bluuebunny/crossref_metadata_2025 huggingface dataset:
A comparison of the gene expression profiles and pathway network analyses after treatment of Prostate cancer cell lines with different Ganoderma lucidum based extracts
Authors: Kao Chi H.J. , Bishop Karen S , Han Dug Yeo , Murray Pamela M , Glucina Marcus P. , Marlow Gareth J. , Ferguson Lynnette R
Published: August 2018

Background: Ganoderma lucidum is a type of fungus commonly consumed in Asia for the promotion of health and longevity. The observed biological activity of G. lucidum includes anti-cancer and anti-inflammatory effects which may be useful in the treatment and prevention of cancer and other chronic diseases. G. lucidum grows under conditions which range from tropical to temperate and has a different physiology depending on the geographical region in which it is grown. For this reason, the health benefits may vary depending on the form of G. lucidum and the environmental conditions to which it was exposed. This led us to investigate the effect of wildly grown G. lucidum, from the Himalayan region versus other commercially available G. lucidum products, on two human cancer cell lines.Methods: Extraction of the bioactive components found in G. lucidum is essential, as the fungus is tough and indigestible. Four different Ganoderma extracts were prepared. Thereafter, the extracts were tested on two human prostate cancer cell lines, and the IC50s were determined. This was followed by the use of Affymetrix GeneChip® PrimeView™ Human Gene Expression Arrays to identify the changes in gene expression due to the treatment of prostate cancer cell lines (PC3 and DU145) with Ganoderma extracts. Several key genes identified with Affymetrix analysis were validated using RT-PCR.Results and Discussion: We found that all the Ganoderma extracts showed growth inhibition in the cancer cell lines tested. Using Affymetrix microarray analysis, we identified four main biologically active pathways: cell cycle control/apoptosis, cell-cell adhesion, DNA repair, and inflammatory /immune response, where activity was influenced by the Ganoderma extracts used. Using RT-PCR, we tested ten genes associated with all four pathways. The RT-PCR results supported our findings in the Affymetrix analysis, i.e. that G. lucidum extracts have an anti-inflammatory and cell cycle effect and therefore may have long term health benefits. These effects were specific to the extract tested.Key Words: Ganoderma lucidum, PC3, DU145, gene expression, Affymetrix, pathways, RT-PCR
Enhanced Antibacterial Activity of MGOTM Manuka Honey complexed with a- cyclodextrin (Manuka Honey with CycloPowerTM)
Authors: Swift Simon , Chepulis Lynne M. , Uy Benedict , Radcliff Fiona J
Published: August 2018

Background: Manuka honey is recognized for it’s health-promoting properties and it’s use in medicine is well documented. However, the actions of Manuka honey are limited by rapid digestion and the inactivation of bioactive components such as methylglyoxal. Cyclodextrins are naturally occurring glucose rings that improve stability and bioactivity of products. This study investigates the tolerability and bioactivity of a-cyclodextrin-complexed Manuka honey called Manuka Honey with CycloPower TM.Methods: The antibacterial properties of Manuka honey complexed with a-cyclodextrin (Manuka honey with CyclopowerTM) were compared to uncomplexed Manuka honey against a range of common organisms using standard measurements of minimum inhibitory (MIC) and bactericidal (MBC) concentrations. Time course growth measurements were determined using a sublethal concentration of 2% w (honey solids)/v and measuring the area under the growth curve.Results: In tube MIC assays, Manuka honey completely inhibited Staphylococcus aureus (MSSA and MRSA), Streptococcus pyogenes, Helicobacter pylori and Moraxella catarrhalis at concentrations of 10% w/v or less, with MIC values decreasing as the methylglyoxal content of the honeys increased from 100 to 550 mg/kg. MIC values at a given methlyglyoxal level were also decreased for S. pyogenes, M. catarrhalis and H. pylori by complexing the Manuka honey with a-cyclodextrin. Pseudomonas aeruginosa was not inhibited by any of the Manuka honey or Cyclopower treatments at the concentrations tested (2-10% w/v). Manuka honey with CyclopowerTM had an increased bacteriostatic action against S. aureus, MRSA and P. aeruginosa compared with Manuka honey.Conclusions: This study concludes that Manuka honey is an effective antibacterial agent that can be enhanced by complexing with a-cyclodextrin.Keywords: Manuka honey, methylglyoxal, a-cyclodextrin, antimicrobial
“Weak direct” and “Strong indirect” interactions are the mode of action of food factors
Authors: Konishi Tetsuya
Published: August 2018

Age-dependent and lifestyle related diseases such as metabolic syndromes have become a social problem worldwide. Since these disorders are closely related to dietary lifestyle, the old saying “foods are medicine” is now being re-evaluated. Thus, dietary protection against these diseases is attracting much attention. As research into functional foods advances, a book of knowledge is being accumulated on the active ingredients, termed “food factors”, present in food resources. Identifying such molecules usually follows the conventional methodology used for finding drug candidates from natural resources. The question has arisen as to whether the mode of action of food factors as molecules is the same as that of drugs. In this article, the functional properties of food factors and drugs are comparatively reviewed and the characteristic features of food factor function is discussed, based on the idea of “weak direct” and “strong indirect” actions of food factors to their receptors.Keywords: Food factor; Functional models; Weak direct interaction; Strong indirect interaction; Ligand-receptor interaction
Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms
Authors: Tsai Chi-Yi , Hsu Kuang-Jui , Nisar Humaira
Published: August 2018

Three-Dimensional (3D) object pose estimation plays a crucial role in computer vision because it is an essential function in many practical applications. In this paper, we propose a real-time model-based object pose estimation algorithm, which integrates template matching and Perspective-n-Point (PnP) pose estimation methods to deal with this issue efficiently. The proposed method firstly extracts and matches keypoints of the scene image and the object reference image. Based on the matched keypoints, a two-dimensional (2D) planar transformation between the reference image and the detected object can be formulated by a homography matrix, which can initialize a template tracking algorithm efficiently. Based on the template tracking result, the correspondence between image features and control points of the Computer-Aided Design (CAD) model of the object can be determined efficiently, thus leading to a fast 3D pose tracking result. Finally, the 3D pose of the object with respect to the camera is estimated by a PnP solver based on the tracked 2D-3D correspondences, which improves the accuracy of the pose estimation. Experimental results show that the proposed method not only achieves real-time performance in tracking multiple objects, but also provides accurate pose estimation results. These advantages make the proposed method suitable for many practical applications, such as augmented reality.
Time Series Forecasting Using a Two-Level Multi-Objective Genetic Algorithm: A Case Study of Maintenance Cost Data for Tunnel Fans
Authors: Al-Douri Yamur K. , Hamodi Hussan , Lundberg Jan
Published: August 2018

The aim of this study has been to develop a novel two-level multi-objective genetic algorithm (GA) to optimize time series forecasting data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). Level 1 is for the process of forecasting time series cost data, while level 2 evaluates the forecasting. Level 1 implements either a multi-objective GA based on the ARIMA model or a multi-objective GA based on the dynamic regression model. Level 2 utilises a multi-objective GA based on different forecasting error rates to identify a proper forecasting. Our method is compared with using the ARIMA model only. The results show the drawbacks of time series forecasting using only the ARIMA model. In addition, the results of the two-level model show the drawbacks of forecasting using a multi-objective GA based on the dynamic regression model. A multi-objective GA based on the ARIMA model produces better forecasting results. In level 2, five forecasting accuracy functions help in selecting the best forecasting. Selecting a proper methodology for forecasting is based on the averages of the forecasted data, the historical data, the actual data and the polynomial trends. The forecasted data can be used for life cycle cost (LCC) analysis.
Why Pain Is Still a Welfare Issue for Farm Animals, and How Facial Expression Could Be the Answer
Authors: McLennan Krista Marie
Published: August 2018

Pain is a sensory and emotional experience that significantly affects animal welfare and has negative impacts on the economics of farming. Pain is often associated with common production diseases such as lameness and mastitis, as well as introduced to the animal through routine husbandry practices such as castration and tail docking. Farm animals are prey species which tend not to overtly express pain or weakness, making recognizing and evaluating pain incredibly difficult. Current methods of pain assessment do not provide information on what the animal is experiencing at that moment in time, only that its experience is having a long term negative impact on its behavior and biological functioning. Measures that provide reliable information about the animals’ affective state in that moment are urgently required; facial expression as a pain assessment tool has this ability. Automation of the detection and analysis of facial expression is currently in development, providing further incentive to use these methods in animal welfare assessment.
Impact of High Temperature and Drought Stresses on Chickpea Production
Authors: Devasirvatham Viola , Tan Daniel K. Y.
Published: August 2018

Global climate change has caused severe crop yield losses worldwide and is endangering food security in the future. The impact of climate change on food production is high in Australia and globally. Climate change is projected to have a negative impact on crop production. Chickpea is a cool season legume crop mostly grown on residual soil moisture. High temperature and terminal drought are common in different regions of chickpea production with varying intensities and frequencies. Therefore, stable chickpea production will depend on the release of new cultivars with improved adaptation to major events such as drought and high temperature. Recent progress in chickpea breeding has increased the efficiency of assessing genetic diversity in germplasm collections. This review provides an overview of the integration of new approaches and tools into breeding programs and their impact on the development of stress tolerance in chickpea.
Efficiency of Cassava Production in China: Empirical Analysis of Field Surveys from Six Provinces
Authors: Fu Hailing , Qu Yi , Pan Yi
Published: August 2018

Cassava is becoming increasingly important as an industrial raw material in China. However, an insufficient supply of cassava raw materials and the expanding demand for cassava in downstream-processing industries restricts the development of the cassava industry in China. This paper studies how to increase the scale of cassava planting and promoting cassava production efficiency using output-oriented Data Envelopment Analysis (DEA) modeling. Overall Technical Efficiency (OTE), Pure Technical Efficiency (PTE), and Scale Efficiencies (SE) of the cassava-production system in the major cassava production areas of China are calculated using Variable Returns to Scale (VRS). Results reveal that, in addition to the Guangdong province, the OTE of Guangxi, Hainan, Fujian, Yunnan, and Jiangxi is inefficient, with an OTE of less than 1. The largest cassava-planting province, Guangxi, has the lowest SE with 0.551. The PTE of Guangxi is close to the minimum with 0.344. The OTE of Guangxi is also the lowest among the five provinces with 0.190. This study also presents ways to improve production efficiency. Results reveal that Guangxi has a large ratio of transverse adjustment on average. In the Guangxi province, 1.70% of the service cost and 1.72% of the labor cost need to be eliminated to keep the current output scale. Meanwhile, service and labor costs need to be reduced by 3164.85 and 3209.92, respectively, to achieve the best production efficiency. Further industrialization and large-scale cassava cultivation, increased yield, and strengthened cooperation with the Association of South East Asian Nations (ASEAN) and Africa are suggested as policy options to improve the cassava system in China.
Development of an Internet of Things Based Electrochemical Microfluidic System for Free Calcium Detection
Authors: Yuan Yang , Feng Shilun , Alahi Md Eshrat E , Nag Anindya , Afsarimanesh Nasrin , Zhang Hong , He Shan
Published: August 2018

This paper represents the design, fabrication, and implementation of an Internet of Things (IoT)-based electrochemical microfluidic system for free calcium concentration detection with a 3D printing technique. Free calcium solutions with desired concentrations between 0 and 40 µM can be obtained. The solutions were used to calibrate the system by using an impedance analyzer for monitoring the impedance change to determine the operating frequency. Continuously, an IoT enabled point of care device was used for real-time detection and to send signals to the cloud for sharing. The relationship between the concentration and reactance are y = − 1.3812 Lgx + 0.9809 at a wavelength of 450 Hz, with an R2 of 0.9719. We measured the calcium concentration changing from 39.8 µM to 1.35 µM (nearly real-time) by the PoC device and showed the concentration changes resulting with time on the cell phone app. The results depicted in this paper provide a strong platform for the precise and real-time monitoring of different biomedical samples.
An Experimental Setup with Alternating Current Capability for Evaluating Large Lithium-Ion Battery Cells
Authors: Soares Rudi , Bessman Alexander , Wallmark Oskar , Lindbergh Göran , Svens Pontus
Published: August 2018

In the majority of applications using lithium-ion batteries, batteries are exposed to some harmonic content apart from the main charging/discharging current. The understanding of the effects that alternating currents have on batteries requires specific characterization methods and accurate measurement equipment. The lack of commercial battery testers with high alternating current capability simultaneously to the ability of operating at frequencies above 200 Hz, led to the design of the presented experimental setup. Additionally, the experimental setup expands the state-of-the-art of lithium-ion batteries testers by incorporating relevant lithium-ion battery cell characterization routines, namely hybrid pulse power current, incremental capacity analysis and galvanic intermittent titration technique. In this paper the hardware and the measurement capabilities of the experimental setup are presented. Moreover, the measurements errors due to the setup’s instruments were analysed to ensure lithium-ion batteries cell characterization quality. Finally, this paper presents preliminary results of capacity fade tests where 28 Ah cells were cycled with and without the injection of 21 A alternating at 1 kHz. Up to 300 cycles, no significant fade in cell capacity may be measured, meaning that alternating currents may not be as harmful for lithium-ion batteries as considered so far.
Advanced Dynamic Cell and Tissue Culture
Authors: Hansmann Jan , Egger Dominik , Kasper Cornelia
Published: August 2018

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Constructing A Rational Kinetic Model of the Selective Propane Oxidation Over A Mixed Metal Oxide Catalyst
Authors: Sprung Christoph , Yablonsky Gregory S. , Schlögl Robert , Trunschke Annette
Published: August 2018

This research presents a kinetic investigation of the selective oxidation of propane to acrylic acid over a MoVTeNb oxide (M1 phase) catalyst. The paper contains both an overview of the related literature, and original results with a focus on kinetic aspects. Two types of kinetic experiments were performed in a plug flow reactor, observing (i) steady-state conditions (partial pressure variations) and (ii) the catalyst evolution as a function of time-on-stream. For this, the catalyst was treated in reducing atmosphere, before re-oxidising it. These observations in long term behaviour were used to distinguish different catalytic routes, namely for the formation of propene, acetic acid, acrylic acid, carbon monoxide and carbon dioxide. A partial carbon balance was introduced, which is a ‘kinetic fingerprint’, that distinguishes one type of active site from another. Furthermore, an ‘active site’ was found to consist of one or more ‘active centres’. A rational mechanism was developed based on the theory of graphs and includes two time scales belonging to (i) the catalytic cycle and (ii) the catalyst evolution. Several different types of active sites exist, at least as many, as kinetically independent product molecules are formed over a catalyst surface.
Modeling and Simulation of a Novel Combined Solar Photovoltaic-Thermal Panel and Heat Pump Hybrid System
Authors: Sami Samuel
Published: August 2018

A numerical simulation model for a novel concept of a hybrid composed of photovoltaic-thermal solar panels and a heat pump is presented. This concept was developed to assess the performance and energy conversion efficiency of the hybrid system used to produce domestic hot water and electricity. A two-dimensional heat transfer and fluid flow dynamic model was developed to describe the behavior of the hybrid system under different solar irradiance, heat pump boundary conditions and different refrigerants. The model is based on dynamic mass and energy equations coupled with the heat transfer coefficients, and the thermodynamic properties of refrigerants as well as material properties. The model compared fairly to experimental data.
Post-Depositional Biodegradation Processes of Pollutants on Glacier Surfaces
Authors: Pittino Francesca , Ambrosini Roberto , Azzoni Roberto S. , Diolaiuti Guglielmina A. , Villa Sara , Gandolfi Isabella , Franzetti Andrea
Published: August 2018

Glaciers are important fresh-water reservoirs for our planet. Although they are often located at high elevations or in remote areas, glacial ecosystems are not pristine, as many pollutants can undergo long-range atmospheric transport and be deposited on glacier surface, where they can be stored for long periods of time, and then be released into the down-valley ecosystems. Understanding the dynamics of these pollutants in glaciers is therefore important for assessing their environmental fate. To this aim, it is important to study cryoconite holes, small ponds filled with water and with a layer of sediment, the cryoconite, at the bottom, which occur on the surface of most glaciers. Indeed, these environments are hotspots of biodiversity on glacier surface as they host metabolically active bacterial communities that include generalist taxa able to degrade pollutants. In this work, we aim to review the studies that have already investigated pollutant (e.g., chlorpyrifos and polychlorinated-biphenyls (PCBs)) degradation in cryoconite holes and other supraglacial environmental matrices. These studies have revealed that bacteria play a significant role in pollutant degradation in these habitats and can be positively selected in contaminated environments. We will also provide indication for future research in this field.
The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company
Authors: Ugurlu Umut , Tas Oktay , Kaya Aycan , Oksuz Ilkay
Published: August 2018

Electricity price forecasting has a paramount effect on generation companies (GenCos) due to the scheduling of the electricity generation scheme according to electricity price forecasts. Inaccurate electricity price forecasts could cause important loss of profits to the suppliers. In this paper, the financial effect of inaccurate electricity price forecasts on a hydro-based GenCo is examined. Electricity price forecasts of five individual and four hybrid forecast models and the ex-post actual prices are used to schedule the hydro-based GenCo using Mixed Integer Linear Programming (MILP). The financial effect measures of profit loss, Economic Loss Index (ELI) and Price Forecast Disadvantage Index (PFDI), as well as Mean Absolute Error (MAE) of the models are used for comparison of the data from 24 weeks of the year. According to the results, a hybrid model, 50% Artificial Neural Network (ANN)–50% Long Short Term Memory (LSTM), has the best performance in terms of financial effect. Furthermore, the forecast performance evaluation methods, such as Mean Absolute Error (MAE), are not necessarily coherent with inaccurate electricity price forecasts’ financial effect measures.
Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs
Authors: Ni Chenhua , Ma Xiandong
Published: August 2018

Successful development of a marine wave energy converter (WEC) relies strongly on the development of the power generation device, which needs to be efficient and cost-effective. An innovative multi-input approach based on the Convolutional Neural Network (CNN) is investigated to predict the power generation of a WEC system using a double-buoy oscillating body device (OBD). The results from the experimental data show that the proposed multi-input CNN performs much better at predicting results compared with the conventional artificial network and regression models. Through the power generation analysis of this double-buoy OBD, it shows that the power output has a positive correlation with the wave height when it is higher than 0.2 m, which becomes even stronger if the wave height is higher than 0.6 m. Furthermore, the proposed approach associated with the CNN algorithm in this study can potentially detect the changes that could be due to presence of anomalies and therefore be used for condition monitoring and fault diagnosis of marine energy converters. The results are also able to facilitate controlling of the electricity balance among energy conversion, wave power produced and storage.
A Novel Computational Approach for Harmonic Mitigation in PV Systems with Single-Phase Five-Level CHBMI
Authors: Miceli Rosario , Schettino Giuseppe , Viola Fabio
Published: August 2018

In this paper, a novel approach to low order harmonic mitigation in fundamental switching frequency modulation is proposed for high power photovoltaic (PV) applications, without trying to solve the cumbersome non-linear transcendental equations. The proposed method allows for mitigation of the first-five harmonics (third, fifth, seventh, ninth, and eleventh harmonics), to reduce the complexity of the required procedure and to allocate few computational resource in the Field Programmable Gate Array (FPGA) based control board. Therefore, the voltage waveform taken into account is different respect traditional voltage waveform. The same concept, known as “voltage cancelation”, used for single-phase cascaded H-bridge inverters, has been applied at a single-phase five-level cascaded H-bridge multilevel inverter (CHBMI). Through a very basic methodology, the polynomial equations that drive the control angles were detected for a single-phase five-level CHBMI. The acquired polynomial equations were implemented in a digital system to real-time operation. The paper presents the preliminary analysis in simulation environment and its experimental validation.
Electromechanical Transient Modeling of Line Commutated Converter-Modular Multilevel Converter-Based Hybrid Multi-Terminal High Voltage Direct Current Transmission Systems
Authors: Xiao Liang , Li Yan , Xiao Huangqing , Zhang Zheren , Xu Zheng
Published: August 2018

A method for electromechanical modeling of line commutated converter (LCC)-modular multilevel converter (MMC)-based hybrid multi-terminal High Voltage Direct Current Transmission (HVDC) systems for large-scale power system transient stability study is proposed. Firstly, the general idea of modeling the LCC-MMC hybrid multi-terminal HVDC system is presented, then the AC-side and DC-side models of the LCC/MMC are established. Different from the conventional first-order DC-side model of the MMC, an improved second-order DC-side model of the MMC is established. Besides considering the firing angle limit of the LCC, a sequential power flow algorithm is proposed for the initialization of LCC-MMC hybrid multi-terminal HVDC system. Lastly, simulations of small scale and large scale power systems embedded with a three-terminal LCC-MMC hybrid HVDC system are performed on the electromechanical simulation platform PSS/E. It is demonstrated that if the firing angle limit is not considered, the accuracy of the power flow solutions will be greatly affected. Steady state calculation and dynamic simulation show that the developed LCC-MMC hybrid MTDC model is accurate enough for electromechanical transient stability studies of large-scale AC/DC system.
SOLIS—A Novel Decision Support Tool for the Assessment of Solar Radiation in ArcGIS
Authors: Kazak Jan K. , Świąder Małgorzata
Published: August 2018

The global Sustainable Development Goals influence the implementation of energy development strategies worldwide. However, in order to support local stakeholders in sustainable energy development strategies and climate change adaptation plans and the implementation of policies, there is a need to equip local decision makers with tools enabling the assessment of sustainable energy investments. In order to do so, the aim of this study is to create a novel tool for the assessment of solar radiation (SOLIS) in ArcGIS. The SOLIS tool builds on the existing ArcGIS algorithm by including input data conversion and post-processing of the results. This should expand the group of potential users of solar radiation analyses. The self-filtering tool excludes surfaces that are not suitable for solar energy investments due to geometrical reasons. The reduction of the size of the output data is positive for technical reasons (speed of the calculation and occupied storage place) and for cognitive reasons (reduction of the number of objects necessary to analyse by the user). The SOLIS tool limits the requirement for users to insert three-dimensional (3D) models of roofs (with any geometry) and select solar radiation calculation periods. The highlight of this research is to develop the decision support tool for the assessment of solar radiation, which would reduce the requirements for potential users, in order to promote indicator-based assessments among non-Geographical Information Systems (GIS) specialists.
Determinants of Above-Ground Biomass and Its Spatial Variability in a Temperate Forest Managed for Timber Production
Authors: Soriano-Luna María de los Ángeles , Ángeles-Pérez Gregorio , Guevara Mario , Birdsey Richard , Pan Yude , Vaquera-Huerta Humberto , Valdez-Lazalde José René , Johnson Kristofer D. , Vargas Rodrigo
Published: August 2018

The proper estimation of above-ground biomass (AGB) stocks of managed forests is a prerequisite to quantifying their role in climate change mitigation. The aim of this study was to analyze the spatial variability of AGB and its uncertainty between actively managed pine and unmanaged pine-oak reference forests in central Mexico. To investigate the determinants of AGB, we analyzed variables related to forest management, stand structure, topography, and climate. We developed linear (LM), generalized additive (GAM), and Random Forest (RF) empirical models to derive spatially explicit estimates and their uncertainty, and compared them. AGB was strongly influenced by forest management, as LiDAR-derived stand structure and stand age explained 80.9% to 89.8% of its spatial variability. The spatial heterogeneity of AGB varied positively with stand structural complexity and age in the managed forests. The type of predictive model had an impact on estimates of total AGB in our study site, which varied by as much as 19%. AGB densities varied from 0 to 492 ± 17 Mg ha−1 and the highest values were predicted by GAM. Uncertainty was not spatially homogeneously distributed and was higher with higher AGB values. Spatially explicit AGB estimates and their association with management and other variables in the study site can assist forest managers in planning thinning and harvesting schedules that would maximize carbon stocks on the landscape while continuing to provide timber and other ecosystem services. Our study represents an advancement toward the development of efficient strategies to spatially estimate AGB stocks and their uncertainty, as the GAM approach was used for the first time with improved results for such a purpose.
Using the Mutation-Selection Framework to Characterize Selection on Protein Sequences
Authors: Teufel Ashley I. , Ritchie Andrew M. , Wilke Claus O. , Liberles David A.
Published: August 2018

When mutational pressure is weak, the generative process of protein evolution involves explicit probabilities of mutations of different types coupled to their conditional probabilities of fixation dependent on selection. Establishing this mechanistic modeling framework for the detection of selection has been a goal in the field of molecular evolution. Building on a mathematical framework proposed more than a decade ago, numerous methods have been introduced in an attempt to detect and measure selection on protein sequences. In this review, we discuss the structure of the original model, subsequent advances, and the series of assumptions that these models operate under.
Relationship between SHARE-FI Frailty Scores and Physical Performance Measures in Older Adult Medicaid Recipients
Authors: Danilovich Margaret K. , Diaz Laura , Corcos Daniel M. , Ciolino Jody D.
Published: August 2018

The Survey of Health, Ageing and Retirement in Europe-Frailty Instrument (SHARE-FI) is a frailty assessment tool designed for primary care settings comprised of four self-report questions and grip strength measurement, yet it is not known how SHARE-FI scores relate to objective physical performance measures that assess physical functioning, fall risk, and disability. This cross-sectional, observational study examined the association between SHARE-FI scores and a battery of physical performance measures in a sample of older adult, Medicaid waiver recipients (n = 139, mean age = 74.19 ± 8.36 years). We administered the SHARE-FI, Timed Up and Go (TUG), gait speed, and Short Physical Performance Battery (SPPB) in participants’ homes. Among clients, 45% were frail, 35% pre-frail, and 20% non-frail. There were significant differences in all physical performance measure scores with respect to SHARE-FI category. SHARE-FI continuous scores significantly predicted TUG time, all domains of the SPPB, gait speed, and inability to complete the chair rise test. Self-reported walking difficulty and objectively measured gait speed were significantly correlated. The SHARE-FI continuous frailty score predicts scores on a variety of validated physical performance measures. Given the fast administration time, the SHARE-FI could potentially be used to serve as a surrogate for physical performance measures with known association with physical function, fall risk, and disability.
Victorian Murder and the Digital Humanities
Authors: McCaw Neil
Published: August 2018

The rapid extension of what has become known as the Digital Humanities has resulted in an array of online resources for researchers within the subdiscipline of Victorian Studies. But the increasingly acquisitive nature of these digital projects poses the question as to what happens once all the information and material we have related to the Victorians has been archived? This paper is an attempt to anticipate this question with specific reference to future digital resources for the study of ‘Victorian murder culture’, and in particular, the essentially textual nature of the nineteenth-century experience of crime. It will argue that there is potential for new forms of digital-humanities archive that offer a more participatory user experience, one that nurtures a cognitively empathic understanding of the complex intertextuality of Victorian crime culture.
Evolution Characteristics of Surface Water Quality Due to Climate Change and LUCC under Scenario Simulations: A Case Study in the Luanhe River Basin
Authors: Bi Wuxia , Weng Baisha , Yuan Zhe , Ye Mao , Zhang Cheng , Zhao Yu , Yan Dengming , Xu Ting
Published: August 2018

It is of great significance to study the effects and mechanisms of the key driving forces of surface water quality deterioration—climate change and LUCC (land use and land cover change). The Luanhe River Basin (LRB) in north-eastern China was examined for qualitatively and quantitatively assessing the responses of total nitrogen (TN) and total phosphorus (TP) loads on different climate scenarios and LUCC scenarios. The results show that from 1963 to 2017, the TN and TP loads basically presented a negative correlation with the temperature change (except for winter), while showing a significant positive correlation with the precipitation change. The incidence of TN pollution is sensitive to temperature increase. From 2020 to 2050, the annual average loads of TN and TP were slightly lower than from 1963 to 2017. The contribution of rising temperature was more significant on nutrient loads. Also, the incidence of TN pollution is sensitive to the future climate change. Under LUCC scenarios, the TN and TP loads and pollution incidence increased correspondingly with the decrease of natural land. The evolution characteristics analysis can provide support for the effect and adaptation-strategies study of climate change and LUCC on surface water quality.
Detailed Assessment of the Spatial Distribution of Urban Parks According to Day and Travel Mode Based on Web Mapping API: A Case Study of Main Parks in Wuhan
Authors: Niu Qiang , Wang Ye , Xia Yuan , Wu Hao , Tang Xi
Published: August 2018

This article employs two indexes—accessibility and effective service ratio (ESR)—to assess the spatial distribution of urban parks with the consideration of both equity and efficiency. Traditional approaches to calculate these two indexes are often based on the shortest distance to the park within its service radius by network analysis. Such approaches cannot reflect the actual travel behaviors of urban residents and require extensive data collection of road networks and complex parameter setting. To avoid these defects, this study directly acquires travel time data for various travel modes in a specific time period to the park through web mapping API (Application Program Interface), then calculates the accessibility and ESR of urban parks based on these detailed data. This method gets closer to actual park usage situation and avoids the cumbersome process of road network model building. At last, a case study is conducted on the assessment of spatial distribution of main parks in Wuhan, finding that districts with poor park accessibility in Wuhan can be divided into three types: districts with an absence of parks, districts with an insufficiency with parks, and districts separated from parks by traffic. Then, pertinent improvement suggestions are proposed, which provide some bases for decisions on future park planning and construction.
On the Nature of Evidence and ‘Proving’ Causality: Smoking and Lung Cancer vs. Sun Exposure, Vitamin D and Multiple Sclerosis
Authors: Lucas Robyn M. , Rodney Harris Rachael M.
Published: August 2018

If environmental exposures are shown to cause an adverse health outcome, reducing exposure should reduce the disease risk. Links between exposures and outcomes are typically based on ‘associations’ derived from observational studies, and causality may not be clear. Randomized controlled trials to ‘prove’ causality are often not feasible or ethical. Here the history of evidence that tobacco smoking causes lung cancer—from observational studies—is compared to that of low sun exposure and/or low vitamin D status as causal risk factors for the autoimmune disease, multiple sclerosis (MS). Evidence derives from in vitro and animal studies, as well as ecological, case-control and cohort studies, in order of increasing strength. For smoking and lung cancer, the associations are strong, consistent, and biologically plausible—the evidence is coherent or ‘in harmony’. For low sun exposure/vitamin D as risk factors for MS, the evidence is weaker, with smaller effect sizes, but coherent across a range of sources of evidence, and biologically plausible. The association is less direct—smoking is directly toxic and carcinogenic to the lung, but sun exposure/vitamin D modulate the immune system, which in turn may reduce the risk of immune attack on self-proteins in the central nervous system. Opinion about whether there is sufficient evidence to conclude that low sun exposure/vitamin D increase the risk of multiple sclerosis, is divided. General public health advice to receive sufficient sun exposure to avoid vitamin D deficiency (<50 nmol/L) should also ensure any benefits for multiple sclerosis, but must be tempered against the risk of skin cancers.
Using Calcination Remediation to Stabilize Heavy Metals and Simultaneously Remove Polycyclic Aromatic Hydrocarbons in Soil
Authors: Wang Peixin , Hu Xiaojie , He Qianjia , Waigi Michael Gatheru , Wang Jian , Ling Wanting
Published: August 2018

Co-contaminated soils containing heavy metals and polycyclic aromatic hydrocarbons (PAHs) are an environmental and human health risk. Research into the remediation of these soils is imperative. In this paper, a novel investigation utilizing calcination technique to stabilize heavy metals and simultaneously remove PAHs in soil was conducted. Calcination temperature (300–700 °C) was observed to play a dominant role in heavy metal stabilization and PAH removal in soils. However, calcination time (0.5–8 h) had no significant effect on these contaminants during calcination at different temperatures. Considering the remediation cycle requirements and economic costs of engineering, we suggested that the optimal calcination condition for Zn, Cu, naphthalene, and fluoranthene was at 700 °C for 0.5 h, and the corresponding stabilization or removal efficiency values were 96.95%, 98.41%, 98.49%, and 98.04%, respectively. Results indicate that calcination as a remedial strategy exhibits a bright future for practical applications in the simultaneous stabilization of heavy metals and PAH removal from co-contaminated sites.
A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases
Authors: Wang Xueli , Zhou Moqin , Jia Jinzhu , Geng Zhi , Xiao Gexin
Published: August 2018

Foodborne diseases have a big impact on public health and are often underreported. This is because a lot of patients delay treatment when they suffer from foodborne diseases. In Hunan Province (China), a total of 21,226 confirmed foodborne disease cases were reported from 1 March 2015 to 28 February 2016 by the Foodborne Surveillance Database (FSD) of the China National Centre for Food Safety Risk Assessment (CFSA). The purpose of this study was to make use of the daily number of visiting patients to forecast the daily true number of patients. Our main contribution is that we take the reporting delays into consideration and apply a Bayesian hierarchical model for this forecast problem. The data shows that there were 21,226 confirmed cases reported among 21,866 visiting patients, a proportion as high as 97%. Given this observation, the Bayesian hierarchical model was established to predict the daily true number of patients using the number of visiting patients. We propose several scoring rules to assess the performance of different nowcasting procedures. We conclude that Bayesian nowcasting with consideration of right truncation of the reporting delays has a good performance for short-term forecasting, and could effectively predict the epidemic trends of foodborne diseases. Meanwhile, this approach could provide a methodological basis for future foodborne disease monitoring and control strategies, which are crucial for public health.
Exploring the Dynamic Links between GCC Sukuk and Commodity Market Volatility
Authors: Naifar Nader
Published: August 2018

This study investigates the impact of commodity price volatility (including soft commodities, precious metals, industrial metals, and energy) on the dynamics of corporate sukuk returns. Using a sample of sukuk indices from Gulf Cooperation Council (GCC) countries, we study the dynamic conditional correlation using a multivariate generalized autoregressive conditional heteroskedasticity dynamic conditional correlation (GARCH-DCC) process. Empirical results show a time-varying negative correlation between GCC sukuk returns and commodity prices. In fact, a negative conditional correlation among assets of a given portfolio implies higher gain-to-risk ratios. An understanding of volatility and dynamic co-movements in financial and commodity markets is important for portfolio allocation and risk management practices.
Transcriptome Analysis of JA Signal Transduction, Transcription Factors, and Monoterpene Biosynthesis Pathway in Response to Methyl Jasmonate Elicitation in Mentha canadensis L.
Authors: Qi Xiwu , Fang Hailing , Yu Xu , Xu Dongbei , Li Li , Liang Chengyuan , Lu Hongfei , Li Weilin , Chen Yin , Chen Zequn
Published: August 2018

Mentha canadensis L. has important economic value for its abundance in essential oils. Menthol is the main component of M. canadensis essential oils, which is certainly the best-known monoterpene for its simple structure and wide applications. However, the regulation of menthol biosynthesis remains elusive in M. canadensis. In this study, transcriptome sequencing of M. canadensis with MeJA treatment was applied to illustrate the transcriptional regulation of plant secondary metabolites, especially menthol biosynthesis. Six sequencing libraries were constructed including three replicates for both control check (CK) and methyl jasmonate (MeJA) treatment and at least 8 Gb clean bases was produced for each library. After assembly, a total of 81,843 unigenes were obtained with an average length of 724 bp. Functional annotation indicated that 64.55% of unigenes could be annotated in at least one database. Additionally, 4430 differentially expressed genes (DEGs) with 2383 up-regulated and 2047 down-regulated transcripts were identified under MeJA treatment. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment indicated that “Monoterpenoid biosynthesis” was one of the most significantly enriched pathways in metabolism. Subsequently, DEGs involved in JA signal transduction, transcription factors, and monoterpene biosynthesis were analyzed. 9 orthologous genes involved in menthol biosynthesis were also identified. This is the first report of a transcriptome study of M. canadensis and will facilitate the studies of monoterpene biosynthesis in the genus Mentha.
ATP as a Pathophysiologic Mediator of Bacteria-Host Crosstalk in the Gastrointestinal Tract
Authors: Inami Akie , Kiyono Hiroshi , Kurashima Yosuke
Published: August 2018

Extracellular nucleotides, such as adenosine triphosphate (ATP), are released from host cells including nerve termini, immune cells, injured or dead cells, and the commensal bacteria that reside in the gut lumen. Extracellular ATP interacts with the host through purinergic receptors, and promotes intercellular and bacteria-host communication to maintain the tissue homeostasis. However, the release of massive concentrations of ATP into extracellular compartments initiates acute and chronic inflammatory responses through the activation of immunocompetent cells (e.g., T cells, macrophages, and mast cells). In this review, we focus on the functions of ATP as a pathophysiologic mediator that is required for the induction and resolution of inflammation and inter-species communication.
Prostanoid EP2 Receptors Are Up-Regulated in Human Pulmonary Arterial Hypertension: A Key Anti-Proliferative Target for Treprostinil in Smooth Muscle Cells
Authors: Patel Jigisha A. , Shen Lei , Hall Susan M. , Benyahia Chabha , Norel Xavier , McAnulty Robin J. , Moledina Shahin , Silverstein Adam M. , Whittle Brendan J. , Clapp Lucie H.
Published: August 2018

Prostacyclins are extensively used to treat pulmonary arterial hypertension (PAH), a life-threatening disease involving the progressive thickening of small pulmonary arteries. Although these agents are considered to act therapeutically via the prostanoid IP receptor, treprostinil is the only prostacyclin mimetic that potently binds to the prostanoid EP2 receptor, the role of which is unknown in PAH. We hypothesised that EP2 receptors contribute to the anti-proliferative effects of treprostinil in human pulmonary arterial smooth muscle cells (PASMCs), contrasting with selexipag, a non-prostanoid selective IP agonist. Human PASMCs from PAH patients were used to assess prostanoid receptor expression, cell proliferation, and cyclic adenosine monophosphate (cAMP) levels following the addition of agonists, antagonists or EP2 receptor small interfering RNAs (siRNAs). Immunohistochemical staining was performed in lung sections from control and PAH patients. We demonstrate using selective IP (RO1138452) and EP2 (PF-04418948) antagonists that the anti-proliferative actions of treprostinil depend largely on EP2 receptors rather than IP receptors, unlike MRE-269 (selexipag-active metabolite). Likewise, EP2 receptor knockdown selectively reduced the functional responses to treprostinil but not MRE-269. Furthermore, EP2 receptor levels were enhanced in human PASMCs and in lung sections from PAH patients compared to controls. Thus, EP2 receptors represent a novel therapeutic target for treprostinil, highlighting key pharmacological differences between prostacyclin mimetics used in PAH.
The Regulation and Function of the L-Type Amino Acid Transporter 1 (LAT1) in Cancer
Authors: Salisbury Travis B , Arthur Subha
Published: August 2018

The progression of cancer is associated with increases in amino acid uptake by cancer cells. Upon their entry into cells through specific transporters, exogenous amino acids are used to synthesize proteins, nucleic acids and lipids and to generate ATP. The essential amino acid leucine is also important for maintaining cancer-associated signaling pathways. By upregulating amino acid transporters, cancer cells gain greater access to exogenous amino acids to support chronic proliferation, maintain metabolic pathways, and to enhance certain signal transduction pathways. Suppressing cancer growth by targeting amino acid transporters will require an in-depth understanding of how cancer cells acquire amino acids, in particular, the transporters involved and which cancer pathways are most sensitive to amino acid deprivation. L-Type Amino Acid Transporter 1 (LAT1) mediates the uptake of essential amino acids and its expression is upregulated during the progression of several cancers. We will review the upstream regulators of LAT1 and the downstream effects caused by the overexpression of LAT1 in cancer cells.