Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid SNP Discovery and Genetic Mapping Using Sequenced RAD Markers

Single nucleotide polymorphism (SNP) discovery and genotyping are essential to genetic mapping. There remains a need for a simple, inexpensive platform that allows high-density SNP discovery and genotyping in large populations. Here we describe the sequencing of restriction-site associated DNA (RAD) tags, which identified more than 13,000 SNPs, and mapped three traits in two model organisms, using less than half the capacity of one Illumina sequencing run. We demonstrated that different marker densities can be attained by choice of restriction enzyme. Furthermore, we developed a barcoding system for sample multiplexing and fine mapped the genetic basis of lateral plate armor loss in threespine stickleback by identifying recombinant breakpoints in F2 individuals. Barcoding also facilitated mapping of a second trait, a reduction of pelvic structure, by in silico re-sorting of individuals. To further demonstrate the ease of the RAD sequencing approach we identified polymorphic markers and mapped an induced mutation in Neurospora crassa. Sequencing of RAD markers is an integrated platform for SNP discovery and genotyping. This approach should be widely applicable to genetic mapping in a variety of organisms.
RiboTag Analysis of Actively Translated mRNAs in Sertoli and Leydig Cells In Vivo

Male spermatogenesis is a complex biological process that is regulated by hormonal signals from the hypothalamus (GnRH), the pituitary gonadotropins (LH and FSH) and the testis (androgens, inhibin). The two key somatic cell types of the testis, Leydig and Sertoli cells, respond to gonadotropins and androgens and regulate the development and maturation of fertilization competent spermatozoa. Although progress has been made in the identification of specific transcripts that are translated in Sertoli and Leydig cells and their response to hormones, efforts to expand these studies have been restricted by technical hurdles. In order to address this problem we have applied an in vivo ribosome tagging strategy (RiboTag) that allows a detailed and physiologically relevant characterization of the “translatome” (polysome-associated mRNAs) of Leydig or Sertoli cells in vivo. Our analysis identified all previously characterized Leydig and Sertoli cell-specific markers and identified in a comprehensive manner novel markers of Leydig and Sertoli cells; the translational response of these two cell types to gonadotropins or testosterone was also investigated. Modulation of a small subset of Sertoli cell genes occurred after FSH and testosterone stimulation. However, Leydig cells responded robustly to gonadotropin deprivation and LH restoration with acute changes in polysome-associated mRNAs. These studies identified the transcription factors that are induced by LH stimulation, uncovered novel potential regulators of LH signaling and steroidogenesis, and demonstrate the effects of LH on the translational machinery in vivo in the Leydig cell.
A flat neural network architecture to represent movement primitives with integrated sequencing

The paper proposes a minimalistic network to learn a set of movement primitives and their sequencing in one single feedforward network. Utilizing an ex- treme learning machine with output feedback and a simple inhibition mechanism, this approach can sequence movement primitives efficiently with very moderate network size. It can interpolate movement primitives to create new motions. This work thus demonstrates that an unspecific single hidden layer, that is a flat represen- tation is sufficient to efficiently compose complex sequences, a task which usually requires hierarchy, multiple timescales and multi-level control mechanisms.
Vision-Based Control of a MultiRotor Helicopter

Autonomous air vehicles frequently rely on GPS as a primary source of state feedback. However, relying on GPS disallows operation in enclosed spaces, under heavy vegetation or near large obstacles since GPS does not provide sufficient accuracy in these environments. Similar work in GPS-denied navigation uses laser-based odometry, structured-light or places visual markers in the environment. These approaches are not appropriate for operating in unstructured environments, therefore it is necessary to develop a system around more robust vision-based techniques. This work presents a method for controlling an autonomous, multi-rotor helicopter based on visual odometry which consists of two major sections. First, a method for developing an accurate dynamic model of a multi-rotor helicopter based on a combination of first priciples and emperical data is presented. This modeling technique is used to develop a control system which enables trajectory tracking. Second, a vision-based state-estimation technique is presented along with a hardware implementation that enables execution of the algorithms in real-time on board a small vehicle with strict payload constraints. The methods described are implemented in flight-ready hardware with a minimal weight, power and computational footprint. The system is then evaluated on board a small, eight-rotor helicopter. We successfully demonstrate vision-based trajectory tracking in flight on this vehicle.
ProPOSEC: A Prosody and PoS Annotated Spoken English Corpus

We have previously reported on ProPOSEL, a purpose-built Prosody and PoS English Lexicon compatible with the Python Natural Language ToolKit. ProPOSEC is a new corpus research resource built using this lexicon, intended for distribution with the Aix-MARSEC dataset. ProPOSEC comprises multi-level parallel annotations, juxtaposing prosodic and syntactic information from different versions of the Spoken English Corpus, with canonical dictionary forms, in a query format optimized for Perl, Python, and text processing programs. The order and content of fields in the text file is as follows: (1) Aix-MARSEC file number; (2) word; (3) LOB PoS-tag; (4) C5 PoS-tag; (5) Aix SAM-PA phonetic transcription; (6) SAM-PA phonetic transcription from ProPOSEL; (7) syllable count; (8) lexical stress pattern; (9) default content or function word tag; (10) DISC stressed and syllabified phonetic transcription; (11) alternative DISC representation, incorporating lexical stress pattern; (12) nested arrays of phonemes and tonic stress marks from Aix. As an experimental dataset, ProPOSEC can be used to study correlations between these annotation tiers, where significant findings are then expressed as additional features for phrasing models integral to Text-to-Speech and Speech Recognition. As a training set, ProPOSEC can be used for machine learning tasks in Information Retrieval and Speech Understanding systems.
Slope Centering : Making Shortcut Weights Effective ∗ May 9 , 1998

Shortcut connections are a popular architectural feature of multi-layer perceptrons. It is generally assumed that by implementing a linear submapping, shortcuts assist the learning process in the remainder of the network. Here we find that this is not always the case: shortcut weights may also act as distractors that slow down convergence and can lead to inferior solutions. This problem can be addressed with slope centering, a particular form of gradient factor centering [2]. By removing the linear component of the error signal at a hidden node, slope centering effectively decouples that node from the shortcuts that bypass it. This eliminates the possibility of destructive interference from shortcut weights, and thus ensures that the benefits of shortcut connections are fully realized.
Hardware implementation of smooth region switching for wind turbine control using PDF controller

Control system for wind turbine will operate with different objectives throughout its complete wind speed regions: from cut-in speed to cut-out speed. This paper presents a method for smoothly switching of controllers between these operating regions. The controllers designed in this paper are based on Pseudo Derivative Feedback (PDF), which provides smoother dynamic and simpler tuning of parameters than general PI controllers. Simulations of the presented method are performed with a non-linear wind turbine model at first, followed by preliminary results of hardware-in-the-loop simulation. The simulation and hardware implementation results present a smooth performance of region switching between different controllers and verify the effectiveness of the controller proposed.
Research on Motivation in Collaborative Learning: Moving Beyond the Cognitive–Situative Divide and Combining Individual and Social Processes

In this article we propose that in order to advance our understanding of motivation in collaborative learning we should move beyond the cognitive–situative epistemological divide and combine individual and social processes. Our claim is that although recent research has recognized the importance of social aspects in emerging and sustained motivation in collaborative learning activities, the social is mainly conceived as a unidirectional source of influence on individual motivation. In the article we examine the significance of motivation in research on collaborative learning. We discuss two characterizations of the role of the social in conceptualizations of motivation, namely, social influence and social construction, and outline our case for moving beyond the cognitive–situative divide and combining individual and social processes in research on motivation. Finally, we present illustrations from recent research on motivation in collaborative learning that has attempted to bridge the cognitive–situative divide across theoretical perspectives or using different methods.
Dual-hop variable gain relaying in mixed multipath/shadowing fading channels

In this paper, we investigated the end-to-end performance of a dual-hop variable gain relaying system over mixed fading environment. In such environment, the wireless links of relaying system undergo different fading conditions, where one link is subject to the Nakagami-m fading, the other link is subject to the composite Nakagami-lognormal fading which is approximated by using mixture gamma fading model. Based on the cumulative distribution function of the end-to-end signal-to-noise ratio (SNR), some novel closedform expressions of the average end-to-end SNR, the outage probability, the symbol error rate and the ergodic capacity for the dualhop variable gain system are derived, respectively. Then, some approximate analysis and the diversity order are found based on the above new expressions in high SNR region. Finally, numerical and simulation results are shown to verify the accuracy of the theoretical analysis.
Detection of High Rate STBC in Frequency Selective m- Nakagami Fading Environment

In this article, we concerned with the performance of high rate space time block code (STBC) scheme for Frequency selective fading Environment. Due to large channel delay spread in Frequency selective channel inter symbol interference (ISI) occurred. In high rate STBC, ISI occurs due to loss of "quasi - static" assumption and Classical Zero forcing (ZF) receiver produces error floor in Bit error rate (BER) performance. In this article we evaluate and proposed low Complexity Zero forcing which reduce the complexity of receiver for detection of high rate STBC and evaluate the performance in m-Nakagami fading environment. Keywords- Space time block code (STBC), Inter symbol interference (ISI), Zero forcing (ZF).
Filtering the unknown: speech activity detection in heterogeneous video collections

In this paper we discuss the speech activity detection system that we used for detecting speech regions in the Dutch TRECVID video collection. The system is designed to filter non-speech like music or sound effects out of the signal without the use of predefined non-speech models. Because the system trains its models on-line, it is robust for handling out-of-domain data. The speech activity error rate on an out-of-domain test set, recordings of English conference meetings, was 4.4%. The overall error rate on twelve randomly selected five minute TRECVID fragments was 11.5%.
How many high-level concepts will fill the semantic gap in news video retrieval?

A number of researchers have been building high-level semantic concept detectors such as outdoors, face, building, etc., to help with semantic video retrieval. Using the TRECVID video collection and LSCOM truth annotations from 300 concepts, we simulate performance of video retrieval under different assumptions of concept detection accuracy. Even low detection accuracy provides good retrieval results, when sufficiently many concepts are used. Considering this extrapolation under reasonable assumptions, this paper arrives at the conclusion that "concept-based" video retrieval with fewer than 5000 concepts, detected with minimal accuracy of 10% mean average precision is likely to provide high accuracy results, comparable to text retrieval on the web, in a typical broadcast news collection. We also derive evidence that it should be feasible to find sufficiently many new, useful concepts that would be helpful for retrieval.
The career outlooks of I/S professionals

This follow-up study contrasted the pre-graduation and post-employment job characteristic preferences vs. realities of a sample of 290 I/S professionals. The preference-reality job characteristic discrepancies, job and career attitudes at follow-up, and two moderating variables (I/S salary level and length of I/S employment) became the independent variables in a multiple regression equation with present and long-term I/S career outlook as the dependent variables. The 16 independent variables had a significant impact on both present and long-term I/S career outlook (p < .00001). The reality shock experienced by entering I/S professionals and its impact on career outlook are discussed.
Adaptive threshold for energy detector based on Discrete Wavelet Packet Transform

One promising approach to achieving high precision and low complexity in a cognitive radio system is the energy detector based on the Discrete Wavelet Packet Transform (DWPT). However, the thresholds used in previous spectrum detection algorithms are fixed values determined by false alarm probability and sample points. When the Signal to Noise Ratio (SNR) is lower than 5dB, an energy detector with fixed threshold may falsely determine some unoccupied sub-channels as occupied. In this paper, a threshold adapter adopting adaptive threshold is proposed to increase the detection sensitivity, meanwhile, reduce the computational complexity. Simulation results are presented to demonstrate the effectiveness of this algorithm.
Evaluating the efficacy of a small-group oral narrative intervention programme for pre-primary children with narrative difficulties in a mainstream school setting

ABSTRACT This study designed and evaluated the efficacy of a manualised programme for children in mainstream school with delays in narrative discourse. Efficacy was evaluated using a Phase 1 non-randomised single-subject across multiple-baselines design. The programme was delivered by a speech pathologist with 11 mainstream children aged 5;0–5;11 years, in small groups, three times a week for 6 weeks. Intervention focused on explicit teaching of narrative macrostructure using icons, graphic organisers and repeated story retellings. Microstructure (morphosyntax and vocabulary) was targeted using implicit language facilitation procedures including modelling, recasting, expansion and vertical structuring. Participation in the programme resulted in significant changes with moderate to large effect sizes for most participants in the number of macrostructure elements, and conjunctions and adverbs. Analysis of pre-post standardised narrative data revealed clinically significant improvements for 9 of the 11 participants. The findings add to the research supporting the effectiveness of small-group oral narrative intervention.
Fast denoising for fluorescence image sequences in a nonlocal means framework

In fluorescence live-cell imaging there is always a trade-off between image quality and cell viability. While avoiding photo bleaching and photo toxicity, light exposure time must be limited which results in low signal-to-noise ratio. We present a fast non-local means technique to denoise 3D image sequences acquired via fluorescence microscopy. The commonly used non-local means filter for image sequences is computationally inefficient. We reduce the computational cost by carrying out the denoising in the lower dimensional subspace determined by principal component analysis (PCA). Image neighbourhoods are projected onto the lower dimensional subspace determined by PCA. We use shot boundary detection as a preprocessing step to identify and form different shots with content-wise similar frames. We show that the proposed method reduces the computations in addition to improving the accuracy. Our results are also compared with other fast NLM based techniques.
Ablation of Cellular Prion Protein Does Not Ameliorate Abnormal Neural Network Activity or Cognitive Dysfunction in the J20 Line of Human Amyloid Precursor Protein Transgenic Mice

Previous studies suggested that the cellular prion protein (PrPc) plays a critical role in the pathogenesis of Alzheimer's disease (AD). Specifically, amyloid-β (Aβ) oligomers were proposed to cause synaptic and cognitive dysfunction by binding to PrPc. To test this hypothesis, we crossed human amyloid precursor protein (hAPP) transgenic mice from line J20 onto a PrPc-deficient background. Ablation of PrPc did not prevent the premature mortality and abnormal neural network activity typically seen in hAPPJ20 mice. Furthermore, hAPPJ20 mice with or without PrPc expression showed comparably robust abnormalities in learning and memory and in other behavioral domains at 6–8 months of age. Notably, these abnormalities are not refractory to therapeutic manipulations in general: they can be effectively prevented by interventions that prevent Aβ-dependent neuronal dysfunction also in other lines of hAPP transgenic mice. Thus, at least in this model, PrPc is not an important mediator of Aβ-induced neurological impairments.
Translation and Cultural Adaptation of the Cognitive Assessment System 2: Rating Scale

In Puerto Rico there are no scales in Spanish for teachers to assess the neurocognitive processes underlying the academic and social functioning of students, as established in the Individuals with Disabilities Education Act (IDEA). This paper documents the process of translation and cultural adaptation of the Cognitive Assessment System 2: Rating Scale, which allows teachers to assess the neurocognitive processes of the PASS theory (Planning, Attention, Simultaneous and Successive Processing) in children and adolescents. A concurrent triangulation was used with a sample that included 2 translators, 8 experts in neurocognitive processes and 15 teachers. Chavez and Canino’s (2005) methodology was used to obtain semantic and content equivalence. The procedure included: translation into Spanish, review by bilingual experts and teachers, back-translation and final review by experts. According to the results, the reviewers understood the translation of all items, but suggested semantic (e.g. grammatical) and content (e.g. examples of cultural concepts) changes to maintain equivalence with the original version. This work shows the importance of avoiding literal translations, while using comprehensive models of translation and adaptation. In addition, it provides a tool for the identification and early intervention of Specific Learning Disorders (SLD) in Spanish-speaking students, in compliance with IDEA.
DESIGN OF ON-LINE ALGORITHMS USING HITTING TIMES

Random walks are well known for playing a crucial role in the design of randomized off-line as well as on-line algorithms. In this work we prove some basic identities for ergodic Markov chains (e.g., an interesting characterization of reversibility in Markov chains is obtained in terms of first passage times). Besides providing new insight into random walks on weighted graphs, we show how these identities give us a way of designing competitive randomized on-line algorithms for certain well-known problems.
Anti-red blood cell antibodies, free light chains, and antiphospholipid antibodies in intravenous immunoglobulin preparations.

BACKGROUND Anti-red blood cell antibodies, free light chains (FLC) and prothrombotic proteins (PTP) may co-elute with intact immunoglobulin (IgG), and may be the cause of adverse reactions to intravenous immunoglobulin preparations (IVIG). OBJECTIVES To investigate the presence of residual amounts of these components in IVIG and their effects on ABO blood group agglutination. METHODS Iso-agglutinin anti-A and anti-B activity was determined with a direct hemagglutination assay of red blood cell (RBC) suspensions from 1% of 46 blood donors together with the serial dilutions of five IVIG (IV1, IV2, IV3, IV4, IV5). Anti-A1 monoclonal antibody was used to confirm reactivity with the A1-reference RBC. The selected IVIG were diluted to a final concentration of 25 mg/ml in 0.15 M NaCI and 0.01 M phosphate-buffered saline, pH 7.4, with or without a further twofold dilution in a low ionic strength solution. RESULTS A variation up to fivefold in the titer strength of anti-A/B activity was observed between the IVIG preparations. A2-type RBC required higher IVIG inputs when tested in 0.15 M NaCl. The differences in FLC kappa and lambda concentrations were as high as > 400 mg/L among the various IVIG. Only IV1 had a significantly high level of antiphospholipid IgG antibodies (18 U/ml). We demonstrated the presence of anti-RBC antibodies, FLC and PTP in IVIG preparations. CONCLUSIONS Our findings provide clear evidence that IVIG may harbor pathophysiological substrates with a potential risk for adverse effects such as iatrogenic hemolysis, FLC-associated disorders, and thromboembolism.
Refactoring Network Control and Management: A Case for the 4D Architecture

We argue for the refactoring of the IP control plane to support network-wide objectives and control. We put forward a design that refactors functionality into a novel 4D architecture composed of four separate planes: decision, dissemination, discovery and data. All decision-making logic is moved out of routers along with current management plane functions to create a logically centralized decision plane, where network-level objectives and policies are specified and enforced by direct configuration of states on individual network elements. Pulling much of the control state and logic out of the routers enables both simpler protocols, which do not have to embed decision-making logic, and more powerful decision algorithms for implementing sophisticated goals. Remaining on the routers is a wafer-thin class of intrinsically distributed control functions. These support the discovery plane, consisting of elementary functions to discover topology and network state, and the dissemination plane, consisting of elementary functions to distribute explicit instructions to manipulate the data plane forwarding mechanisms. This paper motivates the need for a new approach to network control and management, describes the 4D architecture, and sketches the design space and challenges posed by the architecture. As a first exploration of the design space and its challengs, we have constructed a working prototype that implements the 4D architecture. Through evaluation of this prototype on 9 different network topologies derived from production networks, we demonstrate that (i) the 4D architecture can achieve subsecond reconvergence times upon single link or router failures and can adequately deal with other failure scenarios including network partition; (ii) the 4D architecture is able to implement a network design intent such as a reachability matrix more robustly than currently possible; and (iii) the 4D architecture does not introduce excess overhead.