bluuebunny/crossref_metadata_2025 huggingface dataset:
Nipple-Sparing Mastectomy Long-Term Outcomes: Early and Late Complications
Authors: Metere Alessio , Fabiani Elisabetta , Lonardo Maria Teresa , Giannotti Domenico , Pace Daniela , Giacomelli Laura
Published: April 2020

Background and Objectives: The surgical choice treatment of the breast cancer mostly depends on the stage of the disease. In the last years, breast cancer surgery has moved from being destructive to being more respectful of the anatomical and physiological integrity of the gland. The aim of the breast surgery should be finalized to obtain the best aesthetic and functional results, respecting the principles of oncologic radicality. The present study is a retrospective analysis aimed to evaluate the long-term outcomes of a conservative technique like the nipple-sparing mastectomy. Materials and Methods: We observed 894 patients with a median age of 47.5 years old, underwent nipple-sparing mastectomy between 2002–2017. The data acquired include population and tumor characteristics, patient reconstructive outcomes, including locoregional, regional, and distant metastases; other variables, among nipple–areola complex necrosis and infection were collected. Results: The complications detected were considered as “early” within 1 month later the nipple-sparing mastectomy or “late” after this time. The overall complications rate (early and late) and the overall survival and the relapses detected by this study were comparable with those reported in the literature. In order to identify factors that correlate with complications, either early or later, it has been processed an evaluation of the univariate analysis showing adjuvant chemotherapy as the only predictive factor for late complications, while we encountered no predictors for early complications. Conclusions: The present study adds to the data already present in literature, demonstrating that the nipple-sparing mastectomy is a safe procedure, providing good oncological and aesthetic results in patients carefully selected.
Comparative Study on the Uniaxial Behaviour of Topology-Optimised and Crystal-Inspired Lattice Materials
Authors: Yang Chengxing , Xu Kai , Xie Suchao
Published: April 2020

This work comparatively studies the uniaxial compressive performances of three types of lattice materials, namely face-centre cube (FCC), edge-centre cube (ECC), and vertex cube (VC), which are separately generated by topology optimisation and crystal inspiration. High similarities are observed between the materials designed by these two methods. The effects of design method, cell topology, and relative density on deformation mode, mechanical properties, and energy absorption are numerically investigated and also fitted by the power law. The results illustrate that both topology-optimised and crystal-inspired lattices are mainly dominated by bending deformation mode. In terms of collapse strength and elastic modulus, VC lattice is stronger than FCC and ECC lattices because its struts are arranged along the loading direction. In addition, the collapse strength and elastic modulus of the topology-optimised FCC and ECC are close to those generated by crystal inspiration at lower relative density, but the topology-optimised FCC and ECC are obviously superior at a higher relative density. Overall, all topology-generated lattices outperform the corresponding crystal-guided lattice materials with regard to the toughness and energy absorption per unit volume.
The Influence of Laser Shock Peening on Fatigue Properties of AA2024-T3 Alloy with a Fastener Hole
Authors: Sikhamov Ruslan , Fomin Fedor , Klusemann Benjamin , Kashaev Nikolai
Published: April 2020

The objective of the present study was to estimate the influence of laser shock peening on the fatigue properties of AA2024-T3 specimens with a fastener hole and to investigate the possibility to heal the initial cracks in such specimens. Fatigue cracks of different lengths were introduced in the specimens with a fastener hole before applying laser shock peening. Deep compressive residual stresses, characterized by the hole drilling method, were generated into the specimens by applying laser shock peening on both sides. Subsequently, the specimens were subjected to fatigue tests. The results show that laser shock peening has a positive effect regarding the fatigue life improvement in the specimens with a fastener hole. In addition, laser shock peening leads to a healing effect on fatigue cracks. The efficiency of this effect depends on the initial crack length. The effect of laser shock peening on the fatigue life periods was determined by using resonant frequency graphs.
Experimental Model Study of Liquid–Liquid and Liquid–Gas Interfaces during Blast Furnace Hearth Drainage
Authors: Liu Weiqiang , Shao Lei , Saxén Henrik
Published: April 2020

The smooth drainage of produced iron and slag is a prerequisite for stable and efficient blast furnace operation. For this it is essential to understand the drainage behavior and the evolution of the liquid levels in the hearth. A two-dimensional Hele–Shaw model was used to study the liquid–liquid and liquid–gas interfaces experimentally and to clarify the effect of the initial amount of iron and slag, slag viscosity, and blast pressure on the drainage behavior. In accordance with the findings of other investigators, the gas breakthrough time increased and residual ratios for both liquids decreased with an increase of the initial levels of iron and slag, a decrease in blast pressure, and an increase in slag viscosity. The conditions under which the slag–iron interface in the end state was at the taphole and not below it were finally studied and reported.
Analytical Prediction of Residual Stress in the Machined Surface during Milling
Authors: Yue Caixu , Hao Xiaole , Ji Xia , Liu Xianli , Liang Steven Y. , Wang Lihui , Yan Fugang
Published: April 2020

An analytical prediction model for residual stress during milling is established, which considers the thermal-mechanical coupling effect. Considering the effects of thermal-mechanical coupling, the residual stress distribution in the workpiece is determined by the stress loading history according to McDowell′s hybrid algorithm. Based on the analysis of the geometric relationship of orthogonal cutting, the prediction model for milling force and residual stress in the machined surface is established. The research results can provide theoretical basis for stress control during milling.
2D/1D V2O5 Nanoplates Anchored Carbon Nanofibers as Efficient Separator Interlayer for Highly Stable Lithium–Sulfur Battery
Authors: Zhang Zongtao , Wu Guodong , Ji Haipeng , Chen Deliang , Xia Dengchao , Gao Keke , Xu Jianfei , Mao Bin , Yi Shasha , Zhang Liying , Wang Yu , Zhou Ying , Kang Litao , Gao Yanfeng
Published: April 2020

Quick capacity loss due to the polysulfide shuttle effects is a critical challenge for high-performance lithium–sulfur (Li–S) batteries. Herein, a novel 2D/1D V2O5 nanoplates anchored carbon nanofiber (V-CF) interlayer coated on standard polypropylene (PP) separator is constructed, and a stabilization mechanism derived from a quasi-confined cushion space (QCCS) that can flexibly accommodate the polysulfide utilization is demonstrated. The incorporation of the V-CF interlayer ensures stable electron and ion pathway, and significantly enhanced long-term cycling performances are obtained. A Li–S battery assembled with the V-CF membrane exhibited a high initial capacity of 1140.8 mAh·g−1 and a reversed capacitance of 1110.2 mAh·g−1 after 100 cycles at 0.2 C. A high reversible capacity of 887.2 mAh·g−1 is also maintained after 500 cycles at 1 C, reaching an ultra-low decay rate of 0.0093% per cycle. The excellent electrochemical properties, especially the long-term cycling stability, can offer a promising designer protocol for developing highly stable Li–S batteries by introducing well-designed fine architectures to the separator.
Improved Diabetic Wound Healing by EGF Encapsulation in Gelatin-Alginate Coacervates
Authors: Jeong Seonghee , Kim ByungWook , Park Minwoo , Ban Eunmi , Lee Soo-Hyeon , Kim Aeri
Published: April 2020

Topical imageplication of epidermal growth fctor (EGF) has been used to accelerate diabetic foot ulcers but with limited efficacy. In this study, we selected a complex coacervate (EGF-Coa) composed of the low molecular weight gelatin type A and sodium alginate as a novel delivery system for EGF, based on encapsulation efficiency and protection of EGF from protease. EGF-Coa enhanced in vitro migration of keratinocytes and accelerated wound healing in streptozotocin-induced diabetic mice with increased granulation and re-epithelialization. While diabetic wound sites without treatment showed downward growth of hyperproliferative epidermis along the wound edges with poor matrix formation, EGF-Coa treatment recovered horizontal migration of epidermis over the newly deposited dermal matrix. EGF-Coa treatment also resulted in reduced levels of proinflammatory cytokines IL-1, IL-6, and THF-α. Freeze-dried coacervates packaged in aluminum pouches were stable for up to 4 months at 4 and 25 °C in terms of appearance, purity by RP-HPLC, and in vitro release profiles. There were significant physical and chemical changes in relative humidity above 33% or at 37 °C, suggesting the requirement for moisture-proof packaging and cold chain storage for long term stability. We propose low molecular weight gelatin type A and sodium alginate (LWGA-SA) coacervates as a novel EGF delivery system with enhanced efficacy for chronic wounds.
A New Industrial Technology for Mass Production of Graphene/PEBA Membranes for CO2/CH4 Selectivity with High Dispersion, Thermal and Mechanical Performance
Authors: Yousef Samy , Sarwar Zahid , Šereika Justas , Striūgas Nerijus , Krugly Edvinas , Danilovas Paulius Pavelas , Martuzevicius Dainius
Published: April 2020

Polyether block amide (PEBA) nanocomposite membranes, including Graphene (GA)/PEBA membranes are considered to be a promising emerging technology for removing CO2 from natural gas and biogas. However, poor dispersion of GA in the produced membranes at industrial scale still forms the main barrier to commercialize. Within this frame, this research aims to develop a new industrial approach to produce GA/PEBA granules that could be used as a feedstock material for mass production of GA/PEBA membranes. The developed approach consists of three sequential phases. The first stage was concentrated on production of GA/PEBA granules using extrusion process (at 170–210 °C, depending on GA concentration) in the presence of Paraffin Liquid (PL) as an adhesive layer (between GA and PEBA) and assisted melting of PEBA. The second phase was devoted to production of GA/PEBA membranes using a solution casting method. The last phase was focused on evaluation of CO2/CH4 selectivity of the fabricated membranes at low and high temperatures (25 and 55 °C) at a constant feeding pressure (2 bar) using a test rig built especially for that purpose. The granules and membranes were prepared with different concentrations of GA in the range 0.05 to 0.5 wt.% and constant amount of PL (2 wt.%). Also, the morphology, physical, chemical, thermal, and mechanical behaviors of the synthesized membranes were analyzed with the help of SEM, TEM, XRD, FTIR, TGA-DTG, and universal testing machine. The results showed that incorporation of GA with PEBA using the developed approach resulted in significant improvements in dispersion, thermal, and mechanical properties (higher elasticity increased by ~10%). Also, ideal CO2/CH4 selectivity was improved by 29% at 25 °C and 32% at 55 °C.
Enhanced Thermoelectric Performance of Indacenodithiophene-Benzothiadiazole Copolymer Containing Polar Side Chains and Single Wall Carbon Nanotubes Composites
Authors: Chen Zhongming , Liu Tongchao , Pan Chengjun , Tan Guiping
Published: April 2020

Composite films of indacenodithiophene-bezothiadazole copolymers bearing polar side chains (P1) and single wall carbon nanotubes (SWCNTs) are found to show a competitive thermoelectric performance compared to their analogous polymers with aliphatic side chains (P2). The enhanced power factors could be attributed to the stronger interfacial interactions between the P1/SWCNTs compared to that of P2/SWCNTs containing the same ratio of SWCNTs. A maximum power factor of 161.34 μW m−1 K−2 was obtained for the composite films of P1/SWCNTs for a filler content of 50 wt%, which is higher than that of P2/SWCNTs (139.06 μW m−1 K−2, 50 wt%). Our work sheds light on the design of side-chains in efficient conjugated polymers/SWCNTs thermoelectric materials and contributes to the understanding of their thermoelectric properties.
Biomolecules as Flame Retardant Additives for Polymers: A Review
Authors: Villamil Watson Daniel A. , Schiraldi David A.
Published: April 2020

Biological molecules can be obtained from natural sources or from commercial waste streams and can serve as effective feedstocks for a wide range of polymer products. From foams to epoxies and composites to bulk plastics, biomolecules show processability, thermal stability, and mechanical adaptations to fulfill current material requirements. This paper summarizes the known bio-sourced (or bio-derived), environmentally safe, thermo-oxidative, and flame retardant (BEST-FR) additives from animal tissues, plant fibers, food waste, and other natural resources. The flammability, flame retardance, and—where available—effects on polymer matrix’s mechanical properties of these materials will be presented. Their method of incorporation into the matrix, and the matrices for which the BEST-FR should be applicable will also be made known if reported. Lastly, a review on terminology and testing methodology is provided with comments on future developments in the field.
Solubility Improvement of Progesterone from Solid Dispersions Prepared by Solvent Evaporation and Co-milling
Authors: Chen Xing , Partheniadis Ioannis , Nikolakakis Ioannis , Al-Obaidi Hisham
Published: April 2020

The aim of this contribution was to evaluate the impact of processing methods and polymeric carriers on the physicochemical properties of solid dispersions of the poorly soluble drug progesterone (PG). Five polymers: hydroxypropyl methylcellulose (HPMC), hydroxypropyl methylcellulose acetate succinate (HPMCAS), microcrystalline cellulose (MCC), polyvinylpyrrolidone (PVP) and silica (SiO2), and two processing methods: solvent evaporation (SE) and mechano-chemical activation by co-milling (BM) were applied. H-bonding was demonstrated by FTIR spectra as clear shifting of drug peaks at 1707 cm−1 (C20 carbonyl) and 1668 cm−1 (C3 carbonyl). Additionally, spectroscopic and thermal analysis revealed the presence of unstable PG II polymorphic form and a second heating DSC cycle, the presence of another polymorph possibly assigned to form III, but their influence on drug solubility was not apparent. Except for PG–MCC, solid dispersions improved drug solubility compared to physical mixtures. For SE dispersions, an inverse relationship was found between drug water solubility and drug–polymer Hansen solubility parameter difference (Δδt), whereas for BM dispersions, the solubility was influenced by both the intermolecular interactions and the polymer Tg. Solubility improvement with SE was demonstrated for all except PG–MCC dispersions, whereas improvement with BM was demonstrated by the PG–HPMC, PG–PVP and PG–HPMCAS dispersions, the last showing impressive increase from 34.21 to 82.13 μg/mL. The extensive H-bonding between PG and HPMCAS was proved by FTIR analysis of the dispersion in the liquid state. In conclusion, although SE improved drug solubility, BM gave more than twice greater improvement. This indicates that directly operating intermolecular forces are more efficient than the solvent mediated.
Green Synthesis of Mg0.99 Zn0.01O Nanoparticles for the Fabrication of κ-Carrageenan/NaCMC Hydrogel in order to Deliver Catechin
Authors: Sabbagh Farzaneh , Kiarostami Khadijeh , Mahmoudi Khatir Nadia , Rezania Shahabaldin , Muhamad Ida Idayu
Published: April 2020

Currently, the role of the nanoparticles in the structure of the composites and their benefits for the health of the body is valuable. In this study, the effects of the doping on the structural and morphological properties of the hydrogels using a Mg co-doped ZnO hydrogel, which has been fabricated by the sol–gel process, have been investigated. Then, a hydrogel containing nanoparticle and a hydrogel without any nanoparticles was produced as a control. The hydrogels were loaded with catechin and the related characterization was evolved based on the new structure of the matrices. The Mg0.99Zn0.01O nanoparticles were synthesized using a green synthesis method. To investigate the properties of the nanoparticles, zeta potential and XRD were studied. The field emission scanning electron microscopy (FESEM), FTIR, TGA, swelling Ratio, and compression tests were investigated for the hydrogels. Based on the results, FESEM showed a more compressed structure for hydrogels including nanoparticles rather than the hydrogels without a nanoparticle. The TGA showed a higher decomposition temperature in the hydrogels including nanoparticles. The swelling ratio of hydrogels containing a nanoparticle was higher than the control hydrogel. κ-Carrageenan/ Mg0.99Zn0.01O/NaCMC/Catechin had the highest swelling ratio (44.15%) rather than the κ-Carrageenan/NaCMC (33.22%). Mg0.99Zn0.01O nanoparticles presented a stronger structure of hydrogels in the compression test. It is concluded that the role of the synthesized nanoparticle is critical in the structure of the hydrogel.
Study on the Properties of Transparent Bamboo Prepared by Epoxy Resin Impregnation
Authors: Wu Yan , Wang Yajing , Yang Feng , Wang Jing , Wang Xuehua
Published: April 2020

In this paper, Moso bamboo (Phyllostachys heterocycle) before and after heat treatment were used as raw materials to prepare transparent bamboo (TB). In an acidic environment, the lignin contained in the bamboo material was removed to obtain a bamboo template, and an epoxy resin similar to the cellulose refractive index was used for vacuum impregnation into the bamboo template to obtain a transparent bamboo material. The purpose of this study was to compare the physical and chemical properties of TB and original bamboo and the differences between TBs before and after heat treatment, taken from different parts of bamboo, in order to explore the performance advantages and disadvantages of TB as a new material. The Fourier transform infrared spectroscopy analysis (FTIR), scanning electron microscope testing (SEM), three elements analysis, light transmittance testing, and mechanical strength testing were used to study the molecular composition, microstructure, chemical composition, light transmittance, and tensile strength of the TB samples. The results showed that the lignin content of the delignified bamboo templates was greatly reduced. In addition, the SEM images showed that a large amount of epoxy resin (type E51 and type B210 curing agent) was covered on the cross-section surface and pores of the TB samples. The FTIR showed that the epoxy molecular groups appeared on the TB, and the delignified bamboo template and the resin had a good synergy effect. According to the light transmittance testing, the original bamboo samples hardly contained light transmittance under visible light. The transmittance of transparent inner bamboo (TIB) and transparent heat-treated inner bamboo (THIB) could reach about 11%, and the transmittance of transparent outer bamboo (TOB) and transparent heat-treated outer bamboo (THOB) was about 2%. The light transmittance had been significantly improved when compared with the original bamboo samples. The transmittances of the TB samples before and after heat treatment in different parts of bamboo were different. In the visible light irradiation range, the light transmittances of TB samples were as follows: TIB > THIB and THOB > TOB. Meanwhile, the tensile strength of TB was reduced, especially for TOB and THOB. In addition, TB has a wide range of raw materials, and the preparation process is environmentally friendly. It can be used for decorative materials in homes, buildings, etc., and has a great application potential.
Fatal Rattlesnake Envenomation in Northernmost Brazilian Amazon: A Case Report and Literature Overview
Authors: Medeiros Jilvando M. , Oliveira Isadora S. , Ferreira Isabela G. , Alexandre-Silva Gabriel Melo , Cerni Felipe A. , Zottich Umberto , B. Pucca Manuela
Published: April 2020

Snakebite envenomations are classified as Category A Neglected Tropical Diseases by the World Health Organization. In Brazil, 405 snake species are distributed among 11 families, with the genera Bothrops and Crotalus being the most studied and main responsible for severe and lethal envenomations. In the country, Crotalus genus (i.e., rattlesnakes) is represented by Crotalus durissus species, showing seven different subspecies distributed along the country, including Crotalus durissus ruruima, which inhabits Roraima, the Brazilian nothermost state from Amazon forest. Here, we report a fatal case of a severe envenomation following a rattlesnake bite. The patient presented classic crotalic neurological signs and symptoms such as ptosis, drooling of saliva, sluggishness, macroscopic hematuria, and oliguria, which evolved to acute kidney failure (AKF) and hemodynamic instability. Although the patient was treated with the specific antivenom therapy, the severe envenomation resulted in three cardiac arrests and death of the victim in less than 38 h. This study discusses the causes of the patient death, the features of rattlesnake venom-induced AKF, and shows evidences that the Brazilian crotalic antivenom should be improved to treat rattlesnake envenomations caused by C. d. ruruima venom in Roraima state.
Land Cover Change in the Central Region of the Lower Yangtze River Based on Landsat Imagery and the Google Earth Engine: A Case Study in Nanjing, China
Authors: Zhang Dong-Dong , Zhang Lei
Published: April 2020

Urbanization in China is progressing rapidly and continuously, especially in the newly developed metropolitan areas. The Google Earth Engine (GEE) is a powerful tool that can be used to efficiently investigate these changes using a large repository of available optical imagery. This work examined land-cover changes in the central region of the lower Yangtze River and exemplifies the application of GEE using the random forest classification algorithm on Landsat dense stacks spanning the 30 years from 1987 to 2017. Based on the obtained time-series land-cover classification results, the spatiotemporal land-use/cover changes were analyzed, as well as the main factors driving the changes in different land-cover categories. The results show that: (1) The obtained land datasets were reliable and highly accurate, with an overall accuracy ranging from 88% to 92%. (2) Over the past 30 years, built-up areas have continued to expand, increasing from 537.9 km2 to 1500.5 km2, and the total area occupied by built-up regions has expanded by 178.9% to occupy an additional 962.7 km2. The surface water area first decreased, then increased, and generally showed an increasing trend, expanding by 17.9%, with an area increase of approximately 131 km2. Barren areas accounted for 6.6% of the total area in the period 2015–2017, which was an increase of 94.8% relative to the period 1987–1989. The expansion of the built-up area was accompanied by an overall 25.6% (1305.7 km2) reduction in vegetation. (3) The complexity of the key factors driving the changes in the regional surface water extent was made apparent, mainly including the changes in runoff of the Yangtze River and the construction of various water conservancy projects. The effects of increasing the urban population and expanding industrial development were the main factors driving the expansion of urban built-up areas and the significant reduction in vegetation. The advantages and limitations arising from land-cover mapping by using the Google Earth Engine are also discussed.
Mechanical, Electrical, and Piezoresistive Sensing Characteristics of Epoxy-Based Composites Incorporating Hybridized Networks of Carbon Nanotubes, Graphene, Carbon Nanofibers, or Graphite Nanoplatelets
Authors: Wang XiaoDong , Wang JianChao , Biswas Swarup , Kim Hyeok , Nam IlWoo
Published: April 2020

The present study compared the mechanical, electrical, morphological, and piezoresistive characteristics of epoxy-based sensing nanocomposites fabricated with inclusions of hybridized networks of four different carbon nanomaterials (CNMs), such as carbon nanotube (CNT), graphene, carbon nanofiber (CNF), and graphite nanoplatelet (GNP). Enhancements in elastic modulus and electrical conductivity were achieved by CNT–graphene composites and CNT–CNF composites, and these were explained by the morphological observations carried out in the present study and experimental studies found in the literature. The greatest gauge factor was accomplished by the CNT–GNP composite, followed by the CNT–CNF composite among composites where the CNM networks were sufficiently formed with a content ratio of 3%. The two types of the composites outperformed the composites incorporating solely CNT in terms of gauge factor, and this superiority was explained with the excluded volume theory.
Gait Characteristics Based on Shoe-Type Inertial Measurement Units in Healthy Young Adults during Treadmill Walking
Authors: Lee Myeounggon , Youm Changhong , Noh Byungjoo , Park Hwayoung
Published: April 2020

This study investigated the gait characteristics of healthy young adults using shoe-type inertial measurement units (IMU) during treadmill walking. A total of 1478 participants were tested. Principal component analyses (PCA) were conducted to determine which principal components (PCs) best defined the characteristics of healthy young adults. A non-hierarchical cluster analysis was conducted to evaluate the essential gait ability, according to the results of the PC1 score. One-way repeated analysis of variance with the Bonferroni correction was used to compare gait performances in the cluster groups. PCA outcomes indicated 76.9% variance for PC1–PC6, where PC1 (gait variability (GV): 18.5%), PC2 (pace: 17.8%), PC3 (rhythm and phase: 13.9%), and PC4 (bilateral coordination: 11.2%) were the gait-related factors. All of the pace, rhythm, GV, and variables for bilateral coordination classified the gait ability in the cluster groups. We suggest that the treadmill walking task may be reliable to evaluate the gait performances, which may provide insight into understanding the decline of gait ability. The presented results are considered meaningful for understanding the gait patterns of healthy adults and may prove useful as reference outcomes for future gait analyses.
Pre-Pressure Optimization for Ultrasonic Motors Based on Multi-Sensor Fusion
Authors: Chen Ning , Zheng Jieji , Fan Dapeng
Published: April 2020

This paper investigates the pre-pressure’s influence on the key performance of a traveling wave ultrasonic motor (TRUM) using simulations and experimental tests. An analytical model accompanied with power dissipation is built, and an electric cylinder is first adopted in regulating the pre-pressure rapidly, flexibly and accurately. Both results provide several new features for exploring the function of pre-pressure. It turns out that the proportion of driving zone within the contact region declines as the pre-pressure increases, while a lower power dissipation and slower temperature rise can be achieved when the driving zones and the braking zones are in balance. Moreover, the shrinking speed fluctuations with the increasing pre-pressures are verified by the periodic-varying axial pressure. Finally, stalling torque, maximum efficiency, temperature rise and speed variance are all integrated to form a novel optimization criterion, which achieves a slower temperature rise and lower stationary error between 260 and 320 N. The practical speed control errors demonstrate that the proportion of residual error declines from 2.88% to 0.75% when the pre-pressure is changed from 150 to 300 N, which serves as one of the pieces of evidence of the criterion’s effectiveness.
Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions
Authors: Hoffmann Martin W. , Wildermuth Stephan , Gitzel Ralf , Boyaci Aydin , Gebhardt Jörg , Kaul Holger , Amihai Ido , Forg Bodo , Suriyah Michael , Leibfried Thomas , Stich Volker , Hicking Jan , Bremer Martin , Kaminski Lars , Beverungen Daniel , zur Heiden Philipp , Tornede Tanja
Published: April 2020

The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
A Visual Attentive Model for Discovering Patterns in Eye-Tracking Data—A Proposal in Cultural Heritage
Authors: Pierdicca Roberto , Paolanti Marina , Quattrini Ramona , Mameli Marco , Frontoni Emanuele
Published: April 2020

In the Cultural Heritage (CH) context, art galleries and museums employ technology devices to enhance and personalise the museum visit experience. However, the most challenging aspect is to determine what the visitor is interested in. In this work, a novel Visual Attentive Model (VAM) has been proposed that is learned from eye tracking data. In particular, eye-tracking data of adults and children observing five paintings with similar characteristics have been collected. The images are selected by CH experts and are—the three “Ideal Cities” (Urbino, Baltimore and Berlin), the Inlaid chest in the National Gallery of Marche and Wooden panel in the “Studiolo del Duca” with Marche view. These pictures have been recognized by experts as having analogous features thus providing coherent visual stimuli. Our proposed method combines a new coordinates representation from eye sequences by using Geometric Algebra with a deep learning model for automated recognition (to identify, differentiate, or authenticate individuals) of people by the attention focus of distinctive eye movement patterns. The experiments were conducted by comparing five Deep Convolutional Neural Networks (DCNNs), yield high accuracy (more than 80 %), demonstrating the effectiveness and suitability of the proposed approach in identifying adults and children as museums’ visitors.
Estimating Exerted Hand Force via Force Myography to Interact with a Biaxial Stage in Real-Time by Learning Human Intentions: A Preliminary Investigation
Authors: Zakia Umme , Menon Carlo
Published: April 2020

Force myography (FMG) signals can read volumetric changes of muscle movements, while a human participant interacts with the environment. For collaborative activities, FMG signals could potentially provide a viable solution to controlling manipulators. In this paper, a novel method to interact with a two-degree-of-freedom (DoF) system consisting of two perpendicular linear stages using FMG is investigated. The method consists in estimating exerted hand forces in dynamic arm motions of a participant using FMG signals to provide velocity commands to the biaxial stage during interactions. Five different arm motion patterns with increasing complexities, i.e., “x-direction”, “y-direction”, “diagonal”, “square”, and “diamond”, were considered as human intentions to manipulate the stage within its planar workspace. FMG-based force estimation was implemented and evaluated with a support vector regressor (SVR) and a kernel ridge regressor (KRR). Real-time assessments, where 10 healthy participants were asked to interact with the biaxial stage by exerted hand forces in the five intended arm motions mentioned above, were conducted. Both the SVR and the KRR obtained higher estimation accuracies of 90–94% during interactions with simple arm motions (x-direction and y-direction), while for complex arm motions (diagonal, square, and diamond) the notable accuracies of 82–89% supported the viability of the FMG-based interactive control.
Deep Learning to Unveil Correlations between Urban Landscape and Population Health
Authors: Pala Daniele , Caldarone Alessandro Aldo , Franzini Marica , Malovini Alberto , Larizza Cristiana , Casella Vittorio , Bellazzi Riccardo
Published: April 2020

The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Several diseases such as asthma and cardiovascular conditions are becoming more diffuse, due to a rise in pollution exposure and a more sedentary lifestyle. Healthcare providers deal with increasing new challenges, and thanks to fast-developing big data technologies, they can be faced with systems that provide direct support to citizens. In this context, within the EU-funded Participatory Urban Living for Sustainable Environments (PULSE) project, we are implementing a data analytic platform designed to provide public health decision makers with advanced approaches, to jointly analyze maps and geospatial information with healthcare and air pollution data. In this paper we describe a component of such platforms, which couples deep learning analysis of urban geospatial images with healthcare indexes collected by the 500 Cities project. By applying a pre-learned deep Neural Network architecture, satellite images of New York City are analyzed and latent feature variables are extracted. These features are used to derive clusters, which are correlated with healthcare indicators by means of a multivariate classification model. Thanks to this pipeline, it is possible to show that, in New York City, health care indexes are significantly correlated to the urban landscape. This pipeline can serve as a basis to ease urban planning, since the same interventions can be organized on similar areas, even if geographically distant.
Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion
Authors: Liu Long , Qiu Sen , Wang ZheLong , Li Jie , Wang JiaXin
Published: April 2020

Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist’s motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist’s attitude information after sensor calibration, and then the motions of canoeist’s actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learning algorithm was used as the classification method to divide the stroke cycle into different phases, including propulsion-phase and recovery-phase, a quantitative kinematic analysis was carried out. Experiments conducted in this paper demonstrated that our method possesses the capacity to reveal the similarities and differences between novice and coach, the whole process of canoeist’s motions can be analyzed with satisfactory accuracy validated by videography method. It can provide quantitative data for coaches or athletes, which can be used to improve the skills of rowers.
DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding
Authors: Krasovsky Tal , Weiss Patrice L. , Zuckerman Oren , Bar Avihay , Keren-Capelovitch Tal , Friedman Jason
Published: April 2020

Clinically feasible assessment of self-feeding is important for adults and children with motor impairments such as stroke or cerebral palsy. However, no validated assessment tool for self-feeding kinematics exists. This work presents an initial validation of an instrumented spoon (DataSpoon) developed as an evaluation tool for self-feeding kinematics. Ten young, healthy adults (three male; age 27.2 ± 6.6 years) used DataSpoon at three movement speeds (slow, comfortable, fast) and with three different grips: “natural”, power and rotated power grip. Movement kinematics were recorded concurrently using DataSpoon and a magnetic motion capture system (trakSTAR). Eating events were automatically identified for both systems and kinematic measures were extracted from yaw, pitch and roll (YPR) data as well as from acceleration and tangential velocity profiles. Two-way, mixed model Intraclass correlation coefficients (ICC) and 95% limits of agreement (LOA) were computed to determine agreement between the systems for each kinematic variable. Most variables demonstrated fair to excellent agreement. Agreement for measures of duration, pitch and roll exceeded 0.8 (excellent agreement) for >80% of speed and grip conditions, whereas lower agreement (ICC < 0.46) was measured for tangential velocity and acceleration. A bias of 0.01–0.07 s (95% LOA [−0.54, 0.53] to [−0.63, 0.48]) was calculated for measures of duration. DataSpoon enables automatic detection of self-feeding using simple, affordable movement sensors. Using movement kinematics, variables associated with self-feeding can be identified and aid clinical reasoning for adults and children with motor impairments.
Miniaturized 3D Depth Sensing-Based Smartphone Light Field Camera
Authors: Kim Hyun Myung , Kim Min Seok , Lee Gil Ju , Jang Hyuk Jae , Song Young Min
Published: April 2020

The miniaturization of 3D depth camera systems to reduce cost and power consumption is essential for their application in electrical devices that are trending toward smaller sizes (such as smartphones and unmanned aerial systems) and in other applications that cannot be realized via conventional approaches. Currently, equipment exists for a wide range of depth-sensing devices, including stereo vision, structured light, and time-of-flight. This paper reports on a miniaturized 3D depth camera based on a light field camera (LFC) configured with a single aperture and a micro-lens array (MLA). The single aperture and each micro-lens of the MLA serve as multi-camera systems for 3D surface imaging. To overcome the optical alignment challenge in the miniaturized LFC system, the MLA was designed to focus by attaching it to an image sensor. Theoretical analysis of the optical parameters was performed using optical simulation based on Monte Carlo ray tracing to find the valid optical parameters for miniaturized 3D camera systems. Moreover, we demonstrated multi-viewpoint image acquisition via a miniaturized 3D camera module integrated into a smartphone.
Leading Schools towards Sustainability. Fields of Action and Management Strategies for Principals
Authors: Müller Ulrich , Lude Armin , Hancock Dawson R.
Published: April 2020

Education is expected to support the development of a more sustainable way of thinking, working, and living. Although there is a broad range of literature on Education for Sustainable Development (ESD), the role of principals in the implementation of sustainability and ESD in schools has rarely been taken into consideration. However, based on the results of school effectiveness research, one can assume that school principals exert a significant influence on ESD. Sustainability is a leadership issue. When a school aims at integrating sustainability and ESD, the principal plays a pivotal role. She or he has to support the endeavor wholeheartedly and credibly, organize a participative process of school development, emphasize sustainability and ESD in the daily life of the school, support teaching staff in the application of ESD, and offer students opportunities to launch their own initiatives. This article for the special issue on “Sustainability in leadership and education” is a theoretical concept paper based on a literature review and the authors’ conceptual work. It offers a model and seeks to support principals in leading their schools towards sustainability. Therefore, a framework of four stages of the integration of sustainability and ESD in a school is defined. For each of these stages, a number of practical actions and management strategies are suggested and explained in detail.
Hydrodynamics Interactions of Metachronal Waves on Particulate-Liquid Motion through a Ciliated Annulus: Application of Bio-Engineering in Blood Clotting and Endoscopy
Authors: Bhatti Muhammad Mubashir , Elelamy Asmaa F. , M. Sait Sadiq , Ellahi Rahmat
Published: April 2020

This study deals with the mass transport phenomena on the particle-fluid motion through an annulus. The non-Newtonian fluid propagates through a ciliated annulus in the presence of two phenomenon, namely (i) endoscopy, and (ii) blood clot. The outer tube is ciliated. To examine the flow behavior we consider the bi-viscosity fluid model. The mathematical modeling has been formulated for small Reynolds number to examine the inertia free flow. The purpose of this assumption is that wavelength-to-diameter is maximal, and the pressure could be considerably uniform throughout the entire cross-section. The resulting equations are analytically solved, and exact solutions are given for particle- and fluid-phase profiles. Computational software Mathematica has been used to evaluate both the closed-form and numerical results. The graphical behavior across each parameter has been discussed in detail and presented with graphs. The trapping mechanism is also shown across each parameter. It is noticed clearly that particle volume fraction and the blood clot reveal converse behavior on fluid velocity; however, the velocity of the fluid reduced significantly when the fluid behaves as a Newtonian fluid. Schmidt and Soret numbers enhance the concentration mechanism. Furthermore, more pressure is required to pass the fluid when the blood clot appears.
A Nonlinear Convergence Consensus: Extreme Doubly Stochastic Quadratic Operators for Multi-Agent Systems
Authors: Abdulghafor Rawad , Almotairi Sultan , Almohamedh Hamad , Almutairi Badr , Bajahzar Abdullah , Almutairi Sulaiman Sulmi
Published: April 2020

We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic operators (EDSQO), based on majorization theory and Markov chains for time-varying multi-agent distributed systems. We describe a dynamic system that has a local interaction network among agents. EDSQO has been applied for distributed agent systems, on a finite dimensional stochastic matrix. We prove that multi-agent systems converge at a center (common value) via the extreme waited value of doubly stochastic quadratic operators (DSQO), which are only 1 or 0 or 1/2 1 2 if the exchanges of each agent member has no selfish communication. Applying this rule means that the consensus is nonlinear and low-complexity computational for fast time convergence. The investigated nonlinear model of EDSQO follows the structure of the DeGroot linear (DGL) consensus model. However, EDSQO is nonlinear and faster convergent than the DGL model and is of lower complexity than DSQO and cubic stochastic quadratic operators (CSQO). The simulation result and theoretical proof are illustrated.
Pattern Recognition of Single-Channel sEMG Signal Using PCA and ANN Method to Classify Nine Hand Movements
Authors: Arozi Moh , Caesarendra Wahyu , Ariyanto Mochammad , Munadi M. , Setiawan Joga D. , Glowacz Adam
Published: April 2020

A number of researchers prefer using multi-channel surface electromyography (sEMG) pattern recognition in hand gesture recognition to increase classification accuracy. Using this method can lead to computational complexity. Hand gesture classification by employing single channel sEMG signal acquisition is quite challenging, especially for low-rate sampling frequency. In this paper, a study on the pattern recognition method for sEMG signals of nine finger movements is presented. Common surface single channel electromyography (sEMG) was used to measure five different subjects with no neurological or muscular disorder by having nine hand movements. This research had several sequential processes (i.e., feature extraction, feature reduction, and feature classification). Sixteen time-domain features were employed for feature extraction. The features were then reduced using principal component analysis (PCA) into two and three-dimensional feature space. The artificial neural network (ANN) classifier was tested on two different feature sets: (1) using all principal components obtained from PCA (PC1–PC3) and (2) using selected principal components (PC2 and PC3). The third best principal components were then used for classification using ANN. The average accuracy using all subject signals was 86.7% to discriminate the nine finger movements.
An Approach for Studying Asymptotic Properties of Solutions of Neutral Differential Equations
Authors: Bazighifan Omar
Published: April 2020

The paper is devoted to the study of oscillation of even-order neutral differential equations. New Kamenev-type oscillation criteria are established, and they essentially improve and complement some the well-known results reported in the literature. Ideas of symmetry help us determine the correct ways to study these topics and show us the correct direction, because they are often invisible. To illustrate the main results, some examples are mentioned.
A Fuzzy Bivariate Poisson Control Chart
Authors: Wibawati  , Mashuri Muhammad , Purhadi  , Irhamah
Published: April 2020

In the present paper, we develop a fuzzy bivariate Poisson (FBP) control chart based on a fuzzy c chart. The FBP chart is used to monitor the sum of the nonconformities of each quality characteristic. There are two contributions of this work. First, we propose a new fuzzy parameter estimation to create a triangular fuzzy number (TFN). Second, our control chart is flexible, because we involve the α c u t to measure the level of tightness of inspection. Furthermore, the statistic of FBP is being able to visualise the monitoring process in a graphical form. In addition, the simulation study indicates that the performance of our proposed chart, based on average run length (ARL), is more sensitive than the performance of a conventional bivariate Poisson (BP) chart. Moreover, an illustration example shows that the FBP chart has relatively more sensitive performance compared to the conventional BP chart.
Space-Efficient Prime Knot 7-Mosaics
Authors: Heap Aaron , LaCourt Natalie
Published: April 2020

The concepts of tile number and space-efficiency for knot mosaics were first explored by Heap and Knowles in 2018, where they determined the possible tile numbers and space-efficient layouts for every prime knot with mosaic number 6 or less. In this paper, we extend those results to prime knots with mosaic number 7. Specifically, we find the possible values for the number of non-blank tiles used in a space-efficient 7 × 7 mosaic of a prime knot are 27, 29, 31, 32, 34, 36, 37, 39, and 41. We also provide the possible layouts for the mosaics that lead to these values. Finally, we determine which prime knots can be placed within the first of these layouts, resulting in a list of knots with mosaic number 7 and tile number 27.