bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator
Authors: Comamala Martí , Cózar Ivan Ruiz , Massaguer Albert , Massaguer Eduard , Pujol Toni
Published: November 2018

The need for more sustainable mobility promoted research into the use of waste heat to reduce emissions and fuel consumption. As such, thermoelectric generation is a promising technique thanks to its robustness and simplicity. Automotive thermoelectric generators (ATEGs) are installed in the tailpipe and convert heat directly into electricity. Previous works on ATEGs mainly focused on extracting the maximum amount of electrical power. However, the back pressure caused by the ATEG heavily influences fuel consumption. Here, an ATEG numerical model was first validated with experimental data and then applied to investigate the effects that modifying the main ATEG design parameters had on both fuel economy and output power. The cooling flow rate and the geometrical dimensions of the heat exchanger on the hot side and the cold side of the ATEG were varied. The design that produced the maximum output power differed from that which maximized fuel economy. Back pressure was the most limiting factor in attaining fuel savings. Back pressure values lower than 5 mbar led to a < 0.2% increase in fuel consumption. In the ATEG design analyzed here, the generation of electrical output power reduced fuel consumption by a maximum of 0.5%.
A Method to Process Hollow-Core Anti-Resonant Fibers into Fiber Filters
Authors: Huang Xiaosheng , Yong Ken-Tye , Yoo Seongwoo
Published: November 2018

Hollow-Core Anti-Resonant Fiber (HC-ARF) shows promising applications. Nevertheless, there has been a persistent problem when it comes to all-fiber integration due to a lack of HC-ARF-based fiber components. In response to this remaining challenge, we investigate a reliable, versatile and efficient method to convert an HC-ARF into a fiber filter. By locally heating an HC-ARF with a CO2 laser, the fiber structure becomes deformed, and cladding capillaries shrink to produce a thicker wall. This process is analogous to “writing” a new fiber with a thicker wall on the original fiber, resulting in creating new high loss regions in the original transmission bands. Thus, the construction of a fiber filter is realized by “writing” a new fiber on the original fiber. The feasibility of this method is confirmed through experiments, adopting both one- and two-layer HC-ARF. The HC-ARF-based fiber filters are found to have transmission spectra consistent with simulation prediction. Both band pass and band reject fiber filters with more than a 20-dB extinction ratio are obtainable without extra loss. Thus, an in-fiber HC-ARF filter is demonstrated by the CO2 writing process. Its versatile approach promises controlled band selection and would find interesting applications to be discussed.
Implementing a Modern E-Learning Strategy in an Interdisciplinary Environment—Empowering UNESCO Stakeholders to Use Earth Observation
Authors: Matusch Tobias , Schneibel Anne , Dannwolf Lisa , Siegmund Alexander
Published: November 2018

The Copernicus Program and the fleet of available Earth observation satellites provide valuable services in sectors such as agriculture, forestry, urban monitoring, and heritage management. However, drawbacks such as knowledge gaps by the user, limited technical and financial facilities or the lack of ready-to-use data, result in insufficient exploitation of these opportunities by heritage site managers and other relevant stakeholders. Based on an initial assessment of current threats, existing limitations and potential applications, we developed the e-learning module Space2Place. Through the use of the learning module, stakeholders get a substantial introduction into Earth observation and knowledge barriers that may exist are removed. For this purpose, we refined an existing e-learning platform, which was developed in close relation to an online remote sensing application and adapted to the needs of UNESCO site stakeholders. One of the main features is the personalization of the learning modules content depending on the abilities or interests of the user. The platform offers information with different levels of difficulty and adaptable learning paths. A graduation certificate and practical exercises in an online remote sensing application increase the specific added value for UNESCO site manager. By using the associated remote sensing application and its link to Space2Place, heritage site managers also improve their knowledge on image processing by working with original satellite imagery. Additional advantages of using the platform will be enhanced through the introduction of new learning modules, translation into other languages and accompanying scientific research.
Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs
Authors: Wojciech Maleika
Published: November 2018

The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius”). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.
Reduced Risks of Both Ischemic and Hemorrhagic Strokes in Nurses: A Population-Based Cohort Study in Taiwan
Authors: Liao Hui-Chuan , Peng Yi-Hao , Chen Yu-Pei , Huang Li-Chi , Liang Wen-Miin , Hsu Chung Y. , Kao Chia-Hung , Tseng Chun-Hung
Published: November 2018

Background: Nurses are typically required to address patient emergencies, and they experience high stress levels in their work, which may expose them to a higher risk of stroke. This cohort study compared the risk of stroke between nurses and the general population. Methods: We used the Taiwan National Health Insurance database to conduct our retrospective cohort study, and we identified 83,641 individuals in the nurse group and 334,564 individuals in the control group. For the nurse group and the control group, we used the chi-square test in addition to applying Student’s t-test, in order to compare the distribution differences for the continuous variables. We estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) for ischemic stroke and hemorrhagic stroke through univariate and multivariate Cox proportional-hazards regression models, with stratification according to age, sex, and comorbidity. Results: The nurse group had a lower risk of ischemic stroke and hemorrhagic stroke in the crude model (HR = 0.66, 95% CI = 0.58–0.75; HR = 0.58, 95% CI = 0.47–0.72). After adjusting the prevalent variables, the nurse group still had a lower risk of stroke (HR = 0.68, 95% CI = 0.60–0.77; HR = 0.59, 95% CI = 0.48–0.73). Conclusion: The risks of both stroke types were lower in the nurse group than in the control. For stroke prevention, more frequent physical examinations are needed in order to enhance the health and well-being of people, including the nurses.
Assessing Health Vulnerabilities and Adaptation to Climate Change: A Review of International Progress
Authors: Berry Peter , Enright Paddy M. , Shumake-Guillemot Joy , Villalobos Prats Elena , Campbell-Lendrum Diarmid
Published: November 2018

Climate change is increasing risks to human health and to the health systems that seek to protect the safety and well-being of populations. Health authorities require information about current associations between health outcomes and weather or climate, vulnerable populations, projections of future risks and adaptation opportunities in order to reduce exposures, empower individuals to take needed protective actions and build climate-resilient health systems. An increasing number of health authorities from local to national levels seek this information by conducting climate change and health vulnerability and adaptation assessments. While assessments can provide valuable information to plan for climate change impacts, the results of many studies are not helping to build the global evidence-base of knowledge in this area. They are also often not integrated into adaptation decision making, sometimes because the health sector is not involved in climate change policy making processes at the national level. Significant barriers related to data accessibility, a limited number of climate and health models, uncertainty in climate projections, and a lack of funding and expertise, particularly in developing countries, challenge health authority efforts to conduct rigorous assessments and apply the findings. This paper examines the evolution of climate change and health vulnerability and adaptation assessments, including guidance developed for such projects, the number of assessments that have been conducted globally and implementation of the findings to support health adaptation action. Greater capacity building that facilitates assessments from local to national scales will support collaborative efforts to protect health from current climate hazards and future climate change. Health sector officials will benefit from additional resources and partnership opportunities to ensure that evidence about climate change impacts on health is effectively translated into needed actions to build health resilience.
Identification of Genes that Control Silk Yield by RNA Sequencing Analysis of Silkworm (Bombyx mori) Strains of Variable Silk Yield
Authors: Luan Yue , Zuo Weidong , Li Chunlin , Gao Rui , Zhang Hao , Tong Xiaoling , Han Minjin , Hu Hai , Lu Cheng , Dai Fangyin
Published: November 2018

Silk is an important natural fiber of high economic value, and thus genetic study of the silkworm is a major area of research. Transcriptome analysis can provide guidance for genetic studies of silk yield traits. In this study, we performed a transcriptome comparison using multiple silkworms with different silk yields. A total of 22 common differentially expressed genes (DEGs) were identified in multiple strains and were mainly involved in metabolic pathways. Among these, seven significant common DEGs were verified by quantitative reverse transcription polymerase chain reaction, and the results coincided with the findings generated by RNA sequencing. Association analysis showed that BGIBMGA003330 and BGIBMGA005780 are significantly associated with cocoon shell weight and encode uridine nucleosidase and small heat shock protein, respectively. Functional annotation of these genes suggest that these play a role in silkworm silk gland development or silk protein synthesis. In addition, we performed principal component analysis (PCA) in combination with wild silkworm analysis, which indicates that modern breeding has a stronger selection effect on silk yield traits than domestication, and imply that silkworm breeding induces aggregation of genes related to silk yield.
Study on Thermal Decomposition Behaviors of Terpolymers of Carbon Dioxide, Propylene Oxide, and Cyclohexene Oxide
Authors: Chen Shaoyun , Xiao Min , Sun Luyi , Meng Yuezhong
Published: November 2018

The terpolymerization of carbon dioxide (CO2), propylene oxide (PO), and cyclohexene oxide (CHO) were performed by both random polymerization and block polymerization to synthesize the random poly (propylene cyclohexene carbonate) (PPCHC), di-block polymers of poly (propylene carbonate–cyclohexyl carbonate) (PPC-PCHC), and tri-block polymers of poly (cyclohexyl carbonate–propylene carbonate–cyclohexyl carbonate) (PCHC-PPC-PCHC). The kinetics of the thermal degradation of the terpolymers was investigated by the multiple heating rate method (Kissinger-Akahira-Sunose (KAS) method), the single heating rate method (Coats-Redfern method), and the Isoconversional kinetic analysis method proposed by Vyazovkin with the data from thermogravimetric analysis under dynamic conditions. The values of ln k vs. T−1 for the thermal decomposition of four polymers demonstrate the thermal stability of PPC and PPC-PCHC are poorer than PPCHC and PCHC-PPC-PCHC. In addition, for PPCHC and PCHC-PPC-PCHC, there is an intersection between the two rate constant lines, which means that, for thermal stability of PPCHC, it is more stable than PCHC-PPC-PCHC at the temperature less than 309 °C and less stable when the decomposed temperature is more than 309 °C. Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and thermogravimetric analysis/infrared spectrometry (TG/FTIR) techniques were applied to investigate the thermal degradation behavior of the polymers. The results showed that unzipping was the main degradation mechanism of all polymers so the final pyrolysates were cyclic propylene carbonate and cyclic cyclohexene carbonate. For the block copolymers, the main chain scission reaction first occurs at PC-PC linkages initiating an unzipping reaction of PPC chain and then, at CHC–CHC linkages, initiating an unzipping reaction of the PCHC chain. That is why the T−5% of di-block and tri-block polymers were not much higher than that of PPC while two maximum decomposition temperatures were observed for both the block copolymer and the second one were much higher than that of PPC. For PPCHC, the random arranged bulky cyclohexane groups in the polymer chain can effectively suppress the backbiting process and retard the unzipping reaction. Thus, it exhibited much higher T−5% than that of PPC and block copolymers.
Vascular Plant One-Zinc-Finger (VOZ) Transcription Factors Are Positive Regulators of Salt Tolerance in Arabidopsis
Authors: Prasad Kasavajhala V. S. K. , Xing Denghui , Reddy Anireddy S. N.
Published: November 2018

Soil salinity, a significant problem in agriculture, severely limits the productivity of crop plants. Plants respond to and cope with salt stress by reprogramming gene expression via multiple signaling pathways that converge on transcription factors. To develop strategies to generate salt-tolerant crops, it is necessary to identify transcription factors that modulate salt stress responses in plants. In this study, we investigated the role of VOZ (VASCULAR PLANT ONE-ZINC FINGER PROTEIN) transcription factors (VOZs) in salt stress response. Transcriptome analysis in WT (wild-type), voz1-1, voz2-1 double mutant and a VOZ2 complemented line revealed that many stress-responsive genes are regulated by VOZs. Enrichment analysis for gene ontology terms in misregulated genes in voz double mutant confirmed previously identified roles of VOZs and suggested a new role for them in salt stress. To confirm VOZs role in salt stress, we analyzed seed germination and seedling growth of WT, voz1, voz2-1, voz2-2 single mutants, voz1-1 voz2-1 double mutant and a complemented line under different concentrations of NaCl. Only the double mutant exhibited hypersensitivity to salt stress as compared to WT, single mutants, and a complemented line. Expression analysis showed that hypersensitivity of the double mutant was accompanied by reduced expression of salt-inducible genes. These results suggest that VOZ transcription factors act as positive regulators of several salt-responsive genes and that the two VOZs are functionally redundant in salt stress.
The MTNR1B rs10830963 Variant in Interaction with Pre-Pregnancy BMI is a Pharmacogenetic Marker for the Initiation of Antenatal Insulin Therapy in Gestational Diabetes Mellitus
Authors: Firneisz Gábor , Rosta Klara , Al-Aissa Zahra , Hadarits Orsolya , Harreiter Jürgen , Nádasdi Ákos , Bancher-Todesca Dagmar , Németh László , Igaz Péter , Rigó János , Sziller István , Kautzky-Willer Alexandra , Somogyi Anikó
Published: November 2018

The rs10830963 variant of the Melatonin Receptor 1B (MTNR1B) gene is associated with the development of gestational diabetes mellitus (GDM). We hypothesized that carrying the rs10830963/G risk allele had effect on antenatal insulin therapy (AIT) initiation in GDM in a body mass index (BMI)-dependent manner. Design: In this post hoc analysis the MTNR1B rs10830963 genotype and the clinical data of 211 Caucasian GDM patients were assessed. As a first step, a pre-pregnancy BMI threshold was determined where the effect of MTNR1B rs10830963/G allele carrying on AIT initiation was the most significant using logistic regression. Maternal age adjusted real-life odds ratios (OR) values were calculated. The chi-square test was also used to calculate the p value and 10.000 bootstrap simulations were performed in each case to re-assess the statistical power and the OR. Carrying the MTNR1B rs10830963/G allele increased the odds of AIT initiation (OR = 5.2, p = 0.02 [χ2 test], statistical power = 0.53) in GDM patients with pre-pregnancy BMI ≥ 29 kg/m2. The statistical power reached 0.77, when the pre-pregnancy BMI cutoff of 27 kg/m2 was used and the genetic effect on AIT initiation was still significant, but only using the logistic regression model. Carrying the MTNR1B rs10830963/G risk allele—in interaction with pre-pregnancy BMI—is likely be considered as a candidate pharmacogenetic marker of antenatal insulin therapy initiation and should be further assessed in precision medicine trials in GDM.
The Past, Present, and Future of the Hemlock Woolly Adelgid (Adelges tsugae) and Its Ecological Interactions with Eastern Hemlock (Tsuga canadensis) Forests
Authors: Ellison Aaron M. , Orwig David A. , Fitzpatrick Matthew C. , Preisser Evan L.
Published: November 2018

The nonnative hemlock woolly adelgid is steadily killing eastern hemlock trees in many parts of eastern North America. We summarize impacts of the adelgid on these forest foundation species; review previous models and analyses of adelgid spread dynamics; and examine how previous forecasts of adelgid spread and ecosystem dynamics compare with current conditions. The adelgid has reset successional sequences, homogenized biological diversity at landscape scales, altered hydrological dynamics, and changed forest stands from carbon sinks into carbon sources. A new model better predicts spread of the adelgid in the south and west of the range of hemlock, but still under-predicts its spread in the north and east. Whether these underpredictions result from inadequately modeling accelerating climate change or accounting for people inadvertently moving the adelgid into new locales needs further study. Ecosystem models of adelgid-driven hemlock dynamics have consistently forecast that forest carbon stocks will be little affected by the shift from hemlock to early-successional mixed hardwood stands, but these forecasts have assumed that the intermediate stages will remain carbon sinks. New forecasting models of adelgid-driven hemlock decline should account for observed abrupt changes in carbon flux and ongoing and accelerating human-driven land-use and climatic changes.
Low-Complexity Loeffler DCT Approximations for Image and Video Coding
Authors: Coelho Diego F. G. , Cintra Renato J. , Bayer Fábio M. , Kulasekera Sunera , Madanayake Arjuna , Martinez Paulo , Silveira Thiago L. T. , Oliveira Raíza S. , Dimitrov Vassil S.
Published: November 2018

This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of 8-point DCT approximations was proposed, capable of unifying the mathematical formalism of several 8-point DCT approximations archived in the literature. Pareto-efficient DCT approximations are obtained through multicriteria optimization, where computational complexity, proximity, and coding performance are considered. Efficient approximations and their scaled 16- and 32-point versions are embedded into image and video encoders, including a JPEG-like codec and H.264/AVC and H.265/HEVC standards. Results are compared to the unmodified standard codecs. Efficient approximations are mapped and implemented on a Xilinx VLX240T FPGA and evaluated for area, speed, and power consumption.
Performance Consistency of AlSi10Mg Alloy Manufactured by Simulating Multi Laser Beam Selective Laser Melting (SLM): Microstructures and Mechanical Properties
Authors: Liu Bin , Kuai Zezhou , Li Zhonghua , Tong Jianbin , Bai Peikang , Li Baoqiang , Nie Yunfei
Published: November 2018

Multi-laser beam selective laser melting (SLM) technology based on a powder bed has been used to manufacture AlSi10Mg samples. The AlSi10Mg alloy was used as research material to systematically study the performance consistency of both the laser overlap areas and the isolated areas of the multi-laser beam SLM manufactured parts. The microstructures and mechanical properties of all isolated and overlap processing areas were compared under optimized process parameters. It was discovered that there is a raised platform at the junction of the overlap areas and the isolated areas of the multi-laser SLM samples. The roughness is significantly reduced after two scans. However, the surface roughness of the samples is highest after four scans. As the number of laser scans increases, the relative density of the overlap areas of the samples improves, and there is no significant change in hardness. The tensile properties of the tensile samples are poor when the overlap area width is 0, 0.1, or 0.2 mm. When the widths of the overlap areas are equal to or greater than 0.3 mm, there is no significant difference in the tensile strength between the overlap and the isolated areas.
Determination of Activation Overpotential during the Nucleation of Hcp-Cobalt Nanowires Synthesized by Potentio-Static Electrochemical Reduction
Authors: Saeki Ryusei , Ohgai Takeshi
Published: November 2018

The crystal growth process and ferromagnetic properties of electrodeposited cobalt nanowires were investigated by controlling the bath temperature and cathodic overpotential. The cathodic overpotential during electrodeposition of cobalt nanowire arrays, ΔEcath, was theoretically estimated by the difference between the cathode potential, Ecath, and the equilibrium potential, Eeq, calculated by the Nernst equation. On the other hand, the activation overpotential, ΔEact, was experimentally determined by the Arrhenius plot on the growth rate of cobalt nanowire arrays, Rg, versus (vs.) reciprocal temperature, 1/T. The ferromagnetic cobalt nanowire arrays with a diameter of circa (ca.) 25 nm had the preferred crystal orientation of (100) and the aspect ratio reached up to ca. 1800. The average crystal grain size, Ds, of (100) peaks was estimated by X-ray diffraction patterns and was increased by decreasing the cathodic overpotential for cobalt electrodeposition by shifting the cathode potential in the noble direction. Axial magnetization performance was observed in the cobalt nanowire arrays. With increasing Ds, coercivity of the film increased and reached up to ca. 1.88 kOe.
Influence of Vanadium on the Microstructure and Mechanical Properties of Medium-Carbon Steels for Wheels
Authors: Wang Pengfei , Li Zhaodong , Lin Guobiao , Zhou Shitong , Yang Caifu , Yong Qilong
Published: November 2018

Steels used for high-speed train wheels require a combination of high strength, toughness, and wear resistance. In 0.54% C-0.9% Si wheel steel, the addition of 0.075 or 0.12 wt % V can refine grains and increase the ferrite content and toughness, although the influence on the microstructure and toughness is complex and poorly understood. We investigated the effect of 0.03, 0.12, and 0.23 wt % V on the microstructure and mechanical properties of medium-carbon steels (0.54% C-0.9% Si) for train wheels. As the V content increased, the precipitation strengthening increased, whereas the grain refinement initially increased, and then it remained unchanged. The increase in strength and hardness was mainly due to V(C,N) precipitation strengthening. Increasing the V content to 0.12 wt % refined the austenite grain size and pearlite block size, and increased the density of high-angle ferrite boundaries and ferrite volume fraction. The grain refinement improved the impact toughness. However, the impact toughness then reduced as the V content was increased to 0.23 wt %, because grain refinement did not further increase, whereas precipitation strengthening and ferrite hardening occurred.
Optimizing the Mechanical Properties in the Repair Zone of 5Cr5MoV by Controlling Welding Heat Input
Authors: Liang Yan , Liu Yaohui , Song Yulai , Cui Wei
Published: November 2018

The influence of welding heat input on the microstructure and mechanical properties of 5Cr5MoV die steel was studied in order to improve the mechanical properties of the cold working die and extend its service life. Shielded metal arc welding (SMAW) method was used with different heat inputs in the range from 4.2 to 6.61 kJ/cm to repair the 5Cr5MoV die steel. Microhardness and tensile properties were performed to evaluate the repaired quality of the cold working die steel. The microhardness of the weld repaired zone gradually decreased from the weld to the tempering zone. The highest microhardness in the weld repaired zone was 863 HV, and finally, it decreased to about 300 HV. With the increase of heat input, the tensile strength of the weld and the heat affected zone increased; nevertheless, the tensile strength of the tempering zone increased first and then decreased. As a result, 6.6 kJ/cm is the best value of heat input judged from the microhardness distribution and the tensile properties.
“Zero-Waste”: A Sustainable Approach on Pyrometallurgical Processing of Manganese Nodule Slags
Authors: Sommerfeld Marcus , Friedmann David , Kuhn Thomas , Friedrich Bernd
Published: November 2018

A continuously growing demand for valuable non-ferrous metals and therefore an increase in their prices at the metal exchanges makes it necessary and profitable to investigate alternative metal resources. Polymetallic deep-sea nodules contain cobalt, copper, manganese, molybdenum and nickel, and are highly abundant on the sea floor. Developing a metallurgical process to recover the metal content from manganese nodules can close the predicted supply gap of critical metals like cobalt. This paper investigated a potential extraction process for valuable metals from manganese nodules supplied by the German Federal Institute for Geosciences and Natural Resources. The samples originated from the German license area of the Clarion-Clipperton Zone in the Pacific Ocean. Due to a low concentration of valuable metals in nodules, a pyrometallurgical enrichment step was carried out to separate cobalt, copper, molybdenum and nickel in a metallic phase. The manganese was discarded in the slag and recovered in a second smelting step as ferromanganese. To aid the experiments, FactSageTM was used for thermodynamic modeling of the smelting steps. To increase metal yields and to alter the composition of the metal alloys, different fluxes were investigated. The final slag after two reduction steps were heavy-metal free and a utilization as a mineral product was desired to ensure a zero-waste process.
Structure of Active Sites of Fe-N-C Nano-Catalysts for Alkaline Exchange Membrane Fuel Cells
Authors: Kishi Hirofumi , Sakamoto Tomokazu , Asazawa Koichiro , Yamaguchi Susumu , Kato Takeshi , Zulevi Barr , Serov Alexey , Artyushkova Kateryna , Atanassov Plamen , Matsumura Daiju , Tamura Kazuhisa , Nishihata Yasuo , Tanaka Hirohisa
Published: November 2018

Platinum group metal-free (PGM-free) catalysts based on transition metal-nitrogen-carbon nanomaterials have been studied by a combination of ex situ and in situ synchrotron X-ray spectroscopy techniques; high-resolution Transmission Electron Microscope (TEM); Mößbauer spectroscopy combined with electrochemical methods and Density Functional Theory (DFT) modeling/theoretical approaches. The main objective of this study was to correlate the HO2− generation with the chemical nature and surface availability of active sites in iron-nitrogen-carbon (Fe-N-C) catalysts derived by sacrificial support method (SSM). These nanomaterials present a carbonaceous matrix with nitrogen-doped sites and atomically dispersed and; in some cases; iron and nanoparticles embedded in the carbonaceous matrix. Fe-N-C oxygen reduction reaction electrocatalysts were synthesized by varying several synthetic parameters to obtain nanomaterials with different composition and morphology. Combining spectroscopy, microscopy and electrochemical reactivity allowed the building of structure-to-properties correlations which demonstrate the contributions of these moieties to the catalyst activity, and mechanistically assign the active sites to individual reaction steps. Associated with Fe-Nx motive and the presence of Fe metallic particles in the electrocatalysts showed the clear differences in the variation of composition; processing and treatment conditions of SSM. From the results of material characterization; catalytic activity and theoretical studies; Fe metallic particles (coated with carbon) are main contributors into the HO2− generation.
The Other, Shame, and Politics: Levinas, Justice, and Feeling Responsible
Authors: Larocco Steve
Published: November 2018

Adi Ophir has suggested that the political realm is an order of evils, producing and managing regular forms of suffering and violence rather than eliminating them. Thus, the political is always to some extent a corrupted order of justice. Emmanuel Levinas’ work presents in its focus on the face-to-face relationship a means of rethinking how to make the political more open to compassionate justice. Though Levinas himself doesn’t sufficiently take on this question, I argue that his work facilitates a way of thinking about commiserative shame that provides a means to connect the face-to-face to its potential effects in the political sphere. If such shame isn’t ignored or bypassed, it produces an unsettling relation to the other that in its adversity motivates a kind of responsibility and care for the other that can alter the public sphere.
Natural Computing Applied to the Underground System: A Synergistic Approach for Smart Cities
Authors: Morales Lucas Clemencio , De Mingo López Luis Fernando , Gómez Blas Nuria
Published: November 2018

The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within the Smart Cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable, and self-organized behavior to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms to build a system that makes the complete control of the UPTS a tangible reality.
Over One-Year Long-Term Laboratory Tests of pH Electrodes in Terms of Industrial Applications Checking Stabilities of Their Parameters and Their Influence on Uncertainties of Measurements
Authors: Wiora Alicja , Wiora Józef
Published: November 2018

Glass pH electrodes are still successfully applied in the chemical and environmental industry. During their long-term use, periodic calibration is required to maintain the required accuracy of measurements because the parameters of the electrodes change over time. This work presents an aging of 11 pH electrodes within approximately 600 days in tap water. During this period, potentials of all electrodes in five buffer solutions were measured 44 times. This allowed determining the aging models of the electrodes. Models in other mediums might be different. Changes in slope, standard potential, hysteresis, and linearity of the characteristics were the objects of observations. A method for predicting electrode parameters is proposed. Furthermore, the procedure for estimating the uncertainty of pH measurements considering the aging of the electrodes is described. As a result of this work, a model of the aging process of pH electrodes in tap water can be constructed and subsequently, the measurement accuracy in the periods between calibrations can be improved.
Design and Evaluation of a Structural Analysis-Based Fault Detection and Identification Scheme for a Hydraulic Torque Converter
Authors: Chen Qi , Wang Jincheng , Ahmed Qadeer
Published: November 2018

A hydraulic torque converter (HTC) is a key component in an automatic transmission. To monitor its operating status and to detect and locate faults, and considering the high-efficiency fault detection and identification (FDI) scheme design by the methodology of structural analysis (SA), this paper presents an SA-based FDI system design and validation for the HTC. By the technique of fault mode and effect analysis (FMEA), eight critical faults are obtained, and then two fault variables are chosen to delegate them. Fault detectability and isolability, coupled with different sensor placements, are analyzed, and as a result, two speed sensors and two torque sensors of pump and turbine are selected to realize the maximal fault detectability and fault isolability: all six faults are detectable, four faults are uniquely isolable, and two faults are isolated from the other faults, but not from each other. Then five minimal structurally overdetermined (MSO) sets are easily acquired by SA to generate five corresponding residuals. The proposed FDI scheme of the HTC by SA is first validated by a theoretical model, then by an offline experiment in a commercial SUV, and the testing results indicate a consistent conclusion with the simulations and theory analysis.
Compressibility of High-Density EEG Signals in Stroke Patients
Authors: Mammone Nadia , De Salvo Simona , Ieracitano Cosimo , Marino Silvia , Cartella Emanuele , Bramanti Alessia , Giorgianni Roberto , Morabito Francesco C.
Published: November 2018

Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between neurons and the macroscopic effects of such currents can be detected at the scalp through electroencephalographic (EEG) sensors. EEG can be used to study the lesions in the brain indirectly, by studying their effects on the brain electrical activity. The primary goal of the present work was to investigate possible asymmetries in the activity of the two hemispheres, in the case one of them is affected by a lesion due to stroke. In particular, the compressibility of High-Density-EEG (HD-EEG) recorded at the two hemispheres was investigated since the presence of the lesion is expected to impact on the regularity of EEG signals. The secondary objective was to evaluate if standard low density EEG is able to provide such information. Eighteen patients with unilateral stroke were recruited and underwent HD-EEG recording. Each EEG signal was compressively sensed, using Block Sparse Bayesian Learning, at increasing compression rate. The two hemispheres showed significant differences in the compressibility of EEG. Signals acquired at the electrode locations of the affected hemisphere showed a better reconstruction quality, quantified by the Structural SIMilarity index (SSIM), than the EEG signals recorded at the healthy hemisphere (p < 0.05), for each compression rate value. The presence of the lesion seems to induce an increased regularity in the electrical activity of the brain, thus an increased compressibility.
A Vehicle Recognition Algorithm Based on Deep Transfer Learning with a Multiple Feature Subspace Distribution
Authors: Wang Hai , Yu Yijie , Cai Yingfeng , Chen Long , Chen Xiaobo
Published: November 2018

Vehicle detection is a key component of environmental sensing systems for Intelligent Vehicles (IVs). The traditional shallow model and offline learning-based vehicle detection method are not able to satisfy the real-world challenges of environmental complexity and scene dynamics. Focusing on these problems, this work proposes a vehicle detection algorithm based on a multiple feature subspace distribution deep model with online transfer learning. Based on the multiple feature subspace distribution hypothesis, a deep model is established in which multiple Restricted Boltzmann Machines (RBMs) construct the lower layers and a Deep Belief Network (DBN) composes the superstructure. For this deep model, an unsupervised feature extraction method is applied, which is based on sparse constraints. Then, a transfer learning method with online sample generation is proposed based on the deep model. Finally, the entire classifier is retrained online with supervised learning. The experiment is actuated using the KITTI road image datasets. The performance of the proposed method is compared with many state-of-the-art methods and it is demonstrated that the proposed deep transfer learning-based algorithm outperformed existing state-of-the-art methods.
Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review
Authors: Tang Xiaoli , Wang Xianghong , Cattley Robert , Gu Fengshou , Ball Andrew D.
Published: November 2018

Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.
A High-Birefringence Microfiber Sagnac-Interferometer Biosensor Based on the Vernier Effect
Authors: Wang Xue-Zhou , Wang Qi
Published: November 2018

We propose a high-sensitive Sagnac-interferometer biosensor based on theVernier effect (VE) with a high-birefringence microfiber. The sensitivity enhancement is achieved by utilizing two cascaded Sagnac interferometers. One of the two interference loops consists of a panda polarization-maintaining fiber as a filter, whilst the other is comprised of high-birefringent microfiber coated Graphene oxide (GO) as a sensing channel. We theoretically analyzed the sensitivity of the sensor and verified it with experiments. The results of the simulation show that the refractive index sensitivity is more than five times that of the fiber sensor based on a single Sagnac loop. The sensitivity of the refractive index in the experiments can reach 2429 nm/refractive index unit (RIU), which is basically in accordance with the simulation. We also use electrostatic adsorption to coat GO on the surface of the sensing channel. GO is employed to adsorb bovine serum albumin (BSA) molecules to achieve the desired detection results, which has good biocompatibility and large specific surface area. The sensitivity to detect BSA can reach 9.097 nm/(mg×mL−1).
Intensification and Upgrading Dynamics in Emerging Dairy Clusters in the East African Highlands
Authors: Van der Lee Jan , Klerkx Laurens , Bebe Bockline Omedo , Mengistu Ashenafi , Oosting Simon
Published: November 2018

Based on farmer and value chain actor interviews, this comparative study of five emerging dairy clusters elaborates on the upgrading of farming systems, value chains, and context shapes transformations from semi-subsistent to market-oriented dairy farming. The main results show unequal cluster upgrading along two intensification dimensions: dairy feeding system and cash cropping. Intensive dairy is competing with other high-value cash crop options that resource-endowed farmers specialize in, given conducive support service arrangements and context conditions. A large number of drivers and co-dependencies between technical, value chain, and institutional upgrading build up to system jumps. Transformation may take decades when market and context conditions remain sub-optimal. Clusters can be expected to move further along initial intensification pathways, unless actors consciously redirect course. The main theoretical implications for debate about cluster upgrading are that co-dependencies between farming system, market, and context factors determine upgrading outcomes; the implications for the debate about intensification pathways are that they need to consider differences in farmer resource endowments, path dependency, concurrency, and upgrading investments. Sustainability issues for consideration include enabling a larger proportion of resource-poor farmers to participate in markets; enabling private input and service provision models; attention for food safety; and climate smartness.
Investigating Key Factors Influencing Farming Decisions Based on Soil Testing and Fertilizer Recommendation Facilities (STFRF)—A Case Study on Rural Bangladesh
Authors: Faruque-As-Sunny  , Huang Zuhui , Karimanzira Taonarufaro Tinaye Pemberai
Published: November 2018

Proper nourishment is fundamental for satisfactory crop growth and production. However, for efficient crop production, it is important to understand the soil environment, to recognize the limitations of that environment, and to ameliorate them where possible without damaging the soil quality. Soil testing and fertilizer recommendation facilities (STFRF) can help farmers to achieve environmental and economic sustainability by assisting them in recognizing their soil condition, reducing agrochemicals usage, using an appropriate amount of fertilizer, minimizing input costs, and achieving higher yield. These facilities are not new in the context of Bangladesh, yet the adoption rate among farmers is low and its determinants have rarely been empirically tested based on microlevel data. Therefore, this study examined those factors underlying the adoption of soil testing and fertilizer recommendation facilities using field surveyed data of 176 individual farmers. Our evidence shows that young farmers with less farming experience are more likely to adopt these facilities. Additionally, being small-scale farmers, having higher education, having more farming income, and having more knowledge about these facilities and the fees of these facilities were found to have a significant effect on the adoption. On the other hand, gender, land ownership, and secondary income were found to be insignificant with regard to the adoption of soil testing and fertilizer recommendation facilities. Our results also revealed that most adopter farmers not only focused on profitability, but were additionally concerned with environmental well-being.
Towards Economic Corporate Sustainability in Reporting: What Does Earnings Management around Equity Offerings Mean for Long-Term Performance?
Authors: Lizińska Joanna , Czapiewski Leszek
Published: November 2018

Companies are very important contributors to the long-term sustainable wealth of economies and society. Public companies are likely to be especially important for economic, environmental, and social development. That is why we focus on initial public offerings (IPO). Responsible external reporting relates to the long-term value of companies and influences perceptions of value by stakeholders. This study contributes to the literature not only because it concentrates on earning quality in terms of going public, but it also combines it with another market puzzle, namely, long-term value. Previous conclusions for other markets should not simply be generalized for Poland, as the country has been an emerging market with many public firms controlled by insiders, with a limited role for the equity market and quite considerable bank financing. Using a unique dataset, we find positive and significant discretionary accruals in the IPO year, which may be perceived as a sign of poor earning quality. We also show that these accruals are negatively correlated with subsequent long-term market value for IPOs made before the financial crisis. The general conclusions are robust with respect to the latest innovations in proxies for earnings management, and also to a variety of alternative specifications.
The Panama Canal Expansion and Its Impact on East–West Liner Shipping Route Selection
Authors: Pham Thi Yen , Kim Ki Young , YEO Gi-Tae
Published: November 2018

Through an empirical study of ocean-borne trade between Hong Kong and New York, we combined qualitative and quantitative analysis to examine route selection decisions in a post-expansion era of the Panama Canal. A two-stage methodological framework was developed to assess the competitiveness of the three route alternatives, namely the Panama and Suez canals and the US intermodal system. In the first stage, a combination of literature review and expert knowledge was employed to identify the determinants of route selection. In the second stage, fuzzy theory and the multi-criteria decision-making technique were used to evaluate the criteria and the route alternatives. The results indicate that transportation cost is the most important factor in choosing a route, followed by transportation time, reliability, and route characteristics. The “all water route” via the Panama Canal is preferred over the Suez and U.S. intermodal options.