nils-herrmann/clean_scirepeval huggingface dataset:
Global transcriptome analysis of developing chickpea (Cicer arietinum L.) seeds

Understanding developmental processes, especially in non-model crop plants, is extremely important in order to unravel unique mechanisms regulating development. Chickpea (C. arietinum L.) seeds are especially valued for their high carbohydrate and protein content. Therefore, in order to elucidate the mechanisms underlying seed development in chickpea, deep sequencing of transcriptomes from four developmental stages was undertaken. In this study, next generation sequencing platform was utilized to sequence the transcriptome of four distinct stages of seed development in chickpea. About 1.3 million reads were generated which were assembled into 51,099 unigenes by merging the de novo and reference assemblies. Functional annotation of the unigenes was carried out using the Uniprot, COG and KEGG databases. RPKM based digital expression analysis revealed specific gene activities at different stages of development which was validated using Real time PCR analysis. More than 90% of the unigenes were found to be expressed in at least one of the four seed tissues. DEGseq was used to determine differentially expressing genes which revealed that only 6.75% of the unigenes were differentially expressed at various stages. Homology based comparison revealed 17.5% of the unigenes to be putatively seed specific. Transcription factors were predicted based on HMM profiles built using TF sequences from five legume plants and analyzed for their differential expression during progression of seed development. Expression analysis of genes involved in biosynthesis of important secondary metabolites suggested that chickpea seeds can serve as a good source of antioxidants. Since transcriptomes are a valuable source of molecular markers like simple sequence repeats (SSRs), about 12,000 SSRs were mined in chickpea seed transcriptome and few of them were validated. In conclusion, this study will serve as a valuable resource for improved chickpea breeding.
Fusing Social Networks with Deep Learning for Volunteerism Tendency Prediction

Zobrist  An Efficient Work Distribution Method for Parallel Best-First Search Yuu Jinnai, Alex Fukunaga VIS: Text and Vision Oral Presentations 1326 SentiCap: Generating Image Descriptions with Sentiments Alexander Patrick Mathews, Lexing Xie, Xuming He 1950 Reading Scene Text in Deep Convolutional Sequences Pan He, Weilin Huang, Yu Qiao, Chen Change Loy, Xiaoou Tang 1247 Creating Images by Learning Image Semantics Using Vector Space Models Derrall Heath, Dan Ventura Poster Spotlight Talks 655 Towards Domain Adaptive Vehicle Detection in Satellite Image by Supervised SuperResolution Transfer Liujuan Cao, Rongrong Ji, Cheng Wang, Jonathan Li 499 Transductive Zero-Shot Recognition via Shared Model Space Learning Yuchen Guo, Guiguang Ding, Xiaoming Jin, Jianmin Wang 1255 Exploiting View-Specific Appearance Similarities Across Classes for Zero-shot Pose Prediction: A Metric Learning Approach Alina Kuznetsova, Sung Ju Hwang, Bodo Rosenhahn, Leonid Sigal NLP: Topic Flow Oral Presentations 744 Topical Analysis of Interactions Between News and Social Media Ting Hua, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan 1561 Tracking Idea Flows between Social Groups Yangxin Zhong, Shixia Liu, Xiting Wang, Jiannan Xiao, Yangqiu Song 1201 Modeling Evolving Relationships Between Characters in Literary Novels Snigdha Chaturvedi, Shashank Srivastava, Hal Daume III, Chris Dyer Poster Spotlight Talks 405 Identifying Search
Behavioral / Systems / Cognitive Functional Connectivity and Brain Networks in Schizophrenia

Mary-Ellen Lynall,1,2 Danielle S. Bassett,1,2,3,4 Robert Kerwin,5 Peter J. McKenna,6 Manfred Kitzbichler,1,2 Ulrich Muller,1,2 and Ed Bullmore1,2,7 1Behavioural and Clinical Neuroscience Institute and 2Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, United Kingdom, 3Cognition, and Psychosis Program, Clinical Brain Disorders Branch, Genes, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, 4Biological Soft Systems Sector, Department of Physics, University of Cambridge, Cambridge CB3 0HE, United Kingdom, 5Institute of Psychiatry, King’s College London, London SE5 8AF, United Kingdom, 6Benito Menni Complex Assistencial en Salut Mental, Centro de Investigacion en Red de Salut Mental, Sant Boi de Llobregat, Barcelona 08840, Spain, and 7Clinical Unit Cambridge, GlaxoSmithKline, Addenbrooke’s Hospital, Cambridge CB2 0QQ, United Kingdom
Heritage BIM integration with mixed reality for building preventive maintenance

Historical and cultural building conservation is nowadays limited to high value buildings and only receive financial support when serious issues arise. HeritageCARE project is willing to shift this mentality, towards "prevention is better than the cure". New technologies are able to support such motivation by improving building inspector work during their inspection routine. In that regard, mixed reality will be explored to offer easy and efficient interaction while remaining focused on the task at hand. Moreover, integration with historical building information model will ensure capture of localized data and easier exchange with stakeholders in case of renovation projects. This paper presents an architecture for a mixed reality application working towards this goal and a first prototype.
Practical Strategies for Power-Efficient Computing Technologies

After decades of continuous scaling, further advancement of silicon microelectronics across the entire spectrum of computing applications is today limited by power dissipation. While the trade-off between power and performance is well-recognized, most recent studies focus on the extreme ends of this balance. By concentrating instead on an intermediate range, an ~ 8× improvement in power efficiency can be attained without system performance loss in parallelizable applications-those in which such efficiency is most critical. It is argued that power-efficient hardware is fundamentally limited by voltage scaling, which can be achieved only by blurring the boundaries between devices, circuits, and systems and cannot be realized by addressing any one area alone. By simultaneously considering all three perspectives, the major issues involved in improving power efficiency in light of performance and area constraints are identified. Solutions for the critical elements of a practical computing system are discussed, including the underlying logic device, associated cache memory, off-chip interconnect, and power delivery system. The IBM Blue Gene system is then presented as a case study to exemplify several proposed directions. Going forward, further power reduction may demand radical changes in device technologies and computer architecture; hence, a few such promising methods are briefly considered.
A Survey on Access Control Deployment

Access control is a security aspect whose requirements evolve with technology advances and, at the same time, contemporary social contexts. Multitudes of access control models grow out of their respective application domains such as healthcare and collaborative enterprises; and even then, further administering means, human factor considerations, and infringement management are required to effectively deploy the model in the particular usage environment. This paper presents a survey of access control mechanisms along with their deployment issues and solutions available today. We aim to give a comprehensive big picture as well as pragmatic deployment details to guide in understanding, setting up and enforcing access control in its real world application.
This Ain't Your Dose: Sensor Spoofing Attack on Medical Infusion Pump

Sensors measure physical quantities of the environment for sensing and actuation systems, and are widely used in many commercial embedded systems such as smart devices, drones, and medical devices because they offer convenience and accuracy. As many sensing and actuation systems depend entirely on data from sensors, these systems are naturally vulnerable to sensor spoofing attacks that use fabricated physical stimuli. As a result, the systems become entirely insecure and unsafe. In this paper, we propose a new type of sensor spoofing attack based on saturation. A sensor shows a linear characteristic between its input physical stimuli and output sensor values in a typical operating region. However, if the input exceeds the upper bound of the operating region, the output is saturated and does not change as much as the corresponding changes of the input. Using saturation, our attack can make a sensor to ignore legitimate inputs. To demonstrate our sensor spoofing attack, we target two medical infusion pumps equipped with infrared (IR) drop sensors to control precisely the amount of medicine injected into a patients’ body. Our experiments based on analyses of the drop sensors show that the output of them could be manipulated by saturating the sensors using an additional IR source. In addition, by analyzing the infusion pumps’ firmware, we figure out the vulnerability in the mechanism handling the output of the drop sensors, and implement a sensor spoofing attack that can bypass the alarm systems of the targets. As a result, we show that both over-infusion and under-infusion are possible: our spoofing attack can inject up to 3.33 times the intended amount of fluid or 0.65 times of it for a 10 minute period.
Soft-Switching SEPIC Converter With Ripple-Free Input Current

A soft-switching single-ended primary inductor converter (SEPIC) is presented in this paper. An auxiliary switch and a clamp capacitor are connected. A coupled inductor and an auxiliary inductor are utilized to obtain ripple-free input current and achieve zero-voltage-switching (ZVS) operation of the main and auxiliary switches. The voltage multiplier technique and active clamp technique are applied to the conventional SEPIC converter to increase the voltage gain, reduce the voltage stresses of the power switches and diode. Moreover, by utilizing the resonance between the resonant inductor and the capacitor in the voltage multiplier circuit, the zero-current-switching operation of the output diode is achieved and its reverse-recovery loss is significantly reduced. The proposed converter achieves high efficiency due to soft-switching commutations of the power semiconductor devices. The presented theoretical analysis is verified by a prototype of 100 kHz and 80 W converter. Also, the measured efficiency of the proposed converter has reached a value of 94.8% at the maximum output power.
GNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques

Various measurement monitoring techniques are investigated to mitigate the effect of global navigation satellite systems (GNSS) code multipath through error correction, stochastic weighting of measurements and detection and exclusion (or de-weighting) of affected measurements. Following a comprehensive review of each approach, the paper focuses on detection/exclusion and detection/de-weighting techniques where several single and dual-frequency monitoring metrics are employed in a combination with time-averaging and the M of N detection strategy. A new Geometry-Free (GF) detection metric is proposed given its capability to be combined with a preceding Code-Minus-Carrier (CMC)-based error correction to reduce the number of excluded or de-weighted measurements and thus preserve the measurement geometry. Three geometry-based algorithms, namely measurement subset testing, consecutive exclusion and iterative change of measurement weights are investigated to address multipath scenarios with multiple simultaneously affected measurements. Experimental results are provided using GPS L1, L2C and L5 data collected in multipath environments for static and kinematic scenarios. For GPS L1, the proposed combined method shows more than 38% improvement over a conventional Carrier-to-Noise-density ratio (C/N₀)-based Least-Squares (LS) solution in all but deep urban canyons. Lower performance was observed for L2C and L5 frequencies with a limited number of satellites in view.
αRoute: A name based routing scheme for Information Centric Networks

One of the crucial building blocks for Information Centric Networking (ICN) is a name based routing scheme that can route directly on content names instead of IP addresses. However, moving the address space from IP addresses to content names brings scalability issues to a whole new level, due to two reasons. First, name aggregation is not as trivial a task as the IP address aggregation in BGP routing. Second, the number of addressable contents in the Internet is several orders of magnitude higher than the number of IP addresses. With the current size of the Internet, name based, anycast routing is very challenging specially when routing efficiency is of prime importance. We propose a novel name-based routing scheme (αRoute) for ICN that offers efficient bandwidth usage, guaranteed content lookup and scalable routing table size.
SUMMARIZATION USING AGGREGATE SIMILARITY

This paper proposes an Arabic text summarization approach based on an aggregate similarity method which is originally proposed for the Korean language text. The proposed approach depends mainly on nouns as indicators of the importance of the sentences. Hence, the noun extraction process is the main process in the proposed approach. To do summarization of a given document, the document is segmented into sentences and then the sentences are tokenized into words. The noun extraction process is performed using fourteen noun extraction rules that are used as indication for the distinction of nouns from other non noun words. In the next step the frequencies for each noun in each sentence and in the whole document are computed and the sentence similarity between the noun frequency in the sentence and the document is calculated using the Inner Product measure. The summation of all similarities of every sentence represents an Aggregate similarity; the sentences that have the highest value of similarity are selected as the summary where the number of sentences that are selected is determined by a user defined threshold value. To evaluate the proposed approach, a dataset of fifty documents is used and the performance of the approach is evaluated using the Recall and Precision measures. The results obtained were 62% for Precision, 70 % for Recall, and 14% for the compression rate. As a conclusion, the result is acceptable according to the nature of the Arabic language which has rich vocabulary and complex grammar rules.
Predictive Factors for a Kyphosis Recurrence Following Short-Segment Pedicle Screw Fixation Including Fractured Vertebral Body in Unstable Thoracolumbar Burst Fractures

The technique of short segment pedicle screw fixation (SSPSF) has been widely used for stabilization in thoracolumbar burst fractures (TLBFs), but some studies reported high rate of kyphosis recurrence or hardware failure. This study was to evaluate the results of SSPSF including fractured level and to find the risk factors concerned with the kyphosis recurrence in TLBFs.



This study included 42 patients, including 25 males and 17 females, who underwent SSPSF for stabilization of TLBFs between January 2003 and December 2010. For radiologic assessments, Cobb angle (CA), vertebral wedge angle (VWA), vertebral body compression ratio (VBCR), and difference between VWA and Cobb angle (DbVC) were measured. The relationships between kyphosis recurrence and radiologic parameters or demographic features were investigated. Frankel classification and low back outcome score (LBOS) were used for assessment of clinical outcomes.



The mean follow-up period was 38.6 months. CA, VWA, and VBCR were improved after SSPSF, and these parameters were well maintained at the final follow-up with minimal degree of correction loss. Kyphosis recurrence showed a significant increase in patients with Denis burst type A, load-sharing classification (LSC) score >6 or DbVC >6 (p<0.05). There were no patients who worsened to clinical outcome, and there was no significant correlation between kyphosis recurrence and clinical outcome in this series.



SSPSF including the fractured vertebra is an effective surgical method for restoration and maintenance of vertebral column stability in TLBFs. However, kyphosis recurrence was significantly associated with Denis burst type A fracture, LSC score >6, or DbVC >6.
A comparison of picking , storage , and routing policies in manual order picking

This article examines the effect of three process decisions (picking, storage, and routing) on order picker travel, which is a major cost component of order fulfillment. The authors use a simulation model based on the operations of a distribution center that is currently picking one order at a time, storing product in a haphazard or random fashion, and using a simplistic procedure for routing pickers. Several picking, storage, and routing policies are evaluated to determine which process decision provides the greatest percent savings relative to the current baseline policies. Several sensitivity analyses are completed to examine the effect of order size, warehouse shape, location of pick-up/drop-off point, and demand distribution on performance. Results show that batching of orders yield the greatest savings particularly when smaller order sizes are common. Results also show the use of either a class-based or volume-based storage policy provides nearly the same level of savings as batching, while being less sensitive to the average order size. r 2003 Elsevier B.V. All rights reserved.
Transdermal Drug Delivery

Due to its numerous advantages, transdermal drug delivery has attracted considerable attention in recent times. The protective barrier nature of the skin however limits the absorption of most drugs across the skin. A variety of strategies are available for the modification of the drug and/or vehicle or the composition of the stratum corneum (SC), the outermost layer of the skin, to improve the absorption of most drugs. Furthermore, various techniques are available for studying the effectiveness, mode of action and skin toxicity of the penetration enhancers. Most of the earlier reviews have focused on a certain selected aspect of transdermal drug delivery. This review presents a comprehensive account of various aspects of drug delivery by transdermal route including the various chemical and physical penetration enhancers. It also discusses the in vivo and in vitro methods of evaluating chemical enhancers , their mode of action and safety.  Chemical penetration enhancers; Permeation studies ; Physical penetration enhancers; Transdemal drug delivery. ______________________________________________________________________________
Plant Identification in an Open-world (LifeCLEF 2016)

The LifeCLEF plant identification challenge aims at evaluating plant identification methods and systems at a very large scale, close to the conditions of a real-world biodiversity monitoring scenario. The 2016-th edition was actually conducted on a set of more than 110K images illustrating 1000 plant species living in West Europe, built through a large-scale participatory sensing platform initiated in 2011 and which now involves tens of thousands of contributors. The main novelty over the previous years is that the identification task was evaluated as an open-set recognition problem, i.e. a problem in which the recognition system has to be robust to unknown and never seen categories. Beyond the brute-force classification across the known classes of the training set, the big challenge was thus to automatically reject the false positive classification hits that are caused by the unknown classes. This overview presents more precisely the resources and assessments of the challenge, summarizes the approaches and systems employed by the participating research groups, and provides an analysis of the main outcomes.
Automatic segmentation of MR images of the developing newborn brain

This paper describes an automatic tissue segmentation method for newborn brains from magnetic resonance images (MRI). The analysis and study of newborn brain MRI is of great interest due to its potential for studying early growth patterns and morphological changes in neurodevelopmental disorders. Automatic segmentation of newborn MRI is a challenging task mainly due to the low intensity contrast and the growth process of the white matter tissue. Newborn white matter tissue undergoes a rapid myelination process, where the nerves are covered in myelin sheathes. It is necessary to identify the white matter tissue as myelinated or non-myelinated regions. The degree of myelination is a fractional voxel property that represents regional changes of white matter as a function of age. Our method makes use of a registered probabilistic brain atlas. The method first uses robust graph clustering and parameter estimation to find the initial intensity distributions. The distribution estimates are then used together with the spatial priors to perform bias correction. Finally, the method refines the segmentation using training sample pruning and non-parametric kernel density estimation. Our results demonstrate that the method is able to segment the brain tissue and identify myelinated and non-myelinated white matter regions.
Intent-aware search result diversification

Search result diversification has gained momentum as a way to tackle ambiguous queries. An effective approach to this problem is to explicitly model the possible aspects underlying a query, in order to maximise the estimated relevance of the retrieved documents with respect to the different aspects. However, such aspects themselves may represent information needs with rather distinct intents (e.g., informational or navigational). Hence, a diverse ranking could benefit from applying intent-aware retrieval models when estimating the relevance of documents to different aspects. In this paper, we propose to diversify the results retrieved for a given query, by learning the appropriateness of different retrieval models for each of the aspects underlying this query. Thorough experiments within the evaluation framework provided by the diversity task of the TREC 2009 and 2010 Web tracks show that the proposed approach can significantly improve state-of-the-art diversification approaches.