Miracle-dz/UniFAR-FTUs huggingface dataset:
Back-stepping control design for transport aircraft in airdropping heavy cargo

In this paper, a nonlinear model for transport aircraft with continuous airdropping heavy cargo is presented and back-stepping controller is employed. For the attitude subsystem and the velocity subsystem, the dynamics are transformed into the strict-feedback form by using back-stepping scheme respectively. In the back-stepping controller, the virtual controllers are designed to compensate control system and ensure the stability and reliability. Moreover, to avoid "explosion of complexity", command filter design is used. With the proposed controller, the bounded stability analysis is presented. The simulations compare the accurate model with the model with uncertainties, and proof the effectiveness and robustness of back-stepping controller in continuous airdropping heavy cargos.
Eighteen Years with Spinal Muscular Atrophy (SMA) Type 1

SMA-1, also known as Werdnig-Hoffmann disease, is the most common neuromuscular disease of hypotonic newborns. Its incidence is over 1 per 8000 births and is a common cause of sudden infant death syndrome. It is characterized by the degeneration of the anterior horn cells of the spinal cord and of the motor nuclei in the lower brainstem (1). About 99% of patients have deletions in exons 6 and 7 of chromosome 5q13 causing a decrease in the transcription of survival motor neuron (SMN) protein. The SMAs are classified as types 1 through 4. Children with type 1 are hypotonic at birth, never sit independently, and 85% develop acute respiratory failure (ARF) before 18 months of age and the remainder, subsequently (2). Patients with severe SMA-1 either die or become continuously respirator-dependent before 6 months of age; patients with typical SMA-1 develop ARF during otherwise benign upper respiratory tract infections (URIs) at 6 to 18 months of age; and the 10 to 15% with mild SMA-1 develop ARF during URIs (2). When intubated for acute ARF, only 6% of the conventionally managed typical SMA-1 patients are successfully extubated without undergoing tracheotomy (3). Although there are numerous reports of severe and typical SMA-1 patients dying from ARF before 18 months of age (4–6), it has also been reported that these patients can survive for years when undergoing tracheotomy for long-term tracheostomy mechanical ventilation (TMV) (3, 7). Thus far, however, only one center has reported prolonged survival in SMA-1 by continuous long-term noninvasive intermittent positive pressure ventilatory support (CNVS) or high span (inspiratory positive airway pressure [IPAP], expiratory PAP [EPAP] spans greater than 10 cm H2O) bi-level PAP without the need to resort to tracheotomy (3). This has led to intubated children with SMA-1 being flown to that center from their native lands to avoid tracheotomy by being successfully extubated despite having failed extubation attempts and all spontaneous breathing trials (8). In some cases, families have emigrated to avoid their children from ever having to undergo tracheotomy. This is a report of one such patient who, along with her family, emigrated from Iran to prolong her survival without undergoing tracheotomy.
Distance metric learning with eigenvalue fine tuning

Distance metric learning focuses on learning one global or multiple local distance functions to draw similar instances close to each other and push away dissimilar ones. Most existing work has to do matrix projection to learn distance functions. In this paper, we present a novel distance function learning model which is based on eigenvalue fine tuning. Our model not only is able to learn the global distance function but also can be easily adopted into local metric learning tasks. From the perspective of dimension reduction, the proposed model can measure how much information has been preserved after feature transformation. Moreover, we connect our model with principal components analysis to improve its performance by introducing the label information. Experimental results have demonstrated the effectiveness of the proposed method.
Effect of autoclaving cocoa nibs before roasting on the precursors of the Maillard reaction and pyrazines

Summary Nibs of raw cocoa (N) were roasted (R) at 150 ∞C for 38 min. Some samples were autoclaved at 121 ∞C for 15 min (A) and roasted (AR) at 150 ∞C for 38 min. The samples were then analysed for moisture content, water activity (aw), reducing sugar and amino group (a-N) levels and, absorption at 275 nm (A275) for a trichloro acetic acid (TCA) extract and at 280 nm (A280) for the distillate. Tri- and tetramethylpyrazines were quantified by solid phase micro extraction-gas chromatography (SPME-GC). There was a reduction in the levels of a-N, in the order N>A>R>AR. The same sequence was observed for reducing sugars. The tetramethylpyrazine had an Areapyrazine/ Areainternal standard of N<R<A<AR and for trimethylpyrazine the order was N<A <R<AR. After autoclaving, the Atetra/Atri decreased from 31.30 (N) to 11.06 (A). With roasting, this ratio was 2.18 (R) and 2.58 (AR). Autoclaving nibs before roasting significantly influenced the levels of compounds which contribute to cocoa flavour formation and increased the concentration of tri- and tetramethylpyrazines in the headspace of cocoa samples. Autoclaving prior to roasting also aAected the sensory properties of the samples.
(μ3-Hydrido)[μ3-2-(trimethylsilyl)ethylidyne-κ3 C 1:C 1:C 1]tetrakis[(η5-cyclopentadienyl)cobalt(II)]

In the title compound, [Co4(C5H5)4(μ3-CCH2SiMe3)(μ3-H)], the Co atoms form a distorted tetrahedron with the ethylidyne moiety bridging three of the Co atoms as well as the hydrido ligand also bridging three of the Co atoms. The Co—Co bond lengths in the Co4 tetrahedron vary from 2.3844 (4) to 2.4608 (4) Å. Each Co atom is additionally η5-bonded to a cyclopentadienyl (Cp) anion.
: CARDIAC ACQUISITION PLANE RECOGNITION 1 Recognizing cardiac magnetic resonance acquisition planes

In this paper we propose a method for automatic wrangling of missing or noisy acquisition plane information of cardiac magnetic resonance images in order to simplify case filtering and image lookup in large collections of cardiac data. To recognize standard cardiac planes we use features based on image miniatures combined with a decision forest classifier. We show that augmenting the dataset with a set of nondestructive transformations can improve classification accuracy. Our approach compares favorably to the state of the art while requiring fewer manual annotations.
Incidence and characteristics of injuries during the 2011 West Africa Football Union (WAFU) Nations' Cup.

BACKGROUND Prospective studies on football injuries and their risk factors in the African setting are sparse. Such studies are needed to understand the peculiarities of injuries and hence proffer appropriate intervention for injury prevention in the region. OBJECTIVE To evaluate the incidence and characteristics of match injuries during the 2011 West Africa Football Union (WAFU) cup. METHODS Team physiotherapists from the participating teams documented all newly incurred injuries on standardised injury report forms using the Federation of International Football Association's (FIFA) Medical Assessment and Research Centre protocols. RESULTS An overall of 89 injuries were sustained during the tournament, resulting in 9.9 injuries per match or 289 injuries per 1000 player hours. Seventeen (19.1%) of these injuries resulted in loss of competition activity (time-loss), equivalent to 1.9 injuries per match or 55.2 injuries per 1000 player hours. Over three quarters (73; 82%) of injuries were incurred through contact with another player. The lower leg accounted for almost a quarter of all injuries (21; 23.6%) while the knee recorded the highest number of time-loss injuries (5; 29.4%). The most frequent types of injury were contusion (61; 68.5%) and strain (13; 14.6%). CONCLUSION The overall incidence of injuries during the WAFU cup was much higher than those of other tournaments ever documented but the characteristics of injuries were similar. In order to fully define the nature of injuries and more reliably identify the risk of injury for the establishment of injury prevention strategies that will be appropriate for this region of the world, it is imperative that further systematic injury recording and analysis in African players are carried out.
Correlated Multiple Antennas Spectrum Sensing Under Calibration Uncertainty

We address the problem of spectrum sensing in cognitive radios (CRs) when the secondary user (SU) is equipped with a multiantenna receiver. We consider scenarios with correlation between the received channels at different antennas and unequal per-antenna noise variances to accommodate calibration errors. First, we derive the exact as well as the asymptotic performance of the genie-aided (benchmark) detector with perfect knowledge of the antenna correlation coefficients, the primary user (PU) signal power and the noise covariance matrix. Then, we consider the sensing problem in which the SU is non-cognizant of the per-antenna noise variances, the PU signal power and the correlation of channel gains, starting with a specific treatment of the two-antenna case. For a general multiantenna receiver, we propose combining the derived test statistics among all antenna pairs. The related optimization problem to obtain the optimum combination weights is analyzed, which requires the analytical performance characterization of the constituent two-antenna detector. Thus, we compute the exact performance of the proposed detector in a special case (a particular case of the Hadamard ratio test) in terms of its detection and false alarm probabilities. Performance analyses are verified with simulations, showing that the proposed detector outperforms several recently-proposed multiantenna detectors for CR in the scenarios considered.
Factors distiguishing employed from unemployed people in the Positive Health Study

Objective:To identify predictors of unemployment among Australian people living with HIV/AIDS. Design:A longitudinal cohort of Australian men living with HIV/AIDS. Methods:Participants were separated into two groups, currently working versus currently unemployed. The two groups were compared on a range of factors related to physical health, mental health and sociodemographic variables. Each family of variables was reduced to a set of best predictors, and multivariate log binomial regression was used to identify the predictors of unemployment. Results:Unemployment was more likely among those who experienced HIV/AIDS-related illness, scored higher on the Kessler scale of psychological distress and were older. There was a lower likelihood of unemployment among those who had better self-rated health, had been living with HIV/AIDS for a shorter period and who had a tertiary education. Conclusion:These findings indicate that unemployment among people living with HIV/AIDS is best understood within a combined social and medical context. Interventions that acknowledge the differences in age and education that contribute to unemployment would improve employment prospects among people living with HIV/AIDS.
Fault-tolerant incremental diagnosis with limited historical data

We describe a novel incremental diagnostic system based on a statistical model that is trained from empirical data. The system guides the user by calculating what additional information would be most helpful for the diagnosis. We show that our diagnostic system can produce satisfactory classification rates, using only small amounts of available background information, such that the need of collecting vast quantities of initial training data is reduced. Further, we show that incorporation of inconsistency-checking mechanisms in our diagnostic system reduces the number of incorrect diagnoses caused by erroneous input.
The Silicon Valley Edge: A Habitat for Innovation and Entrepreneurship

Introduction 1. The Silicon Valley habitat Chong-Moon Lee, William F. Miller, Marguerite Gong Hancock and Henry S. Rowen 2. Mysteries of the region: knowledge dynamics in Silicon Valley John Seely Brown and Paul Duguid Part I. Silicon Valley Today: 3. A profile of the Valley's evolving structure Doug Henton 4. Life in Silicon Valley: a first-hand view of the region's growth E. Floyd Kvamme 5. Innovation in business models T. Michael Nevens 6. Four styles of Valley entrepreneurship Chong-Moon Lee 7. Changing everything: the Internet revolution and Silicon valley Steve Jurvetson Part II. The Evolution of Silicon Valley: 8. Fairchild semiconductor and its influence Christopher Le cuyer 9. Serendipity or strategy: how technology and markets came to favor Silicon Valley Henry S. Rowen 10. The role of Stanford University: a Dean's reflections James Gibbons 11. Social networks in Silicon Valley' Emilio J. Castilla, Hokyu Hwang, Ellen Granovetter and Mark Granovetter 12. Networks of immigrant entrepreneurs Annalee Saxeninan Part III. A Clustered Community: 13. Venture capitalists: the coaches of Silicon Valley Thomas F. Hellmann 14. The valley of deals: how venture capital helped shape the region P. Banatao and Kevin A. Fong 15. Fueling the revolution: commercial bank financing John C. Dean 16. Advising the new economy: the role of lawyers Craig W. Johnson 17. Shepherding the faithful: the influence of executive search firms Thomas J. Friel 18. Guiding the innovators: why accountants are valued James D. Atwell 19. Free advice: consulting the Silicon Valley way Regis McKenna Afterword: sustaining the edge Chong-Moon Lee, William F. Miller, Marguerite Gong Hancock and Henry S. Rowen Notes References Index.
Detection of pathogens in foods: the current state-of-the-art and future directions

Over the last fifty years, microbiologists have developed reliable culture-based techniques to detect food borne pathogens. Although these are considered to be the “gold-standard,” they remain cumbersome and time consuming. Despite the advent of rapid detection methods such as ELISA and PCR, it is clear that reduction and/or elimination of cultural enrichment will be essential in the quest for truly real-time detection methods. As such, there is an important role for bacterial concentration and purification from the sample matrix as a step preceding detection, so-called pre-analytical sample processing. This article reviews recent advancements in food borne pathogen detection and discusses future methods with a focus on pre-analytical sample processing, culture independent methods, and biosensors.
Secure virtual private networks: the future of data communications

The Internet is an almost ideal means for information retrieval and exchange. It is cost-effective, easy to use and easily accessible. However, it can also be susceptible to devious practices such as data tempering, eavesdropping and theft. This paper analyses secure virtual private networks lVPNsr and their use in countering the problems of the Internet. Copyright © 1999 John Wiley & Sons, Ltd.
Zimmermann and Monika Sieverding and assessment methods Young adults ' images of abstaining and drinking : Prototype dimensions , correlates

This research investigated contents of actor and abstainer prototypes with regard to young adults’ social drinking combining quantitative and qualitative approaches (adjective ratings, N = 300; open answers, N = 90). Exploratory and confirmatory factor analyses yielded two factors (sociability/hedonism, responsibility) in both prototypes, confirmed by qualitative data. Given the importance for intention and willingness to drink alcohol, interventions should focus on the factor ‘sociability/hedonism’ of the actor and the abstainer prototype to reduce heavy drinking; addressing ‘responsibility’ may be ineffective. Participants’ evaluations appeared to be less prone to mean tendencies subsequent to open answers compared with adjective scales.
Support for a Long Lifetime and Short End-to-End Delays with TDMA Protocols in Sensor Networks

This work addresses a tough challenge of achieving two opposing goals: ensuring long lifetimes and supporting short end-to-end delays in sensor networks. Obviously, sensor nodes must wake up often to support short delays in multi-hop networks. As event occurs seldom in common applications, most wake-up are useless: nodes waste energy due to idle listening. We introduce a set of solutions, referred to as LETED (limiting end-to-end delays), which shorten the wake-up periods, reduce idle listening, and save energy. We exploit hardware features of available transceivers that allow early detection of idle wake-up periods. This feature is introduced on top of our approach to reduce idle listening stemming from clock drift owing to the estimation of run-time drift. To evaluate LETED and other MAC protocols that support short end-to-end delays we present an analytical model, which considers almost 30 hardware and software parameters. Our evaluation revealed that LETED reduces idle listening by 15x and more against similar solutions. Also, LETED outperforms other protocols and provides significant longer lifetimes. For example, nodes with LETED work 8x longer than those with a common TDMA and 2x-3x longer than with protocols based on preamble sampling, like B-MAC.
Teaching Software Defined Networking: It's not just coding

The current distributed networking model is the basis for applied network management courses all over the world, at all levels of adult education. This is because the one model has become dominant in the established networks throughout the world. There is evidence this domination is lessening. Software Defined Networking (SDN) has been in use in datacentres and private networks for over 10 years and is slowly emerging from the datacentre towards becoming an option for any TCP/IP network. There are numerous potential advantages to an organisation that chooses to adopt SDN. It is a key part of securing our future in the changing world of network infrastructure.
Predicting Age and Gender by Keystroke Dynamics and Mouse Patterns

In human computer interaction, some of the user activities are intentional, and other unintentional, but user interfaces are usually designed to react only to intentional commands. However, user's unintentional activity contains many clues about a user, that can be beneficial to take into account in designing appropriate response. Current study focuses on these unintentional traces, that left behind by use of standard input devices, keyboard and mouse, and specifically, we try to predict users age and gender. Mouse and keyboard data used in this study, are collected in six different systems between 2011 and 2017 in total from 1519 subjects. Some supervised machine learning models yield to f-scores over 0.9 when predicted both user age or gender.
Adaptive subspace sampling for class imbalance processing

This paper presents a novel oversampling technique that addresses highly imbalanced data distribution. At present, the imbalanced data that have anomalous class distribution and underrepresented data are difficult to deal with through a variety of conventional machine learning technologies. In order to balance class distributions, an adaptive subspace self-organizing map (ASSOM) that combines the local mapping scheme and globally competitive rule is proposed to artificially generate synthetic samples focusing on minority class samples. The ASSOM is conformed with feature-invariant characteristics, including translation, scaling and rotation, and it retains the independence of basis vectors in each module. Specifically, basis vectors generated via each ASSOM module can avoid generating repeated representative features that offer nothing but heavy computational load. Several experimental results demonstrate that the proposed ASSOM method with supervised learning manner is superior to other existing oversampling techniques.
EEG Correlations during WCST Performance in Female Adolescents with Sexual Abuse-Related Post-Traumatic Stress Disorder

Child sexual abuse (CSA) survivors can present post-traumatic stress disorder (PTSD) and alterations in EEG activity and cognition. The aim of this study was to evaluate EEG correlations in female adolescents with CSA-related PTSD during performance of the Wisconsin Card-Sorting Test (WSCT). Inter- and intrahemispheric EEG correlations (INTERr and INTRAr) of those subjects were calculated at rest and during performance of WCST. On this task, the PTSD group obtained higher scores than the control group for the number of correct responses and failure to maintain set. In the between-groups comparisons, the PTSD group presented a higher INTERr between frontal areas in the gamma and slow bands, as well as a higher correlation in the delta band at Fp1-F3; however, this group presented a lower INTRAr between Fp1-P3 and Fp2-P4 in the theta and alpha1 bands. In the comparison between conditions, the PTSD group presented an increased correlation during execution of the WCST, mainly in the gamma band, while the control group showed a decrease of INTRAr in the slow bands. Results are discussed with respect to the influence of CSA- related PTSD on the development of cognition and functional connectivity in the brain.
Wireless Sensing in Complex Electromagnetic Media: Construction Materials and Structural Monitoring

In this paper, wireless sensing in the presence of complex electromagnetic media created by combinations of reinforcing bars and concrete is investigated. The wireless displacement sensing system, primarily designed for use in structural health monitoring (SHM), is composed of a comb-like nested split-ring resonator (NSRR) probe and a transceiver antenna. Although each complex medium scenario is predicted to have a detrimental effect on sensing in principle, it is demonstrated that the proposed sensor geometry is able to operate fairly well in all scenarios except one. In these scenarios that mimic real-life SHM, it is shown that this sensor exhibits a high displacement resolution of 1 μm, a good sensitivity of 7 MHz/mm in average, and a high dynamic range extending over 20 mm. For the most disruptive scenario of placing concrete immediately behind NSRR, a solution based on employing a separator behind the probe is proposed to overcome the handicaps introduced by the medium. In order to obtain a one-to-one mapping from the measured frequency shift to the displacement, a numerical fit is proposed and used. The effects of several complex medium scenarios on this fit are discussed. These results indicate that the proposed sensing scheme works well in real-life SHM applications.
Compensative microstepping based position control with passive nonlinear adaptive observer for permanent magnet stepper motors

1991 Copyright c The Korean Institute of Electrical Engineers This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Compensative Microstepping Based Position Control with Passive Nonlinear Adaptive Observer for Permanent Magnet Stepper Motors