bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study and Modeling of Bifidobacterium and Bacillus Coculture Continuous Fermentation under Distal Intestine Simulated Conditions
Authors: Evdokimova Svetlana A. , Karetkin Boris A. , Guseva Elena V. , Gordienko Maria G. , Khabibulina Natalia V. , Panfilov Victor I. , Menshutina Natalia V. , Gradova Nina B.
Published: April 2022

The diversity and the stability of the microbial community are associated with microecological interactions between its members. Antagonism is one type of interaction, which particularly determines the benefits that probiotics bring to host health by suppressing opportunistic pathogens and microbial contaminants in food. Mathematical models allow for quantitatively predicting intrapopulation relationships. The aim of this study was to create predictive models for bacterial contamination outcomes depending on the probiotic antagonism and prebiotic concentration. This should allow an improvement in the screening of synbiotic composition for preventing gut microbial infections. The functional model (fermentation) was based on a three-stage continuous system, and the distal colon section (N2, pH 6.8, flow rate 0.04 h–1) was simulated. The strains Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 were chosen as the model probiotic and pathogen. Oligofructose Orafti P95 (OF) was used as the prebiotic at concentrations of 2, 5, 7, 10, 12, and 15 g/L of the medium. In the first stage, the system was inoculated with Bifidobacterium, and a dynamic equilibrium (Bifidobacterium count, lactic, and acetic acids) was achieved. Then, the system was contaminated with a 3-day Bacillus suspension (spores). The microbial count, as well as the concentration of acids and residual carbohydrates, was measured. A Bacillus monoculture was studied as a control. The stationary count of Bacillus in monoculture was markedly higher. An increase (up to 8 h) in the lag phase was observed for higher prebiotic concentrations. The specific growth rate in the exponential phase varied at different OF concentrations. Thus, the OF concentration influenced two key events of bacterial infection, which together determine when the maximal pathogen count will be reached. The mathematical models were developed, and their accuracies were acceptable for Bifidobacterium (relative errors ranging from 1.00% to 2.58%) and Bacillus (relative errors ranging from 0.74% to 2.78%) count prediction.
Protective, Biostimulating, and Eliciting Effects of Chitosan and Its Derivatives on Crop Plants
Authors: Stasińska-Jakubas Maria , Hawrylak-Nowak Barbara
Published: April 2022

Chitosan is a biodegradable and biocompatible polysaccharide obtained by partial deacetylation of chitin. This polymer has been gaining increasing popularity due to its natural origin, favorable physicochemical properties, and multidirectional bioactivity. In agriculture, the greatest hopes are raised by the possibility of using chitosan as a biostimulant, a plant protection product, an elicitor, or an agent to increase the storage stability of plant raw materials. The most important properties of chitosan include induction of plant defense mechanisms and regulation of metabolic processes. Additionally, it has antifungal, antibacterial, antiviral, and antioxidant activity. The effectiveness of chitosan interactions is determined by its origin, deacetylation degree and acetylation pattern, molecular weight, type of chemical modifications, pH, concentration, and solubility. There is a need to conduct research on alternative sources of chitosan, extraction methods, optimization of physicochemical properties, and commercial implementation of scientific progress outcomes in this field. Moreover, studies are necessary to assess the bioactivity and toxicity of chitosan nanoparticles and chitosan conjugates with other substances and to evaluate the consequences of the large-scale use thereof. This review presents the unique properties of chitosan and its derivatives that have the greatest importance for plant production and yield quality as well as the benefits and limitations of their application.
Structural Analysis of the Michael-Michael Ring Closure (MIMIRC) Reaction Products
Authors: Montenegro-Sustaita Mabel M. , Jiménez-Vázquez Hugo A. , Vargas-Díaz Elena , Herbert-Pucheta J. Enrique , Zepeda-Vallejo L. Gerardo
Published: April 2022

A representative number of decalin and hydrindane derivatives 2a–l were prepared in 11–91% yield by means of a cascade reaction of cyclohexanone/cyclopentanone enolates and methyl acrylate through a Michael–Michael ring closure (MIMIRC) process. The relative stereochemistry of the four stereogenic centers formed in all products was determined by analyzing the vicinal coupling constants from the 1H NMR and X-ray crystallography. Such a stereochemical outcome was corroborated by conformational analysis supported by DFT calculations and simulating the 1H NMR spectra of representative products. All products showed the same relative stereochemistry at C-1 and C-8a, while at C-3 and bridgehead carbon C-4a, configurational changes were observed. The present results provide some insights about the scope and limitations of the triple cascade reaction between cycloalkanone enolates with methyl acrylate. This synthetic protocol is still a simple and very practical alternative to generate decalin and hydrindane derivatives with great structural diversity.
Physicochemical and Microbiological Stability of Two Oral Solutions of Methadone Hydrochloride 10 mg/mL
Authors: Álvaro-Alonso Elena Alba , Lorenzo Ma Paz , Gonzalez-Prieto Andrea , Izquierdo-García Elsa , Escobar-Rodríguez Ismael , Aguilar-Ros Antonio
Published: April 2022

In this article, we studied physicochemical and microbiological stability and determined the beyond-use date of two oral solutions of methadone in three storage conditions. For this, two oral solutions of methadone (10 mg/mL) were prepared, with and without parabens, as preservatives. They were packed in amber glass vials kept unopened until the day of the test, and in a multi-dose umber glass bottle opened daily. They were stored at 5 ± 3 °C, 25 ± 2 °C and 40 ± 2 °C. pH, clarity, and organoleptic characteristics were obtained. A stability-indicating high-performance liquid chromatography method was used to determine methadone. Microbiological quality was studied and antimicrobial effectiveness testing was also determined following European Pharmacopoeia guidelines. Samples were analyzed at days 0, 7, 14, 21, 28, 42, 56, 70, and 91 in triplicate. After 91 days of storage, pH remained stable at about 6.5–7 in the two solutions, ensuring no risk of methadone precipitation. The organoleptic characteristics remained stable (colorless, odorless, and bitter taste). The absence of particles was confirmed. No differences were found with the use of preservatives. Methadone concentration remained within 95–105% in all samples. No microbial growth was observed. Hence, the two oral methadone solutions were physically and microbiologically stable at 5 ± 3 °C, 25 ± 2 °C, and 40 ± 2 °C for 91 days in closed and opened amber glass bottles.
Effectiveness of Volatile Natural Deep Eutectic Solvents (VNADESs) for the Green Extraction of Chelidonium majus Isoquinoline Alkaloids
Authors: Strzemski Maciej , Dresler Sławomir , Podkościelna Beata , Skic Kamil , Sowa Ireneusz , Załuski Daniel , Verpoorte Rob , Zielińska Sylwia , Krawczyk Paweł , Wójciak Magdalena
Published: April 2022

The Chelidonium majus plant is rich in biologically active isoquinoline alkaloids. These alkaline polar compounds are isolated from raw materials with the use of acidified water or methanol; next, after alkalisation of the extract, they are extracted using chloroform or dichloromethane. This procedure requires the use of toxic solvents. The present study assessed the possibility of using volatile natural deep eutectic solvents (VNADESs) for the efficient and environmentally friendly extraction of Chelidonium alkaloids. The roots and herb of the plant were subjected three times to extraction with various menthol, thymol, and camphor mixtures and with water and methanol (acidified and nonacidified). It has been shown that alkaloids can be efficiently isolated using menthol–camphor and menthol–thymol mixtures. In comparison with the extraction with acidified methanol, the use of appropriate VNADESs formulations yielded higher amounts of protopine (by 16%), chelidonine (35%), berberine (76%), chelerythrine (12%), and coptisine (180%). Sanguinarine extraction efficiency was at the same level. Additionally, the values of the contact angles of the raw materials treated with the tested solvents were assessed, and higher wetting dynamics were observed in the case of VNADESs when compared with water. These results suggest that VNADESs can be used for the efficient and environmentally friendly extraction of Chelidonium alkaloids.
1-Hydroxy-2(1H)-pyridinone-Based Chelators with Potential Catechol O-Methyl Transferase Inhibition and Neurorescue Dual Action against Parkinson’s Disease
Authors: Bergin Joseph C. J. , Tan Kean Kan , Nelson Anya K. , Amarandei Cristina-Andreea , Hubscher-Bruder Véronique , Brandel Jérémy , Voinarovska Varvara , Dejaegere Annick , Stote Roland H. , Tétard David
Published: April 2022

Two analogues of tolcapone where the nitrocatechol group has been replaced by a 1-hydroxy-2(1H)-pyridinone have been designed and synthesised. These compounds are expected to have a dual mode of action both beneficial against Parkinson’s disease: they are designed to be inhibitors of catechol O-methyl transferase, which contribute to the reduction of dopamine in the brain, and to protect neurons against oxidative damage. To assess whether these compounds are worthy of biological assessment to demonstrate these effects, measurement of their pKa and stability constants for Fe(III), in silico modelling of their potential to inhibit COMT and blood–brain barrier scoring were performed. These results demonstrate that the compounds may indeed have the desired properties, indicating they are indeed promising candidates for further evaluation.
Synthetic Receptors Based on Abiotic Cyclo(pseudo)peptides
Authors: Kubik Stefan
Published: April 2022

Work on the use of cyclic peptides or pseudopeptides as synthetic receptors started even before the field of supramolecular chemistry was firmly established. Research initially focused on the development of synthetic ionophores and involved the use of macrocycles with a repeating sequence of subunits along the ring to facilitate the correlation between structure, conformation, and binding properties. Later, nonnatural amino acids as building blocks were also considered. With growing research in this area, cyclopeptides and related macrocycles developed into an important and structurally diverse receptor family. This review provides an overview of these developments, starting from the early years. The presented systems are classified according to characteristic structural elements present along the ring. Wherever possible, structural aspects are correlated with binding properties to illustrate how natural or nonnatural amino acids affect binding properties.
Therapeutic Targets in Allergic Conjunctivitis
Authors: Labib Bisant A. , Chigbu DeGaulle I.
Published: April 2022

Allergic conjunctivitis (AC) is a common condition resulting from exposure to allergens such as pollen, animal dander, or mold. It is typically mediated by allergen-induced crosslinking of immunoglobulin E attached to receptors on primed conjunctival mast cells, which results in mast cell degranulation and histamine release, as well as the release of lipid mediators, cytokines, and chemokines. The clinical result is conjunctival hyperemia, tearing, intense itching, and chemosis. Refractory and chronic cases can result in ocular surface complications that may be vision threatening. Patients who experience even mild forms of this disease report an impact on their quality of life. Current treatment options range from non-pharmacologic therapies to ocular and systemic options. However, to adequately control AC, the use of multiple agents is often required. As such, a precise understanding of the immune mechanisms responsible for this ocular surface inflammation is needed to support ongoing research for potential therapeutic targets such as chemokine receptors, cytokine receptors, non-receptor tyrosine kinases, and integrins. This review utilized several published articles regarding the current therapeutic options to treat AC, as well as the pathological and immune mechanisms relevant to AC. This review will also focus on cellular and molecular targets in AC, with particular emphasis on potential therapeutic agents that can attenuate the pathology and immune mechanisms driven by cells, receptors, and molecules that participate in the immunopathogenesis and immunopathology of AC.
A Simplified Laser System for Atom Interferometry Based on a Free-Space EOM
Authors: Wu Bin , Zhao Yingpeng , Cheng Bing , Zhang Can , Li Dianrong , Zhu Dong , Yue Yazhou , Li Jun , Zhang Kaijun , Lin Qiang , Weng Kanxing
Published: April 2022

In this paper, a compact laser system for 87Rb atom interferometry based on only one free-space electro-optic modulator (EOM) was realized, where repumping and Raman beams were generated with a free-space EOM. In addition, this laser system does not require a laser amplifier compared to fibered EOM since fibered EOM cannot transmit high-power lasers. However, due to the narrow modulation linewidth of free-space EOM, it is impossible to obtain the frequencies of repumping and Raman beams separately, which would lead to some complicated effects. Therefore, a theoretical analysis was carried out to solve this problem, and a new frequency scheme for AI is proposed. For the experiment, the laser system of AI was built up. Moreover, the atomic interference fringes were obtained with a contrast of 20.7% (T = 60 ms) and the fitted phase resolution is approximately 1.25 mrad. The presented laser system could provide a new solution for compact AI systems in the future.
History of Herbicide-Resistant Traits in Cotton in the U.S. and the Importance of Integrated Weed Management for Technology Stewardship
Authors: Vulchi Rohith , Bagavathiannan Muthukumar , Nolte Scott A.
Published: April 2022

This paper reviews the history of herbicide-resistant (HR) traits in U.S. cotton since the beginning, highlighting the shortcomings of each trait over time that has led to the development of their successor and emphasizing the importance of integrated weed management (IWM) going forward to ensure their long-term sustainability. Introduction of glyphosate-resistant cropping systems has allowed for expansion of no-till systems more reliant on herbicides, favored less diverse crop rotations, and heavily relied on a single herbicide mode of action (MOA). With repeated applications of glyphosate over the years, biotypes of glyphosate-resistant (GR) A. palmeri and other weeds became economically damaging pests in cotton production systems throughout the U.S. Moreover, the reported cases of weeds resistant to different MOA across various parts of the United States has increased. The dicamba- (XtendFlex®) and 2,4-D-resistant (Enlist®) cotton traits (with stacks of glyphosate and glufosinate resistance) were introduced and have been highly adopted in the U.S. to manage HR weeds. Given the current rate of novel herbicide MOA discovery and increase in new HR weed cases, the future of sustainable weed management relies on an integrated approach that includes non-herbicidal methods with herbicides to ensure long-term success.
Vegetation Classification and Distribution Patterns in the South Slope of Yarlung Zangbo Grand Canyon National Nature Reserve, Eastern Himalayas
Authors: Wu Po-Po , Wang Zi , Jia Ning-Xia , Dong Shao-Qiong , Qu Xiao-Yun , Qiao Xian-Guo , Liu Chang-Cheng , Guo Ke
Published: April 2022

Yarlung Zangbo Grand Canyon National Nature Reserve has the most complete vertical vegetation belts in China. However, identification and distribution of vertical vegetation belts is still uncertain and in debate. To explore the above issues, 190 plots were surveyed within the reserve from 2019 to 2021. Based on the vegetation plot data, cluster analysis, ordination analysis, and biodiversity statistics were performed to reveal the structure of vertical vegetation belts–the driving factors of vegetation distribution–to describe the main biodiversity patterns. Five vertical vegetation belts were identified by clustering. NMDS ordination showed that the main factor of vegetation distribution is elevation. Based on the results of the analysis and previous literature, a new scheme of vertical vegetation belts in the south slope of the reserve was proposed. There was a lower montane seasonal rainforest belt (600–1100 m), a lower montane evergreen broadleaf forest belt (1100–1800 m), a middle montane semi-evergreen broadleaf forest belt (1800–2400 m), a subalpine evergreen needleleaf forest belt (2400–3800 m), a alpine shrubland and meadow belt (3800–4400 m), an alpine sparse vegetation belt (4400–4800 m), and a nival belt (4800–7782 m). Among them, the seasonal rainforest belts are the northernmost distribution of this type, and the semi-evergreen broadleaf forest belts exist only in the Eastern Himalayas. The study showed a unimodal pattern in plant species diversity, the peak of which is about 1900 m. The middle montane semi-evergreen broadleaf forest belt had the highest species diversity in the reserve. This study settled the issues regarding the vertical vegetation belts, the main drivers of vegetation and assessment of plant species diversity in the south slope of the Yarlung Zangbo Grand Canyon National Nature Reserve. It provides essential support for the management and conservation of these ecosystems in the reserve.
Desiccation Tolerance in Ramonda serbica Panc.: An Integrative Transcriptomic, Proteomic, Metabolite and Photosynthetic Study
Authors: Vidović Marija , Battisti Ilaria , Pantelić Ana , Morina Filis , Arrigoni Giorgio , Masi Antonio , Jovanović Sonja Veljović
Published: April 2022

The resurrection plant Ramonda serbica Panc. survives long desiccation periods and fully recovers metabolic functions within one day upon watering. This study aimed to identify key candidates and pathways involved in desiccation tolerance in R. serbica. We combined differential transcriptomics and proteomics, phenolic and sugar analysis, FTIR analysis of the cell wall polymers, and detailed analysis of the photosynthetic electron transport (PET) chain. The proteomic analysis allowed the relative quantification of 1192 different protein groups, of which 408 were differentially abundant between hydrated (HL) and desiccated leaves (DL). Almost all differentially abundant proteins related to photosynthetic processes were less abundant, while chlorophyll fluorescence measurements implied shifting from linear PET to cyclic electron transport (CET). The levels of H2O2 scavenging enzymes, ascorbate-glutathione cycle components, catalases, peroxiredoxins, Fe-, and Mn superoxide dismutase (SOD) were reduced in DL. However, six germin-like proteins (GLPs), four Cu/ZnSOD isoforms, three polyphenol oxidases, and 22 late embryogenesis abundant proteins (LEAPs; mainly LEA4 and dehydrins), were desiccation-inducible. Desiccation provoked cell wall remodeling related to GLP-derived H2O2/HO● activity and pectin demethylesterification. This comprehensive study contributes to understanding the role and regulation of the main metabolic pathways during desiccation aiming at crop drought tolerance improvement.
Characteristics of Sunburn Browning Fruit and Rootstock-Dependent Damage-Free Yield of Ambrosia™ Apple after Sustained Summer Heat Events
Authors: Xu Hao , Watanabe Yoichiro , Ediger Danielle , Yang Xiaotang , Iritani Davis
Published: April 2022

The 2021 summer heat waves experienced in the Pacific Northwest led to considerable fruit damage in many apple production zones. Sunburn browning (SB) was a particularly evident symptom. To understand the mechanism underlying the damage and to facilitate the early assessment of compromised fruit quality, we conducted a study on external characteristics and internal quality attributes of SB ‘Ambrosia’ apple (Malus domestica var. Ambrosia) and evaluated the fruit loss on five rootstocks. The cell integrity of the epidermal and hypodermal layers of fruit skins in the SB patch was compromised. Specifically, the number of chloroplasts and anthocyanin decreased in damaged cells, while autofluorescent stress-related compounds accumulated in dead cells. Consequently, the affected sun-exposed skin demonstrated a significant increase in differential absorbance between 670 nm and 720 nm, measured using a handheld apple DA meter, highlighting the potential of using this method as a non-destructive early indicator for sunburn damage. Sunburn browning eventually led to lower fruit weight, an increase in average dry matter content, soluble solids content, acidity, deteriorated weight retention, quicker loss of firmness, and accelerated ethylene emission during ripening. Significant inconsistency was found between the sun-exposed and shaded sides in SB apples regarding dry matter content, firmness, and tissue water potential, which implied preharvest water deficit in damaged tissues and the risk of quicker decline of postharvest quality. Geneva 935 (G.935), a large-dwarfing rootstock with more vigor and higher water transport capacity, led to a lower ratio of heat-damaged fruits and a higher yield of disorder-free fruits, suggesting rootstock selection as a long-term horticultural measure to mitigate summer heat stress.
Updated Principles of Sustainable Engineering
Authors: Glavič Peter
Published: April 2022

A change in human development patterns is needed, including mankind’s environmental, economic, and social behavior. Engineering methods and practices have a substantial impact on the way to sustainable development. An overview of the guiding principles of sustainability, sustainable design, green engineering, and sustainable engineering is presented first. Sustainable engineering principles need to be updated to include the present state of the art in human knowledge. Therefore, the updated principles of sustainable development are presented, including traditional and more recent items: a holistic approach, sustainability hierarchies, sustainable consumption, resource scarcity, equalities within and between generations, all stakeholders’ engagement, and internalizing externalities. Environmental, social, and economic impacts that respect humans’ true needs and well-being are of importance to the future. The updated 12 principles include the tridimensional system’s approach, precautionary and preventive approaches, and corporate reporting liability. The environmental principles comprise a circular economy with waste minimization, efficient use of resources, increased share of renewables, and sustainable production. The social pillar includes different views of equality, the engagement of stakeholders, social responsibilities, and decent work. Economic principles embrace human capital, creativity, and innovation in the development of products, processes and services, cost-benefit analysis using the Life Cycle Assessment, and the polluters must pay principle. The principles will require further development by engaging individual engineers, educators, and their associations.
Effects of a Guide Cone on the Flow Field and Performance of a New Dynamic Air Classifier
Authors: Li Qiang , Mou Xinliang , Fang Ying
Published: April 2022

A new dynamic air classifier was designed to address the problems of uneven material dispersion and high dust concentration in industrial applications of turbo air classifiers. This paper presents a study on the use of guide cones in the new dynamic air classifier. The ANSYS-Fluent 19.2 software was implemented to simulate the airflow in the dynamic air classifier, and the impact of the guide cone size on the flow field and classification performance of the dynamic air classifier was investigated. The simulation results indicated that with the increase in the guide cone height, the flow field distribution becomes reasonable and the velocity distributions become uniform. When the guide cone height is greater than twice the distance between the guide cone and the bottom of the rotor cage, there is no discernible change in the flow field distribution and classification efficiency. When the guide cone diameter is approximately 0.9 times the diameter of the rotor cage, the airflow pathline is more reasonable, and the flow field and velocity distributions are more uniform. An improper guide cone diameter and height will worsen the classification environment, resulting in a significant decline in classification performance. The material experimental and discrete phase simulation (DPM) showed that DPM can anticipate the changing trends of the cut size and classification accuracy. This study provides theoretical assistance for the structural design and optimization of an air classifier.
Coating Process of Honeycomb Cordierite Support with Ni/Boehmite Gels
Authors: Claude Vincent , Mahy Julien G. , Lohay Timothée , Geens Jérémy , Lambert Stéphanie D.
Published: April 2022

This study presents the development of a method for the washcoating of Ni/boehmite gels, prepared by the sol–gel process, onto the surface of a commercial ceramic monolith. Indeed, a cordierite monolith in a honeycomb shape was used as the substrate for the Ni/Al2O3 deposition. An experimental assembly was made in order to apply the coating on the cordierite surface. Different suspensions were used with various viscosities, and multiple coating parameters were tested as the withdrawal speed, or the number of impregnations. It was observed that the simple deposition of the Ni/boehmite gel led to the formation of coating. Different morphologies were observed, and defects were highlighted as cracks, coating-free areas or aggregates. Among the various parameters studied, the pH of the sol appeared to play a role even more important than the viscosity. Indeed, the sol acidified with nitric acid showed a coating which was almost free of cracks or of large aggregates. Moreover, the use of a slurry mix of calcined alumina particles and colloidal boehmite appeared also as an interesting path. The beneficial influence of the slurry was attributed to a better resistance of the coating against the stresses induced during drying, and a deviation of the cracks in the gels by slurry grains.
Unshakeable Hope: Pandemic Disruption, Climate Disruption, and the Ultimate Test of Theologies of Abundance
Authors: Grenfell-Lee Tallessyn Zawn
Published: April 2022

Leaders on the forefront of the rapidly escalating climate crisis continually seek effective strategies to help communities stay engaged without burning out or spiraling into despair. This paper examines the concept of adaptive change for its potential to reframe disruption and intentionally harness its potential for building resilience in both practical and psychological ways. In particular, social science suggests that secure communal bonds lay the foundation for the adaptive ability to build resilience through and from disruption. Swiss history offers an intriguing example of this phenomenon: held up as a model for its social, political, and ecological resilience, Swiss democracy evolved as part of the restructuring of society after a series of disruptive historical pandemics. This paper uses the Swiss example and the current COVID-19 (Coronavirus Disease) pandemic in order to explore the potential of transcendent and adaptive sociological and theological frameworks for the development of robust concepts of resilience in the face of climate destabilization. It further argues that a wide theological interpretation of Eucharistic abundance offers a lens through which to claim the liberative resurrection of disruptions, even, or perhaps especially, in the extreme case of human or planetary annihilation.
An Attention-Guided Framework for Explainable Biometric Presentation Attack Detection
Authors: Pan Shi , Hoque Sanaul , Deravi Farzin
Published: April 2022

Despite the high performances achieved using deep learning techniques in biometric systems, the inability to rationalise the decisions reached by such approaches is a significant drawback for the usability and security requirements of many applications. For Facial Biometric Presentation Attack Detection (PAD), deep learning approaches can provide good classification results but cannot answer the questions such as “Why did the system make this decision”? To overcome this limitation, an explainable deep neural architecture for Facial Biometric Presentation Attack Detection is introduced in this paper. Both visual and verbal explanations are produced using the saliency maps from a Grad-CAM approach and the gradient from a Long-Short-Term-Memory (LSTM) network with a modified gate function. These explanations have also been used in the proposed framework as additional information to further improve the classification performance. The proposed framework utilises both spatial and temporal information to help the model focus on anomalous visual characteristics that indicate spoofing attacks. The performance of the proposed approach is evaluated using the CASIA-FA, Replay Attack, MSU-MFSD, and HKBU MARs datasets and indicates the effectiveness of the proposed method for improving performance and producing usable explanations.
LEMON: A Lightweight Facial Emotion Recognition System for Assistive Robotics Based on Dilated Residual Convolutional Neural Networks
Authors: Devaram Rami Reddy , Beraldo Gloria , De Benedictis Riccardo , Mongiovì Misael , Cesta Amedeo
Published: April 2022

The development of a Social Intelligence System based on artificial intelligence is one of the cutting edge technologies in Assistive Robotics. Such systems need to create an empathic interaction with the users; therefore, it os required to include an Emotion Recognition (ER) framework which has to run, in near real-time, together with several other intelligent services. Most of the low-cost commercial robots, however, although more accessible by users and healthcare facilities, have to balance costs and effectiveness, resulting in under-performing hardware in terms of memory and processing unit. This aspect makes the design of the systems challenging, requiring a trade-off between the accuracy and the complexity of the adopted models. This paper proposes a compact and robust service for Assistive Robotics, called Lightweight EMotion recognitiON (LEMON), which uses image processing, Computer Vision and Deep Learning (DL) algorithms to recognize facial expressions. Specifically, the proposed DL model is based on Residual Convolutional Neural Networks with the combination of Dilated and Standard Convolution Layers. The first remarkable result is the few numbers (i.e., 1.6 Million) of parameters characterizing our model. In addition, Dilated Convolutions expand receptive fields exponentially with preserving resolution, less computation and memory cost to recognize the distinction among facial expressions by capturing the displacement of the pixels. Finally, to reduce the dying ReLU problem and improve the stability of the model, we apply an Exponential Linear Unit (ELU) activation function in the initial layers of the model. We have performed training and evaluation (via one- and five-fold cross validation) of the model with five datasets available in the community and one mixed dataset created by taking samples from all of them. With respect to the other approaches, our model achieves comparable results with a significant reduction in terms of the number of parameters.
High-Definition Survey of Architectural Heritage Fusing Multisensors—The Case of Beamless Hall at Linggu Temple in Nanjing, China
Authors: Fang Junwei , Zhang Yingying , Zhang Yiru , Guo Huayu , Sun Zheng
Published: April 2022

Following the development of digital measurement technology in recent years, the information contained in the measurement outcomes have become increasingly rich. However, the traditional graphical representation method based on vector graph needs to be updated. In this study, we use the Beamless Hall of Linggu Temple as an example. Measurements are conducted by using digital techniques, including three-dimensional (3D) laser scanning, close-range photogrammetry, and infrared thermal imaging. The pseudocolours that express spatial information and moisture distribution are calculated and generated through point clouds, which are used to express the land subsidence, wall deformation, moisture distribution, and other effects of the Beamless Hall. Furthermore, combining it with two-dimensional (2D) graphical representation, such as the plan, elevation, and section, damage-related information can be expressed intuitively and efficiently. This method can combine the advantages of graphics and images to provide a comprehensive and intuitive representation of the digital measurement results of brick architecture heritage. It can also provide a reference for surveying similar monuments and buildings of our architectural heritage.
Research on the Coordinate Attention Mechanism Fuse in a YOLOv5 Deep Learning Detector for the SAR Ship Detection Task
Authors: Xie Fang , Lin Baojun , Liu Yingchun
Published: April 2022

The real-time performance of ship detection is an important index in the marine remote sensing detection task. Due to the computing resources on the satellite being limited by the solar array size and the radiation-resistant electronic components, information extraction tasks are usually implemented after the image is transmitted to the ground. However, in recent years, the one-stage based target detector such as the You Only Look Once Version 5 (YOLOv5) deep learning framework shows powerful performance while being lightweight, and it provides an implementation scheme for on-orbit reasoning to shorten the time delay of ship detention. Optimizing the lightweight model has important research significance for SAR image onboard processing. In this paper, we studied the fusion problem of two lightweight models which are the Coordinate Attention (CA) mechanism module and the YOLOv5 detector. We propose a novel lightweight end-to-end object detection framework fused with a CA module in the backbone of a suitable position: YOLO Coordinate Attention SAR Ship (YOLO-CASS), for the SAR ship target detection task. The experimental results on the SSDD synthetic aperture radar (SAR) remote sensing imagery indicate that our method shows significant gains in both efficiency and performance, and it has the potential to be developed into onboard processing in the SAR satellite platform. The techniques we explored provide a solution to improve the performance of the lightweight deep learning-based object detection framework.
Transient Detection of Rotor Asymmetries in Squirrel-Cage Induction Motors Using a Model-Based Tacholess Order Tracking
Authors: Etien Erik , Doget Thierry , Rambault Laurent , Cauet Sebastien , Sakout Anas , Moreau Sandrine
Published: April 2022

In this article, we propose to determine the dynamic model of a squirrel-cage induction motor from a reduced amount of information. An adaptive observer is also built from this model in order to obtain a speed estimation and to perform rotor fault monitoring by Tacholess Order Tracking (TOT). We also propose a generalization of the notion of angular sampling in order to adapt to this type of defect. The procedure is validated in the laboratory on a test bench dedicated to the study of rotor bar defects.
A Multi-Mode Switching Variational Bayesian Adaptive Kalman Filter Algorithm for the SINS/PNS/GMNS Navigation System of Pelagic Ships
Authors: Zhang Jie , Wang Shanpeng , Li Wenshuo , Qiu Zhenbing
Published: April 2022

The ocean-going environment is complex and changeable with great uncertainty, which poses a huge challenge to the navigation ability of ships working in the pelagic ocean. In this paper, in an attempt to deal with the complex uncertain interference that the environment may bring to the strap-down inertial navigation system/polarization navigation system/geomagnetic navigation system (SINS/PNS/GMNS) integrated navigation system, the multi-mode switching variational Bayesian adaptive Kalman filter (MMS-VBAKF) algorithm is proposed. To be more specific, to identify the degrees of measurement interference more effectively, we design an interference evaluation and multi-mode switching mechanism using the original polarization information and geomagnetic information. Through this mechanism, the interference to the SINS/PNS/GMNS navigation system is divided into three cases. In case of slight interference (case SI), the variational Bayesian method is adopted directly to solve the problem that the statistical characteristics of measurement noise are unknown. By the fixed-point iteration mechanism, the statistical properties of the measurement noise and the system states can be estimated adaptively in real time. In case of interference-tolerance (case TI), the estimation of the statistical characteristics of measurement noise need to weigh the measurement information at the moment and a priori value information comprehensively. In case of excessive interference (case EI), the SINS/PNS/GMNS integrated navigation system will perform mode switching and filtering system reconstruction in advance. Then, the information fusion and navigation states estimation can be completed. Consequently, the reliability, robustness, and accuracy of the SINS/PNS/GMNS integrated navigation system can be guaranteed. Finally, the effectiveness of the algorithm is illustrated by the simulation experiments.
Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning
Authors: Alsaedi Mohammed , Ghaleb Fuad , Saeed Faisal , Ahmad Jawad , Alasli Mohammed
Published: April 2022

Web applications have become ubiquitous for many business sectors due to their platform independence and low operation cost. Billions of users are visiting these applications to accomplish their daily tasks. However, many of these applications are either vulnerable to web defacement attacks or created and managed by hackers such as fraudulent and phishing websites. Detecting malicious websites is essential to prevent the spreading of malware and protect end-users from being victims. However, most existing solutions rely on extracting features from the website’s content which can be harmful to the detection machines themselves and subject to obfuscations. Detecting malicious Uniform Resource Locators (URLs) is safer and more efficient than content analysis. However, the detection of malicious URLs is still not well addressed due to insufficient features and inaccurate classification. This study aims at improving the detection accuracy of malicious URL detection by designing and developing a cyber threat intelligence-based malicious URL detection model using two-stage ensemble learning. The cyber threat intelligence-based features are extracted from web searches to improve detection accuracy. Cybersecurity analysts and users reports around the globe can provide important information regarding malicious websites. Therefore, cyber threat intelligence-based (CTI) features extracted from Google searches and Whois websites are used to improve detection performance. The study also proposed a two-stage ensemble learning model that combines the random forest (RF) algorithm for preclassification with multilayer perceptron (MLP) for final decision making. The trained MLP classifier has replaced the majority voting scheme of the three trained random forest classifiers for decision making. The probabilistic output of the weak classifiers of the random forest was aggregated and used as input for the MLP classifier for adequate classification. Results show that the extracted CTI-based features with the two-stage classification outperform other studies’ detection models. The proposed CTI-based detection model achieved a 7.8% accuracy improvement and 6.7% reduction in false-positive rates compared with the traditional URL-based model.
Optimizing the Sensitivity of Biological Particle Detectors through Atmospheric Particle Analysis According to Climatic Characteristics in South Korea
Authors: Seo Hyunsoo , Choi Kibong , Jeong Young-Su
Published: April 2022

Biological agents used in biological warfare or bioterrorism are also present in bioaerosols. Prompt identification of a biological weapon and its characteristics is necessary. Herein, we optimized an environmentally adaptive detection algorithm that can better reflect changes in the complex South Korean environment than the current models. The algorithm distinguished between normal and biological particles using a laser-induced fluorescence-based biological particle detector capable of real-time measurements and size classification. We ensured that the algorithm operated with minimal false alarms in any environment by training based on experimental data acquired from an area where rainfall, snow, fog and mist, Asian dust, and water waves on the beach occur. To prevent time and money wastage due to false alarms, the detection performance for each level of sensitivity was examined to enable the selection of multiple sensitivities according to the background, and the appropriate level of sensitivity for the climate was determined. The basic sensitivity was set more conservatively than before, with a 3% alarm rate at 20 agent-containing particles per liter of air (ACPLA) and a 100% alarm rate at 63 ACPLA. The reliability was increased by optimizing five variables. False alarms did not occur in situations where no alarm was unnecessary.
Melding Fog Computing and IoT for Deploying Secure, Response-Capable Healthcare Services in 5G and Beyond
Authors: Tselios Christos , Politis Ilias , Amaxilatis Dimitrios , Akrivopoulos Orestis , Chatzigiannakis Ioannis , Panagiotakis Spyros , Markakis Evangelos K.
Published: April 2022

The fifth generation (5G) of mobile networks is designed to mark the beginning of the hyper-connected society through a broad set of novel features and disruptive characteristics, delivering massive connectivity, coverage and availability paired with unprecedented speed, throughput and capacity. Such a highly capable networking paradigm, facilitated by its integrated segments and available subsystems, will propel numerous cutting-edge, innovative and versatile services, spanning every possible business vertical. Augmented, response-capable healthcare services have already been identified as one of the prime objectives of both vendors and customers; therefore, addressing controversies and shortcomings related to the specific field is considered a priority for all stakeholders. The scope of this paper is to present the architectural elements of 5G which enable efficient, remote healthcare services along with emergency health monitoring and response capability. In addition, we propose a holistic scheme based on technical enablers such as Internet-of-Things (IoT) and Fog Computing, for mitigating common issues and current limitations which may compromise the proclaimed service delivery.
Spectral Reflectance as a Unique Tissue Identifier in Healthy Humans and Inhalation Injury Subjects
Authors: Bedolla Carlos N. , Rauschendorfer Catherine , Havard Drew B. , Guenther Blaine A. , Rizzo Julie A. , Blackburn August N. , Ryan Kathy L. , Blackburn Megan B.
Published: April 2022

Tracheal intubation is the preferred method of airway management, a common emergency trauma medicine problem. Currently, methods for confirming tracheal tube placement are lacking, and we propose a novel technology, spectral reflectance, which may be incorporated into the tracheal tube for verification of placement. Previous work demonstrated a unique spectral profile in the trachea, which allowed differentiation from esophageal tissue in ex vivo swine, in vivo swine, and human cadavers. The goal of this study is to determine if spectral reflectance can differentiate between trachea and other airway tissues in living humans and whether the unique tracheal spectral profile persists in the presence of an inhalation injury. Reflectance spectra were captured using a custom fiber-optic probe from the buccal mucosa, posterior oropharynx, and trachea of healthy humans intubated for third molar extraction and from the trachea of patients admitted to a burn intensive care unit with and without inhalation injury. Using ratio comparisons, we found that the tracheal spectral profile was significantly different from buccal mucosa or posterior oropharynx, but the area under the curve values are not high enough to be used clinically. In addition, inhalation injury did not significantly alter the spectral reflectance of the trachea. Further studies are needed to determine the utility of this technology in a clinical setting and to develop an algorithm for tissue differentiation.
Evaluation of the Multipath Environment Using Electromagnetic-Absorbing Materials at Continuous GNSS Stations
Authors: Hunegnaw Addisu , Teferle Felix Norman
Published: April 2022

To date, no universal modelling technique is available to mitigate the effect of site-specific multipaths in high-precision global navigation satellite system (GNSS) data processing. Multipaths affect both carrier-phase and code/pseudorange measurements, and the errors can propagate and cause position biases. This paper presents the use of an Eccosorb AN-W-79 microwave-absorbing material mounted around a GNSS antenna that reflects less than −17 dB of normal incident energy above a frequency of 600 MHz. To verify the feasibility and effectiveness of the Eccosorb, we installed two close stations by continuously operating multi-GNSS (BeiDou, GLONASS, Galileo and GPS) in a challenging location. One station is equipped with the Eccosorb AN-W-79, covering a square area of 3.35 m2 around the antenna, and the second station operates without it. The standard deviation reductions from single point positioning estimates are significant for all the individual GNSS solutions for the station equipped with microwave-absorbing material. The reductions are as follows: for GPS, between 15% and 23%; for Galileo, between 22% and 45%; for GLONASS, 22%; and for BeiDou, 4%. Furthermore, we assess the influence of multipaths by analysing the linear combinations of code and carrier phase measurements for various GNSS frequencies. The Galileo code multipath shows a reduction of more than 60% for the station with microwave-absorbing material. For GLONASS, particularly for the GLOM3X and GLOM1P code multipath combinations, the reduction reaches 50%, depending on the observation code types. For BeiDou, the reduction is more than 30%, and for GPS, it reaches between 20% and 40%. The Eccosorb AN-W-79 microwave-absorbing material shows convincing results in reducing the code multipath noise level. Again, using microwave-absorbing material leads to an improvement between 15% and 60% in carrier phase cycle slips. The carrier-phase multipath contents on the post-fit residuals from the processed GNSS solutions show a relative RMS reduction of 13% for Galileo and 9% for GLONASS and GPS when using the microwave-absorbing material. This study also presents power spectral contents from residual signal-to-noise ratio time series using Morlet wavelet transformation. The power spectra from the antenna with the Eccosorb AN-W-79 have the smallest magnitude, demonstrating the capacity of microwave-absorbing materials to lessen the multipath influence while not eliminating it.