bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Impact of University Student Engagement on Junior Faculty’s Online Teaching Anxiety and Coping Strategies during COVID-19
Authors: Wang Yu , Wang Rong , Lu Jinjin
Published: September 2022

(1) Background: When online teaching or blended teaching becomes the new normal in college teaching and learning during the pandemic phase, how to cope with teaching anxiety and enhance online student engagement has been frequently discussed among scholars and practitioners. (2) Methods: This qualitative study aims to investigate the impact of online college student engagement on junior faculty’s online teaching anxiety in the pandemic era, with an emergent shift to online teaching as a new normal for higher education. The study analyzed the ways junior faculty adapted to enhance online student engagement and cope with anxiety-provoking sources. (3) Results: Online teaching anxiety may occur at the beginning of the semester or during a large amount of assessment and marking and can also occur with student complaints and the inactive online engagement of students. Student engagement is the most challenging pedagogical issue during online teaching, especially social and emotional engagement. (4) Conclusion: This study recommends that peer mentoring and university-level faculty professional development services are effective strategies to reduce junior faculty’s teaching anxiety. Pedagogy training and support should provide faculty with hands-on activities with problem-solving toolkits that they can take away to their own teaching.
Effects of Composite Electrode Structure on Performance of Intermediate-Temperature Solid Oxide Electrolysis Cell
Authors: Fu Zaiguo , Wang Zijing , Li Yongwei , Li Jingfa , Shao Yan , Zhu Qunzhi , Weng Peifen
Published: September 2022

The composite electrode structure plays an important role in the optimization of performance of the intermediate-temperature solid oxide electrolysis cell (IT-SOEC). However, the structural influence of the composite electrode on the performance of IT-SOEC is not clear. In this study, we developed a three-dimensional macroscale model coupled with the mesoscale model based on percolation theory. We describe the electrode structure on a mesoscopic scale, looking at the electrochemical reactions, flow, and mass transport inside an IT-SOEC unit with a composite electrode. The accuracy of this multi-scale model was verified by two groups of experimental data. We investigated the effects of operating pressure, volume fraction of the electrode phase, and particle diameter in the composite electrode on electrolysis reaction rate, overpotential, convection/diffusion flux, and hydrogen mole fraction. The results showed that the variation in the volume fraction of the electrode phase had opposite effects on the electrochemical reaction rate and multi-component diffusion inside the composite electrode. Meanwhile, an optimal range of 0.8–1 for the particle diameter ratio was favorable for hydrogen production. The analysis of IT-SOEC with composite electrodes using this multi-scale model enables the subsequent optimization of cell performance and composite electrode structure.
Improving Efficiency of Electric Energy System and Grid Operating Modes: Review of Optimization Techniques
Authors: Varganova Aleksandra V. , Khramshin Vadim R. , Radionov Andrey A.
Published: September 2022

Continuously growing tariff rates for energy carriers required to generate electrical and thermal energy bring about the need to search for alternatives. Such alternatives are intended for the reduction in the electricity and heat net costs as well as the expenses for the operation and maintenance of system elements and damage from power outages or deteriorated power quality. A way to reduce electricity and heat costs is the introduction of distributed energy resources capable of operating on both conventional (natural gas) and alternative (solar and wind energy, biomass, etc.) fuels. The problem of reducing electricity and, in some cases, heat costs are solved by applying mathematical optimization techniques adapted to a specific element or system of the industry in question. When it comes to power industry facilities, optimization, as a rule, includes reducing active power losses by controlling the system mode or specific power unit parameters; planning generating equipment operating modes; defining the optimal equipment composition; improving the regime and structural reliability of grids; scheduling preventive maintenance of equipment; searching for effective power unit operating modes. Many of the problems listed are solved using direct enumeration techniques; modern technical tools allow quickly solving such local problems with a large number of source data. However, in the case of integrated control over the power system or its individual elements, optimization techniques are used that allow considering a lot of operating limitations and the target function multicriteriality. This paper provides an analytical review of optimization techniques adapted to solving problems of improving the efficiency of the power facility operating modes. The article is made on the basis of the research conducted by the authors in the area of optimization of operating modes for electric energy systems and grids. The authors drew conclusions on the applicability of mathematical optimization methods in the power energy area. While conducting the research, the authors relied on their expertise in the development and introduction of the method to optimize the operation modes of energy supply systems with heterogeneous energy sources.
Model Control and Digital Implementation of the Three Phase Interleaved Parallel Bidirectional Buck–Boost Converter for New Energy Electric Vehicles
Authors: Zhang Chi , Xu Binyue , Jasni Jasronita , Radzi Mohd Amran Mohd , Azis Norhafiz , Zhang Qi
Published: September 2022

In recent years, the imminent environmental problems and increasing attention to the global energy crisis have prompted the need for new opportunities and technologies to meet higher demands for clean and sustainable energy systems. As a result, new energy electric vehicles have been developed to replace fossil fuel cars. Therefore, this paper presents a three-phase interleaved parallel bidirectional buck–boost converter, which is the core factor of electrical energy flow regulation and management between the battery pack and motor drive inverter within the high voltage direct current bus and converts the voltage from two directions. Corresponding circuit topology, mathematical model, and control strategy are analyzed in three operation states: charge buck, discharge boost, and electric energy interaction modes. The digital implementation with double closed loop, power feedforward compensation, and bidirectional switching logic are realized by XDPTM Digital Power Controllers XDPP1100-Q040 of Infineon Technologies AG. Finally, the experimental results of the proposed converter clearly show that it achieves the objectives, namely, the feasibility and practicality of the system.
Impact of Blockchain Technology on Smart Grids
Authors: Khan Hamzah , Masood Tariq
Published: September 2022

Energy systems are transforming due to the incorporation of multiple distributed energy resources, such as renewable energy and battery storage systems. This transformation has triggered a need to shift power distribution from a low efficiency centralized model with high coordination costs to a decentralized distribution system comprising smart grids. Researchers have discovered a number of uses for blockchain technology in the energy sector because of its decentralized structure and possibility for safe transactions. In order to pinpoint current trends and important research directions in this area, this article thoroughly examines the effects of blockchain technology on smart grids and distributed energy resources. The aim of this paper is also to identify research gaps and future research initiatives in the area of blockchain-based energy distribution. To do this, 92 research publications were subjected to a comprehensive literature review based on predetermined criteria. Transactive Energy, Electric Vehicle Integration, Privacy and Security, and Demand Response, together with some other relatively fresh and unexplored topics, were, therefore, highlighted as four major focal areas of blockchain energy research. We have also drawn attention to the gaps in the research that has already been done and the constraints imposed by present systems that must be removed before blockchain technology can be widely used.
Combined Effects of Defatted Hydrolyzed Collagen from Salmon Skin and Vitamin C on Proliferation and Migration of Human Fibroblast Cell
Authors: Chotphruethipong Lalita , Hutamekalin Pilaiwanwadee , Nilsuwan Krisana , Sukketsiri Wanida , Aluko Rotimi E. , Abdul Nazeer Rasool , Benjakul Soottawat
Published: September 2022

Skin injury causes fibroblast dysfunction and lowers collagen production. Safe, functional ingredients such as vitamin C (Vit C) and fish hydrolyzed collagen (HC) have been used to alleviate this problem. Defatted HC from salmon (Oncorhynchus nerka) skin could be a potential functional ingredient with skin nourishment activity. This study aimed to investigate the combined effects of HC and Vit C on the proliferation and migration of human dermal fibroblast (HDF). Molecular weight ranging from 102 Da to 10,175 Da and high imino acid content were found in HC. HC (0–800 µg/mL) or vitamin C (Vit C) (0.01–100 µg/mL) was applied for HDF treatment. Higher cell proliferation was found by adding HC at 50 µg/mL or Vit C at 0.01 µg/mL compared to the control and those treated with both compounds at other levels (p < 0.05). Cells treated with HC (50 µg/mL) combined with Vit C (0.01 µg/mL) (HC+Vit C) showed higher proliferation, migration, and lamellipodia formation of HDF cells than those treated with HC or Vit C alone. Moreover, all the samples tested could stimulate the proliferation and migration of HDF cells via FAK/Akt and ERK/p38 MAPK signaling pathways. Thus, HC combined with Vit C could be a promising functional ingredient for skin nourishment and would healing.
Establishing the Signal above the Noise: Accounting for an Environmental Background in the Detection and Quantification of Salmonid Environmental DNA
Authors: Hocking Morgan D. , MacAdams Jeffrey C. , Allison Michael J. , Bergman Lauren C. , Sneiderman Robert , Koop Ben F. , Starzomski Brian M. , Lesperance Mary L. , Helbing Caren C.
Published: September 2022

A current challenge for environmental DNA (eDNA) applications is how to account for an environmental (or false-positive) background in surveys. We performed two controlled experiments in the Goldstream Hatchery in British Columbia using a validated coho salmon (Oncorhynchus kisutch) eDNA assay (eONKI4). In the density experiment at high copy number, eDNA in 2 L water samples was measured from four 10 kL tanks containing 1 to 65 juvenile coho salmon. At these densities, we obtained a strong positive 1:1 relationship between predicted copy number/L and coho salmon biomass (g/L). The dilution experiment simulated a situation where fish leave a pool environment, and water from upstream continues to flow through at rates of 141–159 L/min. Here, three coho salmon were placed in four 10 kL tanks, removed after nine days, and the amount of remaining eDNA was measured at times coinciding with dilutions of 20, 40, 80, 160, and 1000 kL. The dilution experiment demonstrates a novel method using Binomial–Poisson distributions to detect target species eDNA at low copy number in the presence of an environmental background. This includes determination of the limit of blank with background (LOB-B) with a controlled false positive rate, and limit of detection with background (LOD-B) with a controlled false negative rate, which provides a statistically robust “Detect” or “No Detect” assessment for eDNA surveys.
Effects of Brief UV-C Irradiation Treatments on Rooting Performance of Pelargonium × hortorum (L.H. Bailey) Stem Cuttings
Authors: Darras Anastasios I. , Grigoropoulou Katerina , Dimiza Kallirroi , Zulfiqar Faisal
Published: September 2022

Pelargonium × hortorum (L.H. Bailey), is a South African native ornamental plant with worldwide commercial recognition used in gardens and terraces. In the present study, we evaluated the effects of low doses of UV-C irradiation on rooting performance of P. × hortorum stem cuttings. We also tested the hypothesis that UV-C-induced ethylene production directly interacted with rooting process. Over a 40 d evaluation period, the ethylene production of the UV-C-treated stem cuttings was significantly increased. UV-C irradiation positively affected rooting performance. Rooting percentage was increased in the UV-C-irradiated stem cuttings by up to 17%, time to rooting was decreased by 15% (e.g., 5 d) and root weight increased by 17% compared to the nonirradiated controls. UV-C irradiation did not affect net CO2 assimilation (As), but it induced transpiration (E) on the 14, 20, 22 and 24 d of the evaluation period. Positive correlations were found between ethylene production and As, E, stomatal conductance (gs) and root weight, while a negative correlation was recorded between days to rooting and ethylene. UV-C hastened flower production of the cuttings, but it did not affect colour parameters. We suggest that low doses of UV-C may induce endogenous ethylene production, which at low levels, interact with other hormonal mechanisms to activate root development.
Analysis of Host–Bacteria Protein Interactions Reveals Conserved Domains and Motifs That Mediate Fundamental Infection Pathways
Authors: Gómez Borrego Jordi , Torrent Burgas Marc
Published: September 2022

Adhesion and colonization of host cells by pathogenic bacteria depend on protein–protein interactions (PPIs). These interactions are interesting from the pharmacological point of view since new molecules that inhibit host-pathogen PPIs would act as new antimicrobials. Most of these interactions are discovered using high-throughput methods that may display a high false positive rate. The absence of curation of these databases can make the available data unreliable. To address this issue, a comprehensive filtering process was developed to obtain a reliable list of domains and motifs that participate in PPIs between bacteria and human cells. From a structural point of view, our analysis revealed that human proteins involved in the interactions are rich in alpha helix and disordered regions and poorer in beta structure. Disordered regions in human proteins harbor short sequence motifs that are specifically recognized by certain domains in pathogenic proteins. The most relevant domain–domain interactions were validated by AlphaFold, showing that a proper analysis of host-pathogen PPI databases can reveal structural conserved patterns. Domain–motif interactions, on the contrary, were more difficult to validate, since unstructured regions were involved, where AlphaFold could not make a good prediction. Moreover, these interactions are also likely accommodated by post-translational modifications, especially phosphorylation, which can potentially occur in 25–50% of host proteins. Hence, while common structural patterns are involved in host–pathogen PPIs and can be retrieved from available databases, more information is required to properly infer the full interactome. By resolving these issues, and in combination with new prediction tools like Alphafold, new classes of antimicrobials could be discovered from a more detailed understanding of these interactions.
miRNA: A Promising Therapeutic Target in Cancer
Authors: Menon Amrutha , Abd-Aziz Noraini , Khalid Kanwal , Poh Chit Laa , Naidu Rakesh
Published: September 2022

microRNAs are small non-coding RNAs that regulate several genes post-transcriptionally by complementarity pairing. Since discovery, they have been reported to be involved in a variety of biological functions and pathologies including cancer. In cancer, they can act as a tumor suppressor or oncomiR depending on the cell type. Studies have shown that miRNA-based therapy, either by inhibiting an oncomiR or by inducing a tumor suppressor, is effective in cancer treatment. This review focusses on the role of miRNA in cancer, therapeutic approaches with miRNAs and how they can be effectively delivered into a system. We have also summarized the patents and clinical trials in progress for miRNA therapy.
Milk Exosomal microRNAs: Postnatal Promoters of β Cell Proliferation but Potential Inducers of β Cell De-Differentiation in Adult Life
Authors: Melnik Bodo C. , Schmitz Gerd
Published: September 2022

Pancreatic β cell expansion and functional maturation during the birth-to-weaning period is driven by epigenetic programs primarily triggered by growth factors, hormones, and nutrients provided by human milk. As shown recently, exosomes derived from various origins interact with β cells. This review elucidates the potential role of milk-derived exosomes (MEX) and their microRNAs (miRs) on pancreatic β cell programming during the postnatal period of lactation as well as during continuous cow milk exposure of adult humans to bovine MEX. Mechanistic evidence suggests that MEX miRs stimulate mTORC1/c-MYC-dependent postnatal β cell proliferation and glycolysis, but attenuate β cell differentiation, mitochondrial function, and insulin synthesis and secretion. MEX miR content is negatively affected by maternal obesity, gestational diabetes, psychological stress, caesarean delivery, and is completely absent in infant formula. Weaning-related disappearance of MEX miRs may be the critical event switching β cells from proliferation to TGF-β/AMPK-mediated cell differentiation, whereas continued exposure of adult humans to bovine MEX miRs via intake of pasteurized cow milk may reverse β cell differentiation, promoting β cell de-differentiation. Whereas MEX miR signaling supports postnatal β cell proliferation (diabetes prevention), persistent bovine MEX exposure after the lactation period may de-differentiate β cells back to the postnatal phenotype (diabetes induction).
Novel Insights on Pyoverdine: From Biosynthesis to Biotechnological Application
Authors: Dell’Anno Filippo , Vitale Giovanni Andrea , Buonocore Carmine , Vitale Laura , Palma Esposito Fortunato , Coppola Daniela , Della Sala Gerardo , Tedesco Pietro , de Pascale Donatella
Published: September 2022

Pyoverdines (PVDs) are a class of siderophores produced mostly by members of the genus Pseudomonas. Their primary function is to accumulate, mobilize, and transport iron necessary for cell metabolism. Moreover, PVDs also play a crucial role in microbes’ survival by mediating biofilm formation and virulence. In this review, we reorganize the information produced in recent years regarding PVDs biosynthesis and pathogenic mechanisms, since PVDs are extremely valuable compounds. Additionally, we summarize the therapeutic applications deriving from the PVDs’ use and focus on their role as therapeutic target themselves. We assess the current biotechnological applications of different sectors and evaluate the state-of-the-art technology relating to the use of synthetic biology tools for pathway engineering. Finally, we review the most recent methods and techniques capable of identifying such molecules in complex matrices for drug-discovery purposes.
Role of Fibroblast Growth Factors in the Crosstalk of Hepatic Stellate Cells and Uveal Melanoma Cells in the Liver Metastatic Niche
Authors: Seitz Tatjana , John Nora , Sommer Judith , Dietrich Peter , Thasler Wolfgang E. , Hartmann Arndt , Evert Katja , Lang Sven A. , Bosserhoff Anja , Hellerbrand Claus
Published: September 2022

Hepatic metastasis is the critical factor determining tumor-associated mortality in different types of cancer. This is particularly true for uveal melanoma (UM), which almost exclusively metastasizes to the liver. Hepatic stellate cells (HSCs) are the precursors of tumor-associated fibroblasts and support the growth of metastases. However, the underlying mechanisms are widely unknown. Fibroblast growth factor (FGF) signaling is dysregulated in many types of cancer. The aim of this study was to analyze the pro-tumorigenic effects of HSCs on UM cells and the role of FGFs in this crosstalk. Conditioned medium (CM) from activated human HSCs significantly induced proliferation together with enhanced ERK and JNK activation in UM cells. An in silico database analysis revealed that there are almost no mutations of FGF receptors (FGFR) in UM. However, a high FGFR expression was found to be associated with poor survival for UM patients. In vitro, the pro-tumorigenic effects of HSC-CM on UM cells were abrogated by a pharmacological inhibitor (BGJ398) of FGFR1/2/3. The expression analysis revealed that the majority of paracrine FGFs are expressed by HSCs, but not by UM cells, including FGF9. Furthermore, the immunofluorescence analysis indicated HSCs as a cellular source of FGF9 in hepatic metastases of UM patients. Treatment with recombinant FGF9 significantly enhanced the proliferation of UM cells, and this effect was efficiently blocked by the FGFR1/2/3 inhibitor BGJ398. Our study indicates that FGF9 released by HSCs promotes the tumorigenicity of UM cells, and thus suggests FGF9 as a promising therapeutic target in hepatic metastasis.
The Translatability of Multiple Sclerosis Animal Models for Biomarkers Discovery and Their Clinical Use
Authors: Birmpili Dafni , Charmarke Askar Imane , Bigaut Kévin , Bagnard Dominique
Published: September 2022

Multiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system which is characterized by demyelinating lesions and axonal damage. MS is a complex disease characterized by important pathophysiological heterogeneity affecting the clinical appearance, progression and therapeutic response for each patient. Therefore, there is a strong unmet need to define specific biomarkers that will reflect the different features of the disease. Experimental autoimmune encephalomyelitis (EAE) is the most commonly used experimental model for the study of MS, as it resembles the pathological features of human MS in many aspects and has allowed for the elucidation of pathogenesis pathways and the validation of certain targets for MS therapies. In this review, we discuss clinically relevant MS molecular biomarkers, divided into five groups based on the key pathological hallmarks of MS: inflammation, blood–brain barrier disruption, myelin and axonal damage, gliosis and, ultimately, repair mechanisms. To address the feasibility of translation between the animal model and human disease, we present an overview of several molecular biomarkers of each category and compare their respective deregulation patterns. We conclude that, like any disease animal model, EAE models can sometimes fail to mimic the entire spectrum of human disease, but they can nonetheless recapitulate the disease’s primary hallmarks. We show that the EAE model is a valuable tool for understanding MS physiopathological mechanisms and for identifying biomarkers fundamental for drug development.
Spiropyran/Merocyanine Amphiphile in Various Solvents: A Joint Experimental–Theoretical Approach to Photophysical Properties and Self-Assembly
Authors: Savchenko Vladyslav , Lomadze Nino , Santer Svetlana , Guskova Olga
Published: September 2022

This joint experimental-theoretical work focuses on molecular and photophysical properties of the spiropyran-containing amphiphilic molecule in organic and aqueous solutions. Being dissolved in tested organic solvents, the system demonstrates positive photochromism, i.e., upon UV stimulus the colorless spiropyran form is transformed into colorful merocyanine isomer. However, the aqueous solution of the amphiphile possesses a negative photochromism: the orange-red merocyanine form becomes thermodynamically more stable in water, and both UV and vis stimuli lead to the partial or complete photobleaching of the solution. The explanation of this phenomenon is given on the basis of density functional theory calculations and classical modeling including thermodynamic integration. The simulations reveal that stabilization of merocyanine in water proceeds with the energy of ca. 70 kJ mol−1, and that the Helmholtz free energy of hydration of merocyanine form is 100 kJ mol−1 lower as compared to the behavior of SP isomer in water. The explanation of such a difference lies in the molecular properties of the merocyanine: after ring-opening reaction this molecule transforms into a zwitterionic form, as evidenced by the electrostatic potential plotted around the opened form. The presence of three charged groups on the periphery of a flat conjugated backbone stimulates the self-assembly of merocyanine molecules in water, ending up with the formation of elongated associates with stack-like building blocks, as shown in molecular dynamics simulations of the aqueous solution with the concentration above critical micelle concentration. Our quantitative evaluation of the hydrophilicity switching in spiropyran/merocyanine containing surfactants may prompt the search for new systems, including colloidal and polymeric ones, aiming at remote tuning of their morphology, which could give new promising shapes and patterns for the needs of modern nanotechnology.
Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations
Authors: Shah Asghar Ali , Alturise Fahad , Alkhalifah Tamim , Khan Yaser Daanial
Published: September 2022

Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocarcinoma starts in secretary cells. Breast adenocarcinoma is the most common of all cancers that occur in women. According to a survey within the United States of America, there are more than 282,000 breast adenocarcinoma patients registered each 12 months, and most of them are women. Recognition of cancer in its early stages saves many lives. A proposed framework is developed for the early detection of breast adenocarcinoma using an ensemble learning technique with multiple deep learning algorithms, specifically: Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Bi-directional LSTM. There are 99 types of driver genes involved in breast adenocarcinoma. This study uses a dataset of 4127 samples including men and women taken from more than 12 cohorts of cancer detection institutes. The dataset encompasses a total of 6170 mutations that occur in 99 genes. On these gene sequences, different algorithms are applied for feature extraction. Three types of testing techniques including independent set testing, self-consistency testing, and a 10-fold cross-validation test is applied to validate and test the learning approaches. Subsequently, multiple deep learning approaches such as LSTM, GRU, and bi-directional LSTM algorithms are applied. Several evaluation metrics are enumerated for the validation of results including accuracy, sensitivity, specificity, Mathew’s correlation coefficient, area under the curve, training loss, precision, recall, F1 score, and Cohen’s kappa while the values obtained are 99.57, 99.50, 99.63, 0.99, 1.0, 0.2027, 99.57, 99.57, 99.57, and 99.14 respectively.
Anti-Viral Photodynamic Inactivation of T4-like Bacteriophage as a Mammalian Virus Model in Blood
Authors: Santos Patrícia , Gomes Ana T. P. C. , Lourenço Leandro M. O. , Faustino Maria A. F. , Neves Maria G. P. M. S. , Almeida Adelaide
Published: September 2022

The laboratorial available methods applied in plasma disinfection can induce damage in other blood components. Antimicrobial photodynamic therapy (aPDT) represents a promising approach and is approved for plasma and platelet disinfection using non-porphyrinic photosensitizers (PSs), such as methylene blue (MB). In this study, the photodynamic action of three cationic porphyrins (Tri-Py(+)-Me, Tetra-Py(+)-Me and Tetra-S-Py(+)-Me) towards viruses was evaluated under white light irradiation at an irradiance of 25 and 150 mW·cm−2, and the results were compared with the efficacy of the approved MB. None of the PSs caused hemolysis at the isotonic conditions, using a T4-like phage as a model of mammalian viruses. All porphyrins were more effective than MB in the photoinactivation of the T4-like phage in plasma. Moreover, the most efficient PS promoted a moderate inactivation rate of the T4-like phage in whole blood. Nevertheless, these porphyrins, such as MB, can be considered promising and safe PSs to photoinactivate viruses in blood plasma.
A Comprehensive Review of High-Pressure Laser-Induced Materials Processing, Part I: Laser-Heated Diamond Anvil Cells
Authors: Alabdulkarim Mohamad E. , Maxwell Wendy D. , Thapliyal Vibhor , Maxwell James L.
Published: September 2022

Laser-heated diamond anvil cell (LH-DAC) experimentation has emerged as a leading technique for materials processing at extreme pressures and temperatures. LH-DAC systems are often employed to better characterise the structure and properties of materials in applications ranging from condensed matter physics to geophysical research to planetary science. This article reviews LH-DAC and related laser-based characterisation, as the first part of a series within the broader context of all high-pressure laser-induced material processing. In part I of this review, a synopsis of laser-heated diamond anvil cell experimental methods, developmental history, fundamental physicochemical processes, and emerging research trends are provided. Important examples of minerals/materials modified during LH-DAC investigations (since their inception) are also tabulated, including key phase transformations, material syntheses, laser parameters, and process conditions—as a reference for the reader and as a guide for directing future research efforts. Note that laser-dynamic-compression within diamond anvil cells (LDC-DAC experimentation) and laser-induced reactive chemical synthesis within diamond anvil cells (LRS-DAC experimentation) are treated separately, as Parts II and III of this review.
Influence of a Flat Polyimide Inlay on the Propagation of Guided Ultrasonic Waves in a Narrow GFRP-Specimen
Authors: Rittmeier Liv , Roloff Thomas , Rauter Natalie , Mikhaylenko Andrey , Haus Jan Niklas , Lammering Rolf , Dietzel Andreas , Sinapius Michael
Published: September 2022

Structural health monitoring systems for composite laminates using guided ultrasonic waves become more versatile with the structural integration of sensors. However, the data generated within these sensors have to be transmitted from the laminate to the outside, where polyimide-based printed circuit boards play a major role. This study investigates, to what extent integrated polyimide inlays with applied sensor bodies influence the guided ultrasonic wave propagation in glass fiber-reinforced polymer specimens. For reasons of resource efficiency, narrow specimens are used. Numerical simulations of a damping-free specimen indicate reflections of the S0-mode at the integrated inlay. This is validated experimentally with an air-coupled ultrasonic technique and a 3D laser Doppler vibrometry measurement. The experimental data are evaluated with a method including temporal and spatial continuous wavelet transformations to clearly identify periodically occurring wave packages as edge reflections and distinguish them from possible inlay reflections. However, even when separating in-plane and out-of-plane movements using the 3D measurement, no reflections at the inlays are detected. This leads to the conclusion that polyimide inlays are well suited as substrates for printed circuit boards integrated into fiber-reinforced polymer structures for structural health monitoring, since they do not significantly influence the wave propagation.
The Effect of Mixture Proportion on the Performance of Alkali-Activated Slag Concrete Subjected to Sulfuric Acid Attack
Authors: Teymouri Mohammad , Behfarnia Kiachehr , Shabani Amirhosein , Saadatian Armin
Published: September 2022

Long-term deterioration and durability concerns in harsh environments with acidic attacks are considered as the weaknesses of ordinary Portland cement (OPC) concrete. Although the performance of alkali-activated slag concrete (AASC) has been reported to be superior in acidic environments, there is a poor understanding regarding the impacts of diverse mix design parameters on AASC durability in an acidic environment. This research aims to understand the impact of mix design parameters on the durability of AASC in the sulfuric acid (H2SO4) environment with pH = 3. The type of alkaline solution, the molarity of alkaline solutions, the weight ratio of alkaline solutions to slag, and the weight ratio of NaOH to Na2SiO3 are mix design parameters investigated in this study. The compressive strength reduction and weight loss were monitored from early ages up to 180 days. Moreover, an OPC concrete sample was produced as a reference.
Bolt-Loosening Detection Using 1D and 2D Input Data Based on Two-Stream Convolutional Neural Networks
Authors: Hou Xiaoli , Guo Weichao , Ren Shengjie , Li Yan , Si Yue , Su Lizheng
Published: September 2022

At present, the detection accuracy of bolt-loosening diagnoses is still not high. In order to improve the detection accuracy, this paper proposes a fault diagnosis model based on the TSCNN model, which can simultaneously extract fault features from vibration signals and time-frequency images and can precisely detect the bolt-loosening states. In this paper, the LeNet-5 network is improved by adjusting the size and number of the convolution kernels, introducing the dropout operation, and building a two-dimensional convolutional neural network (2DCNN) model. Combining the advantages of a one-dimensional convolutional neural network (1DCNN) with wide first-layer kernels to suppress high-frequency noise, a two-stream convolutional neural network (TSCNN) is proposed based on 1D and 2D input data. The proposed model uses raw vibration signals and time-frequency images as input and automatically extracts sensitive features and representative information. Finally, the effectiveness and superiority of the proposed approach are verified by practical experiments that are carried out on a machine tool guideway. The experimental results show that the proposed approach can effectively achieve end-to-end bolt-loosening fault diagnoses, with an average recognition accuracy of 99.58%. In addition, the method can easily achieve over 93% accuracy when the SNR is over 0 dB without any denoising preprocessing. The results show that the proposed approach not only achieves high classification accuracy but also has good noise immunity.
The Effect of Micro-Alloying and Surface Finishes on the Thermal Cycling Reliability of Doped SAC Solder Alloys
Authors: Akkara Francy John , Hamasha Sa’d , Alahmer Ali , Evans John , Belhadi Mohamed El Amine , Wei Xin
Published: September 2022

The surface finish (SF) becomes a part of the solder joint during assembly and improves the component’s reliability. Furthermore, the SF influences the solder joint’s reliability by affecting the thickness of the intermetallic compound (IMC) layer at the solder interface and copper pads. In this experiment, five different alloys are used and compared with the SAC305 alloy, two of which, Innolot and SAC-Bi, are bi-based solder alloys. This study includes three common SFs: electroless nickel immersion gold (ENIG), immersion silver (ImAg), and organic solderability preserve (OSP). The performance of three surface finishes is examined in terms of component characteristic life. All of the boards were isothermally aged for twelve months at 125 °C. The boards were then exposed to 5000 cycles of thermal cycling at temperatures ranging from −40–+125 °C. Most of the current research considers only one or two factors affecting the reliability of the electronic package. This study combines the effect of multiple factors, including solder paste content, SF, isothermal aging, and thermal cycling, to ensure that the test conditions represent real-world applications. In addition, the electronics packages are assembled using commercialized alloys. The current study focuses on a high-performance alloy already present in the electronic market. The failure data were analyzed statistically using the Weibull distribution and design of experiments (DOE) analysis of variance (ANOVA) techniques. The findings reveal that the micro and uniformly distributed precipitates in solder microstructures are critical for high-reliability solder joints. Re-crystallization of the thermally cycled solder joints promotes the local formation of numerous new grains in stress-concentrated zones. As the fracture spreads along these grain boundaries and eventually fails, these new grains participate in crack propagation. Aging significantly worsens this situation. Finally, although the ENIG surface finish with its Ni layer outperforms other SFs, this does not imply that ENIG is more reliable in all solder paste/sphere/finish combinations.
Investigation on Atomic Bonding Structure of Solution-Processed Indium-Zinc-Oxide Semiconductors According to Doped Indium Content and Its Effects on the Transistor Performance
Authors: Kim Dongwook , Lee Hyeonju , Kim Bokyung , Baang Sungkeun , Ejderha Kadir , Bae Jin-Hyuk , Park Jaehoon
Published: September 2022

The atomic composition ratio of solution-processed oxide semiconductors is crucial in controlling the electrical performance of thin-film transistors (TFTs) because the crystallinity and defects of the random network structure of oxide semiconductors change critically with respect to the atomic composition ratio. Herein, the relationship between the film properties of nitrate precursor-based indium-zinc-oxide (IZO) semiconductors and electrical performance of solution-processed IZO TFTs with respect to the In molar ratio was investigated. The thickness, morphological characteristics, crystallinity, and depth profile of the IZO semiconductor film were measured to analyze the correlation between the structural properties of IZO film and electrical performances of the IZO TFT. In addition, the stoichiometric and electrical properties of the IZO semiconductor films were analyzed using film density, atomic composition profile, and Hall effect measurements. Based on the structural and stoichiometric results for the IZO semiconductor, the doping effect of the IZO film with respect to the In molar ratio was theoretically explained. The atomic bonding structure by the In doping in solution-processed IZO semiconductor and resulting increase in free carriers are discussed through a simple bonding model and band gap formation energy.
Epigenetic Manipulation Induced Production of Immunosuppressive Chromones and Cytochalasins from the Mangrove Endophytic Fungus Phomopsis asparagi DHS-48
Authors: Feng Ting , Wei Chengwen , Deng Xiaolin , Chen Dandan , Wen Zhenchang , Xu Jing
Published: September 2022

A mangrove endophytic fungus Phomopsis asparagi DHS-48 was found to be particularly productive with regard to the accumulation of substantial new compounds in our previous study. In order to explore its potential to produce more unobserved secondary metabolites, epigenetic manipulation was used on this fungus to activate cryptic or silent genes by using the histone deacetylase (HDAC) inhibitor sodium butyrate and the DNA methyltransferase (DNMT) inhibitor 5-azacytidine (5-Aza). Based on colony growth, dry biomass, HPLC, and 1H NMR analyses, the fungal chemical diversity profile was significantly changed compared with the control. Two new compounds, named phaseolorin J (1) and phomoparagin D (5), along with three known chromones (2–4) and six known cytochalasins (6–11), were isolated from the culture treated with sodium butyrate. Their structures, including their absolute configurations, were elucidated using a combination of detailed HRESIMS, NMR, and ECD and 13C NMR calculations. The immunosuppressive and cytotoxic activities of all isolated compounds were evaluated. Compounds 1 and 8 moderately inhibited the proliferation of ConA (concanavalin A)-induced T and LPS (lipopolysaccharide)-induced B murine spleen lymphocytes. Compound 5 exhibited significant in vitro cytotoxicity against the tested human cancer cell lines Hela and HepG2, which was comparative to the positive control adriamycin and fluorouracil. Our finding demonstrated that epigenetic manipulation should be an efficient strategy for the induction of new metabolites from mangrove endophytic fungi.
A Practical Method for Blind Pixel Detection for the Push-Broom Thermal-Infrared Hyperspectral Imager
Authors: Liu Bingxin , Du Yulong , Liu Chengyu , Li Ying
Published: September 2022

Thermal infrared hyperspectral imager is one of the frontier payloads in current hyperspectral remote sensing research. It has broad application prospects in land and ocean temperature inversion, environmental monitoring, and other fields. However, due to the influence of the production process of the infrared focal plane array and the characteristics of the material itself, the infrared focal plane array inevitably has blind pixels, resulting in spectral distortion of the data or even invalid data, which limits the application of thermal infrared hyperspectral data. Most of the current blind pixels detection methods are based on the spatial dimension of the image, that is, processing single-band area images. The push-broom thermal infrared hyperspectral imager works completely different from the conventional area array thermal imager, and only one row of data is obtained per scan. Therefore, the current method cannot be directly applied to blind pixels detection of push-broom thermal infrared hyperspectral imagers. Based on the imaging principle of push-broom thermal infrared hyperspectral imager, we propose a practical blind pixels detection method. The method consists of two stages to detect and repair four common types of blind pixels: dead pixel, dark current pixel, blinking pixel, and noise pixel. In the first stage, dead pixels and dark current pixels with a low spectral response rate are detected by spectral filter detection; noise pixels are detected by spatial noise detection; and dark current pixels with a negative response slope are detected by response slope detection. In the second stage, according to the random appearance of blinking pixels, spectral filter detection is used to detect and repair spectral anomalies caused by blinking pixels line by line. In order to verify the effectiveness of the proposed method, a flight test was carried out, using the Airborne Thermal-infrared Hyperspectral Imaging System (ATHIS), the latest thermal infrared imager in China, for data acquisition. The results show that the method proposed in this paper can accurately detect and repair blind pixel, thus effectively eliminating spectral anomalies and significantly improving image quality.
Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
Authors: Boolani Ali , Martin Joel , Huang Haikun , Yu Lap-Fai , Stark Maggie , Grin Zachary , Roy Marissa , Yager Chelsea , Teymouri Seema , Bradley Dylan , Martin Rebecca , Fulk George , Kakar Rumit Singh
Published: September 2022

Failure to obtain the recommended 7–9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7–9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night’s sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night’s sleep using single-task gait.
Thermal Infrared Tracking Method Based on Efficient Global Information Perception
Authors: Zhao Long , Liu Xiaoye , Ren Honge , Xue Lingjixuan
Published: September 2022

To solve the insufficient ability of the current Thermal InfraRed (TIR) tracking methods to resist occlusion and interference from similar targets, we propose a TIR tracking method based on efficient global information perception. In order to efficiently obtain the global semantic information of images, we use the Transformer structure for feature extraction and fusion. In the feature extraction process, the Focal Transformer structure is used to improve the efficiency of remote information modeling, which is highly similar to the human attention mechanism. The feature fusion process supplements the relative position encoding to the standard Transformer structure, which allows the model to continuously consider the influence of positional relationships during the learning process. It can also generalize to capture the different positional information for different input sequences. Thus, it makes the Transformer structure model the semantic information contained in images more efficiently. To further improve the tracking accuracy and robustness, the heterogeneous bi-prediction head is utilized in the object prediction process. The fully connected sub-network is responsible for the classification prediction of the foreground or background. The convolutional sub-network is responsible for the regression prediction of the object bounding box. In order to alleviate the contradiction between the vast demand for training data of the Transformer model and the insufficient scale of the TIR tracking dataset, the LaSOT-TIR dataset is generated with the generative adversarial network for network training. Our method achieves the best performance compared with other state-of-the-art trackers on the VOT2015-TIR, VOT2017-TIR, PTB-TIR and LSOTB-TIR datasets, and performs outstandingly especially when dealing with severe occlusion or interference from similar objects.