Miracle-dz/UniFAR-FTUs huggingface dataset:
Skipping-oriented Data Design for Large-Scale Analytics

Author(s): Sun, Liwen | Advisor(s): Franklin, Michael J | Abstract: As data volumes continue to expand, analytics approaches that require exhaustively scanning data sets become untenable. For this reason, modern analytics systems employ data skipping techniques to avoid looking at large volumes of irrelevant data. By maintaining some metadata for each block of data, a query may skip a data block if the metadata indicates that the block does not contain relevant data. The effectiveness of data skipping, however, depends on how the underlying data are organized into blocks. In this dissertation, we propose a fine-grained data layout framework, called ``Generalized Skipping-Oriented Partitioning and Replication'' (GSOP-R), which aims to maximize query performance through aggressive data skipping. Based on observations of real-world analytics workloads, we find that the workload patterns can be summarized as a succinct set of features. The GSOP-R framework uses these features to transform the incoming data into a small set of feature vectors, and then performs clustering algorithms using the feature vectors instead of the actual data. A resulting GSOP-R layout scheme is highly flexible. For instance, it allows different columns to be horizontally partitioned in different ways and supports replication of only parts of rows or columns. We developed several designs for GSOP-R on Apache Spark and Apache Parquet and then evaluated their performance using two public benchmarks and several real-world workloads. Our results show that GSOP-R can reduce the amount of data scanned and improve end-to-end query response times over the state-of-the-art techniques by a factor of 2 to 9.
A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living

Ambient Assisted Living (AAL) systems aim to enable the elderly people to stay active and live independently into older age by monitoring their behaviour, provide the needed assistance and detect early signs of health status deterioration. Non-intrusive sensors are preferred by the elderly to be used for the monitoring purposes. However, false positive or negative triggers of those sensors could lead to a misleading interpretation of the status of the elderlies. This paper presents a systematic literature review of the sensor failure detection and fault tolerance in AAL equipped with non-intrusive, event-driven, binary sensors. The existing works are discussed, and the limitations and research gaps are highlighted.
A GNU Radio Implementation for Frequency Hopping Spread Spectrum Receiver Synchronization

In this paper a GNU Radio implementation for a signal processing block that allows synchronizing a software defined radio receiver to frequency hopping spread spectrum (FHSS) signals is proposed. The receiver requires no knowledge of the hopping pattern or the dwell time of the FHSS signal. These parameters are re-engineered by the proposed block before the receiver is synchronized to the hopping signal. The implementation is independent of the modulation scheme that is applied to the individual channels. As part of a research project, the signal processing block is implemented with the intention of analyzing the radio communication of civilian drones. However, the concept presented in this paper can also be applied for other use cases.
Complementary Densities of Lévy Walks: Typical and Rare Fluctuations

Strong anomalous diffusion is a recurring phenomenon in many fields, ranging from the spreading of cold atoms in optical lattices to transport processes in living cells. For such processes the scaling of the moments follows ⟨|x (t )|q ⟩ ∼ t qν (q ) and is characterized by a bi-linear spectrum of the scaling exponents, qν (q ). Here we analyze Levy walks, with power law distributed times of flight ψ (τ ) ∼ τ −(1+α ) , demonstrating sharp bi-linear scaling. Previously we showed that for α > 1 the asymptotic behavior is characterized by two complementary densities corresponding to the bi-scaling of the moments of x (t ). The first density is the expected generalized central limit theorem which is responsible for the low-order moments 0 . The second one, a non-normalizable density (also called infinite density) is formed by rare fluctuations and determines the time evolution of higher-order moments. Here we use the Faa di Bruno formalism to derive the moments of sub-ballistic super-diffusive Levy walks and then apply the Mellin transform technique to derive exact expressions for their infinite densities. We find a uniform approximation for the density of particles using Levy distribution for typical fluctuations and the infinite density for the rare ones. For ballistic Levy walks 0 < 1 we obtain mono-scaling behavior which is quantified.
Prostaglandin Signaling Governs Spike Timing-Dependent Plasticity at Sensory Synapses onto Mouse Spinal Projection Neurons

Highly correlated presynaptic and postsynaptic activity evokes spike timing-dependent long-term potentiation (t-LTP) at primary afferent synapses onto spinal projection neurons. While prior evidence indicates that t-LTP depends upon an elevation in intracellular Ca2+ within projection neurons, the downstream signaling pathways that trigger the observed increase in glutamate release from sensory neurons remain poorly understood. Using in vitro patch-clamp recordings from female mouse lamina I spino-parabrachial neurons, the present study demonstrates a critical role for prostaglandin synthesis in the generation of t-LTP. Bath application of the selective phospholipase A2 (PLA2) inhibitor arachidonyl trifluoromethyl ketone (AACOCF3) or the cyclooxygenase 2 (Cox-2) inhibitor nimesulide prevented t-LTP at sensory synapses onto spino-parabrachial neurons. Similar results were observed following the block of the EP2 subtype of prostaglandin E2 (PGE2) receptor with PF 04418948. Meanwhile, perfusion with PGE2 or the EP2 agonist butaprost potentiated the amplitude of monosynaptic primary afferent-evoked EPSCs while decreasing the paired-pulse ratio, suggesting a presynaptic site of action. Cox-2 was constitutively expressed in both spinal microglia and lamina I projection neurons within the superficial dorsal horn (SDH). Suppression of microglial activation with minocycline had no effect on the production of t-LTP, suggesting the possibility that prostaglandins produced within projection neurons could contribute to an enhanced probability of glutamate release at primary afferent synapses. Collectively, the results suggest that the amplification of ascending nociceptive transmission by the spinal SDH network is governed by PLA2–Cox-2–PGE2 signaling. SIGNIFICANCE STATEMENT Long-term potentiation (LTP) of primary afferent synapses contributes to the sensitization of spinal nociceptive circuits and has been linked to greater pain sensation in humans. Prior work has implicated elevated glutamate release in the generation of spike timing-dependent LTP (t-LTP) at sensory synapses onto ascending spinal projection neurons, but the underlying mechanisms remain unknown. Here we provide evidence that the activation of EP2 prostaglandin receptors by prostaglandin E2, occurring downstream of phospholipase A2 and cyclooxygenase 2 activation, mediates t-LTP at these synapses via changes in presynaptic function. This suggests that prostaglandins can increase the flow of nociceptive information from the spinal cord to the brain independently of their known ability to suppress synaptic inhibition within the dorsal horn.
Multi-Domain Flight Simulation with the DLR Robotic Motion Simulator

Aircraft are highly optimized, integrated systems that operate under vastly varying conditions and provide many functionalities. The systems providing these functionalities are highly interconnected, making the design of aircraft a very complex and risky undertaking. The ever increasing complexity is a strong motivation to not only address individual disciplines, but also their integration and interactions from the earliest design stages.Multi-disciplinary modeling and simulation have been of strong interest for many years. In this paper, a highly modular framework for aircraft models and model components is presented that is able to integrate and interchange all relevant physical aspects, systems and environmental aspects.The resulting simulation enables to 'fly' an aircraft with all relevant functionalities under realistic circumstances and enables integrated design analyses, covering operational aspects and failure cases. The integrated simulation can run in batch mode as well as real-time application driving the DLR Robotic Motion Simulator.
Lexicon-based sentiment analysis approach for ranking event entities

Social media platforms (SMP) are new resource for data analytics. Multiple aspects can be studied by using its variety of features. Sentiment analysis (SA) is a rising research topic in SMPs. SA approaches on studying and analysing events are still missing several shortcomings. In this paper, we address the problem of ranking event entities and propose a novel approach for this goal. An entity is a person who presents some task in such event, for e.g., a researcher in a conference. To achieve our target, we employ the lexical approach, in addition to associating features from both Facebook and Twitter platforms. We used Facebook reactions also, that not been used in the state-of-the-art approaches. Our results have shown that by associating both features from Facebook and Twitter and by using reactions, we can successfully rank entities participating in a specific event having high precision.
The Second-Order Factor Structure

A review of the research into the second-order factor structure of the 16 Personality Factor Questionnaire (16 PF) indicates disagreement about the number and meaning of the second-order factors. However, repeated analyses of the second-order factor structure have consistently found fewer than the eight factors suggested by Catell (1973) and the Institute for Personality and Ability Testing (IPAT) (1972). This research extended knowledge in this area by investigating the second-order factor structure of the 16 PF and comparing the results to those found in previous studies. The sample consisted of 2,225 individuals who applied to the college of education of a large university who took the 16 PF as part of admissions requirements. Results yielded a four-factor solution, one of the smallest factor solutions yet obtained. These findings are more consistent with previously reported five-factor solutions and the five second-order factors common to five personality questionnaires than with the eight-factor solution of Catell and IPAT. Ten tables present study findings. (Contains 15 references.) (Author/SLD) *********************************************************************** Reproductions supplied by EDRS are the best that can be made * from the original document. ***********************************************************************
AN OPTICAL CROSS-CORRELATION SCHEME TO SYNCHRONIZE DISTRIBUTED LASER SYSTEMS AT FLASH

The VUV- and soft X-ray free-electron laser FLASH and the planned European XFEL generate X-ray light pulses in the femto-second range. For time-resolved pump-probeex-periments, future operation modes by means of laser seed-ing and for special diagnostic measurements it is crucial to synchronize various laser systems to the electron beam with an long-term stability of better than 30 fs. For this purpose an optical synchronization system is currently being installed and tested at FLASH. In this paper, we report on the progress of the development of a background-freeoptical cross-correlation scheme to synchronize two individual mode-locked laser systems of different center wavelengths and repetition rates with an accuracy of better than 10 fs. The scheme is being tested by linking a commercial Ti:sapphire oscillator, used for electro-optical diagnostics at FLASH, to a locally installed erbium-doped ﬁber laser. Later, this laser will be replaced by an end-point of an actively length-stabilized ﬁber-link distributing the pulses from the master laser oscillator of the machine to lock the diagnostics laser to the optical synchronization system.
Implementing Fusion Techniques for the Classification of Paralinguistic Information

This work tests several classiﬁcation techniques and acoustic features and further combines them using late fusion to classify paralinguistic information for the ComParE 2018 challenge. We use Multiple Linear Regression (MLR) with Ordinary Least Squares (OLS) analysis to select the most informative features for Self-Assessed Affect (SSA) sub-Challenge. We also pro-pose to use raw-waveform convolutional neural networks (CNN) in the context of three paralinguistic sub-challenges. By using combined evaluation split for estimating codebook, we obtain better representation for Bag-of-Audio-Words approach. We preprocess the speech to vocalized segments to improve classi-ﬁcation performance. For fusion of our leading classiﬁcation techniques, we use weighted late fusion approach applied for conﬁdence scores. We use two mismatched evaluation phases by exchanging the training and development sets, and this estimates the optimal fusion weight. Weighted late fusion provides better performance on development sets in comparison with baseline techniques. Raw-waveform techniques perform comparable to the baseline.
Box–Behnken experimental design for preparation and optimization of the intranasal gels of selegiline hydrochloride

Abstract Selegiline hydrochloride (SL) is chosen as an adjunct for the control of clinical signs of Parkinsonian patients. The aim of the present work is to develop and optimize thermosensitive gels using Pluronic (F-127) for enhancing transport of SL into the brain through the nasal route. SL gels were prepared using a cold method and the Box–Behnken experimental design methodology. Drug (SL), gelling agent (F-127), and emulsifier (Propylene glycol, PG) were selected as independent variables, while the gelation temperature, gel strength, pH, gel content, and gel erosion were considered as dependent variables. For further understanding of the interaction between the various variables, contour plots and surface plots were also applied. Selected formulations, like S10 (contain 25 mg SL, 20 g F-127, and 1 g PG) and S14 (contain 50 mg SL, 18 g F-127 and 1 g PG), had a clear appearance in the sol form, with gelling temperature of the nasal gel ranging between 33 and 34, respectively. The gel strength of the formulations varied from 4.67 and 0.68 mm and the drug content was 100%. The pH of the formulations ranged between 6.71 and 7.11. Detachment force was acceptable (63.69–244.16 N/cm2) to provide prolonged adhesion. In vitro, drug release studies showed that the prepared formulations could release SL for up to 8 h. Permeation flux for the S10 gel was 0.0002 mg/min/cm2. Results demonstrated that the potential use of SL gels can enhance the therapeutic effect of SL through the intranasal administration.
Systolic Sparse Matrix Vector Multiply in the Age of TPUs and Accelerators

Tensor Processing Units has brought back systolic arrays as a computational alternative to high performance computing. Recently Google presented a Tensor Processing Unit for handling matrix multiplication using systolic arrays. This unit is designed for dense matrices only. As they stated, sparse architectural support was omitted momentarily but they will focus on sparsity in future designs. We propose a systolic array to compute the Sparse Matrix Vector product in $T2(n)\approx \displaystyle \lceil\frac{nnz}{2}\rceil+2n+2$ using 2 n+2 processing elements. The systolic array we propose also use accumulators to collect the partial results of the resulting vector and supports adapting tiling.
Research of dynamic load balancing based on stimulated annealing algorithm

This article analyses advantages and shortages of classical load balancing algorithms based on dynamic feed-back on server cluster, and combined stimulated annealing with this strategy to put forward an optimised model of dynamic load balancing. This model uses stimulated annealing algorithm to calculate accurate performance parameters of load information on every service node, then estimates the actual load of nodes by dynamic feed-back, in order to insure a reasonable distribution reasonable of tasks. Experimental result shows that in the case of large amount of requests, this algorithm, in comparison with classical load balancing strategy of dynamic feedback, can effectively reduce response time of tasks and ensure high throughput which could improve the whole system performance.
Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato1[OPEN]

Analysis of integrated prior knowledge and ensemble networks highlights a previously unidentified connection between ethylene and salicylic acid signaling modules in potato. To develop novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modeling represents a powerful tool that can unravel properties of complex biological systems. In this study, we aimed to use network modeling to better understand immune signaling in potato (Solanum tuberosum). For this, we first built on a reliable Arabidopsis (Arabidopsis thaliana) immune signaling model, extending it with the information from diverse publicly available resources. Next, we translated the resulting prior knowledge network (20,012 nodes and 70,091 connections) to potato and superimposed it with an ensemble network inferred from time-resolved transcriptomics data for potato. We used different network modeling approaches to generate specific hypotheses of potato immune signaling mechanisms. An interesting finding was the identification of a string of molecular events illuminating the ethylene pathway modulation of the salicylic acid pathway through Nonexpressor of PR Genes1 gene expression. Functional validations confirmed this modulation, thus supporting the potential of our integrative network modeling approach for unraveling molecular mechanisms in complex systems. In addition, this approach can ultimately result in improved breeding strategies for potato and other sensitive crops.
IS THE MAGNETIC FIELD IN THE HELIOSHEATH LAMINAR OR A TURBULENT SEA OF BUBBLES?

All current global models of the heliosphere are based on the assumption that the magnetic field in the heliosheath, in the region close to the heliopause (HP), is laminar. We argue that in that region the heliospheric magnetic field is not laminar but instead consists of magnetic bubbles. We refer to it as the bubble-dominated heliosheath region. Recently, we proposed that the annihilation of the “sectored” magnetic field within the heliosheath as it is compressed on its approach to the HP produces anomalous cosmic rays and also energetic electrons. As a product of the annihilation of the sectored magnetic field, densely packed magnetic islands (which further interact to form magnetic bubbles) are produced. These magnetic islands/bubbles will be convected with ambient flows as the sector region is carried to higher latitudes filling the heliosheath. We further argue that the magnetic islands/bubbles will develop upstream within the heliosheath. As a result, the magnetic field in the heliosheath sector region will be disordered well upstream of the HP. We present a three-dimensional MHD simulation with very high numerical resolution that captures the north–south boundaries of the sector region. We show that due to the high pressure of the interstellar magnetic field a north–south asymmetry develops such that the disordered sectored region fills a large portion of the northern part of the heliosphere with a smaller extension in the southern hemisphere. We suggest that this scenario is supported by the following changes that occurred around 2008 and from 2009.16 onward: (1) the sudden decrease in the intensity of low energy electrons (0.02–1.5 MeV) detected by Voyager 2, (2) a sharp reduction in the intensity of fluctuations of the radial flow, and (3) the dramatic differences in intensity trends between galactic cosmic ray electrons (3.8–59 MeV) at Voyager 1 and 2. We argue that these observations are a consequence of Voyager 2 leaving the sector region of disordered field during these periods and crossing into a region of unipolar laminar field.
Micro- and Nanoscale Approaches in Antifungal Drug Discovery

Clinical needs for novel antifungal agents have increased due to the increase of people with a compromised immune system, the appearance of resistant fungi, and infections by unusual yeasts. The search for new molecular targets for antifungals has generated considerable research, especially using modern omics methods (genomics, genome-wide collections of mutants, and proteomics) and bioinformatics approaches. Recently, micro- and nanoscale approaches have been introduced in antifungal drug discovery. Microfluidic platforms have been developed, since they have a number of advantages compared to traditional multiwell-plate screening, such as low reagent consumption, the manipulation of a large number of cells simultaneously and independently, and ease of integrating numerous analytical standard operations and large-scale integration. Automated high-throughput antifungal drug screening is achievable by massive parallel processing. Various microfluidic antimicrobial susceptibility testing (AST) methods have been developed, since they can provide the result in a short time-frame, which is necessary for personalized medicine in the clinic. New nanosensors, based on detecting the nanomotions of cells, have been developed to further decrease the time to test antifungal susceptibility to a few minutes. Finally, nanoparticles (especially, silver nanoparticles) that demonstrated antifungal activity are reviewed.
Cost-effective analysis of teaching pelvic examination skills using Gynaecology Teaching Associates (GTAs) compared with manikin models (The CEAT Study)

Objective To determine the cost-effectiveness of Gynaecology Teaching Associate (GTA) teaching versus conventional pelvic model (manikin) teaching of pelvic examination skills for final year medical students within a UK undergraduate obstetrics and gynaecology (O&G) curriculum. Methods An economic evaluation was carried out alongside a randomised controlled trial involving 492 final year medical students. 240 students received manikin teaching, and 241 GTA-led teaching. 418 (85%) students completed their assessment. Proficiency in gynaecological pelvic examination on GTAs was estimated by a senior clinical examiner, blinded to the method of teaching, using a standardised assessment tool. University of Birmingham Medical School thresholds were applied to determine proficiency levels; competence (pass) 50%, merit 60% and distinction 70%. Costs incurred in the delivery of both the educational pathways (control and intervention) were combined. All costs are reported in 2013–2014 prices and earlier costs adjusted using inflation indices. Outcome measures Cost per student competent in pelvic examination at completion of a 5-week clinical O&G placement. Results GTA teaching was more effective compared with conventional teaching with 12 more students considered competent at pass level and 28 more students competent at merit and distinction levels, respectively. However, the average cost of GTA teaching was £45.06 per student compared with £7.40 per student for conventional teaching, with an increased cost of £37.66 per student. The incremental cost-effectiveness ratio demonstrated that it cost an additional £640.20 per competent student and £274.37 per student competent at merit level and £274.37 at distinction level compared with conventional manikin-based teaching. Conclusions GTA teaching of female pelvic examination at the start of undergraduate medical student O&G clinical placements is shown to cost more and be more effective. GTA teaching is likely to be considered cost-effective in the context of other tests, and over the lifespan of a competent doctor’s career. Trial registration number NCT01944592.