bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Analysis between Wild and Cultivated Cucumbers Reveals Transcriptional Changes during Domestication Process
Authors: Abdel-Salam Eslam M. , Faisal Mohammad , Alatar Abdulrahman A. , Saquib Quaiser , Alwathnani Hend A.
Published: January 2020

The cultivated cucumber (Cucumis sativus L.) was reported to have been developed from a wild cucumber (Cucumis hystrix Chakrav.), nevertheless, these two organisms exhibit noteworthy differences. For example, the wild cucumber is known for its high resistance to different biotic and abiotic stresses. Moreover, the leaves and fruits of the wild cucumber have a bitter taste compared to the cultivated cucumber. These differences could be attributed mainly to the differences in gene expression levels. In the present investigation, we analyzed the RNA-sequencing data to show the differentially expressed genes (DEGs) between the wild and cultivated cucumbers. The identified DEGs were further utilized for Gene Ontology (GO) and pathway enrichment analysis and for identification of transcription factors and regulators. In the results, several enriched GO terms in the biological process, cellular component, and molecular functions categories were identified and various enriched pathways, especially the biosynthesis pathways of secondary products were recognized. Plant-specific transcription factor families were differentially expressed between the wild and cultivated cucumbers. The results obtained provide preliminary evidence for the transcriptional differences between the wild and cultivated cucumbers which developed during the domestication process as a result of natural and/or artificial selection, and they formulate the basis for future genetic research and improvement of the cultivated cucumber.
Gene Expression and K+ Uptake of Two Tomato Cultivars in Response to Sub-Optimal Temperature
Authors: Gao Huan , Yang Wanji , Li Chunxia , Zhou Xingang , Gao Danmei , Khashi u Rahman Muhammad , Li Naihui , Wu Fengzhi
Published: January 2020

Sub-optimal temperatures can adversely affect tomato (Solanum lycopersicum) growth, and K+ plays an important role in the cold tolerance of plants. However, gene expression and K+ uptake in tomato in response to sub-optimal temperatures are still not very clear. To address these questions, one cold-tolerant tomato cultivar, Dongnong 722 (T722), and one cold-sensitive cultivar, Dongnong 708 (S708), were exposed to sub-optimal (15/10 °C) and normal temperatures (25/18 °C), and the differences in growth, K+ uptake characteristics and global gene expressions were investigated. The results showed that compared to S708, T722 exhibited lower reduction in plant growth rate, the whole plant K+ amount and K+ net uptake rate, and T722 also had higher peroxidase activity and lower K+ efflux rate under sub-optimal temperature conditions. RNA-seq analysis showed that a total of 1476 and 2188 differentially expressed genes (DEGs) responding to sub-optimal temperature were identified in S708 and T722 roots, respectively. Functional classification revealed that most DEGs were involved in “plant hormone signal transduction”, “phenylpropanoid biosynthesis”, “sulfur metabolism” and “cytochrome P450”. The genes that were significantly up-regulated only in T722 were involved in the “phenylpropanoid biosynthesis” and “plant hormone signal transduction” pathways. Moreover, we also found that sub-optimal temperature inhibited the expression of gene coding for K+ transporter SIHAK5 in both cultivars, but decreased the expression of gene coding for K+ channel AKT1 only in S708. Overall, our results revealed the cold response genes in tomato roots, and provided a foundation for further investigation of mechanism involved in K+ uptake in tomato under sub-optimal temperatures.
The Effect of Organic Mulching and Irrigation on the Weed Species Composition and the Soil Weed Seed Bank of Tomato
Authors: Petrikovszki Renáta , Zalai Mihály , Tóthné Bogdányi Franciska , Tóth Ferenc
Published: January 2020

Mulching is a management technique to control weeds in organic and integrated tomato production. Our experiment was designed to investigate the impact of organic mulch combined with irrigation on the weed species composition and weed seed bank of open-field tomato. For three consecutive years (2016–2018), treatment of microplots included mulch only, irrigation only, mulch and irrigation combined, and the untreated control. Marginal microplots (bordered by the surrounding mown grassland) were distinguished from inner microplots to check margin effect. We collected soil samples from different depths and let the weed seeds germinate in a greenhouse. Germinated weed seedlings were counted and identified. The number of weeds, and time needed for weeding was reduced by mulching, temperature, sampling date, and the succession of the study years. Irrigation, on the other hand, had no effect on weeding time. Margin effect and year had the highest influence on weed species composition. Regarding seed bank, year and mulching had the highest influence. The importance of other variables remained low, with mulching being the strongest explained variable. Regardless of treatments, weed composition of the study area was transformed during the three-year study.
Potential and Challenges of Improving Photosynthesis in Algae
Authors: Vecchi Valeria , Barera Simone , Bassi Roberto , Dall’Osto Luca
Published: January 2020

Sunlight energy largely exceeds the energy required by anthropic activities, and therefore its exploitation represents a major target in the field of renewable energies. The interest in the mass cultivation of green microalgae has grown in the last decades, as algal biomass could be employed to cover a significant portion of global energy demand. Advantages of microalgal vs. plant biomass production include higher light-use efficiency, efficient carbon capture and the valorization of marginal lands and wastewaters. Realization of this potential requires a decrease of the current production costs, which can be obtained by increasing the productivity of the most common industrial strains, by the identification of factors limiting biomass yield, and by removing bottlenecks, namely through domestication strategies aimed to fill the gap between the theoretical and real productivity of algal cultures. In particular, the light-to-biomass conversion efficiency represents one of the major constraints for achieving a significant improvement of algal cell lines. This review outlines the molecular events of photosynthesis, which regulate the conversion of light into biomass, and discusses how these can be targeted to enhance productivity through mutagenesis, strain selection or genetic engineering. This review highlights the most recent results in the manipulation of the fundamental mechanisms of algal photosynthesis, which revealed that a significant yield enhancement is feasible. Moreover, metabolic engineering of microalgae, focused upon the development of renewable fuel biorefineries, has also drawn attention and resulted in efforts for enhancing productivity of oil or isoprenoids.
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing
Authors: Hu Zhengbiao , He Dongfeng , Song Wei , Feng Kai
Published: January 2020

Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man–machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption.
Microwave Heating Behavior in SiC Fiber-MO2 Mixtures (M = Ce, Zr)—Selective Heating of Micrometer-Sized Fibers Facilitated by ZrO2 Powder
Authors: Kashimura Keiichiro , Fukushima Jun , Namioka Tomoaki , Fujii Takashi , Takizawa Hirotsugu , Fukushima Hideoki
Published: January 2020

SiC fiber-MO2 (M = Ce, Zr) mixtures with various compositions were heated by applying an 80 W microwave electric field, to investigate their heating rate, maximum temperature, and dielectric constant. For the SiC fiber-CeO2 mixture, all three parameters continued to increase as the weight ratio of the SiC fiber increased; in contrast, for the SiC fiber-ZrO2 mixture, these parameters reached a maximum value at a certain composition. A thermal gradient of 500 °C was observed at a microlevel in the SiC fiber-ZrO2 mixture, and hot spots were located in regions with a certain composition. This result not only contributes to designing a novel good microwave absorber but also presents new aspects with regard to high-temperature microwave processing, including the mechanism behind the high-temperature gradients on the order of micrometers as well as engineering applications that utilize these high-temperature gradients.
Model-Based Tools for Pharmaceutical Manufacturing Processes
Authors: Schenkendorf René , Gerogiorgis Dimitrios , Mansouri Seyed , Gernaey Krist
Published: January 2020

Active pharmaceutical ingredients (APIs) are highly valuable, highly sensitive products resulting from production processes with strict quality control specifications and regulations that are required for the safety of patients [...]
A Hybrid Inverse Problem Approach to Model-Based Fault Diagnosis of a Distillation Column
Authors: Sun Suli , Cui Zhe , Zhang Xiang , Tian Wende
Published: January 2020

Early-stage fault detection and diagnosis of distillation has been considered an essential technique in the chemical industry. In this paper, fault diagnosis of a distillation column is formulated as an inverse problem. The nonlinear least squares algorithm is used to evaluate fault parameters embedded in a nonlinear dynamic model of distillation once abnormal symptoms are detected. A partial least squares regression model is built based on fault parameter history to explicitly predict the development of fault parameters. With the stripper of Tennessee Eastman process as example, this novel approach is tested for step- and random-type faults and several factors affecting its efficiency are discussed. The application result shows that the hybrid inverse problem approach gives the correct change of fault parameter at a speed far faster than the base approach with only a nonlinear model.
Leaching Behaviors of Impurities in Titanium-Bearing Electric Furnace Slag in Sulfuric Acid
Authors: Nie Wenlin , Wen Shuming , Liu Dan , Zhang Qian , Liu Junbo , Feng Qicheng
Published: January 2020

Titanium-bearing electric furnace slag (TEFS) was prepared from vanadium titanomagnetite and leached with sulfuric acid. The Ti leaching rate of vanadium titanomagnetite TEFS is significantly lower than that of ilmenite TEFS. The impurity content in vanadium titanomagnetite TEFS is higher than that in ilmenite TEFS. This might be one of the main factors resulting in the low leaching rate of Ti, so the leaching behaviors of various impurities under different conditions (temperature, acid/solid weight ratio, particle size, and initial sulfuric acid concentration) were investigated. The following trends were observed under different leaching conditions: The leaching rate of Fe increased rapidly and reached equilibrium quickly, that of Si increased quickly in the early stage and then decreased in the later stage, that of Ca increased initially and reached equilibrium later, and the leaching rates of Mg and Al increased gradually until the equilibrium was reached. The leaching rate of Fe was too rapid to be able to investigate its leaching kinetics, and the insoluble leached products of Si and Ca interfered with their leaching. The effects of leaching parameters on the leaching of impurities were further analyzed by X-ray diffraction (XRD) and scanning electron microscopy analysis. XRD data indicated that spinel is the major Mg- and Al-bearing mineral in TEFS. Mg and Al showed similar leaching behaviors, and their leaching conformed to a new model based on interface transfer and diffusion across the product layer, both of which affect the leaching rate.
Assessment of the Use of Natural Extracted Dyes and Pancreatin Enzyme for Dyeing of Four Natural Textiles: HPLC Analysis of Phytochemicals
Authors: Salem Mohamed Z. M. , Ibrahim Ibrahim H. M. , Ali Hayssam M. , Helmy Hany M.
Published: January 2020

In the present study, four natural textiles (cotton, linen, wool, and silk) were dyed with 14 naturally extracted dyes, and pancreatin enzyme was used in the dyeing process. The effects of pancreatin enzyme and its buffer on naturally dyed textile samples were evaluated. Two concentrations of pancreatin enzyme and buffer were used as pretreatments for dyed textiles. Proteinic fabrics showed the highest relative color strength (RCS) values of 137.23% and 132.2% when the pancreatin enzyme was applied on wool and silk dyed with pomegranate skin and bloodroot at concentrations A and B, respectively. Linen fiber dyed with catechu tree showed the highest total color difference (TCD) values with buffer (6.83) and pancreatin enzyme A (5.7) and B (6.3). This shows that there were no side effects of the pancreatin enzyme on the studied dyed textiles. By high-performance liquid chromatography (HPLC) analysis, the root extract from madder showed the presence of salicylic acid (1758.91 mg/kg extract), quercetin (844.23 mg/kg extract), ellagic acid (784.86 mg/kg extract) and benzoic acid (582.68 mg/kg extract) as main compounds. In cochineal extract the main compounds were rutin (37.732 mg/kg extract), kampherol (1915.98 mg/kg extract), myricetin (809.97 mg/kg extract), quercetin (496.76 mg/kg extract) and salicylic acid (193.87 mg/kg extract).
Study on Oil Film Characteristics of Piston-Cylinder Pair of Ultra-High Pressure Axial Piston Pump
Authors: Zhang Jin , Liu Baolei , LÜ Ruiqi , Yang Qifan , Dai Qimei
Published: January 2020

The piston-cylinder pair is the key friction pairs in the piston pump. Its performance determines the volume efficiency of piston pump. With the increase of load pressure, the leakage at the clearance of piston-cylinder pair will also increase. In order to reduce leakage, the clearance of the piston-cylinder pair of the ultra-high pressure piston pump is smaller than that of the medium-high pressure piston pump. In order to explore whether the piston will stuck in the narrow gap, it is necessary to study the oil film characteristics of the piston-cylinder pair under the condition of ultra-high pressure, so as to provide a theoretical basis for the optimal design of the piston-cylinder pair of ultra-high pressure axial piston pump. In this paper, an ultra-high pressure axial piston pump is taken as the research object, and its structural characteristics are analyzed. The mathematical model of the oil film thickness of the piston-cylinder pair is established by using the cosine theorem in the cross section of the piston. The finite volume method is used to discretize the Reynolds equation of the oil film of the piston-cylinder pair, and the over relaxation iteration method is used to solve the discrete equations, and the mathematical model of the oil film pressure of the piston-cylinder pair is obtained. The mathematical model of oil film thickness and pressure field of piston-cylinder pair is solved by programming. The dynamic change process of oil film thickness and pressure field of the plunger pair of the ultra-high pressure axial piston pump under the load of 20 MPa and 70 MPa is obtained. Under the two conditions, the thinnest area of the oil film reaches 3 μm and 2 μm dangerous area respectively; the oil film pressure reaches 20 MPa and 70 MPa respectively when the swashplate rotates 10° and continues to increase with the increase of swashplate rotation angle. When the rotation angle reaches 90°, the oil film pressure also reaches the maximum value, but there is no pressure spike phenomenon. The oil film pressure characteristics of ultra-high pressure axial piston pump under conventional and ultra-high pressure conditions were obtained by modification and experimentation.
Numerical Analysis to the Effect of Guiding Plate on Flow Characteristics in a Ball Valve
Authors: Wang Yanping , Zhu Chaoning , Zhang Guang , Wang Dejing , Jiang Minghe , Zhu Zuchao , Lin Zhe
Published: January 2020

When internal flows go through a valve with a small opening degree, high-speed jet flows are induced, which causes the erosion of the valve core and affects the stability of the flow field. Setting guiding plates in the valve behind the valve core has the function of reducing the adverse effect of high-speed jet flows. In this work, numerical simulations were carried out to investigate the effect of the guiding plate on flow and resistance coefficient, velocity and pressure distributions and flow stability downstream of the valve. The number of guiding plates was changed from 0 to 3 and the opening degree was varied from 0 to 100% at intervals of 10%. A guiding plate with holes in it plays the role of bypassing and guiding flow. Under the action of the guiding plate, the flow coefficient obviously decreases, the gap flow between the valve core and the valve wall in the top of the valve are modified, and the gap flow even disappeared in the valve with 3 guiding plates. It was found that setting the guiding plate can improve the performance of the ball valve, reducing the internal erosion and increasing the stability of valve downstream flow efficiently.
Exergy, Economic, and Life-Cycle Assessment of ORC System for Waste Heat Recovery in a Natural Gas Internal Combustion Engine
Authors: Valencia Ochoa Guillermo , Cárdenas Gutierrez Javier , Duarte Forero Jorge
Published: January 2020

In this article, an organic Rankine cycle (ORC) was integrated into a 2-MW natural gas engine to evaluate the possibility of generating electricity by recovering the engine’s exhaust heat. The operational and design variables with the greatest influence on the energy, economic, and environmental performance of the system were analyzed. Likewise, the components with greater exergy destruction were identified through the variety of different operating parameters. From the parametric results, it was found that the evaporation pressure has the greatest influence on the destruction of exergy. The highest fraction of exergy was obtained for the Shell and tube heat exchanger (ITC1) with 38% of the total exergy destruction of the system. It was also determined that the high value of the heat transfer area increases its acquisition costs and the levelized cost of energy (LCOE) of the thermal system. Therefore, these systems must have a turbine technology with an efficiency not exceeding 90% because, from this value, the LCOE of the system surpasses the LCOE of a gas turbine. Lastly, a life cycle analysis (LCA) was developed on the system operating under the selected organic working fluids. It was found that the component with the greatest environmental impact was the turbine, which reached a maximum value of 3013.65 Pts when the material was aluminum. Acetone was used as the organic working fluid.
An Analysis of Waste Heat Recovery from Wastewater on Livestock and Agriculture Farms
Authors: Słyś Daniel , Pochwat Kamil , Czarniecki Dorian
Published: January 2020

Agriculture is one of the sectors of the economy in which it is possible to conduct much more rational energy economy. The easiest way to achieve financial savings as well as reduce air pollution is to use waste heat sources. Heat pumps are perfect for this. Particularly favorable is the case when the device can operate in an alternative system and serve both heating and cooling purposes. The purpose of this article was to present possible solutions for installations enabling heat recovery from wastewater to supply agri-breeding farms with hot utility and technological water, a financial analysis of their application, and an assessment of the impact of these solutions on possible reduction of pollutant emissions. The tests were carried out for four variants of cooperation between a heat pump and an exchanger. In the first variant, waste heat was used in the process of heating water used to clean stands and prepare feed. In the second variant, waste heat took part in heating the water used for watering plants. In the third variant, waste heat was used in the process of drying cereals. In turn, in the last variant, waste heat supported the preparation of utility hot water for the breeder’s residential building. The study showed the legitimacy of using thermal energy from liquid manure as a waste heat source on farms and farming. This is mainly due to the short payback period, which can be within 2–4 years. In turn, the analysis of pollution reduction associated with the recovery of waste energy showed that the use of heat pumps allowed a significant reduction in the emission of harmful compounds to the atmosphere, in particular carbon dioxide. It is worth noting that livestock breeding is one of the most important branches of agricultural production not only in Poland but also throughout Europe, Asia and South and North America. For this reason, the use of waste heat-recovery systems enables real savings in the purchase of energy and reduction of pollutant emissions arising during traditional production processes.
Risks Special Issue on “Granular Models and Machine Learning Models”
Authors: Taylor Greg
Published: January 2020

It is probably fair to date loss reserving by means of claim modelling from the late 1960s [...]
In-Sample Hazard Forecasting Based on Survival Models with Operational Time
Authors: Bischofberger Stephan M.
Published: January 2020

We introduce a generalization of the one-dimensional accelerated failure time model allowing the covariate effect to be any positive function of the covariate. This function and the baseline hazard rate are estimated nonparametrically via an iterative algorithm. In an application in non-life reserving, the survival time models the settlement delay of a claim and the covariate effect is often called operational time. The accident date of a claim serves as covariate. The estimated hazard rate is a nonparametric continuous-time alternative to chain-ladder development factors in reserving and is used to forecast outstanding liabilities. Hence, we provide an extension of the chain-ladder framework for claim numbers without the assumption of independence between settlement delay and accident date. Our proposed algorithm is an unsupervised learning approach to reserving that detects operational time in the data and adjusts for it in the estimation process. Advantages of the new estimation method are illustrated in a data set consisting of paid claims from a motor insurance business line on which we forecast the number of outstanding claims.
Dedicated Nonlinear Control of Robot Manipulators in the Presence of External Vibration and Uncertain Payload
Authors: Mustafa Mustafa M. , Hamarash Ibrahim , Crane Carl D.
Published: January 2020

Robot manipulators are often tasked with working in environments with vibrations and are subject to load uncertainty. Providing an accurate tracking control design with implementable torque input for these robots is a complex topic. This paper presents two approaches to solve this problem. The approaches consider joint space tracking control design in the presence of nonlinear uncertain torques caused by external vibration and payload variation. The properties of the uncertain torques are used in both approaches. The first approach is based on the boundedness property, while the second approach considers the differentiability and boundedness together. The controllers derived from each approach differ from the perspectives of accuracy, control effort, and disturbance properties. A Lyapunov-based analysis is utilized to guarantee the stability of the control design in each case. Simulation results validate the approaches and demonstrate the performance of the controllers. The derived controllers show stable results at the cost of the mentioned properties.
A Variational Stacked Autoencoder with Harmony Search Optimizer for Valve Train Fault Diagnosis of Diesel Engine
Authors: Chen Kun , Mao Zhiwei , Zhao Haipeng , Jiang Zhinong , Zhang Jinjie
Published: January 2020

Diesel engine fault diagnosis is vital due to enhanced reliability and economic efficiency requirements. The extracted features in traditional fault diagnosis are constructed manually, which is very cumbersome because of the requirement for lots of expertise. To handle this issue, this paper proposed a variational stacked autoencoder (VSAE) to adaptively extract features from angular domain signals. As an unsupervised algorithm, VSAE can extract high-level features with the help of multiple encoding layers. Layer-wise pre-training and fine-tuning are introduced to get a better network initialization value. Moreover, the dropout technique and the batch normalization technique are carried out to prevent over-fitting and implement fast convergence. Finally, the harmony search optimizer (HSO) algorithm is introduced to get an appropriate hyper-parameter setting in the VSAE model, as well as make adaptive adjustment of the network structure. In order to verify the proposed method, the valve train fault data is collected on the diesel engine test rig under twelve operating conditions. The results indicate that the proposed scheme can effectively diagnose different degrees of intake valve fault, exhaust valve fault, and coupling fault under various operating conditions. Furthermore, the classification accuracy improved from 94.10% to 98.85%VSAE compared with stacked autoencoder (SAE) and some other traditional fault diagnosis algorithms.
Tracking Monochloramine Decomposition in MIMS Analysis
Authors: Roumiguières Adrien , Kinani Said , Bouchonnet Stéphane
Published: January 2020

Membrane-introduction mass spectrometry (MIMS) has been presented as one of the promising approaches for online and real-time analysis of monochloramine (NH2Cl) in diverse matrices such as air, human breath, and aqueous matrices. Selective pervaporation of NH2Cl through the introduction membrane overcomes the need for sample preparation steps. However, both the selectivity and sensitivity of MIMS can be affected by isobaric interferences, as reported by several researchers. High-resolution mass spectrometry helps to overcome those interferences. Recent miniaturization of Fourier transform—ion cyclotron resonance—mass spectrometry (FT-ICR MS) technology coupled to the membrane-introduction system provides a potent tool for in field analysis of monochloramine in environmental matrices. Monochloramine analysis by MIMS based FT-ICR MS system demonstrated decomposition into ammonia. To further clarify the origin of this decomposition, headspace analyses after bypassing the membrane were undertaken and showed that monochloramine decomposition was not exclusively related to interactions within the membrane. Adsorption inside the MIMS device, followed by surface-catalyzed decomposition, was suggested as a plausible additional mechanism of monochloramine decomposition to ammonia.
Two Different Methods to Measure the Stability of Acetabular Implants: A Comparison Using Artificial Acetabular Models
Authors: Goossens Quentin , Pastrav Leonard Cezar , Mulier Michiel , Desmet Wim , Vander Sloten Jos , Denis Kathleen
Published: January 2020

The total number of total hip arthroplasties is increasing every year, and approximately 10% of these surgeries are revisions. New implant design and surgical techniques are evolving quickly and demand accurate preclinical evaluation. The initial stability of cementless implants is one of the main concerns of these preclinical evaluations. A broad range of initial stability test methods is currently used, which can be categorized into two main groups: Load-to-failure tests and relative micromotion measurements. Measuring relative micromotion between implant and bone is recognized as the golden standard for implant stability testing as this micromotion is directly linked to the long-term fixation of cementless implants. However, specific custom-made set-ups are required to measure this micromotion, with the result that numerous studies opt to perform more straightforward load-to-failure tests. A custom-made micromotion test set-up for artificial acetabular bone models was developed and used to compare load-to-failure (implant push-out test) with micromotion and to assess the influence of bone material properties and press-fit on the implant stability. The results showed a high degree of correlation between micromotion and load-to-failure stability metrics, which indicates that load-to-failure stability tests can be an appropriate estimator of the primary stability of acetabular implants. Nevertheless, micromotions still apply as the golden standard and are preferred when high accuracy is necessary. Higher bone density resulted in an increase in implant stability. An increase of press-fit from 0.7 mm to 1.2 mm did not significantly increase implant stability.
Minimizing the Energy Hole Problem in Wireless Sensor Networks: A Wedge Merging Approach
Authors: Sharmin Nusrat , Karmaker Amit , Lambert William Luke , Alam Mohammad Shah , Shawkat MST Shamim Ara
Published: January 2020

The Energy hole problem, a common phenomenon in wireless sensor networks, significantly decreases the lifetime of any deployed network. Some of the popular techniques to minimize such problems are using mobile sinks instead of static sinks, extending the transmission range dynamically, and deploying redundant sensor nodes near the base station/sink. The major drawback to these techniques are that energy holes may still be created at some point due to their static nature of deployment, despite having the overall residual energy very high. In this research work, we adopt a new approach by dividing the whole network into equiangular wedges and merging a wedge with its neighboring wedge dynamically whenever individual residual energy of all member nodes of a wedge fall below a threshold value. We also propose an efficient Head Node (HN) selection scheme to reduce the transmission energy needed for forwarding data packets among Head Nodes. Simulation results show that WEMER, our proposed WEdge MERging based scheme, provides significantly higher lifetime and better energy efficiency compared to state-of-the-art Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and contemporary Concentric Clustering Scheme (CCS), and Multilayer Cluster Designing Algorithm (MCDA).
Impact of SCHC Compression and Fragmentation in LPWAN: A Case Study with LoRaWAN
Authors: Sanchez-Gomez Jesus , Gallego-Madrid Jorge , Sanchez-Iborra Ramon , Santa Jose , Skarmeta Antonio
Published: January 2020

The dawn of the Internet of Things (IoT) paradigm has brought about a series of novel services never imagined until recently. However, certain deployments such as those employing Low-Power Wide-Area Network (LPWAN)-based technologies may present severe network restrictions in terms of throughput and supported packet length. This situation prompts the isolation of LPWAN systems on islands with limited interoperability with the Internet. For that reason, the IETF’s LPWAN working group has proposed a Static Context Header Compression (SCHC) scheme that permits compression and fragmentation of and IPv6/UDP/CoAP packets with the aim of making them suitable for transmission over the restricted links of LPWANs. Given the impact that such a solution can have in many IoT scenarios, this paper addresses its real evaluation in terms not only of latency and delivery ratio improvements, as a consequence of different compression and fragmentation levels, but also of the overhead in end node resources and useful payload sent per fragment. This has been carried out with the implementation of middleware and using a real testbed implementation of a LoRaWAN-to-IPv6 architecture together with a publish/subscribe broker for CoAP. The attained results show the advantages of SCHC, and sustain discussion regarding the impact of different SCHC and LoRaWAN configurations on the performance. It is highlighted that necessary end node resources are low as compared to the benefit of delivering long IPv6 packets over the LPWAN links. In turn, fragmentation can impose a lack of efficiency in terms of data and energy and, hence, a cross-layer solution is needed in order to obtain the best throughput of the network.
RGB-IR Cross Input and Sub-Pixel Upsampling Network for Infrared Image Super-Resolution
Authors: Du Juan , Zhou Huixin , Qian Kun , Tan Wei , Zhang Zhe , Gu Lin , Yu Yue
Published: January 2020

Deep learning-based image super-resolution has shown significantly good performance in improving image quality. In this paper, the RGB-IR cross input and sub-pixel upsampling network is proposed to increase the spatial resolution of an Infrared (IR) image by combining it with a color image of higher spatial resolution obtained with a different imaging modality. Specifically, this is accomplished by fusion of the features map of two RGB-IR inputs in the reconstruction of an infrared image. To improve the accuracy of feature extraction, deconvolution is replaced by sub-pixel convolution to upsample image in the network. Then, the guided filter layer is introduced for image denoising of IR images, and it can preserve the image detail. In addition, the experimental dataset, which is collected by us, contains large numbers of RGB images and corresponding IR images with the same scene. Experimental results on our dataset and other datasets demonstrate that the method is superior to existing methods in accuracy and visual improvement.
A Survey of Blockchain Enabled Cyber-Physical Systems
Authors: Rathore Heena , Mohamed Amr , Guizani Mohsen
Published: January 2020

Cyber-physical systems (CPS) is a setup that controls and monitors the physical world around us. The advancement of these systems needs to incorporate an unequivocal spotlight on making these systems efficient. Blockchains and their inherent combination of consensus algorithms, distributed data storage, and secure protocols can be utilized to build robustness and reliability in these systems. Blockchain is the underlying technology behind bitcoins and it provides a decentralized framework to validate transactions and ensure that they cannot be modified. By distributing the role of information validation across the network peers, blockchain eliminates the risks associated with a centralized architecture. It is the most secure validation mechanism that is efficient and enables the provision of financial services, thereby giving users more freedom and power. This upcoming technology provides internet users with the capability to create value and authenticate digital information. It has the capability to revolutionize a diverse set of business applications, ranging from sharing economy to data management and prediction markets. In this paper, we present a holistic survey of various applications of CPS where blockchain has been utilized. Smart grids, health-care systems, and industrial production processes are some of the many applications that can benefit from the blockchain technology and will be discussed in the paper.
Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things
Authors: Khan Fawad Ali , Noor Rafidah Md , Kiah Miss Laiha Mat , Ahmedy Ismail , Yamani Mohd , Soon Tey Kok , Ahmad Muneer
Published: January 2020

Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms.
Seeking Gastronomic, Healthy, and Social Experiences in Tuscan Agritourism Facilities
Authors: Fanelli Rosa Maria
Published: January 2020

There is a growing desire among tourists to improve their lifestyle and pass their vacations in areas with a strong local gastronomic heritage. Indeed, one of the most important factors that drives visitors to choose an agritourism facility for their vacation is the pull of good food and wine. This manuscript examines visitors’ evaluations of their time spent in Tuscan agritourism facilities with particular focus on the cuisine, the health benefits, and the social experience. The analysis is based on a representative sample of 1886 reviews posted by visitors from all over of the world on the websites of 60 agritourism facilities that operate in Tuscan municipalities. By exploring visitor evaluations, which consist of an overall rating of their agritourism experience and separate ratings for the cuisine, the physical environment, and the service, this paper expands the scope of previous studies into food and drink management development as a way of attracting new visitors, by providing additional information on the distinctive characteristics of the local cuisine on offer. Results indicate that visitors—above all families—prefer an agritourism facility that offers authentic local cuisine and beverages and also offers them the possibility of spending time outdoors in destinations with a rich culinary heritage. Visibility of the main attractive attributes of agritourism facilities and the local cuisine through websites is needed in order to drive consumers in their vacation choices and to allow these structures to consolidate their place in the food and drink market.
A Systematic Review of Sustainable Banking through a Co-Word Analysis
Authors: Nájera-Sánchez Juan J.
Published: January 2020

The 2008 financial crisis placed banks in the gaze of public opinion. Financial entities did not delay in reacting, intensifying their efforts in what had become known as sustainable banking, with the goal of counteracting the negative effects of their loss of reputation. Neither has the academic community delayed their reaction, with the rapid growth of scientific production around this topic. However, no review of this literature through qualitative methods or bibliometry exists. The work presented in this paper fills one of those gaps, setting up a statistical description of the principal features of sustainable banking research and carrying out an analysis about its knowledge structure via co-word analysis. The results show a rapid evolution of the topics addressed, highlighting studies about the consequences of banks’ sustainability programs on their competitiveness. Future trends point to the search for more complex models, the incorporation of new stakeholders in the analysis and the consideration of different contexts.
Let’s Talk about Circular Economy: A Qualitative Exploration of Consumer Perceptions
Authors: Sijtsema Siet J. , Snoek Harriëtte M. , van Haaster-de Winter Mariët A. , Dagevos Hans
Published: January 2020

Consumer involvement plays a major role in the circular economy (CE), which requires a new and more active role of consumers. However, consumer awareness of and interest and involvement in the CE is low. Therefore, we aimed to find the starting points for consumer involvement in activities that promote a CE by exploring consumers’ general perceptions of the CE and several practice cases. Four focus group discussions were conducted (N = 24) in the Netherlands. The group discussions showed that most consumers did not have a clear understanding of the term “circular economy,” although their associations pointed in the right direction. Perceptions, attitudes, motives and barriers in terms of advantages and disadvantages varied among the participants and were related to (1) the functionalities of the products, (2) the production system, (3) economic aspects and (4) emotions such as concern about risks. We identified four key messages: targeting with regard to behaviours, attitudes and product functionalities; aligning with emotions; linking to practical cases; and applying multidimensional CE-related behaviour in everyday life and involving consumers in its innovation. These key messages are helpful in overcoming obstacles and barriers, raising awareness and providing input for sustainable consumption and production in the CE.
Wild Bee Conservation within Urban Gardens and Nurseries: Effects of Local and Landscape Management
Authors: Egerer Monika , Cecala Jacob , Cohen Hamutahl
Published: January 2020

Across urban environments, vegetated habitats provide refuge for biodiversity. Gardens (designed for food crop production) and nurseries (designed for ornamental plant production) are both urban agricultural habitats characterized by high plant species richness but may vary in their ability to support wild pollinators, particularly bees. In gardens, pollinators are valued for crop production. In nurseries, ornamental plants rarely require pollination; thus, the potential of nurseries to support pollinators has not been examined. We asked how these habitats vary in their ability to support wild bees, and what habitat features relate to this variability. In 19 gardens and 11 nurseries in California, USA, we compared how local habitat and landscape features affected wild bee species abundance and richness. To assess local features, we estimated floral richness and measured ground cover as proxies for food and nesting resources, respectively. To assess landscape features, we measured impervious land cover surrounding each site. Our analyses showed that differences in floral richness, local habitat size, and the amount of urban land cover impacted garden wild bee species richness. In nurseries, floral richness and the proportion of native plant species impacted wild bee abundance and richness. We suggest management guidelines for supporting wild pollinators in both habitats.
Sustainable Fruition of Cultural Heritage in Areas Affected by Rockfalls
Authors: Mineo Simone , Pappalardo Giovanna
Published: January 2020

This paper deals with the evaluation of rockfall risk in cultural heritage, in the frame of a quick protocol for a preliminary zonation, to ensure the safe management and sustainable fruition of the sites. Several historical complexes in mountainous areas are indeed threatened by rock slope instability, and rockfalls can be counted among the main causes of fatality. In such a complex, a rockfall risk zonation would represent a useful management tool for both the choice of specific safe tourist paths, but also for the proper employment of economic resources allocated for mitigation measures. Nevertheless, the management of cultural heritage lacks such plans and tourists are often exposed to risks, while funds are often employed without a specific priority. In this paper, a quick procedure was tested at the historical complex of Taormina (southern Italy), which hosts numerous tourist spots often affected by rockfalls. The Saracen castle, for example, is currently closed to the public due to the rockfalls that repeatedly affected the entrance road, while Castelmola village, counted among one of the most beautiful Italian villages, stands on the top of a cliff affected by frequent rockfalls involving the only access road. The approach is composed of several steps and requires a heavy site characterization in terms of historical records and geostructural setting. The risk assessment procedure was chosen among the semiquantitative ones available in literature, and the final assessed risk was represented on a thematic map to provide a tool which could be used as a base for the planning of final remedial works.
Fuzzy Cognitive Map-Based Sustainable Socio-Economic Development Planning for Rural Communities
Authors: Papageorgiou Konstantinos , Singh Pramod K. , Papageorgiou Elpiniki , Chudasama Harpalsinh , Bochtis Dionysis , Stamoulis George
Published: January 2020

Every development and production process needs to operate within a circular economy to keep the human being within a safe limit of the planetary boundary. Policymakers are in the quest of a powerful and easy-to-use tool for representing the perceived causal structure of a complex system that could help them choose and develop the right strategies. In this context, fuzzy cognitive maps (FCMs) can serve as a soft computing method for modelling human knowledge and developing quantitative dynamic models. FCM-based modelling includes the aggregation of knowledge from a variety of sources involving multiple stakeholders, thus offering a more reliable final model. The average aggregation method for weighted interconnections among concepts is widely used in FCM modelling. In this research, we applied the OWA (ordered weighted averaging) learning operators in aggregating FCM weights, assigned by various participants/ stakeholders. Our case study involves a complex phenomenon of poverty eradication and socio-economic development strategies in rural areas under the DAY-NRLM (Deendayal Antyodaya Yojana-National Rural Livelihoods Mission) in India. Various scenarios examining the economic sustainability and livelihood diversification of poor women in rural areas were performed using the FCM-based simulation process implemented by the “FCMWizard” tool. The objective of this study was three-fold: (i) to perform a brief comparative analysis between the proposed aggregation method called “OWA learning aggregation” and the conventional average aggregation method, (ii) to identify the significant concepts and their impact on the examined FCM model regarding poverty alleviation, and (iii) to advance the knowledge of circular economy in the context of poverty alleviation. Overall, the proposed method can support policymakers in eliciting accurate outcomes of proposed policies that deal with social resilience and sustainable socio-economic development strategies.