading to sparse representation of tutor song memory in auditory cortical neurons.
Strength of Validation for Surrogate End Points Used in the US Food and Drug Administration's Approval of Oncology Drugs.
Venue: Mayo Clinic proceedings

To determine the strength of the surrogate survival correlation for cancer drug approvals based on a surrogate.  We performed a retrospective study of the US Food and Drug Administration (FDA) database, with focused searches of MEDLINE and Google Scholar. Among cancer drugs approved based on a surrogate end point, we examined previous publications assessing the strength of the surrogate survival correlation. Specifically, we identified the percentage of surrogate approvals lacking any formal analysis of the strength of the surrogate survival correlation, and when conducted, the strength of such correlations.  Between January 1, 2009, and December 31, 2014, the FDA approved marketing applications for 55 indications based on a surrogate, of which 25 were accelerated approvals and 30 were traditional approvals. We could not find any formal analyses of the strength of the surrogate survival correlation in 14 out of 25 accelerated approvals (56% and 11 out of 30 traditional approvals (37% For accelerated approvals, just 4 approvals (16% were made where a level 1 analysis (the most robust way to validate a surrogate) had been performed, with all 4 studies reporting low correlation (r<=0.7) For traditional approvals, a level 1 analysis had been performed for 15 approvals (50% 8 (53% reported low correlation (r<=0.7) 4 (27% medium correlation (r>0.7 to r<0.85) and 3 (20% high correlation (r>=0.85) with survival.  The use of surrogate end points for drug approval often lacks formal empirical verification of the strength of the surrogate survival association.
Unitary construct of generalized cognitive ability underlying BACS performance across psychotic disorders and in their first degree relatives
Venue: Schizophrenia Research

Despite robust evidence of neurocognitive dysfunction in psychotic patients, the degree of similarity in cognitive architecture across psychotic disorders and among their respective first degree relatives is not well delineated. The present study examined the latent factor structure of the Brief Assessment of Cognition in Schizophrenia (BACS) neuropsychological battery. Analyses were conducted on 783 psychosis spectrum probands (schizophrenia, schizoaffective, psychotic bipolar) 887 of their first degree relatives, and 396 non psychiatric controls from the Bipolar Schizophrenia Network on Intermediate Phenotypes (B SNIP) consortium. Exploratory factor analysis of BACS subtest scores indicated a single factor solution that was similar across all groups and provided the best overall data fit in confirmatory analyses. Correlations between the standard BACS composite score and the sum of subscale scores weighted by their loadings on this unitary factor were very high in all groups (r>.99) Thus, the BACS assesses a similar unitary cognitive construct in probands with different psychotic disorders, in their first degree relatives, and in healthy controls, and this factor is well measured by the test's standard composite score.
Building Automation planning and design tool implementing EN 15 232 BACS efficiency classes
Venue: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA)

The proper design of Building Automation and Control Systems (BACS) and Technical Building Management (TBM) with complex technical systems and thousands of devices is a very difficult process with a lot of laborious works. The usage of dedicated tools for design process may simplifies these efforts and works. The BACS and TBM have impact not only on buildings' comfort and safety, but also on the energy performance. In this paper concept of a new software tool is introduced. This tool provides guidance for taking the BACS and TBM functions as far as possible into account under buildings planning and design processes. The guidance based on the EN 15232 standard, defining the BACS and TBM efficiency classes. First stages of development of the proposed software tool have been presented. Proposed by authors software tool helps to solve typical issues under BACS design process.
Distributional Hypernym Generation by Jointly Learning Clusters and Projections
Venue: COLING

We propose a novel word embedding based hypernym generation model that jointly learns clusters of hyponym hypernym relations, i.e. hypernymy, and projections from hyponym to hypernym embeddings. Most of the recent hypernym detection models focus on a hypernymy classification problem that determines whether a pair of words is in hypernymy or not. These models do not directly deal with a hypernym generation problem in that a model generates hypernyms for a given word. Differently from previous studies, our model jointly learns the clusters and projections with adjusting the number of clusters so that the number of clusters can be determined depending on the learned projections and vice versa. Our model also boosts the performance by incorporating inner product based similarity measures and negative examples, i.e. sampled non hypernyms, into our objectives in learning. We evaluated our joint learning models on the task of Japanese and English hypernym generation and showed a significant improvement over an existing pipeline model. Our model also compared favorably to existing distributed hypernym detection models on the English hypernym classification task.
Science teaching in science education

Reading the interesting article Discerning selective traditions in science education by Per Sund, which is published in this issue of CSSE, allows us to open the discussion on procedures for teaching science today. Clearly there is overlap between the teaching of science and other areas of knowledge. However, we must constantly develop new methods to teach and differentiate between science education and teaching science in response to the changing needs of our students, and we must analyze what role teachers and teacher educators play in both. We must continually examine the methods and concepts involved in developing pedagogical content knowledge in science teachers. Otherwise, the possibility that these routines, based on subjective traditions, prevent emerging processes of educational innovation. Modern science is an enormous field of knowledge in its own right, which is made more expansive when examined within the context of its place in society. We propose the need to design educative interactions around situations that involve science and society. Science education must provide students with all four dimensions of the cognitive process: factual knowledge, conceptual knowledge, procedural knowledge, and metacognitive knowledge. We can observe in classrooms at all levels of education that students understand the concepts better when they have the opportunity to apply the scientific knowledge in a personally relevant way. When students find value in practical exercises and they are provided opportunities to reinterpret their experiences, greater learning gains are achieved. In this sense, a key aspect of educational innovation is the change in teaching methodology. We need new tools to respond to new problems. A shift in teacher education is needed to realize the rewards of situating science questions in a societal context and opening classroom doors to active methodologies in science education to promote meaningful learning through meaningful teaching.
Mitigation of black hole attacks in Routing Protocol for Low Power and Lossy Networks
Venue: Secur. Commun. Networks

Routing Protocol for Low Power and Lossy Networks (RPL) has been standardized by the Internet Engineering Task Force to efficiently manage the functions of the network layer when providing Internet connectivity for wireless sensor networks. RPL has been designed for constrained devices and networks. Owing to their constrained nature, RPL based networks can be exposed to a wide variety of security attacks. One of the most serious attacks in RPL is a black hole attack, where a malicious node silently drops all the packets that it is supposed to forward. This paper proposes a mitigation technique against black hole attack with low packet loss and high reliability. The proposed technique consists of a local decision and a global verification process. First, each node observes the communication behavior of its neighboring nodes by overhearing packets transmitted by its neighbors and attempts to identify suspicious nodes based on their behavior. In the second process, if a node identifies a suspicious node, then it verifies whether the suspicious node is a black hole. We demonstrate that the proposed approach increases packet delivery rate significantly and detects black hole attack effectively.
The need for community inclusion in water basin governance in Bangladesh

In this paper we focus on the principle of community inclusion in water and ecological resource governance and document the negative impacts of its absence, in Chapra village, Bangladesh, on sustainable development and livelihood security. This community depends heavily on common property resources such as wild plant foods, fish and 'natural' crop fertilizers derived from river siltation and other sources. For the vast majority of people in Chapra, these common ecological resources create the ability to effectively match livelihood strategies to the conditions of both dry and rainy seasons. However, this socioecological livelihood pattern is increasingly undermined by the hydropolitics and top down water management practices that prevail throughout the Ganges Brahmaputra Basin in Bangladesh. These practices lead to ecosystem failures and ecological resource degradation which in turn cause survival challenges for the marginalized people who constitute the vast majority of the population. In this paper we explicitly seek to answer the question: how might community inclusion in governance processes help protect ecological integrity and common property resources and thereby support an alternative and more sustainable form of development for the region? In order to answer this question we first document the nature of livelihood practices in Chapra, based on 1 year of fieldwork, and then outline the mismatch that now occurs between livelihood practices, ecological characteristics and governance practices. We conclude with the argument that greater community inclusion in governance must be part of the solution to existing problems and we propose specific governance reform measures to facilitate community inclusion.
Nearest Neighbor Search in the Metric Space of a Complex Network for Community Detection
Venue: Inf.

The objective of this article is to bridge the gap between two important research directions: (1) nearest neighbor search, which is a fundamental computational tool for large data analysis; and (2) complex network analysis, which deals with large real graphs but is generally studied via graph theoretic analysis or spectral analysis. In this article, we have studied the nearest neighbor search problem in a complex network by the development of a suitable notion of nearness. The computation of efficient nearest neighbor search among the nodes of a complex network using the metric tree and locality sensitive hashing (LSH) are also studied and experimented. For evaluation of the proposed nearest neighbor search in a complex network, we applied it to a network community detection problem. Experiments are performed to verify the usefulness of nearness measures for the complex networks, the role of metric tree and LSH to compute fast and approximate node nearness and the the efficiency of community detection using nearest neighbor search. We observed that nearest neighbor between network nodes is a very efficient tool to explore better the community structure of the real networks. Several efficient approximation schemes are very useful for large networks, which hardly made any degradation of results, whereas they save lot of computational times, and nearest neighbor based community detection approach is very competitive in terms of efficiency and time.
BOOK REVIEW OF LITTLE LORD FAUNTLEROY WRITTEN BY FRANCES HODGSON BURNETT

There are many well known writers who use their own imaginations of childhood for their novel. Burnett, for example, is a modern novelist in the early twentieth century. Her seventh novel was published by Scribner publisher in October, in 1886, entitled Little Lord Fauntleroy It is interesting to review Little Lord Fauntleroy since it represents the kindness and ordinary life of a little boy noble who does not only care to his family, but also to the people around.
A two stage stochastic programming model for lot sizing and scheduling under uncertainty

A lot sizing and scheduling problem with sequence dependent setups is addressed in this paper. In the production system, manufactories receive raw materials from upstream sites, and after production, the final products are shipped to downstream sites and customers. The key is to find a good production planning so that their cost is minimized. A two stage stochastic programming model is formulated to minimize the total production, inventory and backorder costs. The first stage decides the baseline production including the production quantity of each product and the sequence of production while the second stage focuses on the possible updates of baseline production such as overtime production. The goal is to find the best sequence of production quantities under random demand with backorders allowed. Uncertainty is explicitly represented with a scenario tree then selecting the most representative scenarios in order to obtain a smaller subset while preserving essential properties. Both setup time and setup cost are product dependent. A case study for a manufacturing company producing braking equipment has been conducted to illustrate and validate the model. The results show that the stochastic model outperforms the deterministic model, especially when there are sufficient production resources.
Addressing Complex and Subjective Product Related Queries with Customer Reviews
Venue: WWW

Online reviews are often our first port of call when considering products and purchases online. When evaluating a potential purchase, we may have a specific query in mind, e.g. `will this baby seat fit in the overhead compartment of a 747? or `will I like this album if I liked Taylor Swift's 1989? To answer such questions we must either wade through huge volumes of consumer reviews hoping to find one that is relevant, or otherwise pose our question directly to the community via a Q/A system. In this paper we hope to fuse these two paradigms: given a large volume of previously answered queries about products, we hope to automatically learn whether a review of a product is relevant to a given query. We formulate this as a machine learning problem using a mixture of experts type framework here each review is an `expert' that gets to vote on the response to a particular query; simultaneously we learn a relevance function such that `relevant' reviews are those that vote correctly. At test time this learned relevance function allows us to surface reviews that are relevant to new queries on demand. We evaluate our system, Moqa, on a novel corpus of 1.4 million questions (and answers) and 13 million reviews. We show quantitatively that it is effective at addressing both binary and open ended queries, and qualitatively that it surfaces reviews that human evaluators consider to be relevant.
Mining Opinion Features in Customer Reviews.

Now days, E commerce systems have become extremely important. Large numbers of customers are choosing online shopping because of its convenience, reliability, and cost. Client generated information and especially item reviews are significant sources of data for consumers to make informed buy choices and for makers to keep track of customer's opinions. It is difficult for customers to make purchasing decisions based on only pictures and short product descriptions. On the other hand, mining product reviews has become a hot research topic and prior researches are mostly based on pre specified product features to analyse the opinions. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to raw customer reviews and keywords can be extracted. This paper presents a survey on the techniques used for designing software to mine opinion features in reviews. Elven IEEE papers are selected and a comparison is made between them. These papers are representative of the significant improvements in opinion mining in the past decade.
Investigating Discontinuity of Age Relations in Cognitive Functioning, General Health Status, Activity Participation, and Life Satisfaction between Young Old and Old Old Age
Venue: International journal of environmental research and public health

Health research suggests that findings on young old adults cannot be generalized to old old adults and thus that old old age seems not a simple continuation of young old age due to qualitative changes that result in a discontinuity in old age. Specifically, it would be of conceptual and methodological importance to inform research regarding estimates around which chronological age the beginning of old old age could be placed at a population level, and whether this is universal or domain specific. To derive such criteria, we investigated potential discontinuity of age relations between young old and old old age in a large population based sample considering measures in different domains (processing speed, verbal abilities, general health status, activity participation, and life satisfaction) For processing speed, verbal abilities, general health status, and life satisfaction we observed some very small indication that there might be a discontinuity of age relations at the end of individuals' eighties, and for activity participation already at the beginning of individuals' eighties. In conclusion, models conceptualizing aging as a gradual development might not suffice to adequately represent the differences between the stages of young old and old old age due to some very small indication that there might be discontinuity in late adulthood.
The Study of Structural Relationship among Forgiveness, Life Satisfaction, and General Health in Students

The purpose of the present study was to investigate the effect of forgiveness on general health through life satisfaction in students.  The study was based on the causal correlation method, and the statistical population consisted of all the students of Payam Nour and Azad University of Lamerd in the second semester of the academic year 2013 2014. The sample of the study consisted of 166 (99 male and 67 female) students which were selected by multistage random sampling. Data collection tools were Heartland Forgiveness Scale (HFS) Satisfaction with Life Scale (SWLS) and General Health Questionnaire (GHQ) Structural equation modeling (SEM) through AMOS 16 and SPSS 16 software packages was used for data analysis.  Analysis of structural equation modeling indicated that the default model of effect of forgiveness on general health through life satisfaction fit the data. Further analysis revealed that forgiveness had indirect and direct significant relationship with general health through life satisfaction.  Based on the results, it can be said that people bring themselves feelings of satisfaction and happiness and reduce their physical and mental problems and discomforts by forgiving their own mistakes and those