bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Evaluation of Aerosol Therapy with Pentamidine-Loaded Liposomes Coated with Chondroitin Sulfate or Heparin for the Treatment of Leishmaniasis
Authors: Román-Álamo Lucía , Allaw Mohamad , Avalos-Padilla Yunuen , Manca Maria Letizia , Manconi Maria , Fulgheri Federica , Fernández-Lajo Jorge , Rivas Luis , Vázquez José Antonio , Peris José Esteban , Roca-Geronès Xavier , Poonlaphdecha Srisupaph , Alcover Maria Magdalena , Fisa Roser , Riera Cristina , Fernàndez-Busquets Xavier
Published: April 2023

The second-line antileishmanial compound pentamidine is administered intramuscularly or, preferably, by intravenous infusion, with its use limited by severe adverse effects, including diabetes, severe hypoglycemia, myocarditis and renal toxicity. We sought to test the potential of phospholipid vesicles to improve the patient compliance and efficacy of this drug for the treatment of leishmaniasis by means of aerosol therapy. The targeting to macrophages of pentamidine-loaded liposomes coated with chondroitin sulfate or heparin increased about twofold (up to ca. 90%) relative to noncoated liposomes. The encapsulation of pentamidine in liposomes ameliorated its activity on the amastigote and promastigote forms of Leishmania infantum and Leishmania pifanoi, and it significantly reduced cytotoxicity on human umbilical endothelial cells, for which the concentration inhibiting 50% of cell viability was 144.2 ± 12.7 µM for pentamidine-containing heparin-coated liposomes vs. 59.3 ± 4.9 µM for free pentamidine. The deposition of liposome dispersions after nebulization was evaluated with the Next Generation Impactor, which mimics human airways. Approximately 53% of total initial pentamidine in solution reached the deeper stages of the impactor, with a median aerodynamic diameter of ~2.8 µm, supporting a partial deposition on the lung alveoli. Upon loading pentamidine in phospholipid vesicles, its deposition in the deeper stages significantly increased up to ~68%, and the median aerodynamic diameter decreased to a range between 1.4 and 1.8 µm, suggesting a better aptitude to reach the deeper lung airways in higher amounts. In all, nebulization of liposome-encapsulated pentamidine improved the bioavailability of this neglected drug by a patient-friendly delivery route amenable to self-administration, paving the way for the treatment of leishmaniasis and other infections where pentamidine is active.
The Pharmacological Treatment of Chronic Pain: From Guidelines to Daily Clinical Practice
Authors: Marcianò Gianmarco , Vocca Cristina , Evangelista Maurizio , Palleria Caterina , Muraca Lucia , Galati Cecilia , Monea Francesco , Sportiello Liberata , De Sarro Giovambattista , Capuano Annalisa , Gallelli Luca
Published: April 2023

In agreement with the International Association for the Study of Pain, chronic pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage. To date, there are several types of pain: nociceptive, neuropathic, and nociplastic. In the present narrative review, we evaluated the characteristics of the drugs used for each type of pain, according to guidelines, and their effects in people with comorbidity to reduce the development of severe adverse events.
Ultrasound and Microbubbles Mediated Bleomycin Delivery in Feline Oral Squamous Cell Carcinoma—An In Vivo Veterinary Study
Authors: de Maar Josanne S. , Zandvliet Maurice M. J. M. , Veraa Stefanie , Tobón Restrepo Mauricio , Moonen Chrit T. W. , Deckers Roel
Published: April 2023

To investigate the feasibility and tolerability of ultrasound and microbubbles (USMB)-enhanced chemotherapy delivery for head and neck cancer, we performed a veterinary trial in feline companion animals with oral squamous cell carcinomas. Six cats were treated with a combination of bleomycin and USMB therapy three times, using the Pulse Wave Doppler mode on a clinical ultrasound system and EMA/FDA approved microbubbles. They were evaluated for adverse events, quality of life, tumour response and survival. Furthermore, tumour perfusion was monitored before and after USMB therapy using contrast-enhanced ultrasound (CEUS). USMB treatments were feasible and well tolerated. Among 5 cats treated with optimized US settings, 3 had stable disease at first, but showed disease progression 5 or 11 weeks after first treatment. One cat had progressive disease one week after the first treatment session, maintaining a stable disease thereafter. Eventually, all cats except one showed progressive disease, but each survived longer than the median overall survival time of 44 days reported in literature. CEUS performed immediately before and after USMB therapy suggested an increase in tumour perfusion based on an increase in median area under the curve (AUC) in 6 out of 12 evaluated treatment sessions. In this small hypothesis-generating study, USMB plus chemotherapy was feasible and well-tolerated in a feline companion animal model and showed potential for enhancing tumour perfusion in order to increase drug delivery. This could be a forward step toward clinical translation of USMB therapy to human patients with a clinical need for locally enhanced treatment.
Mesenchymal Stem Cell-Derived Exosomes in Ophthalmology: A Comprehensive Review
Authors: Wu Kevin Y. , Ahmad Hamza , Lin Grace , Carbonneau Marjorie , Tran Simon D.
Published: April 2023

Over the past decade, the field of mesenchymal stem cell (MSC) therapy has exhibited rapid growth. Due to their regenerative, reparatory, and immunomodulatory capacities, MSCs have been widely investigated as therapeutic agents in the cell-based treatment of chronic ophthalmic pathologies. However, the applicability of MSC-based therapy is limited by suboptimal biocompatibility, penetration, and delivery to the target ocular tissues. An emerging body of research has elucidated the role of exosomes in the biological functions of MSCs, and that MSC-derived extracellular vesicles (EVs) possess anti-inflammatory, anti-apoptotic, tissue repairing, neuroprotective, and immunomodulatory properties similar to MSCs. The recent advances in MSCs-derived exosomes can serve as solutions to the challenges faced by MSCs-therapy. Due to their nano-dimensions, MSC-derived exosomes can rapidly penetrate biological barriers and reach immune-privileged organs, allowing for efficient delivery of therapeutic factors such as trophic and immunomodulatory agents to ocular tissues that are typically challenging to target by conventional therapy and MSCs transplantation. In addition, the use of EVs minimizes the risks associated with mesenchymal stem cell transplantation. In this literature review, we focus on the studies published between 2017 and 2022, highlighting the characteristics of EVs derived from MSCs and their biological functions in treating anterior and posterior segment ocular diseases. Additionally, we discuss the potential use of EVs in clinical settings. Rapid advancements in regenerative medicine and exosome-based drug delivery, in conjunction with an increased understanding of ocular pathology and pharmacology, hold great promise for the treatment of ocular diseases. The potential of exosome-based therapies is exciting and can revolutionize the way we approach these ocular conditions.
Pharmacist-Led Implementation of Brief Tobacco Cessation Interventions during Mobile Health Access Events
Authors: Hudmon Karen Suchanek , Czarnik Julia S. , Lahey Alexa M. , Crowe Susie J. , Conklin Megan , Corelli Robin L. , Gonzalvo Jasmine D. , Hilts Katy Ellis
Published: April 2023

To address gaps in care for individuals from under-resourced communities disproportionately affected by tobacco use, this pharmacist-led demonstration project evaluated the feasibility of implementing tobacco use screening and brief cessation interventions during mobile health access events. A brief tobacco use survey was administered verbally during events at two food pantries and one homeless shelter in Indiana to assess the interest and potential demand for tobacco cessation assistance. Individuals currently using tobacco were advised to quit, assessed for their readiness to quit, and, if interested, offered a tobacco quitline card. Data were logged prospectively, analyzed using descriptive statistics, and group differences were assessed by site type (pantry versus shelter). Across 11 events (7 at food pantries and 4 at the homeless shelter), 639 individuals were assessed for tobacco use (n = 552 at food pantries; n = 87 at the homeless shelter). Among these, 189 self-reported current use (29.6%); 23.7% at food pantries, and 66.7% at the homeless shelter (p < 0.0001). About half indicated readiness to quit within 2 months; of these, 9 out of 10 accepted a tobacco quitline card. The results suggest that pharmacist-led health events at sites serving populations that are under-resourced afford unique opportunities to interface with and provide brief interventions for people who use tobacco.
Coupling of Photonic and Plasmonic Modes for Double Nanowire Cavities
Authors: Peng Xuanran , Liu Jing , Kang Yaru , Mao Xu , Yan Wei , Wang Xiaohui , Liu Kong , Xu Rui , Yang Fuhua , Li Zhaofeng
Published: April 2023

We analyze the coupling between double nanowire cavities for both photonic modes and plasmonic modes. When the spacing between nanowires reduces, a redshift of the resonant frequency of the symmetric mode and a blueshift of the resonant frequency of the antisymmetric mode are observed. Compared to single nanowire cavity modes, the Q factors of antisymmetric supermodes of double nanowires can be improved by 51% for photonic modes and by 24% for plasmonic modes. The mechanisms of Q factor improvement for photonic modes and plasmonic modes are studied based on the field distribution of radiations from the modes. This paper may contribute to research and applications for double nanowire lasers and nanowire laser arrays.
Adapting from Low to High: An Update to CO2-Concentrating Mechanisms of Cyanobacteria and Microalgae
Authors: Kupriyanova Elena V. , Pronina Natalia A. , Los Dmitry A.
Published: April 2023

The intracellular accumulation of inorganic carbon (Ci) by microalgae and cyanobacteria under ambient atmospheric CO2 levels was first documented in the 80s of the 20th Century. Hence, a third variety of the CO2-concentrating mechanism (CCM), acting in aquatic photoautotrophs with the C3 photosynthetic pathway, was revealed in addition to the then-known schemes of CCM, functioning in CAM and C4 higher plants. Despite the low affinity of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) of microalgae and cyanobacteria for the CO2 substrate and low CO2/O2 specificity, CCM allows them to perform efficient CO2 fixation in the reductive pentose phosphate (RPP) cycle. CCM is based on the coordinated operation of strategically located carbonic anhydrases and CO2/HCO3− uptake systems. This cooperation enables the intracellular accumulation of HCO3−, which is then employed to generate a high concentration of CO2 molecules in the vicinity of Rubisco’s active centers compensating up for the shortcomings of enzyme features. CCM functions as an add-on to the RPP cycle while also acting as an important regulatory link in the interaction of dark and light reactions of photosynthesis. This review summarizes recent advances in the study of CCM molecular and cellular organization in microalgae and cyanobacteria, as well as the fundamental principles of its functioning and regulation.
Variation of the Tensile Properties of Basalt-Fiber-Reinforced Polybutylene Succinate Matrix Composites during Microbial Degradation
Authors: Rova Lovisa , Kurita Hiroki , Kudo Shinji , Hatayama Sho , Kanno Teruyoshi , Gallet--Pandellé Alia , Narita Fumio
Published: April 2023

Little is known about how the strength of biodegradable polymers changes during decomposition. This study investigated the changes in the tensile properties of polybutylene succinate (PBS) and basalt-fiber (BF)-reinforced PBS (PBS-BF) composite sheets during degradation in bacterial solutions. Seven days after the start of the experiment, the elongation at break of the PBS specimens decreased significantly, and the PBS-BF composite specimens were characterized by barely any change in ultimate tensile strength (UTS) after immersion in the bacteria-free medium for 7 and 56 days. Meanwhile, when immersed in the bacterial solution, the UTS of the PBS-BF composite specimens showed a tendency to decrease after 7 days. After 56 days, the UTS decreased to about half of its value immediately after fabrication. The degradation of the material was attributed to infiltration of the bacterial solution into structurally weak areas, causing decomposition throughout the material.
Development and Characterization of New Energetic Composites Based on HNTO/AN Co-Crystal and Nitro-Cellulosic Materials
Authors: Boukeciat Hani , Tarchoun Ahmed Fouzi , Trache Djalal , Abdelaziz Amir , Meziani Redha , Klapötke Thomas M.
Published: April 2023

To develop advanced cellulose-based energetic composites, new types of high-energy-density formulations containing hydrazine 3-nitro-1,2,4-triazol-5-one (HNTO)/ammonium nitrate (AN) cocrystals combined with nitrocellulose or nanostructured cellulose nitrate (NC and NMCC) were experimentally characterized. The prepared energetic formulations were analyzed in terms of their physicochemical properties, mechanical sensitivities, structural features, and thermal behavior. Their heats of combustion and theoretical energetic performance were assessed as well. Experimental results exhibited the inherent characteristics of the designed NC@HNTO/AN and NMCC@HNTO/AN, including improved density, specific impulse, and impact sensitivity compared to their raw compounds. Besides that, thermo-kinetic findings revealed that the as-prepared insensitive and high-energy-density composites undergo two exothermic decomposition processes, and that NC@HNTO/AN has higher thermal activity. The present study demonstrated the outstanding characteristics of the new composites and could serve as a reference for developing more advanced cellulose-based energetic formulations.
Time–Concentration Superposition for Linear Viscoelasticity of Polymer Solutions
Authors: Li Can-Qi , Winter Horst Henning , Fan Yuan-Qi , Xu Geng-Xin , Yuan Xue-Feng
Published: April 2023

The concentration dependence of linear viscoelastic properties of polymer solutions is a well-studied topic in polymer physics. Dynamic scaling theories allow qualitative predictions of polymer solution rheology, but quantitative predictions are still limited to model polymers. Meanwhile, the scaling properties of non-model polymer solutions must be determined experimentally. In present paper, the time–concentration superposition (TCS) of experimental data is shown to be a robust procedure for studying the concentration scaling properties of binary and ternary polymer solutions. TCS can not only identify whether power law scaling may exist or not, and over which concentration range, but also unambiguously estimate the concentration scaling exponents of linear viscoelastic properties for a range of non-model polymer solutions.
Thermal-Mechanical Analysis of a Metro Station’s Concrete Structure
Authors: Ma Zongyuan , Li Wei , Li Zhaoyu ,   Xuefei Ruan, Jiao Kai
Published: April 2023

The problem of temperature variation in mass concrete construction is a crucial problem in civil engineering. The problems of the temperature field, damaged areas, and the cracking of the structure during the construction process of concrete pouring are analyzed in this paper. An elastic and damaged constitutive model for concrete and a fully coupled analysis method for analyzing the temperature-stress field was proposed to simulate and predict the construction process of a concrete structure in a metro station. The influence of different concrete compositions and material properties was not taken into account in this study. The results show that the temperature-stress complete coupling analysis method can be applied to the calculation and analysis of cracking in a concrete structure that is caused by internal temperature variations during the pouring process of complex concrete structures. An efficient method and research approach is proposed by this study to analyze the damage and cracking issues caused by temperature changes during the pouring process of concrete structures in metro stations. The area and extent of the damage and cracking during the construction can be predicted and evaluated, and a reference for metro station construction and operation is proposed.
Fixed Bed Batch Slow Pyrolysis Process for Polystyrene Waste Recycling
Authors: Albor Galo , Mirkouei Amin , McDonald Armando G. , Struhs Ethan , Sotoudehnia Farid
Published: April 2023

This study evaluates the potential of recycling polystyrene (PS) plastic wastes via a fixed bed (batch) slow pyrolysis reactor. The novelty lies in examining the reactor design, conversion parameters, and reaction kinetics to improve the process yield, activation energy, and chemical composition. PS samples were pyrolyzed at 475–575 °C for 30 min under 10–15 psi. Process yield and product attributes were evaluated using different methods to understand PS thermal degradation characteristics better. The results show that PS decomposition started within 2 min from all temperatures, and the total decomposition point of 97% at 475 °C at approximately 5 min. Additionally, analytical results indicate that the average necessary activation energy is 191 kJ/mol. Pyrolysis oil from PS was characterized by gas chromatography–mass spectrometry. The results show that styrene was produced 57–60% from all leading oil compounds (i.e., 2,4-diphenyl-1-butene, 2,4,6-triphenyl-1-hexene, and toluene), and 475 °C has the major average of conversion effectiveness of 91.3%. The results show that the reactor temperature remains the main conversion parameter to achieve the high process yield for oil production from PS. It is concluded that pyrolysis provides a sustainable pathway for PS waste recycling and conversion to value-added products, such as resins and polymers. The proposed method and analytical results are compared with earlier studies to identify directions for future studies.
A Novel Ascorbic Acid Based Natural Deep Eutectic Solvent as a Drilling Mud Additive for Shale Stabilization
Authors: Rasool Muhammad Hammad , Ahmad Maqsood , Ayoub Muhammad , Abbas Muhammad Adeem
Published: April 2023

During drilling, almost 70% of wellbore instability issues result from the encountering of shale formations. Various additives such as salts, silicates, and polymers are used in water-based mud to enhance its shale-inhibition capability; however, such additives have certain limitations. Lately, ionic liquids and deep eutectic solvents (DES) have been used by various research groups as shale inhibitors in drilling fluid due to their biodegradability and efficacy. However, their popularity faded when a natural derivative of DES, i.e., Natural Deep Eutectic solvent (NADES), came into the picture. This research utilizes the in-house-prepared Ascorbic acid and Glycerine (AA:Gly)-based NADES as a drilling fluid additive for shale inhibition and compares its efficacy with counterpart inhibitors such as KCl, imidazolium-based ionic liquid, and Choline Chloride-based DES. The results show that 3% NADES improved the overall Yield point to Plastic viscosity ratio, with a 39.69% decline in mud cake thickness and a 28% decline in the filtrate volume of drilling mud. Along with improved drilling fluid properties, 3% NADES resulted in 77.77% shale inhibition and 87% shale recovery. Surface tension, d-spacing, zeta potential, and FESEM have been conducted to justify and elucidate the inherent mechanism behind the working of NADES as a drilling fluid additive and clay stabilizer. Thus, Ascorbic acid-based NADES is recommended as a potential non-toxic and cheap drilling fluid additive to improve drilling fluid properties and clay stability.
Temporal and Spatial Distribution Characteristics of Microplastics and Their Influencing Factors in the Lincheng River, Zhoushan City, China
Authors: Cao Lu , Chen Wei , Wang Yudong , Li Sen , Jin Zhiyuan , Bian Jiayin , Li Qiang , Li Mingchang
Published: April 2023

Microplastics (MPs), a new type of pollutant, pose a significant threat to the environment at high concentrations. One of the primary sources of MPs in the ocean is river runoff, highlighting the need to investigate the spatial and temporal variations of MPs in rivers that flow into the sea, as well as their contributing factors. In this study, we analyzed MPs distribution and their influence factors in the Lincheng River, China. The Lincheng is the second largest river in Zhoushan island that directly flows into the ocean. MPs in the river water and sediments were detected during the wet season (July 2021), the dry season (November 2021) and the typhoon season (September 2021), and MPs were present in all reaches of the river. The abundance of MPs in the river was moderate compared to other studies, with the river water exhibiting a concentration of 15 ± 2.64 n/L and the sediment containing 318.24 ± 49.53 n/kg of MPs. In surface water, the most commonly found MP was blue man-made cellulose (CE), while the sediment contained mostly fragments of polypropylene (PP) and polypropylene polyethylene blends (PP + PE) in blue and green colors. The abundance of MPs showed significant seasonal differences, with higher abundance during the wet season compared to the dry season and typhoon period. Furthermore, local construction activities may contribute to higher MP abundance. To explore the influence factors of MPs, the Basin Development Index (BDI) was proposed, and a positive correlation between BDI and MP abundance was founded. This correlation indicates that the increase in land use for construction highly contributes to the MP pollution. In conclusion, future long-term monitoring of the abundance of MPs in the Lincheng River is necessary.
Integrated a Fused Silica Capillary Cell and In Situ Raman Spectroscopy for Determining the Solubility of CO2 in n-Decane and n-Decane + n-Hexane System
Authors: Wang Junliang , Zhang Zhenzhen , Wang Quanyuan , Lou Tianhong , Pan Zhiyan , Hu Mian
Published: April 2023

Understanding the solubility of CO2 is critical for implementing CO2-enhanced oil recovery (CO2-EOR). In this work, the solubility of CO2 in n-decane in a temperature range between 303.15 K and 353.15 K and pressures up to 15 MPa was measured using a fused silica capillary cell with in situ Raman spectroscopy. A semi-empirical CO2 solubility prediction model was obtained according to the experimental results. In order to improve the solubility of CO2 in n-decane, the solubility of CO2 in n-decane and co-solvent n-hexane (3% wt) mixture was also comparatively investigated. The results indicated that the solubility of CO2 in n-decane was 1.6355~64.0084 mol/kg. The data from the prediction model were in good agreement with the experimental data, and the mean relative deviation was 3.65%, indicating that the prediction model could be used to predict the solubility of CO2 in n-decane under different conditions. The solubility of CO2 in n-decane + n-hexane system ranged from 1.0127 mol/kg to 65.7286 mol/kg. It was found that, under low-pressure conditions, the addition of co-solvent n-hexane did not enhance the solubility of CO2, while it had a certain enhancement effect on the dissolution of CO2 under high-pressure conditions. As the temperature increased from 303.15 K to 353.15 K, the enhancement efficiency of the solubility of CO2 also increased from 1.34~2.05% to 8.17~9.82%, and the average enhancement efficiency increased from 1.74% to 9.00%. This study provides more CO2 solubility data for CO2-EOR.
Alive Publication
Authors: Gorbunov-Posadov Mikhail
Published: April 2023

An alive publication is a new genre for presenting the results of scientific research, where the scientific work is published online, and then is constantly being developed and improved by its author. Serious errors and typos are no longer fatal, nor do they haunt the author for the rest of his or her life. The reader of an alive publication knows that the author is constantly monitoring changes occurring in this branch of science. Alive publication faces the inertia of scientific publishing traditions and, in particular, traditional bibliometrics. Unfortunately, at present, the author who supports an alive publication is dramatically losing out on many generally accepted bibliometric indicators. The alive publication encourages the development of the bibliography apparatus. Each bibliographic reference will soon have to contain on-the-fly attributes such as attendance, number of external links, date of the last revision, etc. In the opinion of the writer of these lines, as the alive publication spreads over to the scientific world, the author’s concern for the publication’s evolution will become like a parent’s care for the development of a child. The Internet will be filled with scientific publications that do not lose their relevance with time.
Understanding Human Dignity in Shi’i Islam: Debates, Challenges, and Solutions for Contemporary Issues
Authors: Asghari SeyedAmirHossein
Published: April 2023

This study delves into the nuanced understanding of human dignity as expressed and upheld within the framework of Shi’i Islam. Drawing on the Quran as the primary source of Shi’i interpretation of the law and human rights, this research investigates the portrayal of human dignity in the Shia tradition through Islamic revelation. Furthermore, this study illuminates how certain Shia scholars depict the Quran as striving for the coherence of diverse religions and cultures and how Shia Imams have contributed to the discourse surrounding human dignity through their thoughts and actions. In addition, this study scrutinizes the debates on the compatibility of Islamic human dignity with the Universal Declaration of Human Rights, including contemporary challenges and the responses of Shi’i jurists to these challenges. However, while the Quran and Hadith resources offer sufficient references to human dignity, various approaches to human dignity remain among Shia jurists. Some Shia scholars consider human dignity to be acquired (Iktisābī) through human thoughts and deeds, while others ascribe to dignity an essential characteristic of humankind (dhātī) unconditionally bestowed by God. This research elaborates on how these interpretations, consequences, and requirements inspire Shia jurisprudence (fiqh), particularly in contemporary multicultural and pluralistic societies. Furthermore, it examines how this challenge is being debated among the proponents of each group and how it relates to human rights and current challenges. The study of contemporary developments in Shi’i fiqh regarding the role of human dignity and justice as Legal Maxims (al-qawāʿid al-fiqh) provides a necessary context for understanding and ensuring just legal rulings. Philosophically speaking, if God is the Lawgiver (Shāriʿ) and is Just and Wise, this raises the question of whether it is permissible for a jurist to enact laws that contradict human dignity and justice. This study aims to explore potential solutions to traditional challenges that do not consider human dignity and to suggest ways in which human dignity and justice can be applied as legal maxims.
Convolutional Neural Network Maps Plant Communities in Semi-Natural Grasslands Using Multispectral Unmanned Aerial Vehicle Imagery
Authors: Pöttker Maren , Kiehl Kathrin , Jarmer Thomas , Trautz Dieter
Published: April 2023

Semi-natural grasslands (SNGs) are an essential part of European cultural landscapes. They are an important habitat for many animal and plant species and offer a variety of ecological functions. Diverse plant communities have evolved over time depending on environmental and management factors in grasslands. These different plant communities offer multiple ecosystem services and also have an effect on the forage value of fodder for domestic livestock. However, with increasing intensification in agriculture and the loss of SNGs, the biodiversity of grasslands continues to decline. In this paper, we present a method to spatially classify plant communities in grasslands in order to identify and map plant communities and weed species that occur in a semi-natural meadow. For this, high-resolution multispectral remote sensing data were captured by an unmanned aerial vehicle (UAV) in regular intervals and classified by a convolutional neural network (CNN). As the study area, a heterogeneous semi-natural hay meadow with first- and second-growth vegetation was chosen. Botanical relevés of fixed plots were used as ground truth and independent test data. Accuracies up to 88% on these independent test data were achieved, showing the great potential of the usage of CNNs for plant community mapping in high-resolution UAV data for ecological and agricultural applications.
The Development of a Low-Cost Hydrophone for Passive Acoustic Monitoring of Dolphin’s Vocalizations
Authors: De Marco Rocco , Di Nardo Francesco , Lucchetti Alessandro , Virgili Massimo , Petetta Andrea , Li Veli Daniel , Screpanti Laura , Bartolucci Veronica , Scaradozzi David
Published: April 2023

Passive acoustics are widely used to monitor the presence of dolphins in the marine environment. This study aims to introduce a low-cost and homemade approach for assembling a complete underwater microphone (i.e., the hydrophone), employing cheap and easy to obtain components. The hydrophone was assembled with two piezo disks connected in a balanced configuration and encased in a plastic container filled with plastic foam. The hydrophone’s performance was validated by direct comparison with the commercially available AS-1 hydrophone (Aquarian Hydrophones, Anacortes, U.S.) on different underwater acoustic signals: artificial acoustic signals (ramp and multitone signals) and various dolphin vocalizations (whistle, echolocation clicks, and burst pulse signals). The sensitivity of the device’s performance to changes in the emission source position was also tested. The results of the validation procedure on both artificial signals and real dolphin vocalizations showed that the significant cost savings associated with cheap technology had a minimal effect on the recording device’s performance within the frequency range of 0–35 kHz. At this stage of experimentation, the global cost of the hydrophone could be estimated at a few euros, making it extremely price competitive when compared to more expensive commercially available models. In the future, this effective and low-cost technology would allow for continuous monitoring of the presence of free-ranging dolphins, significantly lowering the total cost of autonomous monitoring systems. This would permit broadening the monitored areas and creating a network of recorders, thus improving the acquisition of data.
Multi-Resolution Population Mapping Based on a Stepwise Downscaling Approach Using Multisource Data
Authors: Jin Yan , Liu Rui , Fan Haoyu , Li Pengdu , Liu Yaojie , Jia Yan
Published: April 2023

The distribution of the population is an essential aspect of addressing social, economic, and environmental problems. Gridded population data can provide more detailed information than census data, and multisource data from remote sensing and geographic information systems have been widely used for population estimation studies. However, due to spatial heterogeneity, the population has different distribution characteristics and variation patterns at different scales, while the relationships between multiple variables also vary with scale. This article presents a stepwise downscaling approach in that the random forest regression kriging technique is used to downscale census data to multi-resolution gridded population datasets. Using Nanjing, China, as the experimental case, population distribution maps were generated at 100 m, 500 m, and 1 km spatial resolution, and compared with the other three downscaling methods and three population products. The results demonstrated the produced gridded population maps by the proposed approach have higher accuracy and more accurate details of population distribution with the smallest mean absolute error (MAE) and root mean squared error (RMSE) values of 1.590 and 2.189 ten thousand people (over 40% reduction). The artificial land and road data are the two most important indicators of population distribution for the regional random forest modeling in Nanjing. Our proposed method can be a valuable tool for population mapping and has the potential to monitor sustainable development goals.
Long-Range Lightning Interferometry Using Coherency
Authors: Bai Xue , Füllekrug Martin
Published: April 2023

Traditional lightning detection and location networks use the time of arrival (TOA) technique to locate lightning events with a single time stamp. This contribution introduces a simulation study to lay the foundation for new lightning location concepts. Here, a novel interferometric method is studied which expands the data use and maps lightning events into an area by using coherency. The amplitude waveform bank, which consists of averaged waveforms classified by their propagation distances, is first used to test interferometric methods. Subsequently, the study is extended to individual lightning event waveforms. Both amplitude and phase coherency of the analytic signal are used here to further develop the interferometric method. To determine a single location for the lightning event and avoid interference between the ground wave and the first skywave, two solutions are proposed: (1) use a small receiver network and (2) apply an impulse response function to the recorded waveforms, which uses an impulse to represent the lightning occurrence. Both methods effectively remove the first skywave interference. This study potentially helps to identify the lightning ground wave without interference from skywaves with a long-range low frequency (LF) network. It is planned to expand the simulation work with data reflecting a variety of ionospheric and geographic scenarios.
High-Resolution Monitoring of Scour Using a Novel Fiber-Optic Distributed Temperature Sensing Device: A Proof-of-Concept Laboratory Study
Authors: Hatley Rebecca , Shehata Mahmoud , Sayde Chadi , Castro-Bolinaga Celso
Published: April 2023

Scour events can severely change the characteristics of streams and impose detrimental hazards on any structures built on them. The development of robust and accurate devices to monitor scour is therefore essential for studying and developing mitigation strategies for these adverse consequences. This technical note introduces a novel scour-monitoring device that utilizes new advances in the fiber-optic distributed temperature sensing (FO-DTS) technology. The novel FO-DTS scour-monitoring device utilizes the differential thermal responses of sediment, water, and air media to a heating event to accurately identify the locations of the interfaces between them. The performance of the device was tested in a laboratory flume under flow conditions with water velocities ranging from 0 m/s to 0.16 m/s. In addition, the effect of the measurement duration on the device’s measurement accuracy was also investigated. The FO-DTS scour-monitoring device managed to detect the sediment–water and water–air interfaces with average absolute errors of 1.60 cm and 0.63 cm, respectively. A measurement duration of fewer than 238 s was sufficient to obtain stable measurements of the locations of the sediment–water and water–air interfaces for all the tested flow conditions.
Defect Detection for Metal Shaft Surfaces Based on an Improved YOLOv5 Algorithm and Transfer Learning
Authors: Li Bi , Gao Quanjie
Published: April 2023

To address the problem of low efficiency for manual detection in the defect detection field for metal shafts, we propose a deep learning defect detection method based on the improved YOLOv5 algorithm. First, we add a Convolutional Block Attention Module (CBAM) mechanism layer to the last layer of the backbone network to improve the feature extraction capability. Second, the neck network introduces the Bi-directional Feature Pyramid Network (BiFPN) module to replace the original Path-Aggregation Network (PAN) structure and enhance the multi-scale feature fusion. Finally, we use transfer learning to pre-train the model and improve the generalization ability of the model. The experimental results show that the method achieves an average accuracy of 93.6% mAP and a detection speed of 16.7 FPS for defect detection on the dataset, which can identify metal shaft surface defects quickly and accurately, and is of reference significance for practical industrial applications.
A Novel OpenBCI Framework for EEG-Based Neurophysiological Experiments
Authors: Cardona-Álvarez Yeison Nolberto , Álvarez-Meza Andrés Marino , Cárdenas-Peña David Augusto , Castaño-Duque Germán Albeiro , Castellanos-Dominguez German
Published: April 2023

An Open Brain–Computer Interface (OpenBCI) provides unparalleled freedom and flexibility through open-source hardware and firmware at a low-cost implementation. It exploits robust hardware platforms and powerful software development kits to create customized drivers with advanced capabilities. Still, several restrictions may significantly reduce the performance of OpenBCI. These limitations include the need for more effective communication between computers and peripheral devices and more flexibility for fast settings under specific protocols for neurophysiological data. This paper describes a flexible and scalable OpenBCI framework for electroencephalographic (EEG) data experiments using the Cyton acquisition board with updated drivers to maximize the hardware benefits of ADS1299 platforms. The framework handles distributed computing tasks and supports multiple sampling rates, communication protocols, free electrode placement, and single marker synchronization. As a result, the OpenBCI system delivers real-time feedback and controlled execution of EEG-based clinical protocols for implementing the steps of neural recording, decoding, stimulation, and real-time analysis. In addition, the system incorporates automatic background configuration and user-friendly widgets for stimuli delivery. Motor imagery tests the closed-loop BCI designed to enable real-time streaming within the required latency and jitter ranges. Therefore, the presented framework offers a promising solution for tailored neurophysiological data processing.
Neustrelitz Total Electron Content Model for Galileo Performance: A Position Domain Analysis
Authors: Gioia Ciro , Angrisano Antonio , Gaglione Salvatore
Published: April 2023

Ionospheric error is one of the largest errors affecting global navigation satellite system (GNSS) users in open-sky conditions. This error can be mitigated using different approaches including dual-frequency measurements and corrections from augmentation systems. Although the adoption of multi-frequency devices has increased in recent years, most GNSS devices are still single-frequency standalone receivers. For these devices, the most used approach to correct ionospheric delays is to rely on a model. Recently, the empirical model Neustrelitz Total Electron Content Model for Galileo (NTCM-G) has been proposed as an alternative to Klobuchar and NeQuick-G (currently adopted by GPS and Galileo, respectively). While the latter outperforms the Klobuchar model, it requires a significantly higher computational load, which can limit its exploitation in some market segments. NTCM-G has a performance close to that of NeQuick-G and it shares with Klobuchar the limited computation load; the adoption of this model is emerging as a trade-off between performance and complexity. The performance of the three algorithms is assessed in the position domain using data for different geomagnetic locations and different solar activities and their execution time is also analysed. From the test results, it has emerged that in low- and medium-solar-activity conditions, NTCM-G provides slightly better performance, while NeQuick-G has better performance with intense solar activity. The NTCM-G computational load is significantly lower with respect to that of NeQuick-G and is comparable with that of Klobuchar.
Method of Failure Diagnostics to Linear Rolling Guides in Handling Machines
Authors: Jírová Radka , Pešík Lubomír , Žuľová Lucia , Grega Robert
Published: April 2023

Linear rolling guides, used in production machines for the realisation of linear motion, demand in industrial practice early damage identification to prevent production outages and losses. Therefore, the article aims for early damage diagnostics that use the principle of a load-free diagnostic part integrated into the carriage of the linear rolling guide. This principle was employed for developing an innovative method of damage identification to a guiding profile or rolling elements. The proposed innovative method is based on analysing vibration acceleration measured on the diagnostic part in the context of carriage position. In addition, a unique connection of an acceleration sensor to the diagnostic part through a mechanical component with defined parameters of stiffness and mass was designed. The innovative method was verified by laboratory testing on a designed functional sample of the diagnostic system. The computed reliability of the proposed diagnostic method reached 98%.
Automatic Pavement Crack Detection Transformer Based on Convolutional and Sequential Feature Fusion
Authors: Sun Zhaoyun , Zhai Junzhi , Pei Lili , Li Wei , Zhao Kaiyue
Published: April 2023

To solve the problem of low accuracy of pavement crack detection caused by natural environment interference, this paper designed a lightweight detection framework named PCDETR (Pavement Crack DEtection TRansformer) network, based on the fusion of the convolution features with the sequence features and proposed an efficient pavement crack detection method. Firstly, the scalable Swin-Transformer network and the residual network are used as two parallel channels of the backbone network to extract the long-sequence global features and the underlying visual local features of the pavement cracks, respectively, which are concatenated and fused to enrich the extracted feature information. Then, the encoder and decoder of the transformer detection framework are optimized; the location and category information of the pavement cracks can be obtained directly using the set prediction, which provided a low-code method to reduce the implementation complexity. The research result shows that the highest AP (Average Precision) of this method reaches 45.8% on the COCO dataset, which is significantly higher than that of DETR and its variants model Conditional DETR where the AP values are 36.9% and 42.8%, respectively. On the self-collected pavement crack dataset, the AP of the proposed method reaches 45.6%, which is 3.8% higher than that of Mask R-CNN (Region-based Convolution Neural Network) and 8.8% higher than that of Faster R-CNN. Therefore, this method is an efficient pavement crack detection algorithm.
Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors
Authors: Airaksinen Manu , Vanhatalo Sampsa , Räsänen Okko
Published: April 2023

Infant motility assessment using intelligent wearables is a promising new approach for assessment of infant neurophysiological development, and where efficient signal analysis plays a central role. This study investigates the use of different end-to-end neural network architectures for processing infant motility data from wearable sensors. We focus on the performance and computational burden of alternative sensor encoder and time series modeling modules and their combinations. In addition, we explore the benefits of data augmentation methods in ideal and nonideal recording conditions. The experiments are conducted using a dataset of multisensor movement recordings from 7-month-old infants, as captured by a recently proposed smart jumpsuit for infant motility assessment. Our results indicate that the choice of the encoder module has a major impact on classifier performance. For sensor encoders, the best performance was obtained with parallel two-dimensional convolutions for intrasensor channel fusion with shared weights for all sensors. The results also indicate that a relatively compact feature representation is obtainable for within-sensor feature extraction without a drastic loss to classifier performance. Comparison of time series models revealed that feedforward dilated convolutions with residual and skip connections outperformed all recurrent neural network (RNN)-based models in performance, training time, and training stability. The experiments also indicate that data augmentation improves model robustness in simulated packet loss or sensor dropout scenarios. In particular, signal- and sensor-dropout-based augmentation strategies provided considerable boosts to performance without negatively affecting the baseline performance. Overall, the results provide tangible suggestions on how to optimize end-to-end neural network training for multichannel movement sensor data.
A Digital Twin-Based Distributed Manufacturing Execution System for Industry 4.0 with AI-Powered On-The-Fly Replanning Capabilities
Authors: Vyskočil Jiří , Douda Petr , Novák Petr , Wally Bernhard
Published: April 2023

Industry 4.0 smart production systems comprise industrial systems and subsystems that need to be integrated in such a way that they are able to support high modularity and reconfigurability of all system components. In today’s industrial production, manufacturing execution systems (MESs) and supervisory control and data acquisition (SCADA) systems are typically in charge of orchestrating and monitoring automated production processes. This article explicates an MES architecture that is capable of autonomously composing, verifying, interpreting, and executing production plans using digital twins and symbolic planning methods. To support more efficient production, the proposed solution assumes that the manufacturing process can be started with an initial production plan that may be relatively inefficient but quickly found by an AI. While executing this initial plan, the AI searches for more efficient alternatives and forwards better solutions to the proposed MES, which is able to seamlessly switch between the currently executed plan and the new plan, even during production. Further, this on-the-fly replanning capability is also applicable when newly identified production circumstances/objectives appear, such as a malfunctioning robot, material shortage, or a last-minute change to a customizable product. Another feature of the proposed MES solution is its distributed operation with multiple instances. Each instance can interpret its part of the production plan, dedicated to a location within the entire production site. All of these MES instances are continuously synchronized, and the actual global or partial (i.e., from the instance perspective) progress of the production is handled in real-time within one common digital twin. This article presents three main contributions: (i) an execution system that is capable of switching seamlessly between an original and a subsequently introduced alternative production plan, (ii) on-the-fly AI-powered planning and replanning of industrial production integrated into a digital twin, and (iii) a distributed MES, which allows for running multiple instances that may depend on topology or specific conditions of a real production plant. All of these outcomes are demonstrated and validated on a use-case utilizing an Industry 4.0 testbed, which is equipped with an automated transport system and several industrial robots. While our solution is tested on a lab-sized production system, the technological base is prepared to be scaled up to larger systems.