bluuebunny/crossref_metadata_2025 huggingface dataset:
Application Status of Sacrificial Biomaterials in 3D Bioprinting
Authors: Liu Siyu , Wang Tianlin , Li Shenglong , Wang Xiaohong
Published: May 2022

Additive manufacturing, also known as three-dimensional (3D) printing, relates to several rapid prototyping (RP) technologies, and has shown great potential in the manufacture of organoids and even complex bioartificial organs. A major challenge for 3D bioprinting complex org unit ans is the competitive requirements with respect to structural biomimeticability, material integrability, and functional manufacturability. Over the past several years, 3D bioprinting based on sacrificial templates has shown its unique advantages in building hierarchical vascular networks in complex organs. Sacrificial biomaterials as supporting structures have been used widely in the construction of tubular tissues. The advent of suspension printing has enabled the precise printing of some soft biomaterials (e.g., collagen and fibrinogen), which were previously considered unprintable singly with cells. In addition, the introduction of sacrificial biomaterials can improve the porosity of biomaterials, making the printed structures more favorable for cell proliferation, migration and connection. In this review, we mainly consider the latest developments and applications of 3D bioprinting based on the strategy of sacrificial biomaterials, discuss the basic principles of sacrificial templates, and look forward to the broad prospects of this approach for complex organ engineering or manufacturing.
Cryo-Structuring of Polymeric Systems. Poly(Vinyl Alcohol)-Based Cryogels Loaded with the Poly(3-hydroxybutyrate) Microbeads and the Evaluation of Such Composites as the Delivery Vehicles for Simvastatin
Authors: Michurov Dmitrii A. , Makhina Tatiana K. , Siracusa Valentina , Bonartsev Anton P. , Lozinsky Vladimir I. , Iordanskii Alexey L.
Published: May 2022

Highly porous composite poly(vinyl alcohol) (PVA) cryogels loaded with the poly(3-hydroxybutyrate) (PHB) microbeads containing the drug, simvastatin (SVN), were prepared via cryogenic processing (freezing—storing frozen—defrosting) of the beads’ suspensions in aqueous PVA solution. The rigidity of the resultant composite cryogels increased with increasing the filler content. Optical microscopy of the thin section of such gel matrices revealed macro-porous morphology of both continuous (PVA cryogels) and discrete (PHB-microbeads) phases. Kinetic studies of the SVN release from the drug-loaded microbeads, the non-filled PVA cryogel and the composite material showed that the cryogel-based composite system could potentially serve as a candidate for the long-term therapeutic system for controlled drug delivery. Such PHB-microbeads-containing PVA-cryogel-based composite drug delivery carriers were unknown earlier; their preparation and studies have been performed for the first time.
Cross-Linking of Polypropylene with Thiophene and Imidazole
Authors: Muljana Henky , Remerie Klaas , Boven Gert , Picchioni Francesco , Bose Ranjita K.
Published: May 2022

In this work, two novel routes to synthesis cross-linked polypropylene (PP) are introduced by using two different precursors (2-thiophenemethyl amine (TMA) and 1-(3 aminopropyl) imidazole (API)), both cross-linked with 1,1′-(methylenedi-4,1-phenylene) bismaleimide (BM) at two different annealing temperature values (T = 50 °C and T = 150 °C). Both Diels–Alder (DA) and Michael addition reactions were successfully performed with TMA and API, respectively, albeit with different reactivity. Imidazole clearly shows a higher reactivity compared to thiophene. In addition, an increase in annealing temperature leads to a higher degree of cross-linking. The highest degree of cross-linking was obtained by the imidazole product after annealing at 150 °C (IMG1A150) as evident from the highest complex viscosity (|η*|) value of IMG1A150. A difference in rheology and thermal properties between the imidazole and thiophene cross-linked products was also observed. However, both products have superior melt properties and thermal stability compared with the starting material. They show processability at high temperatures. The melt flow behavior and de-cross-linking at higher temperatures can be tuned depending on the choice of imidazole or thiophene. This study shows an advance on the cross-linked PP processing and its product performances for further application on the commercial scale.
Room-Temperature Solid-State UV Cross-Linkable Vitrimer-like Polymers for Additive Manufacturing
Authors: Chen Jian , Wen Ya , Zeng Lingyi , Wang Xinchun , Chen Hongmei , Huang Wei Min , Bai Yuefeng , Yu Wenhao , Zhao Keqing , Hu Ping
Published: May 2022

In this paper, a UV cross-linkable vitrimer-like polymer, ureidopyrimidinone functionalized telechelic polybutadiene, is reported. It is synthesized in two steps. First, 2(6-isocyanatohexylaminocarbonylamino)-6-methyl-4[1H]-pyrimidinone (UPy-NCO) reacts with hydroxy-functionalized polybutadiene (HTPB) to obtain UPy-HTPB-UPy, and then the resulted UPy-HTPB-UPy is cross-linked under 365 nm UV light (photo-initiator: bimethoxy-2-phenylacetophenone, DMPA). Further investigation reveals that the density of cross-linking and mechanical properties of the resulting polymers can be tailored via varying the amount of photo-initiator and UV exposure time. Before UV cross-linking, UPy-HTPB-UPy is found to be vitrimer-like due to the quadruple hydrogen-bonding interactions. The UPy groups at the end of the chain also enable for rapid solidification upon the evaporation of the solvent. The unsaturated double bonds in the HTPB chains enable UPy-HTPB-UPy to be UV cross-linkable in the solid state at room temperature. After cross-linking, the polymers have good shape memory effect (SME). Here, we demonstrate that this type of polymer can have many potential applications in additive manufacturing. In the cases of fused deposition modelling (FDM) and direct ink writing (DIW), not only the strength of the interlayer bonding but also the strength of the polymer itself can be enhanced via UV exposure (from thermoplastic to thermoset) either during printing or after printing. The SME after cross-linking further helps to achieve rapid volumetric additive manufacturing anytime and anywhere.
Valorization of Starch to Biobased Materials: A Review
Authors: Falua Kehinde James , Pokharel Anamol , Babaei-Ghazvini Amin , Ai Yongfeng , Acharya Bishnu
Published: May 2022

Many concerns are being expressed about the biodegradability, biocompatibility, and long-term viability of polymer-based substances. This prompted the quest for an alternative source of material that could be utilized for various purposes. Starch is widely used as a thickener, emulsifier, and binder in many food and non-food sectors, but research focuses on increasing its application beyond these areas. Due to its biodegradability, low cost, renewability, and abundance, starch is considered a “green path” raw material for generating porous substances such as aerogels, biofoams, and bioplastics, which have sparked an academic interest. Existing research has focused on strategies for developing biomaterials from organic polymers (e.g., cellulose), but there has been little research on its polysaccharide counterpart (starch). This review paper highlighted the structure of starch, the context of amylose and amylopectin, and the extraction and modification of starch with their processes and limitations. Moreover, this paper describes nanofillers, intelligent pH-sensitive films, biofoams, aerogels of various types, bioplastics, and their precursors, including drying and manufacturing. The perspectives reveal the great potential of starch-based biomaterials in food, pharmaceuticals, biomedicine, and non-food applications.
Research on Preparation of Three-Component Composite Fiber with Complex Cross-Sectional Pattern
Authors: Zhang Ronggen , Feng Pei , Yang Chongchang
Published: May 2022

In this work, a preparation method of three-component composite fibers with complex cross-sectional patterns was proposed, and the fibers with complex cross-sectional patterns were fabricated using melt spinning. Initially, inspired by the shape of a fishbone, a spinning pack with three-component melt channels was designed for spinning fibers with a “fishbone” cross-sectional pattern. Then, the numerical simulation of the melt flow in the channels of the spinning pack was performed using Polyflow software. The spinning pack structure was optimized by analyzing the flow velocity distribution and shear rate distribution of different components within the spinning pack channels. The results showed that smaller velocity fluctuations contribute to the clarity of the cross-sectional pattern. Thereafter, the spinning experiments were carried out based on the optimized spinning pack. The effect of the flow ratio between the three components on the cross-sectional pattern was discussed, and the three-component composite fibers with a clear “fishbone” cross-sectional pattern were obtained. Finally, in order to further study the effectiveness of the complex cross-sectional pattern fiber preparation proposed in this paper, another spinning pack for fibers with an “H-shaped” cross-sectional pattern was designed according to the aforementioned method, and spinning experiments were carried out. The SEM images of the cross-sections of fibers with “fishbone” and “H-shaped” cross-sectional patterns were obtained, verifying the feasibility of the method proposed in this paper. Moreover, the fibers with complex cross-sectional patterns obtained by this method have a certain anti-counterfeiting effect and can also be blended with other yarns to obtain fabrics with anti-counterfeiting effects.
Behaviour of Hybrid Fibre-Reinforced Ternary Blend Geopolymer Concrete Beam-Column Joints under Reverse Cyclic Loading
Authors: Sathish Kumar Veerappan , Ganesan Namasivayam , Indira Pookattu Vattarambath , Murali Gunasekaran , Vatin Nikolai Ivanovich
Published: May 2022

Beam–column joints are extremely vulnerable to lateral and vertical loads in reinforced concrete (RC) structures. This insufficiency in joint performance can lead to the failure of the whole structure in the event of unforeseen seismic and wind loads. This experimental work was conducted to study the behaviour of ternary blend geopolymer concrete (TGPC) beam-column joints with the addition of hybrid fibres, viz., steel and polypropylene fibres, under reverse cyclic loads. Nine RC beam-column joints were prepared and tested under reverse cyclic loading to recreate the conditions during an earthquake. M55 grade TGPC was designed and used in this present study. The primary parameters studied in this experimental investigation were the volume fractions of steel fibres (0.5% and 1.0%) and polypropylene fibres, viz., 0.1 to 0.25%, with an increment of 0.05%. In this study, the properties of hybrid fibre-reinforced ternary blend geopolymer concrete (HTGPC) beam-column joints, such as their ductility, energy absorption capacity, initial crack load and peak load carrying capacity, were investigated. The test results imply that the hybridisation of fibres effectively enhances the joint performance of TGPC. Also, an effort was made to compare the shear strength of HTGPC beam-column connections with existing equations from the literature. As the available models did not match the actual test results, a method was performed to obtain the shear strength of HTGPC beam-column connections. The developed equation was found to compare convincingly with the experimental test results.
Perfluorocarbon Nanodroplets for Dual Delivery with Ultrasound/GSH-Responsive Release of Model Drug and Passive Release of Nitric Oxide
Authors: Choi Moonhyun , Jazani Arman Moini , Oh Jung Kwon , Noh Seung Man
Published: May 2022

Nitric oxide (NO) plays a critical role as an important signaling molecule for a variety of biological functions, particularly inhibiting cell proliferation or killing target pathogens. To deliver active radical NO gaseous molecule whose half-life is a few seconds in a stable state, the design and development of effective exogenous NO supply nanocarriers are essential. Additionally, the delivery of desired drugs with NO can produce synergistic effects. Herein, we report a new approach that allows for the fabrication of dual ultrasound (US)/glutathione (GSH)-responsive perfluorocarbon (PFC) nanodroplets for the controlled release of model drug and passive release of safely incorporated NO. The approach centers on the synthesis of a disulfide-labeled amphiphilic block copolymer and its use as a GSH-degradable macromolecular emulsifier for oil-in-water emulsification process of PFC. The fabricated PFC nanodroplets are colloidally stable and enable the encapsulation of both NO and model drugs. Encapsulated drug molecules are synergistically released when ultrasound and GSH are presented, while NO molecules are passively but rapidly released. Our preliminary results demonstrate that the approach is versatile and can be extended to not only GSH-responsive but also other stimuli-responsive block copolymers, thereby allowing for the fabrication of broad choices of stimuli-responsive (smart) PFC-nanodroplets in aqueous solution for dual delivery of drug and NO therapeutics.
Optimization of Variable Stiffness Joint in Robot Manipulator Using a Novel NSWOA-MARCOS Approach
Authors: Shanmugasundar G. , Fegade Vishal , Mahdal Miroslav , Kalita Kanak
Published: May 2022

Robots and robotic systems have become an inevitable part of modern industrial settings. Robotics systems are being introduced for various household services as well. As the interactions between the workspace of robots and humans increases, there is an increased likelihood of unintended harm being caused by the robots to humans due to collisions or abrupt contact. To mitigate this, active and passive compliant mechanisms must be introduced in these systems. In this study, a design optimization case study is carried out for the optimization of a passive compliance mechanism achieved with variable stiffness joints realized by the use of permanent magnets. Three design parameters of the systems, namely, inner stator width, outer stator width, and magnet height, are considered. The objective is to minimize the weight and maximize the maximum torque. A nature-inspired metaheuristic hybridized with a multi-criteria decision-making method is introduced to achieve this. The Non-dominated Sorting Whale Optimization Algorithm (NSWOA) is used for Pareto optimal front generation and MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) is applied to extract the best feasible solution from the Pareto front. We observed 1.8% and 41% improvements as compared to the previous known best design and original design, respectively.
Study on Performance Improvement of Sodium Acetate Trihydrate in Thermal Energy Storage System by Disturbance
Authors: Wang Suyaola , Wang Chuang , Hussain Muhammad Bilal , Cheng Xingxing , Wang Zhiqiang
Published: May 2022

Phase change materials (PCM) have been widely used in Thermal Energy Storage (TES) Systems. Considering the energy efficiency and the use of domestic hot water, the melting temperature range of phase change materials is considered to be optimal in the range of 50–60 °C. The most commonly used is sodium acetate trihydrate-based phase change material, which has the advantages of high latent heat and low price, but its high supercooling, low thermal conductivity, and phase separation affect its application. Therefore, this paper used sodium acetate trihydrate, disodium hydrogen phosphate dodecahydrate (DSP), and expanded graphite (EG) as raw materials to prepare composite phase change materials (CPCM) and used physical disturbance to further improve their properties. Firstly, their thermophysical properties were investigated by the step cooling curve method, differential scanning calorimetry (DSC), and x-ray diffraction (XRD). Secondly, in order to further evaluate the effect of physical disturbance on CPCM crystallization, further experimental studies were carried out by adjusting the rotor mass and rotational speed. The experimental results showed that when 1.5 wt.% DSP, 1.5 wt.% EG and physical perturbation work together, the CPCM phase transition temperature is 56.7 °C, and the latent heat is as high as 258.98 kJ/kg. At this time, its thermal conductivity increased from 0.62 w/m·k to 1.1625 w/m·k, and its subcooling degree decreased from above 20 °C to less than 0.5 °C, and no phase separation occurred. The greater the disturbance momentum (the greater the rotor mass or the greater the rotational speed), the shorter the induction time, which is more conducive to the crystallization of CPCM. The results obtained in this paper are instructive for the preparation of efficient new CPCMs.
Spermidine Binding to the Acetinobacter baumannii Efflux Protein AceI Observed by Near-UV Synchrotron Radiation Circular Dichroism Spectroscopy
Authors: Patching Simon G.
Published: May 2022

The aim of this work was to test polyamines as potential natural substrates of the Acinetobacter baumannii chlorhexidine efflux protein AceI using near-UV synchrotron radiation circular dichroism (SRCD) spectroscopy. The Gram-negative bacterium A. Baumannii is a leading cause of hospital-acquired infections and an important foodborne pathogen. A. Baumannii strains are becoming increasingly resistant to antimicrobial agents, including the synthetic antiseptic chlorhexidine. AceI (144-residues) was the founding member of the recently recognised PACE family of bacterial multidrug efflux proteins. Using the plasmid construct pTTQ18-aceI(His6) containing the A. baumannii aceI gene directly upstream from a His6-tag coding sequence, expression of AceI(His6) was amplified in E. coli BL21(DE3) cells. Near-UV (250–340 nm) SRCD measurements were performed on detergent-solubilised and purified AceI(His6) at 20 °C. Sample and SRCD experimental conditions were identified that detected binding of the triamine spermidine to AceI(His6). In a titration with spermidine (0–10 mM), this binding was saturable and fitting of the curve for the change in signal intensity produced an apparent binding affinity (KD) of 3.97 ± 0.45 mM. These SRCD results were the first experimental evidence obtained for polyamines as natural substrates of PACE proteins.
Valorization of Microcrystalline Cellulose Using Heterogeneous Protonated Zeolite Catalyst: An Experimental and Kinetics Approach
Authors: Kassaye Samuel , Gupta Dinesh , Pant Kamal Kishore , Jain Sapna
Published: May 2022

This study aimed to valorize microcrystalline cellulose (MCC) using protonated zeolite catalysts such as (H-ZSM-5) and Cr/H-ZSM-5 (5%) in ionic liquid. The catalytic effect in synergy with 1-butyl-3-methylimidazolium Chloride ([BMIM] Cl) ionic liquid was studied in detail. The total reducing sugar (TRS) was determined using the 3, 5-dinitrisalcylic acid (DNS) array method. The catalysts were characterized using techniques such as Fourier transform infrared (FT-IR), X-ray diffraction analysis (XRD), temperature-programmed desorption of ammonia (NH3-TPD), and BET-surface area analyzer. H-ZSM-5 effectively depolymerized cellulose with a maximum yield of 70% total reducing sugar (34% glucose, 8% fructose, and 4.5% 5-HMF). Cr/H-ZSM-5 catalyst dehydrated fructose to 5-HMF with a yield of 53%. The use of ionic liquid significantly reduced the activation energy of formation and decomposition. The activation energy determined in cellulose hydrolysis was 85.83 KJ mol−1 for a reaction time of 180 min while the decomposition energy was found to be 42.5 kJ mol−1.
Identifying Future Skill Requirements of the Job Profiles for a Sustainable European Manufacturing Industry 4.0
Authors: Akyazi Tugce , del Val Patricia , Goti Aitor , Oyarbide Aitor
Published: May 2022

The exponential growth of digitalisation and the continuous increase in sustainability needs are currently reshaping the European manufacturing industry through its entire value chain. Industrial sectors have undergone significant changes globally in recent years, and they will continue to face this deep transformation. The manufacturing sectors, more specifically, companies, need to develop a relevant strategy that can support their organisation to handle the upcoming future technological developments and sustainability requirements properly. In order to implement the strategy effectively and achieve an adequate digital and green transformation, their main focus should be the development of a multi-skilled workforce. This competent workforce can only be built by foreseeing the changes in the needed skills for the manufacturing industry and then updating the skills of the current workforce accordingly. As an answer to this need, we developed an automated skill database for the manufacturing industry, particularly transversal occupations of this sector related to the industrial symbiosis (IS) and energy efficiency (EE). Differently from the conventional ones, the generated database incorporated not only the current but also the future skill needs for each profile. During the development of the future skills for each occupation in the database, we identified the foreseen skill needs for the manufacturing industry through detailed desk research. Therefore, this paper presents a valuable perspective on the subject. Our work aimed to fill the gap for a database specifically developed for the manufacturing industry, which provides the end-users with data about the new skills requirements resulting from industrial changes and sustainability needs. We believe that companies, education and training institutions and policymakers can make use of the generated database as a complementary tool for developing their training programmes or strategy roadmaps to cover the emerging changes in each individual industrial sector.
Estimating Copula-Based Extension of Tail Value-at-Risk and Its Application in Insurance Claim
Authors: Syuhada Khreshna , Neswan Oki , Josaphat Bony Parulian
Published: May 2022

Dependent Tail Value-at-Risk, abbreviated as DTVaR, is a copula-based extension of Tail Value-at-Risk (TVaR). This risk measure is an expectation of a target loss once the loss and its associated loss are above their respective quantiles but bounded above by their respective larger quantiles. In this paper, we propose nonparametric estimators for DTVaR and establish their property of consistency. Moreover, we also propose the variability measure around this expected value truncated by the quantiles, called the Dependent Conditional Tail Variance (DCTV). We use this measure for constructing confidence intervals of the DTVaR. Both parametric and nonparametric approaches for DTVaR estimations are explored. Furthermore, we assess the performance of DTVaR estimations using a proposed backtest based on the DCTV. As for the numerical study, we take an application in the insurance claim amount.
Smart Sticker Ultra-Low-Power Shock Detection in the Supply Chain
Authors: Matić Tomislav , Zidar Josip , Aleksi Ivan , Žagar Drago
Published: May 2022

This paper presents a shock detection device for packages in the supply chain. The primary purpose is to identify package damage during storage, delivery, and handling. Additionally, products are likely to be damaged if dropped from a certain height, which sometimes does not appear on the package. By continuously measuring package vibrations and detecting shocks in the supply chain, consumers can gain an insight into the state of the product upon delivery. This paper presents the Smart Sticker implementation for ultra-low-power shock detection in the supply chain. The overall energy consumption must be kept as low as possible while continuously sensing the presence of shock to ensure that the Smart Sticker’s battery lasts as long as possible. The Smart Sticker functions in three modes to meet the established constraints: low-power, active, and data transfer mode. While detecting the shock, the low-power mode uses the least amount of energy needed. If the shock exceeds the threshold, the Smart Sticker enters active mode, stores the detected g force value in memory, and then switches back to low-power mode. Finally, employing Near Field Communication (NFC) and energy harvesting, the data transfer mode allows the consumer to read the recorded data. The results show that the Smart Sticker for shock detection performs according to set requirements and successfully monitors and detects shock for packages in the supply chain.
Analysis of Magnetic Field Measurements for Indoor Positioning
Authors: Ouyang Guanglie , Abed-Meraim Karim
Published: May 2022

Infrastructure-free magnetic fields are ubiquitous and have attracted tremendous interest in magnetic field-based indoor positioning. However, magnetic field-based indoor positioning applications face challenges such as low discernibility, heterogeneous devices, and interference from ferromagnetic materials. This paper first analyzes the statistical characteristics of magnetic field (MF) measurements from heterogeneous smartphones. It demonstrates that, in the absence of disturbances, the MF measurements in indoor environments follow a Gaussian distribution with temporal stability and spatial discernibility. It shows the fluctuations in magnetic field intensity caused by the rotation of a smartphone around the Z-axis. Secondly, it suggests that the RLOWESS method can be used to eliminate magnetic field anomalies, using magnetometer calibration to ensure consistent MF measurements in heterogeneous smartphones. Thirdly, it tests the magnetic field positioning performance of homogeneous and heterogeneous devices using different machine learning methods. Finally, it summarizes the feasibility/limitations of using only MF measurement for indoor positioning.
Optimization of the NRCS Sampling at the Sea Wind Retrieval by the Airborne Rotating-Beam Scatterometer Mounted under Fuselage
Authors: Nekrasov Alexey , Khachaturian Alena , Vorobev Evgenii
Published: May 2022

The optimization of normalized radar cross-section (NRCS) sampling by a scatterometer allows an increase in the accuracy of the wind retrieval over the water surface and a decrease in the time of the measurement. Here, we investigate the possibility of improving wind vector measurement with an airborne rotating-beam scatterometer mounted under the fuselage. For this purpose, we investigated NRCS sampling at various incidence angles, and the possibility of using NRCS samples obtained during simultaneous measurement at different incidence angles to perform wind retrieval. The proposed wind algorithms are based on a geophysical model function (GMF). Sea wind retrieval was carried out using Monte Carlo simulations with consideration of a single incidence angle or combinations of several incidence angles. The incidence angles of interest were 30°, 35°, 40°, 45°, 50°, 55°, and 60°. The simulation showed that the wind speed error decreased with an increase in the incidence angle, and the wind direction error tended to decrease with an increase in the incidence angle. The single incidence angle case is characterized by higher maximum wind retrieval errors but allows for a higher maximum altitude of the wind retrieval method’s applicability to be achieved. The use of several neighboring incidence angles allows a better wind vector retrieval accuracy to be achieved. The combinations of three and four incidence angles provided the lowest maximum wind speed and direction errors in the range of the incidence angles from 45° to 60° but, unfortunately, provide the lowest maximum altitude of applicability of the wind retrieval method. At the same time, the combination of two incidence angles is characterized by slightly higher maximum wind retrieval errors than in the cases of three and four incidence angles, but they are lower than in the case of the single incidence angle. Moreover, the two incidence angles’ combination is a simpler way to decrease the wind retrieval errors, especially for measurement near an incidence angle of 30°, providing nearly the highest maximum altitude of the wind retrieval method applicability. The results obtained can be used to enhance existing airborne radars and in the development of new remote sensing systems.
Real-Time Assessment of Mandarin Crop Water Stress Index
Authors: Appiah Sadick Amoakohene , Li Jiuhao , Lan Yubin , Darko Ransford Opoku , Alordzinu Kelvin Edom , Al Aasmi Alaa , Asenso Evans , Issaka Fuseini , Afful Ebenezer Acheampong , Wang Hao , Qiao Songyang
Published: May 2022

The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level of water stress in plants continuously and to provide automatic sensing and controls. This research aimed at determining the viability, efficiency, and swiftness in employing the commercial Workswell WIRIS Agro R infrared camera (WWARIC) in monitoring water stress and scheduling appropriate irrigation regimes in mandarin plants. The experiment used a four-by-three randomized complete block design with 80–100% FC water treatment as full field capacity and three deficit irrigation treatments at 70–75% FC, 60–65% FC, and 50–55% FC. Air temperature, canopy temperature, and vapor pressure deficits were measured and employed to deduce the empirical crop water stress index, using the Idso approach (CWSI(Idso)) as well as baseline equations to calculate non-water stress and water stressed conditions. The relative leaf water content (RLWC) of mandarin plants was also determined for the growing season. From the experiment, CWSI(Idso) and CWSI were estimated using the Workswell Wiris Agro R infrared camera (CWSIW) and showed a high correlation (R2 = 0.75 at p < 0.05) in assessing the extent of water stress in mandarin plants. The results also showed that at an altitude of 12 m above the mandarin canopy, the WWARIC was able to identify water stress using three modes (empirical, differential, and theoretical). The WWARIC’s color map feature, presented in real time, makes the camera a suitable device, as there is no need for complex computations or expert advice before determining the extent of the stress the crops are subjected to. The results prove that this novel use of the WWARIC demonstrated sufficient precision, swiftness, and intelligibility in the real-time detection of the mandarin water stress index and, accordingly, assisted in scheduling irrigation.
Dual Mode pHRI-teleHRI Control System with a Hybrid Admittance-Force Controller for Ultrasound Imaging
Authors: Li Teng , Meng Xiao , Tavakoli Mahdi
Published: May 2022

The COVID-19 pandemic has brought unprecedented extreme pressure on the medical system due to the physical distance policy, especially for procedures such as ultrasound (US) imaging, which are usually carried out in person. Tele-operation systems are a promising way to avoid physical human–robot interaction (pHRI). However, the system usually requires another robot on the remote doctor side to provide haptic feedback, which makes it expensive and complex. To reduce the cost and system complexity, in this paper, we present a low-cost, easy-to-use, dual-mode pHRI-teleHRI control system with a custom-designed hybrid admittance-force controller for US imaging. The proposed system requires only a tracking camera rather than a sophisticated robot on the remote side. An audio feedback is designed for replacing haptic feedback on the remote side, and its sufficiency is experimentally verified. The experimental results indicate that the designed hybrid controller can significantly improve the task performance in both modes. Furthermore, the proposed system enables the user to conduct US imaging while complying with the physical distance policy, and allows them to seamlessly switch modes from one to another in an online manner. The novel system can be easily adapted to other medical applications beyond the pandemic, such as tele-healthcare, palpation, and auscultation.
BepFAMN: A Method for Linear B-Cell Epitope Predictions Based on Fuzzy-ARTMAP Artificial Neural Network
Authors: La Marca Anthony F. , Lopes Robson da S. , Lotufo Anna Diva P. , Bartholomeu Daniella C. , Minussi Carlos R.
Published: May 2022

The public health system is extremely dependent on the use of vaccines to immunize the population from a series of infectious and dangerous diseases, preventing the system from collapsing and millions of people dying every year. However, to develop these vaccines and effectively monitor these diseases, it is necessary to use accurate diagnostic methods capable of identifying highly immunogenic regions within a given pathogenic protein. Existing experimental methods are expensive, time-consuming, and require arduous laboratory work, as they require the screening of a large number of potential candidate epitopes, making the methods extremely laborious, especially for application to larger microorganisms. In the last decades, researchers have developed in silico prediction methods, based on machine learning, to identify these markers, to drastically reduce the list of potential candidate epitopes for experimental tests, and, consequently, to reduce the laborious task associated with their mapping. Despite these efforts, the tools and methods still have low accuracy, slow diagnosis, and offline training. Thus, we develop a method to predict B-cell linear epitopes which are based on a Fuzzy-ARTMAP neural network architecture, called BepFAMN (B Epitope Prediction Fuzzy ARTMAP Artificial Neural Network). This was trained using a linear averaging scheme on 15 properties that include an amino acid ratio scale and a set of 14 physicochemical scales. The database used was obtained from the IEDB website, from which the amino acid sequences with the annotations of their positive and negative epitopes were taken. To train and validate the knowledge models, five-fold cross-validation and competition techniques were used. The BepiPred-2.0 database, an independent database, was used for the tests. In our experiment, the validation dataset reached sensitivity = 91.50%, specificity = 91.49%, accuracy = 91.49%, MCC = 0.83, and an area under the curve (AUC) ROC of approximately 0.9289. The result in the testing dataset achieves a significant improvement, with sensitivity = 81.87%, specificity = 74.75%, accuracy = 78.27%, MCC = 0.56, and AOC = 0.7831. These achieved values demonstrate that BepFAMN outperforms all other linear B-cell epitope prediction tools currently used. In addition, the architecture provides mechanisms for online training, which allow the user to find a new B-cell linear epitope, and to improve the model without need to re-train itself with the whole dataset. This fact contributes to a considerable reduction in the number of potential linear epitopes to be experimentally validated, reducing laboratory time and accelerating the development of diagnostic tests, vaccines, and immunotherapeutic approaches.
Stress Monitoring of Concrete via Uniaxial Piezoelectric Sensor
Authors: Wu Chen , Xiang Hong , Jiang Shaofei , Ma Shenglan
Published: May 2022

The uniaxial piezoelectric sensor was developed to overcome the problem of reflecting the output charge of the piezoelectric element as a combination of vectors in the three stress directions. The work performance of the uniaxial piezoelectric sensor under varying load patterns and load rates was investigated. The sensor was embedded in concrete to monitor stress, and its elastic modulus was used as the intermediate bridge to establish the correlation between the embedded sensor and the external sensor. Furthermore, a correction factor for the charge transformation strain was suggested to overcome the mismatching of the sensor’s medium and the concrete. Considering related circumstances, a new stress monitoring method based on a uniaxial piezoelectric sensor was proposed, which can achieve stress whole-process monitoring in concrete and confining stress monitoring in the reinforced concrete column. The results reveal that through the proposed method, the output charge curve of the sensor has a substantial overlap with the stress waveform and high fitting linearity. The work performance of the sensor was stable, and its sensitivity was not affected by loading rate and load pattern. The sensor was embedded in concrete and can coordinate with the concrete deformation. The correction factor of strain obtained by the sensor embedded in concrete was 1.07. The relationship between the charge produced by the embedded sensor and its external calibration sensitivity may be used to implement the whole process of stress monitoring in concrete.
Graph Optimization Model Fusing BLE Ranging with Wi-Fi Fingerprint for Indoor Positioning
Authors: Zhou Rong , Chen Puchun , Teng Jing , Meng Fengying
Published: May 2022

To improve the user’s positioning accuracy of a Wi-Fi fingerprint-based positioning algorithm, this study proposes a graph optimization model based on the framework of g2o that fuses a Wi-Fi fingerprint and Bluetooth Low Energy (BLE) ranging technologies. In our model, the improvement in positioning can be formulated as a nonlinear least-squares optimization problem that a graph can represent. The graph regards users as nodes and our self-designed error functions between users as edges. In the graph, the nodes obtain the initial coordinates through Wi-Fi fingerprint positioning, and all error functions aggregate to a total error function to be solved. To improve the solution effect of the total error function and weaken the influence of measurement error, an information matrix, an edge selection principle, and a Huber kernel function are introduced. The Levenberg–Marquardt (LM) algorithm is used to solve the total error function and the affine transformation estimation is used for the drifting solution. Through experiments, the influence of the threshold in the Huber kernel function is explored, the relationship between the number of nodes in the graph and the optimization effect is analyzed, and the impact of the distribution of nodes is researched. The experimental results show improvements in the positioning accuracy of four common Wi-Fi fingerprint-matching algorithms: KNN, WKNN, GK, and Stg.
Experimental Study on Shear Wave Transmission in Fractured Media
Authors: Cai Ming , Wu Hongliang , Xin Yi , Liu Peng , Zhang Chengguang , Tang Jun , Lin Minjie , Tan Lihong
Published: May 2022

Unconventional oil and gas reservoirs have broad exploration and development prospects. Fracture parameters and effectiveness evaluation are two of the key tasks for the evaluation of these types of reservoirs. Array acoustic logging can be used for fracture evaluation to compensate for the deficiencies of the image logging fracture evaluation method. Therefore, to develop acoustic logging evaluation methods as well as nondestructive testing methods for fractures, experiments were conducted to study the shear wave transmission in fractured media. Experiment data demonstrate a good correlation between the shear wave attenuation coefficient and fracture width, and the shear wave attenuation coefficients rise logarithmically with the increase in the fracture width for all models with different porosities and distinct dip angles of fractures. The shear wave attenuation coefficient changes relatively faster with the fracture width when the fracture width is within 250 μm. In addition, the shear wave attenuation is affected by the core porosity and fracture dip angle. When the fracture width is constant, the shear wave attenuation caused by the 0° fracture is relatively larger and is obviously greater than that of the fractures at other angles, which is consistent with the existing experimental results. The results of this study can be used to guide further research on amplitude compensation methods for sonic signal transmission in fractured media and fracture evaluation methods.
A Multifunctional Battery-Free Bluetooth Low Energy Wireless Sensor Node Remotely Powered by Electromagnetic Wireless Power Transfer in Far-Field
Authors: Sidibe Alassane , Loubet Gaël , Takacs Alexandru , Dragomirescu Daniela
Published: May 2022

This paper presents a multifunctional battery-free wireless sensing node (SN) designed to monitor physical parameters (e.g., temperature, humidity and resistivity) of reinforced concrete. The SN, which is intended to be embedded into a concrete cavity, is autonomous and can be wirelessly powered thanks to the wireless power transmission technique. Once enough energy is stored in a capacitor, the active components (sensor and transceiver) are supplied with the harvested power. The data from the sensor are then wirelessly transmitted via the Bluetooth Low Energy (BLE) technology in broadcasting mode to a device configured as an observer. The feature of energy harvesting (EH) is achieved thanks to an RF-to-DC converter (a rectifier) optimized for a low power input level. It is based on a voltage doubler topology with SMS7630-005LF Schottky diode optimized at −15 dBm input power and a load of 10 kΩ. The harvested DC power is then managed and boosted by a power management unit (PMU). The proposed system has the advantage of presenting two different power management units (PMUs) and two rectifiers working in different European Industrial, Scientific and Medical (ISM) frequency bands (868 MHz and 2.45 GHz) depending on the available power density. The PMU interfaces a storage capacitor to store the harvested power and then power the active components of the sensing node. The low power digital sensor HD2080 is selected to provide accurate humidity and temperature measurements. Resistivity measurement (not reported in this paper) can also be achieved through a current injection on the concrete probes. For wireless communications, the QN9080 system-on-chip (SoC) was chosen as a BLE transceiver thanks to its attractive features: a small package size and extremely low power consumption. For low power consumption, the SN is configured in broadcasting mode. The measured power consumption of the SN in a deep-sleep mode is 946 µJ for four advertising events (spaced at 250 ms maximum) after the functioning of sensors. It also includes voltage offset cancelling functionality for resistivity measurement. Far-field measurement operated in an anechoic chamber with the most efficient PMU (AEM30940) gives a first charging time of 48 s (with an empty capacitor) and recharge duration of 27 s for a complete measurement and data transmission cycle.
Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study
Authors: An Qiyuan , McBeth Rafe , Zhou Houliang , Lawlor Bryan , Nguyen Dan , Jiang Steve , Link Mark S. , Zhu Yingying
Published: May 2022

Atrial fibrillation (AF) is a common cardiac arrhythmia and affects one to two percent of the population. In this work, we leverage the three-dimensional atrial endocardial unipolar/bipolar voltage map to predict the AF type and recurrence of AF in 1 year. This problem is challenging for two reasons: (1) the unipolar/bipolar voltages are collected at different locations on the endocardium and the shapes of the endocardium vary widely in different patients, and thus the unipolar/bipolar voltage maps need aligning to the same coordinate; (2) the collected dataset size is very limited. To address these issues, we exploit a pretrained 3D point cloud registration approach and finetune it on left atrial voltage maps to learn the geometric feature and align all voltage maps into the same coordinate. After alignment, we feed the unipolar/bipolar voltages from the registered points into a multilayer perceptron (MLP) classifier to predict whether patients have paroxysmal or persistent AF, and the risk of recurrence of AF in 1 year for patients in sinus rhythm. The experiment shows our method classifies the type and recurrence of AF effectively.
A Novel Carrier Loop Based on Coarse-to-Fine Weighted Adaptive Kalman Filter for Weak Communication-Positioning Integrated Signal
Authors: Deng Xiwen , Deng Zhongliang , Liu Jingrong , Zhang Zhichao
Published: May 2022

We propose a communication-navigation integrated signal (CPIS), which is superimposed on the communication signal with power that does not affect the communication service, and realizes high-precision indoor positioning in a mobile communication network. Due to the occlusion of indoor obstacles and the power limitation of the positioning signal, existing carrier loop algorithms have large tracking errors in weak signal environments, which limits the positioning performance of the receiver in a complex environment. The carrier loop based on Kalman filtering (KF) has a good performance in respect of weak signals. However, the carrier frequency error of acquisition under weak signals is large, and the KF loop cannot converge quickly. Moreover, the KF algorithm based on fixed noise covariance increases or diverges in filtering error in complex environments. In this paper, a coarse-to-fine weighted adaptive Kalman filter (WAKF)-based carrier loop algorithm is proposed to solve the above problems of the receiver. In the coarse tracking stage, acquisition error reduction and bit synchronization are realized, and then a carrier loop based on Sage–Husa adaptive filtering is entered. Considering the shortcomings of the filter divergence caused by the negative covariance matrix of Sage–Husa in the filter update process, the weighted factor is given and UD decomposition is introduced to suppress the filtering divergence and improve the filtering accuracy. The simulation and actual environment test results show that the tracking sensitivity of the proposed algorithm is better than that based on the Sage–Husa adaptive filtering algorithm. In addition, compared with the weighted Sage–Husa AKF algorithm, the coarse-to-fine WAKF-based carrier loop algorithm converges faster.
Wearable Sensor Based on Flexible Sinusoidal Antenna for Strain Sensing Applications
Authors: Ahadi Mehran , Roudjane Mourad , Dugas Marc-André , Miled Amine , Messaddeq Younès
Published: May 2022

A flexible sinusoidal-shaped antenna sensor is introduced in this work, which is a modified half-wave dipole that can be used for strain sensing applications. The presented antenna is an improved extension of the previously introduced antenna sensor for respiration monitoring. The electrical and radiative characteristics of the sinusoidal antenna and the effects of the geometrical factors are studied. An approach is provided for designing the antenna, and equations are introduced to estimate the geometrical parameters based on desired electrical specifications. It is shown that the antenna sensor can be designed to have up to 5.5 times more sensitivity compared to the last generation of the antenna sensor previously introduced for respiration monitoring. The conductive polymer material used to fabricate the new antenna makes it more flexible and durable compared to the previous generation of antenna sensors made of glass-based material. Finally, a reference antenna made of copper and an antenna sensor made of the conductive polymer are fabricated, and their electrical characteristics are analyzed in free space and over the body.