bluuebunny/crossref_metadata_2025 huggingface dataset:
Relevance of a TCGA-derived Glioblastoma Subtype Gene-Classifier among Patient Populations
Authors: Teo Wan-Yee , Sekar Karthik , Seshachalam Pratap , Shen Jianhe , Chow Wing-Yuk , Lau Ching C. , Yang HeeKyoung , Park Junseong , Kang Seok-Gu , Li Xiaonan , Nam Do-Hyun , Hui Kam M.
Published: May 2019

Glioblastoma multiforme (GBM), a deadly cancer, is the most lethal and common malignant brain tumor, and the leading cause of death in adult brain tumors. While genomic data continues to rocket, clinical application and translation to patient care are lagging behind. Big data now deposited in the TCGA network offers a window to generate novel clinical hypotheses. We hypothesized that a TCGA-derived gene-classifier can be applied across different gene profiling platforms and population groups. This gene-classifier validated three robust GBM-subtypes across six different platforms, among Caucasian, Korean and Chinese populations: Three Caucasian-predominant TCGA-cohorts (Affymetrix U133A = 548, Agilent Custom-Array = 588, RNA-seq = 168), and three Asian-cohorts (Affymetrix Human Gene 1.0ST-Array = 61, Illumina = 52, Agilent 4 × 44 K = 60). To understand subtype-relevance in patient therapy, we investigated retrospective TCGA patient clinical sets. Subtype-specific patient survival outcome was similarly poor and reflected the net result of a mixture of treatment regimens with/without surgical resection. As a proof-of-concept, in subtype-specific patient-derived orthotopic xenograft (PDOX) mice, Classical-subtype demonstrated no survival difference comparing radiation-therapy versus temozolomide monotherapies. Though preliminary, a PDOX model of Proneural/Neural-subtype demonstrated significantly improved survival with temozolomide compared to radiation-therapy. A larger scale study using this gene-classifier may be useful in clinical outcome prediction and patient selection for trials based on subtyping.
Discrimination of the hierarchical structure of cortical layers in 2-photon microscopy data by combined unsupervised and supervised machine learning
Authors: Li Dong , Zavaglia Melissa , Wang Guangyu , Xie Hong , Hu Yi , Werner Rene , Guan Ji-Song , Hilgetag Claus C.
Published: May 2019

The laminar organization of the cerebral cortex is a fundamental characteristic of the brain, with essential implications for cortical function. Due to the rapidly growing amount of high-resolution brain imaging data, a great demand arises for automated and flexible methods for discriminating the laminar texture of the cortex. Here, we propose a combined approach of unsupervised and supervised machine learning to discriminate the hierarchical cortical laminar organization in high-resolution 2-photon microscopic neural image data of mouse brain without observer bias, that is, without the prerequisite of manually labeled training data. For local cortical foci, we modify an unsupervised clustering approach to identify and represent the laminar cortical structure. Subsequently, supervised machine learning is applied to transfer the resulting layer labels across different locations and image data, to ensure the existence of a consistent layer label system. By using neurobiologically meaningful features, the discrimination results are shown to be consistent with the layer classification of the classical Brodmann scheme, and provide additional insight into the structure of the cerebral cortex and its hierarchical organization. Thus, our work paves a new way for studying the anatomical organization of the cerebral cortex, and potentially its functional organization.
Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma
Authors: Harder Nathalie , Schönmeyer Ralf , Nekolla Katharina , Meier Armin , Brieu Nicolas , Vanegas Carolina , Madonna Gabriele , Capone Mariaelena , Botti Gerardo , Ascierto Paolo A. , Schmidt Günter
Published: May 2019

In the context of precision medicine with immunotherapies there is an increasing need for companion diagnostic tests to identify potential therapy responders and avoid treatment coming along with severe adverse events for non-responders. Here, we present a retrospective case study to discover image-based signatures for developing a potential companion diagnostic test for ipilimumab (IPI) in malignant melanoma. Signature discovery is based on digital pathology and fully automatic quantitative image analysis using virtual multiplexing as well as machine learning and deep learning on whole-slide images. We systematically correlated the patient outcome data with potentially relevant local image features using a Tissue Phenomics approach with a sound cross validation procedure for reliable performance evaluation. Besides uni-variate models we also studied combinations of signatures in several multi-variate models. The most robust and best performing model was a decision tree model based on relative densities of CD8+ tumor infiltrating lymphocytes in the intra-tumoral infiltration region. Our results are well in agreement with observations described in previously published studies regarding the predictive value of the immune contexture, and thus, provide predictive potential for future development of a companion diagnostic test.
Generation of a Jurkat-based fluorescent reporter cell line to evaluate lipid antigen interaction with the human iNKT cell receptor
Authors: Humeniuk Piotr , Geiselhart Sabine , Battin Claire , Webb Tonya , Steinberger Peter , Paster Wolfgang , Hoffmann-Sommergruber Karin
Published: May 2019

Invariant natural killer T (iNKT) cells are a specialized subset of T cells contributing to both, the innate and adaptive immune responses. In contrast to conventional T lymphocytes they recognize lipid antigens. The aim of the project is to establish a novel model system, to study iNKT-TCR – ligand interaction. An iNKT reporter cell line (JE6-1REP-iNKT) was engineered by introducing the human iNKT-TCR into a human leukemic T cell line carrying an NF-κB-driven fluorescent transcriptional reporter construct. Antigen presenting BWSTIMcells expressing human CD1d and CD80 were generated. Reporter induction in JE6-1REP-iNKTcells was assessed by flow cytometry. CRISPR/Cas9 was used for β2M knock out in JE6-1REP-iNKTcells to abrogate CD1d expression and thus excluding antigen self-presentation. Reporter cells were shown to specifically react with iNKT antigens presented via CD1d. Their sensitivity towards α-GalCer was comparable to a murine iNKT hybridoma cell line. In conclusion, we created a novel iNKT reporter platform which, compared to traditional iNKT cell assays, is characterized by a shorter turnaround time and lower costs. It thus facilitates the identification of antigenic structures that drive the activation of iNKT cells in health and disease.
Improvement of wear resistance in a pearlitic rail steel via quenching and partitioning processing
Authors: Masoumi Mohammad , Echeverri Edwan Anderson Ariza , Tschiptschin André Paulo , Goldenstein Hélio
Published: May 2019

Improvement of wear resistance and mechanical performance of rails used in heavy-haul railway are essential to reduce railroad maintenance costs. A novel heat treatment based on quenching and partitioning (Q&P) processing was proposed to improve the wear resistance of a hypereutectoid pearlitic rail. 50% of austenite was transformed into martensite under an interrupted quenching from full austenitization temperature to 140 °C. A multiphase microstructure resulted from the quenching and partitioning process, consisting of tempered martensite, bainite, retained austenite, and pearlite colonies. The partitioning step was performed in the range of 350–650 °C. Microstructure characteristics were investigated using scanning electron microscopy, microhardness measurements, X-ray and electron backscattered diffraction. Uniaxial tensile and pin-on-disc tests were also performed to evaluate the mechanical properties and wear resistance. The best combination of wear resistance and mechanical performance was obtained in samples partitioned at 450 and 550 °C, which may be applied in the railway industries.
Computed tomography porosity and spherical indentation for determining cortical bone millimetre-scale mechanical properties
Authors: Boughton Oliver R. , Ma Shaocheng , Cai Xiran , Yan Liye , Peralta Laura , Laugier Pascal , Marrow James , Giuliani Finn , Hansen Ulrich , Abel Richard L. , Grimal Quentin , Cobb Justin P.
Published: May 2019

The cortex of the femoral neck is a key structural element of the human body, yet there is not a reliable metric for predicting the mechanical properties of the bone in this critical region. This study explored the use of a range of non-destructive metrics to measure femoral neck cortical bone stiffness at the millimetre length scale. A range of testing methods and imaging techniques were assessed for their ability to measure or predict the mechanical properties of cortical bone samples obtained from the femoral neck of hip replacement patients. Techniques that can potentially be applied in vivo to measure bone stiffness, including computed tomography (CT), bulk wave ultrasound (BWUS) and indentation, were compared against in vitro techniques, including compression testing, density measurements and resonant ultrasound spectroscopy. Porosity, as measured by micro-CT, correlated with femoral neck cortical bone’s elastic modulus and ultimate compressive strength at the millimetre length scale. Large-tip spherical indentation also correlated with bone mechanical properties at this length scale but to a lesser extent. As the elastic mechanical properties of cortical bone correlated with porosity, we would recommend further development of technologies that can safely measure cortical porosity in vivo.
Optimizing Silicon photomultipliers for Quantum Optics
Authors: Chesi Giovanni , Malinverno Luca , Allevi Alessia , Santoro Romualdo , Caccia Massimo , Martemiyanov Alexander , Bondani Maria
Published: May 2019

Silicon Photomultipliers are potentially ideal detectors for Quantum Optics and Quantum Information studies based on mesoscopic states of light. However, their non-idealities hampered their use so far. An optimal mode of operation has been developed and it is presented here, proving that this class of sensors can actually be exploited for the characterization of both classical and quantum properties of light.
Investigating the Effect of the Environment on Prey Detection Ability in Humans
Authors: Allen Peter J. , Wiener Jan M. , Gatzidis Christos , Stringer Chris B. , Stewart John R.
Published: May 2019

Visual search experiments used in the field of psychology may be applied to investigate the relationship between environments and prey detection rates that could influence hunting behaviours in ancient humans. Two lab-based experiments were designed to examine the effects of differing virtual environments, representing Marine Isotope Stage 3 (MIS3) in Europe, on participants’ ability to locate prey. The results show that prey detection performance is highly influenced by vegetation structure, both in terms of the biome type (wooded vs. grassland environments) and the density of the vegetation (trees in wooded and shrubs in grassland environments). However, the density of vegetation has a greater relative effect in grassland than in wooded biomes. Closer examination of the transition between biomes (relative percentages of trees vs. shrubs) at the same vegetative density shows a non-linear relationship between prey detection performance and the relative tree to shrub percentages. Changes in the distribution of biomes occurred throughout the Quaternary. The composition of those biomes will have likely affected hominin hunting behaviours because of their intermediary effects on prey detection performance. This may, therefore, have played a role in the turn-overs of hunter-gatherer hominin populations during MIS3 and at other times in the Quaternary.
The significance of serum HMGB1 level in humans with acute paraquat poisoning
Authors: Chen Feng , Liu Zuolong , Li Wei , Li Dan , Yan Bailing
Published: May 2019

High-mobility group box 1 (HMGB1) mediates acute lung injury in a mouse model of paraquat poisoning. However, published reports showing a clinically relevant association between HMGB1 and paraquat exposure are lacking. The objective of the present study was to investigate the potential role of serum HMGB1 level as a prognostic marker of mortality in patients with paraquat poisoning in a clinical setting. This retrospective observational cohort study included a convenience sample of 92 patients with acute paraquat poisoning admitted to the emergency room (ER) of The First Hospital of Jilin University between January 2014 and December 2016. Baseline serum HMGB1 levels and other laboratory parameters were measured on admission. Cumulative incidence of mortality during the first 30 days after admission was 50% (n = 46/92). Serum HMGB1 levels were higher in fatalities than survivors (P = 0.015), 30-day mortality increased with increasing baseline serum HMGB1 level (P < 0.001), and higher serum HMGB1 levels were associated with an increase in 30-day mortality on Kaplan-Meier analysis. Multivariate Cox regression analysis identified baseline serum HMGB1 levels, white blood cell count, and serum lactic acid levels as independent prognostic markers of 30-day mortality. These data suggest that serum HMGB1 levels measured on admission to the ER are an independent predictor of 30-day mortality in patients with acute paraquat poisoning.
Alterations in resting-state functional connectivity in patients with Crohn’s disease in remission
Authors: Hou Jiancheng , Mohanty Rosaleena , Nair Veena A. , Dodd Keith , Beniwal-Patel Poonam , Saha Sumona , Prabhakaran Vivek
Published: May 2019

Previous studies have found neural alterations in regions involved in cognitive and affective functions among Crohn’s disease (CD) patients. The present work recruited 18 CD patients and 18 age-gender matched healthy controls (HC) and specifically compared differences in resting-state functional connectivity (RSFC) within the executive control network (ECN) which has been implicated in cognitive function and default mode network (DMN), which has been implicated in affective function. Additionally, we examined the correlations between RSFC in ECN and verbal fluency (VF) in both groups as well as RSFC in DMN and anxiety level in the CD group. Results showed significantly increased RSFC between the right middle frontal gyrus and right inferior parietal lobule in ECN, as well as increased RSFC between the right precuneus and right posterior cingulate cortex in DMN, among CD patients compared to HC. However, the correlations between ECN/DMN and behavioral scores in each group were not significant, which was possibility due to the limited sample size. These findings suggest that CD patients may experience changes in the connectivity patterns in ECN and DMN. Increased connectivity observed on these networks could be a potential biomarker of a neuropsychiatric manifestation of CD.
Single-molecule pull-out manipulation of the shaft of the rotary motor F1-ATPase
Authors: Naito Tatsuya M. , Masaike Tomoko , Nakane Daisuke , Sugawa Mitsuhiro , Okada Kaoru A. , Nishizaka Takayuki
Published: May 2019

F1-ATPase is a rotary motor protein in which the central γ-subunit rotates inside the cylinder made of α3β3 subunits. To investigate interactions between the γ shaft and the cylinder at the molecular scale, load was imposed on γ through a polystyrene bead by three-dimensional optical trapping in the direction along which the shaft penetrates the cylinder. Pull-out event was observed under high-load, and thus load-dependency of lifetime of the interaction was estimated. Notably, accumulated counts of lifetime were comprised of fast and slow components. Both components exponentially dropped with imposed loads, suggesting that the binding energy is compensated by the work done by optical trapping. Because the mutant, in which the half of the shaft was deleted, showed only one fast component in the bond lifetime, the slow component is likely due to the native interaction mode held by multiple interfaces.
RAD sequencing sheds new light on the genetic structure and local adaptation of European scallops and resolves their demographic histories
Authors: Vendrami David L. J. , De Noia Michele , Telesca Luca , Handal William , Charrier Grégory , Boudry Pierre , Eberhart-Phillips Luke , Hoffman Joseph I.
Published: May 2019

Recent developments in genomics are advancing our understanding of the processes shaping population structure in wild organisms. In particular, reduced representation sequencing has facilitated the generation of dense genetic marker datasets that provide greater power for resolving population structure, investigating the role of selection and reconstructing demographic histories. We therefore used RAD sequencing to study the great scallopPecten maximusand its sister speciesP. jacobeusalong a latitudinal cline in Europe. Analysis of 219 samples genotyped at 82,439 single nucleotide polymorphisms clearly resolved an Atlantic and a Norwegian group withinP. maximusas well asP. jacobeus, in support of previous studies. Fine-scale structure was also detected, including pronounced differences involving Mulroy Bay in Ireland, where scallops are commercially cultured. Furthermore, we identified a suite of 279 environmentally associated loci that resolved a contrasting phylogenetic pattern to the remaining neutral loci, consistent with ecologically mediated divergence. Finally, demographic inference provided support for the twoP. maximusgroups having diverged during the last glacial maximum and subsequently expanded, whereasP. jacobeusdiverged around 95,000 generations ago and experienced less pronounced expansion. Our results provide an integrative perspective on the factors shaping genome-wide differentiation in a commercially important marine invertebrate.
Risk factors for in-brain local progression in elderly patients after resection of cerebral metastases
Authors: Munoz-Bendix Christopher , Rapp Marion , Mijderwijk Hendrik-Jan , von Sass Christiane , Dibué-Adjei Maxine , Cornelius Jan Frederick , Steiger Hans-Jakob , Turowski Bernd , Sabel Michael , Kamp Marcel A.
Published: May 2019

Intracranial metastases are the most frequent brain tumor with recurrence rates after treatment of around 40–60%. Age is still considered a determinant of treatment and prognosis in this pathology. Recent studies analyzing the impact of metastasectomy in elderly patients focused on reporting perioperative mortality and morbidity rates but not on the evaluation of oncological outcome parameters. Aim of this study is to determine risk factors for in-brain local recurrence after brain surgery in this sub-population. From October 2009 until September 2016 all patients aged 65 years and above with histopathologically confirmed metastasis after surgical resection were retrospectively studied. Clinical, radiological and perioperative information was collected and statistically analysed. Follow-up consisted of clinical and radiological assessment every 3-months following surgery. 78 patients were included, of these 50% were female (39 patients). Median age was 71 years (66–83). Early postoperative-MRI verified a complete surgical resection in 41 patients (52.6%) and showed a tumor-remnant in 15 patients (19.2%). In 22 patients the MRI result was inconclusive (28.2%). None of the patients experienced severe complications due to surgery. The median postoperative NIHSS was adequate 1 ± 1.4 (0–6), nonetheless, insignificantly improved in comparison to the preoperative NIHSS (p = 0.16). A total of 20 patients (25.6%) presented local recurrence. The only statistically significant factor for development of local in-brain recurrence after resection of cerebral metastases in patients above 65 years of age was a tumor-remnant in the early postoperative MRI (p = 0.00005). Median overall survival was 13 months. Local in-brain recurrence after surgical resection of a cerebral metastasis in patients above 65 years of age was 25.6%. In our analysis, tumor-remnant in early postoperative MRI is the only risk factor for local in-brain recurrence. Oncological parameters in the present cohort do not seem to differ from recent phase III studies with non-geriatric patients. Nevertheless, controlled studies on the impact of metastasectomy in elderly patients delivering high quality reliable data are required.
Oral somatosensatory acuity is related to particle size perception in chocolate
Authors: Breen Scott P. , Etter Nicole M. , Ziegler Gregory R. , Hayes John E.
Published: May 2019

Texture affects liking or rejection of many foods for clinically relevant populations and the general public. Phenotypic differences in chemosensation are well documented and influence food choices, but oral touch perception is less understood. Here, we used chocolate as a model food to explore texture perception, specifically grittiness perception. In Experiment 1, the Just Noticeable Difference (JND) for particle size in melted chocolate was ~5 μm in a particle size range commonly found in commercial chocolates; as expected, the JND increased with particle size, with a Weber Fraction of ~0.17. In Experiment 2, individual differences in touch perception were explored: detection and discrimination thresholds for oral point pressure were determined with Von Frey Hairs. Discrimination thresholds varied across individuals, allowing us to separate participants into high and low sensitivity groups. Across all participants, two solid commercial chocolates (with particle sizes of 19 and 26 μm; i.e., just above the JND) were successfully discriminated in a forced-choice task. However, this was driven entirely by individuals with better oral acuity: 17 of 20 of more acute individuals correctly identified the grittier chocolate versus 12 of 24 less acute individuals. This suggests phenotypic differences in oral somatosensation can influence texture perception of foods.
Author Correction: A micromechanics-based analytical solution for the effective thermal conductivity of composites with orthotropic matrices and interfacial thermal resistance
Authors: Lee Sangryun , Lee Jinyeop , Ryu Byungki , Ryu Seunghwa
Published: May 2019

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
Author Correction: Fast, Cost-effective and Energy Efficient Mercury Removal-Recycling Technology
Authors: Ganguly Mainak , Dib Simon , Ariya Parisa A.
Published: May 2019

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
Optimized liquid chromatography-electrospray quadrupole linear ion trap mass spectrometry method for the quantitation of paraquat in plasma: application to a toxicokinetic study
Authors: Fan Jiaming , Li Pengfei , Liu He , Zhao Rui , Zhao Zhixia , Du Ping , Liu Lihong
Published: May 2019

A convenient and sensitive LC-MS/MS method fitting for toxicokinetics study was validated for quantitation of paraquat in rat plasma.
Templated nanoreactor arrays for nanoscale-tunable liquid-phase catalysis
Authors: Zhang Shuo , Quan Xie , Chen Shuo , Yu Hongtao
Published: May 2019

Ordered nanocatalysts were produced alongside AAO channels, forming 3D-flexible nanoreactors with enhanced mass transfer and kinetics for internal catalysis.
In situ, operando studies on the size and structure of supported Pt catalysts under supercritical conditions by simultaneous synchrotron-based X-ray techniques
Authors: Lee Sungwon , Lee Sungsik , Gerceker Duygu , Kumbhalkar Mrunmayi D. , Wiaderek Kamila M. , Ball Madelyn R. , Mavrikakis Manos , Dumesic James A. , Winans Randall E.
Published: May 2019

Investigation of the size and structure of supported Pt catalysts under supercritical conditions leads to a fundamentally new level of understanding of nanoscale materials under extreme conditions.
Interaction potential surface between Raman scattering enhancing nanoparticles conjugated with a functional copolymer
Authors: Morita Takeshi , Ogawa Yuki , Imamura Hiroshi , Ookubo Kouki , Uehara Nobuo , Sumi Tomonari
Published: May 2019

The nano gap and the interaction aspect between Raman scattering enhancing nanoparticles conjugated with a functional copolymer were revealed based on the determined interaction potential surface.
Boronic acid catalysis
Authors: Hall Dennis G.
Published: May 2019

Although boronic acids are recognized primarily for their utility as reagents in transition metal-catalyzed transformations, other applications are emerging, including their use as reaction catalysts.
C–C coupling at a zeolite-supported Rh(i) complex. DFT search for the mechanism
Authors: Vummaleti Sai V. C. , Kuriakose Nishamol , Dinda Shrabani , Wu Yin , Genest Alexander , Rösch Notker
Published: May 2019

DFT modelling suggests a metallacycle mechanism for the dimerization of ethene over a faujasite-supported Rh(i) complex, rationalizing the experimental selectivity.
Metal-coordination driven intramolecular twisting: a turn-on fluorescent-redox probe for Hg2+ions through the interaction of ferrocene nonbonding orbitals and dibenzylidenehydrazine
Authors: Bhatta Sushil Ranjan , Mondal Bijan , Lima Sudhir , Thakur Arunabha
Published: May 2019

A uniqueC2 symmetric azine bridged bi-ferrocenyl receptor has been designed and synthesized for the selective detection of Hg2+ion with a low detection limit as 15 nMviaturn on fluorescence with a blue shift.
Synthesis and structural characterization of homochiral coordination polymers with imidazole-based monocarboxylate ligands
Authors: Borrego Elena , Nicasio Antonio I. , Álvarez Eleuterio , Montilla Francisco , Córdoba José Manuel , Galindo Agustín
Published: May 2019

Two-dimensional homochiral coordination polymers of sodium, silver, copper and zinc were obtained with 2alkyl,2-(1H-imidazol-1-yl)acetate anions as bridging ligands.
A model sensitivity analysis to determine the most important physicochemical properties driving environmental fate and exposure of engineered nanoparticles
Authors: Meesters J. A. J. , Peijnenburg W. J. G. M. , Hendriks A. J. , Van de Meent D. , Quik J. T. K.
Published: May 2019

Sensitivity analyses indicate attachment efficiency and transformation rate constant are most important in modeling environmental fate of engineered nanoparticles.
Ferric reducing reactivity assay with theoretical kinetic modeling uncovers electron transfer schemes of metallic-nanoparticle-mediated redox in water solutions
Authors: Bi Xiangyu , Westerhoff Paul
Published: May 2019

We probed that metallic nanoparticles (NPs) can mediate electron transfer in water by different schemes.
CO2 conversion by high-dose rate electron beam irradiation: one-step, metal-free and simultaneous production of H2, CO, CH4, C2H6 and organic acids from an acid-decomposed CaCO3/additive EtOH mixture
Authors: Hosokawa Yoichi , Kajiya Shuji , Ohshima Ayako , Ishida Nobuhiro , Washio Masakazu , Usuki Arimitsu
Published: May 2019

The reduction in CO2 emissions is an important issue across many industries.
The speciation analysis of iodate and iodide in high salt brine by high performance liquid chromatography and inductively coupled plasma mass spectrometry
Authors: Cui Wanjing , Hou Hongfang , Chen Jiaojiao , Yu Xiaoping , Guo Yafei , Tao Zhanhui , Deng Tianlong , Chen Yu-Wei , Belzile Nelson
Published: May 2019

A sensitive and interference-free iodine speciation analysis in high salt matrix is crucial either for the application of iodine ion-exchange adsorption removal or in brine chemical engineering industrial of caustic soda.
High efficiency tandem polymer solar cells with MoO3/Ni/ZnO:PEOz hybrid interconnection layers
Authors: Seo Jooyeok , Moon Yejin , Lee Sooyong , Lee Chulyeon , Kim Dohan , Kim Hwajeong , Kim Youngkyoo
Published: May 2019

Tandem polymer solar cells with MoO3/Ni/ZnO:PEOz interconnection layers exhibited PCE = 14.22% at the Ni thickness of 6 nm.
Recent insights into upconverting nanoparticles: spectroscopy, modeling, and routes to improved luminescence
Authors: Tessitore Gabriella , Mandl Gabrielle A. , Brik Mikhail G. , Park Wounjhang , Capobianco John A.
Published: May 2019

Advances in understanding the mechanisms of luminescence in lanthanide-doped upconverting nanoparticles can guide researchers in developing brighter materials. This review discusses the latest developments in the field and suggests routes to improvements.
NHC-copper-thiophene-2-carboxylate complex for the hydroboration of terminal alkynes
Authors: Jang Won Jun , Kang Byung-Nam , Lee Ji Hun , Choi Yoon Mi , Kim Chong-Hyeak , Yun Jaesook
Published: May 2019

An air-stable N-heterocyclic carbene–copper thiophene-2-carboxylate (CuTC) complex has been prepared for the stereoselective hydroboration of terminal alkynes using pinacolborane (HBpin) or 1,8-naphthalenediaminatoborane (HBdan).
Polymer-grafted gold nanoflowers with temperature-controlled catalytic features by in situ particle growth and polymerization
Authors: Chen Chaojian , Ng David Yuen Wah , Weil Tanja
Published: May 2019

Catalytically active polymer-grafted gold nanoflowers are prepared by combining ARGET ATRP and metal reduction in a one pot reaction.
Electrochemical Minisci-type trifluoromethylation of electron-deficient heterocycles mediated by bromide ions
Authors: Dou Gui-Yuan , Jiang Yang-Ye , Xu Kun , Zeng Cheng-Chu
Published: May 2019

An electrochemical methodology for the Minisci-type trifluoromethylation of electron-deficient heterocycles mediated by cheap and easily available bromide ions has been developed.
Hepatitis B virus S gene therapy with 10-23 DNAzyme delivered by chitosan-g-stearic acid micelles
Authors: Hong Yun , Mao Dongsen , Wu Rui , Gao Zhe , Meng Tingting , Wang Rongrong , Liu Lin , Miao Jing
Published: May 2019

DrzBS, which targets HBV S gene expression, has important research significance and potential application value. CSO-SA is a safe and efficient non-viral gene carrier and CSO-SA/DrzBS micelles are a promising application for anti-HBV gene therapy.
Mixture of quantum dots and ZnS nanoparticles as emissive layer for improved quantum dots light emitting diodes
Authors: Song Taeyoung , Cheong Jun Young , Cho Hyunjin , Kim Il-Doo , Jeon Duk Young
Published: May 2019

Mixture of quantum dots and ZnS nanoparticles as emissive layer for improved QLEDs by decreasing energy transfer between the QDs.
Rheological properties of an ultra-high salt hydrophobic associated polymer as a fracturing fluid system
Authors: Gao Jinhao , Zhang Guanghua , Wang Lei , Ding Li , Shi Huaqiang , Lai Xiaojuan , Wen Xin , Ma Shaoyun , Huang Chuanqing
Published: May 2019

Surfactant and hydrophobic chains form a dense network structure, resulting in an improvement in the salt tolerance of the polymer.
Vesicular self-assembly of a natural ursane-type dihydroxy-triterpenoid corosolic acid
Authors: Bag Braja G. , Garai Chhabi , Ghorai Subrata
Published: May 2019

Corosolic acid, a natural ursane-type 6-6-6-6-6 pentacyclic dihydroxy triterpenic acid, self-assembled in binary liquid mixtures yielding vesicles.
Variations Within Normal Hearing Acuity and Speech Comprehension: An Exploratory Study
Authors: Ayasse Nicole D. , Penn Lana R. , Wingfield Arthur
Published: May 2019

Purpose

Many young adults with a mild hearing loss can appear unaware or unconcerned about their loss or its potential effects. A question that has not been raised in prior research is whether slight variability, even within the range of clinically normal hearing, may have a detrimental effect on comprehension of spoken sentences, especially when attempting to understand the meaning of sentences that offer an additional cognitive challenge. The purpose of this study was to address this question.

Method

An exploratory analysis was conducted on data from 3 published studies that included young adults, ages 18 to 29 years, with audiometrically normal hearing acuity (pure-tone average < 15 dB HL) tested for comprehension of sentences that conveyed the sentence meaning with simpler or more complex linguistic structures. A product–moment correlation was conducted between individuals' hearing acuity and their comprehension accuracy.

Results

A significant correlation appeared between hearing acuity and comprehension accuracy for syntactically complex sentences, but not for sentences with a simpler syntactic structure. Partial correlations confirmed this relationship to hold independent of participant age within this relatively narrow age range.

Conclusion

These findings suggest that slight elevations in hearing thresholds, even among young adults who pass a screen for normal hearing, can affect comprehension accuracy for spoken sentences when combined with cognitive demands imposed by sentences that convey their meaning with a complex linguistic structure. These findings support limited resource models of attentional allocation and argue for routine baseline hearing evaluations of young adults with current age-normal hearing acuity.
Hiding in Plain Sight: Text Comprehension, Hyperlexia, and Adolescents With Autism Spectrum Disorder
Authors: Robertson Shari B.
Published: May 2019

Purpose

Reading comprehension is a critical skill for success in academic, social, and vocational settings. However, comprehension problems for readers with autism spectrum disorder (ASD) are often overlooked during the period when most children are learning to read, masked by strong early decoding skills, a good memory for specific facts, and an understanding of concrete content. As students progress through the grades, the content of what they must read to be successful becomes increasingly complex and the comprehension deficit, present but unrecognized from the earliest interactions with text, is revealed. This article provides an overview of how the core deficits of individuals with ASD impact on the reading comprehension and academic success of older students.

Conclusion

Identification and intervention to address the underlying comprehension deficit has the potential to provide benefit in academic and personal pursuits of adolescent readers with ASD.
Distributed secondary voltage control for autonomous microgrids under additive measurement noises and time delays
Authors: Lai Jingang , Lu Xiaoqing , Monti Antonello
Published: May 2019

This study addresses the secondary voltage restoration problem of ac autonomous microgrids with additive measurement noises and time delays. Existing distributed control methods commonly assume ideal communication among distributed generators (DG), however, the channels are prone to additive noises (i.e. caused by environmental causes, such as rain etc.) and time delays, then each DG obtains noisy and delayed measurements of the states of its neighbouring DGs. The proposed distributed cooperative control strategy will achieve voltage restoration of DGs through a sparse communication network subject to noisy and delayed measurements. The theoretical concepts and necessary conditions for stability and robust performance of the proposed distributed secondary voltage control strategy are outlined by the graph theory, stochastic theory, and Lyapunov functional approach. Furthermore, the proposed control strategy is fully distributed and therefore the central controller is no longer required bringing about several advantages, e.g. plug‐and‐play property. Simulation results on an autonomous ac microgrid test system are obtained to evaluate the performance of the proposed control method to achieve voltage restoration in the MATLAB/SimPowerSystems Toolbox.
Miniaturised frequency selective surface based on fractal arrays with square slots for enhanced bandwidth
Authors: Anwar Rana Sadaf , Wei Yuan , Mao Lingfeng , Ning Huansheng
Published: May 2019

A novel approach is used to miniaturise the array size and broaden the bandwidth (BW) of a multilayer antenna‐filter antenna‐ based frequency selective surface (FSS). Although such FSSs have broadly been investigated for higher frequency selectivity and less thickness, they still own high periodicity and lower BW. The proposed fractal FSS with centre square slots consists of three metallic layers, separated by two dielectric substrates and periodicity of the unit cell is sub‐wavelength order (0.2λₒ). Central square slots are added in the external Minkowski fractal patches to increase the capacitive effect whereas fractal slots are etched on the ground placed in the middle for enhanced coupling. It is demonstrated through simulations that proposed design can effectively minimise the element size and enhance the BW. Owing to minuscule array size and symmetric fractal geometry, the presented structure is insensitive to higher incidence angles (up to 30°) for both polarisations. A prototype of the proposed FSS is also fabricated and tested in a microwave anechoic chamber. An equivalent circuit model, full wave simulation and measurement results agree well and demonstrate stable response with 3 dB fractional BW approaching 87.4 and 92%, respectively, at a normal angle of incidence.
Wide‐stopband and high selectivity step impedance resonator bandpass filter using T‐network and antiparallel coupled line
Authors: Kim Phirun , Chaudhary Girdhari , Jeong Yongchae
Published: May 2019

A wide‐stopband attenuation with high‐selectivity step impedance resonator (SIR) bandpass filter (BPF) is presented in this study. The T‐network stubs are used to produce transmission zeros (TZs) close to the centre frequency (f0) with a high‐selectivity. Moreover, the antiparallel coupled lines can produce a TZ at spurious frequency of conventional SIR BPF for all step impedance ratio (K). For the validation, a half‐wavelength (λ/2) SIR BPF with T‐network stubs at the input/output ports was designed at f0 of 2.6 GHz. From the experiment, the insertion and return losses at f0 were determined to be 0.91 and 21.25 dB, respectively. The insertion and return losses were better than 1.1 and 16.5 dB, respectively, of the 180 MHz bandwidth. The TZ frequencies (fZ1, fZ2, and fZ3) were located at 1.69 GHz (0.63f0), 2.98 GHz (1.12f0), and 3.17 GHz (1.19f0), respectively, with a high selectivity. The stopband attenuation was better than 25 dB from DC to 2.23 GHz and from 2.89 to 9.82 GHz.
Optimisation configuration of hybrid AC/DC microgrid containing electric vehicles based on the NSGA‐II algorithm
Authors: Ye Bin , Shi Xuemei , Wang Xuli , Wu Hongbin
Published: May 2019

Based on the development of hybrid AC/DC microgrid, considering the objectives of microgrid life‐cycle cost, self‐balancing rate and converter losses, an optimisation configuration model of a hybrid AC/DC microgrid is established here. Based on the different model of EVs to connect with grid, the matching control strategies for the model are proposed. The elitist non‐dominated sorting genetic algorithm (NSGA‐II) is applied to solve the optimisation configuration model. With the example system simulation, the demand response function of EVs is analysed, and the impacts of different EVs charging modes on optimisation configuration results of the hybrid AC/DC microgrid are studied and discussed. The rationality and effectiveness of proposed models and strategies are verified.
Abnormal behaviour analysis algorithm for electricity consumption based on density clustering
Authors: Xiang Min , Rao Huayang , Tan Tong , Wang Zaiqian , Ma Yue
Published: May 2019

How to effectively detect abnormal electricity consumption behaviour from a large‐scale electrical load data is very important to smart grid. An abnormal electricity consumption analysis method based on density clustering is proposed. First, the similar users located in fix area are clustered in accordance with the electricity consumption characteristics. Then, on the basis of electricity consumption data sequence, the outlier electricity consumption for the similar users are obtained with density clustering. The matching degrees of these outliers can be calculated based on the similar user electricity consumption model and historical electricity consumption model. Finally, according to the threshold value, the abnormal electricity consumption can be discriminated with the comprehensive support degree. The simulation results show that this method can effectively identify the abnormal electricity consumption behaviour.
Uniform attribute‐content model
Authors: Xiang Yingzhuo , Yan Jikun , You Ling , An Pu
Published: May 2019

There have been growing needs for text processing, such as classifying, retrieving and clustering. The foundation of such a process is to extract features, which can best describe the text. Great progress has been made in text modelling. However, most of the text modelling methods are based only on the content, nor only on the attributes. Although there have been some combined models proposed in recent years, the lack of universality limits such models. In this study, the authors propose a uniform attribute‐content model, which uses the attributes to influence the content feature extraction process. They design the attributes as a special filter to each feature extracted from the content. Thus the mixed features contain both content information and attribute information, which can describe the text more precise. They also propose a Monte Carlo method to solve this model. Experimental results on the Enron email dataset demonstrate the effectiveness of the authors’ proposed models.
Novel method to forecast software aging problems
Authors: Yan Yongquan
Published: May 2019

As software system becomes complex and large, some phenomena, performance degradation, error service, and even the abrupt system outage, have been found in the operating system, web server, and even in the security system. These phenomena can be called software ageing problems. In order to make software re‐enter into a robust state, some prediction methods need be used to find an optimal time to do rejuvenation. Since the prediction method used now is linear or non‐linear, a hybrid method is proposed in this work to improve the prediction accuracy. The proposed method contains three phases. Firstly, a linear method is applied to capture the linear characteristics of resource consumption series. Secondly, a non‐linear method is used to fit non‐linear features in the original data and residual data. Finally, the characteristic of the linear and non‐linear part will be fitted by a non‐linear model. In the experiments, the results show that the proposed method outperforms the other two single models.
Novel physical network algorithm for indirect measurement of polished rod load of beam‐pumping unit
Authors: Wang Ke , Gong Guoliang , Shen Rongxuan , Wang An , Yao Zhaolin , Mao Wenyu , Lu Huaxiang
Published: May 2019

A novel neural network algorithm for indirect measurement of the polished rod load of the beam‐pumping unit is proposed. The dynamometer card is a two‐dimension graph of polished rod load versus horse head position, and it is widely used for working state monitoring of pumping unit. The drift problem of load sensor makes the direct measurement of polished rod load not economical and practical, so indirect measurement of polished rod load is crucial. Through the analysis of the mechanical characteristics of the pumping unit, a neural network with physical meaning (physical network) is designed. The experiment shows that the physical network can simulate the energy transfer process properly with only 18 training data items, which is about 1% of other data‐driven models, and maintains good performance under different down‐hole conditions.
Reduction of common‐mode voltage using a simplified FSC‐MPC for a five‐phase induction motor drive
Authors: Guzman Hugo , Iqbal Atif , Barrero Federico
Published: May 2019

This paper presents a cascaded closed‐loop control of a five‐phase induction motor (IM) drive system with common‐mode voltage reduction capability. The outer loop uses standard PI regulators for speed reference tracking, while the inner control loop is implemented using a reduced order finite‐state model‐based current predictive approach. Establishing certain constraints, different combinations of switching state vectors are obtained, leading to the generation of different magnitudes of common‐mode voltages. As a result, precise speed and current control is achieved in addition to the reduction of common‐mode voltage and computational burden. Experimental results are presented to validate the concept.
Bi‐Signature optical spectroscopy for online fault detection in electrical machines
Authors: Alalibo Belema P. , Cao Wenping , Liu Zheng
Published: May 2019

A novel bi‐signature optical spectroscopy for fault detection in electrical machines is presented. The combined use of long period grating (LPG) and two fibre Bragg gratings (FBG1 and FBG2) is implemented to discriminate between vibration and temperature sensitivity in the detection of machine faults. With LPG having higher sensitivity to temperature compared to both FBGs, machine faults are detected through spectral analysis of both signatures; and the optimal detection signature for each fault is consequently analysed. This novel technique utilises the principle of a shift in the wavelengths of the gratings to determine the kind of fault present in an electrical machine as the signature spectroscopy reveals varying amount of Bragg wavelength shifts for various fault types. The use of FBG sensing for fault detection in electrical machines has the potential of revolutionising non‐intrusive real‐time condition monitoring of future industrial machines with high reliability due to zero electromagnetic interference (EMI) as well as significant low cost of fibre‐optic sensors.
Non‐invasive method for rotor bar fault diagnosis in three‐phase squirrel cage induction motor with advanced signal processing technique
Authors: Barusu Madhusudhana Reddy , Sethurajan Umamaheswari , Deivasigamani Meganathan
Published: May 2019

The condition monitoring of the rotor bar in the squirrel cage induction motors (SCIMs) is performed with various contact methods and non‐contact methods. The various contact methods are zero sequence current spectrum measurement, non‐uniform time resampling of current, motor current spectrum analysis, vibration measurement, etc. Non‐contact methods are infrared thermography, stray flux measurement, acoustic emission measurement, temperature measurement, etc. The contact methods execute via vibration, instantaneous frequency, rotor speed and flux signal analysis. Whereas, non‐contact method accomplishes via acoustic, current, temperature and stray flux measurement. The existing methods suffer from the influence of adjoining machines, surrounding environmental changes; require human expertise to mount sensors and analysing the signals. In this paper, a novel low‐cost and non‐invasive method proposed for rotor bar fault identification in SCIMs with Software Phase Locked Loop (SPLL). The proposed method uses a high‐frequency signal projected on the motor and the reflected signal captured. The captured signal analysed by Fast Fourier Transform (FFT) and Wavelet transforms to identify the fault. The performance of these transforms compared in term of accuracy to identify the rotor bar faults of SCIM. The experimental results show that the proposed method achieves better accuracy than the existing methods..