bluuebunny/crossref_metadata_2025 huggingface dataset:
Pediatric Sarcoidosis: A Review with Emphasis on Early Onset and High-Risk Sarcoidosis and Diagnostic Challenges
Authors: Chiu Brian , Chan Jackie , Das Sumit , Alshamma Zainab , Sergi Consolato
Published: October 2019

Sarcoidosis is a non-necrotizing granulomatous inflammatory syndrome with multisystemic manifestations. We performed a systematic review of sarcoidosis in the pediatric population with particular emphases on early onset sarcoidosis, high-risk sarcoidosis, and newly reported or unusual sarcoid-related diseases. Blau Syndrome and early onset sarcoidosis/ BS-EOS are seen in children younger than five years old presenting with extra-thoracic manifestations but usually without lymphadenopathy and/or pulmonary involvement. The prevalence of high-risk sarcoidosis is very low in children and is further limited by the difficulty of diagnosis in symptomatic children and underdiagnosis in subclinical or asymptomatic patients. Reports of sarcoidal syndromes in users of E-cigarette/marijuana/other flavorings and their induction in cancer immunotherapies are of interests and may be challenging to differentiate from metastatic malignancy. The diagnostic considerations in pediatric sarcoidosis are to support a compatible clinicoradiographic presentation and the pathologic findings of non-necrotizing granulomas by ruling out granulomas of infective etiology. There is no absolutely reliable diagnostic test for sarcoidosis at present. The use of endoscopic bronchial ultrasound (EBUS) and transbronchial fine needle aspiration (TBNA) sampling of intrathoracic lymph nodes and lung, and for superficially accessible lesions, with cytopathological assessment and pathological confirmations provide fair diagnostic yield and excellent patient safety profile in children.
The Newly Normed SKT Reveals Differences in Neuropsychological Profiles of Patients with MCI, Mild Dementia and Depression
Authors: Lehfeld Hartmut , Stemmler Mark
Published: October 2019

The SKT (Syndrom-Kurztest) is a short cognitive performance test assessing deficits of memory and attention in the sense of speed of information processing. The new standardization of the SKT (2015) aimed at improving its sensitivity for early cognitive decline due to dementia in subjects aged 60 or older. The goal of this article is to demonstrate how the neuropsychological test profile of the SKT can be used to provide valuable information for a differential diagnosis between MCI (mild cognitive impairment), dementia and depression. n = 549 patients attending a memory clinic (Nuremberg, Germany) were diagnosed according to ICD-10 and tested with the SKT. The SKT consists of nine subtests, three for the assessment of memory and six for measuring attention in the sense of speed of information processing. The result of the SKT test procedure is a total score, which indicates the severity of overall cognitive impairment. Besides the summary score, two subscores for memory and attention can be interpreted. Using the level of depression as a covariate, statistical comparisons of SKT test profiles between the three patient groups revealed that depressed patients showed more pronounced deficits than MCI patients in all six attention subtests. On the other hand, MCI patients displayed significantly greater mnestic impairment than the depressed group, which was indicated by significant differences in the memory subscore. MCI and dementia patients showed similar deficit patterns dominated by impairment of memory (delayed recall) with MCI patients demonstrating less overall impairment. In sum, the SKT neuropsychological test profiles provided indicators for a differential diagnosis between MCI and beginning dementia vs. depression.
Accelerated Reliability Growth Test for Magnetic Resonance Imaging System Using Time-of-Flight Three-Dimensional Pulse Sequence
Authors: Anand Pradeep Kumar , Shin Dong Ryeol , Saxena Navrati , Memon Mudasar Latif
Published: October 2019

A magnetic resonance imaging (MRI) system is a complex, high cost, and long-life product. It is a widely known fact that performing a system reliability test of a MRI system during the development phase is a challenging task. The major challenges include sample size, high test cost, and long test duration. This paper introduces a novel approach to perform a MRI system reliability test in a reasonably acceptable time with one sample size. Our approach is based on an accelerated reliability growth test, which consists of test cycle made of a very high-energy time-of-flight three-dimensional (TOF3D) pulse sequence representing an actual hospital usage scenario. First, we construct a nominal day usage scenario based on actual data collected from an MRI system used inside the hospital. Then, we calculate the life-time stress based on a usage scenario. Finally, we develop an accelerated reliability growth test cycle based on a TOF3D pulse sequence that exerts highest vibration energy on the gradient coil and MRI system. We use a vibration energy model to map the life-time stress and reduce the test duration from 537 to 55 days. We use a Crow AMSAA plot to demonstrate that system design reaches its useful life after crossing the infant mortality phase.
Privacy-Constrained Biometric System for Non-Cooperative Users
Authors: S. Jahromi Mohammad N. , Buch-Cardona Pau , Avots Egils , Nasrollahi Kamal , Escalera Sergio , Moeslund Thomas B. , Anbarjafari Gholamreza
Published: October 2019

With the consolidation of the new data protection regulation paradigm for each individual within the European Union (EU), major biometric technologies are now confronted with many concerns related to user privacy in biometric deployments. When individual biometrics are disclosed, the sensitive information about his/her personal data such as financial or health are at high risk of being misused or compromised. This issue can be escalated considerably over scenarios of non-cooperative users, such as elderly people residing in care homes, with their inability to interact conveniently and securely with the biometric system. The primary goal of this study is to design a novel database to investigate the problem of automatic people recognition under privacy constraints. To do so, the collected data-set contains the subject’s hand and foot traits and excludes the face biometrics of individuals in order to protect their privacy. We carried out extensive simulations using different baseline methods, including deep learning. Simulation results show that, with the spatial features extracted from the subject sequence in both individual hand or foot videos, state-of-the-art deep models provide promising recognition performance.
Quantum Dynamics in a Fluctuating Environment
Authors: Cai Xiangji
Published: October 2019

We theoretically investigate the dynamics of a quantum system which is coupled to a fluctuating environment based on the framework of Kubo-Anderson spectral diffusion. By employing the projection operator technique, we derive two types of dynamical equations, namely, time-convolution and time-convolutionless quantum master equations, respectively. We derive the exact quantum master equations of a qubit system with both diagonal splitting and tunneling coupling when the environmental noise is subject to a random telegraph process and a Ornstein-Uhlenbeck process, respectively. For the pure decoherence case with no tunneling coupling, the expressions of the decoherence factor we obtained are consistent with the well-known existing ones. The results are significant to quantum information processing and helpful for further understanding the quantum dynamics of open quantum systems.
Undergraduate Disabled Students as Knowledge Producers including Researchers: A Missed Topic in Academic Literature
Authors: Lillywhite Aspen , Wolbring Gregor
Published: October 2019

Research experience is beneficial for undergraduate students for many reasons. For example, it is argued in academic literature and in reports produced by various organizations that engage with science, technology, engineering and math (STEM) education and science education that undergraduate research experience increases the graduation rate in STEM disciplines as well as the amount of students thinking about STEM careers. As such, being researchers should also be of benefit to undergraduate disabled students in all disciplines including STEM education. However, given that undergraduate disabled students encounter many problems within post-secondary education, including STEM education, undergraduate disabled students might encounter problems in becoming researchers. Policies are to be guided by knowledge and evidence. However, knowledge and evidence deficits exist in relation to the lived experience of disabled people. Undergraduate disabled students could decrease the knowledge deficit as researchers and knowledge producers. The numbers of disabled academic faculty are judged as being too low and efforts are under way to increase the number of disabled academics. Increasing the number of undergraduate disabled researchers might increase the available pool of disabled students that pursue an academic career. Given the important role research performed by undergraduate disabled students can play and given that many studies highlight problems for disabled students in post-secondary education in general, we used a scoping review approach to investigate the coverage of undergraduate disabled students as knowledge producers, including as researchers, in the academic literature. Using various search strategies, we obtained 1299 initial hits. However, only 15 had relevant content. No study investigated how undergraduate disabled students select their research topics or how they are enticed to pursue research projects outside of a course-based framework. No study looked at the linkage between being an undergraduate disabled researcher and career choices or using the obtained research skills on the undergraduate level in one’s role as a community member after graduation. Our findings suggest an opportunity for many fields, ranging from disability studies to STEM education, to generate more empirical data and conceptual work on the role of undergraduate disabled students as knowledge producers including as researchers. Such studies could help to increase the numbers of undergraduate disabled students as knowledge producers, including researchers, which in turn could help to increase (a) the number of disabled academics, (b) the number of disabled students who perform research in the community after graduation, (c) the degree success of disabled students and (d) the knowledge available on the social situation of disabled people.
Improving TCP Performance in Vehicle-To-Grid (V2G) Communication
Authors: Park Jinwoo , Kim Hyogon , Choi Jin-Young
Published: October 2019

On a connected car, the performance of Internet access will significantly affect the user experience. For electric cars that use vehicle-to-grid (V2G) communication to interact with the Internet during charging, the charge cable quality poses a challenge to the V2G communication. Specifically, the performance of Transmission Control Protocol (TCP), the transport protocol that most Internet applications use, may suffer due to the high noise and consequent errors that the charge cable presents. Currently, TCP NewReno is the TCP implementation that ISO 15118 standard stipulates for the V2G communication. However, its congestion control algorithm has been designed for the general Internet environment where congestion, not link errors, account for most of packet losses. Indeed, we confirm that the throughput of TCP NewReno rapidly degrades as the error rate increases on the charge cable. Specifically, we show that other TCP variants such as TCP Illinois far exceeds TCP NewReno in both lossy and non-lossy link environments. Finally, we propose how to configure TCP NewReno parameters to make it achieve the throughput comparable to other TCP variants on V2G communication environments, regardless of the link quality presented by the charging cable.
EEG-Based 3D Visual Fatigue Evaluation Using CNN
Authors: Yue Kang , Wang Danli
Published: October 2019

Visual fatigue evaluation plays an important role in applications such as virtual reality since the visual fatigue symptoms always affect the user experience seriously. Existing visual evaluation methods require hand-crafted features for classification, and conduct feature extraction and classification in a separated manner. In this paper, we conduct a designed experiment to collect electroencephalogram (EEG) signals of various visual fatigue levels, and present a multi-scale convolutional neural network (CNN) architecture named MorletInceptionNet to detect visual fatigue using EEG as input, which exploits the spatial-temporal structure of multichannel EEG signals. Our MorletInceptionNet adopts a joint space-time-frequency features extraction scheme in which Morlet wavelet-like kernels are used for time-frequency raw feature extraction and inception architecture are further used to extract multi-scale temporal features. Then, the multi-scale temporal features are concatenated and fed to the fully connected layer for visual fatigue evaluation using classification. In experiment evaluation, we compare our method with five state-of-the-art methods, and the results demonstrate that our model achieve overally the best performance better performance for two widely used evaluation metrics, i.e., classification accuracy and kappa value. Furthermore, we use input-perturbation network-prediction correlation maps to conduct in-depth analysis into the reason why the proposed method outperforms other methods. The results suggest that our model is sensitive to the perturbation of β (14–30 Hz) and γ (30–40 Hz) bands. Furthermore, their spatial patterns are of high correlation with that of the corresponding power spectral densities which are used as evaluation features traditionally. This finding provides evidence of the hypothesis that the proposed model can learn the joint time-frequency-space features to distinguish fatigue levels automatically.
A Novel Chaotic System with Two Circles of Equilibrium Points: Multistability, Electronic Circuit and FPGA Realization
Authors: Sambas Aceng , Vaidyanathan Sundarapandian , Tlelo-Cuautle Esteban , Zhang Sen , Guillen-Fernandez Omar , Sukono  , Hidayat Yuyun , Gundara Gugun
Published: October 2019

This paper introduces a new chaotic system with two circles of equilibrium points. The dynamical properties of the proposed dynamical system are investigated through evaluating Lyapunov exponents, bifurcation diagram and multistability. The qualitative study shows that the new system exhibits coexisting periodic and chaotic attractors for different values of parameters. The new chaotic system is implemented in both analog and digital electronics. In the former case, we introduce the analog circuit of the proposed chaotic system with two circles of equilibrium points using amplifiers, which is simulated in MultiSIM software, version 13.0 and the results of which are in good agreement with the numerical simulations using MATLAB. In addition, we perform the digital implementation of the new chaotic system using field-programmable gate arrays (FPGA), the experimental observations of the attractors of which confirm its suitability to generate chaotic behavior.
Comparison of Nonlinear Wave-Loading Models on Rigid Cylinders in Regular Waves
Authors: Mockutė Agota , Marino Enzo , Lugni Claudio , Borri Claudio
Published: October 2019

Monopiles able to support very large offshore wind turbines are slender structures susceptible to nonlinear resonant phenomena. With the aim to better understand and model the wave-loading on these structures in very steep waves where ringing occurs and the numerical wave-loading models tend to lose validity, this study investigates the distinct influences of nonlinearities in the wave kinematics and in the hydrodynamic loading models. Six wave kinematics from linear to fully nonlinear are modelled in combination with four hydrodynamic loading models from three theories, assessing the effects of both types of nonlinearities and the wave conditions where each type has stronger influence. The main findings include that the nonlinearities in the wave kinematics have stronger influence in the intermediate water depth, while the choice of the hydrodynamic loading model has larger influence in deep water. Moreover, finite-depth FNV theory captures the loading in the widest range of wave and cylinder conditions. The areas of worst prediction by the numerical models were found to be the largest steepness and wave numbers for second harmonic, as well as the vicinity of the wave-breaking limit, especially for the third harmonic. The main cause is the non-monotonic growth of the experimental loading with increasing steepness due to flow separation, which leads to increasing numerical overpredictions since the numerical wave-loading models increase monotonically.
A Hybrid Predictive Control for a Current Source Converter in an Aircraft DC Microgrid
Authors: Yang Hui , Tu Rui , Wang Ke , Lei Jiaxing , Wang Wenjia , Feng Shuang , Wei Chaofan
Published: October 2019

A current source converter (CSC) is a promising topology for interfacing aircraft generators with the onboard DC microgrid. In this paper, a hybrid predictive control is proposed for the CSC with an output LC filter in such application. Deadbeat predictive control with larger sampling time is applied to the output circuit, generating reference source currents. Finite-set model predictive control with smaller sampling time is applied to the input circuit to achieve sinusoidal source currents, which is simplified by saving the source current predictions. The proposed scheme eliminates both the proportional-integral controller and the weighting factor, which are required in the existing studies. Besides, it has lower control complexity. A SiC-MOSFET-based prototype is used to verify the validity of the proposed scheme. Experimental results under 150 V/350–800 Hz AC input and 270 V DC output demonstrate the superior control performance.
Preliminary Assessment of a Biogas-Based Power Plant from Organic Waste in the North Netherlands
Authors: Achinas Spyridon , Martherus Demi , Krooneman Janneke , Euverink Gerrit Jan Willem
Published: October 2019

Biogas is expected to play a crucial role in achieving the energy targets set by the European Union. Biogas, which mainly comprises methane and carbon dioxide, is produced in an anaerobic reactor, which transforms biomass into biogas. A consortium of anaerobic bacteria and archaea produces biogas during the anaerobic digestion (AD) of various types of feedstocks, such as animal slurries, energy crops, and agricultural residues. A biogas-fed gas turbine-generator and steam generator produce heat and power. In this study, a combined heat and power installation is studied. The biogas-based power plant treating cow manure, grass straw, and sugar beet pulp was examined using the software SuperPro Designer, and the obtained economic reports are evaluated. From the results, subsidy for electricity does not change the feasibility of the plants in case that cow manure or sugar beet pulp are used as feedstocks. The net present value (NPV) of biogas plants treating cow manure and sugar beet pulp was negative and the subsidy is not sufficient to make profitable these cases. The biogas power plant treating straw showed a positive net present value even without subsidy, which means that it is more desirable to invest in a plant that produces electricity and digestate from grass straw.
Stacked Auto-Encoder Modeling of an Ultra-Supercritical Boiler-Turbine System
Authors: Zhang Hao , Liu Xiangjie , Kong Xiaobing , Lee Kwang Y.
Published: October 2019

The ultra-supercritical (USC) coal-fired boiler-turbine unit has been widely used in modern power plants due to its high efficiency and low emissions. Since it is a typical multivariable system with large inertia, severe nonlinearity, and strong coupling, building an accurate model of the system using traditional identification methods are almost impossible. In this paper, a deep neural network framework using stacked auto-encoders (SAEs) is presented as an effective way to model the USC unit. In the training process of SAE, maximum correntropy is chosen as the loss function, since it can effectively alleviate the influence of the outliers existing in USC unit data. The SAE model is trained and validated using the real-time measurement data generated in the USC unit, and then compared with the traditional multilayer perceptron network. The results show that SAE has superiority both in forecasting the dynamic behavior as well as eliminating the influence of outliers. Therefore, it can be applicable for the simulation analysis of a 1000 MW USC unit.
State-Of-Charge Estimation for Lithium-Ion Battery Using Improved DUKF Based on State-Parameter Separation
Authors: Yu Chuan-Xiang , Xie Yan-Min , Sang Zhao-Yu , Yang Shi-Ya , Huang Rui
Published: October 2019

State-of-charge estimation and on-line model modification of lithium-ion batteries are more urgently required because of the great impact of the model accuracy on the algorithm performance. This study aims to propose an improved DUKF based on the state-parameter separation. Its characteristics include: (1) State-Of-Charge (SoC) is treated as the only state variable to eliminate the strong correlation between state and parameters. (2) Two filters are ranked to run the parameter modification only when the state estimation has converged. First, the double polarization (DP) model of battery is established, and the parameters of the model are identified at both the pulse discharge and long discharge recovery under Hybrid Pulse Power Characterization (HPPC) test. Second, the implementation of the proposed algorithm is described. Third, combined with the identification results, the study elaborates that it is unreliable to use the predicted voltage error of closed-loop algorithm as the criterion to measure the accuracy of the model, while the output voltage obtained by the open-loop model with dynamic parameters can reflect the real situation. Finally, comparative experiments are designed under HPPC and DST conditions. Results show that the proposed state-parameter separated IAUKF-UKF has higher SoC estimation accuracy and better stability than traditional DUKF.
An Output-Based Limit Protection Strategy for Turbofan Engine Propulsion Control with Output Constraints
Authors: Qin Jiakun , Pan Muxuan , Xu Wenhao , Huang Jinquan
Published: October 2019

To accomplish the limit protection task, the Min-Max selection structure is generally adopted in current aircraft engine control strategies. However, since no relationship between controller switching and limit violation is established, this structure is inherently conservative and may produce slower transient responses than the behavior by engine nature. This paper proposes an output-based limit management strategy, which consists of the safety margin module and the parameter prediction module to monitor system responses, plus the switching logic to govern switches between the main controller and limiters, and, in this way, a faster transient performance is achieved, and the limit protections in transient states become more effective. To realize smooth switching control, the linear-quadratic bumpless transfer method is developed. The design principle of the multi-loop switching control and bumpless compensator is detailed, and the effect—on limit protection control performance—of the design parameters in the safety margin and parameter prediction modules are also analyzed. The proposed approach is tested using simulations covering the whole flight envelope on the nonlinear component-level model of a turbofan engine, and the superiority over the Min-Max architecture is also validated.
Energy Efficient Cooperative Computation Algorithm in Energy Harvesting Internet of Things
Authors: Ko Haneul , Lee Jaewook , Jang Seokwon , Kim Joonwoo , Pack Sangheon
Published: October 2019

The limited battery capacity of Internet of Things (IoT) devices is a major deployment barrier for IoT-based computing systems. In this paper, we propose an energy efficient cooperative computation algorithm (EE-CCA). In an EE-CCA, a pair of IoT devices decide whether to offload some parts of the task to the opponent by considering their energy levels and the task deadline. To minimize the energy outage probability while completing most of tasks before their deadlines, we formulate a constraint Markov decision process (CMDP) problem and the optimal offloading strategy is obtained by linear programming (LP). Meanwhile, an optimization problem of finding pairs of IoT devices (i.e., IoT device pairing problem) is formulated under the optimal offloading strategy. Evaluation results demonstrate that the EE-CCA can reduce the energy outage probability up to 78 % compared with the random offloading scheme while completing tasks before their deadlines with high probability.
Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids
Authors: Buire Jérôme , Colas Frédéric , Dieulot Jean-Yves , Guillaud Xavier
Published: October 2019

This paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.
Optimum Band Gap Energy of ((Ag),Cu)(InGa)Se2 Materials for Combination with NiMo–NiO Catalysts for Thermally Integrated Solar-Driven Water Splitting Applications
Authors: Bayrak Pehlivan İlknur , Edoff Marika , Stolt Lars , Edvinsson Tomas
Published: October 2019

Solar-driven water splitting is considered one of the promising future routes to generate fuel in a sustainable way. A carbon-free solar fuel, molecular hydrogen, can here be produced along two different but intimately related routes, photoelectrochemical (PEC) water splitting or photovoltaic electrolysis (PV-electrolysis), where the latter builds on well-established solar cell and electrolysis materials with high efficiency. The PV-electrolysis approach is also possible to construct from an integrated PEC/PV-system avoiding dc–dc converters and enabling heat exchange between the PV and electrolyzer part, to a conventionally wired PV-electrolysis system. In either case, the operating voltage at a certain current needs to be matched with the catalyst system in the electrolysis part. Here, we investigate ((Ag),Cu)(In,Ga)Se2 ((A)CIGS)-materials with varying Ga-content modules for combination with NiMo–NiO catalysts in alkaline water splitting. The use of (A)CIGS is attractive because of the low cost-to-performance ratio and the possibility to optimize the performance of the system by tuning the band gap of (A)CIGS in contrast to Si technology. The band gap tuning is possible by changing the Ga/(Ga + In) ratio. Optoelectronic properties of the (A)CIGS materials with Ga/(Ga + In) ratios between 0.23 and 0.47 and the voltage and power output from the resulting water splitting modules are reported. Electrolysis is quantified at temperatures between 25 and 60 °C, an interval obtainable by varying the thermal heat exchange form a 1-sun illuminated PV module and an electrolyte system. The band gaps of the (A)CIGS thin films were between 1.08 to 1.25 eV and the three-cell module power conversion efficiencies (PCE) ranged from 16.44% with 1.08 eV band gap and 19.04% with 1.17 eV band gap. The highest solar-to-hydrogen (STH) efficiency was 13.33% for the (A)CIGS–NiMo–NiO system with 17.97% module efficiency and electrolysis at 60 °C compared to a STH efficiency of 12.98% at 25 °C. The increase in STH efficiency with increasing temperature was more notable for lower band gaps as these are closer to the overpotential threshold for performing efficient solar-driven catalysis, while only a modest improvement can be obtained by utilizing thermal exchange for a band gap matched PV-catalysts system. The results show that usage of cost-effective and stable thin film PV materials and earth abundant catalysts can provide STH efficiencies beyond 13% even with PV modules with modest efficiency.
Enhanced Current Reference Calculation to Avoid Harmonic Active Power Oscillations
Authors: Serrano Javier , Moriano Javier , Rizo Mario , Dongil Francisco
Published: October 2019

Energy storage systems play a key role in the rise of distributed power generation systems, hence there is great interest in extending their lifetimes, which are directly related to DC current ripple. One of the ripple sources is the low-frequency active power fluctuations under unbalanced and distorted grid voltage conditions. Therefore, this paper addresses a multifrequency control strategy where the harmonic reference currents are calculated to reduce harmonic active power oscillations. The stationary reference frame (StRF) approach taken here improves the precision and computational time of the current reference calculation method. Additionally, in order to ensure safe converter operation when a multifrequency reference current is provided, a computational efficient peak current saturator is applied while avoiding signal distortion every time step. If the injected current harmonic distortion is to be minimized, which is a feature included in this work, the peak current saturator is a necessary requirement. Active power ripple is reduced even with frequency variations in the grid voltage using a well-known frequency-adaptive scheme. The simulation and experimental results prove the optimized performance for the control objective: power ripple reduction with minimum current harmonic distortion.
An Improved UDE-Based Flux-Weakening Control Strategy for IPMSM
Authors: Gu Xin , Li Tao , Li Xinmin , Zhang Guozheng , Wang Zhiqiang
Published: October 2019

Interior permanent magnet synchronous motors (IPMSMs) are usually used in electric vehicle drives and in other applications. In order to enlarge the speed range of IPMSMs, the flux-weakening control method is adopted. The traditional flux-weakening control strategy degrades the control performance because of parameter mismatches caused by variation of motor parameters. An improved uncertainty and disturbance estimator (UDE)-based flux-weakening control strategy is proposed for IPMSM drives in this paper. The parameter tuning method in the UDE-based control is improved. In addition, a flux-weakening adjusting factor is put forward to reduce the torque fluctuation when the operation point switches between the constant torque region and the flux-weakening region. This factor can be adjusted online by a lookup table. Finally, the validity of proposed method is verified by the simulation and experimental results. The results show that the proposed control strategy can effectively enhance the robustness of the system in the flux-weakening region, and make the system switch more smoothly between the constant torque region and the flux-weakening region.
Different Processing Practices and the Frying Life of Refined Canola Oil
Authors: Adjonu Randy , Zhou Zhongkai , Prenzler Paul D. , Ayton Jamie , Blanchard Christopher L.
Published: October 2019

Refined expeller-pressed (RCanO-I and RCanO-II) and expeller-pressed and solvent-extracted blended (RCanO-III and RCanO-IV) canola oils were compared to determine the effect of processing (extraction) practice on the frying life of canola oil. Samples were from the 2016/2017 and 2017/2018 production seasons and were used to fry potato chips for 36 to 48 cycles. Frying life was assessed by the total polar compounds, retention of tocopherols, antioxidant activity, and other quality indices. RCanO-II exhibited significantly, the longest frying life as compared with the other three oils and this correlated with tocopherol retention and antioxidant activity (p < 0.05). The extraction practice influenced the frying life of canola oil, but this was dependent on other processing practices employed by the individual processors. Variations in initial oil quality dictated the rates of chemical reactions occurring in the oils during frying and influenced oil stability.
Fossilized Endolithic Microorganisms in Pillow Lavas from the Troodos Ophiolite, Cyprus
Authors: Carlsson Diana-Thean , Ivarsson Magnus , Neubeck Anna
Published: October 2019

The last decade has revealed the igneous oceanic crust to host a more abundant and diverse biota than previously expected. These underexplored rock-hosted deep ecosystems dominated Earth’s biosphere prior to plants colonized land in the Ordovician, thus the fossil record of deep endoliths holds invaluable clues to early life and the work to decrypt them needs to be intensified. Here, we present fossilized microorganisms found in open and sealed pore spaces in pillow lavas from the Troodos Ophiolite (91 Ma) on Cyprus. A fungal interpretation is inferred upon the microorganisms based on characteristic morphological features. Geochemical conditions are reconstructed using data from mineralogy, fluid inclusions and the fossils themselves. Mineralogy indicates at least three hydrothermal events and a continuous increase of temperature and pH. Precipitation of 1) celadonite and saponite together with the microbial introduction was followed by 2) Na and Ca zeolites resulting in clay adherence on the microorganisms as protection, and finally 3) Ca carbonates resulted in final fossilization and preservation of the organisms in-situ. Deciphering the fossil record of the deep subseafloor biosphere is a challenging task, but when successful, can unlock doors to life’s cryptic past.
“Always Trembling on the Brink of Poetry”: Katherine Mansfield, Poet
Authors: Kimber Gerri
Published: October 2019

Today, Katherine Mansfield is well known as one of the most exciting and cutting-edge exponents of the modernist short story. Little critical attention, however, has been paid to her poetry, which seems a strange omission, given how much verse she wrote during the course of her life, starting as a very young schoolgirl, right up until the last months prior to her death in 1923. Even Mansfield devotees are not really familiar with any poems beyond the five or six that have most frequently been anthologised since her death, and few editions of her poetry have ever been published. Mansfield’s husband, John Middleton Murry, edited a slim volume, Poems, in 1923, within a few months of her death, followed by a slightly extended edition in 1930, and Vincent O’Sullivan edited another small selection, also titled Poems, in 1988. Unsurprisingly, therefore, critics and biographers have paid little attention to her poetry, tending to imply that it is a minor feature of her art, both in quantity and, more damagingly, in quality. This situation was addressed in 2016, when EUP published a complete and fully annotated edition of Mansfield’s poems, edited by myself and Claire Davison, incorporating all my recent manuscript discoveries, including a collection of 36 poems—The Earth Child—sent unsuccessfully by Mansfield to a London publisher in 1910. This discovery in 2015 revealed how, at the very moment when Mansfield was starting to have stories accepted for commercial publication, she was also taking herself seriously as a poet. Indeed, had the collection been published, perhaps Mansfield might now be celebrated as much for her poetry as for her short stories. Therefore, this article explores the development of Mansfield’s poetic writing throughout her life and makes the case for her reassessment as an innovative poet and not just as a ground-breaking short story writer.
Response to Jewell, Evan. (Re)moving the Masses: Colonisation as Domestic Displacement in the Roman Republic. Humanities 2019, 8, 66
Authors: Gatrell Peter
Published: October 2019

This response engages with Evan Jewell’s article on ‘Colonisation as Domestic Displacement in the Roman Republic’. It supports his argument about the relationship between the conduct of politics in the ancient world and the use of aquatic metaphors to target specific groups for displacement, adding that similar relationships unfolded in more recent times. His emphasis on ‘domestic displacement’ also resonates with twentieth-century projects that displaced people in large numbers in pursuit of what has come to be called ‘development’.
Climate-Driven Adaptation, Household Capital, and Nutritional Outcomes among Farmers in Eswatini
Authors: Bailey Karen M. , McCleery Robert A. , Barnes Grenville , McKune Sarah L.
Published: October 2019

Globally, communities are increasingly impacted by the stressors of climate change. In response, people may adapt to maintain their livelihoods and overall health and nutrition. However, the relationship between climate adaptation and human nutrition is poorly understood and results of adaptation are often unclear. We investigated the relationship between adaptation and child nutrition, in Eswatini (formerly Swaziland) during an extreme drought. Households varied in both adaptation behavior and household resources and we found that, overall, households that adapted had better child nutrition than those that didn’t adapt. When controlling for the influence of household capital, we found that more vulnerable households, those with greater dependence on natural resources and lower income, had a stronger positive relationship between adaptation and nutrition than less vulnerable households. We also found that some adaptations had stronger positive relationships with nutrition than others. In our system, the adaptation that most strongly correlated with improved nutrition, selling chickens, most likely benefits from local social networksand consistent demand, and performed better than other adaptations. Our results emphasize the need to measure adaptation outcomes and identify and support the types of adaptations are most likely to improve nutrition in the future.
Cardiac Vagal Control, Regulatory Processes and Depressive Symptoms: Re-Investigating the Moderating Role of Sleep Quality
Authors: Danböck Sarah K. , Werner Gabriela G.
Published: October 2019

Lower cardiac vagal control (CVC), which is often understood as an indicator for impaired regulatory processes, is assumed to predict the development of depressive symptoms. As this link has not been consistently demonstrated, sleep quality has been proposed as a moderating factor. However, previous studies were limited by non-representative samples, cross-sectional data, and focused on CVC as a physiological indicator for impaired regulatory processes, but neglected corresponding subjective measures. Therefore, we investigated whether sleep quality moderates the effects of CVC (quantified by high-frequency heart rate variability) and self-reported regulatory processes (self- and emotion-regulation) on concurrent depressive symptoms and on depressive symptoms after three months in a representative sample (N = 125). Significant interactions between CVC and sleep quality (in women only), as well as self-/emotion-regulation and sleep quality emerged, whereby higher sleep quality attenuated the relation between all risk factors and current depressive symptoms (cross-sectional data). However, there were no significant interactions between those variables in predicting depressive symptoms three months later (longitudinal data). Our cross-sectional findings extend previous findings on sleep quality as a protective factor against depressive symptoms in the presence of lower CVC and subjective indices of impaired regulatory processes. In contrast, our conflicting longitudinal results stress the need for further investigations.
Hypertension Diagnosis Index for Discrimination of High-Risk Hypertension ECG Signals Using Optimal Orthogonal Wavelet Filter Bank
Authors: Rajput Jaypal Singh , Sharma Manish , Acharya U. Rajendra
Published: October 2019

Hypertension (HT) is an extreme increment in blood pressure that can prompt a stroke, kidney disease, and heart attack. HT does not show any symptoms at the early stage, but can lead to various cardiovascular diseases. Hence, it is essential to identify it at the beginning stages. It is tedious to analyze electrocardiogram (ECG) signals visually due to their low amplitude and small bandwidth. Hence, to avoid possible human errors in the diagnosis of HT patients, an automated ECG-based system is developed. This paper proposes the computerized segregation of low-risk hypertension (LRHT) and high-risk hypertension (HRHT) using ECG signals with an optimal orthogonal wavelet filter bank (OWFB) system. The HRHT class is comprised of patients with myocardial infarction, stroke, and syncope ECG signals. The ECG-data are acquired from physionet’s smart health for accessing risk via ECG event (SHAREE) database, which contains recordings of a total 139 subjects. First, ECG signals are segmented into epochs of 5 min. The segmented epochs are then decomposed into six wavelet sub-bands (WSBs) using OWFB. We extract the signal fractional dimension (SFD) and log-energy (LOGE) features from all six WSBs. Using Student’s t-test ranking, we choose the high ranked WSBs of LOGE and SFD features. We develop a novel hypertension diagnosis index (HDI) using two features (SFD and LOGE) to discriminate LRHT and HRHT classes using a single numeric value. The performance of our developed system is found to be encouraging, and we believe that it can be employed in intensive care units to monitor the abrupt rise in blood pressure while screening the ECG signals, provided this is tested with an extensive independent database.
Emotional Intelligence Profiles of University Students with Motor Disabilities: Differential Analysis of Self-Concept Dimensions
Authors: Suriá-Martínez Raquel , Ortigosa Quiles Juan Manuel , Riquelme Marin Antonio
Published: October 2019

Background: This study compares the self-concept of students that have motor disabilities with that of students in the normative group. It also considers whether there are EI (emotional intelligence) profiles based on combinations of EI components (attention, clarity, and mood repair). Finally, it analyzes whether there are statistically significant differences in self-concept based on the EI profiles found. Method: 102 university students with motor disabilities participated. The age range was 19–33 (M = 20.22, SD = 4.36). The Escala de Autoconcepto Forma 5 (Self-Concept Scale Form 5, AF5) and the Trait Meta-Mood Scale-24 (TMMS-24) were administered. Results: The scores for self-concept were lower in the sample of students with reduced mobility. The cluster analysis also identified three different EI profiles: one group of young people with high general EI scores, one group with high scores for clarity and mood repair, and a last group of students with low EI scores. Finally, the ANOVA showed better self-concept in the group with high scores in the three EI dimensions. The results suggest that better self-concept is associated with a high EI profile. Conclusions: It would be interesting to provide programs that consider EI in more depth to strengthen these students’ self-concept.
Stable H-O Isotopic Composition and Water Quality Assessment of Surface Water and Groundwater: A Case Study in the Dabie Mountains, Central China
Authors: Yang Kunhua , Han Guilin , Song Chao , Zhang Peng
Published: October 2019

In order to understand the water cycle and assess the water quality for irrigation purposes in the Upper Pi River Basin (UPRB), which is the northern slope of the Dabie Mountains, 68 surface water and groundwater samples were collected and analyzed for H-O isotopes and hydrochemistry during the high-flow season in 2017 and 2018. The results show that ranges of hydrogen and oxygen isotopic composition (δ2H: −68.8‰ to −40.8‰, δ18O: −10.05‰ to −5.05‰) are controlled by the medium latitude and high altitude of the UPRB. Among different types of water, the δ2H and δ18O values can be ordered as follows: reservoir water < spring water ≈ river water < pond water. The water of the upstream medium and small reservoir is enriched with lighter isotopes that is likely related to more exchange with rainwater and less residence time; however, large reservoirs are similar to the upstream river and spring in terms of the H-O isotopic composition. Hydro-chemical facies are dominated by the Ca-HCO3 type in the UPRB, which reflects fresh recharged water from rainfall, and few samples are of the Ca-Cl type that is caused by intensive evaporation. The water quality for irrigation purposes was also evaluated. According to the Wilcox diagram, United States Salinity Laboratory (USSL) diagram, magnesium hazard, and Kelly’s ratio, all water samples have been considered suitable for irrigation water.
The Association of Serum TNF-α Levels and Blood Multi-Elements Modified by TNF-α Gene Polymorphisms in Metal Industrial Workers
Authors: Chen Tzu-Hua , Huang Joh-Jong , Kung Wei-Shyang , Lee Su-Shin , Sun Hung-Yu , Chuang Hung-Yi
Published: October 2019

Health of the metal industrial workers should be a noteworthy issue due to the hazard of chronic exposure to metals or toxic elements. The interactions among multiple elements are sophisticated and may differ from person to person. Tumor necrosis factor-α (TNF-α) gene polymorphisms were supposed to be involved with the interactions because TNF-α plays an important role in inflammation, a mechanism by which toxic elements cause threats to human health. This research aimed to analyze the influence of TNF-α gene polymorphisms and multi-elements on serum TNF-α level. Blood multi-elements concentrations (lead, cadmium, arsenic, selenium, cobalt, copper, and zinc), serum TNF-α level, and TNF-α single nucleotide polymorphisms (SNPs), including −238G > A (rs361525), −308G > A (rs1800629), −857C > T (rs1799724), −863C > A (rs1800630), and −1031T > C (rs1799964), were measured in 462 metal industrial workers. We applied mixed-effect models to analyze the interactions among multi-elements and TNF-α SNPs. Blood concentration of all elements were positively associated with serum TNF-α level, and the effects may be modified by TNF-α gene polymorphisms. Our study revealed that TNF-α −308A/A and −1031C/C may be susceptible genotypes, and thus we suggest that those workers should take preventive measures against metal toxicity.