bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Bimetallic Nanoparticles of Cd4HgS5 by Candida Species
Authors: Romero-Núñez Araceli , González Gonzalo , Romero-Ibarra Josué E. , Vega-González Arturo , Cruz-Jiménez Gustavo , Hernández-Cristóbal Orlando , Zárraga-Núñez Ramón A. , Obregón-Herrera Armando , López-Romero Everardo , Pedraza-Reyes Mario , Cuéllar-Cruz Mayra
Published: January 2019

In recent decades, it has been demonstrated that bimetallic nanoparticles (NPs) possess a number of advantages over monometallic NPs, as the combination of metals results in important changes to their physicochemical properties. Synthesis of bimetallic NPs can be achieved through a number of methods, yet there are serious difficulties in controlling these protocols. Biological methods based on the use of microorganisms exhibit important advantages over traditional methods, which makes the search for organisms such as bacteria, yeast and fungi endowed with these abilities an important task. In this context, it has been found that Candida species are able to biosynthesize monometallic NPs, but their ability to form bimetallic NPs has not been investigated. CdHgS is a bimetallic NP of special interest, as it has been found useful in a number of applications; however, its preparation by traditional methods poses certain limitations, and the ability to obtain it through biological procedures has never been demonstrated. With this in mind, the major purpose of this study is to evaluate whether several Candida species were able to synthesize bimetallic NPs of CdHgS in a Cd4HgS5 phase. To our knowledge, this is the first report on the biological synthesis of bimetallic NPs in Candida species.
Retrofit of Residential Buildings in Europe
Authors: Scuderi Giuliana
Published: January 2019

Recently, many cities in Europe are encouraging the recovery of the existing residential heritage. To maximize the benefits of these campaigns, a multi-purpose campaign of architectural, functional, and structural retrofit is essential. Additionally, a fast-changing society requires new living criteria; new models need to be developed to respond to the developing requirements of communities and markets. This paper proposes a method of analysis for 49 residential retrofit projects, a range of “best practices” presented through the definition of strategies, and actions and thematic packages, aiming at reassuming, in a systematic way, the complex panorama of the state of the art in Europe. Each project was analyzed using a data sheet, while synoptic views and tables provided key interpretations and a panorama of strategies and approaches. The analysis of the state of the art showed that lightweight interventions achieved using dry stratified construction technologies of structure/cladding/finishing are a widespread approach to renovation and requalification both for superficial/two-dimensional actions and volumetric/spatial actions. The study also highlights the leading role of the envelope within retrofit interventions. The retrofit approaches appear to reach the greatest efficiency when reversible, because only in this way do they ensure environmentally friendly actions with the possibility of dismantling. The intervention should improve the flexibility of the existing construction with a correct balance between planning for the present and planning for the future.
The Effect of Microdialysis Catheter Insertion on Glutamate and Serotonin Levels in Masseter Muscle in Patients with Myofascial Temporomandibular Disorders and Healthy Controls
Authors: Bajramaj Ermira , Häggman-Henrikson Birgitta , Dawson Andreas , Gerdle Björn , Ghafouri Bijar
Published: January 2019

Myofascial temporomandibular disorders (TMD) are the most common cause of chronic pain in the orofacial region. Microdialysis has been used to study metabolic changes in the human masseter muscle. The insertion of the microdialysis probe causes acute tissue trauma that could affect the metabolic milieu and thereby influence the results when comparing healthy subjects to those with TMD. This study aimed to investigate the levels of serotonin and glutamate during the acute tissue trauma period in healthy subjects and in patients with TMD. Microdialysis was carried out in 15 patients with TMD and 15 controls, and samples were collected every 20 min during a period of 140 min. No significant alterations of serotonin or glutamate were observed over the 2 h period for the healthy subjects. For the TMD group, a significant decrease in serotonin was observed over time (p < 0.001), followed by a significant increase between 120 and 140 min (p < 0.001). For glutamate, a significant reduction was observed at 40 min compared to baseline. The results showed that there was a spontaneous increase of serotonin 2 h after the insertion of the catheter in patients with TMD. In conclusion, the results showed that there are differences in the masseter muscle levels of serotonin and glutamate during acute nociception in patients with myofascial TMD compared to healthy subjects.
PT Symmetry, Non-Gaussian Path Integrals, and the Quantum Black–Scholes Equation
Authors: Hicks Will
Published: January 2019

The Accardi–Boukas quantum Black–Scholes framework, provides a means by which one can apply the Hudson–Parthasarathy quantum stochastic calculus to problems in finance. Solutions to these equations can be modelled using nonlocal diffusion processes, via a Kramers–Moyal expansion, and this provides useful tools to understand their behaviour. In this paper we develop further links between quantum stochastic processes, and nonlocal diffusions, by inverting the question, and showing how certain nonlocal diffusions can be written as quantum stochastic processes. We then go on to show how one can use path integral formalism, and PT symmetric quantum mechanics, to build a non-Gaussian kernel function for the Accardi–Boukas quantum Black–Scholes. Behaviours observed in the real market are a natural model output, rather than something that must be deliberately included.
Novel Entropy and Rotation Forest-Based Credal Decision Tree Classifier for Landslide Susceptibility Modeling
Authors: He Qingfeng , Xu Zhihao , Li Shaojun , Li Renwei , Zhang Shuai , Wang Nianqin , Pham Binh Thai , Chen Wei
Published: January 2019

Landslides are a major geological hazard worldwide. Landslide susceptibility assessments are useful to mitigate human casualties, loss of property, and damage to natural resources, ecosystems, and infrastructures. This study aims to evaluate landslide susceptibility using a novel hybrid intelligence approach with the rotation forest-based credal decision tree (RF-CDT) classifier. First, 152 landslide locations and 15 landslide conditioning factors were collected from the study area. Then, these conditioning factors were assigned values using an entropy method and subsequently optimized using correlation attribute evaluation (CAE). Finally, the performance of the proposed hybrid model was validated using the receiver operating characteristic (ROC) curve and compared with two well-known ensemble models, bagging (bag-CDT) and MultiBoostAB (MB-CDT). Results show that the proposed RF-CDT model had better performance than the single CDT model and hybrid bag-CDT and MB-CDT models. The findings in the present study overall confirm that a combination of the meta model with a decision tree classifier could enhance the prediction power of the single landslide model. The resulting susceptibility maps could be effective for enforcement of land management regulations to reduce landslide hazards in the study area and other similar areas in the world.
Increasing Robustness in the Detection of Freezing of Gait in Parkinson’s Disease
Authors: San-Segundo Rubén , Navarro-Hellín Honorio , Torres-Sánchez Roque , Hodgins Jessica , De la Torre Fernando
Published: January 2019

This paper focuses on detecting freezing of gait in Parkinson’s patients using body-worn accelerometers. In this study, we analyzed the robustness of four feature sets, two of which are new features adapted from speech processing: mel frequency cepstral coefficients and quality assessment metrics. For classification based on these features, we compared random forest, multilayer perceptron, hidden Markov models, and deep neural networks. These algorithms were evaluated using a leave-one-subject-out (LOSO) cross validation to match the situation where a system is being constructed for patients for whom there is no training data. This evaluation was performed using the Daphnet dataset, which includes recordings from ten patients using three accelerometers situated on the ankle, knee, and lower back. We obtained a reduction from 17.3% to 12.5% of the equal error rate compared to the previous best results using this dataset and LOSO testing. For high levels of sensitivity (such as 0.95), the specificity increased from 0.63 to 0.75. The biggest improvement across all of the feature sets and algorithms tested in this study was obtained by integrating information from longer periods of time in a deep neural network with convolutional layers.
Resource Allocation for Relay-Based OFDMA Power Line Communication System
Authors: Zhu Qing , Chen Zhimin , He Xinyi
Published: January 2019

In this paper, we investigate the resource allocation for multi-user orthogonal frequency division multiple access (OFDMA) power line communication (PLC) systems, which satisfy both the total average transmit power constrained by PLC networks and the required interference limitations. First, we propose an optimal resource allocation scheme, with respect to joint consideration of the subcarrier and power constraint to maximize the throughput of the PLC system. Then, we divide the intractable problem into two individual subproblems to decrease the computational burden, which can avoid proceeding the mixed integer nonlinear programming (MINLP) problem. The proposed resource allocation scheme can ensure the optimality and efficiency of the system with rigorous proofs. The simulation results show that our proposed resource allocation scheme for the PLC system outperforms other algorithms, and is efficient with acceptable complexity.
A New Wind Speed Forecasting Modeling Strategy Using Two-Stage Decomposition, Feature Selection and DAWNN
Authors: Sun Sizhou , Wei Lisheng , Xu Jie , Jin Zhenni
Published: January 2019

Accurate wind speed prediction plays a crucial role on the routine operational management of wind farms. However, the irregular characteristics of wind speed time series makes it hard to predict accurately. This study develops a novel forecasting strategy for multi-step wind speed forecasting (WSF) and illustrates its effectiveness. During the WSF process, a two-stage signal decomposition method combining ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) is exploited to decompose the empirical wind speed data. The EEMD algorithm is firstly employed to disassemble wind speed data into several intrinsic mode function (IMFs) and one residual (Res). The highest frequency component, IMF1, obtained by EEMD is further disassembled into different modes by the VMD algorithm. Then, feature selection is applied to eliminate the illusive components in the input-matrix predetermined by partial autocorrelation function (PACF) and the parameters in the proposed wavelet neural network (WNN) model are optimized for improving the forecasting performance, which are realized by hybrid backtracking search optimization algorithm (HBSA) integrating binary-valued BSA (BBSA) with real-valued BSA (RBSA), simultaneously. Combinations of Morlet function and Mexican hat function by weighted coefficient are constructed as activation functions for WNN, namely DAWNN, to enhance its regression performance. In the end, the final WSF values are obtained by assembling the prediction results of each decomposed components. Two sets of actual wind speed data are applied to evaluate and analyze the proposed forecasting strategy. Forecasting results, comparisons, and analysis illustrate that the proposed EEMD/VMD-HSBA-DAWNN is an effective model when employed in multi-step WSF.
Sample Selection Based on Active Learning for Short-Term Wind Speed Prediction
Authors: Yang Jian , Zhao Xin , Wei Haikun , Zhang Kanjian
Published: January 2019

Wind speed prediction is the key to wind power prediction, which is very important to guarantee the security and stability of the power system. Due to dramatic changes in wind speed, it needs high-frequency sampling to describe the wind. A large number of samples are generated and affect modeling time and accuracy. Therefore, two novel active learning methods with sample selection are proposed for short-term wind speed prediction. The main objective of active learning is to minimize the number of training samples and ensure the prediction accuracy. In order to verify the validity of the proposed methods, the results of support vector regression (SVR) and artificial neural network (ANN) models with different training sets are compared. The experimental data are from a wind farm in Jiangsu Province. The simulation results show that the two novel active learning methods can effectively select typical samples. While reducing the number of training samples, the prediction performance remains almost the same or slightly improved.
Control Strategies in Multi-Zone Air Conditioning Systems
Authors: Rismanchi Behzad , Zambrano Juan Mahecha , Saxby Bryan , Tuck Ross , Stenning Mark
Published: January 2019

In a commercial building, a significant amount of energy is used by the ventilation systems to condition the air for the indoor environments to satisfy the required quantity (temperature and humidity) and quality (amount of fresh air). For many years, Variable Air Volume (VAV) systems have been considered as the most efficient solutions by balancing the airflow volume based on the demand making them energy efficient when compared with the traditional Constant Air Volume (CAV) systems. However, the setpoints in VAV systems are often misread by the sensors due to stratification and formation of pollutant pockets and responding to design levels that overestimate the real-time demand conditions, which result in waste of energy, thermal discomfort and unhealthy air. In general, VAV devices are expensive, complicated and prone to failures and they are used only in medium and large projects. More recently, new technologies have evolved to solve this issue. In one of the new solutions, VAV motors terminals are replaced with flaps which are simpler and less expensive thus, they can be implemented in a wider range of projects. In systems, balancing and supplying the optimal airflow to reduce the energy consumption while delivering ideal thermal and Indoor Air Quality (IAQ) levels are the main challenges. In this paper, a comparison of the recent technologies with traditional VAV systems is presented to be used as a guild line for researchers and designers in the field of Heating Ventilation Air Conditioning (HVAC).
Triple Bottom Line Analysis and Optimum Sizing of Renewable Energy Using Improved Hybrid Optimization Employing the Genetic Algorithm: A Case Study from India
Authors: Saiprasad Nithya , Kalam Akhtar , Zayegh Aladin
Published: January 2019

Techno-economic, social, and environmental factors influence a large part of society, predominantly in developing countries. Due to energy poverty and bloating populations, developing countries like India are striving to meet the energy balance. One initiative of India to achieve the country’s Renewable Energy Target (RET) is the setting up of the National Solar Mission (NSM) to meet a target of 175 GW (non-hydro) by the year 2022. Prioritizing Renewable Energy (RE) utilization to achieve techno-economic balance is India’s primary objective and creating a positive environmental impact is a bonus. In this study, various scenarios are explored by investigating the techno-economic and environmental impact on RE adoption for a small community in India by optimally sizing the Hybrid Renewable Energy System (HRES). This study is an exemplar in understanding and exploring RE utilization, whilst examining the recent RE market in depth and exploring the advantages and disadvantages of the current RE situation by initiating it in a smaller community. Improved Hybrid Optimization using Genetic Algorithm (iHOGA) PRO+ software, (Version 2.4 -Pro+, Created by Dr Rodolfo Dufo López, University Zaragoza (Spain)) is used to size the RE systems. The results are categorized using triple bottom line analysis (TBL analysis) and for different scenarios, the techno-economic, environmental, and social merits are weighed upon. The probable hurdles that India has to surpass to achieve easy RE adoption are also discussed in this work. The influential merits for analyzing the TBL for a real-time scenario are Net Present Cost (NPC), Carbon-di-oxide (CO2) emissions, and job criteria. Compared to Hybrid Optimization of Multiple Energy Resources (HOMER) software, iHOGA remains less explored in the literature, specifically for the grid-connected systems. The current study provides a feasibility analysis of grid-connected RE systems for the desired location. iHOGA software simulated 15 sets of results for different values of loads considered and various acquisition costs of HRES. At least 70% of RE can be penetrated for the Aralvaimozhi community with the lowest value of NPC of the HRES. From the TBL analysis conducted, integrating HRES into a micro-grid for the community would result in mitigating CO2 emissions and provide job opportunities to the local community; although, the economic impact should be minimized if the acquisition costs of the HRES are reduced, as has been established through this study.
The Characterization of a Spectrum Splitter of TechSpec AOI 50.0mm Square Hot and Cold Mirrors Using a Halogen Light for a Photovoltaic-Thermoelectric Generator Hybrid
Authors: Piarah Wahyu H. , Djafar Zuryati , Syafaruddin  , Mustofa
Published: January 2019

The characterization of a spectrum splitter of both hot and cold mirror, type TechSpec AOI 50.0, using a 50-Watt halogen bulb light has been done. Both the bulb spectrum, prior to and after spectrum splitting, are described in this study to see the degradation of radiation that occurs because partial energy is absorbed by the splitter. This characterization plays an important role in determining the best position of a photovoltaic (PV) and thermoelectric generator (TEG) in a PV-TEG system. The light spectrum was recorded using mini USB spectrometer hardware and Spectragryph version 1.2.8 software as optical spectroscopic software that displays light records coming with wavelength (nm) on the x-axis and light spectrum intensity in arbitrary units (a.u.) on the y-axis. The measurement results show that the light intensity in the visible light region (300–750) nm is more dominant than the intensity in infrared light (>750 nm), so that the PV placement is preferred over TEG. Furthermore, with a cold mirror, PV is more suitable if placed in a position to receive reflected light, while using a hot mirror is more suitable in the position transmitted light. For TEG, it is placed in a position opposite to PV. As a result, the maximum intensity of the PV light spectrum with cold mirrors is 46.52 a.u at a wavelength of 479.6 nm, while with hot mirrors it is 42.07 a.u with a 457.6 nm wavelength. It can be concluded that the value of the light intensity with a cold mirror is better than that with a hot mirror on the visible light (Vis) spectrum, and the current and voltage are equivalent to the results of the radiation energy area. It was proven that the maximum total output of a hybrid PV-TEG system with Cold Mirror is greater than that with Hot Mirror (100.53 > 68.77) × 10−3 µW. Based on the result of this study, it is recommended that further research can be conducted to increase radiation energy and output power in TEG.
Innovative Modeling Approach for Li-Ion Battery Packs Considering Intrinsic Cell Unbalances and Packaging Elements
Authors: Ko Sung-Tae , Lee Jaehyung , Ahn Jung-Hoon , Lee Byoung Kuk
Published: January 2019

In this paper, an innovative modeling approach for Li-ion battery packs is proposed by considering intrinsic cell unbalances and packaging elements. The proposed modeling method shows that the accurate battery pack model can be achieved if the overall influences of intrinsic cell unbalances and packaging elements are taken account. Concurrently, the proposed method takes a practical model structure, resulting in the reduction of computational burden in a battery management system. Furthermore, because the proposed method utilizes cell information without a manufactured battery pack, it can be helpful to design optimal battery packs. The proposed method is verified through simulation and experimental results of the Li-ion battery pack along with the battery cycler. In three test profiles, the mean absolute percentage errors and root mean square errors of the proposed pack model do not exceed 0.5% and 0.07 V, respectively.
Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment
Authors: Batzelis Efstratios
Published: January 2019

The extraction of the photovoltaic (PV) model parameters remains to this day a long-standing and popular research topic. Numerous methods are available in the literature, widely differing in accuracy, complexity, applicability, and their very nature. This paper focuses on the class of non-iterative parameter extraction methods and is limited to the single-diode PV model. These approaches consist of a few straightforward calculation steps that do not involve iterations; they are generally simple and easy to implement but exhibit moderate accuracy. Seventeen such methods are reviewed, implemented, and evaluated on a dataset of more than one million measured I-V curves of six different PV technologies provided by the National Renewable Energy Laboratories (NREL). A comprehensive comparative assessment takes place to evaluate these alternatives in terms of accuracy, robustness, calculation cost, and applicability to different PV technologies. For the first time, the irregularities found in the extracted parameters (negative or complex values) and the execution failures of these methods are recorded and are used as an assessment criterion. This comprehensive and up-to-date literature review will serve as a useful tool for researchers and engineers in selecting the appropriate parameter extraction method for their application.
Evaluation of the CO2 Emissions Reduction Potential of Li-ion Batteries in Ship Power Systems
Authors: Peralta P. César O. , Vieira Giovani T. T. , Meunier Simon , Vale Rodrigo J. , Salles Mauricio B. C. , Carmo Bruno S.
Published: January 2019

Greenhouse gas emissions are one of the most critical worldwide concerns, and multiple efforts are being proposed to reduce these emissions. Shipping represents around 2% of global CO 2 emissions. Since ship power systems have a high dependence on fossil fuels, hybrid systems using diesel generators and batteries are becoming an interesting solution to reduce CO 2 emissions. In this article, we analyze the potential implementation of Li-ion batteries in a platform supply vessel system through simulations using HOMER software (Hybrid Optimization Model for Multiple Energy Resources). We evaluate the impact of battery characteristics such as round trip efficiency, rated power, and energy capacity. We also evaluate the potential CO 2 emissions reduction that could be achieved with two of the most common types of Li-ion batteries (lithium titanate, lithium iron phosphate). Furthermore, we consider that the Li-ion batteries are installed in a 20 ft container. Results indicate that the lithium iron phosphate battery has a better performance, even though the difference between both technologies is lower than 1% of total emissions. We also analyze the potential emissions reduction for different parts of a mission to an offshore platform for different configurations of the ship power system. The most significant potential CO 2 emissions reduction among the analyzed cases is 8.7% of the total emissions, and it is achieved by the configuration including the main and auxiliary diesel engines as well as batteries. Finally, we present managerial implications of these results for both companies operating ships and ship building companies.
Land Use/Land Cover Change Detection and Urban Sprawl Analysis in the Mount Makiling Forest Reserve Watersheds and Buffer Zone, Philippines
Authors: Soriano Merlyn , Hilvano Noba , Garcia Ronald , Hao Aldrin Joseph , Alegre Aldin , Tiburan, Jr. Cristino
Published: January 2019

Ecologically Valuable Areas play an important role in providing ecosystem services, however, human activities such as land conversion and urban sprawl pose pressures and threats to these areas. The study assessed the land use/land cover and urban sprawl in the Mount Makiling Forest Reserve (MMFR) Watersheds and Buffer Zone from 1992 to 2015 using remote sensing and Geographic Information System (GIS). Results showed that the land use/cover within the MMFR buffer zone has changed from 1992 to 2015 with built-up areas increasing by 117% despite Proclamation 1257, s. 1998 which regulates human activities in the zone. Based on the Shannon entropy analysis the land development in the MMFR buffer zone tends to be dispersed and sprawling. However, when the magnitude of change of urban sprawl in the buffer zone from 2002 to 2015 was calculated, a decrease in the entropy value was observed which implies a compacting pattern as the human settlement in the buffer zone increases over time. Proclamation 1257, s. 1998 needs to be strengthened to protect MMFR and its buffer zone from further encroachment and pressure. Moreover, remote sensing and GIS proved to be useful tools for assessing urban sprawl in ecologically valuable areas such as MMFR.
Genome Survey Sequencing of Acer truncatum Bunge to Identify Genomic Information, Simple Sequence Repeat (SSR) Markers and Complete Chloroplast Genome
Authors: Wang Rongkai , Fan Jinshuan , Chang Pan , Zhu Ling , Zhao Mengran , Li Lingli
Published: January 2019

The Acer truncatum Bunge is a particular forest tree species found in the north of China. Due to the recent discovery that its seeds contain a considerable amount of nervonic acid, this species has received more and more attention. However, there have been no reports of the genome in this species. In this study, we report on the Acer truncatum genome sequence produced by genome survey sequencing. In total, we obtained 61.90 Gbp of high-quality data, representing approximately 116x coverage of the Acer truncatum genome. The genomic characteristics of Acer truncatum include a genome size of 529.88 Mbp, a heterozygosis rate of 1.06% and a repeat rate of 48.8%. A total of 392,961 high-quality genomic SSR markers were developed and a graphical map of the annotated circular chloroplast genome was generated. Thus far, this is the first report of de novo whole genome sequencing and assembly of Acer truncatum. We believe that this genome sequence dataset may provide a new resource for future genomic analysis and molecular breeding studies of Acer truncatum.
A Spatial Prediction-Based Motion-Compensated Frame Rate Up-Conversion
Authors: Li Yanli , Ma Wendan , Han Yue
Published: January 2019

In Multimedia Internet of Things (IoT), in order to reduce the bandwidth consumption of wireless channels, Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is often used to support the low-bitrate video communication. In this paper, we propose a spatial predictive algorithm which is used to improve the performance of MC-FRUC. The core of the proposed algorithm is a predictive model to split a frame into two kinds of blocks: basic blocks and absent blocks. Then an improved bilateral motion estimation is proposed to compute the Motion Vectors (MVs) of basic blocks. Finally, with the spatial correlation of Motion Vector Field (MVF), the MV of an absent block is predicted based on the MVs of its neighboring basic blocks. Experimental results show that the proposed spatial prediction algorithm can improve both the objective and the subjective quality of the interpolated frame, with a low computational complexity.
An Overview of Vehicular Communications
Authors: Arena Fabio , Pau Giovanni
Published: January 2019

The transport sector is commonly subordinate to several issues, such as traffic congestion and accidents. Despite this, in recent years, it is also evolving with regard to cooperation between vehicles. The fundamental objective of this trend is to increase road safety, attempting to anticipate the circumstances of potential danger. Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies strive to give communication models that can be employed by vehicles in different application contexts. The resulting infrastructure is an ad-hoc mesh network whose nodes are not only vehicles but also all mobile devices equipped with wireless modules. The interaction between the multiple connected entities consists of information exchange through the adoption of suitable communication protocols. The main aim of the review carried out in this paper is to examine and assess the most relevant systems, applications, and communication protocols that will distinguish the future road infrastructures used by vehicles. The results of the investigation reveal the real benefits that technological cooperation can involve in road safety.
Cardiac Triangle Mapping: A New Systems Approach for Noninvasive Evaluation of Left Ventricular End Diastolic Pressure
Authors: Pahlevan Niema M. , Matthews Ray V.
Published: January 2019

Noninvasive and practical assessment of hemodynamics is a critical unmet need in the treatment of both chronic and acute cardiovascular diseases. Particularly, the ability to monitor left ventricular end-diastolic pressure (LVEDP) noninvasively offers enormous benefit for managing patients with chronic congestive heart failure. Recently, we provided proof of concept that a new cardiac metric, intrinsic frequency (IF), derived from mathematical analysis of non-invasively captured arterial waveforms, can be used to accurately compute cardiovascular hemodynamic measures, such as left ventricle ejection fraction (LVEF), by using a smartphone. In this manuscript, we propose a new systems-based method called cardiac triangle mapping (CTM) for hemodynamics evaluation of the left ventricle. This method is based on intrinsic frequency (IF) and systolic time interval (STI) methods that allows computation of LVEDP from noninvasive measurements. Since the CTM method only requires arterial waveform and electrocardiogram (ECG), it can eventually be adopted as a simple smartphone-based device, an inexpensive hand-held device, or perhaps (with future design modifications) a wearable sensor. Such devices, combined with this method, would allow for remote monitoring of heart failure patients.
From Genotype to Phenotype: Through Chromatin
Authors: Romanowska Julia , Joshi Anagha
Published: January 2019

Advances in sequencing technologies have enabled the exploration of the genetic basis for several clinical disorders by allowing identification of causal mutations in rare genetic diseases. Sequencing technology has also facilitated genome-wide association studies to gather single nucleotide polymorphisms in common diseases including cancer and diabetes. Sequencing has therefore become common in the clinic for both prognostics and diagnostics. The success in follow-up steps, i.e., mapping mutations to causal genes and therapeutic targets to further the development of novel therapies, has nevertheless been very limited. This is because most mutations associated with diseases lie in inter-genic regions including the so-called regulatory genome. Additionally, no genetic causes are apparent for many diseases including neurodegenerative disorders. A complementary approach is therefore gaining interest, namely to focus on epigenetic control of the disease to generate more complete functional genomic maps. To this end, several recent studies have generated large-scale epigenetic datasets in a disease context to form a link between genotype and phenotype. We focus DNA methylation and important histone marks, where recent advances have been made thanks to technology improvements, cost effectiveness, and large meta-scale epigenome consortia efforts. We summarize recent studies unravelling the mechanistic understanding of epigenetic processes in disease development and progression. Moreover, we show how methodology advancements enable causal relationships to be established, and we pinpoint the most important issues to be addressed by future research.
Functional SNPs in the Human Autoimmunity-Associated Locus 17q12-21
Authors: Ustiugova Alina S. , Korneev Kirill V. , Kuprash Dmitry V. , Afanasyeva Marina A.
Published: January 2019

Genome-wide association studies (GWASes) revealed several single-nucleotide polymorphisms (SNPs) in the human 17q12-21 locus associated with autoimmune diseases. However, follow-up studies are still needed to identify causative SNPs directly mediating autoimmune risk in the locus. We have chosen six SNPs in high linkage disequilibrium with the GWAS hits that showed the strongest evidence of causality according to association pattern and epigenetic data and assessed their functionality in a local genomic context using luciferase reporter system. We found that rs12946510, rs4795397, rs12709365, and rs8067378 influenced the reporter expression level in leukocytic cell lines. The strongest effect visible in three distinct cell types was observed for rs12946510 that is predicted to alter MEF2A/C and FOXO1 binding sites.
Predicting MiRNA-Disease Association by Latent Feature Extraction with Positive Samples
Authors: Che Kai , Guo Maozu , Wang Chunyu , Liu Xiaoyan , Chen Xi
Published: January 2019

In discovering disease etiology and pathogenesis, the associations between MicroRNAs (miRNAs) and diseases play a critical role. Given known miRNA-disease associations (MDAs), how to uncover potential MDAs is an important problem. To solve this problem, most of the existing methods regard known MDAs as positive samples and unknown ones as negative samples, and then predict possible MDAs by iteratively revising the negative samples. However, simply viewing unknown MDAs as negative samples introduces erroneous information, which may result in poor predication performance. To avoid such defects, we present a novel method using only positive samples to predict MDAs by latent features extraction (LFEMDA). We design a new approach to construct the miRNAs similarity matrix. LFEMDA integrates the disease similarity matrix, the known MDAs and the miRNAs similarity matrix to identify potential MDAs. By introducing miRNAs and diseases knowledge as the auxiliary variables, the method can converge to give the optimal solution in each iteration. We conduct experiments on high-association diseases and new diseases datasets, in which our method shows better performance than that of other methods. We also carry out a case study on breast neoplasms to further demonstrate the capacity of our method in uncovering potential MDAs.
Sub-Antarctic Auckland Islands Seafloor Mapping Investigations Using Legacy Data
Authors: Tidey Emily J. , Hulbe Christina L.
Published: January 2019

This paper demonstrates the richness of data collected for nautical charting and considers ways in which chart data can support scientific research, through a case study of two modern navigation surveys undertaken in the Auckland Islands. While legacy charts have coarser resolution, and may synthesize different epochs together into one final product, we examine how they may be used on their own and to complement more recent hydrographic surveys. We argue that the hydrographic and ancillary data, only a fraction of which appears on the final chart, also has scientific value and that the hydrographic surveying principles applied during data collection are equally relevant for all seabed mapping. While the benefits of full bottom coverage obtained by state of-the-art multibeam surveys are clear, there is much more to be discovered in legacy singlebeam datasets than what is displayed on the nautical chart alone.
Latin American Cities: From Subservient Reproductions to Intercontinental Dialogues
Authors: Ultramari Clovis , Cantarim Fernanda , Jazar Manoela
Published: January 2019

This paper investigates the circulation of ideas regarding the city among selected countries in Latin America. It discusses convergences between academic and scientific institutions and investigative weakness in partnerships between Brazil, Argentina, Chile, Colombia, and Mexico. It identifies two historical moments: one of vertical dialogues between Latin America and central countries in the elaboration of urban plans (20th century) and another of contemporary academic exchange signalling a horizontal dialogue that is fragile and sporadic but distinct from those observed in the past. Empirical reference is obtained from the analysis of scientific events and papers published by distinguished post-graduate programs concerning urban topics in selected countries, during the time frame of 2000–2015. The methodological approach is based on a bibliographic review and content analysis. Results indicate that the old “one-way” of transfer of urban planning ideas from central countries to Latin America is changing; slowly, the continent has been growing more independent in terms of knowledge creation and circulation.
Combined Effects of Race and Socioeconomic Status on Cancer Beliefs, Cognitions, and Emotions
Authors: Assari Shervin , Khoshpouri Pegah , Chalian Hamid
Published: January 2019

Aim: To determine whether socioeconomic status (SES; educational attainment and income) explains the racial gap in cancer beliefs, cognitions, and emotions in a national sample of American adults. Methods: For this cross-sectional study, data came from the Health Information National Trends Survey (HINTS) 2017, which included a nationally representative sample of American adults. The study enrolled 2277 adults who were either non-Hispanic Black (n = 409) or non-Hispanic White (n = 1868). Race, demographic factors (age and gender), SES (i.e., educational attainment and income), health access (insurance status, usual source of care), family history of cancer, fatalistic cancer beliefs, perceived risk of cancer, and cancer worries were measured. We ran structural equation models (SEMs) for data analysis. Results: Race and SES were associated with perceived risk of cancer, cancer worries, and fatalistic cancer beliefs, suggesting that non-Hispanic Blacks, low educational attainment and low income were associated with higher fatalistic cancer beliefs, lower perceived risk of cancer, and less cancer worries. Educational attainment and income only partially mediated the effects of race on cancer beliefs, emotions, and cognitions. Race was directly associated with fatalistic cancer beliefs, perceived risk of cancer, and cancer worries, net of SES. Conclusions: Racial gap in SES is not the only reason behind racial gap in cancer beliefs, cognitions, and emotions. Racial gap in cancer related beliefs, emotions, and cognitions is the result of race and SES rather than race or SES. Elimination of racial gap in socioeconomic status will not be enough for elimination of racial disparities in cancer beliefs, cognitions, and emotions in the United States.
Acknowledgement to Reviewers of Horticulturae in 2018
Authors:   Horticulturae Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Healthy-Sustainable Housing Index: A Pilot Study to Link Architecture and Public Health in a Semi-Urban Community in Mexico
Authors: Zúñiga-Bello Pamela , Schilmann Astrid , Félix-Arellano Eunice , Gama-Hernández Gerardo , Alamo-Hernández Urinda
Published: January 2019

The aim of this pilot study was to evaluate the link between housing and children´s respiratory symptoms, through the construction of an index (HSHI) based on the definition of healthy-sustainable housing criteria, in a semi-urban community from Morelos, Mexico. A general and household questionnaire, and respiratory symptoms diary were applied in 60 households to gather information about schoolchildren, respiratory health, housing and lifestyle characteristics. HSHI was constructed using principal component analysis. The association between HSHI and the presence and duration of respiratory symptoms was assessed using logistic and Poisson regression models. HSHI had five components, which accounted for 63% of variance, and were classified into poor and sufficient quality. It was observed that schoolchildren who inhabit a sufficient-quality house, showed a reduction in nose irritation duration and in the allergic symptoms probability regarding component 1 (ventilation, lighting and cloth washing) and presented three times less duration of common cold by component 2 (construction material, painted walls inside the house and type of bathroom) compared to poor-quality house inhabitants. Our results suggest that living in a sufficient-quality house, as described by the HSHI, reduced the prevalence of wheezing episodes and the probability of ear pain, providing evidence about the positive association of a healthy-sustainable housing on the respiratory health of schoolchildren.
Health-Related Quality of Life Impairment among Patients with Different Skin Diseases in Vietnam: A Cross-Sectional Study
Authors: Nguyen Sau Huu , Nguyen Long Hoang , Vu Giang Thu , Nguyen Cuong Tat , Le Thu Hoai Thi , Tran Bach Xuan , Latkin Carl A. , Ho Cyrus S. H. , Ho Roger C. M.
Published: January 2019

Skin diseases have caused a heavy burden on the infected population worldwide. This study aimed to examine the health-related quality of life (HRQOL) among patients with different skin diseases and identify associated factors. A cross-sectional study with 430 participants was conducted at the Vietnam National Hospital of Dermatology and Venereology (NHD) from September to November 2018. The EuroQol-5 Dimensions-5 Levels (EQ-5D-5L) instrument was employed, which measures the EQ-5D index from five domains including mobility, self-care, usual activity, pain/discomfort, and anxiety/depression. Multivariate Tobit regression was adopted to determine factors that were associated with HRQOL (EQ-5D index). The rate of atopic dermatitis was the highest with 28.8%, following by contact dermatitis (17.0%) and skin fungal infections (13.0%). Regarding HRQOL, anxiety/depression was the most common health problem in patients with skin diseases (71.8%), following by pain/discomfort (63.6%). The mean EQ-5D index score was 0.73 (SD = 0.19). The lowest EQ-5D index scores were obtained for females with skin infections (mean = 0.52) and for males with psoriasis (mean = 0.59). Females had significantly lower scores compared to males (Coef. = −0.06; 95% CI = −0.11 to −0.01). Higher income and living in rural areas were also negatively correlated with the EQ-5D index. This study demonstrated the low HRQOL among patients with skin diseases in Vietnam and emphasized the vulnerability of patients with different socioeconomic statuses to their HRQOL.
Trimester-Specific Assessment of Diet Quality in a Sample of Canadian Pregnant Women
Authors: Savard Claudia , Lemieux Simone , Carbonneau Élise , Provencher Véronique , Gagnon Claudia , Robitaille Julie , Morisset Anne-Sophie
Published: January 2019

The present study aimed to (1) examine changes in diet quality throughout pregnancy and (2) identify maternal characteristics associated with trimester-specific diet quality. Pregnant women (n = 79) were recruited in their 1st trimester of pregnancy and completed, at each trimester, three web-based 24-hour dietary recalls, from which the Canadian Healthy Eating Index (HEI) was calculated. Physical activity, nutrition knowledge, and socio-demographic web-questionnaires were also completed. Although no variation in total HEI scores was observed across trimesters, we found an overall decrease in the following subscores: adequacy, total fruits and vegetables, unsaturated fats and saturated fats (p < 0.05). In the 1st trimester, overweight and obese pregnant women had a lower diet quality in comparison with normal-weight and underweight women (HEI scores: 63.1 ± 11.9 vs. 68.0 ± 9.3; p = 0.04). In the 3rd trimester, women younger than 28 years old, with no university degree, poorer nutrition knowledge and who reside in an urban setting, had a lower diet quality (p < 0.05). In conclusion, less educated, younger women who reside in an urban setting may be at a higher risk of poor diet quality in late pregnancy and could benefit from public health programs.
Seasonal Variation and Quality Assessment of the Major and Trace Elements of Atmospheric Dust in a Typical Karst City, Southwest China
Authors: Tang Yang , Han Guilin
Published: January 2019

Atmospheric dust plays an important role in bio-geochemical cycling and the ecological environment. In urban areas, atmospheric dust is more likely to be the carrier of pollutants, thus affecting the air quality of cities. In this study, samples of atmospheric dust were collected monthly for one year in Guiyang City, and the contents of major and trace elements in the dust were determined. The results showed that the major and trace elements in the atmospheric dust of Guiyang city vary with the seasons. The concentrations of trace elements in the dust of autumn and winter were significantly higher than those in spring and summer. Most of the major elements in dust were higher than those in the corresponding topsoil, while most trace elements were similar to those in the topsoil except for Pb. The enrichment factor (EF) values calculated by topsoil as background showed that the Ca and Pb have higher EF values than the rest elements, indicating that some dust may be contaminated by Ca and Pb. The high content of Ca in the dust might be derived from concrete buildings in urban areas, while Pb might be closely related to motor vehicle emissions. The relationship between La and Yb of the atmospheric dust showed that the dust in Guiyang have the same pattern as those of Libo, it also revealed that these dust probably come mainly from natural sources and are less affected by human activities.