bluuebunny/crossref_metadata_2025 huggingface dataset:
The Progress of Investigating the CD137-CD137L Axis as a Potential Target for Systemic Lupus Erythematosus
Authors: Mak Anselm , Schwarz Herbert
Published: September 2019

Costimulatory molecules facilitate cross-talks among leukocytes via mutual stimulatory and inhibitory signalling, contributing to diverse immunological outcomes in normal physiological responses and pathological conditions. Systemic lupus erythematosus (SLE) is a complex multi-systemic autoimmune condition in which cellular communication through the involvement of costimulatory molecules is crucial in driving proinflammatory responses from the stage of autoantigen presentation to the subsequent process of pathogenic autoantibody production. While the physiology of the costimulatory systems including OX40-OX40L, CD28/CTLA-4-CD80/86, ICOS-B7RP1 and CD70-CD27 has been relatively well studied in SLE, recent data on the immunopathology of the CD137-CD137 ligand (CD137L) system in murine lupus models and patients with SLE highlight the critical role of this costimulatory system in initiating and perpetuating the diverse clinical and serological phenotypes of SLE. CD137, a membrane-bound receptor which belongs to the tumour necrosis factor receptor superfamily, is mainly expressed on activated T cells. Activation of the CD137 receptor via its interaction with CD137L which is expressed on antigen present cells (APC) including B cells, triggers bi-directional signalling; that is, signalling through CD137 as well as signalling through CD137L (reverse signalling), which further activates T cells and polarizes them to the Th1/Tc1 pathway. Further, via reverse CD137L signalling it enhances differentiation and maturation of the APC, particularly of dendritic cells, which subsequently drive proinflammatory cytokine production. In this review, recent data including our experience in the manipulation of CD137L signalling pertaining to the pathophysiology of SLE will be critically reviewed. More in-depth understanding of the biology of the CD137-CD137L co-stimulation system opens an opportunity to identify new prognostic biomarkers and the design of novel therapeutic approaches for advancing the management of SLE.
The Role of PARPs in Inflammation—And Metabolic—Related Diseases: Molecular Mechanisms and Beyond
Authors: Ke Yueshuang , Wang Chenxin , Zhang Jiaqi , Zhong Xiyue , Wang Ruoxi , Zeng Xianlu , Ba Xueqing
Published: September 2019

Poly(ADP-ribosyl)ation (PARylation) is an essential post-translational modification catalyzed by poly(ADP-ribose) polymerase (PARP) enzymes. Poly(ADP-ribose) polymerase 1 (PARP1) is a well-characterized member of the PARP family. PARP1 plays a crucial role in multiple biological processes and PARP1 activation contributes to the development of various inflammatory and malignant disorders, including lung inflammatory disorders, cardiovascular disease, ovarian cancer, breast cancer, and diabetes. In this review, we will focus on the role and molecular mechanisms of PARPs enzymes in inflammation- and metabolic-related diseases. Specifically, we discuss the molecular mechanisms and signaling pathways that PARP1 is associated with in the regulation of pathogenesis. Recently, increasing evidence suggests that PARP inhibition is a promising strategy for intervention of some diseases. Thus, our in-depth understanding of the mechanism of how PARPs are activated and how their signaling downstream effecters can provide more potential therapeutic targets for the treatment of the related diseases in the future is crucial.
Identification of Transcriptional Markers and microRNA–mRNA Regulatory Networks in Colon Cancer by Integrative Analysis of mRNA and microRNA Expression Profiles in Colon Tumor Stroma
Authors: Uddin Md. Nazim , Li Mengyuan , Wang Xiaosheng
Published: September 2019

The aberrant expression of microRNAs (miRNAs) and genes in tumor microenvironment (TME) has been associated with the pathogenesis of colon cancer. An integrative exploration of transcriptional markers (gene signatures) and miRNA–mRNA regulatory networks in colon tumor stroma (CTS) remains lacking. Using two datasets of mRNA and miRNA expression profiling in CTS, we identified differentially expressed miRNAs (DEmiRs) and differentially expressed genes (DEGs) between CTS and normal stroma. Furthermore, we identified the transcriptional markers which were both gene targets of DEmiRs and hub genes in the protein–protein interaction (PPI) network of DEGs. Moreover, we investigated the associations between the transcriptional markers and tumor immunity in colon cancer. We identified 17 upregulated and seven downregulated DEmiRs in CTS relative to normal stroma based on a miRNA expression profiling dataset. Pathway analysis revealed that the downregulated DEmiRs were significantly involved in 25 KEGG pathways (such as TGF-β, Wnt, cell adhesion molecules, and cytokine–cytokine receptor interaction), and the upregulated DEmiRs were involved in 10 pathways (such as extracellular matrix (ECM)-receptor interaction and proteoglycans in cancer). Moreover, we identified 460 DEGs in CTS versus normal stroma by a meta-analysis of two gene expression profiling datasets. Among them, eight upregulated DEGs were both hub genes in the PPI network of DEGs and target genes of the downregulated DEmiRs. We found that three of the eight DEGs were negative prognostic factors consistently in two colon cancer cohorts, including COL5A2, EDNRA, and OLR1. The identification of transcriptional markers and miRNA–mRNA regulatory networks in CTS may provide insights into the mechanism of tumor immune microenvironment regulation in colon cancer.
Enhanced Feature Subset Selection Using Niche Based Bat Algorithm
Authors: Saleem Noman , Zafar Kashif , Sabzwari Alizaa
Published: September 2019

Redundant and irrelevant features disturb the accuracy of the classifier. In order to avoid redundancy and irrelevancy problems, feature selection techniques are used. Finding the most relevant feature subset that can enhance the accuracy rate of the classifier is one of the most challenging parts. This paper presents a new solution to finding relevant feature subsets by the niche based bat algorithm (NBBA). It is compared with existing state of the art approaches, including evolutionary based approaches. The multi-objective bat algorithm (MOBA) selected 8, 16, and 248 features with 93.33%, 93.54%, and 78.33% accuracy on ionosphere, sonar, and Madelon datasets, respectively. The multi-objective genetic algorithm (MOGA) selected 10, 17, and 256 features with 91.28%, 88.70%, and 75.16% accuracy on same datasets, respectively. Finally, the multi-objective particle swarm optimization (MOPSO) selected 9, 21, and 312 with 89.52%, 91.93%, and 76% accuracy on the above datasets, respectively. In comparison, NBBA selected 6, 19, and 178 features with 93.33%, 95.16%, and 80.16% accuracy on the above datasets, respectively. The niche multi-objective genetic algorithm selected 8, 15, and 196 features with 93.33%, 91.93%, and 79.16 % accuracy on the above datasets, respectively. Finally, the niche multi-objective particle swarm optimization selected 9, 19, and 213 features with 91.42%, 91.93%, and 76.5% accuracy on the above datasets, respectively. Hence, results show that MOBA outperformed MOGA and MOPSO, and NBBA outperformed the niche multi-objective genetic algorithm and the niche multi-objective particle swarm optimization.
Efficient and Flexible Multi-Factor Authentication Protocol Based on Fuzzy Extractor of Administrator’s Fingerprint and Smart Mobile Device
Authors: Mohammed Alzahraa J. , Yassin Ali A.
Published: September 2019

In an era of tremendous development in information technology and the Internet of Things (IoT), security plays a key role in safety devices connected with the Internet. Authentication is vital in the security field, and to achieve a strong authentication scheme, there are several systems using a Multi-Factor Authentication (MFA) scheme based on a smart card, token, and biometric. However, these schemes have suffered from the extra cost; lost, stolen or broken factor, and malicious attacks. In this paper, we design an MFA protocol to be the authenticated administrator of IoT’s devices. The main components of our protocol are a smart mobile device and the fuzzy extractor of the administrator’s fingerprint. The information of the authenticated user is stored in an anomalous manner in mobile devices and servers to resist well-known attacks, and, as a result, the attacker fails to authenticate the system when they obtain a mobile device or password. Our work overcomes the above-mentioned issues and does not require extra cost for a fingerprint device. By using the AVISPA tool to analysis protocol security, the results are good and safe against known attacks.
The Field-Induced Stop-Bands and Lasing Modes in CLC Layers with Deformed Lying Helix
Authors: Palto Serguei P.
Published: September 2019

Waveguide optical properties of a cholesteric liquid crystal (CLC) layer with a deformed lying helix (DLH) have been studied by numerical simulations using the finite difference time domain method. The DLH structure, when the helix’s axis is oriented in plane of a CLC layer, is induced by an electric field in a virtual CLC cell with periodic (planar/homeotropic) boundary conditions at one of the alignment surfaces. This in-plane helical structure is stable only in a permanently applied electric field providing the helix deformation. In this work the polarized light reflectance spectra have been studied at different electric fields and light impingement into a waveguide formed by the DLH layer. It is found that for light propagating along the helix axis the reflectance spectrum has multiple stop-bands centred at wavelengths λ j = 2 p ⟨ n ⟩ j , which is different from set of bands located at λ j = p ⟨ n ⟩ j , and characteristic of CLC spectra for the Grandjean-plane textures subjected to distortion by an electric or magnetic field perpendicular to the helix axis, where j is a natural number, p is the helix pitch and ⟨ n ⟩ is the average refractive index. Each of the higher order (j > 1) bands consists of three polarization-dependent sub-bands. In the case of an amplifying CLC DLH layer, depending on an extent of the helix deformation, the lasing modes can be excited at different edges of the sub-bands. While at the strongest deformation the lasing is preferable at the edges of the central sub-band; a lower extent of deformation makes favourable conditions for the lasing at edges of the two other sub-bands.
Phylogenetic Diversity of Archaea in Shallow Hydrothermal Vents of Eolian Islands, Italy
Authors: Gugliandolo Concetta , Maugeri Teresa L.
Published: September 2019

Shallow hydrothermal systems (SHS) around the Eolian Islands (Italy), related to both active and extinct volcanism, are characterized by high temperatures, high concentrations of CO2 and H2S, and low pH, prohibitive for the majority of eukaryotes which are less tolerant to the extreme conditions than prokaryotes. Archaea and bacteria are the key elements for the functioning of these ecosystems, as they are involved in the transformation of inorganic compounds released from the vent emissions and are at the basis of the hydrothermal system food web. New extremophilic archaea (thermophilic, hyperthermophilic, acidophilic, alkalophilic, etc.) have been isolated from vents of Vulcano Island, exhibiting interesting features potentially valuable in biotechnology. Metagenomic analyses, which mainly involved molecular studies of the 16S rRNA gene, provided different insights into microbial composition associated with Eolian SHS. Archaeal community composition at Eolian vent sites results greatly affected by the geochemistry of the studied vents, principally by hypersaline conditions and declining temperatures. Archaeal community in sediments was mostly composed by hyperthermophilic members of Crenarchaeota (class Thermoprotei) and Euryarchaeota (Thermococci and Methanococci) at the highest temperature condition. Mesophilic Euryarchaeota (Halobacteria, Methanomicrobia, and Methanobacteria) increased with decreasing temperatures. Eolian SHS harbor a high diversity of largely unknown archaea, and the studied vents may be an important source of new isolates potentially useful for biotechnological purposes.
Influence of Forest Structure and Composition on Summer Habitat Use of Wildlife in an Upland Hardwood Forest
Authors: Pease Brent S. , Holzmueller Eric J. , Nielsen Clayton K.
Published: September 2019

Oak-hickory (Quercus-Carya spp.) forest types are widespread across the midwestern United States, but changes in forest disturbance regimes are resulting in little to no oak recruitment and a compositional shift to shade-tolerant, mesophytic species, such as American beech (Fagus grandifolia) and sugar maple (Acer saccharum). We conducted camera trap surveys in a mature upland hardwood forest of southern Illinois, USA during May to August 2015–2016 to document mammal summer habitat use in relation to forest structure and composition to further understand how regional shifts in forests may affect mammal communities. With nearly 4000 camera days of effort, we modeled occupancy patterns for white-tailed deer (Odocoileus virginianus), raccoon (Procyon lotor), and eastern gray squirrel (Sciurus canadensis). Forest composition models outcompeted forest structure models for white-tailed deer, where we observed a statistically significant negative relationship between white-tailed deer habitat use and beech dominance. Further, we found a strong, positive association between deer and oak dominance. Model selection indicated little support for within-stand forest structure or composition characteristics influencing habitat use for raccoons. Eastern gray squirrel occurrence was best described by forest composition, revealing a positive relationship with beech–maple importance values. Our predictive models indicated that the impact of forest changes underway will have varying impacts on wildlife species. We can expect changes in habitat use patterns to be more pronounced with time barring revised forest management practices, and these changes are likely to be most influential at the landscape-scale. We conclude that a patchwork mosaic of forest conditions will likely best support a diverse and abundant mammal community across the region.
Differential Effect of the Physical Embodiment on the Prefrontal Cortex Activity as Quantified by Its Entropy
Authors: Keshmiri Soheil , Sumioka Hidenobu , Yamazaki Ryuji , Ishiguro Hiroshi
Published: September 2019

Computer-mediated-communication (CMC) research suggests that unembodied media can surpass in-person communication due to their utility to bypass the nonverbal components of verbal communication such as physical presence and facial expressions. However, recent results on communicative humanoids suggest the importance of the physical embodiment of conversational partners. These contradictory findings are strengthened by the fact that almost all of these results are based on the subjective assessments of the behavioural impacts of these systems. To investigate these opposing views of the potential role of the embodiment during communication, we compare the effect of a physically embodied medium that is remotely controlled by a human operator with such unembodied media as telephones and video-chat systems on the frontal brain activity of human subjects, given the pivotal role of this region in social cognition and verbal comprehension. Our results provide evidence that communicating through a physically embodied medium affects the frontal brain activity of humans whose patterns potentially resemble those of in-person communication. These findings argue for the significance of embodiment in naturalistic scenarios of social interaction, such as storytelling and verbal comprehension, and the potential application of brain information as a promising sensory gateway in the characterization of behavioural responses in human-robot interaction.
Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit
Authors: Cui Yi , Jiang Shangming , Jin Juliang , Feng Ping , Ning Shaowei
Published: September 2019

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.
A Combination Method for Averaging OLS and GLS Estimators
Authors: Liu Qingfeng , Vasnev Andrey L.
Published: September 2019

To avoid the risk of misspecification between homoscedastic and heteroscedastic models, we propose a combination method based on ordinary least-squares (OLS) and generalized least-squares (GLS) model-averaging estimators. To select optimal weights for the combination, we suggest two information criteria and propose feasible versions that work even when the variance-covariance matrix is unknown. The optimality of the method is proven under some regularity conditions. The results of a Monte Carlo simulation demonstrate that the method is adaptive in the sense that it achieves almost the same estimation accuracy as if the homoscedasticity or heteroscedasticity of the error term were known.
Area-Efficient Early-Termination Technique for Belief-Propagation Polar Decoders
Authors: Choi Soyeon , Yoo Hoyoung
Published: September 2019

Early-termination techniques for a belief-propagation (BP) decoder of polar codes can improve the decoding throughput by finishing a decoding iteration when an early-termination condition is satisfied. In the BP decoders, the early-termination condition plays an important role, as it affects decoding iteration savings. In this letter, an area-efficient early-termination criterion is proposed, which simplifies the previous threshold-based termination condition by completely eliminating redundant computations. According to the experimental results, the proposed structure for (1024, 512) polar codes can reduce 72.7%, 66.5%, and 59.7% of hardware resources without any degradation in the error-correction performance and decoding throughput compared to the previous threshold-based, information-BER (bit error rate)-based, and frozen-BER-based early-termination techniques, respectively.
Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment
Authors: Zhou Xiaoyang , Chen Hao , Wang Hao , Lev Benjamin , Quan Lifang
Published: September 2019

With the acceleration of industrialization, a large amount of energy consumption has brought tremendous pressure to the natural environment. In order to prevent environmental pollution and promote sustainable development, the environmental efficiency assessment as an effective way to provide decision-making basis has been given wide attention. This study measures the environmental efficiency of 30 provinces in China from 2006 to 2015 based on the Data Envelopment Analysis (DEA) environmental assessment radial model both under natural disposability and managerial disposability that considered the constant variable return to scale (RTS) and the damage to scale (DTS). In addition, the scale efficiency under the two kinds of disposability of China’s 30 provinces were also measured. We found that the environmental efficiencies of different provinces in China showed regional disparities. Provinces such as Beijing, Shanghai, and Guangdong had a good performance in unified environmental efficiency and scale efficiency both under natural disposability and managerial disposability. Generally speaking, the eastern regions always performed better than the central and western regions in unified environmental efficiency during the observed years. Therefore, policies should be established to distribute the resources in balance between the east, center, and west to further promote environmental efficiency.
Capacity Management of Hyperscale Data Centers Using Predictive Modelling
Authors: Islam Raihan Ul , Ruci Xhesika , Hossain Mohammad Shahadat , Andersson Karl , Kor Ah-Lian
Published: September 2019

Big Data applications have become increasingly popular with the emergence of cloud computing and the explosion of artificial intelligence. The increasing adoption of data-intensive machines and services is driving the need for more power to keep the data centers of the world running. It has become crucial for large IT companies to monitor the energy efficiency of their data-center facilities and to take actions on the optimization of these heavy electricity consumers. This paper proposes a Belief Rule-Based Expert System (BRBES)-based predictive model to predict the Power Usage Effectiveness (PUE) of a data center. The uniqueness of this model consists of the integration of a novel learning mechanism consisting of parameter and structure optimization by using BRBES-based adaptive Differential Evolution (BRBaDE), significantly improving the accuracy of PUE prediction. This model has been evaluated by using real-world data collected from a Facebook data center located in Luleå, Sweden. In addition, to prove the robustness of the predictive model, it has been compared with other machine learning techniques, such as an Artificial Neural Network (ANN) and an Adaptive Neuro Fuzzy Inference System (ANFIS), where it showed a better result. Further, due to the flexibility of the BRBES-based predictive model, it can be used to capture the nonlinear dependencies of many variables of a data center, allowing the prediction of PUE with much accuracy. Consequently, this plays an important role to make data centers more energy-efficient.
Experimental and Simulation Studies on Adsorption and Diffusion Characteristics of Coalbed Methane
Authors: Kim Donghyeon , Seo Youngjin , Kim Juhyun , Han Jeongmin , Lee Youngsoo
Published: September 2019

Coalbed methane (CBM) content is generally estimated using the isotherm theory between pressure and adsorbed amounts of methane. It usually determines the maximum content of adsorbed methane or storage capacity. However, CBM content obtained via laboratory experiment is not consistent with that in the in-situ state because samples are usually ground, which changes the specific surface area. In this study, the effect of the specific surface area relative to CBM content was investigated, and diffusion coefficients were estimated using equilibrium time analysis. The differences in adsorbed content with sample particle size allowed the determination of a specific surface area where gases can adsorb. Also, there was an equilibrium time difference between fine and lump coal, because more time is needed for the gas to diffuse through the coal matrix and adsorb onto the surface in lump coal. Based on this, we constructed a laboratory-scale simulation model, which matched with experimental results. Consequently, the diffusion coefficient, which is usually calculated through canister testing, can be easily obtained. These results stress that lump coal experiments and associated simulations are necessary for more reliable CBM production analysis.
Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
Authors: Kruszewska Natalia , Bełdowski Piotr , Weber Piotr , Yuvan Steven , Drechny Marcin , Kośmieja Marcin
Published: September 2019

Molecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus, the inter- and intra-molecular interaction energies between the residues of mucin are analyzed. The results indicate that the mucin concentration significantly impacts its cross-linking behavior. Between 160 g/L and 214 g/L, there seems to be a critical concentration above which crowding begins to alter intermolecular interactions and their energies. This transition is further supported by the mean squared displacement of the molecules. At a high concentration, the system starts to behave subdiffusively due to network development. We also calculate a sample mean squared displacement and p-variation tests to demonstrate how the statistical nature of the dynamics is likewise altered for different concentrations.
A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency
Authors: Crespo Márquez Adolfo , de la Fuente Carmona Antonio , Antomarioni Sara
Published: September 2019

In this paper, we address the problem of asset performance monitoring, with the intention of both detecting any potential reliability problem and predicting any loss of energy consumption efficiency. This is an important concern for many industries and utilities with very intensive capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically with Association Rule (AR) Mining. The combination of these two techniques can now be done using software which can handle large volumes of data (big data), but the process still needs to ensure that the required amount of data will be available during the assets’ life cycle and that its quality is acceptable. The combination of these two techniques in the proposed sequence differs from previous works found in the literature, giving researchers new options to face the problem. Practical implementation of the proposed approach may lead to novel predictive maintenance models (emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of performance and help manage assets’ O&M accordingly. The approach is illustrated using specific examples where asset performance monitoring is rather complex under normal operational conditions.
Sliding Mode Control of the Isolated Bridgeless SEPIC High Power Factor Rectifier Interfacing an AC Source with a LVDC Distribution Bus
Authors: Lopez-Santos Oswaldo , Cabeza-Cabeza Alejandro J. , Garcia Germain , Martinez-Salamero Luis
Published: September 2019

This paper deals with the analysis and design of a sliding mode-based controller to obtain high power factor (HPF) in the bridgeless isolated version of the single ended primary inductor converter (SEPIC) operating as a single-phase rectifier. In the work reported here, the converter is used as a unidirectional isolated interface between an AC source and a low voltage direct current (LVDC) distribution bus. The sliding-mode control is used to ensure the tracking of a high quality current reference at the input side, which is obtained from a sine waveform generator synchronized with the grid. The feasibility of the proposal is validated using simulation and experimental results, both of them confirming a reliable operation and showing good static and dynamic performances.
An Experimental Study on the Heat and Mass Transfer of Liquid Nitrogen in a Loose Medium
Authors: Zhang Yang , Lei Baiwei , Wu Bing , Meng Yu , He Binbin
Published: September 2019

Liquid nitrogen is a vital medium during the extinguishing and chilldown process of coal spontaneous combustion in coal mine goafs. In this paper, the heat and mass transfer of liquid nitrogen in a loose medium was investigated. A laboratory system including a temperature sensing system was designed and built to explore the effects of different nitrogen injection positions and angles on the chilldown effect. The results indicate that after liquid nitrogen injection, the temperatures in the liquid nitrogen flow area and the bottom of the model can be quickly reduced to −196 °C, which was the best chilldown effect zone. With the vaporization of the liquid nitrogen, the cryogenic nitrogen gradually diffused. At 20,000 s, the bottom temperature was about –63 °C, the middle was –30 °C, and the upper was 0 °C. When the model angle was 0°, the effective chilldown zone was the largest. As the angle increased, the effective chilldown volume and holding time decreased significantly. The model angle had a greater impact on the chilldown. For the position of nitrogen injection, the inlet was set slightly farther from the gas outlet’s position, leading to a larger coverage for the liquid nitrogen and cryogenic nitrogen chilldown. This study can provide a theoretical basis for the flow and chilldown of nitrogen injection in goafs.
Dye-Sensitized Solar Cells Using Aluminum-Doped Zinc Oxide/Titanium Dioxide Photoanodes in Parallel
Authors: Chou Jung-Chuan , Ko Cheng-Chu , Chang Jun-Xiang , Lai Chih-Hsien , Nien Yu-Hsun , Kuo Po-Yu , Chen Huang-Hua , Hsu Hui-Hsuan , Hu Geng-Ming
Published: September 2019

In this study, both zinc oxide (ZnO) nanorods and aluminum-doped zinc oxide (AZO) nanosheets were deposited by hydrothermal growth on fluorine-doped tin oxide (FTO) glass. After a photoanode was added to ZnO nanorods or AZO nanosheets, the photovoltaic conversion efficiency (PCE) increased due to improved electron transport and enhanced dye absorption. The improvement in electron transport was verified by electrochemical impedance spectroscopy (EIS), and the increase in dye absorption was verified by ultraviolet-visible spectroscopy. Both of these factors facilitated an increase in PCE. Parameters for dye-sensitized solar cells (DSSCs) using ZnO nanorods/TiO2 and AZO nanosheets/TiO2 photoanodes were tested and the results were recorded using EIS. The results indicated that the addition of the ZnO nanorods increased the short-circuit current density (Jsc) from 9.07 mA/cm2 to 10.91 mA/cm2, the open circuit voltage (Voc) from 0.68 V to 0.70 V, and the PCE from 3.70% to 4.73%, respectively. When the DSSCs were produced in a parallel silver-grid device, the results showed that PCE could be increased from 3.67% to 4.04% due to the reduction in connection resistance.
Performance Enhancement of Hybrid Solid Desiccant Cooling Systems by Integrating Solar Water Collectors in Taiwan
Authors: Luo Win-Jet , Faridah Dini , Fasya Fikri Rahmat , Chen Yu-Sheng , Mulki Fikri Hizbul , Adilah Utami Nuri
Published: September 2019

A hybrid solid desiccant cooling system (SDCS), which combines a solid desiccant system and a vapor compression system, is considered to be an excellent alternative for commercial and residential air conditioning systems. In this study, a solar-assisted hybrid SDCS system was developed in which solar-heated water is used as an additional heat source for the regeneration process, in addition to recovering heat from the condenser of an integrated heat pump. A solar thermal collector sub-system is used to generate solar regeneration water. Experiments were conducted in the typically hot and humid weather of Taichung, Taiwan, from the spring to fall seasons. The experimental results show that the overall performance of the system in terms of power consumption can be enhanced by approximately 10% by integrating a solar-heated water heat exchanger in comparison to the hybrid SDCS system. The results show that the system performs better when the outdoor humidity ratio is large. In addition, regarding the effect of ambient temperature on the coefficient of performance (COP) of the systems, a critical value of outdoor temperature exists. The COP of the systems gradually rises with the increase in ambient temperature. However, when the ambient temperature is greater than the critical value, the COP gradually decreases with the increase in ambient temperature. The critical outdoor temperature of the hybrid SDCS is from 26 °C to 27 °C, and the critical temperature of the solar-assisted hybrid SDCS is from 27 °C to 30 °C.
Electric Vehicle Charge Stations Location Analysis and Determination—Ankara (Turkey) Case Study
Authors: Harighi Tohid , Padmanaban Sanjeevikumar , Bayindir Ramazan , Hossain Eklas , Holm-Nielsen Jens Bo
Published: September 2019

Locating electric vehicle charge stations has always been an important problem for electric distributers. Many basic and complex solutions have been provided by algorithms and methods to solve this problem in real and assumed grids. However, the data, which has been used in those algorithms, are not consistent with the diversity of locations, thus, do not meet the expected results. Grid locations are the most important aspects of this issue in the eyes of designers, investors, and the general public. Locating charge stations must be determined by plans which have influenced majority in the society. In some countries, power quality has been increased by storages, which are used in vehicle-to-grid (V2G) and similar operations. In this paper, all of the variables for locating charging stations are explained according to Ankara metropolitan. During the implemented analysis and literature reviews, an algorithm, based on location and grid priorities and infrastructures, are 154 kV and 33 kV, have been designed. Genetic algorithms have been used to demonstrate this method even though other algorithms can also be adopted to meet the priority.
Effect of Hafnium Addition on the Hydrogenation Process of TiFe Alloy
Authors: Razafindramanana Volatiana , Gorsse Stéphane , Huot Jacques , Bobet Jean Louis
Published: September 2019

The alloy TiFe has interesting hydrogen storage properties for practical applications: low cost, operation at room temperature, and good hydrogen capacity. However, the first hydrogenation is difficult and increases the cost of the alloy. In this work, we studied the effect of adding hafnium to TiFe in order to enhance the first hydrogenation process. TiFe + x Hf alloys, with x = 0, 4, 8, 12, and 16 wt.%, were synthesized by arc melting. The microstructure of the as-cast alloys was investigated by scanning electron microscopy and electron microprobe analysis. These alloys consisted of B2-TiFe, C14-Laves, and BCC (Body Centered Cubic) phases. A minimum of 8 wt.% of hafnium is required to obtain an enhancement of the first hydrogenation. In the first hydrogenation, the material reaches its maximal hydrogen capacity in less than two hours at room temperature and under 20 bars of hydrogen. Hafnium addition also had the effect of lowering the plateau pressure in the pressure-composition isotherm. It could be concluded that hafnium has a positive effect on the activation properties of TiFe.
Nature Conservation and Nature-Based Tourism: A Paradox?
Authors: Wolf Isabelle D. , Croft David B. , Green Ronda J.
Published: September 2019

Throughout the world, areas have been reserved for their exceptional environmental values, such as high biodiversity. Financial, political and community support for these protected areas is often dependent on visitation by nature-based tourists. This visitation inevitably creates environmental impacts, such as the construction and maintenance of roads, tracks and trails; trampling of vegetation and erosion of soils; and propagation of disturbance of resilient species, such as weeds. This creates tension between the conservation of environmental values and visitation. This review examines some of the main features of environmental impacts by nature-based tourists through a discussion of observational and manipulative studies. It explores the disturbance context and unravels the management implications of detecting impacts and understanding their causes. Regulation of access to visitor areas is a typical management response, qualified by the mode of access (e.g., vehicular, ambulatory). Managing access and associated impacts are reviewed in relation to roads, tracks and trails; wildlife viewing; and accommodations. Responses to visitor impacts, such as environmental education and sustainable tour experiences are explored. The review concludes with ten recommendations for further research in order to better resolve the tension between nature conservation and nature-based tourism.
Assessment of Genetic Diversity of Tea Germplasm for Its Management and Sustainable Use in Korea Genebank
Authors: Lee Kyung Jun , Lee Jung-Ro , Sebastin Raveendar , Shin Myoung-Jae , Kim Seong-Hoon , Cho Gyu-Taek , Hyun Do Yoon
Published: September 2019

Tea (Camellia sinensis (L.) O. Kuntze) is cultivated in many developing Asian, African, and South American countries, and is the most widely consumed beverage in the world. It is of critical importance to understand the genetic diversity and population structure of tea germplasm for effective collection, conservation, and utilization. In this study, 410 tea accessions collected from South Korea were analyzed using 21 simple sequence repeat (SSR) markers. Among 410 tea accessions, 85.4% (350 accessions) were collected from Jeollanam-do. A total of 286 alleles were observed, and the genetic diversity and evenness were estimated to be on average 0.79 and 0.61, respectively, across all the tested samples. Using discriminant analysis of principal components, four clusters were detected in 410 tea accessions. Among them, cluster 1 showed a higher frequency of rare alleles (less than 1%). Using the calculation of the index of association and rbaD value, each cluster showed a clonal mode of reproduction. The result of analysis of molecular variance (AMOVA) showed that most of the variation observed was within populations (99%) rather than among populations (1%). The present study revealed the presence of lower diversity and simpler population structure in Korean tea germplasms. Consequently, more attention should be focused on collecting and conserving the new tea individuals to broaden genetic variation of new cultivars in future breeding of the tea plant.
How Much Forest Persists Through Fire? High-Resolution Mapping of Tree Cover to Characterize the Abundance and Spatial Pattern of Fire Refugia Across Mosaics of Burn Severity
Authors: B. Walker Ryan , D. Coop Jonathan , M. Downing William , A. Krawchuk Meg , L. Malone Sparkle , W. Meigs Garrett
Published: September 2019

Wildfires in forest ecosystems produce landscape mosaics that include relatively unaffected areas, termed fire refugia. These patches of persistent forest cover can support fire-sensitive species and the biotic legacies important for post-fire forest recovery, yet little is known about their abundance and distribution within fire perimeters. Readily accessible 30-m resolution satellite imagery and derived burn severity products are commonly employed to characterize post-fire landscapes; however, coarse image resolution, generalized burn severity thresholds, and other limitations can constrain accurate representation of fire refugia. This study quantifies the abundance and pattern of fire refugia within 10 fires occurring in ponderosa pine and dry mixed-conifer forests between 2000 and 2003. We developed high-resolution maps of post-fire landscapes using semi-automated, object-based classification of 1-m aerial imagery, conducted imagery- and field-based accuracy assessments, and contrasted these with Landsat-derived burn severity metrics. Fire refugia area within burn perimeters ranged from 20% to 57%. Refugia proportion generally decreased with increasing Landsat-derived burn severity, but still accounted for 3–12% of areas classified as high severity. Patch size ranged from 1-m2 isolated trees to nearly 8000 ha, and median patch size was 0.01 ha—substantially smaller than a 30-m Landsat pixel. Patch size was negatively related to burn severity; distance to fire refugia from open areas was positively related to burn severity. Finally, optimized thresholds of 30-m post-fire normalized burn ratio (NBR) and relative differenced normalized burn ratio (RdNBR) delineated fire refugia with an accuracy of 77% when validated against the 1-m resolution maps. Estimations of fire refugia abundance based on Landsat-derived burn severity metrics are unlikely to detect small, isolated fire refugia patches. Finer-resolution maps can improve understanding of the distribution of forest legacies and inform post-fire management activities including reforestation and treatments.
Efficiency of the CL, DRIS and CND Methods in Assessing the Nutritional Status of Eucalyptus spp. Rooted Cuttings
Authors: Morais Thaís Chagas Barros de , Prado Renato de Mello , Traspadini Edilaine Istefani Franklin , Wadt Paulo Guilherme Salvador , Paula Rinaldo César de , Rocha Antônio Márcio Souza
Published: September 2019

The efficiency of methods in adequately interpreting the nutritional status of Eucalyptus spp. rooted cuttings remains unknown. The aim was to evaluate the quality of diagnoses obtained using the critical level (CL), diagnosis and recommendation integrated system (DRIS) and compositional nutrient diagnosis (CND) methods to assess the nutritional status of Eucalyptus spp. rooted cuttings, based on two different yield indicators. The data were obtained from commercial nursery and calibration experiments, using seven nutrients as treatments (N, P, K, Mg, Ca, B and Fe) and four concentrations per nutrient, arranged in randomized blocks, with four repetitions. The Eucalyptus spp. clone used in the experiments was AEC 0144. A total of 222 rooted cuttings were obtained from the experimental area and commercial nurseries and the following were determined: leaf nutrient content, whole plant dry matter (DM) content and the Dickson quality index (DQI). Diagnostic accuracy in the experimental plots was ascertained by comparing the diagnosis with plant response as a function of adding the corresponding nutrient. Five measures of accuracy were used to test the efficiency of the diagnostic methods: total accuracy, accuracy for deficiency and sufficiency, deficiency ratio, efficiency ratio, and the net increase in in DM and DQI. The performance of diagnostic methods varied between CL, DRIS and CND, and among the nutrients studied. Given that the seedling production system is largely more controlled, where environmental variations are minimal, and considering that the different diagnostic methods exhibited distinct performance in terms of assessing the true nutritional status of eucalyptus rooted cuttings, the CL method is the most indicated for this situation, due to its better performance in evaluating the nutritional status of most nutrients and easy implementation.
The Draft Genome of the Endangered Sichuan Partridge (Arborophila rufipectus) with Evolutionary Implications
Authors: Zhou Chuang , Tu Hongmei , Yu Haoran , Zheng Shuai , Dai Bo , Price Megan , Wu Yongjie , Yang Nan , Yue Bisong , Meng Yang
Published: September 2019

The Sichuan partridge (Arborophila rufipectus, Phasianidae, Galliformes) is distributed in south-west China, and classified as endangered grade. To examine the evolution and genomic features of Sichuan partridge, we de novo assembled the Sichuan partridge reference genome. The final draft assembly consisted of approximately 1.09 Gb, and had a scaffold N50 of 4.57 Mb. About 1.94 million heterozygous single-nucleotide polymorphisms (SNPs) were detected, 17,519 protein-coding genes were predicted, and 9.29% of the genome was identified as repetitive elements. A total of 56 olfactory receptor (OR) genes were found in Sichuan partridge, and conserved motifs were detected. Comparisons between the Sichuan partridge genome and chicken genome revealed a conserved genome structure, and phylogenetic analysis demonstrated that Arborophila possessed a basal phylogenetic position within Phasianidae. Gene Ontology (GO) enrichment analysis of positively selected genes (PSGs) in Sichuan partridge showed over-represented GO functions related to environmental adaptation, such as energy metabolism and behavior. Pairwise sequentially Markovian coalescent analysis revealed the recent demographic trajectory for the Sichuan partridge. Our data and findings provide valuable genomic resources not only for studying the evolutionary adaptation, but also for facilitating the long-term conservation and genetic diversity for this endangered species.
Previously Identified Genetic Variants in ADGRL3 Are not Associated with Risk for Equine Degenerative Myeloencephalopathy across Breeds
Authors: Marquardt Sabin A. , Wilcox Callie V. , Burns Erin N. , Peterson Janel A. , Finno Carrie J.
Published: September 2019

Equine neuroaxonal dystrophy/equine degenerative myeloencephalopathy (eNAD/EDM) is a neurologic disease that has been reported in young horses from a wide range of breeds. The disease is inherited and associated with vitamin E deficiency during the first two years of life, resulting in bilateral symmetric ataxia. A missense mutation (chr3:71,917,591 C > T) within adhesion G protein-coupled receptor L3 (ADGRL3) was recently associated with risk for EDM in the Caspian breed. In order to confirm these findings, genotyping of this missense mutation, along with the three other associated single nucleotide polymorphisms (SNPs) in the genomic region, was carried out on 31 postmortem-confirmed eNAD/EDM cases and 43 clinically phenotyped controls from various breeds. No significant association was found between eNAD/EDM confirmed cases and genotype at any of the four identified SNPs (P > 0.05), including the nonsynonymous variant (EquCab2.0 chr3:71,917,591; allelic P = 0.85). These findings suggest that the four SNPs, including the missense variant in the ADGRL3 region, are not associated with risk for eNAD/EDM across multiple breeds of horses.
Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine
Authors: Boonen Kurt , Hens Kristien , Menschaert Gerben , Baggerman Geert , Valkenborg Dirk , Ertaylan Gokhan
Published: September 2019

The increasing availability of high throughput proteomics data provides us with opportunities as well as posing new ethical challenges regarding data privacy and re-identifiability of participants. Moreover, the fact that proteomics represents a level between the genotype and the phenotype further exacerbates the situation, introducing dilemmas related to publicly available data, anonymization, ownership of information and incidental findings. In this paper, we try to differentiate proteomics from genomics data and cover the ethical challenges related to proteomics data sharing. Finally, we give an overview of the proposed solutions and the outlook for future studies.