bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards efficient design optimization of a miniaturized thermoelectric generator for electrically active implants via model order reduction and submodeling technique
Authors: Yuan Chengdong , Kreß Stefanie , Sadashivaiah Gunasheela , Rudnyi Evgenii B. , Hohlfeld Dennis , Bechtold Tamara 
Published: January 2020

AbstractThermoelectric generators (TEG) convert the thermal energy into electrical energy and are under investigation as a power supply for medical implants. To improve the performance of TEG, the design optimization process through finite element model simulation is preferred by biomedical engineers. This paper aims to provide an efficient method of speeding up the design optimization process of TEG. A three‐dimensional realistic human torso model incorporating the TEG is investigated, where the internal heat transfer in human tissue is characterized by Pennes bioheat equation. In addition, convection, radiation, and evaporation effects at the skin surface are applied to identify the heat transfer effects between the human body and the environment. To speed up finite element simulation of the large‐scale human torso model, projection‐based model order reduction (MOR) is applied for generation of a compact but highly accurate model. Parametric MOR (pMOR) further enables generating a parameter‐independent compact model. For an efficient design optimization of TEG, this compact human torso model is applied within a thermal submodeling approach. Its temperature distribution results are back‐projected and used as boundary conditions for the TEG submodel. The achieved speed‐up in simulation time, demonstrated in this work, clearly indicates that the design optimization process of TEG is more efficient with the combination of MOR and submodeling techniques.
A Self‐Adjuvanting Vaccine Platform: Optimization of Site‐Specific Sortase A Mediated Conjugation of Toll‐Like Receptor 2 Ligands onto the Carboxyl or Amino terminus of Recombinant Protein Antigens
Authors: Xu Zhenghui , Moyle Peter Michael 
Published: January 2020

AbstractSelf‐adjuvanting vaccines, consisting of recombinant protein antigens and covalently attached Toll‐like receptor (TLR) agonists, have the ability to simultaneously and efficiently deliver antigen and TLR adjuvant to antigen presenting cells (APCs). Here, an enzyme‐mediated ligation approach was used to overcome difficulties in producing homogeneous, molecularly defined self‐adjuvanting vaccine products under native conditions. This process was optimized to allow the incorporation of the lipopeptide TLR2 agonist fibroblast‐stimulating lipopeptide (FSL)‐1 onto the N‐ or C‐termini of recombinant protein antigens, employing the enzyme Staphylococcus aureus sortase A (SrtAsa) penta mutant. In addition, because SrtAsa‐mediated ligations are reversible, a tryptophan zipper derived sequence was introduced into both reactants, which was demonstrated to improve ligation efficiency through the formation of a β‐hairpin structure that hinders the reverse reaction. Finally, it was demonstrated that N‐ or C‐terminal conjugation, and the incorporation of the β‐hairpin structure, did not affect the TLR2‐agonist activities of protein antigen TLR agonist conjugates. Overall, this SrtAsa‐mediated ligation platform enabled production of antigen TLR2 agonist conjugates with enhanced ligation efficiency, with the conjugates demonstrating potent TLR2 signaling activation (EC50<1nM).
Prediction of progression from pre‐diabetes to diabetes: Development and validation of a machine learning model
Authors: Cahn Avivit , Shoshan Avi , Sagiv Tal , Yesharim Rachel , Goshen Ran , Shalev Varda , Raz Itamar 
Published: January 2020

AbstractAimsIdentification, a priori, of those at high risk of progression from pre‐diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whether the use of a machine‐learning model can improve the prediction of incident diabetes utilizing patient data from electronic medical records.MethodsA machine‐learning model predicting the progression from pre‐diabetes to diabetes was developed using a gradient boosted trees model. The model was trained on data from The Health Improvement Network (THIN) database cohort, internally validated on THIN data not used for training, and externally validated on the Canadian AppleTree and the Israeli Maccabi Health Services (MHS) data sets. The model's predictive ability was compared with that of a logistic‐regression model within each data set.ResultsA cohort of 852 454 individuals with pre‐diabetes (glucose ≥ 100 mg/dL and/or HbA1c ≥ 5.7) was used for model training including 4.9 million time points using 900 features. The full model was eventually implemented using 69 variables, generated from 11 basic signals. The machine‐learning model demonstrated superiority over the logistic‐regression model, which was maintained at all sensitivity levels – comparing AUC [95% CI] between the models; in the THIN data set (0.865 [0.860,0.869] vs 0.778 [0.773,0.784] P < .05), the AppleTree data set (0.907 [0.896, 0.919] vs 0.880 [0.867, 0.894] P < .05) and the MHS data set (0.925 [0.923, 0.927] vs 0.876 [0.872, 0.879] P < .05).ConclusionsMachine‐learning models preserve their performance across populations in diabetes prediction, and can be integrated into large clinical systems, leading to judicious selection of persons for interventional programmes.
Transcriptomic regulation of seasonal coat color change in hares
Authors: Ferreira Mafalda S. , Alves Paulo C. , Callahan Colin M. , Giska Iwona , Farelo Liliana , Jenny Hannes , Mills L. Scott , Hackländer Klaus , Good Jeffrey M. , Melo‐Ferreira José 
Published: January 2020

AbstractColor molts from summer brown to winter white coats have evolved in several species to maintain camouflage year‐round in environments with seasonal snow. Despite the eco‐evolutionary relevance of this key phenological adaptation, its molecular regulation has only recently begun to be addressed. Here, we analyze skin transcription changes during the autumn molt of the mountain hare (Lepus timidus) and integrate the results with an established model of gene regulation across the spring molt of the closely related snowshoe hare (L. americanus). We quantified differences in gene expression among three stages of molt progression—“brown” (early molt), “intermediate,” and “white” (late molt). We found 632 differentially expressed genes, with a major pulse of expression early in the molt, followed by a milder one in late molt. The functional makeup of differentially expressed genes anchored the sampled molt stages to the developmental timeline of the hair growth cycle, associating anagen to early molt and the transition to catagen to late molt. The progression of color change was characterized by differential expression of genes involved in pigmentation, circadian, and behavioral regulation. We found significant overlap between differentially expressed genes across the seasonal molts of mountain and snowshoe hares, particularly at molt onset, suggesting conservatism of gene regulation across species and seasons. However, some discrepancies suggest seasonal differences in melanocyte differentiation and the integration of nutritional cues. Our established regulatory model of seasonal coat color molt provides an important mechanistic context to study the functional architecture and evolution of this crucial seasonal adaptation.
Efficacy and safety of sodium zirconium cyclosilicate for hyperkalaemia: the randomized, placebo‐controlled HARMONIZE‐Global study
Authors: Zannad Faiez , Hsu Bang‐Gee , Maeda Yoshitaka , Shin Sug Kyun , Vishneva Elena M. , Rensfeldt Martin , Eklund Stefan , Zhao June 
Published: January 2020

AbstractAimsSodium zirconium cyclosilicate (SZC, formerly ZS‐9) is a selective K+ binder to treat adults with hyperkalaemia. HARMONIZE‐Global examined the efficacy and safety of SZC among outpatients with hyperkalaemia from diverse geographic and ethnic origins.Methods and resultsThis phase 3, randomized, double‐blind, placebo‐controlled study recruited outpatients with serum K+ ≥5.1 mmol/L (measured by point‐of‐care i‐STAT device) at 45 sites in Japan, Russia, South Korea, and Taiwan. Following open‐label treatment with thrice‐daily SZC 10 g during a 48 h correction phase (CP), patients achieving normokalaemia (K+ 3.5–5.0 mmol/L) were randomized 2:2:1 to once‐daily SZC 5 g, SZC 10 g, or placebo during a 28 day maintenance phase (MP). The primary endpoint was mean central‐laboratory K+ level during days 8–29 of the MP. Of 267 patients in the CP, 248 (92.9%) entered the MP. During the CP, mean central‐laboratory K+ was reduced by 1.28 mmol/L at 48 h vs. baseline (P < 0.001). During the MP (days 8–29), SZC 5 and 10 g once‐daily significantly lowered mean central‐laboratory K+ by 9.6% and 17.7%, respectively, vs. placebo (P < 0.001 for both). More patients had normokalaemia (central‐laboratory K+ 3.5–5.0 mmol/L at day 29) with SZC 5 (58.6%) and 10 g (77.3%) vs. placebo (24.0%), with the greatest number of normokalaemic days in the 10‐g group. The most common adverse events with SZC were mild or moderate constipation and oedema.ConclusionsNormokalaemia achieved during the CP was maintained over 28 days with SZC treatment among outpatients with hyperkalaemia.
Misfire detection of homogeneous charge compression ignition engines using matter‐element extension theory and thermodynamic multi zone model
Authors: Asghari Mohsen , Saray Rahim Khoshbakhti , Neshat Elaheh 
Published: January 2020

AbstractNowadays, researchers tend to simulate and model the studied phenomena to reduce the calculation time and cost. Matter‐element extension model is a useful method that can be used to evaluate a wide range of data that belong to different subjects. In this study, this model is used to diagnose different engine's performance modes including misfire, normal, knock, and middle modes in which both of the mentioned modes are occurred simultaneously. To achieve this purpose, a set of performance and emission parameters acquired for a multi zonal model are chosen as input data to the model. Statistical analysis is done on a set of experimental data. First, ANOVA (analysis of variance) is used to determine parameters significant level. Then the proportional weights are given for the chosen parameters with respect to their importance. To do this, linear regression analysis is used for determination of weights. Two kinds of single objective and two objectives matter‐element extension models are employed to diagnose the engine's operation mode. The results show that both the single objective and two objectives models show a good conformity with the corresponding experimental results without acquiring empirical data. Single objective model can predict misfire, normal combustion, and knocking combustion. Meanwhile the two objectives model can predict the middle modes containing normal‐misfire, misfire‐knock, and knock‐normal accurately.
Exergoeconomic analysis and optimization of reverse osmosis desalination integrated with geothermal energy
Authors: Hoseinzadeh Siamak , Yargholi Roya , Kariman Hamed , Heyns P. Stephan 
Published: January 2020

AbstractIn this research, the integrated carbon dioxide power cycle with the geothermal energy source to supply the required reverse osmosis desalination power for freshwater production is defined. The cycling power is consumed by the desalination system and sodium hypochlorite generator. Exergoeconomic analysis, and optimization are studied. Exergoeconomic analysis is shown that the desalination system, sodium hypochlorite generator, carbon dioxide turbine, and natural gas turbine have the highest rate for the sum of capital gain and exergy destruction cost. For the first case of optimization, the total cost rate is considered as the objective function. The optimal inlet discharge rate of sodium hypochlorite generator was 62% of the brine water outlet discharge rate of the desalination system. Plus, the total cost rate is reduced by 10% compared to the general case when 100% of brine water discharge rate of the desalination system enters into the sodium hypochlorite generator. The second case is multiobjective optimization to reduce costs and increase productivity.
Clast transport history influences Schmidt hammer rebound values
Authors: Olsen Telemak , Borella Josh , Stahl Timothy 
Published: January 2020

AbstractThe Schmidt hammer (SH) is widely used in geomorphology for relative‐ and calibrated‐exposure age dating surfaces and deposits within landforms. This study employs a laboratory‐based methodology to assess the effects of surface roughness, clast roundness, and clast volume on SH rebound values (R‐values) by analyzing samples from three modern depositional environments (i.e. river, alluvial fan, talus). Each environment contains clasts of Torlesse supergroup greywacke sandstones with distinct roundness and micro‐scale roughness characteristics. Roundness, surface roughness, and clast volume were all found to influence R‐values significantly. The R‐values from different deposit types are statistically significant and could potentially create an apparent age divergence of several thousand years for samples with the same exposure‐age. © 2020 John Wiley & Sons, Ltd.
Bedrock erosion due to hoeing as tillage technique in a hilly agricultural landscape, southwest China
Authors: Xu Haichao , Zhang Jianhui , Wei Yuhang , Dai Jiadong , Wang Yong 
Published: January 2020

AbstractTillage on hillslopes may not only induce severe soil erosion, but may also cause bedrock erosion under certain conditions. Yet, little is known about bedrock erosion by tillage in a hilly agricultural landscape, southwest China. The aim of this study is to quantify the translocation of rock fragments derived from bedrock fragmentation by hoeing under different conditions, including slope gradient, hoeing depth and soil‐covered thickness using a gravel tracing method. The reliability of the gravel tracing method was confirmed by the bedrock dyeing tracing method. Hoeing depth is a significant factor affecting the translocation rate of rock fragments (Qr). Meanwhile, under the condition of overlying soil layers (0.06−0.10 m thick), the values of Qr were significantly smaller with a reduction of 20.7−25.6%, compared with rock fragmentation by hoeing for bare bedrock. However, slope gradient was found to have insignificant effects on Qr. Fractured bedrock moved as individual small fragments, which was mainly controlled by the hitting force of the hoe, while soil moved in the shape of lumps, which was dominated by both drag force of the hoe and gravity. This study suggests that hoeing into soil‐covered bedrock can diminish bedrock erosion while providing soil matrix for shallow soil layers. Our work presents a quantitative assessment of bedrock erosion by hoeing and an underlying insight into characteristics of bedrock erosion by tillage operations in hilly agricultural regions with mudstone and shale, southwest China. © 2020 John Wiley & Sons, Ltd.
A novel silicon graphite composite material with core‐shell structure as an anode for lithium‐ion batteries
Authors: Yin Ao , Yang Lezhi , Zhuang Zilong , Feng Qingge , Liu Zhikuan , Chen Tao , Tu Feiyue , Peng Qinjiao , Luo Lei , Tang Gang , Chen Wenqiang , Qin Shibiao , Wu Jianghua 
Published: January 2020

AbstractIn this work, a novel core‐shell structure consisting of a porous graphite core, a nanosilicon filler layer, and a pitch coating carbon shell has been developed for lithium‐ion battery anode material. This structure was prepared by liquid‐phase milling and carbonization processes. Compared with other silicon (Si)‐based anode materials, this structure has a unique three‐dimensional conductive network consisting of conductive materials of conductive carbon, graphene, porous graphite, and carbon shell. The conductive network could effectively enhance the conductivity of the core‐shell structure. In addition, this structure was designed with moderate porous rate that provided nanosilicon appropriate expansion space. The coin cell test showed that this new material has a reversible capacity of 400 mA h g−1, retention of above 95% after 40 cycles, an initial columbic efficiency of 83.04%, and an average coulombic efficiency of above 99%. This novel material could have a great potential for future commercial application. The structure designed could be a possible solution for Si anode materials with low manufacturing cost and high performance.
High‐intensity ultrasound applied on cured pork: Sensory and physicochemical characteristics
Authors: Contreras‐Lopez German , Carnero‐Hernandez Andrea , Huerta‐Jimenez Mariana , Alarcon‐Rojo Alma Delia , Garcia‐Galicia Ivan , Carrillo‐López L. M. 
Published: January 2020

AbstractThis research aimed to evaluate the physicochemical characteristics and their relationship with sensory properties of cured porcine m. longissimus lumborum assisted by high‐intensity ultrasound (HIU, 37 kHz, 22 Wcm−2). An experiment was designed with three factors at two levels each: type of curing (immersion or ultrasound‐assisted ‐UA‐), immersion time (30 or 90 min), and steak thickness (1.27 or 2.54 cm). After treatment and 7 days of storage at 4°C, the percentage of salt, pH, CIE L* a* b* color, water holding capacity (WHC), and shear force were determined in the samples. A quantitative descriptive analysis was performed using eight trained panelists. The HIU significantly increased the percentage of NaCl (p < .0005) and decreased the color saturation of the meat (p < .05), but did not affect the luminosity, redness (a*), yellowness (b*), pH, WHC, or shear force (all p > .05). The thickness of the steak had significant effects on almost all of the evaluated variables. Samples with 1.27 cm thickness had lower shear force, higher WHC and salt percentage (p < .0001). In agreement with this, the sensory profiles showed that the 1.27 cm samples treated with HIU for 30 min were perceived as less tough (more tender) and juicier.
Expression scoring of a small‐nucleolar‐RNA signature identified by machine learning serves as a prognostic predictor for head and neck cancer
Authors: Xing Lu , Zhang Xiaoqi , Zhang Xiaoqian , Tong Dongdong 
Published: January 2020

AbstractHead and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. Increasing evidence has demonstrated small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. The aim of this study was to identify a prognostic snoRNA signature of HNSCC. Survival‐related snoRNAs were screened by Cox regression analysis (univariate, least absolute shrinkage and selection operator, and multivariate). The predictive value was validated in different subgroups. The biological functions were explored by coexpression analysis and gene set enrichment analysis (GSEA). One hundred and thirteen survival‐related snoRNAs were identified, and a five‐snoRNA signature predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different sexes, ages, stages, grades, and anatomic subdivisions. Coexpression analysis and GSEA revealed the five‐snoRNA are involved in regulating malignant phenotype and DNA/RNA editing. This five‐snoRNA signature is not only a promising predictor of prognosis and survival but also a potential biomarker for patient stratification management.
A novel method to diagnose the infection of enterovirus A71 in children by detecting IgA from saliva
Authors: Wang Changbing , Chen Yi , Xu Tiantian , Tian Xingui , Zheng Jianbin , Liu Wenkuan , Xia Yu , Li Yinghua , Zhu Bing , Zhou Rong 
Published: January 2020

AbstractEnterovirus A71 (EV‐A71) is one of the main pathogens causing hand, foot, and mouth disease, and often causes diseases of the central nervous system. Early diagnosis is important to prevent EV‐A71 outbreaks. The detection of serum immunoglobulin M (IgM) is widely used for the early diagnosis of EV‐A71 in clinics, especially in rural areas. However, this technique requires the extraction of blood from children who have thin blood vessels and who might fear the use of needles. Therefore, difficulties in the detection process are often encountered. This study developed a noninvasive method to detect EV‐A71‐specific immunoglobulin A (IgA) in saliva for the diagnosis of EV‐A71 infection. The sensitivity and specificity of IgA detection did not differ significantly compared with IgM detection. IgA antibodies were present in saliva for a relatively shorter period than IgM antibodies were present in serum. The sensitivity of IgA detection was higher than that of IgM detection for secondary EV‐A71 infections. These results suggest that the detection of EV‐A71‐specific IgA in the saliva allows the effective early diagnosis of EV‐A71 and may be suitable for detecting EV‐A71 infections in children.
Corrosion of hot‐dip‐galvanised steel and zinc alloy‐coated steel in ammonia and ammonium chloride
Authors: Thierry Dominique , Le Bozec Nathalie , Persson Dan 
Published: January 2020

AbstractThere are many potential causes of corrosion in animal buildings. Animals exhale large quantities of moisture into the air creating high relative humidity in the building if the moisture is not properly vented. High humidity increases the potential for condensation. In addition, ammonia may be found in large quantities in animal buildings. Ammonia is released from manure and urine. In addition, ammonium chloride is used as a nitrogen source in fertilisers. In this study, the atmospheric corrosion of hot‐dip‐galvanised steel and zinc alloy‐coated steel such as zinc–aluminium and zinc–aluminium–magnesium has been studied in atmospheres containing different levels of ammonia. Investigations have also been conducted at different levels of ammonium chloride. The results are discussed in view of the mechanisms of corrosion of zinc and zinc alloy‐coated steel in ammonia and ammonium chloride‐containing environments.
An evaluation of Acacia mearnsii tannin as an aluminum corrosion inhibitor in acid, alkaline, and neutral media
Authors: Rodrigues Silvia R. S. , Dalmoro Viviane , dos Santos João H. Z. 
Published: January 2020

AbstractThe electrochemical behavior of aluminum in tannin from Acacia mearnsii bark was evaluated by potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) in media under three different pH conditions: acid, alkaline, and neutral. A relationship among pH, polymerization grade (PG), zeta potential, surface, and electrochemical properties was observed in the inhibition performance of the tannin. At high pH, the oligomer structure of the tannin was affected, resulting in a low PG (4) and high zeta potential (−75 mV), and consequently, the inhibition efficiency decreased (68%) in comparison with that in acid (99%) and neutral media (96%). The values obtained indicate a physisorption mechanism for the aluminum corrosion inhibition in the studied conditions.