bluuebunny/crossref_metadata_2025 huggingface dataset:
Progressive cranial neuropathy and uterine involvement in myeloid sarcoma
Authors: Khoo Anthony , Kimber Thomas , Cohen Penelope , Ghaoui Roula
Published: June 2020

A rare extramedullary manifestation of haematological malignancy, myeloid sarcoma is most commonly seen in patients with acute myeloid leukaemia. We report on an adult patient who presented with an atypical phenotype of progressive cranial neuropathy without blood or bone marrow involvement, and in whom obtaining material for pathological diagnosis was made challenging by unusual findings of absent fluorodeoxyglucose-positron emission tomography avidity and involvement of sites not readily accessible to biopsy (orbital apex and cauda equina). The eventual diagnosis was obtained through biopsy of the uterine cervix before being verified on repeat lymph node and cerebrospinal fluid sampling prior to initiation of chemotherapy.
Variations in the patterns of prevalence and therapy in Australasian Parkinson’s disease patients of different ethnicities
Authors: Alamri Yassar , Pitcher Toni , Anderson Tim J
Published: June 2020

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly after Alzheimer’s disease. It is expected that PD cumulative incidence will increase in the future, as there are far more people surviving into late age than there ever used to be. While most commonly idiopathic, rare forms of PD can be familial/genetic. In addition, socioeconomic, cultural and genetic factors may influence the way in which anti-parkinsonian medications are prescribed, and how patients respond to them. This review aims to highlight the potential impact of genetic variation on the epidemiology and therapeutics of PD, focusing on data from New Zealand and Australia.
Mapping soil nail loads using Federal Highway Administration (FHWA) simplified models and artificial neural network technique
Authors: Lin Peiyuan , Ni Pengpeng , Guo Chengchao , Mei Guoxiong
Published: June 2020

This study compiles a broad database containing 312 measured maximum soil nail loads under operational conditions. The database is used to re-assess the prediction accuracies of the default Federal Highway Administration (FHWA) nail load model and its modified version previously reported in the literature. Predictions using the default and modified FHWA models are found to be highly dispersive. Moreover, the prediction accuracy is statistically dependent on the magnitudes of the predicted nail load and several model input parameters. The modified FHWA model is then recalibrated by introducing extra empirical terms to account for the influences of wall geometry, nail design configuration, and soil shear strength parameters on the evolvement of nail loads. The recalibrated FHWA model is demonstrated to have much better prediction accuracy compared to the default and modified models. Next, an artificial neural network (ANN) model is developed for mapping soil nail loads, which is shown to be the most advantageous one as it is accurate on average and the dispersion in prediction is low. The abovementioned dependency issue is also not present in the ANN model. The practical value of the ANN model is highlighted by applying it to reliability-based designs of soil nails against internal limit states.
Baffin Bay late Neogene palynostratigraphy at Ocean Drilling Program Site 645
Authors: Aubry Aurélie M.R. , de Vernal Anne , Knutz Paul C.
Published: June 2020

Analyses of marine and terrestrial palynomorphs of Ocean Drilling Program (ODP) Site 645 in Baffin Bay led us to define a new biostratigraphical scheme covering the late Miocene to Pleistocene based on dinocyst and acritarch assemblages. Four biozones were defined. The first one, from 438.6 m below sea floor (mbsf) to 388 mbsf, can be assigned a late Miocene to early Pliocene age (>4.5 Ma), based on the common occurrence of Cristadinium diminutivum and Selenopemphix brevispinosa. Biozone 2, spanning from an erosional unconformity to a recovery hiatus, is marked by the highest occurrences (HOs) of Veriplicidium franklinii and Cristadinium diminutivum, which suggest an early Pliocene age >3.6 Ma (∼4.5 to ∼3.6 Ma). Biozone 3, above the recovery hiatus and up to 220.94 mbsf, corresponds to a late Pliocene or early Pleistocene age based on occurrences of Bitectatodinium readwaldii, Cymatiosphaera? icenorum, and Lavradosphaera canalis. Finally, between 266.4 and 120.56 mbsf, Biozone 4, marked by the HO of Filisphaera filifera, Filisphaera microornata, and Habibacysta tectata, has an early Pleistocene age (>1.4 Ma). Our biostratigraphy implies that horizon b1 of the Baffin Bay seismic stratigraphy corresponds to the recovery hiatus at ODP Site 645, which suggests a very thick Pliocene sequence along the Baffin Island slope. Dinocyst assemblages and terrestrial palynomorphs in our records indicate that the late Miocene and (or) early Pliocene were characterized by relatively warm coastal surface waters and boreal forest or forested tundra vegetation over adjacent lands. In contrast, the early Pleistocene dinocyst assemblages above the recovery hiatus indicate cold surface waters, while pollen data suggest reduced vegetation cover on adjacent lands.
A quantum interpretation of the physical basis of mass–energy equivalence
Authors: Chang Donald C.
Published: June 2020

We know energy and mass of a particle can be connected by [Formula: see text]. What is the physical basis of this relation? Historically, it was thought to be based on the principle of relativity (PR). A careful examination of the literature, however, indicated that this understanding is not true. Einstein did not derive this relation from PR. Instead, his argument was mainly based on thought experiments, which focused on the similarity between radiation and matter. Following this hint, we suspect that the mass–energy equivalence could be based on the quantum property of wave–particle duality. We know photon and electron can behave as a particle as well as a wave. Such a wave property could make the particle behave differently from Newtonian mechanics. Indeed, using a wave model which treats particles as excitations of the vacuum, we show that the mass–energy equivalence relation can be directly derived based on the quantum relations of Planck and de Broglie. This wave hypothesis has several advantages; not only can it explain naturally why particles can be created in the vacuum; it also predicts that a particle cannot travel faster than the speed of light. This hypothesis can also be tested in experiment.
A Passed Test Case Cluster Method to Improve Fault Localization
Authors: Wang Weibo , Wu Yonghao , Liu Yong
Published: June 2020

Coverage-Based Fault Localization (CBFL) techniques are based on the conjecture that the program elements executed by more failed test cases and less passed test cases have more chance to be faulty. Coincidental Correct (CC) test case is one of the negative impacts on CBFL, for the reason that the CC test cases execute the faulty element but not propagate the faulty status to the final output. To alleviate the negative impact of CC test cases, in this paper, we propose a cluster-based technique to identify CC test cases from the passed test suite. To evaluate the effectiveness of our method, we conduct empirical studies on 102 versions from six programs. The experimental results show that, when using our method, it can accurately recognize CC test cases, where the precision and recall rate are both higher than 85%. A further study shows that, after removing identified CC test cases, the fault localization accuracy of SBFL can be improved apparently.
Automation of Bandwidth Re-design and its Applications in Amplifier Tuned Oscillators Based on Nullors
Authors: Krishnan R. Rohith , Krishnakumar S.
Published: June 2020

In this paper, the method for the design automation of a narrow band-pass amplifier, and hence the amplifier tuned oscillator is discussed. A fixator approach is utilized in this method to design the narrow band-pass amplifiers and a reference circuit is required for this process. The fixator–norator pair helps to generate an extra sub-circuit, generally the feedback network; the addition of this sub-circuit in the actual amplifier circuit will modify the frequency response of the amplifier. The amplifier now behaves like an active narrow band-pass filter, which exactly follows the frequency response of the model circuit. This can be turned into an oscillator by providing positive feedback. Such a circuit possesses independent frequency and amplitude control. Hence, the re-designed circuit can be employed as an active filter or an oscillator at the selected center frequency. In addition to the technical merits, the proposed method has pedagogical importance. Few case studies are worked out in this paper to demonstrate the method.
Deep Learning Based Sentiment Analysis in a Code-Mixed English-Hindi and English-Bengali Social Media Corpus
Authors: Jamatia Anupam , Swamy Steve Durairaj , Gambäck Björn , Das Amitava , Debbarma Swapan
Published: June 2020

Sentiment analysis is a circumstantial analysis of text, identifying the social sentiment to better understand the source material. The article addresses sentiment analysis of an English-Hindi and English-Bengali code-mixed textual corpus collected from social media. Code-mixing is an amalgamation of multiple languages, which previously mainly was associated with spoken language. However, social media users also deploy it to communicate in ways that tend to be somewhat casual. The coarse nature of social media text poses challenges for many language processing applications. Here, the focus is on the low predictive nature of traditional machine learners when compared to Deep Learning counterparts, including the contextual language representation model BERT (Bidirectional Encoder Representations from Transformers), on the task of extracting user sentiment from code-mixed texts. Three deep learners (a BiLSTM CNN, a Double BiLSTM and an Attention-based model) attained accuracy 20–60% greater than traditional approaches on code-mixed data, and were for comparison also tested on monolingual English data.
Model Selection Methods for Reliability Assessment Based on Interval-Censored Field Failure Samples
Authors: Tsai Tzong-Ru , Wu Sih-Hua , Shen Yan
Published: June 2020

Incomplete field failure data from automated production are often applied for evaluating the system reliability. But the evaluation could be impacted by the uncertainty of the product’s lifetime distribution, which is usually predetermined but may be misspecified. In this paper, we assume that the system lifetime distribution follows a location-scale family with several candidates instead of a certain distribution. Two model selection procedures are proposed to assign the most likely candidate distribution from a pool of the location-scale distributions based on interval-censored field failure samples. The maximum likelihood estimates (MLE) of parameters of the candidate distribution are estimated by using the Newton–Raphson method and the MLE of a quartile is assigned as the reliability measure for assessing the reliability of systems. To illustrate the applications of the proposed model selection procedures, an example of high-speed motor with interval-censored field failure data is given. Monte Carlo simulations are carried out to evaluate the performance of the proposed model selection procedures. Simulation results show that the proposed methods are efficient for model identification and can provide reliable reliability assessment.
Lifting modules with finite internal exchange property and direct sums of hollow modules
Authors: Kuratomi Yosuke
Published: June 2020

A module [Formula: see text] is said to be lifting if, for any submodule [Formula: see text] of [Formula: see text], there exists a decomposition [Formula: see text] such that [Formula: see text] and [Formula: see text] is a small submodule of [Formula: see text]. A lifting module is defined as a dual concept of the extending module. A module [Formula: see text] is said to have the finite internal exchange property if, for any direct summand [Formula: see text] of [Formula: see text] and any finite direct sum decomposition [Formula: see text], there exists a direct summand [Formula: see text] of [Formula: see text] [Formula: see text] such that [Formula: see text].

This paper is concerned with the following two fundamental unsolved problems of lifting modules: “Classify those rings all of whose lifting modules have the finite internal exchange property” and “When is a direct sum of indecomposable lifting modules lifting?”. In this paper, we prove that any [Formula: see text]-square-free lifting module over a right perfect ring satisfies the finite internal exchange property. In addition, we give some necessary and sufficient conditions for a direct sum of hollow modules over a right perfect ring to be lifting with the finite internal exchange property.
Robust recovery of signals with partially known support information using weighted BPDN
Authors: Wang Wendong , Wang Jianjun
Published: June 2020

In this paper, some theoretical results are established for the weighted Basis Pursuit De-Noising (BPDN) to guarantee the robust signal recovery when partial support information of the signals is known in advance. To be specific, equipped with two popular and powerful restricted isometry property and coherence tools, we obtain two kinds of deterministic performance guarantees of this weighted BPDN, including some recovery conditions and their resultant error estimates. These results demonstrate that if half of the support information at least is assumed to be accurate, then the weighted BPDN will perform robust under much weaker conditions than the analogous ones for the BPDN. This theoretical finding not only coincides with the ones established previously for the constrained weighted [Formula: see text]-minimization model, but also well complements the previous investigation of the weighted BPDN that is based on the asymptotic analysis. Moreover, the extensive numerical experiments are also conducted to support the assessed performance of the weighted BPDN. Finally, we also discuss the potential to apply the obtained results to deal with the robust signal recovery when the multiple support information of signals becomes available.
A Non-Matching Nodes Interface Model with Radial Interpolation Function for Simulating 2D Soil–Structure Interface Behaviors
Authors: Gong Jin , Zou Degao , Kong Xianjing , Qu Yongqian , Zhou Yang
Published: June 2020

In this paper, the meshless method is extended to simulate the interaction between soil and structure through 2D finite element (FE) model. The background mesh line shared by each surface of interface is introduced for Gauss points’ generation and interpolation. Thus, instead of a series of interface elements, the whole soil–structure interface can be presented by an arbitrary number of nodes with flexible distribution on the contacting surfaces. The radial basis function (RBF) is introduced as the interpolation function to obtain the displacement of each Gauss points by surrounding the nodes along the surfaces. The research of shape parameters and the rate of convergence are also conducted. With non-matching nodes interface, the soil and structure zone can be modeled independently and connected with the proposed non-matching nodes interface flexibly and effectively. Furthermore, the proposed method can easily enable cross-scale modeling, which has high utility for enabling refined analysis without excessively increasing the computational costs. In addition, under the standard finite element framework, nonlinear constitutive models can be employed to capture the complex behaviors at the interface. Several simulations are presented to demonstrate the high flexibility, extensive applicability and precision of the proposed non-matching nodes interface based on meshless method.
Application of the Electrostatic Micro-Speakers for Producing Audible Directional Sound
Authors: Homaei Mohammad , Fathalilou Mohammad , Shabani Rasoul , Rezazadeh Ghader
Published: June 2020

In recent years, the demand for control of sound power and radiation patterns in personal messaging, calls, automotive entertainment, and gaming has brought a new interest in the audio world. The aim of this paper is to investigate the feasibility of producing the sound waves in the audible range and directing them in the desired listening zone by electrostatic micro-speakers. Therefore, a capacitive circular micro-plate has been modeled as an electrostatic micro-speaker. Then a Bessel panel array has been developed using a number of these plates arranged in a square array. The equations governing the vibrations of the micro-speaker’s diaphragm, as well as radiation pattern of the sound waves, have been introduced and solved. The results have shown that the Micro-Electro Mechanical Systems (MEMS) electrostatic diaphragms have the capability of producing the directional sound in the human hearing range. Moreover, we have investigated the effect of different excitation frequencies, radii size and the number of the diaphragms as well as the inter-element spacing on the sound radiation pattern of the Bessel panel array.
Bacterium-Derived Carbon Dots as a Novel “Turn-On-On-Off-On” Sensor for Cr(VI) and 4-Nitrophenol Detection Based on Inner Filter Effect Mechanism
Authors: Wang Suping , Tu Yujiao , Qin Kunhao , Yuan Xiaotian , Chen Wei , Wei Yunlin , Xu Zhiwei , Zhang Qi , Ji Xiuling
Published: June 2020

Phenolic compounds, especially 4-nitrophenol (4-NP), and chromium (VI) are highly toxic environmental pollutants. Thus, it is significantly important to establish a rapid and sensitive sensor for 4-NP and Cr(VI) monitoring in environment. In this paper, a novel approach has been adopted where E. coli-derived CDs (CDs-WT) prepared by one step hydrothermal method previously and sensitized by ampicillin (turn-on) were used as fluorescence nanoprobe (CDs-WT-Amp) for 4-NP and Cr(VI) determination based on the inner filter effect quenching mechanism (turn-off). Then, the quenching fluorescence was reversed by addition of ampicillin (turn-on). The linear ranges of 4-NP and Cr(VI) detection were 0–50[Formula: see text][Formula: see text]M and 0–25[Formula: see text][Formula: see text]M, with the limits of detection 88.89[Formula: see text]nM and 64.75[Formula: see text]nM, respectively. The “turn-on-on-off-on” fluorescent nanosensor system was successfully used to determine Cr(VI) and 4-NP in water with satisfactory results. It shows that the “turn-on-off-on” nanoprobe has great promising potential for application to environmental pollutant detection.
Note on topological ternary semigroup
Authors: Samanta S. , Jana S. , Kar S.
Published: June 2020

In this paper, we have discussed various topological properties of (Hausdörff) topological ternary semigroup and topological ternary group. We have proved that the Cartesian product of an arbitrary family of topological ternary semigroups is again a topological ternary semigroup. We have investigated the existence of identity and idempotent in a topological ternary semigroup and discussed a method to topologize a ternary semigroup (group) with a compatible topology using some family of pseudometrics. Finally, we have proved that a compact topological ternary semigroup contains a ternary subgroup.
Numerical solution for singular differential equations using Haar wavelet
Authors: Shukla Shitesh , Kumar Manoj
Published: June 2020

The aim of this paper is to obtain the numerical solution of singular ordinary differential equations using the Haar-wavelet approach. The proposed method is mathematically simple and provides highly accurate solutions. In this method, we derive the Haar operational matrix using Haar function. Haar operational matrix is a basic tool and applied in system analysis to evaluate the numerical solution of differential equations. The convergence of the proposed method is discussed through its error analysis. To illustrate the efficiency of this method, solutions of four singular differential equations are obtained.
Ready, Steady, Touch!
Authors: Shi Yilei , Zhang Haimo , Zhao Kaixing , Cao Jiashuo , Sun Mengmeng , Nanayakkara Suranga
Published: June 2020

A finger held in the air exhibits microvibrations, which are reduced when it touches a static object. When a finger moves along a surface, the friction between them produces vibrations, which can not be produced with a free-moving finger in the air. With an inertial measurement unit (IMU) capturing such motion characteristics, we demonstrate the feasibility to detect contact between the finger and static objects. We call our technique ActualTouch. Studies show that a single nail-mounted IMU on the index finger provides sufficient data to train a binary touch status classifier (i.e., touch vs. no-touch), with an accuracy above 95%, generalised across users. This model, trained on a rigid tabletop surface, was found to retain an average accuracy of 96% for 7 other types of everyday surfaces with varying rigidity, and in walking and sitting scenarios where no touch occurred. ActualTouch can be combined with other interaction techniques, such as in a uni-stroke gesture recogniser on arbitrary surfaces, where touch status from ActualTouch is used to delimit the motion gesture data that feed into the recogniser. We demonstrate the potential of ActualTouch in a range of scenarios, such as interaction for augmented reality applications, and leveraging daily surfaces and objects for ad-hoc interactions.
NeckSense
Authors: Zhang Shibo , Zhao Yuqi , Nguyen Dzung Tri , Xu Runsheng , Sen Sougata , Hester Josiah , Alshurafa Nabil
Published: June 2020

We present the design, implementation, and evaluation of a multi-sensor, low-power necklace, NeckSense, for automatically and unobtrusively capturing fine-grained information about an individual's eating activity and eating episodes, across an entire waking day in a naturalistic setting. NeckSense fuses and classifies the proximity of the necklace from the chin, the ambient light, the Lean Forward Angle, and the energy signals to determine chewing sequences, a building block of the eating activity. It then clusters the identified chewing sequences to determine eating episodes. We tested NeckSense on 11 participants with and 9 participants without obesity, across two studies, where we collected more than 470 hours of data in a naturalistic setting. Our results demonstrate that NeckSense enables reliable eating detection for individuals with diverse body mass index (BMI) profiles, across an entire waking day, even in free-living environments. Overall, our system achieves an F1-score of 81.6% in detecting eating episodes in an exploratory study. Moreover, our system can achieve an F1-score of 77.1% for episodes even in an all-day-long free-living setting. With more than 15.8 hours of battery life, NeckSense will allow researchers and dietitians to better understand natural chewing and eating behaviors. In the future, researchers and dietitians can use NeckSense to provide appropriate real-time interventions when an eating episode is detected or when problematic eating is identified.
Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables
Authors: Sheng Taoran , Huber Manfred
Published: June 2020

Sensor data streams from wearable devices and smart environments are widely studied in areas like human activity recognition (HAR), person identification, or health monitoring. However, most of the previous works in activity and sensor stream analysis have been focusing on one aspect of the data, e.g. only recognizing the type of the activity or only identifying the person who performed the activity. We instead propose an approach that uses a weakly supervised multi-output siamese network that learns to map the data into multiple representation spaces, where each representation space focuses on one aspect of the data. The representation vectors of the data samples are positioned in the space such that the data with the same semantic meaning in that aspect are closely located to each other. Therefore, as demonstrated with a set of experiments, the trained model can provide metrics for clustering data based on multiple aspects, allowing it to address multiple tasks simultaneously and even to outperform single task supervised methods in many situations. In addition, further experiments are presented that in more detail analyze the effect of the architecture and of using multiple tasks within this framework, that investigate the scalability of the model to include additional tasks, and that demonstrate the ability of the framework to combine data for which only partial relationship information with respect to the target tasks is available.
Mobileportation
Authors: Young Jacob , Langlotz Tobias , Mills Steven , Regenbrecht Holger
Published: June 2020

The desire to stay connected to one another over large distances has guided decades of telepresence research. Most focuses on stationary solutions that can deliver high-fidelity telepresence experiences, but these are usually impractical for the wider population who cannot afford the necessary proprietary equipment or are unwilling to regress to non-mobile communication. In this paper we present Mobileportation, a nomadic telepresence prototype that takes advantage of recent developments in mobile technology to provide immersive experiences wherever the user desires by allowing for seamless transitions between ego- and exocentric views within a mutually shared three-dimensional environment. The results of a user study are also discussed that show Mobileportation's ability to induce a sense of presence within this environment and with the remote communication partner, as well as the potential of this platform for future telepresence research.
IoT Inspector
Authors: Huang Danny Yuxing , Apthorpe Noah , Li Frank , Acar Gunes , Feamster Nick
Published: June 2020

The proliferation of smart home devices has created new opportunities for empirical research in ubiquitous computing, ranging from security and privacy to personal health. Yet, data from smart home deployments are hard to come by, and existing empirical studies of smart home devices typically involve only a small number of devices in lab settings. To contribute to data-driven smart home research, we crowdsource the largest known dataset of labeled network traffic from smart home devices from within real-world home networks. To do so, we developed and released IoT Inspector, an open-source tool that allows users to observe the traffic from smart home devices on their own home networks. Between April 10, 2019 and January 21, 2020, 5,404 users have installed IoT Inspector, allowing us to collect labeled network traffic from 54,094 smart home devices. At the time of publication, IoT Inspector is still gaining users and collecting data from more devices. We demonstrate how this data enables new research into smart homes through two case studies focused on security and privacy. First, we find that many device vendors, including Amazon and Google, use outdated TLS versions and send unencrypted traffic, sometimes to advertising and tracking services. Second, we discover that smart TVs from at least 10 vendors communicated with advertising and tracking services. Finally, we find widespread cross-border communications, sometimes unencrypted, between devices and Internet services that are located in countries with potentially poor privacy practices. To facilitate future reproducible research in smart homes, we will release the IoT Inspector data to the public.
Outstanding Oxygen Reduction Kinetics of La0.6Sr0.4FeO3−δ Surfaces Decorated with Platinum Nanoparticles
Authors: Riedl Christoph , Schmid Alexander , Nenning Andreas , Summerer Harald , Smetaczek Stefan , Schwarz Sabine , Bernardi Johannes , Optiz Alexander , Limbeck Andreas , Fleig Juergen
Published: June 2020

La0.6Sr0.4FeO3−δ
 (LSF64) thin films are prepared by pulsed laser deposition (PLD) on yttria stabilized zirconia single crystals (YSZ) and characterized by electrochemical impedance spectroscopy (EIS) measurements before and after decoration with platinum nanoparticles. The platinum on the surface of LSF64 strongly accelerates the oxygen surface exchange kinetics. Especially at low oxygen partial pressures, the area-specific resistance (ASR) decreases by almost two orders of magnitude (e.g. in 0.25 mbar pO2 from 125 Ωcm2 to ca. 2 Ωcm2 at 600 °C). While the pure LSF64 films exhibit severe degradation of the polarization resistance, Pt decorated films degrade much slower and show less scatter between individual samples. Surprisingly, faster oxygen incorporation (=lower polarization resistance) results for lower oxygen partial pressures, which indicates a severe mechanism change compared to undecorated LSF64 surfaces. The obtained results thus also reveal valuable information on the rate-determining step of oxygen exchange on LSF64 surfaces with and without platinum. On undecorated LSF64 surfaces oxygen dissociation is suggested to be rate limiting, while the Pt particles on LSF64 enable fast oxygen dissociation. Consequently, on Pt-decorated LSF64 electrodes a kind of job sharing mechanism results, with oxygen dissociation taking place on Pt and oxide ion formation and incorporation proceeding on the oxide.
Effect of Agar as Electrolyte Additive on the Aluminum-Air Batteries
Authors: Lee Woo-Hyuk , Choi Seok-Ryul , Kim Jung-Gu
Published: June 2020

The performance of aluminum-air battery is improved by adding agar molecules to the electrolyte (4 M NaOH). A significant suppression of the parasitic self-corrosion reaction and the improvement of fuel efficiency were obtained. The fuel efficiency is elevated up to 35.95% and the corrosion inhibition efficiency increases up to 62.8%. The physisorption of the agar molecules on the aluminum surface improved the performance of aluminum-air battery. The adsorption of agar molecules on the aluminum surface was observed from the surface analysis with SEM, Freundlich adsorption isotherm and the adsorption energies from the computational simulations. Furthermore, the optimized structure model of agar molecules on the aluminum surface was proposed. To figure out the inhibition performance of agar molecules as an electrolyte additive for aluminum-air batteries, the experimental methods such as hydrogen evolution test, electrochemical tests, surface analysis and density functional theory (DFT) with computational simulations are used in this study.
Evolution of altered tubular metabolism and mitochondrial function in sepsis-associated acute kidney injury
Authors: Li Ying , Nourbakhsh Noureddin , Pham Hai , Tham Rick , Zuckerman Jonathan E. , Singh Prabhleen
Published: June 2020

Sepsis-associated acute kidney injury (s-AKI) has a staggering impact in patients and lacks any treatment. Incomplete understanding of the pathogenesis of s-AKI is a major barrier to the development of effective therapies. We address the gaps in knowledge regarding renal oxygenation, tubular metabolism, and mitochondrial function in the pathogenesis of s-AKI using the cecal ligation and puncture (CLP) model in mice. At 24 h after CLP, renal oxygen delivery was reduced; however, fractional oxygen extraction was unchanged, suggesting inefficient renal oxygen utilization despite decreased glomerular filtration rate and filtered load. To investigate the underlying mechanisms, we examined temporal changes in mitochondrial function and metabolism at 4 and 24 h after CLP. At 4 h after CLP, markers of mitochondrial content and biogenesis were increased in CLP kidneys, but mitochondrial oxygen consumption rates were suppressed in proximal tubules. Interestingly, at 24 h, proximal tubular mitochondria displayed high respiratory capacity, but with decreased mitochondrial content, biogenesis, fusion, and ATP levels in CLP kidneys, suggesting decreased ATP synthesis efficiency. We further investigated metabolic reprogramming after CLP and observed reduced expression of fatty acid oxidation enzymes but increased expression of glycolytic enzymes at 24 h. However, assessment of functional glycolysis revealed lower glycolytic capacity, glycolytic reserve, and compensatory glycolysis in CLP proximal tubules, which may explain their susceptibility to injury. In conclusion, we demonstrated significant alterations in renal oxygenation, tubular mitochondrial function, and metabolic reprogramming in s-AKI, which may play an important role in the progression of injury and recovery from AKI in sepsis.
Th2-Immune Polarizing and Anti-Inflammatory Properties of Insulin Are Not Effective in Type 2 Diabetic Pregnancy
Authors: Fagninou Adnette , Nekoua Magloire Pandoua , Sossou Darius , Moutairou Kabirou , Fievet Nadine , Yessoufou Akadiri
Published: June 2020

Background. The implication of the immune system in the physiopathology of pregnancy complicated by diabetes has been reported. Here, we investigated the effects of insulin treatment on the frequencies of immune cell subpopulations as well as T cell-derived cytokines in type 2 diabetic (T2D) pregnancy compared to gestational diabetes mellitus (GDM). Methods. Fifteen (15) women with GDM, twenty (20) insulin-treated T2D pregnant women, and twenty-five (25) pregnant controls were selected. Immune cell subpopulation frequencies were determined in blood using flow cytometry. The proliferative capacity of T cells was performed, and serum and cell culture supernatant cytokine levels were also quantified. Results. The frequencies of total CD3+ and CD4+ T cells and nonclassical monocytes significantly increased in insulin-treated T2D pregnant women compared to pregnant controls. The proportions of CD4+ T cells as well as B cells were significantly higher in women with GDM than in pregnant controls. GDM was associated with high frequencies of total CD3+ and CD4+ T cells and B cell expansion, suggesting a concomitant activation of cellular and humoral immunity. Concomitantly, Th1/Th2 ratio, determined as IFN-γ/IL-4, was shifted towards Th1 phenotype in women with GDM and insulin-treated T2D pregnant women. Besides, isolated T cells elicited similar proliferative capacity in the three groups of women. Insulin-treated T2D pregnant women and women with GDM exhibited a low serum IL-10 level, without any change in the number of Treg cells. Conclusion. Our study showed that, despite insulin treatment, pregnant women with T2D displayed a proinflammatory status consistent with high proportions of CD3+ and CD4+ T cells, upregulation of Th1 cytokines, and low IL-10 production, suggesting a reduced immune-suppressive activity of regulatory T cells. However, GDM, although associated with proinflammatory status, has shown increased humoral immunity consistent with high proportion of CD19+ B cells. Thus, the lack of response to insulin in diabetes during pregnancy and clinical implications of these immunological parameters deserves further investigations.
Existence and Uniqueness Results for a Class of Singular Fractional Boundary Value Problems with the p-Laplacian Operator via the Upper and Lower Solutions Approach
Authors: Jong KumSong , Choi HuiChol , Jang KyongJun , Pak SunAe
Published: June 2020

In this paper, we study the existence and uniqueness of positive solutions to a class of multipoint boundary value problems for singular fractional differential equations with the p-Laplacian operator. Here, the nonlinear source term f permits singularity with respect to its time variable t. Some fixed-point theorems such as the Leray-Schauder nonlinear alternative, the Schauder fixed-point theorem, and the Banach contraction mapping principle and the properties of the Gauss hypergeometric function are used to prove our main results. And by employing the upper and lower solutions technique, we derive a new approach to obtain the maximal and minimal solutions to the given problem. Finally, we present some examples to demonstrate our existence and uniqueness results.
Cutaneous Myoepithelioma: An Unusual Tumor in the Hand
Authors: Montalvo Nelson , Redrobán Ligia , Galarza David , Ramírez Iván
Published: June 2020

Cutaneous myoepithelioma (CM) is a rare tumor among the primary skin neoplasms. We present the case of a patient with a diagnosis of CM in the right hypothenar region. Histological study showed a proliferation of myoepithelial cells with a solid, reticular growth pattern in a chondromyxoid stroma. The tumor cells were positive for CK AE, S-100, EMA, and p63.
High-Speed Train Emergency Brake Modeling and Online Identification of Time-Varying Parameters
Authors: Jin Yongze , Xie Guo , Chen Pang , Hei Xinhong , Ji Wenjiang , Zhao Jinwei
Published: June 2020

By analyzing the mechanism of pure air emergency brake for high-speed train, the discrete emergency brake model is established. Aiming at the problem that time-varying hidden parameters cannot be observed directly, the sliding window-based expectation maximization is proposed, and the unobserved time-varying brake parameters are identified. Firstly, the position and size of the sliding window are selected; then, the sliding window-based expectation maximization is used for brake parameter identification; finally, combined with the gradient optimization, the optimal identifications of emergency brake parameters are obtained. The simulation results show that the brake parameters can be identified quickly and accurately by the proposed method. Under uniform noise, the identification errors of friction coefficient and braking ratio are ±0.0068 and ±0.0349, respectively, and the maximum relative errors between the identifications and true values are 2.4807% and 1.3154%, respectively, which can meet the actual requirements of the brake system. The effectiveness and practicability of the proposed model and method are verified.
Prediction of Protein‐Protein Interactions with Local Weight‐Sharing Mechanism in Deep Learning
Authors: Yang Lei , Han Yukun , Zhang Huixue , Li Wenlong , Dai Yu
Published: June 2020

Protein‐protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time‐consuming and expensive. Therefore, it is important to develop computational approaches for predicting PPIs. In this paper, an improved model is proposed to use a machine learning method in the study of protein‐protein interactions. With the consideration of the factors affecting the prediction of the PPIs, a method of feature extraction and fusion is proposed to improve the variety of the features to be considered in the prediction. Besides, with the consideration of the effect affected by the different input order of the two proteins, we propose a “Y‐type” Bi‐RNN model and train the network by using a method which both needs backward and forward training. In order to insure the training time caused on the extra training either a backward one or a forward one, this paper proposes a weight‐sharing policy to minimize the parameters in the training. The experimental results show that the proposed method can achieve an accuracy of 99.57%, recall of 99.36%, sensitivity of 99.76%, precision of 99.74%, MCC of 99.14%, and AUC of 99.56% under the benchmark dataset.
Real-World Results of Ocrelizumab Treatment for Primary Progressive Multiple Sclerosis
Authors: Daniels K. , van der Nat P. B. , Frequin S. T. F. M. , van der Wees P. J. , Biesma D. H. , Hoogervorst E. L. J. , van de Garde E. M. W.
Published: June 2020

Background. Recently, ocrelizumab (Ocrevus®) was approved for the treatment of primary progressive multiple sclerosis (PPMS) based on data from the ORATORIO clinical trial. Real-world data about the clinical effectiveness of ocrelizumab has yet to be gathered. Objective. The aim of this study was to provide data about the clinical effectiveness of ocrelizumab for patients diagnosed with PPMS in a real-world setting. Methods. We conducted a retrospective cohort study of all patients with PPMS who started ocrelizumab treatment (n=21) in St. Antonius Hospital (Utrecht/Nieuwegein, the Netherlands) between April 2018 and December 31, 2018. Primary outcome was pre- versus post-ocrelizumab disability worsening rate (from 96 weeks prior to first ocrelizumab administration up to 24 weeks post first ocrelizumab administration). Results. Disability worsening rate while on treatment significantly differed (lower) from disability worsening rate in pre-treatment period (Z=−2.81, p≤.01). Three out of 17 patients showed a clinically relevant improvement in disability status after treatment start. Conclusion. Ocrelizumab can stabilize disability progression in patients with PPMS. Some patients even showed a clinically relevant improvement in disability status. Further research should help to identify which patients benefit most from ocrelizumab.
BCG-Induced Trained Immunity in Healthy Individuals: The Effect of Plasma Muramyl Dipeptide Concentrations
Authors: Mourits Vera P. , Koeken Valerie A. C. M. , de Bree L. Charlotte J. , Moorlag Simone J. C. F. M. , Chu Wern Cui , Xu Xiaoli , Dijkstra Helga , Lemmers Heidi , Joosten Leo A. B. , Wang Yue , van Crevel Reinout , Netea Mihai G.
Published: June 2020

BCG vaccination protects not only against tuberculosis but also against heterologous infections. This effect differs between individuals, yet the factors responsible for this variation are unknown. BCG-induced nonspecific protection is, at least partially, mediated by innate immune reprogramming (trained immunity), which can be induced by the muramyl dipeptide (MDP) component of peptidoglycans. We aimed to study whether differential release of MDP in healthy individuals may explain variability of their response to BCG vaccination. Circulating MDP concentrations were increased up to three months after BCG vaccination. MDP concentrations at baseline, but not their increase postvaccination, positively correlated with the induction of trained immunity and not with mycobacteria-induced T-cell responses. Interestingly, MDP concentrations correlated with inflammatory markers in the circulation. In conclusion, circulating MDP concentrations are associated with the strength of trained immunity responses and thus influence the biological effects of BCG vaccination. This study increases our understanding about the role of MDP in BCG-induced trained immunity, which might help to optimize vaccine efficacy and explore novel applications of BCG vaccination.
A Dynamic Thermal-Allocation Solution to the Complex Economic Benefit for a Data Center
Authors: Liu Hui , Song Wenyu , Jin Tianqi , Wu Zhiyong , Yan Fusheng , Song Jie
Published: June 2020

Data centers, which provide computing services and gain profits, are indispensable to every city in the information era. They offer computation and storage while consuming energy and generate thermal discharges. To maximize the economic benefit, the existing research studies on the data center workload management mostly leverage the dynamical power model, i.e., the power-aware workload allocation. Nevertheless, we argue that for the complex relationship between the economic benefit and so many attributes, such as computation, energy consumption, thermal distribution, cooling, and equipment life, the thermal distribution dominates the others. Thus, thermal-aware workload allocation is more efficient. From the perspective of economic benefits, we propose a mathematical model for thermal distribution of a data center and study which workload distribution could determinately change the thermal distribution in the dynamic data center runtime, so as to reduce the cost and improve the economic benefits under the guarantee of service provisioning. By solving the thermal environment evaluation indexes, RHI (Return Heat Index) and RTI (Return Temperature Index), as well as heat dissipation models, we define quantitative models for the economic analysis such as energy consumption model for the busy servers and cooling, energy price model, and the profit model of data centers. Numerical simulation results validate our propositions and show that the average temperature of the data center reaches the best values, and the local hot spots are avoided effectively in various situations. As a conclusion, our studies contribute to the thermal management of the dynamic data center runtime for better economic benefits.
Subthreshold Autism Spectrum in a Patient with Anorexia Nervosa and Behçet’s Syndrome
Authors: Dell’Osso L. , Carpita B. , Cremone I. M. , Mucci F. , Salerni A. , Marazziti D. , Carmassi C. , Gesi C.
Published: June 2020

Recently, increasing research stressed the presence of subthreshold autistic traits in patients with other psychiatric conditions. In this framework, a significant relationship between anorexia nervosa (AN) and the autism spectrum has been frequently reported, in particular among female samples, to the point that AN has been hypothesized to be a female phenotype of autism spectrum disorder (ASD). On the other hand, among subjects with ASD has been reported a higher prevalence of immune diseases and altered immune functions. While these reports seem to support an association between neurodevelopmental and immune system alterations in ASD, the relationship between the immune system and the broader autism spectrum, including its subthreshold manifestations, remains poorly investigated. In this report, we described the presence of autistic traits in a male inpatient with AN and separation anxiety disorder, who also show a diagnosis of Behçet’s syndrome (BS). This case seems to further stress the association between AN and the autism spectrum, which may not be limited to the female gender. Moreover, it further suggests a deeper link between neurodevelopmental and immune system alterations. Implications are discussed in light of the more recent neurobiological and psychopathological hypothesis about the autism spectrum.
Periodic Averaging Principle for Neutral Stochastic Delay Differential Equations with Impulses
Authors: Wang Peiguang , Xu Yan
Published: June 2020

In this paper, we study the periodic averaging principle for neutral stochastic delay differential equations with impulses under non-Lipschitz condition. By using the linear operator theory, we deal with the difficulty brought by delay term of the neutral system and obtain the conclusion that the solutions of neutral stochastic delay differential equations with impulses converge to the solutions of the corresponding averaged stochastic delay differential equations without impulses in the sense of mean square and in probability. At last, an example is presented to show the validity of the proposed theories.