bluuebunny/crossref_metadata_2025 huggingface dataset:
Deciphering the Interplay between Genetic Risk Scores and Lifestyle Factors on Individual Obesity Predisposition
Authors: Chermon Danyel , Birk Ruth
Published: April 2024

Obesity’s variability is significantly influenced by the interplay between genetic and environmental factors. We aimed to integrate the combined impact of genetic risk score (GRSBMI) with physical activity (PA), sugar-sweetened beverages (SSB), wine intake, and eating habits score (EHS) on obesity predisposition risk. Adults’ (n = 5824) data were analyzed for common obesity-related single nucleotide polymorphisms and lifestyle habits. The weighted GRSBMI was constructed and categorized into quartiles (Qs), and the adjusted multivariate logistic regression models examined the association of GRSBMI with obesity (BMI ≥ 30) and lifestyle factors. GRSBMI was significantly associated with obesity risk. Each GRSBMI unit was associated with an increase of 3.06 BMI units (p ≤ 0.0001). PA markedly reduced obesity risk across GRSBMI Qs. Inactive participants’ (≥90 min/week) mean BMI was higher in GRSBMI Q3–Q4 compared to Q1 (p = 0.003 and p < 0.001, respectively). Scoring EHS ≥ median, SSBs (≥1 cup/day), and non-wine drinking were associated with higher BMI within all GRSBMI Qs compared to EHS < median, non-SSBs, and non-wine drinkers. Mean BMI was higher in GRSBMI Q4 compared to other quartiles (p < 0.0001) in non-wine drinkers and compared to Q1 for SSB’s consumers (p = 0.07). A higher GRSBMI augmented the impact of lifestyle factors on obesity. The interplay between GRSBMI and modifiable lifestyle factors provides a tailored personalized prevention and treatment for obesity management.
Oleocanthal Protects C2C12 Myotubes against the Pro-Catabolic and Anti-Myogenic Action of Stimuli Able to Induce Muscle Wasting In Vivo
Authors: De Stefanis Daniela , Balestrini Andrea , Costelli Paola
Published: April 2024

Oleocanthal (OC) is a monophenol of extra-virgin olive oil (EVOO) endowed with antibiotic, cardioprotective and anticancer effects, among others, mainly in view of its antioxidant and anti-inflammatory properties. OC has been largely investigated in terms of its anticancer activity, in Alzheimer disease and in collagen-induced arthritis; however, the possibility that it can also affect muscle biology has been totally overlooked so far. This study is the first to describe that OC modulates alterations induced in C2C12 myotubes by stimuli known to induce muscle wasting in vivo, namely TNF-α, or in the medium conditioned by the C26 cachexia-inducing tumor (CM-C26). C2C12 myotubes were exposed to CM-C26 or TNF-α in the presence or absence of OC for 24 and 48 h and analyzed by immunofluorescence and Western blotting. In combination with TNF-α or CM-C26, OC was revealed to be able to restore both the myotube’s original size and morphology and normal levels of both atrogin-1 and MuRF1. OC seems unable to impinge on the autophagic–lysosomal proteolytic system or protein synthesis. Modulations towards normal levels of the expression of molecules involved in myogenesis, such as Pax7, myogenin and MyHC, were also observed in the myotube cultures exposed to OC and TNF-α or CM-C26. In conclusion, the data presented here show that OC exerts a protective action in C2C12 myotubes exposed to TNF-α or CM-C26, with mechanisms likely involving the downregulation of ubiquitin–proteasome-dependent proteolysis and the partial relief of myogenic differentiation impairment.
Correction: Shakir et al. Exorbitant Drug Loading of Metformin and Sitagliptin in Mucoadhesive Buccal Tablet: In Vitro and In Vivo Characterization in Healthy Volunteers. Pharmaceuticals 2022, 15, 686
Authors: Shakir Rouheena , Hanif Sana , Salawi Ahmad , Arshad Rabia , Sarfraz Rai Muhammad , Irfan Muhammad , Raza Syed Atif , Barkat Kashif , Sabei Fahad Y. , Almoshari Yosif , Alshamrani Meshal , Syed Muhammad Ali
Published: April 2024

In the original publication, a mistake was observed in Figure 5 as published [...]
Therapeutic Effects of Essential Oils and Their Bioactive Compounds on Prostate Cancer Treatment
Authors: Pimentel Leticia Santos , Bastos Luciana Machado , Goulart Luiz Ricardo , Ribeiro Lígia Nunes de Morais
Published: April 2024

Since prostate cancer (PCa) relies on limited therapies, more effective alternatives are required. Essential oils (EOs) and their bioactive compounds are natural products that have many properties including anticancer activity. This review covers studies published between 2000 and 2023 and discusses the anti-prostate cancer mechanisms of the EOs from several plant species and their main bioactive compounds. It also provides a critical perspective regarding the challenges to be overcome until they reach the market. EOs from chamomile, cinnamon, Citrus species, turmeric, Cymbopogon species, ginger, lavender, Mentha species, rosemary, Salvia species, thyme and other species have been tested in different PCa cell lines and have shown excellent results, including the inhibition of cell growth and migration, the induction of apoptosis, modulation in the expression of apoptotic and anti-apoptotic genes and the suppression of angiogenesis. The most challenging aspects of EOs, which limit their clinical uses, are their highly lipophilic nature, physicochemical instability, photosensitivity, high volatility and composition variability. The processing of EO-based products in the pharmaceutical field may be an interesting alternative to circumvent EOs’ limitations, resulting in several benefits in their further clinical use. Identifying their bioactive compounds, therapeutic effects and chemical structures could open new perspectives for innovative developments in the field. Moreover, this could be helpful in obtaining versatile chemical synthesis routes and/or biotechnological drug production strategies, providing an accurate, safe and sustainable source of these bioactive compounds, while looking at their use as gold-standard therapy in the close future.
QbD Approach-Based Preparation and Optimization of Hydrophobic Ion-Pairing Complex of Lysozyme with Sodium Dodecyl Sulphate to Enhance Stability in Lipid-Based Carriers
Authors: Hassan Alharith A. A. , Sovány Tamás , Pamlényi Krisztián , Deák Martin , Hornok Viktória , Csapó Edit , Regdon Géza , Csóka Ildikó , Kristó Katalin
Published: April 2024

Hydrophobic ion pairing (HIP) complexation was found to be an efficient approach in modulating the release and enhancing the stability and encapsulation of hydrophilic macromolecules such as proteins in hydrophobic nano/microcarriers. The present work strives to develop and optimize the preparation of the HIP complex of the antimicrobial enzyme lysozyme (LYZ) with the ion-pairing agent (IPA) sodium dodecyl sulphate (SDS) relying on the quality-by-design (QbD) approach. The quality target product profile (QTPP) includes the achievement of maximal lipophilicity in a reversible manner to enable the maintenance of biological activity. The related critical quality attributes (CQAs) were defined as complexation efficacy, complex stability, enzyme recovery and activity. Three risk assessment (RA) tools were used to identify and rank the critical process parameters (CPPs) and critical material attributes (CMAs). From this assessment, the pH of the medium, LYZ:SDS molar ratio and drying conditions were determined as high-risk factors that need to be investigated. To the best of our knowledge, for the first time, electrostatic titration was used as a smart approach to determine the optimum molar ratio at different pH values. Based on the predefined CQAs, pH 8 with an LYZ/SDS molar ratio of 1:8 was found to be the optimal condition for complexation efficiency and recovery (%) of a biologically active enzyme. A cost-effective drying process based on a ventilated oven was developed, which resulted in complex qualities comparable to those obtained by the commonly used freeze-drying method. In a nutshell, the optimum conditions for the preparation of the LYZ/SDS HIP complex were efficiently facilitated by the rational application of QbD principles and the utilization of efficient electrostatic titration and ventilated oven-drying methods.
Stances and Skills to in-Habit the World: Pragmatic Agnosticisms and Religion
Authors: Zackariasson Ulf
Published: April 2024

This paper explores two routes along which a pragmatic philosophical approach can contribute to reflections on agnosticism. The first of these approaches is developed in dialogue with William James, and it is oriented towards the needs and obligations of individuals and the extent to which agnosticism affects our abilities to lead strenuous lives. The second is developed in dialogue with Richard Rorty. It is oriented towards how agnosticisms can be adopted within particular vocabularies vis-a-vis other vocabularies as a pragmatically helpful strategy or skill. I discuss the extent to which these can contribute to philosophical reflection on agnosticism and propose that they show that the agnosticism debate would benefit from a broadened focus where epistemic and pragmatic considerations are better integrated than presently. This would enable us to discuss different types of agnosticism that come to the fore in various contexts and whether they prevent us or allow us to better handle concrete problems in our interactions with the world.
Channels of Evolution: Unveiling Evolutionary Patterns in Diatom Ca2+ Signalling
Authors: Murphy Eleanor A. , Kleiner Friedrich H. , Helliwell Katherine E. , Wheeler Glen L.
Published: April 2024

Diatoms are important primary producers in marine and freshwater environments, but little is known about the signalling mechanisms they use to detect changes in their environment. All eukaryotic organisms use Ca2+ signalling to perceive and respond to environmental stimuli, employing a range of Ca2+-permeable ion channels to facilitate the movement of Ca2+ across cellular membranes. We investigated the distribution of different families of Ca2+ channels in diatom genomes, with comparison to other members of the stramenopile lineage. The four-domain voltage-gated Ca2+ channels (Cav) are present in some centric diatoms but almost completely absent in pennate diatoms, whereas single-domain voltage-gated EukCatA channels were found in all diatoms. Glutamate receptors (GLRs) and pentameric ligand-gated ion channels (pLGICs) also appear to have been lost in several pennate species. Transient receptor potential (TRP) channels are present in all diatoms, but have not undergone the significant expansion seen in brown algae. All diatom species analysed lacked the mitochondrial uniporter (MCU), a highly conserved channel type found in many eukaryotes, including several stramenopile lineages. These results highlight the unique Ca2+-signalling toolkit of diatoms and indicate that evolutionary gains or losses of different Ca2+ channels may contribute to differences in cellular-signalling mechanisms between species.
Transparent and Efficient Wood-Based Triboelectric Nanogenerators for Energy Harvesting and Self-Powered Sensing
Authors: Cheng Ting , Cao Kunli , Jing Yidan , Wang Hongyan , Wu Yan
Published: April 2024

Wood possesses several advantageous qualities including innocuity, low cost, aesthetic appeal, and excellent biocompatibility, and its naturally abundant functional groups and diverse structural forms facilitate functionalization modification. As the most sustainable bio-based material, the combination of wood with triboelectric nanogenerators (TENGs) stands poised to significantly advance the cause of green sustainable production while mitigating the escalating challenges of energy consumption. However, the inherent weak polarizability of natural wood limits its development for TENGs. Herein, we present the pioneering development of a flexible transparent wood-based triboelectric nanogenerator (TW-TENG) combining excellent triboelectrical properties, optical properties, and wood aesthetics through sodium chlorite delignification and epoxy resin impregnation. Thanks to the strong electron-donating groups in the epoxy resin, the TW-TENG obtained an open-circuit voltage of up to ~127 V, marking a remarkable 530% enhancement compared to the original wood. Furthermore, durability and stability were substantiated through 10,000 working cycles. In addition, the introduction of epoxy resin and lignin removal endowed the TW-TENG with excellent optical characteristics, with optical transmittance of up to 88.8%, while preserving the unique texture and aesthetics of the wood completely. Finally, we show the application prospects of TW-TENGs in the fields of self-power supply, motion sensing, and smart home through the demonstration of a TW-TENG in the charging and discharging of capacitors and the output of electrical signals in different scenarios.
Prediction of the Bubble Growth Behavior by Means of the Time-, Temperature-, Pressure- and Blowing Agent Concentration-Dependent Transient Elongational Viscosity Function of Polymers
Authors: Schaible Tobias , Bonten Christian
Published: April 2024

Bubble growth processes are highly complex processes, which are not only dependent on the foaming process parameters (temperature, pressure and blowing agent concentration) but also on the type and structure of the polymer used. Since the elongational viscosity at the bubble wall during bubble growth also depends on these influencing factors, the so-called transient elongational viscosity plays a key role in describing the gas bubble growth behavior in polymer melts. The model-based description of the transient elongational viscosity function is difficult due to its dependence on time, Hencky strain and strain rate. Therefore, representative viscosities or shear viscosity models are usually used in the literature to predict the bubble growth behavior. In this work, the transient equibiaxial elongational viscosity function at the bubble wall during bubble growth is described holistically for the first time. This is achieved by extending the so-called molecular stress function (MSF) model by superposition principles (temperature, pressure and blowing agent concentration) and by using the elongational deformation behavior (Hencky strain and strain rate) at the bubble wall during the initial, and thus viscosity-driven, bubble growth process. Therefore, transient uniaxial elongational viscosity measurements are performed and the non-linear MSF model parameters of the two investigated polymers PS (linear polymer chains) and PLA (long-chain branched polymer chains) are determined. By applying the superposition principles and by changing the strain mode parameter to the equibiaxial case in the MSF model, the transient equibiaxial viscosity master curve is obtained and used to describe the bubble growth process. The results show that the extended MSF model can fully predict the transient equibiaxial elongational viscosity function at the bubble wall during bubble growth processes. The bubble growth behavior over time can then be realistically described using the defined transient equibiaxial elongational viscosity function at the bubble wall. This is not possible, for example, with a representative viscosity and therefore clearly demonstrates the influence and importance of knowing the transient deformation behavior that prevails at the bubble wall during bubble growth processes.
Carbon Black Functionalized with Serinol Pyrrole to Replace Silica in Elastomeric Composites
Authors: Magaletti Federica , Galbusera Martina , Gentile Davide , Giese Ulrich , Barbera Vincenzina , Galimberti Maurizio
Published: April 2024

Elastomer composites for dynamic mechanical applications with a low dissipation of energy are of great importance in view of their application in tire compounds. In this work, furnace carbon black functionalized with 2-2,5-dimethyl-1H-pyrrol-1-yl-1,3-propanediol (SP) was used in place of silica in an elastomer composite based on poly(styrene-co-butadiene) from solution anionic polymerization and poly(1,4-cis-isoprene) from Hevea Brasiliensis. The traditional coupling agent used for silica was also used for the CB/SP adduct: 3,3′-bis(triethoxysilylpropyl)tetrasulfide (TESPT). The composite with the CB/SP + TESPT system revealed a lower Payne effect, higher dynamic rigidity, and lower hysteresis, compared to the composite with CB + TESPT, although the latter composite had a higher crosslinking density. The properties of the silica and the CB/SP + TESPT-based composites appear similar, though in the presence of slightly higher hysteresis and lower ultimate properties for the CB/SP-based composite. The use of CB in place of silica allows us to prepare lighter compounds and paves the way for the preparation of tire compounds with lower environmental impacts.
Effect of Simulated Dental Pulpal Pressure Using Fetal Bovine Serum for the Bonding Performance of Contemporary Adhesive to Dentin
Authors: Li Yitong , Maeno Masahiko , Cifuentes-Jimenez Carolina Cecilia , Komoto Mei , Liu Yunqing , Nara Yoichiro , Sano Hidehiko , Alvarez-Lloret Pedro , Yamauti Monica , Tomokiyo Atsushi
Published: April 2024

This study evaluated the effect of simulated pulpal pressure (SPP) conditions and storage time on contemporary adhesive systems’ microtensile bond strength (µTBS) to dentin. Extracted human molars were prepared and randomly divided into four groups according to the adhesives: Clearfil Megabond 2 (CSE), Beautibond Xtreme Universal (BXU), G2-Bond (G2B), and Scotchbond Universal Plus (SBP). Each adhesive group was further divided following the SPP conditions: control with no simulation (SPP-CTR), SPP with distilled water (SPP-DTW), and SPP with fetal bovine serum (SPP-FBS). Resin composite build-ups were prepared, and teeth were stored in water (37 °C) for 24 h (24 h) and 3 months (3 m). Then, teeth were sectioned to obtain resin–dentin bonded beams and tested to determine the µTBS. Data were analyzed using three-way ANOVA, Tukey post hoc tests (=0.05), and Weibull failure analysis. Failure mode was observed using scanning electron microscopy. The µTBS response was affected by adhesive systems, simulated pulpal pressure conditions, and storage time. SPP-CTR groups presented a higher overall bond strength than SPP-DTW and SPP-FBS, which were not significantly different from each other. Only for SBP, the SPP-FBS group showed higher µTBS than the SPP-DTW group. The Weibull analysis showed that the bonding reliability and durability under SPP-DTW and SPP-FBS were inferior to SPP-CTR, and the 24 h bonding quality of adhesives to dentin was superior to that of 3 m. SPP drastically reduced the µTBS of all adhesives to dentin regardless of solution (distilled water or fetal bovine serum). Storage after 3 m also decreased µTBS despite the SPP condition.
Predicting Mechanical Properties of Polymer Materials Using Rate-Dependent Material Models: Finite Element Analysis of Bespoke Upper Limb Orthoses
Authors: Mian Syed Hammad , Umer Usama , Moiduddin Khaja , Alkhalefah Hisham
Published: April 2024

Three-dimensional printing—especially with fused deposition modeling (FDM)—is widely used in the medical field as it enables customization. FDM is versatile owing to the availability of various materials, but selecting the appropriate material for a certain application can be challenging. Understanding materials’ mechanical behaviors, particularly those of polymeric materials, is vital to determining their suitability for a given application. Physical testing with universal testing machines is the most used method for determining the mechanical behaviors of polymers. This method is resource-intensive and requires cylinders for compression testing and unique dumbbell-shaped specimens for tensile testing. Thus, a specialized fixture must be designed to conduct mechanical testing for the customized orthosis, which is costly and time-consuming. Finite element (FE) analysis using an appropriate material model must be performed to identify the mechanical behaviors of a customized shape (e.g., an orthosis). This study analyzed three material models, namely the Bergström–Boyce (BB), three-network (TN), and three-network viscoplastic (TNV) models, to determine the mechanical behaviors of polymer materials for personalized upper limb orthoses and examined three polymer materials: PLA, ABS, and PETG. The models were first calibrated for each material using experimental data. Once the models were calibrated and found to fit the data appropriately, they were employed to examine the customized orthosis’s mechanical behaviors through FE analysis. This approach is innovative in that it predicts the mechanical characteristics of a personalized orthosis by combining theoretical and experimental investigations.
Study on the Adaptability Evaluation of Micro-Dispersed-Gel-Strengthened-Alkali-Compound System and the Production Mechanism of Crude Oil
Authors: Wang Teng , Wu Tianjiang , Liu Yunlong , Cheng Chen , Zhao Guang
Published: April 2024

A novel micro-dispersed-gel (MDG)-strengthened-alkali-compound flooding system was proposed for enhanced oil recovery in high-water-cut mature oilfields. Micro-dispersed gel has different adaptability and application schemes with sodium carbonate and sodium hydroxide. The MDG-strengthened-alkali flooding system can reduce the interfacial tension to an ultra-low interfacial-tension level of 10−2 mN/m, which can reverse the wettability of rock surface. After 30 days aging, the MDG-strengthened-Na2CO3 flooding system has good viscosity retention of 74.5%, with an emulsion stability of 79.13%. The enhanced-oil-recovery ability of the MDG-strengthened-Na2CO3 (MDGSC) flooding system is 43.91%, which is slightly weaker than the 47.78% of the MDG-strengthened-NaOH (MDGSH) flooding system. The crude-oil-production mechanism of the two systems is different, but they all show excellent performance in enhanced oil recovery. The MDGSC flooding system mainly regulates and seals micro-fractures, forcing subsequent injected water to enter the low-permeability area, and it has the ability to wash the remaining oil in micro-fractures. The MDGSH flooding system mainly removes the remaining oil on the rock wall surface in the micro-fractures by efficient washing, and the MDG particles can also form weak plugging of the micro-fractures. The MDG-strengthened-alkali flooding system can be used as an alternative to enhance oil recovery in high-water-cut and highly heterogeneous mature oilfields.
The St. Honoré Portal at Amiens Cathedral and Its Reception
Authors: Shalom Gili
Published: April 2024

This article discusses the depictions of healings on the St. Honoré portal at Amiens Cathedral (post-1240) and the visual strategies by which its viewers were invited to participate in the saint’s cult. I contend that the carved figures who gaze or gesture beyond the borders of the tympanum invited the active participation of a broad audience of spectators: male and female, young and old, rich and poor, clerical and lay, and disabled and hale. Moreover, I argue that by referencing both the saint’s vita and more contemporary miracle accounts, the sculptures negotiated between the historical past and the Gothic present, allowing the viewers to share in the hope for a miraculous cure.
Safe and Effective Treatment of Patients with Urinary Tract Infections Caused by Extended-Spectrum Beta Lactamase-Producing Enterobacteriaceae via Telemedicine-Controlled Hospital at Home: A Case Series of 11 Patients
Authors: Gilboa Mayan , Hack Sholem , Hochner Shahar , Gitbinder Mark , Yakovlev Megi , Bineth Noa , Barkai Galia , Segal Gad
Published: April 2024

Background: Resistant bacteria causing urinary tract infections (UTI) are becoming increasingly common worldwide. Patients suffering from such UTIs are often elderly, with complex medical backgrounds, and require prolonged hospital stays due to the frequent need for intravenous antibiotics. The alternative hospital-at-home (HAH) option for such patients should, therefore, be explored. Methods. We present our experience in the treatment of patients with extended-spectrum beta-lactamase (ESBL) infections treated through our HAH service. Results: Eleven such patients were included in our HAH service between February 2022 and December 2023 (median age: 79 years; 64% females; 57% had diabetes mellitus in their background). Of these patients, 27.2% had urinary instrumentations and 81.8% had a history of previous UTIs, of which 77.7% had resistant bacteria. The most common pathogen (7 out of 9 patients) was Escherichia coli. All eleven pathogens were resistant to ceftriaxone and ciprofloxacin. The mean length of hospitalization was 5 ± 2 days. Eight patients (72.7%) did not experience recurrent UTIs. Only two patients (18.2%) experienced acute kidney injury, which resolved during their HAH stay. Two patients died during a 30-day follow up from causes unrelated to their UTI. Conclusions: Treatment of patients presenting with urinary tract infections with resistant ESBL pathogens in the setting of a telemedicine-assisted, hospital-at-home setting is both effective and safe.
The Comminution of Chert Gravel by Microwave Irradiation
Authors: Tzibulsky Mark , Frid Vladimir
Published: April 2024

Chert, a by-product rock of sand quarrying, has historically posed economic challenges for aggregate production, resulting in significant “waste” accumulation in quarries. Our study investigates the effect of microwave irradiation on the mechanical properties of chert gravel, a mineralogically homogenous material composed of fine quartz grains. The results, which demonstrate that increased irradiation time leads to a substantial decrease in chert gravel strength (by a factor of 4–6 for 2.5 min of irradiation), underscore the potential impact of this research on comminution processes. With quenching altering the fractional content of the samples after the crushing test, reducing the Gravel-to-Sand ratio, this study is driven by the promising potential of crushed chert gravel as a pivotal aggregate within the concrete and asphalt industries, offering a practical solution to their material needs. The urgent need to rehabilitate previously utilized quarry areas, offering an environmentally beneficial solution for which we all should be responsible, motivated the present study.
Optimized Decentralized Swarm Communication Algorithms for Efficient Task Allocation and Power Consumption in Swarm Robotics
Authors: Yasser Mohamed , Shalash Omar , Ismail Ossama
Published: April 2024

Unanimous action to achieve specific goals is crucial for the success of a robotic swarm. This requires clearly defined roles and precise communication between the robots of a swarm. An optimized task allocation algorithm defines the mechanism and logistics of decision-making that enable the robotic swarm to achieve such common goals. With more nodes, the traffic of messages that are required to communicate inside the swarm relatively increases to maintain decentralization. Increased traffic eliminates real-time capabilities, which is an essential aspect of a swarm system. The aim of this research is to reduce execution time while retaining efficient power consumption rates. In this research, two novel decentralized swarm communication algorithms are proposed, namely Clustered Dynamic Task Allocation–Centralized Loop (CDTA-CL) and Clustered Dynamic Task Allocation–Dual Loop (CDTA-DL), both inspired by the Clustered Dynamic Task Allocation (CDTA) algorithm. Moreover, a simulation tool was developed to simulate different swarm-clustered communication algorithms in order to calculate the total communication time and consumed power. The results of testing the proposed CDTA-DL and CDTA-CL against the CDTA attest that the proposed algorithm consumes substantially less time. Both CDTA-DL and CDTA-CL have achieved a significant speedup of 75.976% and 54.4% over CDTA, respectively.
Efficient Target Classification Based on Vehicle Volume Estimation in High-Resolution Radar Systems
Authors: Hwangbo Sanghyeok , Cho Seonmin , Kim Junho , Lee Seongwook
Published: April 2024

In this paper, we propose a method for efficient target classification based on the spatial features of the point cloud generated by using a high-resolution radar sensor. The frequency-modulated continuous wave radar sensor can estimate the distance and velocity of a target. In addition, the azimuth and elevation angle of the target can be estimated by using a multiple-input and multiple-output antenna system. Using the estimated distance, velocity, and angle, the 3D point cloud of target can be generated. From the generated point cloud, we extract the point cloud for each individual target using the density-based spatial clustering of application with noise method and a camera mounted on the radar sensor. Then, we define the convex hull boundaries that enclose these point clouds in both 3D and 2D spaces obtained by orthogonally projecting onto the xy, yz, and zx planes. Using the vertices of convex hull, we calculate the volume of the targets and the areas in 2D spaces. Several feature points, including the calculated spatial information, are numerized and configured into feature vectors. We design an uncomplicated deep neural network classifier based on minimal input information to achieve fast and efficient classification performance. As a result, the proposed method achieved an average accuracy of 97.1%, and the time required for training was reduced compared to the method using only point cloud data and the convolutional neural network-based method.
Combining LiDAR and Spaceborne Multispectral Data for Mapping Successional Forest Stages in Subtropical Forests
Authors: Ziegelmaier Neto Bill Herbert , Schimalski Marcos Benedito , Liesenberg Veraldo , Sothe Camile , Martins-Neto Rorai Pereira , Floriani Mireli Moura Pitz
Published: April 2024

The Brazilian Atlantic Rainforest presents great diversity of flora and stand structures, making it difficult for traditional forest inventories to collect reliable and recurrent information to classify forest succession stages. In recent years, remote sensing data have been explored to save time and effort in classifying successional forest stages. However, there is a need to understand if any of these sensors stand out for this purpose. Here, we evaluate the use of multispectral satellite data from four different platforms (CBERS-4A, Landsat-8/OLI, PlanetScope, and Sentinel-2) and airborne light detection and ranging (LiDAR) to classify three forest succession stages in a subtropical ombrophilous mixed forest located in southern Brazil. Different features extracted from multispectral and LiDAR data, such as spectral bands, vegetation indices, texture features, and the canopy height model (CHM) and LiDAR intensity, were explored using two conventional machine learning methods such as random trees (RT) and support vector machine (SVM). The statistically based maximum likelihood (MLC) algorithm was also compared. The classification accuracy was evaluated by generating a confusion matrix and calculating the kappa index and standard deviation based on field measurements and unmanned aerial vehicle (UAV) data. Our results show that the kappa index ranged from 0.48 to 0.95, depending on the chosen dataset and method. The best result was obtained using the SVM algorithm associated with spectral bands, CHM, LiDAR intensity, and vegetation indices, regardless of the sensor. Datasets with Landsat-8 or Sentinel-2 information performed better results than other optical sensors, which may be due to the higher intraclass variability and less spectral bands in CBERS-4A and PlanetScope data. We found that the height information derived from airborne LiDAR and its intensity combined with the multispectral data increased the classification accuracy. However, the results were also satisfactory when using only multispectral data. These results highlight the potential of using freely available satellite information and open-source software to optimize forest inventories and monitoring, enabling a better understanding of forest structure and potentially supporting forest management initiatives and environmental licensing programs.
Full-Process Adaptive Encoding and Decoding Framework for Remote Sensing Images Based on Compression Sensing
Authors: Hu Huiling , Liu Chunyu , Liu Shuai , Ying Shipeng , Wang Chen , Ding Yi
Published: April 2024

Faced with the problem of incompatibility between traditional information acquisition mode and spaceborne earth observation tasks, starting from the general mathematical model of compressed sensing, a theoretical model of block compressed sensing was established, and a full-process adaptive coding and decoding compressed sensing framework for remote sensing images was proposed, which includes five parts: mode selection, feature factor extraction, adaptive shape segmentation, adaptive sampling rate allocation and image reconstruction. Unlike previous semi-adaptive or local adaptive methods, the advantages of the adaptive encoding and decoding method proposed in this paper are mainly reflected in four aspects: (1) Ability to select encoding modes based on image content, and maximizing the use of the richness of the image to select appropriate sampling methods; (2) Capable of utilizing image texture details for adaptive segmentation, effectively separating complex and smooth regions; (3) Being able to detect the sparsity of encoding blocks and adaptively allocate sampling rates to fully explore the compressibility of images; (4) The reconstruction matrix can be adaptively selected based on the size of the encoding block to alleviate block artifacts caused by non-stationary characteristics of the image. Experimental results show that the method proposed in this article has good stability for remote sensing images with complex edge textures, with the peak signal-to-noise ratio and structural similarity remaining above 35 dB and 0.8. Moreover, especially for ocean images with relatively simple image content, when the sampling rate is 0.26, the peak signal-to-noise ratio reaches 50.8 dB, and the structural similarity is 0.99. In addition, the recovered images have the smallest BRISQUE value, with better clarity and less distortion. In the subjective aspect, the reconstructed image has clear edge details and good reconstruction effect, while the block effect is effectively suppressed. The framework designed in this paper is superior to similar algorithms in both subjective visual and objective evaluation indexes, which is of great significance for alleviating the incompatibility between traditional information acquisition methods and satellite-borne earth observation missions.
Overview of High-Power and Wideband Radar Technology Development at MIT Lincoln Laboratory
Authors: MacDonald Michael , Abouzahra Mohamed , Stambaugh Justin
Published: April 2024

This paper summarizes over 60 years of radar system development at MIT Lincoln Laboratory, from early research on satellite tracking and planetary radar to the present ability to perform the centimeter-resolution imaging of resident space objects and future plans to extend this capability to geosynchronous range.
GWO-Based Joint Optimization of Millimeter-Wave System and Multilayer Perceptron for Archaeological Application
Authors: Marot Julien , Zidane Flora , El-Abed Maha , Lanteri Jerome , Dauvignac Jean-Yves , Migliaccio Claire
Published: April 2024

Recently, low THz radar-based measurement and classification for archaeology emerged as a new imaging modality. In this paper, we investigate the classification of pottery shards, a key enabler to understand how the agriculture was introduced from the Fertile Crescent to Europe. Our purpose is to jointly design the measuring radar system and the classification neural network, seeking the maximal compactness and the minimal cost, both directly related to the number of sensors. We aim to select the least possible number of sensors and place them adequately, while minimizing the false recognition rate. For this, we propose a novel version of the Binary Grey Wolf Optimizer, designed to reduce the number of sensors, and a Ternary Grey Wolf Optimizer. Together with the Continuous Grey Wolf Optimizer, they yield the CBTGWO (Continuous Binary Ternary Grey Wolf Optimizer). Working with 7 frequencies and starting with 37 sensors, the CBTGWO selects a single sensor and yields a 0-valued false recognition rate. In a single-frequency scenario, starting with 217 sensors, the CBTGWO selects 2 sensors. The false recognition rate is 2%. The acquisition time is 3.2 s, outperforming the GWO and adaptive mixed GWO, which yield 86.4 and 396.6 s.
Label- and Reagent-Free Optical Sensor for Absorption-Based Detection of Urea Concentration in Water Solutions
Authors: Anelli Carlo , Pellicorio Vanessa , Bello Valentina , Merlo Sabina
Published: April 2024

Contactless and label-free detection of urea content in aqueous solutions is of great interest in chemical, biomedical, industrial, and automotive applications. In this work, we demonstrate a compact and low-cost instrumental configuration for label-free, reagent-free, and contactless detection of urea dissolved in water, which exploits the absorption properties of urea in the near-infrared wavelength region. The intensity of the radiation transmitted through the fluid under test, contained in a rectangle hollow glass tubing with an optical pathlength of 1 mm, is detected in two spectral bands. Two low-cost, low-power LEDs with emission spectra centered at λ = 1450 nm and λ = 2350 nm are used as readout sources. The photodetector is positioned on the other side of the tubing, in front of the LEDs. The detection performances of a photodiode and of a thermal optical power detector have been compared, exploiting different approaches for LED driving current modulation and photodetected signal processing. The implemented detection system has been tested on urea–water solutions with urea concentrations from 0 up to 525 mg/mL as well as on two samples of commercial diesel exhaust fluid (“AdBlue™”). Considering the transmitted intensity in presence of the urea–water solution, at λ = 1450 nm and λ = 2350 nm, normalized to the transmitted intensity in presence of water, we demonstrate that their ratio is linearly related to urea concentration on a wide range and with good sensitivity.
HALNet: Partial Point Cloud Registration Based on Hybrid Attention and Deep Local Features
Authors: Wang Deling , Hao Huadan , Zhang Jinsong
Published: April 2024

Point cloud registration is an important task in computer vision and robotics which is widely used in 3D reconstruction, target recognition, and other fields. At present, many registration methods based on deep learning have better registration accuracy in complete point cloud registration, but partial registration accuracy is poor. Therefore, a partial point cloud registration network, HALNet, is proposed. Firstly, a feature extraction network consisting mainly of adaptive graph convolution (AGConv), two-dimensional convolution, and convolution block attention (CBAM) is used to learn the features of the initial point cloud. Then the overlapping estimation is used to remove the non-overlapping points of the two point clouds, and the hybrid attention mechanism composed of self-attention and cross-attention is used to fuse the geometric information of the two point clouds. Finally, the rigid transformation is obtained by using the fully connected layer. Five methods with excellent registration performance were selected for comparison. Compared with SCANet, which has the best registration performance among the five methods, the RMSE(R) and MAE(R) of HALNet are reduced by 10.67% and 12.05%. In addition, the results of the ablation experiment verify that the hybrid attention mechanism and fully connected layer are conducive to improving registration performance.
Transient Interference Excision and Spectrum Reconstruction with Partial Samples Using Modified Alternating Direction Method of Multipliers-Net for the Over-the-Horizon Radar
Authors: Man Zhang , Huang Quan , Duan Jia
Published: April 2024

Transient interference often submerges the actual targets when employing over-the-horizon radar (OTHR) to detect targets. In addition, modern OTHR needs to carry out multi-target detection from sea to air, resulting in the sparse sampling of echo data. The sparse OTHR signal will raise serious grating lobes using conventional methods and thus degrade target detection performance. This article proposes a modified Alternating Direction Method of Multipliers (ADMM)-Net to reconstruct the target and clutter spectrum of sparse OTHR signals so that target detection can be performed normally. Firstly, transient interferences are identified based on the sparse basis representation and then excised. Therefore, the processed signal can be seen as a sparse OTHR signal. By solving the Doppler sparsity-constrained optimization with the trained network, the complete Doppler spectrum is reconstructed effectively for target detection. Compared with traditional sparse solution methods, the presented approach can balance the efficiency and accuracy of OTHR signal spectrum reconstruction. Both simulation and real-measured OTHR data proved the proposed approach’s performance.
USV Trajectory Tracking Control Based on Receding Horizon Reinforcement Learning
Authors: Wen Yinghan , Chen Yuepeng , Guo Xuan
Published: April 2024

We present a novel approach for achieving high-precision trajectory tracking control in an unmanned surface vehicle (USV) through utilization of receding horizon reinforcement learning (RHRL). The control architecture for the USV involves a composite of feedforward and feedback components. The feedforward control component is derived directly from the curvature of the reference path and the dynamic model. Feedback control is acquired through application of the RHRL algorithm, effectively addressing the problem of achieving optimal tracking control. The methodology introduced in this paper synergizes with the rolling time domain optimization mechanism, converting the perpetual time domain optimal control predicament into a succession of finite time domain control problems amenable to resolution. In contrast to Lyapunov model predictive control (LMPC) and sliding mode control (SMC), our proposed method employs the RHRL controller, which yields an explicit state feedback control law. This characteristic endows the controller with the dual capabilities of direct offline and online learning deployment. Within each prediction time domain, we employ a time-independent executive–evaluator network structure to glean insights into the optimal value function and control strategy. Furthermore, we substantiate the convergence of the RHRL algorithm in each prediction time domain through rigorous theoretical proof, with concurrent analysis to verify the stability of the closed-loop system. To conclude, USV trajectory control tests are carried out within a simulated environment.
Grating (Moiré) Microinterferometric Displacement/Strain Sensor with Polarization Phase Shift
Authors: Sałbut Leszek , Łukaszewski Dariusz , Piekarska Aleksandra
Published: April 2024

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. This article presents both the theoretical considerations associated with the proposed solution and its experimental verification, along with the concept of in-plane displacement/strain sensing using the described head.
Navigating the Power of Artificial Intelligence in Risk Management: A Comparative Analysis
Authors: Yazdi Mohammad , Zarei Esmaeil , Adumene Sidum , Beheshti Amin
Published: April 2024

This study presents a responsive analysis of the role of artificial intelligence (AI) in risk management, contrasting traditional approaches with those augmented by AI and highlighting the challenges and opportunities that emerge. AI, intense learning methodologies such as convolutional neural networks (CNNs), have been identified as pivotal in extracting meaningful insights from image data, a form of analysis that holds significant potential in identifying and managing risks across various industries. The research methodology involves a strategic selection and processing of images for analysis and introduces three case studies that serve as benchmarks for evaluation. These case studies showcase the application of AI, in place of image processing capabilities, to identify hazards, evaluate risks, and suggest control measures. The comparative evaluation focuses on the accuracy, relevance, and practicality of the AI-generated findings alongside the system’s response time and comprehensive understanding of the context. Results reveal that AI can significantly enhance risk assessment processes, offering rapid and detailed insights. However, the study also recognises the intrinsic limitations of AI in contextual interpretation, advocating for a synergy between technological and domain-specific expertise. The conclusion underscores the transformative potential of AI in risk management, supporting continued research to further integrate AI effectively into risk assessment frameworks.
Metabolite Profiling and Molecular Network Shows Kinkeloids as Promoting of Collagen Synthesis from Combretum micranthum
Authors: Messaili Souhila , Haggouch Doha , Bignard Mikaela , Campos Pierre-Eric , Destandau Emilie , Delannay Eldra
Published: April 2024

Combretum micranthum, a plant native to Africa, has a well-documented traditional use in the treatment of various ailments such as fever, diabetes, and malaria. Its pharmaceutical benefits include nephroprotective, anti-inflammatory, antioxidant, and antimicrobial properties, which were proven. In addition, its potential for cosmetic applications is being explored due to its depigmenting, anti-inflammatory, and UV-damage-repairing properties. This article investigates the molecular composition and new cosmetically relevant biological activity of C. micranthum and enriched fractions to begin the establishment of the structure–activity relationship. Firstly, an extract of C. micranthum was prepared and selected for its overall biological response and then fractionated to obtain simplified molecular fractions. One fraction was particularly enriched in kinkeloids, a specific family of compounds to this species. All the fractions and the crude extract were then tested on biological targets to evaluate and compare their cosmetic activities. Molecular networks were constructed from the UHPLC-MS/HRMS data to better characterize the extract and fractions and to highlight structure–activity relationships. This study highlights the metabolic profiling of a butylene glycol extract of C. micranthum, showing its main chemical families and revealing that the kinkeloids, identified by HRMS and NMR, promote an increase in collagen I synthesis, an interesting cosmetic activity neither previously described for these compounds and neither for C. micranthum extract.