bluuebunny/crossref_metadata_2025 huggingface dataset:
Expanding the Structural Diversity of DNA Methyltransferase Inhibitors
Authors: Juárez-Mercado K. Eurídice , Prieto-Martínez Fernando D. , Sánchez-Cruz Norberto , Peña-Castillo Andrea , Prada-Gracia Diego , Medina-Franco José L.
Published: December 2020

Inhibitors of DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug discovery. They are also chemical tools to understand the biochemistry of epigenetic processes. Herein, we report five distinct inhibitors of DNMT1 characterized in enzymatic inhibition assays that did not show activity with DNMT3B. It was concluded that the dietary component theaflavin is an inhibitor of DNMT1. Two additional novel inhibitors of DNMT1 are the approved drugs glyburide and panobinostat. The DNMT1 enzymatic inhibitory activity of panobinostat, a known pan inhibitor of histone deacetylases, agrees with experimental reports of its ability to reduce DNMT1 activity in liver cancer cell lines. Molecular docking of the active compounds with DNMT1, and re-scoring with the recently developed extended connectivity interaction features approach, led to an excellent agreement between the experimental IC50 values and docking scores.
The Positive and Negative Outcome of Morphine and Disulfiram Subacute Co-Administration in Rats in the Absence of Ethanol Challenge
Authors: Frączek Karolina , Kowalczyk Agnieszka , Pekala Martyna , Kasarello Kaja , Sygitowicz Grażyna , Sulejczak Dorota , Zaremba Malgorzata , Konop Marek , Frankowska Malgorzata , Filip Malgorzata , Bujalska-Zadrozny Magdalena , Kleczkowska Patrycja
Published: December 2020

Recently, a well-known anti-alcohol agent, disulfiram (DSF), has gain much interest, as it was found to be effective in the treatment of cocaine abusers, thus also giving hope for patients addicted to opioids and other illicit drugs. Therefore, this study was aimed to investigate the possible outcome that might occur within the subacute co-administration of both morphine (MRF) and DSF in rats, but in the absence of ethanol challenge. As observed, intraperitoneal DSF dose-dependently enhanced MRF-mediated analgesia with the maximal efficacy at a dose of 100 mg/kg. Furthermore, MRF-induced tolerance and aggressive behavior were significantly reduced by DSF (100 mg/kg, i.p.) in comparison to MRF solely. Nonetheless, significant blood biochemical markers of hepatotoxicity were found (i.e., alteration in the levels of glutathione, blood urea nitrogen, etc.), following a combination of both drugs. Likewise, histological analysis of liver tissue revealed severe changes in the group of DSF + MRF, which includes swelling, cell death, damage to certain vessels, and hemorrhages into the liver parenchyma. Our findings indicate that DSF should be used with extreme caution, especially within the course of subacute concomitant use with MRF, as several possible side effects may take place.
Dry Powder for Pulmonary Delivery: A Comprehensive Review
Authors: Chaurasiya Birendra , Zhao You-Yang
Published: December 2020

The pulmonary route has long been used for drug administration for both local and systemic treatment. It possesses several advantages, which can be categorized into physiological, i.e., large surface area, thin epithelial membrane, highly vascularized, limited enzymatic activity, and patient convenience, i.e., non-invasive, self-administration over oral and systemic routes of drug administration. However, the formulation of dry powder for pulmonary delivery is often challenging due to restrictions on aerodynamic size and the lung’s lower tolerance capacity in comparison with an oral route of drug administration. Various physicochemical properties of dry powder play a major role in the aerosolization, deposition, and clearance along the respiratory tract. To prepare suitable particles with optimal physicochemical properties for inhalation, various manufacturing methods have been established. The most frequently used industrial methods are milling and spray-drying, while several other alternative methods such as spray-freeze-drying, supercritical fluid, non-wetting templates, inkjet-printing, thin-film freezing, and hot-melt extrusion methods are also utilized. The aim of this review is to provide an overview of the respiratory tract structure, particle deposition patterns, and possible drug-clearance mechanisms from the lungs. This review also includes the physicochemical properties of dry powder, various techniques used for the preparation of dry powders, and factors affecting the clinical efficacy, as well as various challenges that need to be addressed in the future.
Recent Advances in Functional Polymers Containing Coumarin Chromophores
Authors: Cazin Ines , Rossegger Elisabeth , Guedes de la Cruz Gema , Griesser Thomas , Schlögl Sandra
Published: December 2020

Natural and synthetic coumarin derivatives have gained increased attention in the design of functional polymers and polymer networks due to their unique optical, biological, and photochemical properties. This review provides a comprehensive overview over recent developments in macromolecular architecture and mainly covers examples from the literature published from 2004 to 2020. Along with a discussion on coumarin and its photochemical properties, we focus on polymers containing coumarin as a nonreactive moiety as well as polymer systems exploiting the dimerization and/or reversible nature of the [2πs + 2πs] cycloaddition reaction. Coumarin moieties undergo a reversible [2πs + 2πs] cycloaddition reaction upon irradiation with specific wavelengths in the UV region, which is applied to impart intrinsic healability, shape-memory, and reversible properties into polymers. In addition, coumarin chromophores are able to dimerize under the exposure to direct sunlight, which is a promising route for the synthesis and cross-linking of polymer systems under “green” and environment-friendly conditions. Along with the chemistry and design of coumarin functional polymers, we highlight various future application fields of coumarin containing polymers involving tissue engineering, drug delivery systems, soft robotics, or 4D printing applications.
Novel Semi-Interpenetrated Polymer Networks of Poly(3-Hydroxybutyrate-co-3-Hydroxyvalerate)/Poly (Vinyl Alcohol) with Incorporated Conductive Polypyrrole Nanoparticles
Authors: Aparicio-Collado José Luis , Novoa Juan José , Molina-Mateo José , Torregrosa-Cabanilles Constantino , Serrano-Aroca Ángel , Sabater i Serra Roser
Published: December 2020

This paper reports the preparation and characterization of semi-interpenetrating polymer networks (semi-IPN) of poly(3-hydroxybutirate-co-3-hydroxyvalerate), PHBV, and poly (vinyl alcohol), PVA, with conductive polypirrole (PPy) nanoparticles. Stable hybrid semi-IPN (PHBV/PVA 30/70 ratio) hydrogels were produced by solvent casting, dissolving each polymer in chloroform and 1-methyl-2-pyrrolidone respectively, and subsequent glutaraldehyde crosslinking of the PVA chains. The microstructure and physical properties of this novel polymeric system were analysed, including thermal behaviour and degradation, water sorption, wettability and electrical conductivity. The conductivity of these advanced networks rose significantly at higher PPy nanoparticles content. Fourier transform infrared spectroscopy (FTIR) and calorimetry characterization indicated good miscibility and compatibility between all the constituents, with no phase separation and strong interactions between phases. A single glass transition was observed between those of pure PHBV and PVA, although PVA was dominant in its contribution to the glass transition process. Incorporating PPy nanoparticles significantly reduced the hydrogel swelling, even at low concentrations, indicating molecular interactions between the PPy nanoparticles and the hydrogel matrix. The PHBV/PVA semi-IPN showed higher thermal stability than the neat polymers and PHBV/PVA blend, which also remained in the tertiary systems.
In Situ Surface-Initiated Atom-Transfer Radical Polymerization Utilizing the Nonvolatile Nature of Ionic Liquids: A First Attempt
Authors: Satoh Ryo , Honma Saika , Arafune Hiroyuki , Shomura Ryo , Kamijo Toshio , Morinaga Takashi , Sato Takaya
Published: December 2020

In this paper, in situ surface-initiated atom-transfer radical polymerization (SI-ATRP) based on both an open and a coated system, without using volatile reagents, was developed to overcome the limited usage of ATRP due to the necessity of sealing. Nonvolatile ionic liquid (IL)-type components were used, specifically N,N-diethyl-N-(2-methacryloylethyl)-N-methylammonium bis(trifluoromethylsulfonyl)imide as the polymerizable monomer and N,N-diethylmethyl(2-methoxyethyl)ammonium bis(trifluoromethylsulfonyl)imide as the polymerization solvent. In the experiment, the reversible-deactivation radical polymerization characteristics are properly ensured in nonvolatile ATRP solution coated on silicon wafer as thin liquid film, to form concentrated polymer brushes (CPBs). The average molecular weight and molecular-weight distribution of the polymer produced in the liquid film and formed on silicon wafer were measured by gel permeation chromatography, which confirms that the polymerization reaction occurred as designed. Furthermore, it is clarified that the surface of the polymer brush synthesized in situ swollen by IL also exhibited low friction characteristics, comparable to that synthesized in a typical immersion process. This paper is the first to establish the effectiveness of in situ preparation for CPBs by using the coating technique.
Influence of Mechanical Couplings on the Dynamical Behavior and Energy Harvesting of a Composite Structure
Authors: Borowiec Marek , Gawryluk Jaroslaw , Bochenski Marcin
Published: December 2020

In this paper, the dynamical behavior of composite material is analyzed, including the energy harvesting effect. The composite is modeled by the Finite Element Method (FEM) and is made of pre-impregnate with a matrix of thermosetting epoxy resin reinforced with high-strength R-type glass fibers, and it is designed as a beam structure that is exposed to mechanical vibrations. The structure assumed the form of a beam with a substantially rectangular cross section. The couplings of motion occurring between mode shapes at properly selected fiber orientations are investigated. The beams with determined sets of composite layers and a coupling effect are used to recover electricity from the mechanical vibrations in the vicinity of the first resonance zone. The composite with a certain number of fiber glass layers has assumed an orientation relative to the beam axis. The new values found in this paper are the intensity of the coupling between the bending in the stiff and flexible directions of the beam for a chosen fiber layer stacking sequence. Additionally, the influence of layer configuration on the energy harvesting efficiency of the Macro-Fiber Composite (MFC) piezoelectric element is assessed.
Study on Improving the Processability and Properties of Mixed Polyolefin Post-Consumer Plastics for Piping Applications
Authors: Garofalo Emilia , Di Maio Luciano , Scarfato Paola , Pietrosanto Arianna , Protopapa Antonio , Incarnato Loredana
Published: December 2020

This study focuses on the upgrading strategies to make Fil-s (acronym for film-small), a polyolefin-based material coming from the mechanical recycling of post-consumer flexible packaging, fit for re-use in the piping sector. The effects of washing treatments (at cold and hot conditions) and the addition of an experimental compatibilizer on the chemical-physical properties of Fil-s were first assessed. The measurements of some key properties (density, melt flow index, flexural modulus, yield strength), for both Fil-s as such and the different developed Fil-s based systems, was also conducted in order to evaluate the suitability of this complex and challenging waste stream to replace virgin PE-based pipe and fitting products, in compliance to ASTM D3350 standard. The outcomes of the present work contributed to define a code, for each Fil-s system investigated, useful for identifying the level of their performance in piping applications. All the recyclates were extruded as pipes by using a pilot scale plant, but the process resulted more stable and continuous with the compatibilized Fil-s, as it was deducible from its flow properties. Moreover, the best mechanical performances were exhibited by the hot-washed Fil-s pipes, with an increase in pipe stiffness equal to 65% respect to the unwashed sample.
Porous Graphene Composite Polymer Fibres
Authors: Ahmed Jubair , Tabish Tanveer A. , Zhang Shaowei , Edirisinghe Mohan
Published: December 2020

Since the isolation of graphene, there have been boundless pursuits to exploit the many superior properties that this material possesses; nearing the two-decade mark, progress has been made, but more is yet to be done for it to be truly exploited at a commercial scale. Porous graphene (PG) has recently been explored as a promising membrane material for polymer composite fibres. However, controlling the incorporation of high surface area PG into polymer fibres remain largely unexplored. Additionally, most polymer-graphene composites suffer from low production rates and yields. In this paper, graphene-loaded microfibres, which can be produced at a very high rate and yield have been formed with a carrier polymer, polycaprolactone. For the first time, PG has been incorporated into polymer matrices produced by a high-output manufacturing process and analysed via multiple techniques; scanning electron microscopy (SEM), Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Raman spectra showed that single layer graphene structures were achieved, evidence for which was also backed up by the other techniques. Fibres with an average diameter ranging from 3–8 μm were produced with 3–5 wt% PG. Here, we show how PG can be easily processed into polymeric fibres, allowing for widespread use in electrical and ultrafiltration systems
Continuous Based Direct Ink Write for Tubular Cardiovascular Medical Devices
Authors: Casanova-Batlle Enric , Guerra Antonio J. , Ciurana Joaquim
Published: December 2020

Bioresorbable cardiovascular applications are increasing in demand as fixed medical devices cause episodes of late restenosis. The autologous treatment is, so far, the gold standard for vascular grafts due to the similarities to the replaced tissue. Thus, the possibility of customizing each application to its end user is ideal for treating pathologies within a dynamic system that receives constant stimuli, such as the cardiovascular system. Direct Ink Writing (DIW) is increasingly utilized for biomedical purposes because it can create composite bioinks by combining polymers and materials from other domains to create DIW-printable materials that provide characteristics of interest, such as anticoagulation, mechanical resistance, or radiopacity. In addition, bioinks can be tailored to encounter the optimal rheological properties for the DIW purpose. This review delves into a novel emerging field of cardiovascular medical applications, where this technology is applied in the tubular 3D printing approach. Cardiovascular stents and vascular grafts manufactured with this new technology are reviewed. The advantages and limitations of blending inks with cells, composite materials, or drugs are highlighted. Furthermore, the printing parameters and the different possibilities of designing these medical applications have been explored.
Synthesis, Characterization, and Application of Carboxymethyl Cellulose from Asparagus Stalk End
Authors: Klunklin Warinporn , Jantanasakulwong Kittisak , Phimolsiripol Yuthana , Leksawasdi Noppol , Seesuriyachan Phisit , Chaiyaso Thanongsak , Insomphun Chayatip , Phongthai Suphat , Jantrawut Pensak , Sommano Sarana Rose , Punyodom Winita , Reungsang Alissara , Ngo Thi Minh Phuong , Rachtanapun Pornchai
Published: December 2020

Cellulose from Asparagus officinalis stalk end was extracted and synthesized to carboxymethyl cellulose (CMCas) using monochloroacetic acid (MCA) via carboxymethylation reaction with various sodium hydroxide (NaOH) concentrations starting from 20% to 60%. The cellulose and CMCas were characterized by the physical properties, Fourier Transform Infrared spectroscopy (FTIR), Differential scanning calorimetry (DSC), Scanning electron microscopy (SEM) and X-ray diffraction (XRD). In addition, mechanical properties of CMCas films were also investigated. The optimum condition for producing CMCas was found to be 30% of NaOH concentration for the carboxymethylation reaction, which provided the highest percent yield of CMCas at 44.04% with the highest degree of substitution (DS) at 0.98. The melting point of CMCas decreased with increasing NaOH concentrations. Crystallinity of CMCas was significantly deformed (p < 0.05) after synthesis at a high concentration. The L* value of the CMCas was significantly lower at a high NaOH concentration compared to the cellulose. The highest tensile strength (44.59 MPa) was found in CMCas film synthesized with 40% of NaOH concentration and the highest percent elongation at break (24.99%) was obtained in CMCas film treated with 30% of NaOH concentration. The applications of asparagus stalk end are as biomaterials in drug delivery system, tissue engineering, coating, and food packaging.
An Assessment of the Thermal Behavior of Envelope Surface Coatings with Different Colors
Authors: Pokorska-Silva Iwona , Kadela Marta , Małek Marcin , Fedorowicz Lidia
Published: December 2020

Contemporary solar power engineering enables the conceptual interlocking of the shape of a building object with its location, structural design, and external envelope, as well as applied materials. Suitably selected solutions involving the structure, shape, construction, and location of a building can significantly improve the thermal balance of rooms in a building. Particularly valuable and warranted are studies involving various solutions for building partitions contributing to a considerable improvement in the thermal balance of a building. This article presents the results of research on temperature changes on the surface of the external part of a partition coated with layers of different colors. For the lightest coating (white), both the average temperature obtained on the and the maximum temperature obtained on the surface were the lowest. With the darker coatings, these temperatures were both higher. The back analyses that were performed indicated lower and higher absorption coefficients, respectively, for the coating compared with the base value for the red coating. Additionally, it was demonstrated that the average surface roughness (Ra) after tests in a natural environment decreased by 12.1% for the base (red) coating. For the grey and white samples, a more than two-fold increase in roughness was reported, of 198.6% and 202.0%, respectively. The SEM analysis indicated material loss and discoloration on the sample surfaces.
Micromechanical Punching: A Versatile Method for Non-Spherical Microparticle Fabrication
Authors: Petersen Ritika Singh , Boisen Anja , Keller Stephan Sylvest
Published: December 2020

Microparticles are ubiquitous in applications ranging from electronics and drug delivery to cosmetics and food. Conventionally, non-spherical microparticles in various materials with specific shapes, sizes, and physicochemical properties have been fabricated using cleanroom-free lithography techniques such as soft lithography and its high-resolution version particle replication in non-wetting template (PRINT). These methods process the particle material in its liquid/semi-liquid state by deformable molds, limiting the materials from which the particles and the molds can be fabricated. In this study, the microparticle material is exploited as a sheet placed on a deformable substrate, punched by a robust mold. Drawing inspiration from the macro-manufacturing technique of punching metallic sheets, Micromechanical Punching (MMP) is a high-throughput technique for fabrication of non-spherical microparticles. MMP allows production of microparticles from prepatterned, porous, and fibrous films, constituting thermoplastics and thermosetting polymers. As an illustration of application of MMP in drug delivery, flat, microdisk-shaped Furosemide embedded poly(lactic-co-glycolic acid) microparticles are fabricated and Furosemide release is observed. Thus, it is shown in the paper that Micromechanical punching has potential to make micro/nanofabrication more accessible to the research and industrial communities active in applications that require engineered particles.
Analysis of a Bistatic Ground-Based Synthetic Aperture Radar System and Indoor Experiments
Authors: Lee Hoonyol , Moon Jihyun
Published: December 2020

Recent advancement of satellite synthetic aperture radar (SAR) techniques require more sophisticated system configurations such as the use of bistatic antennas or multi-frequencies. A ground-based experiment is a cost-effective and efficient way to evaluate those new configurations especially in the early stage of the system development. In this paper, a ground-based synthetic aperture radar (GB-SAR) system was constructed and operated in a bistatic mode at Ku-band where a receiving antenna (Rx) follows a transmitting antenna (Tx) separated by a baseline B. A new bistatic GB-SAR focusing algorithm was developed by modifying a conventional range-Doppler algorithm (RDA), and its performance has been evaluated by comparing the results with those from a back-projection algorithm (BPA). The results showed good performance of RDA at far range approaching nominal resolutions of 9.4 cm in range and 4.5 cm in azimuth, but limited quality at near range due to the approximation used in RDA. Signals from three trihedral corner reflectors (CR) reduced with increasing B, showing a typical bidirectional scattering behavior of CR. This GB-SAR system will be a testbed for new SAR imaging configurations with variations in antenna positions and target properties.
DGCB-Net: Dynamic Graph Convolutional Broad Network for 3D Object Recognition in Point Cloud
Authors: Tian Yifei , Chen Long , Song Wei , Sung Yunsick , Woo Sangchul
Published: December 2020

3D (3-Dimensional) object recognition is a hot research topic that benefits environment perception, disease diagnosis, and the mobile robot industry. Point clouds collected by range sensors are a popular data structure to represent a 3D object model. This paper proposed a 3D object recognition method named Dynamic Graph Convolutional Broad Network (DGCB-Net) to realize feature extraction and 3D object recognition from the point cloud. DGCB-Net adopts edge convolutional layers constructed by weight-shared multiple-layer perceptrons (MLPs) to extract local features from the point cloud graph structure automatically. Features obtained from all edge convolutional layers are concatenated together to form a feature aggregation. Unlike stacking many layers in-depth, our DGCB-Net employs a broad architecture to extend point cloud feature aggregation flatly. The broad architecture is structured utilizing a flat combining architecture with multiple feature layers and enhancement layers. Both feature layers and enhancement layers concatenate together to further enrich the features’ information of the point cloud. All features work on the object recognition results thus that our DGCB-Net show better recognition performance than other 3D object recognition algorithms on ModelNet10/40 and our scanning point cloud dataset.
An Internet of Vehicles (IoV) Access Gateway Design Considering the Efficiency of the In-Vehicle Ethernet Backbone
Authors: Kim Dae-Young , Jung Minwoo , Kim Seokhoon
Published: December 2020

A vehicular network is composed of an in-vehicle network (IVN) and Internet of Vehicles (IoV). IVN exchanges information among in-vehicle devices. IoV constructs Vehicle-to-X (V2X) networks outside vehicles and exchanges information among V2X elements. These days, in-vehicle devices that require high bandwidth is increased for autonomous driving services. Thus, the spread of data for vehicles is exploding. This kind of data is exchanged through IoV. Even if the Ethernet backbone of IVN carries a lot of data in the vehicle, the explosive increase in data from outside the vehicle can affect the backbone. That is, the transmission efficiency of the IVN backbone will be reduced due to excessive data traffic. In addition, when IVN data traffic is transmitted to IoV without considering IoV network conditions, the transmission efficiency of IoV is also reduced. Therefore, in this paper, we propose an IoV access gateway to controls the incoming data traffic to the IVN backbone and the outgoing data traffic to the IoV in the network environment where IVN and IoV are integrated. Computer simulations are used to evaluate the performance of the proposed system, and the proposed system shows better performance in the accumulated average transmission delay.
Predicting Dimensions in Microfluidic Paper Based Analytical Devices
Authors: Catalan-Carrio Raquel , Akyazi Tugce , Basabe-Desmonts Lourdes , Benito-Lopez Fernando
Published: December 2020

The main problem for the expansion of the use of microfluidic paper-based analytical devices and, thus, their mass production is their inherent lack of fluid flow control due to its uncontrolled fabrication protocols. To address this issue, the first step is the generation of uniform and reliable microfluidic channels. The most common paper microfluidic fabrication method is wax printing, which consists of two parts, printing and heating, where heating is a critical step for the fabrication of reproducible device dimensions. In order to bring paper-based devices to success, it is essential to optimize the fabrication process in order to always get a reproducible device. Therefore, the optimization of the heating process and the analysis of the parameters that could affect the final dimensions of the device, such as its shape, the width of the wax barrier and the internal area of the device, were performed. Moreover, we present a method to predict reproducible devices with controlled working areas in a simple manner.
Advanced Statistical Analysis of 3D Kinect Data: Mimetic Muscle Rehabilitation Following Head and Neck Surgeries Causing Facial Paresis
Authors: Kohout Jan , Verešpejová Ludmila , Kříž Pavel , Červená Lenka , Štícha Karel , Crha Jan , Trnková Kateřina , Chovanec Martin , Mareš Jan
Published: December 2020

An advanced statistical analysis of patients’ faces after specific surgical procedures that temporarily negatively affect the patient’s mimetic muscles is presented. For effective planning of rehabilitation, which typically lasts several months, it is crucial to correctly evaluate the improvement of the mimetic muscle function. The current way of describing the development of rehabilitation depends on the subjective opinion and expertise of the clinician and is not very precise concerning when the most common classification (House–Brackmann scale) is used. Our system is based on a stereovision Kinect camera and an advanced mathematical approach that objectively quantifies the mimetic muscle function independently of the clinician’s opinion. To effectively deal with the complexity of the 3D camera input data and uncertainty of the evaluation process, we designed a three-stage data-analytic procedure combining the calculation of indicators determined by clinicians with advanced statistical methods including functional data analysis and ordinal (multiple) logistic regression. We worked with a dataset of 93 distinct patients and 122 sets of measurements. In comparison to the classification with the House–Brackmann scale the developed system is able to automatically monitor reinnervation of mimetic muscles giving us opportunity to discriminate even small improvements during the course of rehabilitation.
Knowledge-Based Verification of Concatenative Programming Patterns Inspired by Natural Language for Resource-Constrained Embedded Devices
Authors: Gaglio Salvatore , Lo Re Giuseppe , Martorella Gloria , Peri Daniele
Published: December 2020

We propose a methodology to verify applications developed following programming patterns inspired by natural language that interact with physical environments and run on resource-constrained interconnected devices. Natural language patterns allow for the reduction of intermediate abstraction layers to map physical domain concepts into executable code avoiding the recourse to ontologies, which would need to be shared, kept up to date, and synchronized across a set of devices. Moreover, the computational paradigm we use for effective distributed execution of symbolic code on resource-constrained devices encourages the adoption of such patterns. The methodology is supported by a rule-based system that permits runtime verification of Software Under Test (SUT) on board the target devices through automated oracle and test case generation. Moreover, verification extends from syntactic and semantic checks to the evaluation of the effects of SUT execution on target hardware. Additionally, by exploiting rules tying sensors and actuators to physical quantities, the effects of code execution on the physical environment can be verified. The system is also able to build test code to highlight software issues that may arise during repeated SUT execution on the target hardware.
Time-Aware and Temperature-Aware Fire Evacuation Path Algorithm in IoT-Enabled Multi-Story Multi-Exit Buildings
Authors: Yen Hong-Hsu , Lin Cheng-Han , Tsao Hung-Wei
Published: December 2020

Temperature sensors with a communication capability can help monitor and report temperature values to a control station, which enables dynamic and real-time evacuation paths in fire emergencies. As compared to traditional approaches that identify a one-shot fire evacuation path, in this paper, we develop an intelligent algorithm that can identify time-aware and temperature-aware fire evacuation paths by considering temperature changes at different time slots in multi-story and multi-exit buildings. We first propose a method that can map three-dimensional multi-story multi-exit buildings into a two-dimensional graph. Then, a mathematical optimization model is proposed to capture this time-aware and temperature-aware evacuation path problem in multi-story multi-exit buildings. Six fire evacuation algorithms (BFS, SP, DBFS, TABFS, TASP and TADBFS) are proposed to identify the efficient evacuation path. The first three algorithms that do not address human temperature limit constraints can be used by rescue robots or firemen with fire-proof suits. The last three algorithms that address human temperature limit constraints can be used by evacuees in terms of total time slots and total temperature on the evacuation path. In the computational experiments, the open space building and the Taipei 101 Shopping Mall are all tested to verify the solution quality of these six algorithms. From the computational results, TABFS, TASP and TADBF identify almost the same evacuation path in open space building and the Taipei 101 Shopping Mall. BFS, SP DBFS can locate marginally better results in terms of evacuation time and total temperature on the evacuation path. When considering evacuating a group of evacuees, the computational time of the evacuation algorithm is very important in a time-limited evacuation process. Considering the extreme case of seven fires in eight emergency exits in the Taipei 101 Shopping Mall, the golden window for evacuation is 15 time slots. Only TABFS and TADBFS are applicable to evacuate 1200 people in the Taipei 101 Shopping Mall when one time slot is setting as one minute. The computational results show that the capacity limit for the Taipei 101 Shopping Mall is 800 people in the extreme case of seven fires. In this case, when the number of people in the building is less than 700, TADBFS should be adopted. When the number of people in the building is greater than 700, TABFS can evacuate more people than TADBFS. Besides identifying an efficient evacuation path, another significant contribution of this paper is to identify the best sensor density deployment at large buildings like the Taipei 101 Shopping Mall in considering the fire evacuation.
Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Techniques
Authors: Zarra Tiziano , Galang Mark Gino K. , Ballesteros Florencio C. , Belgiorno Vincenzo , Naddeo Vincenzo
Published: December 2020

Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period from the original response curve, in collaboration with Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANN) as a pattern recognition algorithm, were investigated. Laboratory analyses were performed with real odour samples collected in a complex industrial plant, using an advanced smart IOMS. The results demonstrate the influence of the choice of method on the quality of the OCMM produced. The peak period in combination with the Artificial Neural Network (ANN) highlighted the best combination on the basis of high classification rates. The paper provides information to develop a solution to optimize the performance of IOMS.
Evaluating the Effect of Stimuli Color and Frequency on SSVEP
Authors: Duart Xavier , Quiles Eduardo , Suay Ferran , Chio Nayibe , García Emilio , Morant Francisco
Published: December 2020

Brain–computer interfaces (BCI) can extract information about the subject’s intentions by registering and processing electroencephalographic (EEG) signals to generate actions on physical systems. Steady-state visual-evoked potentials (SSVEP) are produced when the subject stares at flashing visual stimuli. By means of spectral analysis and by measuring the signal-to-noise ratio (SNR) of its harmonic contents, the observed stimulus can be identified. Stimulus color matters, and some authors have proposed red because of its ability to capture attention, while others refuse it because it might induce epileptic seizures. Green has also been proposed and it is claimed that white may generate the best signals. Regarding frequency, middle frequencies are claimed to produce the best SNR, although high frequencies have not been thoroughly studied, and might be advantageous due to the lower spontaneous cerebral activity in this frequency band. Here, we show white, red, and green stimuli, at three frequencies: 5 (low), 12 (middle), and 30 (high) Hz to 42 subjects, and compare them in order to find which one can produce the best SNR. We aim to know if the response to white is as strong as the one to red, and also if the response to high frequency is as strong as the one triggered by lower frequencies. Attention has been measured with the Conner’s Continuous Performance Task version 2 (CPT-II) task, in order to search for a potential relationship between attentional capacity and the SNR previously obtained. An analysis of variance (ANOVA) shows the best SNR with the middle frequency, followed by the low, and finally the high one. White gives as good an SNR as red at 12 Hz and so does green at 5 Hz, with no differences at 30 Hz. These results suggest that middle frequencies are preferable and that using the red color can be avoided. Correlation analysis also show a correlation between attention and the SNR at low frequency, so suggesting that for the low frequencies, more attentional capacity leads to better results.
UAV-Based RGB Imagery for Hokkaido Pumpkin (Cucurbita max.) Detection and Yield Estimation
Authors: Wittstruck Lucas , Kühling Insa , Trautz Dieter , Kohlbrecher Maik , Jarmer Thomas
Published: December 2020

Pumpkins are economically and nutritionally valuable vegetables with increasing popularity and acreage across Europe. Successful commercialization, however, require detailed pre-harvest information about number and weight of the fruits. To get a non-destructive and cost-effective yield estimation, we developed an image processing methodology for high-resolution RGB data from Unmanned aerial vehicle (UAV) and applied this on a Hokkaido pumpkin farmer’s field in North-western Germany. The methodology was implemented in the programming language Python and comprised several steps, including image pre-processing, pixel-based image classification, classification post-processing for single fruit detection, and fruit size and weight quantification. To derive the weight from two-dimensional imagery, we calculated elliptical spheroids from lengths of diameters and heights. The performance of this processes was evaluated by comparison with manually harvested ground-truth samples and cross-checked for misclassification from randomly selected test objects. Errors in classification and fruit geometry could be successfully reduced based on the described processing steps. Additionally, different lighting conditions, as well as shadows, in the image data could be compensated by the proposed methodology. The results revealed a satisfactory detection of 95% (error rate of 5%) from the field sample, as well as a reliable volume and weight estimation with Pearson’s correlation coefficients of 0.83 and 0.84, respectively, from the described ellipsoid approach. The yield was estimated with 1.51 kg m−2 corresponding to an average individual fruit weight of 1100 g and an average number of 1.37 pumpkins per m2. Moreover, spatial distribution of aggregated fruit densities and weights were calculated to assess in-field optimization potential for agronomic management as demonstrated between a shaded edge compared to the rest of the field. The proposed approach provides the Hokkaido producer useful information for more targeted pre-harvest marketing strategies, since most food retailers request homogeneous lots within prescribed size or weight classes.
Electrochemical Immunosensor for the Early Detection of Rheumatoid Arthritis Biomarker: Anti-Cyclic Citrullinated Peptide Antibody in Human Serum Based on Avidin-Biotin System
Authors: Chinnadayyala Somasekhar R. , Cho Sungbo
Published: December 2020

Rheumatoid arthritis (RA) is a chronic autoimmune disease that produces a progressive inflammatory response that leads to severe pain, swelling, and stiffness in the joints of hands and feet, followed by irreversible damage of the joints. The authors developed a miniaturized, label-free electrochemical impedimetric immunosensor for the sensitive and direct detection of arthritis Anti-CCP-ab biomarker. An interdigitated-chain-shaped microelectrode array (ICE) was fabricated by taking the advantage of microelectromechanical systems. The fabricated ICE was modified with a self-assembled monolayer (SAM) of Mercaptohexanoic acid (MHA) for immobilization of the synthetic peptide bio-receptor (B-CCP). The B-CCP was attached onto the surface of SAM modified ICE through a strong avidin-biotin bio-recognition system. The modified ICE surface with the SAM and bio-molecules (Avidin, B-CCP, Anti-CCP-ab and BSA) was morphologically and electrochemically characterized. The change in the sensor signal upon analyte binding on the electrode surface was probed through the electrochemical impedance spectroscopy (EIS) property of charge-transfer resistance (Rct) of the modified electrodes. EIS measurements were target specific and the sensor response was linearly increased with step wise increase in target analyte (Anti-CCP-ab) concentrations. The developed sensor showed a linear range for the addition of Anti-CCP-ab between 1 IU mL−1 → 800 IU mL−1 in phosphate buffered saline (PBS) and Human serum (HS), respectively. The sensor showed a limit of detection of 0.60 IU mL−1 and 0.82 IU mL−1 in the PBS and HS, respectively. The develop bio-electrode showed a good reproducibility (relative standard deviation (RSD), 1.52%), selectivity and stability (1.5% lost at the end of 20th day) with an acceptable recovery rate (98.0% → 101.18%) and % RSD’s for the detection of Anti-CCP-ab in spiked HS samples.
Low-Cost Benzene Toluene Xylene Measurement Gas System Based on the Mini Chromatographic Cartridge
Authors: Zampetti Emiliano , Papa Paolo , Avossa Joshua , Bearzotti Andrea , Balducci Catia , Tranfo Giovanna , Macagnano Antonella
Published: December 2020

Benzene, toluene and xylene (BTX) are an important part of the volatile organic compounds (VOCs) to be detected and monitored in the air, due to their toxicity towards human health. One of the most reliable technique used in BTX detection is gas chromatography (GC), which presents a high sensitivity. On the other hand, it has important drawbacks, such as high costs, the need for qualified personnel and frequent maintenance. To overcome these drawbacks, this work reports the development of a low cost and portable BTX gas detection system based on a mini chromatographic cartridge, a photo ionization detector (PID), a simple control unit (based on Arduino architecture) and a mini pump. In order to separate the BTX components, we propose the use of a cartridge 80 mm in length, composed of several commercial chromatographic column sections. To test the system performances, we have injected different amounts (from about 0.3 to 5.3 µg) of benzene, toluene and xylene and two of the most frequent possible interferents (ethanol, acetone). Experimental results have shown different retention time values (i.e., 25 ± 0.5 s, 51 ± 1.2 s and 117 ± 4 s, respectively) for benzene, toluene and xylene.
Collision Prevention for Duty-Cycle Receiver-Initiation MAC Protocol via Multiple Access Reservation (MAR-RiMAC)
Authors: Gurewitz Omer , Zaharia Oren
Published: December 2020

The prevalence of the Internet of Things (IoT) paradigm in more and more applications associated with our daily lives has induced a dense network in which numerous wireless devices, many of which have limited capabilities (e.g., power, memory, computation), need to communicate with the internet. One of the main bottlenecks of this setup is the wireless channel. Numerous medium access control (MAC) protocols have been devised to coordinate between devices that share the wireless channel. One prominent approach that is highly suitable for IoT and wireless sensor networks (WSNs), which rely on duty cycling, is the receiver-initiated approach, in which, rather than the transmitter, the receiver initiates the transaction. The problem with this approach is that when many devices are trying to respond to the receiver’s transmission invitation and transmit simultaneously, a collision occurs. When the network is highly loaded, resolving such collisions is quite tedious. In this paper, we devise an enhancement to the receiver-initiated approach that aims at preventing this inherent collision scenario. Our modification relies on multiple devices sending a short predefined signal, informing their intended receiver of their intention to transmit simultaneously. The data transaction is done via a four-way handshake in which, after all backlogged devices have informed their designated receiver of their desire to transmit simultaneously, the receiver identifies them and polls them one by one, avoiding the collision. We compare the performance of Receiver-Initiated-MAC protocol (RI-MAC), which is one of the prevalent receiver-initiated protocols, with and without the suggested enhancement, and show superior air-time utilization under high traffic loads, especially in the presence of hidden terminals.
Learning History with Location-Based Applications: An Architecture for Points of Interest in Multiple Layers
Authors: Laato Samuli , Rauti Sampsa , Laato Antti , Laine Teemu , Sutinen Erkki , Lehtinen Erno
Published: December 2020

Location-based applications (LBAs) capture the user’s physical location via satellite navigation sensors and integrate it as part of the digital application. Because of this connection, the real-world environment needs to be accounted for in LBA design. In this work, we focused on creating a database of geographically distributed points of interest (PoIs) that is optimal for learning local history. First, we conducted a requirements elicitation study at three outdoor archaeological sites and identified issues in existing solutions. Second, we designed a multi-layered prototype solution. Third, we evaluated the solution with nine experts who had prior experience with LBAs or similar systems. We incorporated their feedback to our design to iteratively improve it. As a whole, our work contributes to the LBA design literature by proposing a solution that is optimized for the learning of local history.
Research on Finger Vein Image Segmentation and Blood Sampling Point Location in Automatic Blood Collection
Authors: Li Xi , Li Zhangyong , Yang Dewei , Zhong Lisha , Huang Lian , Lin Jinzhao
Published: December 2020

In the fingertip blood automatic sampling process, when the blood sampling point in the fingertip venous area, it will greatly increase the amount of bleeding without being squeezed. In order to accurately locate the blood sampling point in the venous area, we propose a new finger vein image segmentation approach basing on Gabor transform and Gaussian mixed model (GMM). Firstly, Gabor filter parameter can be set adaptively according to the differential excitation of image and we use the local binary pattern (LBP) to fuse the same-scale and multi-orientation Gabor features of the image. Then, finger vein image segmentation is achieved by Gabor-GMM system and optimized by the max flow min cut method which is based on the relative entropy of the foreground and the background. Finally, the blood sampling point can be localized with corner detection. The experimental results show that the proposed approach has significant performance in segmenting finger vein images which the average accuracy of segmentation images reach 91.6%.
Efficient Spectrum Occupancy Prediction Exploiting Multidimensional Correlations through Composite 2D-LSTM Models
Authors: Aygül Mehmet Ali , Nazzal Mahmoud , Sağlam Mehmet İzzet , da Costa Daniel Benevides , Ateş Hasan Fehmi , Arslan Hüseyin
Published: December 2020

In cognitive radio systems, identifying spectrum opportunities is fundamental to efficiently use the spectrum. Spectrum occupancy prediction is a convenient way of revealing opportunities based on previous occupancies. Studies have demonstrated that usage of the spectrum has a high correlation over multidimensions, which includes time, frequency, and space. Accordingly, recent literature uses tensor-based methods to exploit the multidimensional spectrum correlation. However, these methods share two main drawbacks. First, they are computationally complex. Second, they need to re-train the overall model when no information is received from any base station for any reason. Different than the existing works, this paper proposes a method for dividing the multidimensional correlation exploitation problem into a set of smaller sub-problems. This division is achieved through composite two-dimensional (2D)-long short-term memory (LSTM) models. Extensive experimental results reveal a high detection performance with more robustness and less complexity attained by the proposed method. The real-world measurements provided by one of the leading mobile network operators in Turkey validate these results.