bluuebunny/crossref_metadata_2025 huggingface dataset:
Pedagogical introduction to the Sachdev–Ye–Kitaev model and two-dimensional dilaton gravity
Authors: Trunin D A
Published: July 2020

The Sachdev–Ye–Kitaev model and two-dimensional dilaton gravity have recently been attracting increasing attention of the high-energy and condensed-matter physics communities. The success of these models is due to their remarkable properties. Following the original papers, we broadly discuss the properties of these models, including the diagram technique in the limit of a large number of degrees of freedom, the emergence of conformal symmetry in the infrared limit, effective action, four-point functions, and chaos. We also briefly discuss some recent results in this field. On the one hand, we attempt to be maximally rigorous, which means considering all the details and gaps in the argument; on the other hand, we believe that this review can be suitable for those who are not familiar with the relevant models.
A Content Hiding Method for Digital Hologram Using Multiple Fresnel Diffraction
Authors: Seo Young-Ho , Lee Yoon-Hyuk , Kim Dong-Wook
Published: July 2020

A digital hologram (DH) is so highly valued that it needs to be protected from exposure to an unpermitted person, which could be done by a content encryption. We propose an encryption scheme for digital holograms, whose goal is to hide their information with maximal visual distortion and minimal ration of the encrypted data. It uses the characteristics of the Fresnel transform and signal processing techniques. As the diffraction distance increases the region containing the object information relative to the whole diffraction plane becomes smaller. Therefore our scheme diffracts a given digital hologram twice: the first transform for reconstructing the image contained by the hologram and the second transform for concentrating the energy of the object into a small region. Then only the energy-concentrated region is encrypted to reduce the amount of data to be encrypted. Experimental results show that when the diffraction distance of the second transform is about 20 m, the encryption ratio is only 0.0058% of the hologram data, which is enough to hide the object information unrecognizably.
Effects of Vitamin Forms and Levels on Vitamin Bioavailability and Growth Performance in Piglets
Authors: Yang Pan , Zhao Jinbiao , Wang Huakai , Li Longxian , Ma Yongxi
Published: July 2020

The objective of this study was to quantify the relative bioavailability of microencapsulated vitamins A and E in nursery pigs and compare the effects of vitamin forms and vitamin levels on the plasma vitamin content and growth performance of weaned piglets. In experiment (Exp.) 1, 12 nursery pigs (fitted with jugular catheters) were supplied at 0 h with non-microencapsulated or microencapsulated vitamin A and E. Blood samples were collected at 1, 3, 6, 9, 12, 16, 18, 21, 24, 27, 30, 36, 48, and 72 h after feeding to compare the bioavailability of oral vitamins A and E. In Exp. 2, a total of 216 crossbred weaned piglets were assigned to six treatments. This experiment was a 2 × 3 factorial arrangement, with two factors for vitamin forms (non-microencapsulated and microencapsulated) and three factors for vitamin levels (the National Research Council level of vitamins, 75% commercial recommendations of vitamins (CRV) level, and a 100% CVR level). In Exp. 1, the relative bioavailability of microencapsulated vitamin E was significantly greater than that of non-microencapsulated vitamin E. In Exp. 2, the pigs fed diets containing 75% or 100% CRV levels of vitamins increased their growth performance and plasma vitamin concentrations compared to the control group. In conclusion, microencapsulation can improve the bioavailability of vitamins, and supplementation with high levels of vitamins was able to improve the growth performance of the piglets.
Investigation of Molecular Size Effect on the Formation of Lignin Nanoparticles by Nanoprecipitation
Authors: Lee Jae Hoon , Park Shin Young , Choi In-Gyu , Choi Joon Weon
Published: July 2020

In recent years, several studies focused on the synthesis of lignin-based nanoparticle in aqueous solution and its potential applications of the drug carrier were investigated. In this study, soda lignin (SL) nanoparticles (i.d. 128–560 nm) were synthesized by the nanoprecipitation process at three different concentrations (1, 2, and 4 mg/mL THF) with various molecular sizes of soda lignin (NP-F1, NP-F2, and NP-F3) obtained from sequential solvent extraction. The average molecular weights of SL, F1, F2, F3, F4, and F5 were 3130, 1190, 2550, 3680, 5310, and 14,650, respectively. The average size of the spherical lignin nanoparticle was a minimum of 128 nm for NP-C1 and the size increased up to 560 nm with increasing concentration. Particle surface charge increased with increasing concentration from −26 mV for NP-C1 to −38 mV for NP-C4. Contrary to expected general trends in polymeric nanoparticles, there was no remarkable change or trend with increasing lignin molecular weight since chemical structures of each lignin fraction are also remarkably different. Further studies to learn correlation between properties of lignin nanoparticle and its additional details regarding the chemical structures is needed.
Inactivated Platelet Lysate Supports the Proliferation and Immunomodulant Characteristics of Mesenchymal Stromal Cells in GMP Culture Conditions
Authors: Mareschi Katia , Castiglia Sara , Adamini Aloe , Rustichelli Deborah , Marini Elena , Banche Niclot Alessia Giovanna Santa , Bergallo Massimiliano , Labanca Luciana , Ferrero Ivana , Fagioli Franca
Published: July 2020

Mesenchymal stromal cells (MSCs) isolated from bone marrow (BM-MSCs) are considered advanced therapy medicinal products (ATMPs) and need to be produced according to good manufacturing practice (GMP) in their clinical use. Human platelet lysate (HPL) is a good GMP-compliant alternative to animal serum, and we have demonstrated that after pathogen inactivation with psoralen, it was safer and more efficient to use psoralen in the production of MSCs following GMP guidelines. In this study, the MSCs cultivated in fetal bovine serum (FBS-MSC) or inactivated HPL (iHPL-MSC) were compared for their immunomodulatory properties. We studied the effects of MSCs on (1) the proliferation of total lymphocytes (Ly) and on naïve T Ly subsets induced to differentiate in Th1 versus Th2 Ly; (2) the immunophenotype of different T-cell subsets; (3) and the cytokine release to verify Th1, Th2, and Th17 polarization. These were analyzed by using an in vitro co-culture system. We observed that iHPL-MSCs showed the same immunomodulatory properties observed in the FBS-MSC co-cultures. Furthermore, a more efficient effect on the increase of naïve T- cells and in the Th1 cytokine release from iHPL was observed. This study confirms that iHPL, used as a medium supplement, may be considered a good alternative to FBS for a GMP-compliant MSC expansion, and also to preserve their immunomodulatory proprieties.
HDX-MS: An Analytical Tool to Capture Protein Motion in Action
Authors: Narang Dominic , Lento Cristina , J. Wilson Derek
Published: July 2020

Virtually all protein functions in the cell, including pathogenic processes, require coordinated motion of atoms or domains, i.e., conformational dynamics. Understanding protein dynamics is therefore critical both for drug development and to learn about the underlying molecular causes of many diseases. Hydrogen–Deuterium Exchange Mass Spectrometry (HDX-MS) provides valuable information about protein dynamics, which is highly complementary to the static picture provided by conventional high-resolution structural tools (i.e., X-ray crystallography and structural NMR). The amount of protein required to carry out HDX-MS experiments is a fraction of the amount required by alternative biophysical techniques, which are also usually lower resolution. Use of HDX-MS is growing quickly both in industry and academia, and it has been successfully used in numerous drug and vaccine development efforts, with important roles in understanding allosteric effects and mapping binding sites.
Evaluation of Two Resin Composites Having Different Matrix Compositions
Authors: Elshazly Tarek M. , Bourauel Christoph , Sherief Dalia I. , El-Korashy Dalia I.
Published: July 2020

This study compared two resin composites with similar filler systems and different matrix compositions. The depth of cure (DoC), polymerization shrinkage, and marginal leakage were evaluated. A Filtek Bulk Fill resin composite (FB) and a Filtek Supreme resin composite (FS) were used. For the DoC and polymerization shrinkage, cylindrical specimens with different thicknesses were prepared. The DoC was attributed to the bottom/top ratios of Vickers microhardness numbers. For polymerization shrinkage, each specimen was firstly scanned using micro-computed tomography (µCT) then cured for 20 s, then for 10 s, and then for 10 s, and they were rescanned between each curing time. Data were processed using the Mimics software. For marginal leakage, standardized 5 mm cavities were prepared in 90 molars. After etching and bonding, materials were packed according to groups: FB-bulk, FB-incremental, and FS-incremental, which were cured for 20, 30, and 40 s, respectively. After thermo-cycling, teeth were stored in 1% methylene blue dye for 24 h and then sectioned and observed for dye penetration. The results showed insignificant differences in the shrinkage and leakage between the different packing techniques and curing times of both materials. In conclusion, the introduction of a novel matrix into resin composite composition enabled bulk-filling in one layer up to 5 mm deep while keeping a tolerable polymerization shrinkage.
A Novel Image-Encryption Scheme Based on a Non-Linear Cross-Coupled Hyperchaotic System with the Dynamic Correlation of Plaintext Pixels
Authors: Hou Wenjin , Li Shouliang , He Jiapeng , Ma Yide
Published: July 2020

Based on a logistic map and Feigenbaum map, we proposed a logistic Feigenbaum non-linear cross-coupled hyperchaotic map (LF-NCHM) model. Experimental verification showed that the system is a hyperchaotic system. Compared with the existing cross-coupled mapping, LF-NCHM demonstrated a wider hyperchaotic range, better ergodicity and richer dynamic behavior. A hyperchaotic sequence with the same number of image pixels was generated by LF-NCHM, and a novel image-encryption algorithm with permutation that is dynamically related to plaintext pixels was proposed. In the scrambling stage, the position of the first scrambled pixel was related to the sum of the plaintext pixel values, and the positions of the remaining scrambled pixels were related to the pixel values after the previous scrambling. The scrambling operation also had a certain diffusion effect. In the diffusion phase, using the same chaotic sequence as in the scrambling stage increased the usage rate of the hyperchaotic sequence and improved the calculation efficiency of the algorithm. A large number of experimental simulations and cryptanalyses were performed, and the results proved that the algorithm had outstanding security and extremely high encryption efficiency. In addition, LF-NCHM could effectively resist statistical analysis attacks, differential attacks and chosen-plaintext attacks.
Discrete Information Dynamics with Confidence via the Computational Mechanics Bootstrap: Confidence Sets and Significance Tests for Information-Dynamic Measures
Authors: Darmon David
Published: July 2020

Information dynamics and computational mechanics provide a suite of measures for assessing the information- and computation-theoretic properties of complex systems in the absence of mechanistic models. However, both approaches lack a core set of inferential tools needed to make them more broadly useful for analyzing real-world systems, namely reliable methods for constructing confidence sets and hypothesis tests for their underlying measures. We develop the computational mechanics bootstrap, a bootstrap method for constructing confidence sets and significance tests for information-dynamic measures via confidence distributions using estimates of ϵ -machines inferred via the Causal State Splitting Reconstruction (CSSR) algorithm. Via Monte Carlo simulation, we compare the inferential properties of the computational mechanics bootstrap to a Markov model bootstrap. The computational mechanics bootstrap is shown to have desirable inferential properties for a collection of model systems and generally outperforms the Markov model bootstrap. Finally, we perform an in silico experiment to assess the computational mechanics bootstrap’s performance on a corpus of ϵ -machines derived from the activity patterns of fifteen-thousand Twitter users.
Context Aware Video Caption Generation with Consecutive Differentiable Neural Computer
Authors: Kim Jonghong , Choi Inchul , Lee Minho
Published: July 2020

Recent video captioning models aim at describing all events in a long video. However, their event descriptions do not fully exploit the contextual information included in a video because they lack the ability to remember information changes over time. To address this problem, we propose a novel context-aware video captioning model that generates natural language descriptions based on the improved video context understanding. We introduce an external memory, differential neural computer (DNC), to improve video context understanding. DNC naturally learns to use its internal memory for context understanding and also provides contents of its memory as an output for additional connection. By sequentially connecting DNC-based caption models (DNC augmented LSTM) through this memory information, our consecutively connected DNC architecture can understand the context in a video without explicitly searching for event-wise correlation. Our consecutive DNC is sequentially trained with its language model (LSTM) for each video clip to generate context-aware captions with superior quality. In experiments, we demonstrate that our model provides more natural and coherent captions which reflect previous contextual information. Our model also shows superior quantitative performance on video captioning in terms of BLEU (BLEU@4 4.37), METEOR (9.57), and CIDEr-D (28.08).
Design and Implementation of a Dual-Input Single-Output Photovoltaic Converter
Authors: Kabalci Ersan , Kabalci Yasin , Guerrero Josep M.
Published: July 2020

In many solar inverters, a dc/dc converter is mainly located between the solar arrays and the inverter. This study presents an enhanced maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems that drives solar array voltages to track a reference value and decreases fluctuations and oscillations in PV voltage. Different from the previously presented methods, a novel MPPT method is proposed that ensures tracking accuracy by considering output voltage in addition to input voltage and currents. The proposed method detects d I / d V variations, compares the output voltage with the desired reference to shift operation mode and refreshes step size. The digital filtering, enhanced PI, and perturb-and-observe (P&O) tracking features of the proposed MPPT method make it robust to mitigate source fluctuations and sensitivity to partial shading based oscillations. In order to validate the success of the proposed method, a test rig has been installed with dual boost converters. The performance improvements have been verified by both simulation and experimental results that are compared to InCon and P&O MPPT methods. It is also confirmed by experimental results that the proposed MPPT method provides robust control capability in terms of tracking the reference voltage and rejecting the effects of various shading situations on solar arrays.
A Hybrid Optimization Approach for Autonomy Enhancement of Nearly-Zero-Energy Buildings Based on Battery Performance and Artificial Neural Networks
Authors: Georgiou Giorgos S. , Nikolaidis Pavlos , Kalogirou Soteris A. , Christodoulides Paul
Published: July 2020

Reducing the primary energy consumption in buildings and simultaneously increasing self-consumption from renewable energy sources in nearly-zero-energy buildings, as per the 2010/31/EU directive, is crucial nowadays. This work solved the problem of nearly zeroing the net grid electrical energy in buildings in real time. This target was achieved using linear programming (LP)—a convex optimization technique leading to global solutions—to optimally decide the daily charging or discharging (dispatch) of the energy storage in an adaptive manner, in real time, and hence control and minimize both the import and export grid energies. LP was assisted by equally powerful methods, such as artificial neural networks (ANN) for forecasting the building’s load demand and photovoltaic (PV) on a 24 hour basis, and genetic algorithm (GA)—a heuristic optimization technique—for driving the optimum dispatch. Moreover, to address the non-linear nature of the battery and model the energy dispatch in a more realistic manner, the proven freeware system advisor model (SAM) of National Renewable Energy Laboratory (NREL) was integrated with the proposed approach to give the final dispatch. Assessing the case of a building, the results showed that the annual hourly profile of the import and export energies was smoothed and flattened, as compared to the cases without storage and/or using a conventional controller. With the proposed approach, the annual aggregated grid usage was reduced by 53% and the building’s annual energy needs were covered by the renewable energy system at a rate of 60%. It was therefore concluded that the proposed hybrid methodology can provide a tool to maximize the autonomy of nearly-zero-energy buildings and bring them a step closer to implementation.
Comparison of Machine Learning Classifiers for Accurate Prediction of Real-Time Stuck Pipe Incidents
Authors: Khan Javed Akbar , Irfan Muhammad , Irawan Sonny , Yao Fong Kam , Abdul Rahaman Md Shokor , Shahari Ahmad Radzi , Glowacz Adam , Zeb Nazia
Published: July 2020

Stuck pipe incidents are one of the contributors to non-productive time (NPT), where they can result in a higher well cost. This research investigates the feasibility of applying machine learning to predict events of stuck pipes during drilling operations in petroleum fields. The predictive model aims to predict the occurrence of stuck pipes so that relevant drilling operation personnel are warned to enact a mitigation plan to prevent stuck pipes. Two machine learning methodologies were studied in this research, namely, the artificial neural network (ANN) and support vector machine (SVM). A total of 268 data sets were successfully collected through data extraction for the well drilling operation. The data also consist of the parameters with which the stuck pipes occurred during the drilling operations. These drilling parameters include information such as the properties of the drilling fluid, bottom-hole assembly (BHA) specification, state of the bore-hole and operating conditions. The R programming software was used to construct both the ANN and SVM machine learning models. The prediction performance of the machine learning models was evaluated in terms of accuracy, sensitivity and specificity. Sensitivity analysis was conducted on these two machine learning models. For the ANN, two activation functions—namely, the logistic activation function and hyperbolic tangent activation function—were tested. Additionally, all the possible combinations of network structures, from [19, 1, 1, 1, 1] to [19, 10, 10, 10, 1], were tested for each activation function. For the SVM, three kernel functions—namely, linear, Radial Basis Function (RBF) and polynomial—were tested. Apart from that, SVM hyper-parameters such as the regularization factor (C), sigma (σ) and degree (D) were used in sensitivity analysis as well. The results from the sensitivity analysis demonstrate that the best ANN model managed to achieve an 88.89% accuracy, 91.89% sensitivity and 86.36% specificity, whereas the best SVM model managed to achieve an 83.95% accuracy, 86.49% sensitivity and 81.82% specificity. Upon comparison, the ANN model is the better machine learning model in this study because its accuracy, sensitivity and specificity are consistently higher than those of the best SVM model. In conclusion, judging from the promising prediction accurateness as demonstrated in the results of this study, it is suggested that stuck pipe prediction using machine learning is indeed practical.
Production of Hydrogen-Rich Gas by Oxidative Steam Reforming of Dimethoxymethane over CuO-CeO2/γ-Al2O3 Catalyst
Authors: Badmaev Sukhe , Sobyanin Vladimir
Published: July 2020

The catalytic properties of CuO-CeO2 supported on alumina for the oxidative steam reforming (OSR) of dimethoxymethane (DMM) to hydrogen-rich gas in a tubular fixed bed reactor were studied. The CuO-CeO2/γ-Al2O3 catalyst provided complete DMM conversion and hydrogen productivity > 10 L h−1 gcat−1 at 280 °C, GHSV (gas hourly space velocity) = 15,000 h−1 and DMM:O2:H2O:N2 = 10:2.5:40:47.5 vol.%. Comparative studies showed that DMM OSR exceeded DMM steam reforming (SR) and DMM partial oxidation (PO) in terms of hydrogen productivity. Thus, the outcomes of lab-scale catalytic experiments show high promise of DMM oxidative steam reforming to produce hydrogen-rich gas for fuel cell feeding.
Comparison of Two Ensemble Kalman-Based Methods for Estimating Aquifer Parameters from Virtual 2-D Hydraulic and Tracer Tomographic Tests
Authors: Sánchez-León Emilio , Erdal Daniel , Leven Carsten , Cirpka Olaf A.
Published: July 2020

We compare two ensemble Kalman-based methods to estimate the hydraulic conductivity field of an aquifer from data of hydraulic and tracer tomographic experiments: (i) the Ensemble Kalman Filter (EnKF) and (ii) the Kalman Ensemble Generator (KEG). We generated synthetic drawdown and tracer data by simulating two pumping tests, each followed by a tracer test. Parameter updating with the EnKF is performed using the full transient signal. For hydraulic data, we use the standard update scheme of the EnKF with damping, whereas for concentration data, we apply a restart scheme, in which solute transport is resimulated from time zero to the next measurement time after each parameter update. In the KEG, we iteratively assimilate all observations simultaneously, here inverting steady-state heads and mean tracer arrival times. The inversion with the dampened EnKF worked well for the transient pumping-tests, but less for the tracer tests. The KEG produced similar estimates of hydraulic conductivity but at significantly lower costs. We conclude that parameter estimation in well-defined hydraulic tests can be done very efficiently by iterative ensemble Kalman methods, and ambiguity between state and parameter updates can be completely avoided by assimilating temporal moments of concentration data rather than the time series themselves.
Relationship between the Number of Noncommunicable Diseases and Health-Related Quality of Life in Chinese Older Adults: A Cross-Sectional Survey
Authors: Liu Jianjian , Yu Wei , Zhou Jiayi , Yang Yifan , Chen Shuoni , Wu Shaotang
Published: July 2020

China has the largest population of older adults, most of whom suffer from one or more noncommunicable diseases (NCDs). The harm of the number of NCDs on the health-related quality of life (HRQOL) of older adults should be taken seriously. A sample of 5166 adults, aged 60 years and older, was included in this study. The Chinese version of the World Health Organization Quality of Life-Old (WHOQOL-OLD) instrument was used to assess the HRQOL. Multiple linear regression models were established to determine the relationship between the number of NCDs and the total score and scores of each dimension of the WHOQOL-OLD scale. After adjusting for confounding factors, suffering from one NCD (B = −0.87, 95% CI = −1.67 to −0.08, p < 0.05), two NCDs (B = −2.89, 95% CI = −3.87 to −1.90, p < 0.001), and three or more NCDs (B = −4.20, 95% CI = −5.36 to −3.05, p < 0.001), all had negative impacts on the HRQOL of older adults. NCDs had significant negative impacts on the HRQOL of older adults, and as the number of NCDs increased, the HRQOL of older adults deteriorated. Therefore, we should pay attention to the prevention and management of NCDs of older adults to prevent the occurrence of multiple NCDs.
An Exploration of Contextual Aspects that Influence Cardiovascular Disease Risks Perceived by Workers in a Small–Medium-Sized Workplace
Authors: Kim Jin Ah , Hwang Won Ju , Jin Juhye
Published: July 2020

Contextual factors are associated with risks of cardiovascular disease (CVD) perceived by personnel employed in small–medium-sized workplaces. In an ecological model, data collection and analysis were undertaken, stratified by intrapersonal, interpersonal, and organizational contexts of blue-collar workers. Data were collected in face-to-face (n = 36) and focus group (n = 4) interviews and subjected to qualitative content analysis, to generate three main themes, 10 generic categories and 18 sub-categories. At the intrapersonal level, “physical burden”, “burn out due to overtime work”, “no time to take care of health because of family responsibility”, and “lack of recognition and knowledge of CVD risks” were derived from the individual interviews. At the interpersonal level, “stress of possible job losses”, “dislike of stigmatization of unhealthy persons”, “smoking and drinking to reduce relationship stress”, and “unhealthy work environment” differed by level of risk perception. “Preferred economic value” and “lack of understanding about importance of CVD management of an employer” emerged at the organizational level. Factors that influence CVD risks among workers in small–medium-sized business were present at the multiple levels. Therefore, healthcare providers in the field of occupational health should consider CVD risks in the context of blue-collar workers and organizational level for health-promotion programs.
The Contrasting Effects of an Action Video Game on Visuo-Spatial Processing and Proactive Cognitive Control
Authors: West Robert , Swing Edward L. , Anderson Craig A. , Prot Sara
Published: July 2020

First person shooter or action video games represent one of the most popular genres within the gaming industry. Studies reveal that action gaming experience leads to enhancements of visuo-spatial processing. In contrast, some correlational evidence reveals that experience with action video games may be associated with reduced proactive cognitive control. The two primary goals of the current study were to test the causal nature of the effect of action gaming on proactive cognitive control and to examine whether an increase in visuo-spatial processing and a decrease in proactive cognitive control arise from the same amount of experience playing an action video game. Participants completed tasks measuring visuo-spatial processing and cognitive control before and after 10 practice sessions involving one of three video games or were assigned to a no gaming experience control group. The data revealed the typical increase in visuo-spatial processing and a decrease in proactive, but not reactive, cognitive control following action game training. The sizes of these two training effects were similar in magnitude, but interpretation of the effects was constrained by baseline differences between the four groups of subjects. The possibility of a causal effect of action gaming on proactive cognitive control is interesting within the context of correlational evidence linking greater action gaming experience to reduced cognitive control, poor decision making, and increased impulsivity.
Enhanced N2O Production Induced by Soil Salinity at a Specific Range
Authors: Li Yawei , Xu Junzeng , Liu Boyi , Wang Haiyu , Qi Zhiming , Wei Qi , Liao Linxian , Liu Shimeng
Published: July 2020

Nitrous oxide (N2O) as a by-product of soil nitrogen (N) cylces, its production may be affected by soil salinity which have been proved to have significant negative effect on soil N transformation processes. The response of N2O production across a range of different soil salinities is poorly documented; accordingly, we conducted a laboratory incubation experiment using an array of soils bearing six different salinity levels ranging from 0.25 to 6.17 dS m−1. With ammonium-rich organic fertilizer as their N source, the soils were incubated at three soil moisture ( θ ) levels—50%, 75% and 100% of field capacity ( θ fc )—for six weeks. Both N2O fluxes and concentrations of ammonium, nitrite and nitrate (NH4+-N, NO2−-N and NO3−-N) were measured throughout the incubation period. The rates of NH4+-N consumption and NO3−-N accumulation increased with increasing soil moisture and decreased with increasing soil salinity, while the accumulation of NO2−-N increased first then decreased with increasing soil salinity. N2O emissions were significantly promoted by greater soil moisture. As soil salinity increased from 0.25 to 6.17 dS m−1, N2O emissions from soil first increased then decreased at all three soil moisture levels, with N2O emissions peaking at electric conductivity (EC) values of 1.01 and 2.02 dS m−1. N2O emissions form saline soil were found significantly positively correlated to soil NO2−-N accumulation. The present results suggest that greater soil salinity inhibits both steps of nitrification, but that its inhibition of nitrite oxidation is stronger than that on ammonia oxidation, which leads to higher NO2−-N accumulation and enhanced N2O emissions in soil with a specific salinity range.
Occupational Exposure to Pesticides and Chronic Lymphocytic Leukaemia in the MCC-Spain Study
Authors: Benavente Yolanda , Costas Laura , Rodríguez-Suarez Marta Maria , Alguacil Juan , Santibáñez Miguel , Vila Javier , Robles Claudia , Alonso Esther , de la Banda Esmeralda , Gonzalez-Barca Eva , Dierssen-Sotos Trinidad , Gimeno Vazquez Eva , Aymerich Marta , Campo Elias , Jiménez-Moleón José J. , Marcos-Gragera Rafael , Castaño-Vinyals Gemma , Aragonés Nuria , Pollan Marina , de Sanjose Silvia , Kogevinas Manolis , Tardón Adonina , Casabonne Delphine
Published: July 2020

We aimed to study the association between occupational exposure to pesticides and chronic lymphocytic leukemia (CLL) in Spain. Occupational exposure to pesticides (four insecticides, four herbicides and two fungicides) was evaluated using a job-exposure matrix for the Spanish population (MatEmESp) among 302 CLL cases and 1567 population controls in five regions of Spain, 2010–2013. Cumulative exposure scores (CES) were obtained by summing across the exposed jobs the product of prevalence, intensity and duration of exposure to each active substance. Principal components analysis (PCA) and logistic regression models adjusted for age, sex, region, education and occupational exposure to solvents were used. Around 20% of controls and 29% of cases were exposed to one or more pesticides. Compared to non-exposed, subjects in the highest tertile (3rd tertile) of CES of insecticides, herbicides, fungicides were more likely to have CLL [OR (95% CI), P-trend; 2.10 (1.38; 3.19), 0.002; 1.77 (1.12; 2.80), 0.12; and 1.67 (1.06; 2.64), 0.10, respectively). Following PCA, the first component (PC1, explaining 70% of the variation) equally led by seven active substances (the insecticide pyrethrin, all herbicides, all fungicides) was associated with a 26% higher odds of having CLL for 1-standard deviation increase in PC1 (95% CI: 1.14 to 1.40). These results confirm previous associations between CLL and exposure to pesticides and provide additional evidence by application groups and active substance. However, more research is needed to disentangle independent effects of individual active substances.
Is There a Link between Different Types of Alcoholic Drinks and Obesity? An Analysis of 280,183 UK Biobank Participants
Authors: Inan-Eroglu Elif , Powell Lauren , Hamer Mark , O'Donovan Gary , Duncan Mitch J. , Stamatakis Emmanuel
Published: July 2020

Understanding the associations between types of alcoholic drinks and adiposity has public health relevance, considering that adult overweight and obesity prevalence are increasing worldwide. We aimed to evaluate the association between overall alcohol consumption and types of alcohol drinks with markers of adiposity from the UK Biobank baseline data (n = 280,183, 48.3% female). Generalized linear models were used to examine the associations between alcohol consumption with body mass index (BMI) and body fat percentage. Those drinking within the public health guidelines had a lower BMI by 1.34 kg/m2 (95% CI 1.42, 1.26 kg/m2) compared to never drinkers. Association between alcohol consumption and body fat percentage were not statistically significant. Compared to those who never drink wines (red wine, champagne and fortified wine), drinkers of these alcoholic beverages had lower BMI (difference of −0.75 kg/m2, 95% CI −0.78, −0.72 kg/m2; −0.48 kg/m2, 95% CI −0.52, −0.45 kg/m2; and −0.24 kg/m2, 95% CI −0.29, −0.18 kg/m2, respectively). Beer and spirits drinkers had higher BMI compared to never drinkers of beer and spirits (difference of 0.18 kg/m2, 95% CI 0.14, 0.22 kg/m2 and 0.64 kg/m2, 95% CI 0.61, 0.68 kg/m2, respectively). Our data did not find a link between alcohol drinking and higher risk of obesity.
Mining Evolution Patterns from Complex Trajectory Structures—A Case Study of Mesoscale Eddies in the South China Sea
Authors: Wang Huimeng , Du Yunyan , Yi Jiawei , Wang Nan , Liang Fuyuan
Published: July 2020

Real-word phenomena, such as ocean eddies and clouds, tend to split and merge while they are moving around within a space. Their trajectories usually bear one or more branches and are accordingly defined as complex trajectories in this study. The trajectories may show significant spatiotemporal variations in terms of their structures and some of them may be more prominent than the others. The identification of prominent structures in the complex trajectories of such real-world phenomena could better reveal their evolution processes and even shed new light on the driving factors behind them. Methods have been proposed for the extraction of periodic patterns from simple trajectories (i.e., those with linear structure and without any branches) with a focus on mining the related temporal, spatial or semantic information. Unfortunately, it is not appropriate to directly use such methods to examine complex trajectories. This study proposes a novel method to study the periodic patterns of complex trajectories by considering the inherent spatial, temporal and topological information. First, we use a sequence of symbols to represent the various structures of a complex trajectory over its lifespan. We then, on the basis of the PrefixSpan algorithm, propose a periodic pattern mining of structural evolution (PPSE) algorithm and use it to identify the largest and most frequent patterns (LFPs) from the symbol sequence. We also identify potential periodic behaviors. The PPSE method is then used to examine the complex trajectories of the mesoscale eddy in the South China Sea (SCS) from 1993 to 2016. The complex trajectories of ocean eddies in the southeast of Vietnam show are different from other regions in the SCS in terms of their structural evolution processes, as indicated by the LFPs with the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. The LFP in the southeast of Vietnam has the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. Across the SCS, we found seven migration channels. The LFPs of the eddies that migrate through these channels have a temporal cycle of 17–24 years. These channels are also the regions where eddies frequently emerge, as revealed by flow field data.
Map Metadata: the Basis of the Retrieval System of Digital Collections
Authors: Kuźma Marta , Bauer Hans
Published: July 2020

The article presents research on the evaluation of hidden map metadata. A hidden map is a map being part of a book that illustrates certain facts described in the book (e.g., military campaigns, political processes, migrations). The evaluation regards their completeness. Metadata completeness is the degree to which objects are described using all metadata elements. The analysis took into account the metadata of archival maps accessed via the GeoPortOst geoportal. Over 3000 hidden maps from the period 1572–2018 were analyzed, and the map set was divided into 8 collections. The main purpose of cartographers and librarians is to facilitate understanding of the relationship between individual information (librarians) and spatial data (cartographers). To this end, the research focused on the kind of information about old maps that should be stored in metadata to describe them in terms of space, time, content and context so as to increase their interoperability. The following metadata were taken into account in the assessment: title of content, type of content, date, date range, rights, language, subject, distribution format, geographic location, scale of map, reference system, mapping methods, map format, and source materials used to develop the map. The completeness of individual metadata as well as the completeness of metadata for individual collections was assessed. Finally, good practices of individual collections and metadata that could increase the interoperability of the entire collection were identified. The evaluation enables the owners to show the strengths and weaknesses of a given collection in a quick and easy way.
Aggregation and Prion-Inducing Properties of the G-Protein Gamma Subunit Ste18 are Regulated by Membrane Association
Authors: Chernova Tatiana A. , Yang Zhen , Karpova Tatiana S. , Shanks John R. , Shcherbik Natalia , Wilkinson Keith D. , Chernoff Yury O.
Published: July 2020

Yeast prions and mnemons are respectively transmissible and non-transmissible self-perpetuating protein assemblies, frequently based on cross-β ordered detergent-resistant aggregates (amyloids). Prions cause devastating diseases in mammals and control heritable traits in yeast. It was shown that the de novo formation of the prion form [PSI+] of yeast release factor Sup35 is facilitated by aggregates of other proteins. Here we explore the mechanism of the promotion of [PSI+] formation by Ste18, an evolutionarily conserved gamma subunit of a G-protein coupled receptor, a key player in responses to extracellular stimuli. Ste18 forms detergent-resistant aggregates, some of which are colocalized with de novo generated Sup35 aggregates. Membrane association of Ste18 is required for both Ste18 aggregation and [PSI+] induction, while functional interactions involved in signal transduction are not essential for these processes. This emphasizes the significance of a specific location for the nucleation of protein aggregation. In contrast to typical prions, Ste18 aggregates do not show a pattern of heritability. Our finding that Ste18 levels are regulated by the ubiquitin-proteasome system, in conjunction with the previously reported increase in Ste18 levels upon the exposure to mating pheromone, suggests that the concentration-dependent Ste18 aggregation may mediate a mnemon-like response to physiological stimuli.
Cellular Mechanisms of Circulating Tumor Cells During Breast Cancer Metastasis
Authors: Park Han-A , Brown Spenser R. , Kim Yonghyun
Published: July 2020

Circulating tumor cells (CTCs) are cancer cells that detach from the primary site and travel in the blood stream. A higher number of CTCs increases the risk of breast cancer metastasis, and it is inversely associated with the survival rates of patients with breast cancer. Although the numbers of CTCs are generally low and the majority of CTCs die in circulation, the survival of a few CTCs can seed the development of a tumor at a secondary location. An increasing number of studies demonstrate that CTCs undergo modification in response to the dynamic biophysical environment in the blood due in part to fluid shear stress. Fluid shear stress generates reactive oxygen species (ROS), triggers redox-sensitive cell signaling, and alters the function of intracellular organelles. In particular, the mitochondrion is an important target organelle in determining the metastatic phenotype of CTCs. In healthy cells, mitochondria produce adenosine triphosphate (ATP) via oxidative phosphorylation in the electron transport chain, and during oxidative phosphorylation, they produce physiological levels of ROS. Mitochondria also govern death mechanisms such as apoptosis and mitochondrial permeability transition pore opening to, in order eliminate unwanted or damaged cells. However, in cancer cells, mitochondria are dysregulated, causing aberrant energy metabolism, redox homeostasis, and cell death pathways that may favor cancer invasiveness. In this review, we discuss the influence of fluid shear stress on CTCs with an emphasis on breast cancer pathology, then discuss alterations of cellular mechanisms that may increase the metastatic potentials of CTCs.
Epigenome Wide Association and Stochastic Epigenetic Mutation Analysis on Cord Blood of Preterm Birth
Authors: Spada Elena , Calzari Luciano , Corsaro Luigi , Fazia Teresa , Mencarelli Monica , Di Blasio Anna Maria , Bernardinelli Luisa , Zangheri Giulia , Vignali Michele , Gentilini Davide
Published: July 2020

Preterm birth (PTB) can be defined as the endpoint of a complex process that could be influenced by maternal and environmental factors. Epigenetics recently emerged as an interesting field of investigation since it represents an important mechanism of regulation. This study evaluates epigenetic impact of preterm birth on DNA methylation. Genome-wide DNAm was measured using the Illumina 450K array in cord blood samples obtained from 72 full term and 18 preterm newborns. Lymphocyte composition was calculated based on specific epigenetic markers that are present on the 450k array. Differential methylation analysis was performed both at site and region level; moreover, stochastic epigenetic mutations (SEMs) were also evaluated. The study showed significant differences in blood cell composition between the two groups. Moreover, after multiple testing correction, statistically significant differences in DNA methylation levels emerged between the two groups both at site and region levels. Results obtained were compared to those reported by previous EWAS, leading to a list of more consistent genes associated with PTB. Finally, the SEMs analysis revealed that the burden of SEMs resulted significantly higher in the preterm group. In conclusion, PTB resulted associated to specific epigenetic signatures that involve immune system. Moreover, SEMs analysis revealed an increased epigenetic drift at birth in the preterm group.
Evaluation of the In Vitro Damage Caused by Lipid Factors on Stem Cells from a Female Rat Model of Type 2 Diabetes/Obesity and Stress Urinary Incontinence
Authors: Kovanecz Istvan , Gelfand Robert , Sharifzad Sheila , Ohanian Alec , DeCastro William , Cooper Carley , Lin Guiting , Lue Tom , Gonzalez-Cadavid Nestor
Published: July 2020

Human stem cell therapy for type 2 diabetes/obesity (T2D/O) complications is performedwith stem cell autografts, exposed to the noxious T2D/O milieu, often with suboptimal results.We showed in the Obese Zucker (OZ) rat model of T2D/O that when their muscle-derived stemcells (MDSC) were from long-term T2D/O male rats, their repair ecacy for erectile dysfunctionwas impaired and were imprinted with abnormal gene- and miR-global transcriptional signatures(GTS). The damage was reproduced in vitro by short-term exposure of normal MDSC to dyslipidemicserum, causing altered miR-GTS, fat infiltration, apoptosis, impaired scratch healing, and myostatinoverexpression. Similar in vitro alterations occurred with their normal counterparts (ZF4-SC) fromthe T2D/O rat model for female stress urinary incontinence, and with ZL4-SC from non-T2D/O leanfemale rats. In the current work we studied the in vitro eects of cholesterol and Na palmitate aslipid factors on ZF4-SC and ZL4-SC. A damage partially resembling the one caused by the femaledyslipidemic serum was found, but diering between both lipid factors, so that each one appears tocontribute specifically to the stem cell damaging eects of dyslipidemic serum in vitro and T2D/Oin vivo, irrespective of gender. These results also confirm the miR-GTS biomarker value forMDSC damage.
NME3 Regulates Mitochondria to Reduce ROS-Mediated Genome Instability
Authors: Chen Chih-Wei , Tsao Ning , Zhang Wei , Chang Zee-Fen
Published: July 2020

NME3 is a member of the nucleoside diphosphate kinase (NDPK) family that binds to the mitochondrial outer membrane to stimulate mitochondrial fusion. In this study, we showed that NME3 knockdown delayed DNA repair without reducing the cellular levels of nucleotide triphosphates. Further analyses revealed that NME3 knockdown increased fragmentation of mitochondria, which in turn led to mitochondrial oxidative stress-mediated DNA single-strand breaks (SSBs) in nuclear DNA. Re-expression of wild-type NME3 or inhibition of mitochondrial fission markedly reduced SSBs and facilitated DNA repair in NME3 knockdown cells, while expression of N-terminal deleted mutant defective in mitochondrial binding had no rescue effect. We further showed that disruption of mitochondrial fusion by knockdown of NME4 or MFN1 also caused mitochondrial oxidative stress-mediated genome instability. In conclusion, the contribution of NME3 to redox-regulated genome stability lies in its function in mitochondrial fusion.
Citalopram Administration Does Not Promote Function or Histological Recovery after Spinal Cord Injury
Authors: Lima Rui , Monteiro Susana , Gomes Eduardo D. , Vasconcelos Natália L. , Assunção-Silva Rita , Morais Mónica , Salgado António J. , Silva Nuno A.
Published: July 2020

Citalopram is a selective serotonin reuptake inhibitor, and although widely used as an antidepressant, this drug has also demonstrated interesting repairing properties leading to motor recovery and pathology amelioration in animal models of stroke and degeneration. Here, we tested the efficacy of both 7-day and 8-week citalopram treatment in a contusive spinal cord injury (SCI) rat model. A combination of behavioral tests, histological and serum cytokine analysis was used to assess overall recovery. Despite promoting a mild reduction of inflammatory cells as well as an early, but transient increase of specific serum cytokines, citalopram administration showed no overall beneficial effects on motor performance or lesion extension. Our results do not support citalopram treatment as a therapeutic strategy for SCI.