bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Walled Carbon Nanotubes (SWCNTs) as Solid-Contact in All-Solid-State Perchlorate ISEs: Applications to Fireworks and Propellants Analysis
Authors: Hassan Saad S. M. , Galal Eldin Ahmed , Amr Abd El-Galil E. , Al-Omar Mohamed A. , Kamel Ayman H.
Published: June 2019

Herein, we present reliable, robust, stable, and cost-effective solid-contact ion-selective electrodes (ISEs) for perchlorate determination. Single-walled carbon nanotubes (SWCNTs) were used as solid-contact material and indium (III) 5, 10, 15, 20-(tetraphenyl) porphyrin chloride (InIII-porph) as an ion carrier. The sensor exhibited an improved sensitivity towards ClO4− ions with anionic slope of −56.0 ± 1.1 (R2 = 0.9998) mV/decade over a linear range 1.07 × 10−6 – 1.0 × 10−2 M and detection limit of 1.8 × 10−7 M. The short-term potential stability and the double-layer capacitance were measured by chronopotentiometric and electrochemical impedance spectroscopy (EIS) measurements, respectively. The sensor is used for ClO4− determination in fireworks and propellant powders. The results fairly agree with data obtained by ion chromatography.
Improving Sensitivity in Raman Imaging for Thin Layered and Powdered Food Analysis Utilizing a Reflection Mirror
Authors: Lohumi Santosh , Kim Moon S. , Qin Jianwei , Cho Byoung-Kwan
Published: June 2019

Raman imaging has been proven to be a powerful analytical technique for the characterization and visualization of chemical components in a range of products, particularly in the food and pharmaceutical industries. The conventional backscattering Raman imaging technique for the spatial analysis of a deep layer suffers from the presence of intense fluorescent and Raman signals originating from the surface layer which mask the weaker subsurface signals. Here, we demonstrated the application of a new reflection amplifying method using a background mirror as a sample holder to increase the Raman signals from a deep layer. The approach is conceptually demonstrated on enhancing the Raman signals from the subsurface layer. Results show that when bilayer samples are scanned on a reflection mirror, the average signals increase 1.62 times for the intense band at 476 cm−1 of starch powder, and average increases of 2.04 times (for the band at 672 cm−1) for a subsurface layer of high Raman sensitive melamine powder under a 1 mm thick teflon sheet. The method was then applied successfully to detect noninvasively the presence of small polystyrene pieces buried under a 2 mm thick layer of food powder (a case of powdered food adulteration) which otherwise are inaccessible to conventional backscattering Raman imaging. In addition, the increase in the Raman signal to noise ratio when measuring samples on a mirror is an important feature in many applications where high-throughput imaging is of interest. This concept is also applicable in an analogous manner to other disciplines, such as pharmaceutical where the Raman signals from deeper zones are typically, substantially diluted due to the interference from the surface layer.
The Fiber-Optic Rotational Seismograph—Laboratory Tests and Field Application
Authors: Jaroszewicz Leszek R. , Kurzych Anna , Krajewski Zbigniew , Dudek Michał , Kowalski Jerzy K. , Teisseyre Krzysztof P.
Published: June 2019

The paper presents construction and laboratory tests, as well as the first field application of a new fiber-optic rotational seismograph. The system is based on a fiber-optic gyroscope (FOG), with determined Angle Random Walk of the order of 10−8 rad/Sqrt(s) and a few rad/s maximum detectable amplitude of rotation in the frequency range from direct current (DC) to 328.12 Hz. It has been designed for the rotational seismology area of interest. This work also presents exemplary relevant measurements, which were conducted using a set of two devices installed in the geophysical observatory in Książ, Poland.
SERS, XPS and DFT Study of Xanthine Adsorbed on Citrate-Stabilized Gold Nanoparticles
Authors: Caporali Stefano , Muniz-Miranda Francesco , Pedone Alfonso , Muniz-Miranda Maurizio
Published: June 2019

We have studied the adsorption of xanthine, a nucleobase present in human tissue and fluids that is involved in important metabolic processes, on citrate-reduced gold colloidal nanoparticles by means of surface-enhanced Raman scattering (SERS), absorption, and X-ray photoelectron spectroscopy (XPS) measurements, along with density functional theory (DFT) calculations. The citrate anions stabilize the colloidal suspensions by strongly binding the gold nanoparticles. However, these anions do not impair the adsorption of xanthine on positively-charged active sites present on the metal surface. We have obtained the Fourier transform (FT)-SERS spectra of adsorbed xanthine by laser excitation in the near infrared spectral region, where interference due to fluorescence emission does not usually occur. In fact, the addition of chloride ions to the Au/xanthine colloid induces the aggregation of the gold nanoparticles, whose plasmonic band is shifted to the near infrared region where there is the exciting laser line of the FT–Raman instrument. Hence, this analytical approach is potentially suitable for spectroscopic determination of xanthine directly in body fluids, avoiding fluorescence phenomena induced by visible laser irradiation.
Achieving Tiered Model Quality in 3D Structure from Motion Models Using a Multi-Scale View-Planning Algorithm for Automated Targeted Inspection
Authors: Okeson Trent J. , Barrett Benjamin J. , Arce Samuel , Vernon Cory A. , Franke Kevin W. , Hedengren John D.
Published: June 2019

This study presents a novel multi-scale view-planning algorithm for automated targeted inspection using unmanned aircraft systems (UAS). In industrial inspection, it is important to collect the most relevant data to keep processing demands, both human and computational, to a minimum. This study investigates the viability of automated targeted multi-scale image acquisition for Structure from Motion (SfM)-based infrastructure modeling. A traditional view-planning approach for SfM is extended to a multi-scale approach, planning for targeted regions of high, medium, and low priority. The unmanned aerial vehicle (UAV) can traverse the entire aerial space and facilitates collection of an optimized set of views, both close to and far away from areas of interest. The test case for field validation is the Tibble Fork Dam in Utah. Using the targeted multi-scale flight planning, a UAV automatically flies a tiered inspection using less than 25% of the number of photos needed to model the entire dam at high-priority level. This results in approximately 75% reduced flight time and model processing load, while still maintaining high model accuracy where needed. Models display stepped improvement in visual clarity and SfM reconstruction integrity by priority level, with the higher priority regions more accurately modeling smaller and finer features. A resolution map of the final tiered model is included. While this study focuses on multi-scale view planning for optical sensors, the methods potentially extend to other remote sensors, such as aerial LiDAR.
A New Method for Multipath Filtering in GPS Static High-Precision Positioning
Authors: Han Ke , Tang Canyang , Deng Zhongliang
Published: June 2019

It is well known that multipath is one of the main sources of errors in GPS static high precision positioning of short baselines. Most algorithms for reducing multipath manipulate the GPS double difference (DD) observation residuals as input signal in GPS signal processing. In the traditional multipath mitigation methods, applying the wavelet transform (WT) to decompose the GPS DD observation residuals for identifying the multipath disturbance cannot effectively filter out the white noise of the high frequency part of the signal, and it is prone to edge effect. In this paper, for extracting multipath, a wavelet packet algorithm based on two-dimensional moving weighted average processing (WP-TD) is proposed. This algorithm can not only effectively filter out the white noise of the high frequency part of the signal, but also weaken the influence of the edge effect. Furthermore, considering the repeatability of multipath error in static positioning, we propose a method for determining the level of wavelet packet decomposition layers which make multipath extraction more effectively. The experimental results show that the corrected positioning accuracy is 14.14% higher than that of the traditional wavelet transform when applying the obtained multipath to DD coordinate sequences for position correction.
Field Deployment of a Portable Optical Spectrometer for Methane Fugitive Emissions Monitoring on Oil and Gas Well Pads
Authors: Zhang Eric J. , Teng Chu C. , van Kessel Theodore G. , Klein Levente , Muralidhar Ramachandran , Wysocki Gerard , Green William M. J.
Published: June 2019

We present field deployment results of a portable optical absorption spectrometer for localization and quantification of fugitive methane (CH4) emissions. Our near-infrared sensor targets the 2ν3 R(4) CH4 transition at 6057.1 cm−1 (1651 nm) via line-scanned tunable diode-laser absorption spectroscopy (TDLAS), with Allan deviation analysis yielding a normalized 2.0 ppmv∙Hz−1/2 sensitivity (4.5 × 10−6 Hz−1/2 noise-equivalent absorption) over 5 cm open-path length. Controlled CH4 leak experiments are performed at the METEC CSU engineering facility, where concurrent deployment of our TDLAS and a customized volatile organic compound (VOC) sensor demonstrates good linear correlation (R2 = 0.74) over high-flow (>60 SCFH) CH4 releases spanning 4.4 h. In conjunction with simultaneous wind velocity measurements, the leak angle-of-arrival (AOA) is ascertained via correlation of CH4 concentration and wind angle, demonstrating the efficacy of single-sensor line-of-sight (LOS) determination of leak sources. Source magnitude estimation based on a Gaussian plume model is demonstrated, with good correspondence (R2 = 0.74) between calculated and measured release rates.
Circuit Parameters of a Receiver Coil Using a Wiegand Sensor for Wireless Power Transmission
Authors: Takahashi Katsuki , Yamada Tsutomu , Takemura Yasushi
Published: June 2019

We previously demonstrated an efficient method of wireless power transmission using a Wiegand sensor for the application in implantable medical devices. The Wiegand sensor has an advantage in inducing sharp pulse voltage independent of the drive frequency. A down-sized receiver coil for wireless power transmission within blood vessels has been prepared, which enables medical treatment on any part of a human body. In order to develop practical applications of the Wiegand sensor as implantable medical devices, the circuit design is important. The circuit parameters in the circuit model of the Wiegand sensor must be clearly identified. However, a fast reversal of magnetization of the magnetic wire used in the Wiegand sensor, known as a large Barkhausen jump, and the induced nonlinear pulse signal make the inductance of the receiver coil time-dependent and inconsistent as conventionally considered in circuit analysis. In this study, the voltage and current responses of a wire-core coil are analyzed, and the time-dependent inductance is determined. The results showed that the inductance depends on the magnetization state of the wire, which can be negative during the fast reversal of magnetization.
Filtered Multitone Modulation Underwater Acoustic Communications Using Low-Complexity Channel-Estimation-Based MMSE Turbo Equalization
Authors: Sun Lin , Wang Mei , Zhang Guoheng , Li Haisen , Huang Lan
Published: June 2019

Filtered multitone (FMT) modulation divides the communication band into several subbands to shorten the span of symbols affected by multipath in underwater acoustic (UWA) communications. However, there is still intersymbol interference (ISI) in each subband of FMT modulation degrading communication performance. Therefore, ISI suppression techniques must be applied to FMT modulation UWA communications. The suppression performance of traditional adaptive equalization methods often exploited in FMT modulation UWA communications is limited when the effect of ISI spans tens of symbols or large constellation sizes are used. Turbo equalization consisting of adaptive equalization and channel decoding can improve equalization performance through information exchanging and iterative processes. To overcome the shortcoming of traditional minimum mean square error (MMSE) equalization and effectively suppress the ISI with relatively low computation complexity, an FMT modulation UWA communication using low-complexity channel-estimation-based (CE-based) MMSE turbo equalization is proposed in this paper. In the proposed method, turbo equalization is first exploited to suppress the ISI in FMT modulation UWA communications, and the equalizer coefficients of turbo equalization are adjusted using the low-complexity CE-based MMSE algorithm. The proposed method is analyzed in theory and verified by simulation analysis and real data collected in the experiment carried out in a pool with multipath propagation. The results demonstrate that the proposed method can achieve better communication performance with a higher bit rate than the FMT modulation UWA communication using traditional MMSE adaptive equalization.
A Flight Direction Design Method for Airborne Spectral Imaging Considering the Anisotropy Reflectance of the Target in Rugged Terrain
Authors: Zhao Huijie , Cui Bolun , Jia Guorui
Published: June 2019

An excellent mission plan is the prerequisite for the acquisition of high quality airborne hyperspectral images which are useful for environmental research, mining etc. In order to minimize the radiance non-uniformity caused by the anisotropic reflectance of targets, the flight direction is mostly designed on the solar azimuth or 180° from it for whiskbroom and pushbroom imagers. However, the radiance to the observer is determined not only by the reflectance of the target, but also by the terrain, the illumination direction and the observation direction. So, the flight direction which is defined to minimize radiance non-uniformity might change with the terrain. In order to find the best flight direction for rugged terrain, we firstly analyze the causes of the effect of terrain on radiation non-uniformity based on the radiative transfer process. Then, the flight direction design method is proposed for composite sloping terrain. Tested by digital and physical simulation experiments, the radiance non-uniformity is minimized when the aircraft flies in the designated direction. Finally, a workflow for flight direction planning and optimizing is summarized, considering the flight mission planning techniques and the workflow of remote sensing missions.
High Precision, Small Size and Flexible FBG Strain Sensor for Slope Model Monitoring
Authors: Xu Hongbin , Zheng Xinyu , Zhao Weigang , Sun Xu , Li Feng , Du Yanliang , Liu Bo , Gao Yang
Published: June 2019

In this paper, a soft fiber Bragg grating (FBG) strain sensor was constructed of a rubber strip, FBGs and steel plates, which exhibits the advantages of high precision and a small size. A series of FBGs was uniformly pasted on a flexible rubber strip which can monitor the slope deformation by measuring the bending deformation of the rubber strip. Most notably, this sensor can be used to monitor horizontal displacement in the subsurface of the slope model. The relationships among the bending angle of the rubber strip, the strain of the rubber strip, and the subsurface deformation of the slope model were established. In addition, the subsurface deformation of the slope model can be obtained by the FBG strain sensor monitoring. Since a rigid-flexible structure was formed by uniformly pasting a series of steel plates on the other side of the rubber strip, the sensitivity of the FBG strain sensor was improved to be 1.5425 nm/°. The measurement results verify that the FBG strain sensor shows good performance, and the model test results demonstrate that the FBG strain sensor can be used for monitoring the subsurface deformation of the slope model.
Spark-Based Parallel Genetic Algorithm for Simulating a Solution of Optimal Deployment of an Underwater Sensor Network
Authors: Liu Peng , Ye Shuai , Wang Can , Zhu Zongwei
Published: June 2019

Underwater sensor networks have wide application prospects, but the large-scale sensing node deployment is severely hindered by problems like energy constraints, long delays, local disconnections, and heavy energy consumption. These problems can be solved effectively by optimizing sensing node deployment with a genetic algorithm. However, the genetic algorithm (GA) needs many iterations in solving the best location of underwater sensor deployment, which results in long running time delays and limited practical application when dealing with large-scale data. The classical parallel framework Hadoop can improve the GA running efficiency to some extent while the state-of-the-art parallel framework Spark can release much more parallel potential of GA by realizing parallel crossover, mutation, and other operations on each computing node. Giving full allowance for the working environment of the underwater sensor network and the characteristics of sensors, this paper proposes a Spark-based parallel GA to calculate the extremum of the Shubert multi-peak function, through which the optimal deployment of the underwater sensor network can be obtained. Experimental results show that while faced with a large-scale underwater sensor network, compared with single node and Hadoop framework, the Spark-based implementation not only significantly reduces the running time but also effectively avoids the problem of premature convergence because of its powerful randomness.
Evaluation of ESA Active, Passive and Combined Soil Moisture Products Using Upscaled Ground Measurements
Authors: Zhu Luyao , Wang Hongquan , Tong Cheng , Liu Wenbin , Du Benxu
Published: June 2019

The European Space Agency (ESA) Climate Change Initiative (CCI) project combines multi-sensors at different microwave frequencies to derive three harmonized soil moisture products using active, passive and combined approaches. These long-term soil moisture products assist in understanding the global water and carbon cycles. However, extensive validations are a prerequisite before applying the retrieved soil moisture into climatic or hydrological models. To fulfill this objective, we assess the performances of three CCI soil moisture products (active, passive and combined) with respect to in-situ soil moisture networks located in China, Spain and Canada. In order to compensate the scale differences between ground stations and the CCI product’s coarse resolution, we adopted two upscaling approaches of Inverse Distance Weighting (IDW) interpolation and simple Arithmetic Mean (AM). The temporal agreements between the satellite retrieved and ground-measured soil moisture were quantified using the unbiased root mean square error (ubRMSE), RMSE, correlation coefficients (R) and bias. Furthermore, the temporal variability of the CCI soil moisture is interpreted and verified with respect to the Tropical Rainfall Measuring Mission (TRMM) precipitation observations. The results show that the temporal variations of CCI soil moisture agreed with the in-situ ground measurements and the precipitation observations over the China and Spain test sites. In contrast, a significant overestimation was observed over the Canada test sites, which may be due to the strong heterogeneity in soil and vegetation characteristics in accordance with the reported poor performance of soil moisture retrieval there. However, despite a retrieval bias, the relatively temporal variation of the CCI soil moisture also followed the ground measurements. For all the three test sites, the soil moisture retrieved from the combined approach outperformed the active-only and passive-only methods, with ubRMSE of 0.034, 0.050, and 0.050–0.054 m3/m3 over the test sites in China, Spain and Canada, respectively. Thus, the CCI combined soil moisture product is suggested to drive the climatic and hydrological studies.
RGB-D SLAM Using Point–Plane Constraints for Indoor Environments
Authors: Guo Ruibin , Peng Keju , Fan Weihong , Zhai Yongping , Liu Yunhui
Published: June 2019

Pose estimation and map reconstruction are basic requirements for robotic autonomous behavior. In this paper, we propose a point–plane-based method to simultaneously estimate the robot’s poses and reconstruct the current environment’s map using RGB-D cameras. First, we detect and track the point and plane features from color and depth images, and reliable constraints are obtained, even for low-texture scenes. Then, we construct cost functions from these features, and we utilize the plane’s minimal representation to minimize these functions for pose estimation and local map optimization. Furthermore, we extract the Manhattan World (MW) axes on the basis of the plane normals and vanishing directions of parallel lines for the MW scenes, and we add the MW constraint to the point–plane-based cost functions for more accurate pose estimation. The results of experiments on public RGB-D datasets demonstrate the robustness and accuracy of the proposed algorithm for pose estimation and map reconstruction, and we show its advantages compared with alternative methods.
A Differential Pressure Sensor Coupled with Conductance Sensors to Evaluate Pressure Drop Prediction Models of Gas-Water Two-Phase Flow in a Vertical Small Pipe
Authors: Deng Yuan-Rong , Jin Ning-De , Yang Qiu-Yi , Wang Da-Yang
Published: June 2019

In the process of production logging to evaluate fluid flow inside pipe, logging tools that force all flow to pass through a small measuring pipe are commonly utilized for measuring mixture density. For these logging tools, studying the fluid flow phenomenon inside the small diameter pipe and improving the prediction accuracy of pressure drop are beneficial to accurately measure mixture density. In this paper, a pressure drop prediction system is designed based on a combination of an eight-electrode rotating electric field conductance sensor (REFCS), plug-in cross-correlation conductance sensor, and differential pressure sensor. This combination overcomes the limitation of the existing pressure drop prediction model that the inlet flow velocity needs to be known. An experiment is conducted in a flow loop facility with 20 mm inner diameter small pipe. The responses of the combination sensors are collected. The REFCS is used to identify flow pattern and measure water holdup. During which five flow patterns are identified by recurrence plot method, i.e., slug flow, bubble flow, churn flow, bubble-slug transitional flow, and slug-churn transitional flow. The mixture velocity of two-phase flow is determined by the plug-in conductance sensor. The differential pressure sensor provides a differential pressure fluctuation signal. Five models of prediction of pressure drop are evaluated. The mixture friction factor of gas-water two-phase flow is obtained by a fitting method based on the measured parameters and flow pattern identification using the optimal model. Then, the pressure drop can be predicted according to the measurement results of a conductance sensor and fitting relationship. The results of pressure drop prediction show that the model proposed by Ansari et al. presents a higher accuracy compared with the other four differential pressure models with the absolute average percentage deviation (AAPD) of less than 2.632%. Moreover, the accuracy of pressure drop prediction of the Zhang et al. model is improved by using the mixture friction factor.
Server Consolidation Based on Culture Multiple-Ant-Colony Algorithm in Cloud Computing
Authors: Yuan Chunmiao , Sun Xuemei
Published: June 2019

High-energy consumption in data centers has become a critical issue. The dynamic server consolidation has significant effects on saving energy of a data center. An effective way to consolidate virtual machines is to migrate virtual machines in real time so that some light load physical machines can be turned off or switched to low-power mode. The present challenge is to reduce the energy consumption of cloud data centers. In this paper, for the first time, a server consolidation algorithm based on the culture multiple-ant-colony algorithm was proposed for dynamic execution of virtual machine migration, thus reducing the energy consumption of cloud data centers. The server consolidation algorithm based on the culture multiple-ant-colony algorithm (CMACA) finds an approximate optimal solution through a specific target function. The simulation results show that the proposed algorithm not only reduces the energy consumption but also reduces the number of virtual machine migration.
Development of an Occupational Health Safe Return to Work Prototype Application and Ergonomics Dataset for Agricultural Tasks
Authors: Weichelt Bryan , Ray William , Keifer Matthew
Published: June 2019

Serious, restrictive, non-fatal injuries are commonplace in large animal agriculture including in pork and dairy production. Primary care clinicians often have few resources to facilitate workers’ return to work and have difficulties communicating work restrictions/limitations to workers and their employers. This project developed SafeReturnToWork.org, a web-based platform to aid physicians and farmers in farmworkers’ timely and safe return to work. This prototype characterizes the duties of dairy and pork workers, and facilitates the creation of applicable light duty job assemblies for farmers and farmworkers by physicians and other healthcare providers. Guided by interviews and focus groups with physicians, farmers, and farmworkers, the system was developed for use with workplace injuries that could eventually link to human resource department systems, an electronic health record, or expand to other industries beyond agriculture.
Resilience as a Public Object. A Longitudinal Press Analysis of the Press Representations of Resilience in Italy, Spain, and France
Authors: Rochira Alessia , Mannarini Terri , De Simone Evelyn , Verbena Serena , Manfreda Alessandra
Published: June 2019

The notion of “resilience” has spilled over from the field of science and entered the field of policy, turning into a public and political object. The current study explores the social representations of resilience produced by press discourses between 2001 and 2017 in three different national contexts (Spain, France, and Italy), and examines the degree to which such representations incorporate technical and scientific meanings or rather include new components. A total amount of 1,298 articles published in three national newspapers (La Repubblica, Italy; Le Monde, France; and El Pais, Spain) were collected and analyzed for themes using the T-LAB software. The findings revealed more similarities than differences among the countries. The interest towards the topic increased over time, with the representations of resilience becoming more and more diversified and multifaceted. The technical and scientific components remained in the background, while a “practical theory” of resilience emerged, echoing the use of the concept in policy making, specifically in the European Union institutions approach.
Exploring the Impacts of Gentrified Traditional Retail Markets in Lisbon in Local Neighbourhoods
Authors: Guimarães Pedro
Published: June 2019

This article explores recent transformations in retail in Lisbon. We analyse a gentrified traditional retail market located in Campo de Ourique, Lisbon and study the relationship between this retail precinct and the surrounding commercial fabric. Through a set of enquiries on local retailers, our findings show an absence of relationship between the market and the remaining shopping district, insofar as Campo de Ourique market can be designed as a fortress. There is a social implication of this finding in the sense that the gentrification of the traditional retail market is severely detrimental to the local population quality of life. In terms of policy implication, this article demonstrates that this kind of project produces different results from some well-known retail-led urban regeneration projects and, as such, should not be used as a benchmarking for other areas.
Regeneration Ecology of the Rare Plant Species Verbascum dingleri: Implications for Species Conservation
Authors: Ganatsas Petros , Tsakaldimi Marianthi , Damianidis Christos , Stefanaki Anastasia , Kalapothareas Theodoros , Karydopoulos Theodoros , Papapavlou Kelly
Published: June 2019

Verbascum dingleri Mattf and Stef. is a Greek endemic plant species belonging to the family of Scrophulariaceae that only occurs in northeastern Greece, east of the city of Kavala. Knowledge of species distribution, habitat requirements, reproduction, ecology, and population characteristics is limited in the literature. In this study, habitat characteristics, population counts, fruit and seed diversity, and germination were studied for the first time. The results indicate that the species geographical distribution is very restricted, lying in the Mediterranean floristic zone at a low altitude (100–200 m asl) and on very shallow soils. The habitat of this species is characterized by the Csa climate type, with a mean annual precipitation of 602 mm and a mean annual temperature of 14.6 °C. The species occurs in the area lying between the geographical coordinates 40°58′16.59″ N, 24°27′54.93 E, and 41°05′7.2″ N, 24° 47′17.2″ E. The species thrives in degraded shrub communities, dominated by the shrub species Paliurus spina-cristi Mill., Olea europea L. ssp. europaea, and Quercus coccifera L. Only a very small number of individuals were found (less than 200) at a density considered too small for long-term persistence of the species. The fruits of the species contained a high number (mean value 58.2) of minute seeds. The seeds exhibited high germination (up to 80.0% in laboratory and up to 30% in ambient conditions). We conclude that in situ and ex situ species conservation and habitat restoration are feasible through the introduction of seedlings produced from seeds collected from local populations.
The Social and Vocational Integration of Former Users of the Child Protection System in Romania: A Qualitative Study
Authors: Bălăuță Dănuț , Neagoe Alexandru , Vasiluță Ștefănescu Marius , Toderici Ovidiu Florin
Published: June 2019

The social and vocational integration of vulnerable groups is an important aspect of social sustainability. Former users of the residential child protection system represent such a group. The purpose of our research was to investigate the social and vocational integration of individuals raised in the child protection system in Romania. Their experiences during and after their time in residential care are analyzed. The research sample was composed of 23 interviewees (18 male and 5 female) with an average age of thirty-five at the time of the interview (SD = 7.49). Our research method was a qualitative one, based on a semi-structured interview. The results paint a generally bleak image of life in such institutions, both before the fall of communism in Romania in December 1989 and subsequently. In addition, the respondents’ transition from institutional life to independent living was full of challenges. Nevertheless, most of the respondents have demonstrated a remarkable level of resilience, based on factors such as education, self-esteem, work, a life partner and the ability to acquire new skills. As a general conclusion, our study has shown that a sustainable social development plan should include social policies which strive for the de-institutionalization of the child protection system by preventing the separation of children from their biological families or, where necessary, by finding family-type solutions for children in difficulty. If institutional childcare is to continue, it must be accompanied by consistent efforts to prepare these children for their transition to independent living.
Gardeners’ Past Gardening Experience and Its Moderating Effect on Community Garden Participation
Authors: Lee Jae Ho , Matarrita-Cascante David
Published: June 2019

Studies on participation in community gardens have revealed that gardeners’ participation is driven by functional and emotional motives. Most studies, however, have failed to recognize gardeners’ diverse characteristics. To fill this research gap, this study examined the moderating effect that variations within gardeners has on their participation, particularly as in the case of past gardening experience. The data for this study were obtained through a survey administered in three plot-based community gardens in Austin, Texas. Results revealed that increased gardening experience bolsters the effect of emotional motivations on garden participation, while no effect was shown in the relationship between functional motivations and participation. The importance of gardeners’ past gardening experience on emotional motivations is discussed as it relates to sustained participation in gardening.
Pressurization Ventilation Technique for Controlling Gas Leakage and Dispersion at Backfilled Working Faces in Large-Opening Underground Mines: CFD Analysis and Experimental Tests
Authors: Nguyen Van-Duc , Heo Won-Ho , Kubuya Rocky , Lee Chang-Woo
Published: June 2019

Pressurization ventilation techniques, originally designed to control building fires, have never been applied to the mines. The working face, backfilled with fly-ash-based materials, is likely to be contaminated during, and even after, the curing period of the backfill materials. Gases such as NH3 and CO2 may leak out prolongedly from the backfilled sites. Proper ventilation schemes should be implemented to control toxic gas leakage and thus minimize the workers’ exposure. This study aims at evaluating the applicability of a pressurization ventilation scheme at backfilled working faces in large-opening limestone mines. To pressurize the working face, two different fans (15 kW and 37 kW) were developed and two ventilation scenarios were tested. Computational Fluid Dynamics (CFD) analysis was also carried out for comparison purposes. There is no established standard for differential pressure between the inside and outside of working faces to prevent gas leakage at mines. However, taking the differential pressure of 50 Pa in British standards for controlling building fires (where a relatively stronger dissipation force than the gas leakage of a mining face occurs), the pressure differential created by two blowing fans seems to be sufficient to control the gas leakage and dispersion within the work space.
Effect of Policy Incentives on the Uptake of Electric Vehicles in China
Authors: Li Wenbo , Long Ruyin , Chen Hong , Chen Feiyu , Zheng Xiao , Yang Muyi
Published: June 2019

In the backdrop of growing public concerns about climate change and air pollution, and the contribution of petroleum combustion in the transport sector to these issues, China has introduced a range of policy incentives for promoting the uptake of electric vehicles (EVs). These incentives have resulted in a rapid increase in EV stocks since the early 2010s, and this trend is expected to continue, or even accelerate, in the years to come, which would, in turn, lead to a policy-oriented EV market. The primary objective of the project is to develop an understanding of the effect of various policy incentives on EV uptake based on annual data of 43 cities from 2011 to 2017, and these policies mainly refer to those that focus on EV purchasing, registering, driving, and charging stages. The novelty of this paper is that we focused on policy effect on EV adoption behavior, rather than adoption intention which has widely been analyzed in previous studies. Results showed that the abolishment of purchasing and driving restriction, government subsidies, purchase tax exemption, and dedicated license plates significantly promote EV diffusion, and the effect of the two restrictions are more powerful. Thus, this study suggested that abolishment of purchasing and driving restrictions can be insisted to drive EV market share, meanwhile improving policies that can guide consumers through various motivations are also necessary.
Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts
Authors: Bogner Konrad , Pappenberger Florian , Zappa Massimiliano
Published: June 2019

Reliable predictions of the energy consumption and production is important information for the management and integration of renewable energy sources. Several different Machine Learning (ML) methodologies have been tested for predicting the energy consumption/production based on the information of hydro-meteorological data. The methods analysed include Multivariate Adaptive Regression Splines (MARS) and various Quantile Regression (QR) models like Quantile Random Forest (QRF) and Gradient Boosting Machines (GBM). Additionally, a Nonhomogeneous Gaussian Regression (NGR) approach has been tested for combining and calibrating monthly ML based forecasts driven by ensemble weather forecasts. The novelty and main focus of this study is the comparison of the capability of ML methods for producing reliable predictive uncertainties and the application of monthly weather forecasts. Different skill scores have been used to verify the predictions and their uncertainties and first results for combining the ML methods applying the NGR approach and coupling the predictions with monthly ensemble weather forecasts are shown for the southern Switzerland (Canton of Ticino). These results highlight the possibilities of improvements using ML methods and the importance of optimally combining different ML methods for achieving more accurate estimates of future energy consumptions and productions with sharper prediction uncertainty estimates (i.e., narrower prediction intervals).
Repeated-Batch Fermentation of Cheese Whey for Semi-Continuous Lactic Acid Production Using Mixed Cultures at Uncontrolled pH
Authors: Luongo Vincenzo , Policastro Grazia , Ghimire Anish , Pirozzi Francesco , Fabbricino Massimiliano
Published: June 2019

The paper investigates mixed-culture lactate (LA) fermentation of cheese whey (CW) in order to verify the possibility of using waste materials as feedstock to produce a product with high economic potential. The fermentation performance of two reactors operating in repeated-batch mode under uncontrolled pH conditions and various hydraulic retention time and feeding conditions was evaluated in terms of LA production. Five experimental phases were conducted. The hydraulic retention time (HRT) was varied from 1 to 4 days to verify its effect on the process performance. The best results, corresponding to the maximum LA concentration (20.1 g LA/L) and the maximum LA yield (0.37 g chemical oxygen demand (COD)(LA)/g COD(CW)), were reached by feeding the reactors with cheese whey alone and setting the HRT to 2 days. The maximum productivity of lactic acid (10.6 g LA/L/day) was observed when the HRT was decreased to 1 day.
Regional Sustainability, Individual Expectations and Work Motivation: A Multilevel Analysis
Authors: Davidescu Adriana Ana Maria , Roman Monica , Strat Vasile Alecsandru , Mosora Mihaela
Published: June 2019

In the context of the recent labor shortages in Eastern European countries, Romania included, companies, organizations and decision makers need to strongly address the issue of labor motivation for increasing worker performance and also for attracting the scarce labor resources. The main goal of the research is to explore new determinants of work motivation, such as regional sustainability and also individual factors related to individual expectations. Therefore, the responsive methodology used for this purpose implies a multilevel econometric modelling, in which the first level regards individuals, and the second one consists in development regions. Moreover, the role of individual factors is tested using Vroom’s theory of expectations and filling a gap in the existing literature on work motivation in developing, post-communist economies. The main findings prove that one dimension of sustainability, namely social sustainability has a significant impact on work motivation, alongside with four dimensions of individual factors. Economic and environmental sustainability have no significant impact on work motivation in the case of Romanian workers.
Mutual Support, Role Breadth Self-Efficacy, and Sustainable Job Performance of Workers in Young Firms
Authors: Cheah Sarah , li Shiyu , Ho Yuen-Ping
Published: June 2019

Coworking space has flourished in the past decade. Unlike traditional shared services organizations, coworking spaces put a much greater emphasis on ‘sharing’. Members not only can share the physical office space, but also the virtual social spaces created by the coworking space operators managing the office. As coworking spaces provide a community to foster the culture of sharing, which gives rise to social interactions and thus knowledge and idea exchange, entrepreneurs favor such coworking spaces to achieve a higher level of job performance among their workers. Although it is generally accepted that a worker’s job performance varies over time within a job, there have been limited studies on within-person performance sustainability and its comparison with between-person sustainability. We sampled 101 workers of young firms operating in six coworking spaces in Singapore who completed daily surveys twice a day across ten consecutive workdays. By treating participants as the first level and daily observations as the second level, our study develops a dual-path model to explain how daily mutual support influences daily job performance. Our results indicated that daily mutual support is positively related to sustainable job performance after controlling for sleep quality, job requirements and workload stress. Within-person sustainability in mutual support was found to account for part of within-person variance in job performance. We established that mutual support not only predicts job performance, but also varies across workdays. As the collaboration of team members depends on cooperation rather than competition, mutual support is considered essential for team work and thus employees’ job performance. Our study also demonstrated the importance of role breadth self-efficacy as a moderator in the link between mutual support and sustainable job performance. Role breadth self-efficacy refers to the extent to which people feel confident that they are able to carry out a broader and more proactive role, beyond traditional prescribed technical requirements. The results revealed an enhancing moderation effect, where increasing the role breath self-efficacy would enhance the effect of the mutual support predictor on sustainable job performance of workers in young firms operating in the coworking space.
Analysis of Factors Affecting Real-Time Ridesharing Vehicle Crash Severity
Authors: Zhou Bei , Zhang Xinfen , Zhang Shengrui , Li Zongzhi , Liu Xin
Published: June 2019

The popular real-time ridesharing service has promoted social and environmental sustainability in various ways. Meanwhile, it also brings some traffic safety concerns. This paper aims to analyze factors affecting real-time ridesharing vehicle crash severity based on the classification and regression tree (CART) model. The Chicago police-reported crash data from January to December 2018 is collected. Crash severity in the original dataset is highly imbalanced: only 60 out of 2624 crashes are severe injury crashes. To fix the data imbalance problem, a hybrid data preprocessing approach which combines the over- and under-sampling is applied. Model results indicate that, by resampling the crash data, the successfully predicted severe crashes are increased from 0 to 40. Besides, the G-mean is increased from 0% to 73%, and the AUC (area under the receiver operating characteristics curve) is increased from 0.73 to 0.82. The classification tree reveals that following variables are the primary indicators of real-time ridesharing vehicle crash severity: pedestrian/pedalcyclist involvement, number of passengers, weather condition, trafficway type, vehicle manufacture year, traffic control device, driver gender, lighting condition, vehicle type, driver age and crash time. The current study could provide some valuable insights for the sustainable development of real-time ridesharing services and urban transportation.
Session-Based Recommender System for Sustainable Digital Marketing
Authors: Hwangbo Hyunwoo , Kim Yangsok
Published: June 2019

Many companies operate e-commerce websites to sell fashion products. Some customers want to buy products with intention of sustainability and therefore the companies need to suggest appropriate fashion products to those customers. Recommender systems are key applications in these sustainable digital marketing strategies and high performance is the most necessary factor. This research aims to improve recommendation systems’ performance by considering item session and attribute session information. We suggest the Item Session-Based Recommender (ISBR) and the Attribute Session-Based Recommenders (ASBRs) that use item and attribute session data independently, and then we suggest the Feature-Weighted Session-Based Recommenders (FWSBRs) that combine multiple ASBRs with various feature weighting schemes. Our experimental results show that FWSBR with chi-square feature weighting scheme outperforms ISBR, ASBRs, and Collaborative Filtering Recommender (CFR). In addition, it is notable that FWSBRs overcome the cold-start item problem, one significant limitation of CFR and ISBR, without losing performance.
Food Systems Sustainability: An Examination of Different Viewpoints on Food System Change
Authors: Haysom Gareth , Olsson E. Gunilla Almered , Dymitrow Mirek , Opiyo Paul , Taylor Buck Nick , Oloko Michael , Spring Charlotte , Fermskog Kristina , Ingelhag Karin , Kotze Shelley , Agong Stephen Gaya
Published: June 2019

Global food insecurity levels remain stubbornly high. One of the surest ways to grasp the scale and consequence of global inequality is through a food systems lens. In a predominantly urban world, urban food systems present a useful lens to engage a wide variety of urban (and global) challenges—so called ‘wicked problems.’ This paper describes a collaborative research project between four urban food system research units, two European and two African. The project purpose was to seek out solutions to what lay between, across and within the different approaches applied in the understanding of each city’s food system challenges. Contextual differences and immediate (perceived) needs resulted in very different views on the nature of the challenge and the solutions required. Value positions of individuals and their disciplinary “enclaves” presented further boundaries. The paper argues that finding consensus provides false solutions. Rather the identification of novel approaches to such wicked problems is contingent of these differences being brought to the fore, being part of the conversation, as devices through which common positions can be discovered, where spaces are created for the realisation of new perspectives, but also, where difference is celebrated as opposed to censored.
Innovation Clusters Revisited: On Dimensions of Agglomeration, Institution, and Built-Environment
Authors: Li Jianyi , Webster Douglas , Cai Jianming , Muller Larissa
Published: June 2019

Innovation clusters have been the key concept underlying economic development theory and practice since the concept was re-energized in the 1990s. Worldwide efforts promoting cluster development are supposed to be informed by research on cluster dynamics. The plethora of articles and reports on this globally hyped concept often add to the confusion, calling for a systematic synthesis. In academia, the discussion of innovation clusters is characterized by separate literature dealing with agglomeration, institution, and built-environment. This literature review addresses each of those three dimensions, respectively, by discussing both classic perceptions and potential directions for future research.