bluuebunny/crossref_metadata_2025 huggingface dataset:
Engineering a Lactobacillus Lysine Riboswitch to Dynamically Control Metabolic Pathways for Lysine Production in Corynebacterium glutamicum
Authors: Jiang Qingwei , Geng Feng , Shen Juan , Zhu Ping , Lu Zhaoxin , Zhou Libang , Lu Fengxia
Published: March 2024

Knock-out of genes of metabolic pathways is conventionally used in the metabolic engineering of microorganisms, but it is not applicable for genes of essential pathways. In order to avoid undesirable effects caused by gene deletion, it is attractive to develop riboswitches to dynamically control the metabolic pathways of microbial cell factories. In this regard, the aim of this study is to utilize the lysine riboswitch to control gene expressions of the biosynthetic pathways and by-pathways and thus improve lysine production in Corynebacterium glutamicum. To achieve this, a natural lysine riboswitch from Lactobacillus plantarum (LPRS) was first detected and then fused with RFP to test its functionality. After that, engineered lysine-activated (Lys-A) and lysine-repressed (Lys-R) riboswitches were successfully screened by dual genetic selection. Furthermore, the optimized A263 and R152 were applied to control the expression of aspartate kinase III and homoserine dehydrogenase in the lysine-producing strain C. glutamicum QW45, respectively. In contrast with QW45, the growth of the resulting A263-lysC mutant QW48 was similar to that of QW45; however, the growth of the resulting R357-hom mutant QW54 was slightly inhibited, indicating an inhibition of threonine biosynthesis caused by the riboswitch upon binding of intracellular lysine. Importantly, the lysine production of QW48 and QW54 was, respectively, 35% and 43% higher than that of the parent strain QW45, implying more metabolic flux directed into the lysine synthesis pathway. Finally, the engineered A263 and R357 were simultaneously applied to the same mutant QW55, which greatly improved lysine production. Thus, the approach demonstrated in this work could be principally used as a powerful tool to dynamically control any other undesired metabolic pathways.
The Importance of Substituent Position for Antibacterial Activity in the Group of Thiosemicarbazide Derivatives
Authors: Janowska Sara , Stefańska Joanna , Khylyuk Dmytro , Wujec Monika
Published: March 2024

The search for new antibacterial compounds is still a huge challenge for scientists. Each new chemotherapy drug is not 100% effective when introduced into treatment. Bacteria quickly become resistant to known structures. One promising group of new compounds is thiosemicarbazides. In the presented work, we looked for the relationship between structure and antibacterial activity within the group of thiosemicarbazide derivatives. This is a continuation of our previous work. Here, we decided to check to what extent the position of the 3-methoxyphenyl substituent affects potency. We obtained new structures that differ in the positions of the substituent in the thiosemicarbazide skeleton. Based on the obtained results of the biological tests, it can be concluded that the substituent in position 1 of thiosemicarbazide derivatives significantly determines their activity. Generally, among the substituents used, trifluoromethylphenyl turned out to be the most promising. The MIC values for compounds with this substituent are 64 µg/mL towards Staphylococci sp. Using molecular docking, we tried to explain the mechanism behind the antibacterial activity of the tested compounds.
Purification and Biochemical Characterization of Polyphenol Oxidase Extracted from Wheat Bran (Wan grano)
Authors: Yu Kun , He Wei , Ma Xiaoli , Zhang Qi , Chen Chunxu , Li Peiyan , Wu Di
Published: March 2024

Currently, little is known about the characteristics of polyphenol oxidase from wheat bran, which is closely linked to the browning of wheat product. The wheat PPO was purified by ammonium sulfate precipitation, DEAE-Sepharose ion-exchange column, and Superdex G-75 chromatography column. Purified wheat PPO activity was 11.05-fold higher, its specific activity was 1365.12 U/mg, and its yield was 8.46%. SDS-PAGE showed that the molecular weight of wheat PPO was approximately 21 kDa. Its optimal pH and temperature were 6.5 and 35 °C for catechol as substrate, respectively. Twelve phenolic substrates from wheat and green tea were used for analyzing the substrate specificity. Wheat PPO showed the highest affinity to catechol due to its maximum Vmax (517.55 U·mL−1·min−1) and low Km (6.36 mM) values. Docking analysis revealed strong affinities between catechol, gallic acid, EGCG, and EC with binding energies of −5.28 kcal/mol, −4.65 kcal/mol, −4.21 kcal/mol, and −5.62 kcal/mol, respectively, for PPO. Sodium sulfite, ascorbic acid, and sodium bisulfite dramatically inhibited wheat PPO activity. Cu2+ and Ca2+ at 10 mM were considered potent activators and inhibitors for wheat PPO, respectively. This report provides a theoretical basis for controlling the enzymatic browning of wheat products fortified with green tea.
Chemical Composition Variation in Essential Oil and Their Correlation with Climate Factors in Chinese Prickly Ash Peels (Zanthoxylum armatum DC.) from Different Habitats
Authors: Qian Qianqian , Zhuo Zhihang , Peng Yaqin , Xu Danping
Published: March 2024

Essential oils are secondary metabolites in plants with a variety of biological activities. The flavor and quality of Zanthoxylum armatum DC. are mainly determined by the essential oil components in the Chinese prickly ash peels. In this study, the correlation between climate change in different regions and the content of essential oils of Z. armatum was investigated using gas chromatography–mass spectrometry (GC/MS) and multivariate statistical analysis. The Z1–24 refers to 24 batches of samples from different habitats. A total of 145 essential oils were detected in 24 batches of samples, with the highest number of terpene species and the highest content of alcohol. The relative odor activity (ROAV) values identified nine main flavor compounds affecting the odor of Z. armatum. Linalool, decanal, and d-limonene were the most critical main flavor compounds, giving Z. armatum a spicy, floral, oily, and fruity odor. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) classified Z5 into a separate group, Z2 and Z7 were clustered into one group, and the rest of the samples were classified into another group. Correlation analysis and path analysis showed that temperature and precipitation were the main climatic factors affecting essential oils. Comparisons can be made with other plants in the genus Zanthoxylum to analyze differences in essential oil type and content. This study contributes to the identification of Z. armatum quality, promotes the accumulation of theories on the effects of climatic factors on essential oils, and enriches the site selection and breeding of Z. armatum under similar climatic conditions.
The Removal of Arsenic and Its Inorganic Forms from Marine Algae—A Base for Inexpensive and Efficient Fertilizers
Authors: Ostrowski Jarosław , Drozd Alicja , Olchowski Rafał , Chałabis-Mazurek Agnieszka , Sienkiewicz Andrzej , Kierys Agnieszka , Morlo Kinga , Dobrowolski Ryszard
Published: March 2024

Newly synthesized cerium oxide was successfully obtained by the hard templating route. The optimal As(III) and As(V) adsorption onto the studied adsorbent was reached for the initial pH of 4.0 and a contact time of 10 h. The highest static adsorption capacities for As(III) and As(V) were 92 mg g−1 and 66 mg g−1, respectively. The pseudo-second-order model was well fitted to the As(III) and As(V) experimental kinetics data. The Langmuir model described the As(III) and As(V) adsorption isotherms on synthesized material. The adsorption mechanism of the studied ions onto the synthesized cerium oxide was complex and should be further investigated. The optimal solid–liquid ratio during the proposed aqueous extraction of inorganic As from the Fucus vesiculosus algae was 1:50. The optimal dosage of the synthesized cerium oxide (0.06 g L−1) was successfully applied for the first time for inorganic As removal from the aqueous algal extract.
Effects of Additional Protein Intake on Lean Body Mass in Patients Undergoing Multimodal Treatment for Morbid Obesity
Authors: Stein Wiebke , Sauer Helen Josephine , Oberänder Nadine , Weimann Arved , Fischer Martin
Published: March 2024

(1) Multimodal treatment is a standard treatment for patients with obesity. However, weight loss also leads to reductions in fat-free mass. The aim was to investigate whether additional protein intake contributes to better preservation of lean body mass (LBM). (2) A total of 267 obesity patients (age 45.8 years; BMI 47.3 kg/m2) were included in this analysis. For the first 12 weeks of the program, patients were given a formula-based diet of 800–1000 kcal per day. Patients were divided into a control group (CG) (n = 148) and a protein group (PG) (n = 119). The PG was characterized by an additional protein intake with the aim of consuming 1.5 g of protein per kilogram of normalized body weight, whereas the CG had a protein intake of 1 g/kg/d. Bioelectrical impedance analysis was performed at the beginning (t0) and after 12 weeks (t1) of the program. (3) There were no significant differences between the groups with respect to weight loss (p = 0.571). LBM was also significantly reduced in both groups, without significant differences between CG and PG. (4) Increased protein intake had no significant effect on body composition of morbidly obese patients during a 12-week formula-based diet and multimodal treatment.
Field Test of an Autonomous Observing System Prototype for Measuring Oceanographic Parameters from Ships
Authors: Santos Fernando P. , Rosa Teresa L. , Hinostroza Miguel A. , Vettor Roberto , Piecho-Santos A. Miguel , Guedes Soares C.
Published: March 2024

A prototype of an autonomous system for the retrieval of oceanographic, wave, and meteorologic data was installed and tested in May 2021 on a Portuguese research vessel navigating on the Atlantic Ocean. The system was designed to be installed in fishing vessels that could operate as a distributed network of ocean data collection. It consists of an automatic weather station, a ferrybox with a water pumping system, an inertial measurement unit, a GNSS unit, an onboard desktop computer, and a wave estimator algorithm for wave spectra estimation. Among several parameters collected by this system’s sensors are the air temperature, barometric pressure, humidity, wind speed and direction, sea water temperature, pH, dissolved oxygen, salinity, chlorophyll-a, roll, pitch, heave, true heading, and geolocation of the ship. This paper’s objectives are the following: (1) describe the autonomous prototype; and (2) present the data obtained during a full-scale trial; (3) discuss the results, advantages, and limitations of the system and future developments. Meteorologic measurements were validated by a second weather station onboard. The estimated wave parameters and wave spectra showed good agreement with forecasted data from the Copernicus database. The results are promising, and the system can be a cost-effective solution for voluntary observing ships.
Hedgehogs’ Parasitology: An Updated Review on Diagnostic Methods and Treatment
Authors: Alfaia Francisco , Jota Baptista Catarina , Sós-Koroknai Viktória , Hoitsy Márton , Sós Endre , Madeira de Carvalho Luís M.
Published: March 2024

The genus Erinaceus is commonly found in rescue centres across the European continent despite the reported decline in some countries. Parasite infections are frequently detected in rescued hedgehogs, leading to increased morbidity and mortality and consequently conditioning their recovery. Some of the most frequent parasites include respiratory nematodes, such as Crenosoma striatum and Capillaria spp., which may lead to important pneumonia. Moreover, some of these agents have zoonotic potential, such as Cryptosporidium spp., Sarcoptes spp., and several species of ticks and fleas, which may transmit different vector-borne pathogens. This review provides a brief guide on hedgehogs’ internal and external parasitology, as well as some suggestions for diagnosis and treatment that are relevant for wildlife veterinarians, biologists and other researchers.
Exploring the Therapeutic Potential of Ammodaucus leucotrichus Seed Extracts: A Multi-Faceted Analysis of Phytochemical Composition, Anti-Inflammatory Efficacy, Predictive Anti-Arthritic Properties, and Molecular Docking Insights
Authors: Djehiche Cheima , Benzidane Nadia , Djeghim Hanene , Tebboub Mehdi , Mokrani El Hassen , Mebrek Saad , Messaoudi Mohammed , Bensouici Chawki , Alsalme Ali , Cornu David , Bechelany Mikhael , Arrar Lekhmici , Barhoum Ahmed
Published: March 2024

Ammodaucus leucotrichus exhibits promising pharmacological activity, hinting at anti-inflammatory and anti-arthritic effects. This study investigated seed extracts from Ammodaucus leucotrichus using methanol and n-hexane, focusing on anti-inflammatory and anti-arthritic properties. The methanol extract outperformed the n-hexane extract and diclofenac, a reference anti-inflammatory drug, in trypsin inhibition (85% vs. 30% and 64.67% at 125 μg/mL). For trypsin inhibition, the IC50 values were 82.97 μg/mL (methanol), 202.70 μg/mL (n-hexane), and 97.04 μg/mL (diclofenac). Additionally, the n-hexane extract surpassed the methanol extract and diclofenac in BSA (bovine serum albumin) denaturation inhibition (90.4% vs. 22.0% and 51.4% at 62.5 μg/mL). The BSA denaturation IC50 values were 14.30 μg/mL (n-hexane), 5408 μg/mL (methanol), and 42.30 μg/mL (diclofenac). Gas chromatography–mass spectrometry (GC–MS) revealed 59 and 58 secondary metabolites in the methanol and n-hexane extracts, respectively. The higher therapeutic activity of the methanol extract was attributed to hydroxyacetic acid hydrazide, absent in the n-hexane extract. In silico docking studies identified 28 compounds with negative binding energies, indicating potential trypsin inhibition. The 2-hydroxyacetohydrazide displayed superior inhibitory effects compared to diclofenac. Further mechanistic studies are crucial to validate 2-hydroxyacetohydrazide as a potential drug candidate for rheumatoid arthritis treatment.
Cytotoxic and Antiproliferative Activity of LASSBio-2208 and the Attempts to Determine Its Drug Metabolism and Pharmacokinetics In Vitro Profile
Authors: Pillpe-Meza Raysa Magali , Gouveia Wesley Leandro , Barbosa Gisele , Fraga Carlos A. M. , Barreiro Eliezer J. , Lima Lidia Moreira
Published: March 2024

Inappropriate expression of histone deacetylase (HDAC-6) and deregulation of the phosphatidylinositol 3-kinase (PI3K) signalling pathway are common aberrations observed in cancers. LASSBio-2208, has been previously described as a dual inhibitor in the nanomolar range of HDAC-6 and PI3Kα and is three times more potent in inhibiting HDAC-6. In this paper we described the cytotoxic and antiproliferative potency of LASSBio-2208 on different tumour cell lines, its possible synergism effect in association with PI3K and HDAC-6 inhibitors, and its drug metabolism and pharmacokinetics (DMPK) in vitro profile. Our studies have demonstrated that LASSBio-2208 has moderate cytotoxic potency on breast cancer cell line MCF-7 (IC50 = 23 µM), human leukaemia cell line CCRF-CEM (IC50 = 8.54 µM) and T lymphoblast cell line MOLT-4 (IC50 = 7.15 µM), with no cytotoxic effect on human peripheral blood mononuclear cells (hPBMC). In addition, it has a good antiproliferative effect on MCF-7 cells (IC50 = 5.44 µM), low absorption by parallel artificial membrane permeability—gastrointestinal tract (PAMPA—GIT) and low permeation by parallel artificial membrane permeability—blood–brain barrier (BBB) (PAMPA—BBB), exhibiting high metabolic stability in rat plasma. Moreover, LASSBio-2208 exhibited synergism when combined with getadolisib and tubastatin A, using the concentrations corresponding to their CC50 values on MOLT-4 and CCRF-CEM cells.
A Best-Path Approach to the Design of a Hybrid Space–Ground Quantum Network with Dynamic Constraints
Authors: Bakker David L. , Jong Yannick , Dirks Bob P. F. , Amaral Gustavo C.
Published: March 2024

The design and operation of quantum networks are both decisive in the current push towards a global quantum internet. Although space-enabled quantum connectivity has already been identified as a beneficial candidate for long-range quantum channels for over two decades, the architecture of a hybrid space–ground network is still a work in progress. Here, we propose an analysis of such a network based on a best-path approach, where either fiber- or satellite-based elementary links can be concatenated to form a repeater chain. The network consisting of quantum information processing nodes, equipped with both ground and space connections, is mapped into a graph structure, where edge weights represent the achievable secret key rates, chosen as the figure of merit for the network analysis. A weight minimization algorithm allows for identifying the best path dynamically, i.e., as the weather conditions, stray light radiance, and satellite orbital position change. From the results, we conclude that satellite links will play a significant role in the future large-scale quantum internet, in particular when node distances exceed 500 km, and both a constellation of satellites—spanning 20 or more satellites—and significant advances in filtering technology are required to achieve continuous coverage.
Axion Electrodynamics and the Casimir Effect
Authors: Brevik Iver , Pal Subhojit , Li Yang , Gholamhosseinian Ayda , Boström Mathias
Published: March 2024

We present a concise review of selected parts of axion electrodynamics and their application to Casimir physics. We present the general formalism including the boundary conditions at a dielectric surface, derive the dispersion relation in the case where the axion parameter has a constant spatial derivative in the direction normal to the conducting plates, and calculate the Casimir energy for the simple case of scalar electrodynamics using dimensional regularization.
Correction: Gorban et al. The Asymmetric Dynamical Casimir Effect. Physics 2023, 5, 398–422
Authors: Gorban Matthew J. , Julius William D. , Brown Patrick M. , Matulevich Jacob A. , Cleaver Gerald B.
Published: March 2024

There was an error in the original paper [1], which occurred in the calculation of the DCE spectrum from the time-dependant perturbations on λ(t) [...]
Integrated Transcriptome and Proteome Analysis Reveals That Cell Wall Activity Affects Phelipanche aegyptiaca Parasitism
Authors: Chen Meixiu , Zhang Lu , Yao Zhaoqun , Cao Xiaolei , Ma Qianqian , Chen Siyu , Zhang Xuekun , Zhao Sifeng
Published: March 2024

Phelipanche aegyptiaca can infect many crops, causing large agricultural production losses. It is important to study the parasitism mechanism of P. aegyptiaca to control its harm. In this experiment, the P. aegyptiaca HY13M and TE9M from Tacheng Prefecture and Hami City in Xinjiang, respectively, were used to analyze the parasitical mechanism of P. aegyptiaca by means of transcriptome and proteome analyses. The parasitic capacity of TE9M was significantly stronger than that of HY13M in Citrullus lanatus. The results showed that the DEGs and DEPs were prominently enriched in the cell wall metabolism pathways, including “cell wall organization or biogenesis”, “cell wall organization”, and “cell wall”. Moreover, the functions of the pectinesterase enzyme gene (TR138070_c0_g), which is involved in the cell wall metabolism of P. aegyptiaca in its parasitism, were studied by means HIGS. The number and weight of P. aegyptiaca were significantly reduced when TR138070_c0_g1, which encodes a cell-wall-degrading protease, was silenced, indicating that it positively regulates P. aegyptiaca parasitism. Thus, these results suggest that the cell wall metabolism pathway is involved in P. aegyptiaca differentiation of the parasitic ability and that the TR138070_c0_g1 gene plays an important role in P. aegyptiaca’s parasitism.
Performance Evaluation of a Double-Helical-Type-Channel Reinforced Heat Sink Based on Energy and Entropy-Generation Analysis
Authors: He Liyi , Hu Xue , Zhang Lixin , Chen Feng , Zhang Xinwang
Published: March 2024

Heat-transfer enhancement and entropy generation were investigated for a double-helical-type-channel heat sink with different rib structures set on the upper wall. Based on available experimental data, a series of simulations with various turbulence models were conducted to find the best numerical model. Five different rib structures were considered, which were diamond (FC-DR), rectangular (FC-RR), drop-shaped (FC-DSR), elliptic (FC-ER) and frustum (FC-FR). The research was carried out under turbulent flow circumstances with a Reynolds number range of 10,000–60,000 and a constant heat-flow density. The numerical results show that the thermal performance of the flow channel set with a rib structure is better than that of the smooth channel. FC-ER offers the lowest average temperature and the highest temperature uniformity, with a Nusselt number improvement percentage ranging from 15.80% to 30.77%. Overall, FC-ER shows the most excellent performance evaluation criteria and lowest augmentation entropy-generation number compared with the other reinforced flow channels.
Dynamic Mechanical and Biological Characterization of New 3D-Printed Polymeric Dental Materials: A Preliminary Study
Authors: Valenti Chiara , Pagano Stefano , Xhimitiku Iva , Kutrolli Mikaela , Masciotti Francesca , Zara Tommaso , Truffarelli Tiberio , Tribbiani Giulio , Nanussi Alessandro , Marinucci Lorella
Published: March 2024

The literature shows evidence of the mechanical investigation of numerous polymeric dental biomaterials using a static approach. A more representative mechanical analysis of such materials must take into account the dynamic masticatory load of the oral cavity. The aim of this work is to study the dynamic mechanical proprieties and provide an in vitro characterization of 11 3D-printed new dental biomaterials to understand their clinical applications under physiological conditions. The analysis included Dynamical Mechanical Analysis (DMA) and an MTT cytotoxicity assay. The mechanical results at low frequencies (1–11 Hz) show high uncertainty, less fragility, and less strength. The biological results show a significant reduction in cell viability (p < 0.01) at both the 3 and 24 h timepoints, with a degree of recovery observed at 24 h. To assess the clinical potential of dental biomaterials, it is necessary to determine whether there are good dynamic mechanical properties and reduced adverse biological effects on oral cells. This may allow for the facile fabrication via 3D printing of prosthetic devices that can support masticatory loads over long periods of time. Further investigations of the presented polymeric materials are needed, exploring biological assessments for longer than 24 h.
Disparities in Substance Co-Use among Sexual Minority and Heterosexual Adult Hookah Smokers: Findings from Wave 4 (2016–2018) and Wave 5 (2018–2019) of the Population Assessment of Tobacco and Health Study
Authors: Sakthi Chandni , Adolfo Amanda , Warda Umme Shefa , Khaled Asmaa , Brecht Mary-Lynn , Rezk-Hanna Mary
Published: March 2024

Heavily advertised as a harmless tobacco alternative, hookah (i.e., waterpipe)-flavored tobacco smoking has contributed to the wider epidemic of smoking, especially amongst marginalized sexual minority (SM) populations. Evidence regarding the concurrent use of substances and other drugs, among SM current hookah smokers, is scarce. We utilized nationally representative data from the Population Assessment of Tobacco and Health (PATH) Study (2016–2019) to examine patterns of the concurrent use of substances (i.e., marijuana, painkillers, sedatives, tranquilizers, cocaine, stimulants (specifically methamphetamines), and others), in SM adult hookah smokers and their heterosexual counterparts. Current hookah smoking is higher among SM adults (Wave 4: 4.22% [95% CI = 2.94–5.94] and Wave 5: 2.65% [95% CI = 1.81–3.48]) than heterosexuals (Wave 4: 1.31% [95% CI = 1.13–1.50] and Wave 5: 1.07% [95% CI = 0.89–1.25]). Among current SM hookah users, the co-use of substances, including alcohol, marijuana, and cocaine, is comparable to heterosexuals (p = ns). Adjusting for gender alone and all covariates, including age, sex, race/ethnicity, education, income, and education, no differences in concurrent substance use were observed between SM and heterosexual hookah users. While the co-use of substances is comparable between SM and heterosexual hookah smoker adults, the prevalence of current hookah use more than doubled among SM individuals than heterosexual individuals during 2018–2019. Our findings highlight the critical value of prevention efforts directed to increase education and awareness about hookah smoking use and known health effects, particularly tailored towards sexual minorities.
New Choking Epidemic Trends in Psychoactive Drugs: The Zombifying Combination of Fentanyl and Xylazine Cause Overdoses and Little Hope in Rehabilitation
Authors: Dinis-Oliveira Ricardo Jorge
Published: March 2024

The world of drugs of abuse is a complex clinical and forensic topic since their misuse can lead to devastating consequences [...]
Historical Analysis of the Effects of Drought on Rice and Maize Yields in Southeast Asia
Authors: Amnuaylojaroen Teerachai , Chanvichit Pavinee
Published: March 2024

This study performs an empirical orthogonal function (EOF) analysis to study the relationship between rice and maize productivities and the different time scales of the Standardized Precipitation Evapotranspiration Index (SPEI), including 1-month, 6-month, and 12-month time scales in Southeast Asia during the years 1970–2019. For the 1-month time scale, the averaged SPEI values are in the range of −1.0 to 1.0, indicating a moderate degree of dryness and humidity. Both 6-month and 12-month time scales suggest that many countries in Southeast Asia are experiencing mostly wet conditions, with SPEI values reaching up to 1.5. The relationship analysis by using EOF was indicated by the first and second principal components (PC1 and PC2) suggesting that drought events exhibit a positive orientation to crop productivity, especially maize in Southeast Asia. The pattern of climate oscillations, such as the El Niño-Southern Oscillation (ENSO), is likely related to crop productivity in Southeast Asia. The findings emphasize the importance of considering temporal climatic patterns in agricultural decision-making, with implications for enhancing regional climate resilience and ensuring sustainable food security in the face of global climate change.
Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation
Authors: Athayde Alexandre , Moutinho Alexandra , Azinheira José Raúl
Published: March 2024

Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the problem of stabilizing a tail-sitter when hovering. For this purpose, the first controller is an existing strategy for tail-sitter control obtained from the literature, the second is an application of Nonlinear Dynamic Inversion (NDI), and the last one is its incremental version, INDI. These controllers were implemented and tuned in a simulation in order to stabilize a model of the tail-sitter, complemented by estimation methods that allow the feedback of the necessary variables. These estimators and controllers were then implemented in a microcontroller and validated in a Hardware-in-the-Loop (HITL) scenario with simple maneuvers in vertical flight. Lastly, the developed control solutions were used to stabilize the aircraft in experimental flight while being monitored by a motion capture system. The experimental results allow the validation of the model of the X-Vert and provide a comparison of the performance of the different control solutions, where the INDI presents itself as a robust control strategy with accurate tracking capabilities and less actuator demand.
Finding Navigable Paths through Tidal Flats with Synthetic Aperture Radar
Authors: Clark Ruaridh A. , McGrath Ciara N. , Werkmeister Astrid A. , Lowe Christopher J. , Gibbons Gwilym , Macdonald Malcolm
Published: March 2024

Tidal flats are some of the most dynamic coastal environments in the world, where traditional coastal mapping and monitoring provide insufficient temporal resolution to reliably map channels and sand flats. Satellite-based Synthetic Aperture Radar (SAR) enables regular cloud-penetrating detection of water flowing through channels within the tidal flats, referred to as tidal channels. This paper presents a method for detecting a path through tidal channels, using satellite imagery, that supports our understanding and safe exploitation of this valuable coastal environment. This approach is the first proposed to identify navigable paths in all conditions, with SAR images susceptible to variation due to weather and tidal conditions. Tidal channels are known to vary in SAR presentation, and we find that tidal flat presentation is also influenced by conditions. The most influential factor is the wind, with high winds causing an inversion in how both tidal flats and tidal channels present in SAR images. The presented method for the automatic detection of tidal channels accounts for this variability by using previous channel paths as a reference to reliably correct imagery and detect the latest path. The final algorithm produces paths with minor errors in 17.6% of images; the error rate increases to 71.7%, with an almost tenfold increase in errors, when the SAR image and paths are not adjusted to account for conditions. This capability has been used to support the Nith Inshore Rescue in attending call-outs from their base in Glencaple, UK, while the insights from monitoring tidal channels for a year demonstrate how periods of high river flow preceded major changes in the channel path.
Robust Two-Dimensional InSAR Phase Unwrapping via FPA and GAU Dual Attention in ResDANet
Authors: Chen Xiaomao , Zhang Shanshan , Qin Xiaofeng , Lin Jinfeng
Published: March 2024

Two-dimensional phase unwrapping (2-D PU) is vital for reconstructing Earth’s surface topography and displacement from interferometric synthetic aperture radar (InSAR) data. Conventional algorithms rely on the postulate, but this assumption is often insufficient due to abrupt topographic changes and severe noise. To address this challenge, our research proposes a novel approach utilizing deep convolutional neural networks inspired by the U-Net architecture to estimate phase gradient information. Our approach involves downsampling the input data to extract crucial features, followed by upsampling to restore spatial resolution. We incorporate two attention mechanisms—feature pyramid attention (FPA) and global attention upsample (GAU)—and a residual structure in the network’s structure. Thus, we construct ResDANet (residual and dual attention net). We rigorously train ResDANet utilizing simulated datasets and employ an L1-norm objective function to minimize the disparity between unwrapped phase gradients and those calculated by ResDANet, yielding the final 2-D PU results. The network is rigorously trained using two distinct training strategies and encompassing three types of simulated datasets. ResDANet exhibits excellent robust performance and efficiency on simulated data and real data, such as China’s Three Gorges and an Italian volcano.
Investigating a Possible Correlation between NOAA-Satellite-Detected Electron Precipitations and South Pacific Tectonic Events
Authors: Fidani Cristiano , D’Arcangelo Serena , De Santis Angelo , Perrone Loredana , Soldani Maurizio
Published: March 2024

On 4 March 2021, a devastating M8.1 earthquake struck the Kermadec Islands of New Zealand. Given the tremendous energy released during the event, we sought to investigate the event’s potential impact on the ionosphere and the inner Van Allen Belt using data from the high-energy electron detectors on board the NOAA-18 satellite. The survey was also extended to the strongest shallow M6.5+ earthquakes occurring between 150° and 190° in longitude, and between −5° and −35° in latitude over the previous ten years. In nearly all cases, evident electron fluxes entering the loss cone were observed. To explore the possibility of a connection between ionospheric signals and tectonic events in this intensely active region, we analyzed electron losses from the inner Van Allen Belt, taking into account latitude, longitude, day/night times, and proximity to the South Atlantic Anomaly. Compared to previous studies, here only the most significant loss phenomena persistent in the ionosphere were considered. Particular interest was reserved for the intense electron loss events that had a duration spanning from a few to several minutes and occurred several hours before and after strong seismic events. Thereafter, time series of electron counting rates and strong Southern Pacific earthquakes were transformed into binary series, and the series multiplication was investigated. The results suggest four peaks of association, including a first couple between electron perturbations detected for ascending semi-orbits and seismic events and a second one between electron perturbations detected in the southern ionosphere and seismic events. They both anticipated the occurrence of earthquakes, occurring around 4 h before them. Other couples were observed between electron perturbations detected for descending semi-orbits and seismic events and between electron perturbations detected in the northern ionosphere and seismic events. They both occurred around 3 h after the occurrence of earthquakes. The case of perturbations anticipating seismic events has the intriguing properties of sustaining the hypothesis that a physical interaction occurred around 6 h before seismic events as in the West Pacific case. A physical model of electrons detected far several thousands of km from the earthquake epicenters was also presented. However, a simulation of random seismic events suggested that the null hypothesis cannot be fully rejected for these associations, prompting many more analyses and case studies.
Editorial of Special Issue “Remote Sensing Observations to Improve Knowledge of Lithosphere–Atmosphere–Ionosphere Coupling during the Preparatory Phase of Earthquakes”
Authors: Marchetti Dedalo , Yuan Yunbin , Zhu Kaiguang
Published: March 2024

We launched this Special Issue with the aim of collecting papers that use satellite data and new methodologies to understand the preparatory phase of medium–large earthquakes in the world [...]
Automated Seizure Detection Based on State-Space Model Identification
Authors: Wang Zhuo , Sperling Michael R. , Wyeth Dale , Guez Allon
Published: March 2024

In this study, we developed a machine learning model for automated seizure detection using system identification techniques on EEG recordings. System identification builds mathematical models from a time series signal and uses a small number of parameters to represent the entirety of time domain signal epochs. Such parameters were used as features for the classifiers in our study. We analyzed 69 seizure and 55 non-seizure recordings and an additional 10 continuous recordings from Thomas Jefferson University Hospital, alongside a larger dataset from the CHB-MIT database. By dividing EEGs into epochs (1 s, 2 s, 5 s, and 10 s) and employing fifth-order state-space dynamic systems for feature extraction, we tested various classifiers, with the decision tree and 1 s epochs achieving the highest performance: 96.0% accuracy, 92.7% sensitivity, and 97.6% specificity based on the Jefferson dataset. Moreover, as the epoch length increased, the accuracy dropped to 94.9%, with a decrease in sensitivity to 91.5% and specificity to 96.7%. Accuracy for the CHB-MIT dataset was 94.1%, with 87.6% sensitivity and 97.5% specificity. The subject-specific cases showed improved results, with an average of 98.3% accuracy, 97.4% sensitivity, and 98.4% specificity. The average false detection rate per hour was 0.5 ± 0.28 in the 10 continuous EEG recordings. This study suggests that using a system identification technique, specifically, state-space modeling, combined with machine learning classifiers, such as decision trees, is an effective and efficient approach to automated seizure detection.
Investigation of Using Hyperspectral Vegetation Indices to Assess Brassica Downy Mildew
Authors: Liu Bo , Fernandez Marco Antonio , Liu Taryn Michelle , Ding Shunping
Published: March 2024

Downy mildew caused by Hyaloperonospora brassicae is a severe disease in Brassica oleracea that significantly reduces crop yield and marketability. This study aims to evaluate different vegetation indices to assess different downy mildew infection levels in the Brassica variety Mildis using hyperspectral data. Artificial inoculation using H. brassicae sporangia suspension was conducted to induce different levels of downy mildew disease. Spectral measurements, spanning 350 nm to 1050 nm, were conducted on the leaves using an environmentally controlled setup, and the reflectance data were acquired and processed. The Successive Projections Algorithm (SPA) and signal sensitivity calculation were used to extract the most informative wavelengths that could be used to develop downy mildew indices (DMI). A total of 37 existing vegetation indices and three proposed DMIs were evaluated to indicate downy mildew (DM) infection levels. The results showed that the classification using a support vector machine achieved accuracies of 71.3%, 80.7%, and 85.3% for distinguishing healthy leaves from DM1 (early infection), DM2 (progressed infection), and DM3 (severe infection) leaves using the proposed downy mildew index. The proposed new downy mildew index potentially enables the development of an automated DM monitoring system and resistance profiling in Brassica breeding lines.
Leveraging the Sensitivity of Plants with Deep Learning to Recognize Human Emotions
Authors: Kruse Jakob Adrian , Ciechanowski Leon , Dupuis Ambre , Vazquez Ignacio , Gloor Peter A.
Published: March 2024

Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensive, intrusive, and regulated, unlike plants, which have been shown to be sensitive to human steps and sounds. A methodology to use plants as human emotion detectors is proposed. Electrical signals from plants were tracked and labeled based on video data. The labeled data were then used for classification., and the MLP, biLSTM, MFCC-CNN, MFCC-ResNet, Random Forest, 1-Dimensional CNN, and biLSTM (without windowing) models were set using a grid search algorithm with cross-validation. Finally, the best-parameterized models were trained and used on the test set for classification. The performance of this methodology was measured via a case study with 54 participants who were watching an emotionally charged video; as ground truth, their facial emotions were simultaneously measured using facial emotion analysis. The Random Forest model shows the best performance, particularly in recognizing high-arousal emotions, achieving an overall weighted accuracy of 55.2% and demonstrating high weighted recall in emotions such as fear (61.0%) and happiness (60.4%). The MFCC-ResNet model offers decently balanced results, with AccuracyMFCC−ResNet=0.318 and RecallMFCC−ResNet=0.324. Regarding the MFCC-ResNet model, fear and anger were recognized with 75% and 50% recall, respectively. Thus, using plants as an emotion recognition tool seems worth investigating, addressing both cost and privacy concerns.
Ultrasensitive Silicon Photonic Refractive Index Sensor Based on Hybrid Double Slot Subwavelength Grating Microring Resonator
Authors: Lu Kaiwei , Huang Beiju , Lv Xiaoqing , Zhang Zan , Ma Zhengtai
Published: March 2024

Silicon photonic-based refractive index sensors are of great value in the detection of gases, biological and chemical substances. Among them, microring resonators are the most promising due to their compact size and narrow Lorentzian-shaped spectrum. The electric field in a subwavelength grating waveguide (SWG) is essentially confined in the low-refractive index dielectric, favoring enhanced analyte-photon interactions, which represents higher sensitivity. However, it is very challenging to further significantly improve the sensitivity of SWG ring resonator refractive index sensors. Here, a hybrid waveguide blocks double slot subwavelength grating microring resonator (HDSSWG-MRR) refractive index sensor operating in a water refractive index environment is proposed. By designing a new waveguide structure, a sensitivity of up to 1005 nm/RIU has been achieved, which is 182 nm/RIU higher than the currently highest sensitivity silicon photonic micro ring refractive index sensor. Meanwhile, utilizing a unique waveguide structure, a Q of 22,429 was achieved and a low limit of detection of 6.86 × 10−5 RIU was calculated.
An Adaptive Radon-Transform-Based Marker Detection and Localization Method for Displacement Measurements Using Unmanned Aerial Vehicles
Authors: Liu Jianlin , Dai Wujiao , Zhang Yunsheng , Xing Lei , Pan Deyong
Published: March 2024

UAVs have been widely used in deformation monitoring because of their high availability and flexibility. However, the quality of UAV images is affected by changing attitude and surveying environments, resulting in a low monitoring accuracy. Cross-shaped markers are used to improve the accuracy of UAV monitoring due to their distinct center contrast and absence of eccentricity. However, existing methods cannot rapidly and precisely detect these markers in UAV images. To address these problems, this paper proposes an adaptive Radon-transform-based marker detection and localization method for UAV displacement measurements, focusing on two critical detection parameters, namely, the radius of marker information acquisition and the edge width of the cross-shaped scoring template. The experimental results show that the marker detection rate is 97.2% under different combinations of flight altitudes, radius ratios of marker information acquisition, and marker sizes. Furthermore, the root mean square error of detection and localization is 0.57 pixels, significantly surpassing the performance and accuracy of other methods. We also derive the critical detection radius and appropriate parameter combinations for different heights to further improve the practicality of the method.
A Novel Three-Point Localization Method for Bladder Volume Estimation
Authors: Yuan Junru , Shen Mingke , Zhang Tao , Ou-Yang Jun , Yang Xiaofei , Zhu Benpeng
Published: March 2024

The measurement of bladder volume is crucial for the diagnosis and treatment of urinary system diseases. Ultrasound imaging, with its non-invasive, radiation-free, and repeatable scanning capabilities, has become the preferred method for measuring residual urine volume. Nevertheless, it still faces some challenges, including complex imaging methods leading to longer measurement times and lower spatial resolution. Here, we propose a novel three-point localization method that does not require ultrasound imaging to calculate bladder volume. A corresponding triple-element ultrasound probe has been designed based on this method, enabling the ultrasound probe to transmit and receive ultrasound waves in three directions. Furthermore, we utilize the Hilbert Transform algorithm to extract the envelope of the ultrasound signal to enhance the efficiency of bladder volume measurements. The experiment indicates that bladder volume estimation can be completed within 5 s, with a relative error rate of less than 15%. These results demonstrate that this novel three-point localization method offers an effective approach for bladder volume measurement in patients with urological conditions.
Reduced Complexity Sequential Digital Predistortion Technique for 5G Applications
Authors: Abdelnaby Moustafa , Alnajjar Reem , Bensmida Souheil , Hammi Oualid
Published: March 2024

Wireless communication infrastructure is a key enabling technology for smart cities. This paper investigates a novel technique to enhance the performance of 5G base stations by addressing the compensation of nonlinear distortions caused by radiofrequency power amplifiers. For this purpose, a sequential digital predistortion approach that uses twin nonlinear two-box structure along with reduced sampling rates in the feedback path is proposed to implement a linearization system. Such a system is shown to have a correction bandwidth that exceeds the bandwidth of the feedback path. This is achieved by synthesizing the predistortion function in two successive characterization iterations. Both characterizations use the same hardware, which has a reduced sampling rate in the feedback path. Hence, the proposed predistorter scheme does not require any additional hardware compared to standard schemes. Moreover, coarse delay alignment is performed while identifying the memory polynomial function in order to further reduce the computational complexity of the proposed system. Experimental results using an inverse Class-F power amplifier demonstrate the ability of the proposed predistorter to achieve a correction bandwidth of 100 MHz with a feedback sampling rate as low as 25 MSa/s.
A Novel Statistical Framework for Optimal Sizing of Grid-Connected Photovoltaic–Battery Systems for Peak Demand Reduction to Flatten Daily Load Profiles
Authors: Nematirad Reza , Pahwa Anil , Natarajan Balasubramaniam
Published: March 2024

Integrating photovoltaic (PV) systems plays a pivotal role in the global shift toward renewable energy, offering significant environmental benefits. However, the PV installation should provide financial benefits for the utilities. Considering that the utility companies often incur costs for both energy and peak demand, PV installations should aim to reduce both energy and peak demand charges. Although PV systems can reduce energy needs during the day, their effectiveness in reducing peak demand, particularly in the early morning and late evening, is limited, as PV generation is zero or negligible at those times. To address this limitation, battery storage systems are utilized for storing energy during off-peak hours and releasing it during peak times. However, finding the optimal size of PV and the accompanying battery remains a challenge. While valuable optimization models have been developed to determine the optimal size of PV–battery systems, a certain gap remains where peak demand reduction has not been sufficiently addressed in the optimization process. Recognizing this gap, this study proposes a novel statistical model to optimize PV–battery system size for peak demand reduction. The model aims to flatten 95% of daily peak demands up to a certain demand threshold, ensuring consistent energy supply and financial benefit for utility companies. A straightforward and effective search methodology is employed to determine the optimal system sizes. Additionally, the model’s effectiveness is rigorously tested through a modified Monte Carlo simulation coupled with time series clustering to generate various scenarios to assess performance under different conditions. The results indicate that the optimal PV–battery system successfully flattens 95% of daily peak demand with a selected threshold of 2000 kW, yielding a financial benefit of USD 812,648 over 20 years.