bluuebunny/crossref_metadata_2025 huggingface dataset:
In-Vitro Characterization of Growth Inhibition against the Gut Pathogen of Potentially Probiotic Lactic Acid Bacteria Strains Isolated from Fermented Products
Authors: Jung Ji Young , Han Sang-Soo , Kim Z-Hun , Kim Myung Hoo , Kang Hye Kyeong , Jin Hyun Mi , Lee Mi Hwa
Published: October 2021

Lactic acid bacteria (LAB) are probiotic candidates that may restore the balance of microbiota populations in intestinal microbial ecosystems by controlling pathogens and thereby promoting host health. The goal of this study was to isolate potential probiotic LAB strains and characterize their antimicrobial abilities against pathogens in intestinal microbiota. Among 54 LAB strains isolated from fermented products, five LAB strains (NSMJ15, NSMJ16, NSMJ23, NSMJ42, and NFFJ04) were selected as potential probiotic candidates based on in vitro assays of acid and bile salt tolerance, cell surface hydrophobicity, adhesion to the intestinal epithelium, and antagonistic activity. Phylogenetic analysis based on 16S rRNA genes showed that they have high similarities of 99.58–100% to Lacticaseibacillus paracasei strains NSMJ15 and NFFJ04, Lentilactobacillus parabuchneri NSMJ16, Levilactobacillus brevis NSMJ23, and Schleiferilactobacillus harbinensis NSMJ42. To characterize their antimicrobial abilities against pathogens in intestinal microbiota, the impact of cell-free supernatant (CFS) treatment in 10% (v/v) fecal suspensions prepared using pooled cattle feces was investigated using in vitro batch cultures. Bacterial community analysis using rRNA amplicon sequencing for control and CFS-treated fecal samples at 8 and 16 h incubation showed the compositional change after CFS treatment for all five LAB strains. The changed compositions were similar among them, but there were few variable increases or decreases in some bacterial groups. Interestingly, as major genera that could exhibit pathogenicity and antibiotic resistance, the members of Bacillus, Escherichia, Leclercia, Morganella, and Vagococcus were decreased at 16 h in all CFS-treated samples. Species-level classification suggested that the five LAB strains are antagonistic to gut pathogens. This study showed the probiotic potential of the five selected LAB strains; in particular, their antimicrobial properties against pathogens present in the intestinal microbiota. These strains would therefore seem to play an important role in modulating the intestinal microbiome of the host.
Molecular and Stable Isotope Composition of Pollutants Emitted during Thermal Processes within the Rymer Coal Waste Dump (Upper Silesia, Poland)
Authors: Więcław Dariusz , Jurek Krzysztof , Fabiańska Monika J. , Bilkiewicz Elżbieta , Kowalski Adam , Misz-Kennan Magdalena , Ciesielczuk Justyna
Published: October 2021

Twenty-seven gases and sixteen rock wastes from the thermal active Rymer coal waste dump were collected. The composition and origin of gaseous, liquid, and solid pollutants emitted during the self-heating process and the development of these processes with time were established. Gases were subjected to determination of molecular and stable isotope (δ13C and δ2H) composition. Rock-Eval pyrolysis and pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) were applied for evaluation of the quantity and molecular composition of pyrolysates released during the heating of rocks in temperatures from 100 to 650 °C. The main products of Py-GC-MS are released between 350 and 650 °C, namely alkanes, aromatic hydrocarbons, and aromatic alcohols. These components were also recorded in Py-GC-MS products of samples collected from the dump surface. Besides the high-molecular-weight organic compounds, in emitted gases CO2, CO, gaseous hydrocarbons, and S-compounds were recorded. The stable isotope data indicated that methane was generated mainly during the low-temperature thermogenic process, but a share of the microbial-originated gas was visible. The source of the CO2 was the oxidation of organic matter. The gaseous S-compounds were products of high-temperature decomposition of sulphides and organic S-compounds. The hydrocarbon and CO contents of the emitted gases proved to be good indicators for tracking of the self-heating processes.
Simulation to Recover Niobium and Tantalum from the Tin Slags of the Old Penouta Mine: A Case Study
Authors: Magdalena Ricardo , Valero Alicia , Calvo Guiomar , Alguacil Francisco J. , López Félix Antonio
Published: October 2021

Demand for niobium and tantalum is increasing exponentially as these are essential ingredients for the manufacture of, among others, capacitors in technological devices and ferroniobium. Mine tailings rich in such elements could constitute an important source of Nb and Ta in the future and alleviate potential supply risks. This paper evaluates the possibility of recovering niobium and tantalum from the slags generated during the tin beneficiation process of mine tailings from the old Penouta mine, located in Spain. To do so, a simulation of the processes required to beneficiate and refine both elements is carried out. After carbothermic tin reduction, the slags are sent to a hydrometallurgical process where niobium oxide and tantalum oxide are obtained at the end. Reagents, water, and energy consumption, in addition to emissions, effluents, and product yields, are assessed. Certain factors were identified as critical, and recirculation was encouraged in the model to maximise production and minimise reagents’ use and wastes. With this simulation, considering 3000 production hours per year, the metal output from the tailings of the old mine could cover around 1% and 7.4% of the world annual Nb and Ta demand, respectively.
Special Issue “Recent Advances in Flame-Retardant Polymers and Composites”
Authors: Kim Nam Kyeun , Das Oisik
Published: October 2021

The flame-retardant performance of materials has become an increasingly crucial factor for society across a broad range of applications in aircraft, automobiles, civil infrastructure, and consumer products [...]
Shedding Light on the Pharmacological Interactions between μ-Opioid Analgesics and Angiotensin Receptor Modulators: A New Option for Treating Chronic Pain
Authors: Király Kornél , Karádi Dávid Á. , Zádor Ferenc , Mohammadzadeh Amir , Galambos Anna Rita , Balogh Mihály , Riba Pál , Tábi Tamás , Zádori Zoltán S. , Szökő Éva , Fürst Susanna , Al-Khrasani Mahmoud
Published: October 2021

The current protocols for neuropathic pain management include µ-opioid receptor (MOR) analgesics alongside other drugs; however, there is debate on the effectiveness of opioids. Nevertheless, dose escalation is required to maintain their analgesia, which, in turn, contributes to a further increase in opioid side effects. Finding novel approaches to effectively control chronic pain, particularly neuropathic pain, is a great challenge clinically. Literature data related to pain transmission reveal that angiotensin and its receptors (the AT1R, AT2R, and MAS receptors) could affect the nociception both in the periphery and CNS. The MOR and angiotensin receptors or drugs interacting with these receptors have been independently investigated in relation to analgesia. However, the interaction between the MOR and angiotensin receptors has not been excessively studied in chronic pain, particularly neuropathy. This review aims to shed light on existing literature information in relation to the analgesic action of AT1R and AT2R or MASR ligands in neuropathic pain conditions. Finally, based on literature data, we can hypothesize that combining MOR agonists with AT1R or AT2R antagonists might improve analgesia.
Experimental and Theoretical Studies of α-Linolenic Acid as Green Corrosion Inhibitor for Carbon Steel in 0.5 M Sulfuric Acid
Authors: Hermoso-Diaz I.A. , Lopez-Cecenes R. , Rios J.P. Flores-De los , Landeros-Martínez L.L. , Sarmiento-Bustos E. , Uruchurtu-Chavarin J. , Gonzalez-Rodriguez J.G.
Published: October 2021

A component of Salvia hispanica, α-linolenic acid, has been evaluated as a green corrosion inhibitor for 1018 carbon steel in 0.5 M sulfuric acid using weight loss tests, potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) measurements. Theoretical calculations using Density Functional Theory (DFT) were used also. The results have shown that this compound is a good corrosion inhibitor, with an efficiency which increased with an increase in its concentration up to 600 ppm, but it decreased with a further increase in the concentration. α-linolenic acid formed protective corrosion products layer because it was chemically adsorbed onto the steel surface according to a Langmuir type of adsorption isotherms. Polarization curves have shown that α-linolenic acid is a good, mixed type of inhibitor with a predominant effect on the cathodic hydrogen evolution reactions. EIS measurements indicated a charge transfer-controlled corrosion process. DFT calculations indicated that α-linolenic acid was more efficient in an acidic environment than in a neutral one because has a high tendency to donate electrons and can be easily protonated. In addition to this, it had the highest EHUMO value, the best chemical reactivity, the greatest tendency to transfer electrons and a greater facility of modifying its electronic configuration in the presence of carbon steel specimens according to its chemical hardness value.
A Rapid, Reliable RP-UPLC Method for Large-Scale Analysis of Wheat HMW-GS Alleles
Authors: Lee Su-Bin , Yang Yu-Jeong , Lim Sun-Hyung , Gu Yong Q. , Lee Jong-Yeol
Published: October 2021

High-molecular-weight glutenin subunits (HMW-GS) account for only 10% of total wheat storage proteins, but play an important role in the processing quality of wheat flour. Therefore, identifying HMW-GS alleles associated with good end-use quality provides important information for wheat breeders. To rapidly, accurately and reproducibly identify HMW-GS, we established an optimized reversed-phase ultra-performance liquid chromatography (RP-UPLC) method. Separation parameters were optimized using an ACQUITY UPLC Protein BEH C4 column and stepwise ACN gradient, and the separation patterns and retention times (RTs) of 22 subunits were comparatively analyzed in 16 standard wheat cultivars. All HMW-GS proteins were well separated within about 5.5 min, and all analyses were complete within 12 min. We distinguished the 16 subunits based on RT, although three subunits in 1Bx (1Bx7/1Bx7OE and 1Bx17) and three subunits in 1By (1By8*, 1By9 and 1By15) had overlapping RTs; these were differentiated by SDS-PAGE. To distinguish 1Bx7 and 1Bx7OE, which differ in protein abundance, RP-UPLC was combined with PCR analysis of DNA junction markers. The optimized method was successfully applied to determine HMW-GS alleles in a large collection of bread wheat germplasm (1787 lines). This protocol is an appropriate option for selecting lines harboring favorable HMW-GS alleles in wheat breeding.
In Silico and In Vivo Evaluation of SARS-CoV-2 Predicted Epitopes-Based Candidate Vaccine
Authors: Shehata Mahmoud M. , Mahmoud Sara H. , Tarek Mohammad , Al-Karmalawy Ahmed A. , Mahmoud Amal , Mostafa Ahmed , M. Elhefnawi Mahmoud , Ali Mohamed A.
Published: October 2021

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, the causative agent of coronavirus disease (COVID-19)) has caused relatively high mortality rates in humans throughout the world since its first detection in late December 2019, leading to the most devastating pandemic of the current century. Consequently, SARS-CoV-2 therapeutic interventions have received high priority from public health authorities. Despite increased COVID-19 infections, a vaccine or therapy to cover all the population is not yet available. Herein, immunoinformatics and custommune tools were used to identify B and T-cells epitopes from the available SARS-CoV-2 sequences spike (S) protein. In the in silico predictions, six B cell epitopes QTGKIADYNYK, TEIYQASTPCNGVEG, LQSYGFQPT, IRGDEVRQIAPGQTGKIADYNYKLPD, FSQILPDPSKPSKRS and PFAMQMAYRFNG were cross-reacted with MHC-I and MHC-II T-cells binding epitopes and selected for vaccination in experimental animals for evaluation as candidate vaccine(s) due to their high antigenic matching and conserved score. The selected six peptides were used individually or in combinations to immunize female Balb/c mice. The immunized mice raised reactive antibodies against SARS-CoV-2 in two different short peptides located in receptor binding domain and S2 region. In combination groups, an additive effect was demonstrated in-comparison with single peptide immunized mice. This study provides novel epitope-based peptide vaccine candidates against SARS-CoV-2.
Design Principles of Large Cation Incorporation in Halide Perovskites
Authors: Park Heesoo , Kumar Syam , Chawla Sanjay , El-Mellouhi Fedwa
Published: October 2021

Perovskites have stood out as excellent photoactive materials with high efficiencies and stabilities, achieved via cation mixing techniques. Overcoming challenges to the stabilization of Perovskite solar cells calls for the development of design principles of large cation incorporation in halide perovskite to accelerate the discovery of optimal stable compositions. Large fluorinated organic cations incorporation is an attractive method for enhancing the intrinsic stability of halide perovskites due to their high dipole moment and moisture-resistant nature. However, a fluorinated cation has a larger ionic size than its non-fluorinated counterpart, falling within the upper boundary of the mixed-cation incorporation. Here, we report on the intrinsic stability of mixed Methylammonium (MA) lead halides at different concentrations of large cation incorporation, namely, ehtylammonium (EA; [CH3CH2NH3]+) and 2-fluoroethylammonium (FEA; [CH2FCH2NH3]+). Density functional theory (DFT) calculations of the enthalpy of the mixing and analysis of the perovskite structural features enable us to narrow down the compositional search domain for EA and FEA cations around concentrations that preserve the perovskite structure while pointing towards the maximal stability. This work paves the way to developing design principles of a large cation mixture guided by data analysis of DFT data. Finally, we present the automated search of the minimum enthalpy of mixing by implementing Bayesian optimization over the compositional search domain. We introduce and validate an automated workflow designed to accelerate the compositional search, enabling researchers to cut down the computational expense and bias to search for optimal compositions.
Charge Tunable GaAs Quantum Dots in a Photonic n-i-p Diode
Authors: Babin Hans Georg , Ritzmann Julian , Bart Nikolai , Schmidt Marcel , Kruck Timo , Zhai Liang , Löbl Matthias C. , Nguyen Giang N. , Spinnler Clemens , Ranasinghe Leonardo , Warburton Richard J. , Heyn Christian , Wieck Andreas D. , Ludwig Arne
Published: October 2021

In this submission, we discuss the growth of charge-controllable GaAs quantum dots embedded in an n-i-p diode structure, from the perspective of a molecular beam epitaxy grower. The QDs show no blinking and narrow linewidths. We show that the parameters used led to a bimodal growth mode of QDs resulting from low arsenic surface coverage. We identify one of the modes as that showing good properties found in previous work. As the morphology of the fabricated QDs does not hint at outstanding properties, we attribute the good performance of this sample to the low impurity levels in the matrix material and the ability of n- and p-doped contact regions to stabilize the charge state. We present the challenges met in characterizing the sample with ensemble photoluminescence spectroscopy caused by the photonic structure used. We show two straightforward methods to overcome this hurdle and gain insight into QD emission properties.
Primiparous Adaptation with Postpartum Health Issues in Jeddah City, Kingdom of Saudi Arabia: A Quantitative Study
Authors: Al-Zahrani Ahlam , Almutairi Wedad , Elsaba Howaida , Alzahrani Sanaa , Alzahrani Shouq , Althobaiti Linah , Turkestani Ohoud
Published: October 2021

Background: The postpartum or puerperium period is the first 6 weeks after giving birth to an infant. The postpartum period can have negative implications, especially in first-time mothers. With their transition into motherhood, new mothers adopt new lifestyles, which can affect their physical wellbeing. Childbirth has physical, psychological, and emotional effects on women as they try to adapt to their new roles in order to get through this period with no or minimal health issues. Study Aim: The current study aims to explore primiparous adaptations with postpartum health issues in Jeddah City at Kingdom of Saudi Arabia. Methods: The research design is quantitative cross-sectional. A structured questionnaire was developed to collect data in relation to depression and weight gain, which consider the most common postpartum health issues. The inclusion criteria of the participants are: primipara, 2 to 6 months postpartum, and living in Jeddah. Results: 140 participants were included in the study. Mothers gained approximately 9.2 kg within the fifth to ninth month after giving birth. Discussion: Postpartum weight retention is a primary challenge in the majority of primiparous mothers and results in reduced quality of life. Nurses were always available to answer questions related to the postpartum health issues and explained the expectations to the family members. Conclusions: Childbirth and the postpartum period for first-time mothers are crucial in their lives as they try to adapt to a new way of life. The postpartum period can have negative implications, especially in first-time mothers. With their transition into motherhood, new mothers adopt new lifestyles, which can affect their physical wellbeing. More research is needed to explore the impact of postpartum health issues in Saudi Arabia.
Association between Toxoplasma gondii Infection in Brain and a History of Depression in Suicide Decedents: A Cross-Sectional Study
Authors: Alvarado-Esquivel Cosme , Mendoza-Larios Laura Alejandra , García-Dolores Fernando , Sánchez-Anguiano Luis Francisco , Antuna-Salcido Elizabeth Irasema , Hernández-Tinoco Jesús , Rocha-Salais Adriana , Segoviano-Mendoza Marcela Araceli , Sifuentes-Álvarez Antonio
Published: October 2021

We assessed the association between Toxoplasma gondii (T. gondii) infection of the central nervous system and suicide correlates in suicide decedents. Eighty-seven decedents who died by suicide received in a forensic setting for medico-legal autopsies in Mexico City were studied. Two samples of brain (amygdala and prefrontal cortex) from each decedent were examined for detection of T. gondii using immunohistochemistry. Correlates of suicide including a history of previous suicide attempts, co-morbid mental disorder, consumption of alcohol or tobacco, irritability and aggression, economic problems, presence of drugs or alcohol in blood and suicide method were obtained and analyzed for their association with T. gondii infection. T. gondii immunohistochemistry was positive in prefrontal cortex sections in 6 decedents and in an amygdala section in one decedent. Thus, the prevalence of T. gondii infection in brain in suicide victims was 8.0% (7/87). Bivariate and logistic regression analysis of suicide correlates showed that only a history of depression was associated with T. gondii infection of the brain in suicide victims (OR: 12.00; 95% CI: 2.26–63.46; p = 0.003). Our results provide evidence that T. gondii infection in brain is associated with a history of depression in suicide decedents.
An Update on the Laboratory Diagnosis of Rickettsia spp. Infection
Authors: Stewart Adam G. , Stewart Alexandra G. A.
Published: October 2021

Rickettsia species causing human illness are present globally and can cause significant disease. Diagnosis and identification of this intracellular bacteria are challenging with many available diagnostic modalities suffering from several shortcomings. Detection of antibodies directed against Rickettsia spp. via serological methods remains widely used with a broad range of sensitivity and specificity values reported depending on the assay. Molecular methods, including polymerase chain reaction (PCR) testing, enables species-specific identification with a fast turnaround time; however, due to resource requirements, use in some endemic settings is limited. Reports on the use of next-generation sequencing (NGS) and metagenomics to diagnose Rickettsia spp. infection have been increasing. Despite offering several potential advantages in the diagnosis and surveillance of disease, genomic approaches are currently only limited to reference and research laboratories. Continued development of Rickettsia spp. diagnostics is required to improve disease detection and epidemiological surveillance, and to better understand transmission dynamics.
A Constructive Treatment to Elemental Life Forms through Mathematical Philosophy
Authors: Bagchi Susmit
Published: October 2021

The quest to understand the natural and the mathematical as well as philosophical principles of dynamics of life forms are ancient in the human history of science. In ancient times, Pythagoras and Plato, and later, Copernicus and Galileo, correctly observed that the grand book of nature is written in the language of mathematics. Platonism, Aristotelian logism, neo-realism, monadism of Leibniz, Hegelian idealism and others have made efforts to understand reasons of existence of life forms in nature and the underlying principles through the lenses of philosophy and mathematics. In this paper, an approach is made to treat the similar question about nature and existential life forms in view of mathematical philosophy. The approach follows constructivism to formulate an abstract model to understand existential life forms in nature and its dynamics by selectively combining the elements of various schools of thoughts. The formalisms of predicate logic, probabilistic inference and homotopy theory of algebraic topology are employed to construct a structure in local time-scale horizon and in cosmological time-scale horizon. It aims to resolve the relative and apparent conflicts present in various thoughts in the process, and it has made an effort to establish a logically coherent interpretation.
Highly Sensitive Biosensor Based on Partially Immobilized Silver Nanopillars in the Terahertz Band
Authors: Liu Shuo , Li Lin , Bai Zhenxu
Published: October 2021

In this paper, a highly sensitive biosensor based on partially immobilized silver nanopillars is proposed. The working frequency of this sensor is in the terahertz band, and the range of the detected refractive index is 1.33 to 1.38. We set air holes of two different sizes on the cross-section of the optical fiber and arranged them into a hexagon. In order to improve the sensitivity, silver nanopillars were immobilized on part of the surface of the fiber cladding. The method for detecting the change of refractive index of the bio-analyte was based on local surface plasmon resonance properties of noble metal. The research recorded valuable data about the values of loss peak and full width at half maximum as well as resonance frequency shift under different setting conditions. The data present the biosensor’s final sensitivity as 1.749 THz/RIU.
Flexible Broadband Metamaterial Perfect Absorber Based on Graphene-Conductive Inks
Authors: Long Le Van , Khiem Nguyen Sy , Tung Bui Son , Tung Nguyen Thanh , Giang Trinh Thi , Son Pham Thanh , Khuyen Bui Xuan , Lam Vu Dinh , Chen Liangyao , Zheng Haiyu , Lee Youngpak
Published: October 2021

In this work, we proposed a flexible broadband metamaterial perfect absorber (FBMPA) by exploiting a pasted conductive-graphene ink on a polyimide substrate. For the flat FBMPA, an absorption over 90% was found to cover a wide frequency range (from 7.88 to 18.01 GHz). The high-absorption feature was polarization-insensitive and regarded as stable with respect to the oblique incidence up to 30 degrees of electromagnetic wave. The high absorption was maintained well even when the absorber was wrapped. That is, the FBMPA was attached to cylindrical surfaces (with the varying radius from 4 to 50 cm). For both flat and curved states, the absorption mechanism was explained by the perfect impedance matching and the dielectric loss of the proposed absorber. Our work provides the groundwork for the commercialization of future meta-devices such as sensors, optical filters/switchers, photodetectors, and energy converters.
Accelerating the Development of Heat Tolerant Tomato Hybrids through a Multi-Traits Evaluation of Parental Lines Combining Phenotypic and Genotypic Analysis
Authors: Olivieri Fabrizio , Graci Salvatore , Francesca Silvana , Rigano Maria Manuela , Barone Amalia
Published: October 2021

The constitution of heat tolerant F1 hybrids is a challenge to ensure high yield and good fruit quality in the global climate. In the present work, we evaluated 15 genotypes for yield-related traits highly affected by high temperatures (HT). This phenotypic analysis allowed to identify four parental genotypes showing promising yield performances under HT conditions. Two of these genotypes also exhibited good fruit quality traits. A molecular marker analysis was carried out for six resistance genes to pathogens mostly affecting tomatoes. This analysis evidenced the presence of a maximum of three resistant alleles in parental genotypes. Exploring single nucleotide polymorphisms (SNPs) revealed by two high-throughput genotyping platforms allowed identifying additional 12 genes potentially involved in resistance to biotic stress, to be further investigated. Following these considerations, 13 F1 hybrids were constituted combining the parental genotypes and then evaluated for multiple traits under HT conditions. By estimating a hybrid index based on yield performances, desirable quality and resistance gene, we identified seven hybrids showing the best performances. The promising results obtained in the present work should be confirmed by evaluating the best hybrids selected for additional years and environments before proposing them as novel commercial hybrids that could maintain high performances under HT conditions.
Effect of Mn and Cu Substitution on the SrFeO3 Perovskite for Potential Thermochemical Energy Storage Applications
Authors: Darwish Esraa , Mansouri Moufida , Yilmaz Duygu , Leion Henrik
Published: October 2021

Perovskites are well-known oxides for thermochemical energy storage applications (TCES) since they show a great potential for spontaneous O2 release due to their non-stoichiometry. Transition-metal-based perovskites are particularly promising candidates for TCES owing to their different oxidation states. It is important to test the thermal behavior of the perovskites for TCES applications; however, the amount of sample that can be used in thermal analyses is limited. The use of redox cycles in fluidized bed tests can offer a more realistic approach, since a larger amount of sample can be used to test the cyclic behavior of the perovskites. In this study, the oxygen release/consumption behavior of Mn- or Cu-substituted SrFeO3 (SrFe0.5M0.5O3; M: Mn or Cu) under redox cycling was investigated via thermal analysis and fluidized bed tests. The reaction enthalpies of the perovskites were also calculated via differential scanning calorimetry (DSC). Cu substitution in SrFeO3 increased the performance significantly for both cyclic stability and oxygen release/uptake capacity. Mn substitution also increased the cyclic stability; however, the presence of Mn as a substitute for Fe did not improve the oxygen release/uptake performance of the perovskite.
Recovery of Ag, Au, and Pt from Printed Circuit Boards by Pressure Leaching
Authors: Martinez-Ballesteros Guadalupe , Valenzuela-García Jesus Leobardo , Gómez-Alvarez Agustin , Encinas-Romero Martin Antonio , Mejía-Zamudio Flerida Adriana , Rosas-Durazo Aaron de Jesús , Valenzuela-Frisby Roberto
Published: October 2021

Reclamation of printed circuit boards (PCBs) to recover metals is gaining growing attention due to minerals being non-renewable resources. Currently, metals extraction from PCBs through an efficient and green method is still under investigation. The present investigation concerns the recycling of printed circuit boards using hydrometallurgical processes. First, the basic metals (Cu, Ni, Zn and Fe) were separated using a sulfuric acid solution at moderate temperatures. The remaining solids were characterized by SEM-EDS, whereby a high content of precious metals (Au, Ag and Pt) was observed. In the second stage, solids were leached with a solution of HCl and NaClO in a 1-L titanium reactor with varied oxygen pressure (0.2, 0.34 and 0.55 MPa), temperature (40, 50 and 80 °C) and concentration of HCl (2 and 4 M), obtaining extractions above 95% at [HCl] = 4 M, P = 0.34 MPa and T = 40 °C. The extraction increased depending on the concentration of HCl. Eh–pH diagrams for Ag–Cl–H2O, Au–Cl–H2O and Pt–Cl–H2O were constructed to know the possible species in the solution.
Simultaneous Measurement of Thickness and Elastic Properties of Thin Plastic Films by Means of Ultrasonic Guided Waves
Authors: Kažys Rymantas Jonas , Tumšys Olgirdas
Published: October 2021

Ultrasonic guided waves are already used for material characterization. The advantage of these waves is that they propagate in the plane of a plate and their propagation characteristics are sensitive to properties of the material. The objective of this research was to develop an ultrasonic method that could be used to measure the properties of thin plastic polyvinylchloride films (PVC). The proposed method exploits two fundamental Lamb wave modes, A0 and S0, for measurement of a thin film thickness and Young’s modulus. The Young’s modulus is found from the measured phased velocity of the S0 mode and the film thickness from the velocities of both A0 and S0 modes. By using the proposed semi-contactless measurement algorithm, the Young’s modulus and thickness of different thickness (150 µm and 200 µm) PVC films were measured. The uncertainty of thickness measurements of the thinner 150 µm PVC film is 2% and the thicker 200 µm PVC film is 3.9%.
DCPNet: A Densely Connected Pyramid Network for Monocular Depth Estimation
Authors: Lai Zhitong , Tian Rui , Wu Zhiguo , Ding Nannan , Sun Linjian , Wang Yanjie
Published: October 2021

Pyramid architecture is a useful strategy to fuse multi-scale features in deep monocular depth estimation approaches. However, most pyramid networks fuse features only within the adjacent stages in a pyramid structure. To take full advantage of the pyramid structure, inspired by the success of DenseNet, this paper presents DCPNet, a densely connected pyramid network that fuses multi-scale features from multiple stages of the pyramid structure. DCPNet not only performs feature fusion between the adjacent stages, but also non-adjacent stages. To fuse these features, we design a simple and effective dense connection module (DCM). In addition, we offer a new consideration of the common upscale operation in our approach. We believe DCPNet offers a more efficient way to fuse features from multiple scales in a pyramid-like network. We perform extensive experiments using both outdoor and indoor benchmark datasets (i.e., the KITTI and the NYU Depth V2 datasets) and DCPNet achieves the state-of-the-art results.
Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM
Authors: Nowak Tomasz , Ćwian Krzysztof , Skrzypczyński Piotr
Published: October 2021

This article aims at demonstrating the feasibility of modern deep learning techniques for the real-time detection of non-stationary objects in point clouds obtained from 3-D light detecting and ranging (LiDAR) sensors. The motion segmentation task is considered in the application context of automotive Simultaneous Localization and Mapping (SLAM), where we often need to distinguish between the static parts of the environment with respect to which we localize the vehicle, and non-stationary objects that should not be included in the map for localization. Non-stationary objects do not provide repeatable readouts, because they can be in motion, like vehicles and pedestrians, or because they do not have a rigid, stable surface, like trees and lawns. The proposed approach exploits images synthesized from the received intensity data yielded by the modern LiDARs along with the usual range measurements. We demonstrate that non-stationary objects can be detected using neural network models trained with 2-D grayscale images in the supervised or unsupervised training process. This concept makes it possible to alleviate the lack of large datasets of 3-D laser scans with point-wise annotations for non-stationary objects. The point clouds are filtered using the corresponding intensity images with labeled pixels. Finally, we demonstrate that the detection of non-stationary objects using our approach improves the localization results and map consistency in a laser-based SLAM system.
Multiplexed Weak Waist-Enlarged Fiber Taper Curvature Sensor and Its Rapid Inline Fabrication
Authors: Yi Duo , Wang Lina , Geng Youfu , Du Yu , Li Xuejin , Hong Xueming
Published: October 2021

This study proposes a multiplexed weak waist-enlarged fiber taper (WWFT) curvature sensor and its rapid fabrication method. Compared with other types of fiber taper, the proposed WWFT has no difference in appearance with the single mode fiber and has ultralow insertion loss. The fabrication of WWFT also does not need the repeated cleaving and splicing process, and thereby could be rapidly embedded into the inline sensing fiber without splicing point, which greatly enhances the sensor solidity. Owing to the ultralow insertion loss (as low as 0.15 dB), the WWFT-based interferometer is further used for multiplexed curvature sensing. The results show that the different curvatures can be individually detected by the multiplexed interferometers. Furthermore, it also shows that diverse responses for the curvature changes exist in two orthogonal directions, and the corresponding sensitivities are determined to be 79.1°/m−1 and –48.0°/m−1 respectively. This feature can be potentially applied for vector curvature sensing.
Distributed Acoustic Sensing Based on Coherent Microwave Photonics Interferometry
Authors: Hua Liwei , Zhu Xuran , Cheng Baokai , Song Yang , Zhang Qi , Wu Yongji , Murdoch Lawrence C. , Dauson Erin R. , Donahue Carly M. , Xiao Hai
Published: October 2021

A microwave photonics method has been developed for measuring distributed acoustic signals. This method uses microwave-modulated low coherence light as a probe to interrogate distributed in-fiber interferometers, which are used to measure acoustic-induced strain. By sweeping the microwave frequency at a constant rate, the acoustic signals are encoded into the complex microwave spectrum. The microwave spectrum is transformed into the joint time–frequency domain and further processed to obtain the distributed acoustic signals. The method is first evaluated using an intrinsic Fabry Perot interferometer (IFPI). Acoustic signals of frequency up to 15.6 kHz were detected. The method was further demonstrated using an array of in-fiber weak reflectors and an external Michelson interferometer. Two piezoceramic cylinders (PCCs) driven at frequencies of 1700 Hz and 3430 Hz were used as acoustic sources. The experiment results show that the sensing system can locate multiple acoustic sources. The system resolves 20 nε when the spatial resolution is 5 cm. The recovered acoustic signals match the excitation signals in frequency, amplitude, and phase, indicating an excellent potential for distributed acoustic sensing (DAS).
ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments
Authors: Guffanti Diego , Brunete Alberto , Hernando Miguel , Rueda Javier , Navarro Enrique
Published: October 2021

Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multiple medical applications and achieve new discoveries. This study proposes the use of a mobile robotic platform based on depth cameras to perform the analysis of human gait in practical scenarios. The aim is to prove the validity of this robot and its applicability in clinical settings. The mechanical and software design of the system is presented, as well as the design of the controllers of the lane-keeping, person-following, and servoing systems. The accuracy of the system for the evaluation of joint kinematics and the main gait descriptors was validated by comparison with a Vicon-certified system. Some tests were performed in practical scenarios, where the effectiveness of the lane-keeping algorithm was evaluated. Clinical tests with patients with multiple sclerosis gave an initial impression of the applicability of the instrument in patients with abnormal walking patterns. The results demonstrate that the system can perform gait analysis with high accuracy. In the curved sections of the paths, the knee joint is affected by occlusion and the deviation of the person in the camera reference system. This issue was greatly improved by adjusting the servoing system and the following distance. The control strategy of this robot was specifically designed for the analysis of human gait from the frontal part of the participant, which allows one to capture the gait properly and represents one of the major contributions of this study in clinical practice.
Dynamics and Control of a Magnetic Transducer Array Using Multi-Physics Models and Artificial Neural Networks
Authors: Tsakyridis Georgios , Xiros Nikolaos I.
Published: October 2021

A linear mechanical oscillator is non-linearly coupled with an electromagnet and its driving circuit through a magnetic field. The resulting non-linear dynamics are investigated using magnetic circuit approximations without major loss of accuracy and in the interest of brevity. Different computational approaches to simulate the setup in terms of dynamical system response and design parameters optimization are pursued. A current source operating in baseband without modulation directly feeds the electromagnet, which consists commonly of a solenoid and a horseshoe-shaped core. The electromagnet is then magnetically coupled to a mass made of soft magnetic material and attached to a spring with damping. The non-linear system is described by a linearized steady-space representation while is examined for controllability and observability. A controller using a pole placement approach is built to stabilize the element. Drawing upon the fact that coupling works both ways, enabling estimation of the mass position and velocity (state variables) by processing the induced voltage across the electromagnet, a state observer is constructed. Accurate and fast tracking of the state variables, along with the possibility of driving more than one module from the same source using modulation, proves the applicability of the electro-magneto-mechanical transducer for sensor applications. Next, a three-layer feed-forward artificial neural network (ANN) system equivalent was trained using the non-linear plant-linear controller-linear observer configuration. Simulations to investigate the robustness of the system with respect to different equilibrium points and input currents were carried out. The ANN proved robust with respect to position accuracy.
Dry Wearable Textile Electrodes for Portable Electrical Impedance Tomography
Authors: Hu Chang-Lin , Cheng I-Cheng , Huang Chih-Hsien , Liao Yu-Te , Lin Wei-Chieh , Tsai Kun-Ju , Chi Chih-Hsien , Chen Chang-Wen , Wu Chia-Hsi , Lin I-Te , Li Chien-Ju , Lin Chii-Wann
Published: October 2021

Electrical impedance tomography (EIT), a noninvasive and radiation-free medical imaging technique, has been used for continuous real-time regional lung aeration. However, adhesive electrodes could cause discomfort and increase the risk of skin injury during prolonged measurement. Additionally, the conductive gel between the electrodes and skin could evaporate in long-term usage and deteriorate the signal quality. To address these issues, in this work, textile electrodes integrated with a clothing belt are proposed to achieve EIT lung imaging along with a custom portable EIT system. The simulation and experimental results have verified the validity of the proposed portable EIT system. Furthermore, the imaging results of using the proposed textile electrodes were compared with commercial electrocardiogram electrodes to evaluate their performance.
SCADA-Based Message Generator for Multi-Vendor Smart Grids: Distributed Integration and Verification of TASE.2
Authors: Ilgner Petr , Cika Petr , Stusek Martin
Published: October 2021

Recent developments in massive machine-type communication (mMTC) scenarios have given rise to never-seen requirements, which triggered the Industry 4.0 revolution. The new scenarios bring even more pressure to comply with the reliability and communication security and enable flawless functionality of the critical infrastructure, e.g., smart grid infrastructure. We discuss typical network grid architecture, communication strategies, and methods for building scalable and high-speed data processing and storage platform. This paper focuses on the data transmissions using the sets of standards IEC 60870-6 (ICCP/TASE.2). The main goal is to introduce the TASE.2 traffic generator and the data collection back-end with the implemented load balancing functionality to understand the limits of current protocols used in the smart grids. To this end, the assessment framework enabling generating and collecting TASE.2 communication with long-term data storage providing high availability and load balancing capabilities was developed. The designed proof-of-concept supports complete cryptographic security and allows users to perform the complex testing and verification of the TASE.2 network nodes configuration. Implemented components were tested in a cloud-based Microsoft Azure environment in four geographically separated locations. The findings from the testing indicate the high performance and scalability of the proposed platform, allowing the proposed generator to be also used for high-speed load testing purposes. The load-balancing performance shows the CPU usage of the load-balancer below 15% while processing 5000 messages per second. This makes it possible to achieve up to a 7-fold improvement of performance resulting in processing up to 35,000 messages per second.
VR-Based Job Training System Using Tangible Interactions
Authors: Baek Seongmin , Gil Youn-Hee , Kim Yejin
Published: October 2021

Virtual training systems are in an increasing demand because of real-world training, which requires a high cost or accompanying risk, and can be conducted safely through virtual environments. For virtual training to be effective for users, it is important to provide realistic training situations; however, virtual reality (VR) content using VR controllers for experiential learning differ significantly from real content in terms of tangible interactions. In this paper, we propose a method for enhancing the presence and immersion during virtual training by applying various sensors to tangible virtual training as a way to track the movement of real tools used during training and virtualizing the entire body of the actual user for transfer to a virtual environment. The proposed training system connects virtual and real-world spaces through an actual object (e.g., an automobile) to provide the feeling of actual touch during virtual training. Furthermore, the system measures the posture of the tools (steam gun and mop) and the degree of touch and applies them during training (e.g., a steam car wash.) User-testing is conducted to validate the increase in the effectiveness of virtual job training.
Statistical Time-Series Analysis of Interferometric Coherence from Sentinel-1 Sensors for Landslide Detection and Early Warning
Authors: Tzouvaras Marios
Published: October 2021

Landslides are one of the most destructive natural hazards worldwide, affecting greatly built-up areas and critical infrastructure, causing loss of human lives, injuries, destruction of properties, and disturbance in everyday commute. Traditionally, landslides are monitored through time consuming and costly in situ geotechnical investigations and a wide range of conventional means, such as inclinometers and boreholes. Earth Observation and the exploitation of the freely available Copernicus datasets, and especially Sentinel-1 Synthetic Aperture Radar (SAR) images, can assist in the systematic monitoring of landslides, irrespective of weather conditions and time of day, overcoming the restrictions arising from in situ measurements. In the present study, a comprehensive statistical analysis of coherence obtained through processing of a time-series of Sentinel-1 SAR imagery was carried out to investigate and detect early indications of a landslide that took place in Cyprus on 15 February 2019. The application of the proposed methodology led to the detection of a sudden coherence loss prior to the landslide occurrence that can be used as input to Early Warning Systems, giving valuable on-time information about an upcoming landslide to emergency response authorities and the public, saving numerous lives. The statistical significance of the results was tested using Analysis of Variance (ANOVA) tests and two-tailed t-tests.
Functional Connectivity and Frequency Power Alterations during P300 Task as a Result of Amyotrophic Lateral Sclerosis
Authors: Perez-Ortiz Claudia X. , Gordillo Jose L. , Mendoza-Montoya Omar , Antelis Javier M. , Caraza Ricardo , Martinez Hector R.
Published: October 2021

Amyotrophic Lateral Sclerosis (ALS) is one of the most aggressive neurodegenerative diseases and is now recognized as a multisystem network disorder with impaired connectivity. Further research for the understanding of the nature of its cognitive affections is necessary to monitor and detect the disease, so this work provides insight into the neural alterations occurring in ALS patients during a cognitive task (P300 oddball paradigm) by measuring connectivity and the power and latency of the frequency-specific EEG activity of 12 ALS patients and 16 healthy subjects recorded during the use of a P300-based BCI to command a robotic arm. For ALS patients, in comparison to Controls, the results (p < 0.05) were: an increment in latency of the peak ERP in the Delta range (OZ) and Alpha range (PO7), and a decreased power in the Beta band among most electrodes; connectivity alterations among all bands, especially in the Alpha band between PO7 and the channels above the motor cortex. The evolution observed over months of an advanced-state patient backs up these findings. These results were used to compute connectivity- and power-based features to discriminate between ALS and Control groups using Support Vector Machine (SVM). Cross-validation achieved a 100% in specificity and 75% in sensitivity, with an overall 89% success.