bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemotherapy Resistance Explained through Endoplasmic Reticulum Stress-Dependent Signaling
Authors: Bahar Entaz , Kim Ji-Ye , Yoon Hyonok
Published: March 2019

Cancers cells have the ability to develop chemotherapy resistance, which is a persistent problem during cancer treatment. Chemotherapy resistance develops through different molecular mechanisms, which lead to modification of the cancer cells signals needed for cellular proliferation or for stimulating an immune response. The endoplasmic reticulum (ER) is an important organelle involved in protein quality control, by promoting the correct folding of protein and ER-mediated degradation of unfolded or misfolded protein, namely, ER-associated degradation. Disturbances of the normal ER functions causes an accumulation of unfolded or misfolded proteins in the ER lumen, resulting in a condition called “ER stress (ERS).” ERS triggers the unfolded protein response (UPR)—also called the ERS response (ERSR)—to restore homeostasis or activate cell death. Although the ERSR is one emerging potential target for chemotherapeutics to treat cancer, it is also critical for chemotherapeutics resistance, as well. However, the detailed molecular mechanism of the relationship between the ERSR and tumor survival or drug resistance remains to be fully understood. In this review, we aim to describe the most vital molecular mechanism of the relationship between the ERSR and chemotherapy resistance. Moreover, the review also discusses the molecular mechanism of ER stress-mediated apoptosis on cancer treatments.
Effect of Dilute Acid and Alkali Pretreatments on the Catalytic Performance of Bamboo-Derived Carbonaceous Magnetic Solid Acid
Authors: Zhu Yikui , Huang Jiawei , Sun Shaolong , Wu Aimin , Li Huiling
Published: March 2019

Lignocellulose is a widely used renewable energy source on the Earth that is rich in carbon skeletons. The catalytic hydrolysis of lignocellulose over magnetic solid acid is an efficient pathway for the conversion of biomass into fuels and chemicals. In this study, a bamboo-derived carbonaceous magnetic solid acid catalyst was synthesized by FeCl3 impregnation, followed by carbonization and –SO3H group functionalization. The prepared catalyst was further subjected as the solid acid catalyst for the catalytic conversion of corncob polysaccharides into reducing sugars. The results showed that the as-prepared magnetic solid acid contained –SO3H, –COOH, and polycyclic aromatic, and presented good catalytic performance for the hydrolysis of corncob in the aqueous phase. The concentration of H+ was in the range of 0.6487 to 2.3204 mmol/g. Dilute acid and alkali pretreatments of raw material can greatly improve the catalytic activity of bamboo-derived carbonaceous magnetic solid acid. Using the catalyst prepared by 0.25% H2SO4-pretreated bamboo, 6417.5 mg/L of reducing sugars corresponding to 37.17% carbohydrates conversion could be obtained under the reaction conditions of 120 °C for 30 min.
The Use of Power Ultrasound for the Production of PEMFC and PEMWE Catalysts and Low-Pt Loading and High-Performing Electrodes
Authors: Pollet Bruno
Published: March 2019

This short review paper highlights some of the research works undertaken over the years by Pollet’s research groups in Birmingham, Cape Town, and Trondheim, in the use of power ultrasound for the fabrication of low temperature fuel cell and electrolyzer catalysts and electrodes. Since the publication of ‘The use of ultrasound for the fabrication of fuel cell materials’ in 2010, there has been an upsurge of international interest in the use of power ultrasound, sonochemistry, and sonoelectrochemistry for the production of low temperature fuel cell and electrolyzer materials. This is because power ultrasound offers many advantages over traditional synthetic methods. The attraction of power ultrasound is the ability to create localized transient high temperatures and pressures, as a result of cavitation, in solutions at room temperature.
Investigation of Various Pd Species in Pd/BEA for Cold Start Application
Authors: Zhang Beibei , Shen Meiqing , Wang Jianqiang , Wang Jiaming , Wang Jun
Published: March 2019

A series of Pd/BEA catalysts with various Pd loadings were synthesized. Two active Pd2+ species, Z−-Pd2+-Z− and Z−-Pd(OH)+, on exchanged sites of zeolites, were identified by in situ FTIR using CO and NH3 respectively. Higher NOx storage capacity of Z−-Pd2+-Z− was demonstrated compared with that of Z−-Pd(OH)+, which was caused by the different resistance to H2O. Besides, lower Pd loading led to a sharp decline of Z−-Pd(OH)+, which was attributed to the ‘exchange preference’ for Z−-Pd2+-Z− in BEA. Based on this research, the atom utilization of Pd can be improved by decreasing Pd loading.
Zeolites as Acid/Basic Solid Catalysts: Recent Synthetic Developments
Authors: Verdoliva Valentina , Saviano Michele , De Luca Stefania
Published: March 2019

The zeolites are porous solid structures characterized by a particular framework of aluminosilicates, in which the incorporation of the Al+3 ions generates an excess of negative charge compensated by cations (usually alkali or alkali earth) or protons. In the latter case, they are employed as catalysts for a wide variety of reactions, such as dehydration, skeletal isomerization and cracking, while the catalytic activity of basic zeolites has not found, up to now, any industrial or whatever relevant application in chemical processes. In the present review, we firstly intend to give an overview of the fundamental chemical composition, as well as the structural features of the zeolite framework. The purpose of this paper is to analyze their key properties as acid, both Lewis and Brønsted, and basic solid support. Their application as catalysts is discussed by reviewing the already published works in that field, and a final remark of their still unexplored potential as green, mild, and selective catalyst is also reported.
Dictyostelium: A Model for Studying the Extracellular Vesicle Messengers Involved in Human Health and Disease
Authors: Tatischeff Irène
Published: March 2019

Cell-derived extracellular vesicles (EVs) are newly uncovered messengers for intercellular communication. They are released by almost all cell types in the three kingdoms, Archeabacteria, Bacteria and Eukaryotes. They are known to mediate important biological functions and to be increasingly involved in cell physiology and in many human diseases, especially in oncology. The aim of this review is to recapitulate the current knowledge about EVs and to summarize our pioneering work about Dictyostelium discoideum EVs. However, many challenges remain unsolved in the EV research field, before any EV application for theranostics (diagnosis, prognosis, and therapy) of human cancers, can be efficiently implemented in the clinics. Dictyostelium might be an outstanding eukaryotic cell model for deciphering the utmost challenging problem of EV heterogeneity, and for unraveling the still mostly unknown mechanisms of their specific functions as mediators of intercellular communication.
Associations between Fatty Acid-Binding Protein 4–A Proinflammatory Adipokine and Insulin Resistance, Gestational and Type 2 Diabetes Mellitus
Authors: Trojnar Marcin , Patro-Małysza Jolanta , Kimber-Trojnar Żaneta , Leszczyńska-Gorzelak Bożena , Mosiewicz Jerzy
Published: March 2019

There is ample scientific evidence to suggest a link between the fatty acid-binding protein 4 (FABP4) and insulin resistance, gestational (GDM), and type 2 (T2DM) diabetes mellitus. This novel proinflammatory adipokine is engaged in the regulation of lipid metabolism at the cellular level. The molecule takes part in lipid oxidation, the regulation of transcription as well as the synthesis of membranes. An involvement of FABP4 in the pathogenesis of obesity and insulin resistance seems to be mediated via FABP4-dependent peroxisome proliferator-activated receptor γ (PPARγ) inhibition. A considerable number of studies have shown that plasma concentrations of FABP4 is increased in obesity and T2DM, and that circulating FABP4 levels are correlated with certain clinical parameters, such as body mass index, insulin resistance, and dyslipidemia. Since plasma-circulating FABP4 has the potential to modulate the function of several types of cells, it appears to be of extreme interest to try to develop potential therapeutic strategies targeting the pathogenesis of metabolic diseases in this respect. In this manuscript, representing a detailed review of the literature on FABP4 and the abovementioned metabolic disorders, various mechanisms of the interaction of FABP4 with insulin signaling pathways are thoroughly discussed. Clinical aspects of insulin resistance in diabetic patients, including women diagnosed with GDM, are analyzed as well.
Analysis on Environmental Thermal Effect of Functionally Graded Nanocomposite Heat Reflective Coatings for Asphalt Pavement
Authors: Zheng Mulian , Tian Yanjuan , He Litao
Published: March 2019

The heat-reflective coating for asphalt pavement is a functional layer applied on pavement surfaces to reduce heat storage in the pavement via reflecting sunlight, thus inhibiting pavement temperature rise. The objective of this study was to analyze the environmental thermal effect of the self-developed reflective coating, namely, functionally graded nanocomposite reflective coatings, for asphalt pavement. The thermal effects of heat-reflective coatings were compared and analyzed based on field tests. A heating model of the atmosphere layer near the road surface was established. Moreover, the influence of urban road temperature on the thermal comfort of the human body was analyzed. Results showed that the radiation heat of all heat-reflective coatings decreased around two-thirds, and the convective heat decreased nearly 50% when compared with the control asphalt pavement, and the temperatures of the pavement itself and the atmosphere layer were lowered. Additionally, the heat-reflective coating improved the thermal comfort of the human body. This indicated that the heat-reflective coating reduced ambient temperate and relieved the urban heat island effect (UHI) as well as improved the environmental thermal effect.
Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review
Authors: Pehrson Lea Marie , Nielsen Michael Bachmann , Ammitzbøl Lauridsen Carsten
Published: March 2019

The aim of this study was to provide an overview of the literature available on machine learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection (LIDC-IDRI) database as a tool for the optimization of detecting lung nodules in thoracic CT scans. This systematic review was compiled according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles concerning algorithms applied to the LIDC-IDRI database were included. The initial search yielded 1972 publications after removing duplicates, and 41 of these articles were included in this study. The articles were divided into two subcategories describing their overall architecture. The majority of feature-based algorithms achieved an accuracy >90% compared to the deep learning (DL) algorithms that achieved an accuracy in the range of 82.2%–97.6%. In conclusion, ML and DL algorithms are able to detect lung nodules with a high level of accuracy, sensitivity, and specificity using ML, when applied to an annotated archive of CT scans of the lung. However, there is no consensus on the method applied to determine the efficiency of ML algorithms.
Descriptions of Entropy with Fractal Dynamics and Their Applications to the Flow Pressure of Centrifugal Compressor
Authors: Liu Yan , Ding Dongxiao , Ma Kai , Gao Kuan
Published: March 2019

In this study, some important intrinsic dynamics have been captured after analyzing the relationships between the dynamic pressure at an outlet of centrifugal compressor and fractal characteristics, which is one of powerful descriptions in entropy to measure the disorder or complexity in the nonlinear dynamic system. In particular, the fractal dynamics of dynamic pressure of the flow is studied, as the centrifugal compressor is in surge state, resulting in the dynamic pressure of flow and becoming a serious disorder and complex. First, the dynamic pressure at outlet of a centrifugal compressor with 800 kW is tested and then obtained by controlling the opening of the anti-surge valve at the outlet, and both the stable state and surge are initially tested and analyzed. Subsequently, the fractal dynamics is introduced to study the intrinsic dynamics of dynamic pressure under various working conditions, in order to identify surge, which is one typical flow instability in centrifugal compressor. Following fractal dynamics, the Hurst exponent, autocorrelation functions, and variance in measure theories of entropy are studied to obtain the mono-fractal characteristics of the centrifugal compressor. Further, the multi-fractal spectrums are investigated in some detail, and their physical meanings are consequently explained. At last, the statistical reliability of multi-fractal spectrum by modifying the original data has been studied. The results show that a distinct relationship between the dynamic pressure and fractal characteristics exists, including mono-fractal and multi-fractal, and such fractal dynamics are intrinsic. As the centrifugal compressor is working under normal condition, its autocorrelation function curve demonstrates apparent stochastic characteristics, and its Hurst exponent and variance are lower. However, its autocorrelation function curve demonstrates an apparent heavy tail distribution, and its Hurst exponent and variance are higher, as it is working in an unstable condition, namely, surge. In addition, the results show that the multi-fractal spectrum parameters are closely related to the dynamic pressure. With the state of centrifugal compressor being changed from stable to unstable states, some multi-fractal spectrum parameters Δα, Δf(α), αmax, and f(αmin) become larger, but αmin in the multi-fractal spectrum show the opposite trend, and consistent properties are graphically shown for the randomly shuffled data. As a conclusion, the proposed method, as one measure method for entropy, can be used to feasibly identify the incipient surge of a centrifugal compressor and design its surge controller.
An Investigation of Students’ Use of a Computational Science Simulation in an Online High School Physics Class
Authors: Rosenberg Joshua M. , Lawson Michael A.
Published: March 2019

Science educators have begun to explore how students have opportunities to not only view and manipulate simulations, but also to analyze the complex sources of data they generate. While scholars have documented the characteristics and the effects of using simulations as a source of data in face-to-face, K-12 classrooms, how simulations can be taken up and used in such a way in fully-online classes is less-explored. In this study, we present results from our initial qualitative investigation of students’ use of a simulation in such a way across three lessons in an online, Advanced Placement high school physics class. In all, 13 students participated in the use of a computational science simulation that we adapted to output quantitative data across the lesson sequence. Students used the simulation and developed a class data set, which students then used to understand, interpret, and model a thermodynamics-related concept and phenomenon. We explored the progression of students’ conceptual understanding across the three lessons, students’ perceptions of the strengths and weaknesses of the simulation, and how students balanced explaining variability and being able to interpret their model of the class data set. Responses to embedded assessment questions indicated that a few developed more sophisticated conceptual understanding of the particle nature of matter and how it relates to diffusion, while others began the lesson sequence with an already-sophisticated understanding, and a few did not demonstrate changes in their understanding. Students reported that the simulation helped to make a complex idea more accessible and useful and that the data generated by the simulation made it easier to understand what the simulation was representing. When analyzing the class data set, some students focused on fitting the data, not considering the interpretability of the model as much, whereas other students balanced model fit with interpretability and usefulness. In all, findings suggest that the lesson sequence had educational value, but that modifications to the design of the simulation and lesson sequence and to the technologies used could enhance its impact. Implications and recommendations for future research focus on the potential for simulations to be used to engage students in a variety of scientific and engineering practices in online science classes.
Quadruple-Mode Wideband Bandpass Filter with Improved Out-of-Band Rejection
Authors: Hameed Musab , Xiao Gaobiao , Najam Ali Imran , Qiu Lina , Hameed Tayyab
Published: March 2019

This paper proposes a method for designing a quadruple-mode wideband bandpass filter using off-centered perturbed metallic cylinders in a rectangular waveguide cavity with compact size and improved out-of-band rejection. Two off-centered perturbation cylinders were placed at the bottom of the rectangular waveguide cavity along with a pair of perpendicularly-fed coaxial lines, which excited four quasi-transverse magnetic (TM) modes to realize the desired passband. The height of the waveguide cavity and the shape of the perturbation cylinders were exploited to achieve an all quasi-TM modes filter with good out-of-band rejection and sharp skirt selectivity. The proposed filter operates at 2.93 GHz center frequency with 38% wide fractional bandwidth (FBW). The proposed filter is fabricated using aluminum. The measured and simulated results are in good agreement with each other.
Scalable Single-Phase Multi-Functional Inverter for Integration of Rooftop Solar-PV to Low-Voltage Ideal and Weak Utility Grid
Authors: Oruganti Venkata Subrahmanya Raghavendra Varaprasad , Dhanikonda Venkata Sesha Samba Siva Sarma , Simões Marcelo Godoy
Published: March 2019

Integration of rooftop solar-PV (RTSPV) systems and extensive use of nonlinear loads in the low-voltage distribution system (LVDS) leads to poor power quality (PQ). Therefore, it is necessary to address the issues leading to poor PQ at the point of common coupling of the LVDS. In this article, a multi-band hysteresis current control (MB-HCC) for the multi-functional inverter (MFI) is proposed which improves the efficiency of the MFI and also enhances the PQ of the LVDS. The MB-HCC uses simple switching logic and outperforms in its multi-functional tasks such as active power injection and power conditioning. MB-HCC offers better efficiency over variable double-band HCC (VDB-HCC) as it operates at a lower switching frequency. The performance of the proposed system is simulated by using MATLAB/Simulink and validated by OPAL-RT based real-time simulation studies. During the variation of solar irradiation, the proposed MFI has an average efficiency of 98.5% under the ideal grid and 97.34% under the distorted grid. Moreover, the percentage of Total Harmonic Distortion under ideal and distorted grid conditions is brought down to below 5%, and also, reactive power compensation maintains unity power factor operation complying with the IEEE-519-2014 and 1547 standards. These results substantiate the hypothesis of scalability of the single-phase MB-HCC-based MFI for an LVDS contributing to economy and ecology.
Remote Sensing Image Fusion Based on Sparse Representation and Guided Filtering
Authors: Ma Xiaole , Hu Shaohai , Liu Shuaiqi , Fang Jing , Xu Shuwen
Published: March 2019

In this paper, a remote sensing image fusion method is presented since sparse representation (SR) has been widely used in image processing, especially for image fusion. Firstly, we used source images to learn the adaptive dictionary, and sparse coefficients were obtained by sparsely coding the source images with the adaptive dictionary. Then, with the help of improved hyperbolic tangent function (tanh) and l 0 − max , we fused these sparse coefficients together. The initial fused image can be obtained by the image fusion method based on SR. To take full advantage of the spatial information of the source images, the fused image based on the spatial domain (SF) was obtained at the same time. Lastly, the final fused image could be reconstructed by guided filtering of the fused image based on SR and SF. Experimental results show that the proposed method outperforms some state-of-the-art methods on visual and quantitative evaluations.
A 2.6 GS/s 8-Bit Time-Interleaved SAR ADC in 55 nm CMOS Technology
Authors: Wang Dong , Zhu Xiaoge , Guo Xuan , Luan Jian , Zhou Lei , Wu Danyu , Liu Huasen , Wu Jin , Liu Xinyu
Published: March 2019

This paper presents an eight-channel time-interleaved (TI) 2.6 GS/s 8-bit successive approximation register (SAR) analog-to-digital converter (ADC) prototype in a 55-nm complementary metal-oxide-semiconductor (CMOS) process. The channel-selection-embedded bootstrap switch is adopted to perform sampling times synchronization using the full-speed master clock to suppress the time skew between channels. Based on the segmented pre-quantization and bypass switching scheme, double alternate comparators clocked asynchronously with background offset calibration are utilized in sub-channel SAR ADC to achieve high speed and low power. Measurement results show that the signal-to-noise-and-distortion ratio (SNDR) of the ADC is above 38.2 dB up to 500 MHz input frequency and above 31.8 dB across the entire first Nyquist zone. The differential non-linearity (DNL) and integral non-linearity (INL) are +0.93/−0.85 LSB and +0.71/−0.91 LSB, respectively. The ADC consumes 60 mW from a 1.2 V supply, occupies an area of 400 μm × 550 μm, and exhibits a figure-of-merit (FoM) of 348 fJ/conversion-step.
Wireless Energy Harvesting with Cooperative Relaying under the Best Relay Selection Scheme
Authors: Andrawes Admoon , Nordin Rosdiadee , Ismail Mahamod
Published: March 2019

One of the most notable challenges in wireless communications is energy scarcity, which has attracted considerable attention in Fifth Generation (5G) wireless network research. This paper investigates the performance of energy harvesting (EH) relays under the best relay selection (BRS) scheme. The results show degradation of spectral efficiency (SE) due to EH relaying compared with conventional cooperative relaying (CR). Conversely, EH relaying provides a positive gain compared with conventional CR, increasing the lifetime of the network and decreasing energy consumption (EC) and operational cost. Moreover, the EH relaying network has better energy efficiency (EE) compared with conventional relaying networks. Results show that when EH relaying is applied, EE is improved through an increased number of relays. Finally, the SE-EE metric is presented for both conventional and EH relays. Results show that the performance of the proposed technique was able to achieve a maximum SE of 1.4 bits/s/Hz and maximum EE at 0.6 bits/s/Hz, and for the case of conventional relays, a maximum SE of 2 bits/s/Hz and EE at 1.1 bits/s/Hz. This result implies that the proposed EH scheme provides an optimum solution for energy-constrained wireless CR systems.
Intertemporal Static and Dynamic Optimization of Synthesis, Design, and Operation of Integrated Energy Systems of Ships
Authors: Sakalis George N. , Tzortzis George J. , Frangopoulos Christos A.
Published: March 2019

Fuel expenses constitute the largest part of the operating cost of a merchant ship. Integrated energy systems that cover all energy loads with low fuel consumption, while being economically feasible, are increasingly studied and installed. Due to the large variety of possible configurations, design specifications, and operating conditions that change with time, the application of optimization methods is imperative. Designing the system for nominal conditions only is not sufficient. Instead, intertemporal optimization needs to be performed that can be static or dynamic. In the present article, intertemporal static and dynamic optimization problems for the synthesis, design, and operation (SDO) of integrated ship energy systems are stated mathematically and the solution methods are presented, while case studies demonstrate the applicability of the methods and also reveal that the optimal solution may defer significantly from the solutions suggested with the usual practice. While in other works, the SDO optimization problems are usually solved by two- or three-level algorithms; single-level algorithms are developed and applied here, which tackle all three aspects (S, D, and O) concurrently. The methods can also be applied on land installations, e.g., power plants, cogenerations systems, etc., with proper modifications.
Flow Conditions for PATs Operating in Parallel: Experimental and Numerical Analyses
Authors: Simão Mariana , Pérez-Sánchez Modesto , Carravetta Armando , Ramos Helena M.
Published: March 2019

Micro-hydro systems can be used as a promising new source of renewable energy generation, requiring a low investment cost of hydraulic, mechanical, and electrical equipment. The improvement of the water management associated with the use of pumps working as turbines (PATs) is a real advantage when the availability of these machines is considered for a wide range of flow rates and heads. Parallel turbomachines can be used to optimize the flow management of the system. In the present study, experimental tests were performed in two equal PATs working in parallel and in single mode. These results were used to calibrate and validate the numerical simulations. The analysis of pressure variation and head losses was evaluated during steady state conditions using different numerical models (1D and 3D). From the 1D model, the installation curve of the system was able to be defined and used to calculate the operating point of the two PATs running in parallel. As for the computational fluid dynamics (CFD) model, intensive analysis was carried out to predict the PATs′ behavior under different flow conditions and to evaluate the different head losses detected within the impellers. The results show system performance differences between two units running in parallel against a single unit, providing a greater operational flow range. The performance in parallel design conditions show a peak efficiency with less shock losses within the impeller. Furthermore, by combining multiple PATs in parallel arrangement, a site’s efficiency increases, covering a wide range of applications from the minimum to the maximum flow rate. The simulated flow rates were in good agreement with the measured data, presenting an average error of 10%.
Power Management Control Strategy Based on Artificial Neural Networks for Standalone PV Applications with a Hybrid Energy Storage System
Authors: Faria João , Pombo José , Calado Maria do Rosário , Mariano Sílvio
Published: March 2019

Standalone microgrids with photovoltaic (PV) solutions could be a promising solution for powering up off-grid communities. However, this type of application requires the use of energy storage systems (ESS) to manage the intermittency of PV production. The most commonly used ESSs are lithium-ion batteries (Li-ion), but this technology has a low lifespan, mostly caused by the imposed stress. To reduce the stress on Li-ion batteries and extend their lifespan, hybrid energy storage systems (HESS) began to emerge. Although the utilization of HESSs has demonstrated great potential to make up for the limitations of Li-ion batteries, a proper power management strategy is key to achieving the HESS objectives and ensuring a harmonized system operation. This paper proposes a novel power management strategy based on an artificial neural network for a standalone PV system with Li-ion batteries and super-capacitors (SC) HESS. A typical standalone PV system is used to demonstrate and validate the performance of the proposed power management strategy. To demonstrate its effectiveness, computational simulations with short and long duration were performed. The results show a minimization in Li-ion battery dynamic stress and peak current, leading to an increased lifespan of Li-ion batteries. Moreover, the proposed power management strategy increases the level of SC utilization in comparison with other well-established strategies in the literature.
The Effect of Wet Compression on a Centrifugal Compressor for a Compressed Air Energy Storage System
Authors: Sun Jianting , Zhou Xin , Liang Qi , Zuo Zhitao , Chen Haisheng
Published: March 2019

There is an urgent demand to reduce compression power consumption in Compressed Air Energy Storage (CAES) systems. Wet compression has been widely used in gas turbines to reduce compressor power consumption and improve thermal efficiency, but this technology has not been applied yet in the CAES field. In this paper, a centrifugal compressor for CAES was numerically studied to investigate the effect of wet compression on compressor and droplet motion. The results showed that wet compression makes the performance curve shift to a high-pressure ratio/efficiency. Meanwhile, wet compression lowers the stall margin and narrows the stable operation range, and the effect is enhanced with the increase of water injection ratio or the decrease of average droplet diameter. Wet compression can effectively save compressor power consumption during energy storage, and at the designed pressure ratio, the power consumption can be reduced by 1.47% with a water injection ratio of 3% and an average droplet diameter of 5 μm. Influenced by the inertia and secondary flow, the droplets migrate to the impeller pressure and shroud side, thus causing brake loss by impacting on blades. The migration of droplets strengthens with the increase in the average droplet diameter and flow coefficient.
Determinants of the Willingness to Energy Monitoring by Residential Consumers: A Case Study in the City of Wroclaw in Poland
Authors: Kowalska-Pyzalska Anna , Byrka Katarzyna
Published: March 2019

This paper analyses attitudinal and socio-economic determinants of the householders’ willingness to monitor their energy consumption. Residential consumers can monitor their energy consumption by means of traditional (electricity bill) and modern tools (smart metering information platforms, SMP). Within this empirical study we test the effect of environmental attitudes, knowledge and perceived possibilities on consumers’ stages of readiness to adopt SMP based the stage model of self-regulated behavioral change (SSCB). Perceived possibilities to monitor energy consumption on a regular basis was found to be the predictor of adoption in every examined stage of readiness. General knowledge predicted adoption of the stage in which consumers declared willingness to learn know-how of using SMP. The results suggest that an effectiveness of educational campaigns may be restricted to only some consumers.
Enhancing Hydrogen Production from Chlorella sp. Biomass by Pre-Hydrolysis with Simultaneous Saccharification and Fermentation (PSSF)
Authors: Giang Tran Thi , Lunprom Siriporn , Liao Qiang , Reungsang Alissara , Salakkam Apilak
Published: March 2019

Simultaneous saccharification and fermentation (SSF) and pre-hydrolysis with SSF (PSSF) were used to produce hydrogen from the biomass of Chlorella sp. SSF was conducted using an enzyme mixture consisting of 80 filter paper unit (FPU) g-biomass−1 of cellulase, 92 U g-biomass−1 of amylase, and 120 U g-biomass−1 of glucoamylase at 35 °C for 108 h. This yielded 170 mL-H2 g-volatile-solids−1 (VS), with a productivity of 1.6 mL-H2 g-VS−1 h−1. Pre-hydrolyzing the biomass at 50 °C for 12 h resulted in the production of 1.8 g/L of reducing sugars, leading to a hydrogen yield (HY) of 172 mL-H2 g-VS−1. Using PSSF, the fermentation time was shortened by 36 h in which a productivity of 2.4 mL-H2 g-VS−1 h−1 was attained. To the best of our knowledge, the present study is the first report on the use of SSF and PSSF for hydrogen production from microalgal biomass, and the HY obtained in the study is by far the highest yield reported. Our results indicate that PSSF is a promising process for hydrogen production from microalgal biomass.
Experimental Analysis of Brewers’ Spent Grains Steam Gasification in an Allothermal Batch Reactor
Authors: Ferreira Sérgio , Monteiro Eliseu , Brito Paulo , Castro Carlos , Calado Luís , Vilarinho Cândida
Published: March 2019

In this work, brewers’ spent grains (BSG) were evaluated and studied in order to obtain a combustible gas by means of allothermal steam gasification. BSG were preprocessed in a rotary dryer and a pelletizer prior to gasification in an indirectly heated batch reactor. BSG characterization was conducted by means of proximate, ultimate, and thermogravimetric analysis, allowing us to conclude that BSG have characteristics comparable to those of regular lignocellulosic biomasses. Gasification tests were performed in an allothermal bench-scale batch reactor in order to determine the effect of temperature and steam-to-biomass ratio (S/B) in the produced gas. The produced gas was mainly composed of 22.8–30.2% H2, 15.1–22.3% CO, and 7.2–11.1% CH4, contributing to a heating value of 8.11–9.0 MJ/Nm3 with the higher values found for a low S/B ratio and for high temperatures. The performance of the process was assessed by evaluating the cold gas and carbon conversion efficiencies. These indicators were found to be in the ranges 47.0%–52.1% and 57.0%–62.7%, respectively. The main conclusion of this work is that the produced gas obtained from BSG steam gasification has sufficient quality to open other options to beer producers to use their own brewing wastes to satisfy their energy needs, allowing them to progress toward the circular economy concept.
Evaluating the Eccentricities of Poplar Stem Profiles with Terrestrial Laser Scanning
Authors: Puletti Nicola , Grotti Mirko , Scotti Roberto
Published: March 2019

The value of wood for different timber assortments can vary by a factor of ten. Optimization of stem assortments is, hence, a key element in the wood products supply chain, particularly for plantations. ‘Taper functions’ are commonly used in other countries to tackle this issue. In Italy, this approach has not yet entered operational use. These functions are developed based on measures of stem diameters taken at different distances from the base. Such measurements are commonly taken felling the tree and using a tape meter and tree caliper, clearly assuming some approximations. This research assesses the advantages, in terms of assortments evaluation, that can be obtained if the diameters at different heights are extracted adequately to process terrestrial laser scanning (TLS) output. TLS data have been collected, in a poplar plantation, on 36 trees distributed on three stands with different plantation densities in Padana Plane, Italy. The estimated profiles display high variability with an average of 1.6 cm of lateral compression. The results from this study demonstrate the potential and feasibility of estimating bole eccentricity by TLS, providing preliminary tools that will hopefully favor the diffusion of taper functions in operational environments.
Magnetic Fields Around Galactic Discs
Authors: Moss David , Sokoloff Dmitry
Published: March 2019

Magnetic fields in the discs of spiral galaxies are quite well understood, although, of course, many details still require investigation and future observations with new generations of radio telescopes will be valuable here. Magnetic configurations around galactic discs and, in particular, the magnetic field components perpendicular to galactic discs seem to be much more poorly understood and deserve further investigation both observationally and by modelling. Another problem to be addressed in future investigations is the magnetic configuration in galactic halos and, in particular, interactions with the intergalactic medium and various winds. Finally, the importance of the observational determination of such drivers of galactic dynamo action as mirror asymmetry of the turbulent galactic flows are briefly discussed.
Prospectivity Mapping for Epithermal Deposits of Western Milos Using a Fuzzy Multi Criteria Evaluation Approach Parameterized by Airborne Hyperspectral Remote Sensing Data
Authors: Ferrier Graham , Ganas Athanassios , Pope Richard , Jo Miles A.
Published: March 2019

A Mineral prospectivity mapping (MPM) approach using a GIS-based weighted linear combination implementation of a Multi-Criteria Evaluation approach utilising a fuzzy Analytical Hierarchy Process to elucidate expert knowledge has been implemented to analyse the spatial distribution of epithermal deposits on the Island of Milos, Greece and model their association with exploration evidence data with the aim of providing insights into the controls on ore deposition. An integrated field and Digital Airborne Imaging Spectrometer (DAIS) hyperspectral and thermal multispectral airborne remote sensing dataset supported by field mapping and laboratory analyses, has been utilised to resolve hydrothermal alteration and parameterise the MPM. This study has highlighted the intimate spatial relationship between topographic highs and locations with high grade silicified alteration at a number of locations. The ability of high spatial resolution multispectral Thermal InfraRed (TIR) remote sensing imagery, integrated with topographic data, to resolve these silicified topographic highs provides an additional tool in the exploration of epithermal deposits. The spatial relationships between silicified lithocaps, high-grade altered rocks, faulting and topographic highs were utilised in the development of the MPM model. A close association between the modelled results and the hydrothermal alteration mapped in the field supports the accuracy of this MPM approach.
Identification of Micro-Scale Landforms of Landslides Using Precise Digital Elevation Models
Authors: Chudý František , Slámová Martina , Tomaštík Julián , Prokešová Roberta , Mokroš Martin
Published: March 2019

An active gully-related landslide system is located in a deep valley under forest canopy cover. Generally, point clouds from forested areas have a lack of data connectivity, and optical parameters of scanning cameras lead to different densities of point clouds. Data noise or systematic errors (missing data) make the automatic identification of landforms under tree canopy problematic or impossible. We processed, analyzed, and interpreted data from a large-scale landslide survey, which were acquired by the light detection and ranging (LiDAR) technology, remotely piloted aircraft system (RPAS), and close-range photogrammetry (CRP) using the ‘Structure-from-Motion’ (SfM) method. LAStools is a highly efficient Geographic Information System (GIS) tool for point clouds pre-processing and creating precise digital elevation models (DEMs). The main landslide body and its landforms indicating the landslide activity were detected and delineated in DEM-derivatives. Identification of micro-scale landforms in precise DEMs at large scales allow the monitoring and the assessment of these active parts of landslides that are invisible in digital terrain models at smaller scales (obtained from aerial LiDAR or from RPAS) due to insufficient data density or the presence of many data gaps.
Oceanic Impact on European Climate Changes during the Quaternary
Authors: Martin-Garcia Gloria M.
Published: March 2019

Integrative studies on paleoclimate variations over oceanic and continental regions are scarce. Though it is known that Earth’s climate is strongly affected by sea-air exchanges of heat and moisture, the role of oceans in climate variations over land remains relatively unexplored. With the aim to unveil this influence, the present work studies major climate oscillations in the North Atlantic region and Europe during the Quaternary, focusing on the oceanic mechanisms that were related to them. During this period, the European climate experienced long-term and wide-amplitude glacial-interglacial oscillations. A covariance between the North Atlantic sea surface temperature and climate signals over the continent is especially observed in Southern Europe. The most severe and drastic climate changes occurred in association to deglaciations, as a consequence of major oceanographic reorganizations that affected atmospheric circulation and ocean-atmosphere heat-flow, which led to variation of temperature and precipitation inland. Most deglaciations began when Northern Hemisphere summer insolation was maximal. Increased heating facilitated the rapid ice-sheet collapse and the massive release of fresh water into the Northern Atlantic, which triggered the weakening or even the shutdown of the North Atlantic Deep Water (NADW) formation. Though the extension of ice-sheets determined the high-latitude European climate, the climate was more influenced by rapid variations of ice volume, deep-water formation rate, and oceanic and atmospheric circulation in middle and subtropical latitudes. In consequence, the coldest stadials in the mid-latitude North Atlantic and Europe since the early Pleistocene coincided with Terminations (glacial/interglacial transitions) and lesser ice-sheet depletions. They were related with decreases in the NADW formation rate that occurred at these times and the subsequent advection of subpolar waters along the western European margin. In Southern Europe, steppe communities substituted temperate forests. Once the freshwater perturbation stopped and the overturning circulation resumed, very rapid and wide-amplitude warming episodes occurred (interstadials). On the continent, raised temperature and precipitations allowed the rapid expansion of moisture-requiring vegetation.
Simulating 10,000 Years of Erosion to Assess Nuclear Waste Repository Performance
Authors: Atchley Adam L. , Birdsell Kay H. , Crowell Kelly , Middleton Richard S. , Stauffer Philip H.
Published: March 2019

Long-term environmental performance assessments of natural processes, including erosion, are critically important for waste repository site evaluation. However, assessing a site’s ability to continuously function is challenging due to parameter uncertainty and compounding nonlinear processes. In lieu of unavailable site data for model calibration, we present a workflow to include multiple sources of surrogate data and reduced-order models to validate parameters for a long-term erosion assessment of a low-level radioactive nuclear waste repository. We apply this new workflow to a low-level waste repository on mesas in Los Alamos National Laboratory in New Mexico. To account for parameter uncertainty, we simulate high-, moderate-, and low-erosion cases. The assessment extends to 10,000 years, which results in large erosion uncertainties, but is necessary given the nature of the interred waste. Our long-term erosion analysis shows that high-erosion scenarios produce rounded mesa tops and partially filled canyons, diverging from the moderate-erosion case that results in gullies and sharp mesa rims. Our novel model parameterization workflow and modeling exercise demonstrates the utility of long-term assessments, identifies sources of erosion forecast uncertainty, and demonstrates the utility of landscape evolution model development. We conclude with a discussion on methods to reduce assessment uncertainty and increase model confidence.
Using Gamification and Social Incentives to Increase Physical Activity and Related Social Cognition among Undergraduate Students in Shanghai, China
Authors: Mo Dandan , Xiang Mi , Luo Mengyun , Dong Yuanyuan , Fang Yue , Zhang Shunxing , Zhang Zhiruo , Liang Huigang
Published: March 2019

Gamification and social incentives are promising strategies to increase the effectiveness of web-based physical activity (PA) interventions by improving engagement. In this study, we designed a PA intervention integrating gamification and social incentives based on the most popular social networking service in China, WeChat. A controlled trial involving 52 Chinese undergraduate students was implemented to evaluate the effectiveness of the intervention. Subjects in the intervention group received a 7-week intervention. PA behavior and related social cognitive variables according to the theory of planned behavior were measured at the baseline and after the intervention. Daily physical activity duration was measured during the intervention. The results showed that PA-related subjective norms, perceived behavior control, and intention, as well as self-reported vigorous physical activity and moderate physical activity in the intervention group, were increased after the intervention, compared with the control group (p <0.05). During the intervention, perceived daily physical activity duration in the intervention group was on the rise, while it declined in the control group (p <0.001). The findings indicate that WeChat-based intervention integrating gamification and social incentives could effectively increase subjectively measured PA and related social cognition among Chinese undergraduate students and that it is a promising way to ameliorate the problem of insufficient PA among youths.
Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method
Authors: Hao Mengmeng , Jiang Dong , Ding Fangyu , Fu Jingying , Chen Shuai
Published: March 2019

In recent years, various types of terrorist attacks have occurred which have caused worldwide catastrophes. The ability to proactively detect and even predict a potential terrorist risk is critically important for government agencies to react in a timely manner. In this study, a method of geospatial statistics was used to analyse the spatio-temporal evolution of terrorist attacks on the Indochina Peninsula. The machine learning random forest (RF) method was adopted to predict the potential risk of terrorist attacks on the Indochina Peninsula on a spatial scale with 15 driving factors. The RF model performed well with AUC values of 0.839 [95% confidence interval of 0.833–0.844]. The map of the potential distribution of terrorist attack risk was obtained with a 0.05×0.05-degree (approximately 5×5 km) resolution. The results indicate that Thailand is the most dangerous area for terrorist attacks, especially southern Thailand, Bangkok and its surrounding cities. Middle Cambodia and the northern and southern parts of Myanmar are also high-risk areas. Other areas are relatively low risk. This study provides the hotspots for terrorist attacks on a more fine-grained geographical unit. Meanwhile, it shows that machine learning algorithms (e.g., RF) combined with GIS have great potential for simulating the risk of terrorist attacks.