bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Soft Nanocarriers Combining Hyaluronic Acid with Another Functional Polymer for Cancer Therapy and Other Biomedical Applications
Authors: Rippe Marlène , Cosenza Vanina , Auzély-Velty Rachel
Published: July 2019

The rapid advancement in medicine requires the search for new drugs, but also for new carrier systems for more efficient and targeted delivery of the bioactive molecules. Among the latter, polymeric nanocarriers have an increasingly growing potential for clinical applications due to their unique physical and chemical characteristics. In this regard, nanosystems based on hyaluronic acid (HA), a polysaccharide which is ubiquitous in the body, have attracted particular interest because of the biocompatibility, biodegradability and nonimmunogenic property provided by HA. Furthermore, the fact that hyaluronic acid can be recognized by cell surface receptors in tumor cells, makes it an ideal candidate for the targeted delivery of anticancer drugs. In this review, we compile a comprehensive overview of the different types of soft nanocarriers based on HA conjugated or complexed with another polymer: micelles, nanoparticles, nanogels and polymersomes. Emphasis is made on the properties of the polymers used as well as the synthetic approaches for obtaining the different HA-polymer systems. Fabrication, characterization and potential biomedical applications of the nanocarriers will also be described.
Supercritical Solvent Impregnation of Different Drugs in Mesoporous Nanostructured ZnO
Authors: Banchero Mauro , Mohamed Sara S. Y. , Leone Federica , Lopez Francesca , Ronchetti Silvia , Manna Luigi , Onida Barbara
Published: July 2019

Supercritical solvent impregnation (SSI) is a green unconventional technique for preparing amorphous drug formulations. A mesoporous nanostructured ZnO (mesoNsZnO) carrier with 8-nm pores, spherical-nanoparticle morphology, and an SSA of 75 m2/g has been synthesized and, for the first time, subjected to SSI with poorly water-soluble drugs. Ibuprofen (IBU), clotrimazole (CTZ), and hydrocortisone (HC) were selected as highly, moderately, and poorly CO2-soluble drugs. Powder X-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, nitrogen adsorption analysis, and ethanol extraction coupled with ultraviolet spectroscopy were employed to characterize the samples and quantify drug loading. Successful results were obtained with IBU and CTZ while HC loading was negligible, which could be related to different solubilities in CO2, drug size, and polarity. Successful SSI resulted in amorphous multilayer confinement of the drug. The mesoNsZnO-IBU system showed double drug loading than the mesoNsZnO-CTZ one, with a maximum uptake of 0.24 g/g. Variation of contact time during SSI of the mesoNsZnO-IBU system showed that drug loading triplicated between 3 and 8 h with an additional 30% increment between 8 h and 24 h. SSI did not affect the mesoNsZnO structure, and the presence of the adsorbed drug reduced the chemisorption of CO2 on the carrier surface.
An ImmunoPEGliposome for Targeted Antimalarial Combination Therapy at the Nanoscale
Authors: Biosca Arnau , Dirscherl Lorin , Moles Ernest , Imperial Santiago , Fernàndez-Busquets Xavier
Published: July 2019

Combination therapies, where two drugs acting through different mechanisms are administered simultaneously, are one of the most efficient approaches currently used to treat malaria infections. However, the different pharmacokinetic profiles often exhibited by the combined drugs tend to decrease treatment efficacy as the compounds are usually eliminated from the circulation at different rates. To circumvent this obstacle, we have engineered an immunoliposomal nanovector encapsulating hydrophilic and lipophilic compounds in its lumen and lipid bilayer, respectively. The antimalarial domiphen bromide has been encapsulated in the liposome membrane with good efficiency, although its high IC50 of ca. 1 µM for living parasites complicates its use as immunoliposomal therapy due to erythrocyte agglutination. The conjugation of antibodies against glycophorin A targeted the nanocarriers to Plasmodium-infected red blood cells and to gametocytes, the sole malaria parasite stage responsible for the transmission from the human to the mosquito vector. The antimalarials pyronaridine and atovaquone, which block the development of gametocytes, have been co-encapsulated in glycophorin A-targeted immunoliposomes. The co-immunoliposomized drugs have activities significantly higher than their free forms when tested in in vitro Plasmodium falciparum cultures: Pyronaridine and atovaquone concentrations that, when encapsulated in immunoliposomes, resulted in a 50% inhibition of parasite growth had no effect on the viability of the pathogen when used as free drugs.
Reinforcement of the Framework for Experiential Education in Healthcare in Serbia: Post-Implementation Project Review within Pharmacy Education
Authors: Odalović Marina , Parojčić Jelena , Vasiljević Dragana , Đukić Ćosić Danijela , Tasić Ljiljana
Published: July 2019

Background: The Erasmus+ project “Reinforcement of the Framework for Experiential Education in Healthcare in Serbia” (ReFEEHS) has been undertaken with the aim to: (i) reinforce and modernize experiential education (ExEd) in the health sciences curricula, (ii) introduce interprofessional education (IPE), and (iii) promote teaching competency development of academic staff and teacher practitioners/clinician educators. The aim of this paper is a post-implementation review of the project activities and outcomes with the emphasis on the impact and sustainability in pharmacy education. Methods: Project Logical framework matrix has been employed as planning, monitoring and evaluation tool which summarizes the main project objectives, project outcomes, relevant activities, indicators of progress, sources of verification, assumptions and risks. Results: The key project outcomes are: (i) update of competency-based curricula and development of quality assurance framework for students professional practice placements; (ii) development and introduction of interprofessional teaching and learning activities through joint curriculum delivery; and (iii) development and implementation of Teaching Certificate in Health Professions Education (TCinHPE) study program. The short-term impact of project activities and outcomes has been assessed based on the feedback received from relevant stakeholders, as well as self-evaluation of participants enrolled in new/updated curricula. Sustainability of project results is necessary in order to achieve long-term impact envisioned as increased level of professional competency of health science students; increased level of teaching competency of academic staff and teacher practitioners; improved patient healthcare and harmonisation with the EU practice and policies. Conclusions: The project outcomes contributed to building capacity at the Serbian universities involved in terms of collaboration between the healthcare professions and, in curriculum and academic staff development. It is expected that improved curricula will positively impact professional competency development of pharmacy students, graduates employability and increased workforce mobility. Meeting the quality standards of the European Higher Education Area will contribute to visibility of Serbian universities and their internationalisation, which is one of the strategic aims of improvement.
One-Step Synthesis of Silver Nanoparticles Embedded Polyurethane Nano-Fiber/Net Structured Membrane as an Effective Antibacterial Medium
Authors: Pant Bishweshwar , Park Mira , Park Soo-Jin
Published: July 2019

A new and straightforward route was proposed to incorporate silver nanoparticles (Ag NPs) into the surface of polyurethane nanofibers (PU NFs). Uniform distribution of in situ formed Ag NPs on the surface of PU NFs was achieved by adding AgNO3 and tannic acid in a PU solution prior to the electrospinning process. The synthesized nanofiber mats were characterized with state-of-the-art techniques and antibacterial performances were tested against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The cytocompatibility and cell behavior were studied by using fibroblast cells. Following this preparation route, Ag/PU NFs can be obtained with excellent antibacterial performance, thus making them appropriate for various applications such as water filtration, wound dressings, etc.
Antibacterial Activity and Cytotoxicity of Immobilized Glucosamine/Chondroitin Sulfate on Polylactic Acid Films
Authors: Karakurt Ilkay , Ozaltin Kadir , Vesela Daniela , Lehocky Marian , Humpolíček Petr , Mozetič Miran
Published: July 2019

Polylactic acid (PLA) is one of the most produced polymeric materials, due to its exceptional chemical and mechanical properties. Some of them, such as biodegradability and biocompatibility, make them attractive for biomedical applications. Conversely, the major drawback of PLA in the biomedical field is their vulnerability to bacterial contamination. This study focuses on the immobilization of saccharides onto the PLA surface by a multistep approach, with the aim of providing antibacterial features and evaluting the synergistic effect of these saccharides. In this approach, after poly (acrylic acid) (PAA) brushes attached non-covalently to the PLA surface via plasma post-irradiation grafting technique, immobilization of glucosamine (GlcN) and chondroitin sulfate (ChS) to the PAA brushes was carried out. To understand the changes in surface properties, such as chemical composition, surface topography and hydrophilicity, the untreated and treated PLA films were analyzed using various characterization techniques (contact angle, scanning electron microscopy, X-ray photoelectron spectroscopy). In vitro cytotoxicity assays were investigated by the methyl tetrazolium test. The antibacterial activity of the PLA samples was tested against Escherichia coli and Staphylococcus aureus bacteria strains. Plasma-treated films immobilized with ChS and GlcN, separately and in combination, demonstrated bactericidal effect against the both bacteria strains and also the results revealed that the combination has no synergistic effect on antibacterial action.
Characterization of Double-Doped Polymer Optical Fibers as Luminescent Solar Concentrators
Authors: Parola Itxaso , Illarramendi M. Asuncion , Jakobs Florian , Kielhorn Jana , Zaremba Daniel , Johannes Hans-Hermann , Zubia Joseba
Published: July 2019

This work reports on a diameter dependence analysis of the performance as luminescent solar concentrators of three self-fabricated polymer optical fibers (POFs) doped with a hybrid combination of dopants. The works carried out include the design and self-fabrication of the different diameter fibers; an experimental analysis of the output power, of the output irradiance and of the fluorescent fiber solar concentrator efficiency; a comparison of the experimental results with a theoretical model; a study of the performance of all the fibers under different simulated lighting conditions; and a calculation of the active fiber length of each of the samples, all of them as a function of the fiber core diameter. To the best of our knowledge, this paper reports the first analysis of the influence of the POF diameter for luminescent solar concentration applications. The results obtained offer a general perspective on the optimal design of solar energy concentrating systems based on doped POFs and pave the way for the implementation of cost-effective solar energy concentrating devices.
Plasma Nanocoatings Developed to Control the Shear Strength of Polymer Composites
Authors: Zvonek Milan , Sirjovova Veronika , Branecky Martin , Plichta Tomas , Skacel Josef , Cech Vladimir
Published: July 2019

All reinforcements for polymer-matrix composites must be coated with a suitable material in the form of a thin film to improve compatibility and interfacial adhesion between the reinforcement and the polymer matrix. In this study, plasma nanotechnology was used to synthetize such functional nanocoatings using pure tetravinylsilane (TVS) and its mixtures with oxygen gas (O2) as precursors. The plasma-coated glass fibers (GFs) were unidirectionally embedded in a polyester resin to produce short composite beams that were analyzed by a short-beam-shear test to determine the shear strength characterizing the functionality of the nanocoatings in a GF/polyester composite. The developed plasma nanocoatings allowed controlling the shear strength between 26.2–44.1 MPa depending on deposition conditions, i.e., the radiofrequency (RF) power and the oxygen fraction in the TVS/O2 mixture. This range of shear strength appears to be sufficiently broad to be used in the design of composites.
Lanthanum Effect on Ni/Al2O3 as a Catalyst Applied in Steam Reforming of Glycerol for Hydrogen Production
Authors: Sánchez Nuria , Encinar José María , Nogales Sergio , González Juan Félix
Published: July 2019

Nowadays, the massive production of biodiesel leads to a surplus of glycerol. Thus, new applications of this by-product are being developed. In this study, glycerol steam reforming was carried out with Ni catalysts supported on Al2O3 rings and La-modified Al2O3. The catalysts were characterized by N2 physical adsorption, X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, and thermogravimetry. Both catalysts were effective in glycerol steam reforming. However, Ni/Al2O3 activity decreased over reaction time. Ni/La2O3/Al2O3 showed the best stability during the reaction. In addition, the activity of the modified support, La2O3/Al2O3, was evaluated. The modification of the support lent catalytic properties to the solid. Some conditions such as catalyst arrangement (catalyst in the first or second reactor), space velocity, and reaction temperature were studied. The highest hydrogen production was obtained when half the amount of the catalyst was located in both reactors. Glycerol conversion into gases was similar, regardless the space velocity, although higher amounts of H2 were obtained when this variable decreased. Complete glycerol conversion into gases was obtained at 900 and 1000 °C, and hydrogen production reached a H2/glycerol molar ratio of 5.6. Finally, the presence of the catalyst and the optimization of these conditions increased the energy capacity of the produced stream.
Discrete-Time Kalman Filter Design for Linear Infinite-Dimensional Systems
Authors: Xie Junyao , Dubljevic Stevan
Published: July 2019

As the optimal linear filter and estimator, the Kalman filter has been extensively utilized for state estimation and prediction in the realm of lumped parameter systems. However, the dynamics of complex industrial systems often vary in both spatial and temporal domains, which take the forms of partial differential equations (PDEs) and/or delay equations. State estimation for these systems is quite challenging due to the mathematical complexity. This work addresses discrete-time Kalman filter design and realization for linear distributed parameter systems. In particular, the structural- and energy-preserving Crank–Nicolson framework is applied for model time discretization without spatial approximation or model order reduction. In order to ensure the time instance consistency in Kalman filter design, a new discrete model configuration is derived. To verify the feasibility of the proposed design, two widely-used PDEs models are considered, i.e., a pipeline hydraulic model and a 1D boundary damped wave equation.
Mathematical Modelling Forecast on the Idling Transient Characteristic of Reactor Coolant Pump
Authors: Wang Xiuli , Xie Yajie , Lu Yonggang , Zhu Rongsheng , Fu Qiang , Cai Zheng , An Ce
Published: July 2019

The idling behavior of the reactor coolant pump is referred to as an important indicator of the safe operation of the nuclear power system, while the idling transition process under the power failure accident condition is developed as a transient flow process. In this process, the parameters such as the flow rate, speed, and head of the reactor coolant pump are all nonlinear changes. In order to ensure the optimal idling behavior of the reactor coolant pump under the power cutoff accident condition, this manuscript takes the guide vanes of the AP1000 reactor coolant pump as the subject of this study. In this paper, the mathematical model of idling speed and flow characteristic curve of reactor coolant pump under the power failure condition were proposed, while the hydraulic modeling database of different vane structure parameters was modeled based on the orthogonal optimization schemes. Furthermore, based on the mathematical modeling framework of multiple linear regressions, the mathematical relationship of the hydraulic performance of each guide vane in different parameters was predicted. The derived model was verified with the idling test data.
An Improved Hatch Filter Algorithm towards Sub-Meter Positioning Using only Android Raw GNSS Measurements without External Augmentation Corrections
Authors: Geng Jianghui , Jiang Enming , Li Guangcai , Xin Shaoming , Wei Na
Published: July 2019

In May 2016, the availability of GNSS raw measurements on smart devices was announced by Google with the release of Android 7. It means that developers can access carrier-phase and pseudorange measurements and decode navigation messages for the first time from mass-market Android-devices. In this paper, an improved Hatch filter algorithm, i.e., Three-Thresholds and Single-Difference Hatch filter (TT-SD Hatch filter), is proposed for sub-meter single point positioning with raw GNSS measurements on Android devices without any augmentation correction input, where the carrier-phase smoothed pseudorange window width adaptively varies according to the three-threshold detection for ionospheric cumulative errors, cycle slips and outliers. In the mean time, it can also eliminate the inconsistency of receiver clock bias between pseudorange and carrier-phase by inter-satellite difference. To eliminate the effects of frequent smoothing window resets, we combine TT-SD Hatch filter and Kalman filter for both time update and measurement update. The feasibility of the improved TT-SD Hatch filter method is then verified using static and kinematic experiments with a Nexus 9 Android tablet. The result of the static experiment demonstrates that the position RMS of TT-SD Hatch filter is about 0.6 and 0.8 m in the horizontal and vertical components, respectively. It is about 2 and 1.6 m less than the GNSS chipset solutions, and about 10 and 10 m less than the classical Hatch filter solution, respectively. Moreover, the TT-SD Hatch filter can accurately detect the cycle slips and outliers, and reset the smoothed window in time. It thus avoids the smoothing failure of Hatch filter when a large cycle-slip or an outlier occurs in the observations. Meanwhile, with the aid of the Kalman filter, TT-SD Hatch filter can keep continuously positioning at the sub-meter level. The result of the kinematic experiment demonstrates that the TT-SD Hatch filter solution can converge after a few minutes, and the 2D error is about 0.9 m, which is about 64%, 89%, and 92% smaller than that of the chipset solution, the traditional Hatch filter solution and standard single point solution, respectively. Finally, the TT-SD Hatch filter solution can recover a continuous driving track in this kinematic test.
A Semi-empirical Approach Based on Genetic Programming for the Study of Biophysical Controls on Diameter-Growth of Fagus orientalis in Northern Iran
Authors: Bayat Mahmoud , Thanh Noi Phan , Zare Rozita , Tien Bui Dieu
Published: July 2019

This paper examines the possible ecological controls on the diameter increment of oriental beech (Fagus orientalis Lipsky) in a high altitude forest in northern Iran. The main objectives of the study are computer-generated abiotic surfaces and associated plot estimates of (i) growing-season-cumulated potential solar radiation, (ii) seasonal air temperature, (iii) topographic wetness index in representing soil water distribution, and (iv) wind velocity generated from the simulation of fluid-flow dynamics in complex terrain. Plot estimates of the tree growth are based on averaged plot measurements of diameter at breast height increment during a growing period of nine years (2003–2012). Biotic variables related to the tree diameter increment involve averaged 2003 tree diameter and basal area measured in individual forest plots. In the modelling data (144 plots), the assemblage of modelled and observed site variables explained 75% of the variance in plot-level diameter increment. In the validation data (32 plots), the degree of explained variance was 77%. Mean tree diameter at breast height showed the strongest correlation with diameter increment, explaining 32% of the variation between-plot, followed by the configuration of topography and re-distribution of surface water (19.5%) and plot basal area (16.9%). On average, localised estimates of solar radiation and wind velocity potentially contribute to about 20% of the control on plot-level mean increment in oriental beech of the area. The results of the genetic programming showed that controlling the stand basal area and tree size by thinning and/or selective harvesting can have a favourable impact on the future distribution of mean diameter in oriental beech.
Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security
Authors: Derhab Abdelouahid , Guerroumi Mohamed , Gumaei Abdu , Maglaras Leandros , Ferrag Mohamed Amine , Mukherjee Mithun , Khan Farrukh Aslam
Published: July 2019

The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be adopted. In this paper, we focus on the security of commands in industrial IoT against forged commands and misrouting of commands. To this end, we propose a security architecture that integrates the Blockchain and the Software-defined network (SDN) technologies. The proposed security architecture is composed of: (a) an intrusion detection system, namely RSL-KNN, which combines the Random Subspace Learning (RSL) and K-Nearest Neighbor (KNN) to defend against the forged commands, which target the industrial control process, and (b) a Blockchain-based Integrity Checking System (BICS), which can prevent the misrouting attack, which tampers with the OpenFlow rules of the SDN-enabled industrial IoT systems. We test the proposed security solution on an Industrial Control System Cyber attack Dataset and on an experimental platform combining software-defined networking and blockchain technologies. The evaluation results demonstrate the effectiveness and efficiency of the proposed security solution.
SASRT: Semantic-Aware Super-Resolution Transmission for Adaptive Video Streaming over Wireless Multimedia Sensor Networks
Authors: Guo Jia , Gong Xiangyang , Wang Wendong , Que Xirong , Liu Jingyu
Published: July 2019

There are few network resources in wireless multimedia sensor networks (WMSNs). Compressing media data can reduce the reliance of user’s Quality of Experience (QoE) on network resources. Existing video coding software, such as H.264 and H.265, focuses only on spatial and short-term information redundancy. However, video usually contains redundancy over a long period of time. Therefore, compressing video information redundancy with a long period of time without compromising the user experience and adaptive delivery is a challenge in WMSNs. In this paper, a semantic-aware super-resolution transmission for adaptive video streaming system (SASRT) for WMSNs is presented. In the SASRT, some deep learning algorithms are used to extract video semantic information and enrich the video quality. On the multimedia sensor, different bit-rate semantic information and video data are encoded and uploaded to user. Semantic information can also be identified on the user side, further reducing the amount of data that needs to be transferred. However, identifying semantic information on the user side may increase the computational cost of the user side. On the user side, video quality is enriched with super-resolution technologies. The major challenges faced by SASRT include where the semantic information is identified, how to choose the bit rates of semantic and video information, and how network resources should be allocated to video and semantic information. The optimization problem is formulated as a complexity-constrained nonlinear NP-hard problem. Three adaptive strategies and a heuristic algorithm are proposed to solve the optimization problem. Simulation results demonstrate that SASRT can compress video information redundancy with a long period of time effectively and enrich the user experience with limited network resources while simultaneously improving the utilization of these network resources.
A Virtual In-Cylinder Pressure Sensor Based on EKF and Frequency-Amplitude-Modulation Fourier-Series Method
Authors: Wang Qiming , Sun Tao , Lyu Zhichao , Gao Dawei
Published: July 2019

As a crucial and critical factor in monitoring the internal state of an engine, cylinder pressure is mainly used to monitor the burning efficiency, to detect engine faults, and to compute engine dynamics. Although the intrusive type cylinder pressure sensor has been greatly improved, it has been criticized by researchers for high cost, low reliability and short life due to severe working environments. Therefore, aimed at low-cost, real-time, non-invasive, and high-accuracy, this paper presents the cylinder pressure identification method also called a virtual cylinder pressure sensor, involving Frequency-Amplitude Modulated Fourier Series (FAMFS) and Extended-Kalman-Filter-optimized (EKF) engine model. This paper establishes an iterative speed model based on burning theory and Law of energy Conservation. Efficiency coefficient is used to represent operating state of engine from fuel to motion. The iterative speed model associated with the throttle opening value and the crankshaft load. The EKF is used to estimate the optimal output of this iteration model. The optimal output of the speed iteration model is utilized to separately compute the frequency and amplitude of the cylinder pressure cycle-to-cycle. A standard engine’s working cycle, identified by the 24th order Fourier series, is determined. Using frequency and amplitude obtained from the iteration model to modulate the Fourier series yields a complete pressure model. A commercial engine (EA211) provided by the China FAW Group corporate R&D center is used to verify the method. Test results show that this novel method possesses high accuracy and real-time capability, with an error percentage for speed below 9.6% and the cumulative error percentage of cylinder pressure less than 1.8% when A/F Ratio coefficient is setup at 0.85. Error percentage for speed below 1.7% and the cumulative error percentage of cylinder pressure no more than 1.4% when A/F Ratio coefficient is setup at 0.95. Thus, the novel method’s accuracy and feasibility are verified.
Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition
Authors: Zou Yingquan , Chen Yunpeng , Liu Peng
Published: July 2019

Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and time domain integration, according to the vibration signal traits of a bridge. Through simulating bridge analog signals and verifying a vibration test bench, four bridge dynamic displacement monitoring methods were analyzed and compared. The proposed method can effectively eliminate the influence of low-frequency integral drift and high-frequency ambient noise on the integration process. Furthermore, this algorithm has better adaptability and robustness. The effectiveness of the method was verified by field experiments on highway elevated bridges.
A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G
Authors: Usama Muhammad , Erol-Kantarci Melike
Published: July 2019

The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world’s energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues.
Deep CNN for Indoor Localization in IoT-Sensor Systems
Authors: Njima Wafa , Ahriz Iness , Zayani Rafik , Terre Michel , Bouallegue Ridha
Published: July 2019

Currently, indoor localization is among the most challenging issues related to the Internet of Things (IoT). Most of the state-of-the-art indoor localization solutions require a high computational complexity to achieve a satisfying localization accuracy and do not meet the memory limitations of IoT devices. In this paper, we develop a localization framework that shifts the online prediction complexity to an offline preprocessing step, based on Convolutional Neural Networks (CNN). Motivated by the outstanding performance of such networks in the image classification field, the indoor localization problem is formulated as 3D radio image-based region recognition. It aims to localize a sensor node accurately by determining its location region. 3D radio images are constructed based on Received Signal Strength Indicator (RSSI) fingerprints. The simulation results justify the choice of the different parameters, optimization algorithms, and model architectures used. Considering the trade-off between localization accuracy and computational complexity, our proposed method outperforms other popular approaches.
On Mautner-Type Probability of Capture of Intergalactic Meteor Particles by Habitable Exoplanets
Authors: Kovačević Andjelka B.
Published: July 2019

Both macro and microprojectiles (e.g., interplanetary, interstellar and even intergalactic material) are seen as an important vehicle for the exchange of (bio)material within our solar system as well as between stellar systems in our Galaxy. Accordingly, this requires estimates of the impact probabilities for different source populations of projectiles, specifically for intergalactic meteor particles which have received relatively little attention since considered as rare events (discrete occurrences that are statistically improbable due to their very infrequent appearance). We employ the simple but yet comprehensive model of intergalactic microprojectile capture by the gravity of exoplanets which enables us to estimate the map of collisional probabilities for an available sample of exoplanets in habitable zones around host stars. The model includes a dynamical description of the caption adopted from Mautner model of interstellar exchange of microparticles and changed for our purposes. We use statistical and information metrics to calculate probability map of intergalactic meteorite particle capture. Moreover, by calculating the entropy index map we measure the concentration of these rare events. By adopting a model from immigration theory, we show that the transient distribution of birth/death/immigration of material for the simplest case has a high value.
Tourism-Based Circular Economy in Salento (South Italy): A SWOT-ANP Analysis
Authors: Falcone Pasquale Marcello
Published: July 2019

This paper is aimed at eliciting, by means of a multi-level perspective, potential drivers and barriers of the tourism industry in order to generate valuable information for policy makers to improve policy strategies for an effective transition towards sustainability. A Strengths, Weaknesses, Opportunities and Threats–Analytic Network Process (SWOT-ANP) framework was employed to explore the potential development of a second-generation biorefinery in Salento (a touristic area located in the southeast of Italy in Apulia Region) able to integrate waste management, renewable energy and bio-products production based on resource circularity in the tourism industry. Results indicate that survey participants recognized a higher level of priority for the pressures coming from the overall external setting involving values, dominant practices, rules and technologies (landscape and regime) over the internal tourism industry dynamics (niche). Results also show that the top five ranked factors are mainly pertaining to weaknesses (excessive bureaucracy and lack of technology and infrastructure) and threats (social acceptability and lack of long-term planning by governments), which can concretely jeopardize the transition towards a greater sustainability in the investigated area. The analysis presented constitutes a valuable model for agenda setting in order to find adequate policy actions to promote the transition.
Towards a Sustainable Nutrition Paradigm in Physique Sport: A Narrative Review
Authors: Helms Eric R. , Prnjak Katarina , Linardon Jake
Published: July 2019

Physique athletes strive for low body fat with high lean mass and have higher body image and eating disorder rates than the general population, and even other weightlifting populations. Whether athletes with a background or tendency to develop these issues are drawn to the sport, or whether it drives these higher incidences, is unknown. However, the biological drive of cyclical energy restriction may contribute to binge-eating behavior. Additionally, requisite monitoring, manipulation, comparison, and judgement of one’s physique may contribute to body image concerns. Contest preparation necessitates manipulating body composition through energy restriction and increased expenditure, requiring dietary restraint and nutrition, exercise, and physique assessment. Thus, competitors are at mental health risk due to (1) pre-existing or predispositions to develop body image or eating disorders; (2) biological effects of energy restriction on eating psychology; and (3) dietary restraint attitudes and resultant physique, exercise, and nutrition monitoring behavior. In our narrative review we cover each factor, concluding with tentative best-practice recommendations, including dietary flexibility, slower weight loss, structured monitoring, gradual returns to offseason energy intakes, internal eating cues, appropriate offseason body compositions, and support from nutrition and mental health professionals. A mental health focus is a needed paradigm shift in bodybuilding nutrition practice and research.
Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach
Authors: Bányai Tamás , Illés Béla , Gubán Miklós , Gubán Ákos , Schenk Fabian , Bányai Ágota
Published: July 2019

The just-in-sequence inventory strategy, as an important part of the supply chain solutions in the automotive industry, is based on feedback information from the manufacturer. The performance, reliability, availability and cost efficiency are based on the parameters of the members of the supply chain process. To increase the return on assets (ROA) of the manufacturer, the optimization of the supply process is unavoidable. Within the frame of this paper, the authors describe a flower pollination algorithm-based heuristic optimization model of just-in-sequence supply focusing on sustainability aspects, including fuel consumption and emission. After a systematic literature review, this paper introduces a mathematical model of just-in-sequence supply, including assignment and scheduling problems. The objective of the model is to determine the optimal assignment and schedule for each sequence to minimize the total purchasing cost, which allows improving cost efficiency while sustainability aspects are taken into consideration. Next, a flower pollination algorithm-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase cost-efficiency in just-in-sequence solutions.
Work and Social-Ecological Transitions: A Critical Review of Five Contrasting Approaches
Authors: Bottazzi Patrick
Published: July 2019

Going to work has become such a ritualized activity for the modern human that few people challenge its relevance from a sustainability perspective. Since the Industrial Revolution, the prospect of unlimited growth with the aim of jobs creation has been dramatically associated with a massive social-ecological degradation that puts the Earth system at risk. In recent decades, a number of heterodox theories and policies are reconsidering our relationship with work in view of contemporaneous social-ecological challenges. This paper offers critical review of five contrasting approaches. Those promoting ‘green jobs’ consider the possibility of transforming ecological constraints into economic opportunities by incentivising eco-efficient innovations and generating new jobs. Conversely, critical approaches, such as working-time reduction (WTR), labour environmentalism, political ecology of work, and contributive economy and justice, defend decommodifying work to liberate pro-social and pro-environmental behaviours. We additionally present two opposing scenarios mainly inspired by critical theories. One illustrates the root causes of systemic lock-in leading to the present social-ecological work-life degradation, while the other illustrates perspectives on the ‘politics of free time’ and contributive economy and justice oriented towards building capabilities, and workers’ emancipation and justice in search for more sustainable relationships with ecosystems.
The Potential Use of Microorganisms as Restorative Agents: An Update
Authors: Soffritti Irene , D’Accolti Maria , Lanzoni Luca , Volta Antonella , Bisi Matteo , Mazzacane Sante , Caselli Elisabetta
Published: July 2019

The biodeterioration process involves every type of Cultural Heritage item, including monuments, stoneworks, frescoes, and easel paintings. The accurate study of the microbial and fungal communities dwelling on artworks, and involved in their deterioration, is essential for the adoption of optimal prevention and conservation strategies. Conventional restorative methods, that usually involve chemical and physical technologies, present some disadvantages, including short-term and unsatisfactory effects, potential damage to the treated works, human toxicity, and environmental hazards. Research in the field of restoration has paved the way for innovative biological approaches, or ‘biorestoration’, in which microorganisms are not only considered as an eventual danger for artworks, but rather as potential tools for restoration. The present review describes the main aspects of the biodeterioration process and highlights the most relevant biorestoration approaches: bioconsolidation, biocleaning, biological control, and new promising bio-decontaminating compounds.
Residents’ Opinions and Perceptions of Tourism Development in the Historic City of Toledo, Spain
Authors: Escudero Gómez Luis Alfonso
Published: July 2019

Historic centers have become first-line tourist destinations. In order to achieve sustainable development, it is essential to get to know the opinions of the host community on the impact of tourism, the positives, as well as the negatives. This paper aims to understand the residents’ opinions and perceptions of destinations as the historic cities. This research looks into the residents’ opinions on the impact of tourism in the historic city of Toledo, Spain. The results of a quantitative survey among 442 residents in the city of Toledo are presented. The study is a revision of the literature and analysis and explanation of an empiric study’s results. Descriptive statistics have been used, as well as factor analysis and non-parametric tests to analyze data. The main results point out that residents have a positive vision of tourism development, rather than negative. The economic importance of tourism and its ability to create jobs stand out. However, they also think that the historic center is being turned into a museum for tourists. Analyzing their opinions according to certain demographic and socioeconomic characteristics, some major differences come up, such as that the inhabitants of residential areas have a more positive opinion than those who live in the historic center. Understanding the perspective of the residents can help the managers and planners of the tourism in the city to play down the potential negative impact of tourism and to achieve support from the host community in regards to tourism.
Internet Finance, Green Finance, and Sustainability
Authors: Wang Kai , Tsai Sang-Bing , Du Xiaomin , Bi Datian
Published: July 2019

This special issue, “Internet Finance, Green Finance, and Sustainability”, is focused on the prosperous financial industry and the relationship between finance and sustainability. It especially gathers papers pertaining to the hot topic of internet finance and green finance in this field, as well as the manuscripts exploring the operating mechanism between finance and sustainability, both of which are closely linked to the hot spots and pressing demands of society. Therefore, this special issue is of particular valuable for both academic research and the development of society.
Fake Bitrate Detection of HEVC Videos Based on Prediction Process
Authors: Liang Xiaoyun , Li Zhaohong , Li Zhonghao , Zhang Zhenzhen
Published: July 2019

In order to defraud click-through rate, some merchants recompress the low-bitrate video to a high-bitrate one without improving the video quality. This behavior deceives viewers and wastes network resources. Therefore, a stable algorithm that detects fake bitrate videos is urgently needed. High-Efficiency Video Coding (HEVC) is a worldwide popular video coding standard. Hence, in this paper, a robust algorithm is proposed to detect HEVC fake bitrate videos. Firstly, five effective feature sets are extracted from the prediction process of HEVC, including Coding Unit of I-picture/P-picture partitioning modes, Prediction Unit of I-picture/P-picture partitioning modes, Intra Prediction Modes of I-picture. Secondly, feature concatenation is adopted to enhance the expressiveness and improve the effectiveness of the features. Finally, five single feature sets and three concatenate feature sets are separately sent to the support vector machine for modeling and testing. The performance of the proposed algorithm is compared with state-of-the-art algorithms on HEVC videos of various resolutions and fake bitrates. The results show that the proposed algorithm can not only can better detect HEVC fake bitrate videos, but also has strong robustness against frame deletion, copy-paste, and shifted Group of Picture structure attacks.
The Influence of a Network’s Spatial Symmetry, Topological Dimension, and Density on Its Percolation Threshold
Authors: Zhukov Dmitry O. , Andrianova Elena G. , Lesko Sergey A.
Published: July 2019

Analyses of the processes of information transfer within network structures shows that the conductivity and percolation threshold of the network depend not only on its density (average number of links per node), but also on its spatial symmetry groups and topological dimension. The results presented in this paper regarding conductivity simulation in network structures show that, for regular and random 2D and 3D networks, an increase in the number of links (density) per node reduces their percolation threshold value. At the same network density, the percolation threshold value is less for 3D than for 2D networks, whatever their structure and symmetry may be. Regardless of the type of networks and their symmetry, transition from 2D to 3D structures engenders a change of percolation threshold by a value exp{−(d − 1)} that is invariant for transition between structures, for any kind of network (d being topological dimension). It is observed that in 2D or 3D networks, which can be mutually transformed by deformation without breaking and forming new links, symmetry of similarity is observed, and the networks have the same percolation threshold. The presence of symmetry axes and corresponding number of symmetry planes in which they lie affects the percolation threshold value. For transition between orders of symmetry axes, in the presence of the corresponding planes of symmetry, an invariant exists which contributes to the percolation threshold value. Inversion centers also influence the value of the percolation threshold. Moreover, the greater the number of pairs of elements of the structure which have inversion, the more they contribute to the fraction of the percolation threshold in the presence of such a center of symmetry. However, if the center of symmetry lies in the plane of mirror symmetry separating the layers of the 3D structure, the mutual presence of this group of symmetry elements do not affect the percolation threshold value. The scientific novelty of the obtained results is that for different network structures, it was shown that the percolation threshold for the blocking of nodes problem could be represented as an additive set of invariant values, that is, as an algebraic sum, the value of the members of which is stored in the transition from one structure to another. The invariant values are network density, topological dimension, and some of the elements of symmetry (axes of symmetry and the corresponding number of symmetry planes in which they lie, centers of inversion).
Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin: Application of MARSplines and Descriptors Encoded in SMILES String
Authors: Cysewski Piotr , Przybyłek Maciej
Published: July 2019

The quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression equations consisting of new non-linear components (basis functions) being combinations of molecular descriptors. The model was subjected to the standard internal and external validation procedures, which indicated its high predictive power. The appearance of polarity-related descriptors, such as XlogP, confirms the hydrophobic nature of the cyclodextrin cavity. The model can be used for predicting the affinity of new ligands to β-CD. However, a non-standard application was also proposed for classification into Biopharmaceutical Classification System (BCS) drug types. It was found that a single parameter, which is the estimated value of lnK, is sufficient to distinguish highly permeable drugs (BCS class I and II) from low permeable ones (BCS class II and IV). In general, it was found that drugs of the former group exhibit higher affinity to β-CD then the latter group (class III and IV).