bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan
Authors: Rehman Asid Ur , Chishtie Farrukh , Qazi Waqas A. , Ghuffar Sajid , Shahid Imran , Fatima Khunsa
Published: December 2018

Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). Further, a diurnal analysis is performed to authenticate TMPA’s performance in specific hours of the day. In general, the results show the good capability of both TMPA products in the detection of rain/no-rain events in all seasons except winter. Specifically, 3B42V7 performed better than 3B42RT. Moreover, both products detect a high number of rainy days falsely in light rain ranges. Regarding rainfall measurements, TMPA products exhibit an overall underestimation. Seasonally, 3B42V7 underestimates rainfall in monsoon and post-monsoon, and overestimates in winter and pre-monsoon. 3B42RT, on the other hand, underestimates rainfall in all seasons. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = −0.92, −0.70). The correlation is significant at decadal (CC = 0.79, 0.77) and monthly (CC = 0.91, 0.90) timescales. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. Within the parameters of this study, we conclude that the TMPA products are not the best choice at a three-hourly time scale in hilly/semi-hilly areas of Pakistan. However, both products can be used at daily, yet more reliably above daily, time scales, with 3B42V7 preferable due to its consistency.
The Influence of Instrumental Line Shape Degradation on the Partial Columns of O3, CO, CH4 and N2O Derived from High-Resolution FTIR Spectrometry
Authors: Sun Youwen , Liu Cheng , Chan Kalok , Wang Wei , Shan Changong , Hu Qihou , Liu Jianguo
Published: December 2018

High resolution Fourier transform infrared (FTIR) measurement of direct sunlight does not only provide information of trace gas total columns, but also vertical distribution. Measured O3, CO, CH4, and N2O can be separated into multiple partial columns using the optimal estimation method (OEM). The retrieval of trace gas profiles is sensitive to the instrument line shape (ILS) of the FTIR spectrometer. In this paper, we present an investigation of the influence of ILS degradation on the partial column retrieval of O3, CO, CH4, and N2O. Sensitivities of the partial column, error, and degrees of freedom (DOFs) of each layer to different levels of ILS degradation for O3, CO, CH4, and N2O are estimated. We then evaluate the impact of ILS degradation on the long-term measurements. In addition, we derive the range of ILS degradation corresponding to the acceptable uncertainties of O3, CO, CH4, and N2O results. The results show that the uncertainties induced by the ILS degradation on the absolute value, error, and the DOFs of the partial column are altitude and gas species dependent. The uncertainties of the partial columns of O3 and CO are larger than those on CH4 and N2O. The stratospheric partial columns are more sensitive to the ILS degradation compared to the tropospheric part. Our result improves the understanding of the ILS degradation on the FTIR measurements, which is important for the quantification of the measurement uncertainties and minimizes the bias of the inter-comparison between different measurement platforms. This is especially useful for the validation of satellite observations, the data assimilation of chemical model simulations, and the quantification of the source/sink/trend from the FTIR measurements.
Ship Classification and Detection Based on CNN Using GF-3 SAR Images
Authors: Ma Mengyuan , Chen Jie , Liu Wei , Yang Wei
Published: December 2018

Ocean surveillance via high-resolution Synthetic Aperture Radar (SAR) imageries has been a hot issue because SAR is able to work in all-day and all-weather conditions. The launch of Chinese Gaofen-3 (GF-3) satellite has provided a large number of SAR imageries, making it possible to marine targets monitoring. However, it is difficult for traditional methods to extract effective features to classify and detect different types of marine targets in SAR images. This paper proposes a convolutional neutral network (CNN) model for marine target classification at patch level and an overall scheme for marine target detection in large-scale SAR images. First, eight types of marine targets in GF-3 SAR images are labelled based on feature analysis, building the datasets for further experiments. As for the classification task at patch level, a novel CNN model with six convolutional layers, three pooling layers, and two fully connected layers has been designed. With respect to the detection part, a Single Shot Multi-box Detector with a multi-resolution input (MR-SSD) is developed, which can extract more features at different resolution versions. In order to detect different targets in large-scale SAR images, a whole workflow including sea-land segmentation, cropping with overlapping, detection with MR-SSD model, coordinates mapping, and predicted boxes consolidation is developed. Experiments based on the GF-3 dataset demonstrate the merits of the proposed methods for marine target classification and detection.
Development of High-Frequency (>60 MHz) Intravascular Ultrasound (IVUS) Transducer by Using Asymmetric Electrodes for Improved Beam Profile
Authors: Sung Jin Ho , Jeong Jong Seob
Published: December 2018

In most commercial single-element intravascular ultrasound (IVUS) transducers, with 20 MHz to 40 MHz center frequencies, a conductive adhesive is used to bond a micro-sized cable for the signal line to the surface of the transducer aperture (<1 mm × 1 mm size) where ultrasound beam is generated. Therefore, the vibration of the piezoelectric layer is significantly disturbed by the adhesive with the signal line, thereby causing problems, such as reduced sensitivity, shortened penetration depth, and distorted beam profile. This phenomenon becomes more serious as the center frequency of the IVUS transducer is increased, and the aperture size becomes small. Therefore, we propose a novel IVUS acoustic stack employing asymmetric electrodes with conductive and non-conductive backing blocks. The purpose of this study is to verify the extent of performance degradation caused by the adhesive with the signal line, and to demonstrate how much performance degradation can be minimized by the proposed scheme. Finite element analysis (FEA) simulation was conducted, and the results show that −3 dB, −6 dB, and −10 dB penetration depths of the conventional transducer were shortened by 20%, 25%, and 19% respectively, while those of the proposed transducer were reduced only 3%, 4%, and 0% compared with their ideal transducers which have the same effective aperture size. Besides, the proposed transducer improved the −3 dB, −6 dB, and −10 dB penetration depths by 15%, 12%, and 10% respectively, compared with the conventional transducer. We also fabricated a 60 MHz IVUS transducer by using the proposed technique, and high-resolution IVUS B-mode (brightness mode) images were obtained. Thus, the proposed scheme can be one of the potential ways to provide more uniform beam profile resulting in improving the signal to noise ratio (SNR) in IVUS image.
A QoS Based Adaptive Backoff Scheme for Vehicular Ad Hoc Networks
Authors: Zhang Tianjiao , Zhu Qi
Published: December 2018

The media access control (MAC) protocol is a key element in the design of vehicular ad hoc networks (VANETs) that directly affects the network performance. The backoff schemes of existing MAC protocols apply the single backoff process and therefore are not suitable for multi-class data transmission. Additionally, they cannot satisfy the delay requirements of emergency data in the case of varying number of vehicles, causing an adverse effect to the intelligent transportation system (ITS). This paper presents a priority-based adaptive backoff scheme that can enhance the binary exponential backoff (BEB) algorithm as well as the polynomial backoff (QB) algorithm. This system distinguishes priority data with different delay requirements first and designs different backoff schemes for each type of data later. The two-dimensional Markov Chain is used to analyze the backoff scheme and determine the expressions for throughput and delay. The simulation results show that the backoff scheme provided by this paper can reduce the average data delay and regulate each kind of data delay adaptively, according to the varying number of vehicles and different delay requirements.
An Effective Extension of Anti-Collision Protocol for RFID in the Industrial Internet of Things (IIoT)
Authors: Filho Israel Eduardo de Barros , Silva Ivanovitch , Viegas Carlos M. D.
Published: December 2018

The Industrial Internet of Things (IIoT) is often presented as a concept that is significantly changing industry, yet continuous improvements in the identification and automation of objects are still required. Such improvements are related to communication speed, security, and reliability, critical attributes for industrial environments. In this context, the radio-frequency identification (RFID) systems present some issues related to frame collision when there are several tags transmitting data. The dynamic framed-slotted ALOHA (DFSA) is a widely used algorithm to solve collision problems in RFID systems. DFSA dynamically adjusts the frame length based on estimations of the number of labels that have competed for slots in the previous frame. Thus, the accuracy of the estimator is directly related to the label identification performance. In the literature, there are several estimators proposed to improve labels identification accuracy. However, they are not efficient when considering a large tag population, requiring a considerable amount of computational resources to perform the identification. In this context, this work proposes an estimator, which can efficiently identify a large number of labels without requiring additional computational resources. Through a set of simulations, the results demonstrate that the proposed estimator has a nearly ideal channel usage efficiency of 36.1%, which is the maximum efficiency of the DFSA protocol.
Acetylcholinesterase Biosensor Based On Mesoporous Hollow Carbon Spheres/Core-Shell Magnetic Nanoparticles-Modified Electrode for the Detection of Organophosphorus Pesticides
Authors: Luo Ruiping , Feng Zijie , Shen Guannan , Xiu Yi , Zhou Yukun , Niu Xiaodi , Wang Hongsu
Published: December 2018

The present study investigated the synthesis of mesoporous hollow carbon spheres (MHCS) and magnetic mesoporous hollow carbon spheres with core-shell structures (Fe3O4@MHCS). Two acetylcholinesterase sensors (acetylcholinesterase/mesoporous hollow carbon spheres/glassy carbon electrode (AChE/MHCS/GCE) and acetylcholinesterase/core-shell magnetic mesoporous hollow carbon spheres/glassy carbon electrode (AChE/Fe3O4@MHCS/GCE) based on mesoporous carbon materials were prepared. Under the optimum conditions, using Malathion as the model compound, the developed biosensors showed a wide detection range, low detection limit, good reproducibility, and high stability. The AChE/MHCS/GCE electrochemical sensor response exhibited two good linear ranges at the incubation time of 10 min at the Malathion concentration ranges of 0.01 to 100 ppb and 100 to 600 ppb, with a detection limit of 0.0148 ppb (S/N = 3). The AChE/Fe3O4@MHCS/GCE electrochemical sensor that was operated with an incubation time of 12 min at the malathion concentration ranges between 0.01–50 ppb and 50–600 ppb had a detection limit of 0.0182 ppb (S/N = 3). Moreover, the AChE/MHCS/GCE and AChE/Fe3O4@MHCS/GCE biosensors were effective for the detection of real samples, and were demonstrated to be suitable for the field-testing of organophosphorus pesticide (OP) residues.
Social Capital, Human Capital, and Sustainability: A Bibliometric and Visualization Analysis
Authors: Garrigos-Simon Fernando J. , Botella-Carrubi M. Dolores , Gonzalez-Cruz Tomas F.
Published: December 2018

Academic interest in social and human capital is growing significantly. Similarly, their relationship with sustainability is increasing, especially compared to sustainability’s relationship with natural capital and financial and economic capital. Bibliometric and visualization research on these relationships is nonetheless insufficient. This study analyzes the evolution of the literature on natural capital, financial and economic capital, and social and human capital related to sustainability. On the other hand, the study presents a bibliometric analysis on social capital and human capital (SHC) related to sustainability. The article studies 635 references collected from the Web of Science (WoS) Core Collection database and utilizes visualization of similarities (VOS) viewer program to graphically map the material. The analysis involves co-occurrence of keywords, co-citation, and co-authorship. The results reveal not only the state of the art and the leading trends, but also the evolution regarding impact, main journals, documents, topics, authors, institutions, and countries. The study provides researchers and practitioners with a visual and schematic frame of the research on this topic.
Effects of Different Grazing Systems on Aboveground Biomass and Plant Species Dominance in Typical Chinese and Mongolian Steppes
Authors: Na Yintai , Li Jinxia , Hoshino Buho , Bao Saixialt , Qin Fuying , Myagmartseren Purevtseren
Published: December 2018

This study investigated the effects of different grazing systems on plant communities, and examined the causes of Mongolian grassland desertification. The typical steppes near the Chinese-Mongolian border were studied using quadrat sampling and remote sensing methods. Aboveground biomass in the steppe areas differed significantly among the three grazing systems (p < 0.05): Biomass in the grazing-prohibited areas (455.9 g) was greater than that in the rotational-grazing areas (268.4 g) and the continuous grazing areas (122.2 g). Aboveground biomass was well correlated with the Soil Adjusted Vegetation Index (SAVI; y = 5600x2 + 260x + 110; R2 = 0.67; p < 0.05). The relative mean deviation between the aboveground biomass was calculated using this regression and the measured biomass was 29.1%. The Soil Adjusted Vegetation Index (SAVI) values for nomadic-grazing areas were greater than those for continuous-grazing areas in 1989, 2005, 2011, and 2016, and were significantly greater in 2011 and 2016. The SAVI values for the continuous-grazing areas were slightly, but not significantly greater, than those for the nomadic-grazing areas in 1993. Plant species that dominated in moderately degraded areas were most dominant in nomadic-grazing areas, followed by continuous-grazing areas and grazing-prohibited areas. Plant species that dominated in lightly and heavily degraded areas were most dominant in continuous-grazing areas, followed by nomadic-grazing areas and grazing-prohibited areas. Generally, continuous grazing caused more serious grassland degradation than did nomadic grazing, and nomadic-grazing areas tolerated more intense grazing than did continuous-grazing areas.
Measuring Perceived Corporate Hypocrisy: Scale Development in the Context of U.S. Retail Employees
Authors: Goswami Saheli , Ha-Brookshire Jung , Bonifay Wes
Published: December 2018

Despite an increasing amount of research on perceived corporate hypocrisy (PCH), limited research has investigated PCH among employees. Particularly, the literature lacked a valid instrument for estimating employees’ PCH, even though employees experience severe consequences for PCH. To address this gap, a scale was developed to measure employees’ PCH, using a three-stage Item Response Theory modeling approach. After a series of qualitative studies and six quantitative scale-development iterations, PCH was found to be a unidimensional construct represented by the perceived lack of morality, perceived control breach, double standards, and a value‒behavior gap. Further, the nine-item PCH scale was confirmed to be reliable, valid, and unbiased for different demographic groups. The scale makes theoretical contributions by being one of the few attempts to objectively measure employees’ hypocrisy judgements and incorporating corporations’ double standard and perceived commitment to morality as defining features of employees’ PCH. Assessment of employees’ PCH can help in expanding the hypocrisy literature beyond consumers’ perceptions. Finally, the scale enables corporations to measure employees’ PCH and get an in-depth understanding of the issues of concern as work and organizational phenomena. By implementing proper management strategies, corporations can potentially avoid PCH, create more favorable perceptions among employees, and improve their reputations.
Is Big Good or Bad?: Testing the Performance of Urban Growth Cellular Automata Simulation at Different Spatial Extents
Authors: Gao Xuesong , Liu Yu , Liu Lun , Li Qiquan , Deng Ouping , Wei Yali , Ling Jing , Zeng Min
Published: December 2018

The accurate prediction of urban growth is pivotal for managing urbanization, especially in fast-urbanizing countries. For this purpose, cellular automata-based (CA) simulation tools have been widely developed and applied. Previous studies have extensively discussed various model building and calibration techniques to improve simulation performance. However, it has been a common practice that the simulation is conducted at and only at the spatial extent where the results are needed, while as we know, urban development in one place can also be influenced by the situations in the broader contexts. To tackle this gap, in this paper, the impact of the simulation of spatial extent on simulation performance is tested and discussed. We used five villages at the rural–urban fringe in Chengdu, China as the case study. Urban growth CA models are built and trained at the spatial extent of the village and the whole city. Comparisons between the simulation results and the actual urban growth in the study area from 2005 to 2015 show that the accuracy of the city model was 7.33% higher than the village model and the latter had more errors in simulating the growth of small clusters. Our experiment suggests that, at least in some cases, urban growth modeling at a larger spatial extent can yield better results than merely modeling the area of interest, and the impacts of the spatial extent of simulation should be considered by modelers.
Sustainable Inventory Management for Environmental Impact through Partial Backordering and Multi-Trade-Credit-Period
Authors: Sarkar Biswajit , Ahmed Waqas , Choi Seok-Beom , Tayyab Muhammad
Published: December 2018

Incorporation of sustainable management for the rework of defective items brings long lasting benefits. In global business, there are situations when the products are procured from a global supplier. There are chances that the received lot may contain a fraction of imperfect products. These imperfect products are still valuable and can be repairable to save the environment. It is sustainable to repair imperfect items in a local repair store as compared to sending it back to the supplier. The cost of carbon emissions is also incorporated in the function to incorporate the environmental impact on total profit. Meanwhile, the supplier also offers a multi-trade-credit-period to the buyer. The developed model is sustainable and reduces the environmental impact as well as benefits for interim financing. This paper has an objective to maximize the total profit by developing a synergic economic order quantity model by considering multi-trade-credit policy, rework, and shortages simultaneously. This model can help in making decisions to enhance the performance of sustainable inventory management by controlling the cycle time and a fraction of time for a global supply chain. A non-derivative approach is employed to develop a closed-form optimal result. The numerical illustration with sensitivity analysis is also drawn to provide managerial insights into real practices.
Modeling the Impacts of Conservation Agriculture with a Drip Irrigation System on the Hydrology and Water Management in Sub-Saharan Africa
Authors: Assefa Tewodros , Jha Manoj , Reyes Manuel , Worqlul Abeyou W.
Published: December 2018

The agricultural system in Sub-Saharan Africa (SSA) is dominated by traditional farming practices with poor soil and water management, which contributes to soil degradation and low crop productivity. This study integrated field experiments and a field-scale biophysical model (Agricultural Policy Environmental Extender, APEX) to investigate the impacts of conservation agriculture (CA) with a drip irrigation system on the hydrology and water management as compared to the conventional tillage (CT) practice. Field data were collected from four study sites; Dangishita and Robit (Ethiopia), Yemu (Ghana), and Mkindo (Tanzania) to validate APEX for hydrology and crop yield simulation. Each study site consisted of 100 m2 plots divided equally between CA and CT practices and both had a drip irrigation setup. Cropping pattern, management practices, and irrigation scheduling were monitored for each experimental plot. Significant water savings (α = 0.05) were observed under CA practice; evapotranspiration and runoff were reduced by up to 49% and 62%, respectively, whereas percolation increased up to three-fold. Consequently, irrigation water need was reduced in CA plots by about 14–35% for various crops. CA coupled with drip irrigation was found to be an efficient water saving technology and has substantial potential to sustain and intensify crop production in the region.
Use of Steel and Polyolefin Fibres in the La Canda Tunnels: Applying MIVES for Assessing Sustainability Evaluation
Authors: Alberti Marcos G. , Gálvez Jaime C. , Enfedaque Alejandro , Carmona Ana , Valverde Cristina , Pardo Gabriel
Published: December 2018

Construction involves the use of significant quantities of raw materials and entails high-energy consumption. For the sake of choosing the most appropriate solution that considers environmental and sustainable concepts, tools such as the integrated value model for sustainable assessment (Modelo Integrado de Valor para una Evaluación Sostenible, MIVES) used in Spain, plays a key role in obtaining the best solution. MIVES is a multi-criteria decision-making method based on the value function concept and the seminars delivered by experts. Such tools, in order to show how they may work, require application to case studies. In this paper, two concrete slabs manufactured with differing reinforcements during the construction of the La Canda Tunnels are compared by means of MIVES. The two concrete slabs were reinforced with a conventional steel-mesh and with polyolefin fibres. This research was focussed on the main aspects affecting the construction. That is to say, the environmental, economic, and social factors were assessed by the method, being of special impact the issues related with maintenance of the structure. The results showed that from the point of view of sustainability, the use of polyolefin fibres provided a significant advantage, mainly due to the lower maintenance required.
Trialing a Road Lane to Bicycle Path Redesign—Changes in Travel Behavior with a Focus on Users’ Route and Mode Choice
Authors: Vasilev Miroslav , Pritchard Ray , Jonsson Thomas
Published: December 2018

Redistribution of space from private motorized vehicles to sustainable modes of transport is gaining popularity as an approach to alleviate transport problems in many cities around the world. This article investigates the impact of a trial Complete Streets project, in which road space is reallocated to bicyclists and pedestrians in Trondheim, Norway. The paper focuses on changes in the travel behavior of users of the street, with a focus on route and mode choice. In total, 719 people responded to a web-based travel survey, which also encompassed an integrated mapping Application Programming Interface (API). Amongst the findings of the survey is that the average length of the trial project that was utilized by cyclists on their most common journey through the neighborhood nearly doubled from 550 m to 929 m (p < 0.0005), suggesting that the intervention was highly attractive to bicyclists. Respondents were also asked whether they believe the trial project was positive for the local community, with the majority (87%) being positive or highly positive to the change. The intervention had a considerable impact on users’ travel behavior in terms of both frequency and choice of active transportation modes, together with leading to a change in route preferences.
Response of Grazing Land Soil Health to Management Strategies: A Summary Review
Authors: Xu Sutie , Jagadamma Sindhu , Rowntree Jason
Published: December 2018

Grazing land ecosystem services including food provision and climate regulation are greatly influenced by soil health. This paper provides a condensed review of studies on the response of three important soil properties related to soil health to grazing land management: water infiltration, carbon (C) sequestration, and nitrogen use efficiency (NUE). Impacts of management strategies that are often used in grazing lands are discussed in this review including vegetation composition, grazing methods, and other factors such as fertilizer use and climatic conditions. In general, proper grazing management such as continuous moderate grazing and rotational/deferred-rotational grazing with low or moderate stocking rates tends to benefit all three soil properties. Water infiltration can usually be increased with full vegetation cover, increased soil C, and aggregate stability, or be decreased with greater soil bulk density. Adoption of highly productive plant species with faster turnover rates can promote soil C sequestration by increasing C input. However, excessive C removal from ecosystems due to overgrazing or improper soil fertilization management results in higher C loss, which can have detrimental effects on soil C sequestration. Proper stocking rate and a balanced manure/fertilizer management was found to be critical for enhancing NUE. Grazing land management sometimes simultaneously influence the three soil properties. Techniques that can increase soil C such as introduction of high productive plant species can often promote water infiltration and soil nitrogen (N). Some other practices such as adoption of N fertilizer may enhance C sequestration while being detrimental to NUE. An integrated management plan for a specific location or farm should be considered carefully to improve soil health as well as ecosystem production. This review provides farmers and policy makers the current state of general knowledge on how health-related soil processes are affected by grazing land management.
Delay Factors in Reconstruction Projects: A Case Study of Mataf Expansion Project
Authors: Khatib Basem Al , Poh Yap Soon , El-Shafie Ahmed
Published: December 2018

Delays in construction projects are a common phenomenon throughout the industry. This problem has many negative impacts on the time, cost, and sustainability of the projects. Many studies were conducted to identify the main causes of this delay in new construction projects in different regions but very few studies have focused on finding an explanation for the causes of delay in major reconstruction projects that have great religious and cultural sustainability. This paper examines the factors that contributed to work delays in one of the most major reconstruction projects that took place recently in the Middle East, which is namely the Mataf Expansion Project in the city of Mecca, Saudi Arabia. Fourteen interviews were conducted with project managers, construction managers, and senior site engineers to identify the factors that they encountered and led to the delay in the reconstruction activities of this project. Some of the findings were consistent and similar to most other causes of delay that are associated with new construction projects. However, interestingly, this research has discovered the existence of other unavoidable factors that caused a delay and should be considered for any similar reconstruction projects. The results showed that these factors could be divided into two groups: the first one is related to the demolition phase (five factors) and the second group is related to construction works (nine factors). In addition, it has been observed that the building material during the reconstruction is considered one of the major delaying factors. Finally, these 14 delay factors should be carefully considered to assure the sustainability of the main object’s function during the reconstruction activities.
Relationship Modeling of Critical Success Factors for Enhancing Sustainability and Performance in E-Learning
Authors: Ahmad Naim , Quadri Noorulhasan Naveed , Qureshi Mohamed Rafik N. , Alam Mohammad Mahtab
Published: December 2018

E-learning, a technology-mediated learning approach, is a pervasively adopted teaching/learning mode for transferring knowledge. Some of the motivational factors for its wide adoption are time and location independence, user-friendliness, on-demand service, resource richness, and multi-media and technology driven factors. Achieving sustainability and performance in its delivery is of paramount importance. This research utilizes the critical success factors (CSFs) approach to identify the sustainable E-learning implementation model. Fifteen CSFs have been identified through the literature review, expert opinions, and in-depth interviews. These CSFs have been modeled for interdependence using interpretive structural modeling and Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) analysis. Further, the model has been validated through in-depth interviews. The present research provides quantification of CSFs of E-learning in terms of their driving and dependence powers and their classification thorough MICMAC analysis. The E-learning system organizers may focus on improving upon the enablers such as organizational infrastructure readiness, efficient technology infrastructure, appropriate E-learning course design, course flexibility, understandable relevant content, stakeholders’ training, security, access control and privileges, commitment, and being user–friendly and well-organized, in order to enhance the sustainability and performance in E-learning. This study will also help E-learning stakeholders in relocating and prioritizing resources.
Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System
Authors: Kim Min-Sung , Lee Eul-Bum , Jung In-Hye , Alleman Douglas
Published: December 2018

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.
Ecological Niche Space of Fish Communities in Impounded Sections of Large Rivers: Its Application to Assessment of the Impact of Weirs on River Ecosystems
Authors: Hur Jun Wook , Jang Min-Ho , Shin Kyung-Hoon , Lee Kyung-Lak , Chang Kwang-Hyeon
Published: December 2018

To estimate the impact of weirs on large river fish communities, we applied the ecological niche space (ENS) measured quantitatively using carbon and nitrogen stable isotope ratios to the monitoring of effects of weirs constructed on four major rivers in Korea. ENS was calculated using the Bayesian stable isotope in R statistics. The ENS of fish communities showed persistent differences between upstream and downstream areas of all studied weirs. The ENSs of omnivores were larger in upstream impounded areas but the ENSs of predator species, both endemic (Erythroculter erythropterus) and exotic (Micropterus salmoides) predators had decreased ENSs in upstream areas. E. erythropterus showed horizontal variations in a wide range of carbon stable isotopes, whereas M. salmoides showed vertical variations in nitrogen stable isotopes. The results suggest that weir construction may have species-specific impact on the ENS of fish community by impoundment and increase niche overlap in upstream areas of the weir. The measured ENS of fish community was significantly correlated with the relative abundance of tolerant species negatively, whereas correlated with that of endemic species positively, suggesting that the ENS can be used as a comprehensive indicator of habitat conditions.
Comparative Study of Natural Radioactivity and Radiological Hazard Parameters of Various Imported Tiles Used for Decoration in Sudan
Authors: Siddeeg Saifeldin M. , Suliman Mohamed A. , Ben Rebah Faouzi , Mnif Wissem , Ahmed Amel Y. , Salih Isam
Published: December 2018

Various commercially imported ceramic materials used in the building of Sudanese dwellings were examined in order to determine their natural radioactivity and radiological hazard parameters. In this context, twenty-five different consignments were sampled and analyzed using (3″ × 3″) sodium iodide gamma spectrometry system NaI(Tl). The identified average activity concentrations of 238U, 232Th, and 40K were 183 ± 70, 51 ± 44, and 238 ± 77 Bq/kg dry-weights, respectively. A positive correlation between 238U and 232Th in the investigated samples was identified from the observed significant correlation (R2 = 0.8). Interestingly, a low Th/U ratio (~0.3) was recorded, which could be related to the systematic loss of thorium during the fabrication process. The measured activity concentrations for these radionuclides were comparable with the reported data obtained from similar materials used in other countries showing similarity in ceramic materials used in buildings. Five different radiation indices, such as the average radium equivalent (Raeq), the absorbed dose rate (D), the annual effective dose equivalent (AEDE), the external hazard index (Hex), and the radioactivity level index (lγ), which indicate hazardous radiation, were estimated from these measurements. The obtained results revealed average values of 274 ± 106 Bq/kg, 125 ± 48 nGy/h, 1.23 ± 0.48 mSv/y, 0.74 ± 0.29, and 0.94 ± 0.37, for Raeq, D, AEDE, Hex, and lγ, respectively. The mean values of Raeq and Hex were in good agreement with the international limits, while the means of D and lγ were higher than the universal values. Calculated AEDE in about 60% of the samples exceeded the universal limit of 1 mSv/y for the public exposure (maximum value of 2.16 mSv/y). The investigated parameters were in the same range for the majority of imported samples; however, they were slightly higher than the locally produced ceramic, highlighting the importance of monitoring imported materials for their radioactivity contents.
PV Forecasting Using Support Vector Machine Learning in a Big Data Analytics Context
Authors: Preda Stefan , Oprea Simona-Vasilica , Bâra Adela , Belciu (Velicanu) Anda
Published: December 2018

Renewable energy systems (RES) are reliable by nature; the sun and wind are theoretically endless resources. From the beginnings of the power systems, the concern was to know “how much” energy will be generated. Initially, there were voltmeters and power meters; nowadays, there are much more advanced solar controllers, with small displays and built-in modules that handle big data. Usually, large photovoltaic (PV)-battery systems have sophisticated energy management strategies in order to operate unattended. By adding the information collected by sensors managed with powerful technologies such as big data and analytics, the system is able to efficiently react to environmental factors and respond to consumers’ requirements in real time. According to the weather parameters, the output of PV could be symmetric, supplying an asymmetric electricity demand. Thus, a smart adaptive switching module that includes a forecasting component is proposed to improve the symmetry between the PV output and daily load curve. A scaling approach for smaller off-grid systems that provides an accurate forecast of the PV output based on data collected from sensors is developed. The proposed methodology is based on sensor implementation in RES operation and big data technologies are considered for data processing and analytics. In this respect, we analyze data captured from loggers and forecast the PV output with Support Vector Machine (SVM) and linear regression, finding that Root Mean Square Error (RMSE) for prediction is considerably improved when using more parameters in the machine learning process.
Edge-Version Atom-Bond Connectivity and Geometric Arithmetic Indices of Generalized Bridge Molecular Graphs
Authors: Zhang Xiujun , Wu Xinling , Akhter Shehnaz , Jamil Muhammad , Liu Jia-Bao , Farahani Mohammad
Published: December 2018

Topological indices are graph invariants computed by the distance or degree of vertices of the molecular graph. In chemical graph theory, topological indices have been successfully used in describing the structures and predicting certain physicochemical properties of chemical compounds. In this paper, we propose a definition of generalized bridge molecular graphs that can model more kinds of long chain polymerization products than the bridge molecular graphs, and provide some results of the edge versions of atom-bond connectivity ( A B C e ) and geometric arithmetic ( G A e ) indices for some generalized bridge molecular graphs, which have regular, periodic and symmetrical structures. The results of this paper offer promising prospects in the applications for chemical and material engineering, especially in chemical industry research.
Another View of Aggregation Operators on Group-Based Generalized Intuitionistic Fuzzy Soft Sets: Multi-Attribute Decision Making Methods
Authors: Hayat Khizar , Ali Muhammad Irfan , Cao Bing-Yuan , Karaaslan Faruk , Yang Xiao-Peng
Published: December 2018

In this paper, the existing definition of the group-based generalized intuitionistic fuzzy soft set is clarified and redefined by merging intuitionistic fuzzy soft set over the set of alternatives and a group of intuitionistic fuzzy sets on parameters. In this prospect, two new subsets of the group-based generalized intuitionistic fuzzy soft set are proposed and several operations are contemplated. The two new aggregation operators called generalized group-based weighted averaging and generalized group-based weighted geometric operator are introduced. The related properties of proposed operators are discussed. The recent research is emerging on multi-attribute decision making methods based on soft sets, intuitionistic fuzzy soft sets, and generalized intuitionistic fuzzy soft sets. An algorithm is structured and two case studies of multi-attribute decision makings are considered using proposed operators. Further, we provide the comparison and advantages of the proposed method, which give superiorities over recent major existing methods.
Post-Harvest Contamination with Mycotoxins in the Context of the Geographic and Agroclimatic Conditions in Romania
Authors: Gagiu Valeria , Mateescu Elena , Armeanu Ileana , Dobre Alina Alexandra , Smeu Irina , Cucu Mirela Elena , Oprea Oana Alexandra , Iorga Enuta , Belc Nastasia
Published: December 2018

This study aimed to assess post-harvest contamination with mycotoxins in the context of the geographic and agroclimatic conditions in Romania in 2012–2015, a period that was characterized by extreme meteorological events and the effects of climate change. The samples were randomly sampled from five agricultural regions of Romania and analyzed for mycotoxins by enzyme-linked immunosorbent assay. An SPSS analysis was done to explore correlations between mycotoxins (deoxynivalenol—DON, aflatoxins—AF, ochratoxin A—OTA, zearalenone—ZEA), product types (raw cereal, processed cereal, cereal-based food), geographic coordinates (latitude, longitude, agricultural region), and agroclimatic factors (air temperature, precipitation, soil moisture reserve, aridity index, soil type). In the southeast part of the Southern Plain and Dobrogea (Baragan Plain, located at 44–45° N, 26–27° E), contamination with AF and OTA was higher in raw and processed cereals (maize in silo, silo corn germs) in the dry years (2012 and 2013), and contamination with DON was high in processed cereals (wheat flour type 450) in the rainy year (2014). DON and OTA contamination were significantly correlated with cumulative precipitation in all years, while AF and ZEA contamination were non-significantly correlated with climatic factors and aridity indices. The distribution of mycotoxins by product type and the non-robust correlations between post-harvest mycotoxins and agrometeorological factors could be explained by the use of quality management systems that control cereal at warehouse receptions, performant processing technologies, and the quality of storage spaces of agri-food companies. The Baragan Plain is Romania’s most sensitive area to the predicted climate change in southeast Europe, which may be associated with its increased cereal contamination with AF and OTA.
AbobotulinumtoxinA (Dysport®), OnabotulinumtoxinA (Botox®), and IncobotulinumtoxinA (Xeomin®) Neurotoxin Content and Potential Implications for Duration of Response in Patients
Authors: Field Malgorzata , Splevins Andrew , Picaut Philippe , Van der Schans Marcel , Langenberg Jan , Noort Daan , Foster Keith
Published: December 2018

Botulinum neurotoxin type-A (BoNT-A) blocks the release of acetylcholine from peripheral cholinergic nerve terminals and is an important option for the treatment of disorders characterised by excessive cholinergic neuronal activity. Several BoNT-A products are currently marketed, each with unique manufacturing processes, excipients, formulation, and non-interchangeable potency units. Nevertheless, the effects of all the products are mediated by the 150 kDa BoNT-A neurotoxin. We assessed the quantity and light chain (LC) activity of BoNT-A in three commercial BoNT-A products (Dysport®; Botox®; Xeomin®). We quantified 150 kDa BoNT-A by sandwich ELISA and assessed LC activity by EndoPep assay. In both assays, we assessed the results for the commercial products against recombinant 150 kDa BoNT-A. The mean 150 kDa BoNT-A content per vial measured by ELISA was 2.69 ng/500 U vial Dysport®, 0.90 ng/100 U vial Botox®, and 0.40 ng/100 U vial Xeomin®. To present clinically relevant results, we calculated the 150 kDa BoNT-A/US Food and Drug Administration (FDA)-approved dose in adult upper limb spasticity: 5.38 ng Dysport® (1000 U; 2 × 500 U vials), 3.60 ng Botox® (400 U; 4 × 100 U vials), and 1.61 ng Xeomin® (400 U; 4 × 100 U vials). EndoPep assay showed similar LC activity among BoNT-A products. Thus, greater amounts of active neurotoxin are injected with Dysport®, at FDA-approved doses, than with other products. This fact might explain the long duration of action reported across multiple indications, which benefits patients, caregivers, clinicians, and healthcare systems.
Further Understanding of Degradation Pathways of Microcystin-LR by an Indigenous Sphingopyxis sp. in Environmentally Relevant Pollution Concentrations
Authors: Ding Qin , Liu Kaiyan , Xu Kai , Sun Rongli , Zhang Juan , Yin Lihong , Pu Yuepu
Published: December 2018

Microcystin-LR (MC-LR) is the most widely distributed microcystin (MC) that is hazardous to environmental safety and public health, due to high toxicity. Microbial degradation is regarded as an effective and environment-friendly method to remove it, however, the performance of MC-degrading bacteria in environmentally relevant pollution concentrations of MC-LR and the degradation pathways remain unclear. In this study, one autochthonous bacterium, Sphingopyxis sp. m6 which exhibited high MC-LR degradation ability, was isolated from Lake Taihu, and the degrading characteristics in environmentally relevant pollution concentrations were demonstrated. In addition, degradation products were identified by utilizing the full scan mode of UPLC-MS/MS. The data illustrated that strain m6 could decompose MC-LR (1–50 μg/L) completely within 4 h. The degradation rates were significantly affected by temperatures, pH and MC-LR concentrations. Moreover, except for the typical degradation products of MC-LR (linearized MC-LR, tetrapeptide, and Adda), there were 8 different products identified, namely, three tripeptides (Adda-Glu-Mdha, Glu-Mdha-Ala, and Leu-MeAsp-Arg), three dipeptides (Glu-Mdha, Mdha-Ala, and MeAsp-Arg) and two amino acids (Leu, and Arg). To our knowledge, this is the first report of Mdha-Ala, MeAsp-Arg, and Leu as MC-LR metabolites. This study expanded microbial degradation pathways of MC-LR, which lays a foundation for exploring degradation mechanisms and eliminating the pollution of microcystins (MCs).
A Sensitive LC-MS/MS Method for Palytoxin Using Lithium Cationization
Authors: Klijnstra Mirjam D. , Gerssen Arjen
Published: December 2018

Palytoxin (PlTX) and analogues are produced by certain dinoflagellates, sea anemones, corals and cyanobacteria. PlTX can accumulate in the food chain and when consumed it may cause intoxication with symptoms like myalgia, weakness, fever, nausea, and vomiting. The analysis of PlTXs is challenging, and because of the large molecular structure, it is difficult to develop a sensitive and selective liquid chromatography-mass spectrometry (LC-MS/MS) method. In this work, an LC-MS/MS method was developed to analyse PlTXs with use of lithium iodine and formic acid as additives in the mobile phase. For method development, initially, LC-hrMS was used to accurately determine the elemental composition of the precursor and product ions. The main adduct formed was [M + H + 2Li]3+. Fragments were identified with LC-hrMS and these were incorporated in the LC-MS/MS method. A method of 10 min was developed and a solid phase extraction clean-up procedure was optimised for shellfish matrix. The determined limits of detection were respectively 8 and 22 µg PlTX kg−1 for mussel and oyster matrix. Oysters gave a low recovery of approximately 50% for PlTX during extraction. The method was successfully in-house validated, repeatability had a relative standard deviation less than 20% (n = 5) at 30 µg PlTX kg−1 in mussel, cockle, and ensis, and at 60 µg PlTX kg−1 in oyster.