Search Results (116)

Given the growing threat posed by the widespread availability of unmanned aircraft systems (UASs), which can be utilised for various unlawful activities, the need for a standardised method to evaluate the effectiveness of systems capable of detecting, tracking, and identifying (DTI) these devices has become increasingly urgent. This article draws upon research conducted under the European project COURAGEOUS, where 260 existing drone detection systems were analysed, and a methodology was developed for assessing the suitability of C-UASs in relation to specific threat scenarios. The article provides an overview of the most commonly employed technologies in C-UASs, such as radars, visible light cameras, thermal imaging cameras, laser range finders (lidars), and acoustic sensors. It explores the advantages and limitations of each technology, highlighting their reliance on different physical principles, and also briefly touches upon the legal implications associated with their deployment. The article presents the research framework and provides a structural description, alongside the functional and performance requirements, as well as the defined metrics. Furthermore, the methodology for testing the usability and effectiveness of individual C-UAS technologies in addressing specific threat scenarios is elaborated. Lastly, the article offers a concise list of prospective research directions concerning the analysis and evaluation of these technologies. Full article

Siraitia siamensis is a traditional Chinese medicinal herb. In this study, using S. siamensis cultivated in vitro, twelve candidate reference genes under various treatments were analyzed for their expression stability by using algorithms such as GeNorm, NormFinder, BestKeeper, Delta CT, and RefFinder. The selected reference genes were then used to characterize the gene expression of cucurbitadienol synthase, which is a rate-limiting enzyme for mogroside biosynthesis. The results showed that CDC6 and NCBP2 expression was the most stable across all treatments and are the best reference genes under the tested conditions. Utilizing the validated reference genes, we analyzed the expression profiles of genes related to the synthesis pathway of mogroside in S. siamensis in response to a range of abiotic stresses. The findings of this study provide clear standards for gene expression normalization in Siraitia plants and exploring the rationale behind differential gene expression related to mogroside synthesis pathways. Full article

Background: Childhood blindness remains a neglected issue in eye care within low-income countries, with congenital and juvenile cataracts being the most common treatable causes. This study aims to investigate the factors influencing the management of congenital and juvenile bilateral cataracts, provide data on general outcomes and postoperative findings, and discuss treatment in a low-income country context. Methods: In this prospective study, data from clinical care were continuously entered into a database, and one follow-up examination of a cohort of 91 patients with congenital and juvenile bilateral cataracts in Kinshasa, Democratic Republic of the Congo, was conducted. Multiple factors that affect the first clinical presentation, the clinical management, and outcome were investigated. Results: Most patients (88.5%) who received medical treatment were identified by cataract finders. A patient’s presentation time was independent of the parent’s education, social status, income, and sex of the child. The median age at first presentation was 5.8 years (ranging from 0 days to 17.3 years). The best visual acuity outcomes were achieved by patients who underwent surgery during early childhood. According to WHO grades and on an eye level basis, 51.1% (93 out of 182 eyes) showed improvement, while 34.6% (63 eyes) had unchanged results post-surgery. Among the cases without improvement, 76.2% were blind prior to surgery. Postoperative findings were observed in 56% of the patients, with secondary cataracts being the most common, affecting 26.37% of the operated eyes. Conclusions: Optimal management of childhood cataracts involves early identification, efficient hospital infrastructure, high-quality medical care, and long-term follow up. In sub-Saharan Africa, this approach must be adapted to the context of available resources, which differs significantly from those in high- and middle-income countries. Full article

This manuscript focuses on the process of measuring the angular positions of radio sources using radio engineering systems. This study aims to improve the accuracy of measuring the angular positions of sources that radiate functionally determined signals and to expand the range of the unambiguous operation angles for multi-antenna radio direction finders. To achieve this goal, the following tasks were addressed: (1) defining the models of signals, noise, and their statistical characteristics, (2) developing the theoretical foundations of statistical optimization methods for measuring the angular positions of radio sources in multi-antenna radio direction finders, (3) optimizing the structures of radio direction finders with different configurations, (4) analyzing the accuracy and range of the unambiguous measurement angles in the developed methods, and (5) conducting experimental measurements to confirm the main results. The methods used are based on the statistical theory of optimization for remote sensing and radar systems. For the specified type of signals, given by functionally deterministic models, a likelihood function was constructed, and its maxima were determined for different multi-antenna direction finder configurations. The results of statistical synthesis were verified through simulation modeling and experiments. The primary approach to improving measurement accuracy and expanding the range of unambiguous angles involves combining antennas with different spatial characteristics and optimally integrating classical radio direction-finding methods. The following results were obtained: (1) theoretical studies and simulation modeling confirmed the existence of a contradiction between high resolution and the width of the range of the unambiguous measurements in two-antenna radio direction finders, (2) an improved signal processing method was developed for a four-antenna radio direction finder with a pair of high-gain and a pair of low-gain antennas, and (3) to achieve maximum direction-finding accuracy within the unambiguous measurement range, a new signal processing method was synthesized for a six-element radio receiver, combining processing in two amplitude direction finders and one phase direction finder. This work provides a foundation for further theoretical studies, highlights the specifics of combining engineering measurements in direction-finding systems, and offers examples of rapid verification of new methods through computer modeling and experimental measurements. Full article

Aralia continentalis Kitag. (A. continentalis) holds significant medicinal value among the Aralia genus. It has traditionally been employed in ethnomedicine to address a wide range of conditions, including wind–cold–dampness arthralgia; rheumatic pain in the waist and lower extremities; lumbar muscular strain; injuries resulting from falls, fractures, contusions, and strains; headache; toothache; and abscesses. Modern pharmacological research has validated its therapeutic potential, encompassing anti-inflammatory, analgesic, antioxidant, antimicrobial, insecticidal, hepatoprotective, anti-diabetic, and cytotoxic properties, among other pharmacological effects. To compile comprehensive knowledge on A. continentalis, a rigorous literature search was undertaken utilizing databases like SciFinder, PubMed, and Web of Science. This review seeks to delve into the plant’s traditional applications, geographical distribution, botanical characteristics, phytochemistry, and pharmacology. The objective is to lay a foundation and propose novel research directions for exploring the plant’s potential applications. Currently, one hundred and fifty-nine compounds have been isolated and identified from A. continentalis, encompassing diterpenoids, steroids, triterpenoids, volatile components, phenolics, vitamins, trace elements, and other compounds. Notably, diterpenoids, steroids, triterpenoids, volatile components, and phenolics have exhibited pronounced pharmacological effects, such as anti-inflammatory, analgesic, antioxidant, hepatoprotective, antidiabetic, and antimicrobial activities. However, despite the extensive research conducted, further studies are imperative to unravel new components and mechanisms of action, necessitating more in-depth investigations. This comprehensive exploration could pave the way for advancing and harnessing the potential of A. continentalis. Full article

Dexamethasone (Dex) is a widely used glucocorticoid in medical practice, with applications ranging from allergies and inflammation to cerebral edema and shock. Despite its therapeutic benefits, Dex is classified as a prohibited substance for athletes due to its potential performance-enhancing effects. Consequently, there is a critical need for a convenient and rapid detection platform to enable prompt and accurate testing of this drug. In this study, we propose a label-free Förster Resonance Energy Transfer (FRET) aptasensor platform for Dex detection utilizing conjugated polymers (CPs), cationic conjugated polymers (CCPs), and gene finder probes (GFs). The system operates by exploiting the electrostatic interactions between positively charged CCPs and negatively charged DNA, facilitating sensitive and specific Dex detection. The label-free FRET aptasensor platform demonstrated robust performance in detecting Dex, exhibiting high selectivity and sensitivity. The system effectively distinguished Dex from interfering molecules and achieved stable detection across a range of concentrations in a commonly used sports drink matrix. Overall, the label-free FRET Dex detection system offers a simple, cost-effective, and highly sensitive approach for detecting Dex in diverse sample matrices. Its simplicity and effectiveness make it a promising tool for anti-doping efforts and other applications requiring rapid and accurate Dex detection. Full article

This study investigates the differential expression of miRNA gene subtypes in tumoral versus benign nevi in individuals with melanoma, aiming to identify clinically significant correlations that could serve as reliable markers for assessing tumor stage and progression. Conducted between 2019 and 2022, this descriptive, quantitative observational research analyzed 90 formalin-fixed paraffin-embedded (FFPE) samples from the Pius Brinzeu County Emergency Clinical Hospital, Timisoara, including 45 samples of advanced-stage melanoma and 45 samples of pigmented nevi. miRNA purification and analysis were performed using the miRNeasy Kit and the Human Cancer PathwayFinder miScript miRNA PCR Array, with statistical analysis (including logistic regression) to determine associations with cancer staging, such as high Breslow index risk, number of mitoses, and vascular invasion. After the analysis and comparison of 180 miRNA gene subtypes, we selected 10 of the most upregulated and 10 most downregulated genes. The results revealed that hsa-miR-133b, hsa-miR-335-5p, hsa-miR-200a-3p, and hsa-miR-885-5p were significantly upregulated in melanoma samples, with fold changes ranging from 1.09 to 1.12. Conversely, hsa-miR-451a and hsa-miR-29b-3p showed notable downregulation in melanoma, with fold changes of 0.90 and 0.92, respectively. Additionally, logistic regression analysis identified hsa-miR-29b-3p (OR = 2.51) and hsa-miR-200a-3p (OR = 2.10) as significantly associated with an increased risk of a high Breslow index, while hsa-miR-127-3p and hsa-miR-451a were associated with a reduced risk. Conclusively, this study underscores the significant alterations in miRNA expression in melanoma compared to benign nevi and highlights the potential of specific miRNAs as biomarkers for melanoma progression. The identification of miRNAs with significant associations to melanoma characteristics suggests their utility in developing non-invasive, cost-effective diagnostic tools and in guiding therapeutic decisions, potentially improving patient outcomes in melanoma management. Full article

Sirtuins (SIRTs) are classified as class III histone deacetylases (HDACs), a family of enzymes that catalyze the removal of acetyl groups from the ε-N-acetyl lysine residues of histone proteins, thus counteracting the activity performed by histone acetyltransferares (HATs). Based on their involvement in different biological pathways, ranging from transcription to metabolism and genome stability, SIRT dysregulation was investigated in many diseases, such as cancer, neurodegenerative disorders, diabetes, and cardiovascular and autoimmune diseases. The elucidation of a consistent number of SIRT–ligand complexes helped to steer the identification of novel and more selective modulators. Due to the high diversity and quantity of the structural data thus far available, we reviewed some of the different ligands and structure-based methods that have recently been used to identify new promising SIRT1/2 modulators. The present review is structured into two sections: the first includes a comprehensive perspective of the successful computational approaches related to the discovery of SIRT1/2 inhibitors (SIRTIs); the second section deals with the most interesting SIRTIs that have recently appeared in the literature (from 2017). The data reported here are collected from different databases (SciFinder, Web of Science, Scopus, Google Scholar, and PubMed) using “SIRT”, “sirtuin”, and “sirtuin inhibitors” as keywords. Full article

Unmanned aerial vehicles (UAVs) provide benefits through eco-friendliness, cost-effectiveness, and reduction of human risk. Deep reinforcement learning (DRL) is widely used for autonomous UAV navigation; however, current techniques often oversimplify the environment or impose movement restrictions. Additionally, most vision-based systems lack precise depth perception, while range finders provide a limited environmental overview, and LiDAR is energy-intensive. To address these challenges, this paper proposes VizNav, a modular DRL-based framework for autonomous UAV navigation in dynamic 3D environments without imposing conventional mobility constraints. VizNav incorporates the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with Prioritized Experience Replay and Importance Sampling (PER) to improve performance in continuous action spaces and mitigate overestimations. Additionally, VizNav employs depth map images (DMIs) to enhance visual navigation by accurately estimating objects’ depth information, thereby improving obstacle avoidance. Empirical results show that VizNav, by leveraging TD3, improves navigation, and the inclusion of PER and DMI further boosts performance. Furthermore, the deployment of VizNav across various experimental settings confirms its flexibility and adaptability. The framework’s architecture separates the agent’s learning from the training process, facilitating integration with various DRL algorithms, simulation environments, and reward functions. This modularity creates a potential to influence RL simulation in various autonomous navigation systems, including robotics control and autonomous vehicles. Full article

Based on the tunnel crack width identification, there are operating time constraints, limited operating space, high equipment testing costs, and other issues. In this paper, a large subway tunnel is a research object, and the tunnel rail inspection car is an operating platform equipped with industrial cameras in order to meet the requirements of the tunnel tube sheet crack width recognition of more than 0.2 mm, with the measuring instrument to verify that the tunnel rail inspection car in the state of uniform motion camera imaging quality has the reliability through the addition of laser rangefinders, the accurate measurement of the object distance and the calculation of the imaging plane and the angle of the plane to be measured, to amend the three-dimensional cracks. The pixel resolution of the image is corrected, the images imaged by the industrial camera are preprocessed, the YOLOv8 algorithm is used for the intelligent extraction of crack morphology, and finally, the actual width is calculated from the spacing between two points of the crack. The crack detection width obtained by image processing using the YOLOv8 algorithm is basically the same as the value of crack width obtained by manual detection, and the error rate of crack width detection ranges from 0% to 11%, with the average error rate remaining below 4%. Compared with the crack detection error rate of the Support Vector Machine (SVM), the crack extraction model is reduced by 1%, so using the tunnel inspection vehicle as a platform equipped with an industrial camera, YOLOv8 is used to realize the recognition of the shape and width of the cracks on the surface of the tunnel tube sheet to meet the requirements of a higher degree of accuracy. The number of pixels and the detection error rate are inversely proportional to each other. The angle between the imaging plane and the plane under test is directly proportional to the detection error rate. The angle between the vertical axis where the lens midpoint is located and the line connecting the shooting target and the lens center point is ${\alpha }_i$ and the angle ${\theta }_i$ between the measured plane and the imaging plane is reciprocal, i.e., ${\alpha }_i$ + ${\theta }_i$ = 90°. Therefore, using the inspection vehicle as a mobile platform equipped with an industrial camera and based on the YOLOv8 algorithm, the crack recognition of the tunnel tube sheet has the feasibility and the prospect of wide application, which provides a reference method for the detection of cracks in the tunnel tube sheet. Full article

Quantitative reverse transcription PCR (qRT-PCR) can screen applicable reference genes of species, and reference genes can be used to reduce experimental errors. Sudan grass (Sorghum sudanense (Piper) Stapf) is a high-yield, abiotic-tolerant annual high-quality forage with a wide range of uses. However, no studies have reported reference genes suitable for Sudan grass. Therefore, we found eight candidate reference genes, including UBQ10, HIS3, UBQ9, Isoform0012931, PP2A, ACP2, eIF4α, and Actin, under salt stress (NaCl), drought stress (DR), acid aluminum stress (AlCl₃), and methyl jasmonate treatment (MeJA). By using geNorm, NormFinder, BestKeeper, and RefFinder, we ranked eight reference genes on the basis of their expression stabilities. The results indicated that the best reference gene was PP2A under all treatments. eIF4α can be used in CK, MeJA, NaCl, and DR. HIS3 can serve as the best reference gene in AlCl₃. Two target genes (Isoform0007606 and Isoform0002387) belong to drought-stress-response genes, and they are highly expressed in Sudan grass according to transcriptome data. They were used to verify eight candidate reference genes under drought stress. The expression trends of the two most stable reference genes were similar, but the trend in expression for Actin showed a significant difference. The reference genes we screened provided valuable guidance for future research on Sudan grass. Full article

In traditional Chinese medicine, Angelica dahurica is a valuable herb with numerous therapeutic applications for a range of ailments. There have not yet been any articles on the methodical assessment and choice of the best reference genes for A. dahurica gene expression studies. Real-time quantitative PCR (RT-qPCR) is widely employed as the predominant method for investigating gene expression. In order to ensure the precise determination of target gene expression outcomes in RT-qPCR analysis, it is imperative to employ stable reference genes. In this study, a total of 11 candidate reference genes including SAND family protein (SAND), polypyrimidine tract-binding protein (PTBP), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), TIP41-like protein (TIP41), cyclophilin 2 (CYP2), elongation factor 1 α (EF1α), ubiquitin-protein ligase 9 (UBC9), tubulin β-6 (TUB6), thioredoxin-like protein YLS8 (YLS8), and tubulin-α (TUBA) were selected from the transcriptome of A. dahurica. Subsequently, three statistical algorithms (geNorm, NormFinder, and BestKeeper) were employed to assess the stability of their expression patterns across seven distinct stimulus treatments. The outcomes obtained from these analyses were subsequently amalgamated into a comprehensive ranking using RefFinder. Additionally, one target gene, phenylalanine ammonia-lyase (PAL), was used to confirm the effectiveness of the selected reference genes. According to the findings of this study, the two most stable reference genes for normalizing the expression of genes in A. dahurica are TIP41 and UBC9. Overall, our research has determined the appropriate reference genes for RT-qPCR in A. dahurica and provides a crucial foundation for gene screening and identifying genes associated with the biosynthesis of active ingredients in A. dahurica. Full article

Robot autonomous navigation has become a vital area in the industrial development of minimizing labor-intensive tasks. Most of the recently developed robot navigation systems are based on perceiving geometrical features of the environment, utilizing sensory devices such as laser scanners, range-finders, and microwave radars to construct an environment map. However, in robot navigation, scene understanding has become essential for comprehending the area of interest and achieving improved navigation results. The semantic model of the indoor environment provides the robot with a representation that is closer to human perception, thereby enhancing the navigation task and human–robot interaction. However, semantic navigation systems require the utilization of multiple components, including geometry-based and vision-based systems. This paper presents a comprehensive review and critical analysis of recently developed robot semantic navigation systems in the context of their applications for semantic robot navigation in indoor environments. Additionally, we propose a set of evaluation metrics that can be considered to assess the efficiency of any robot semantic navigation system. Full article

Smart parking is an artificial intelligence-based solution to solve the challenges of inefficient utilization of parking slots, wasting time, congestion producing high CO₂ emission levels, inflexible payment methods, and protecting parked vehicles from theft and vandalism. Nothing is worse than parking congestion caused by drivers looking for open spaces. This is common in large parking lots, underground garages, and multi-story car parks, where visibility is limited and signage can be confusing or difficult to read, so drivers have no idea where available parking spaces are. In this paper, a smart real-time parking management system has been introduced. The developed system can deal with the aforementioned challenges by providing dynamic allocation for parking slots while taking into consideration the overall parking situation, providing a mechanism for booking a specific parking slot by using our Artificial Intelligence (AI)-based application, and providing a mechanism to ensure that the car is parked in its correct place. For the sake of providing cost flexibility, we have provided two technical solutions with cost varying. The first solution is developed based on a motion sensor and the second solution is based on a range-finder sensor. A plate detection and recognition system has been used to detect the vehicle’s license plate by capturing the image using an IoT device. The system will recognize the extracted English alphabet and Hindu-Arabic Numerals. The proposed solution was built and field-tested to prove the applicability of the proposed smart parking solution. We have measured and analyzed keen data such as vehicle plate detection accuracy, vehicle plate recognition accuracy, transmission delay time, and processing delay time. Full article

The Hawaiian Islands are renowned for their exceptional biodiversity and are host to a plethora of endemic plant species, which have been utilized in traditional Hawaiian medicine. This scientific review provides an in-depth analysis of the phytochemistry and biological studies of selected endemic Hawaiian plants, highlighting their medicinal properties and therapeutic potential. A literature search was conducted, utilizing major academic databases such as SciFinder, Scopus, Web of Science, PubMed, Google Scholar, Science Direct, and the Scientific Information Database. The primary objective of this search was to identify relevant scholarly articles pertaining to the topic of the review, which focused on the phytochemistry and biological studies of endemic Hawaiian plants. Utilizing these databases, a comprehensive range of literature was obtained, facilitating a comprehensive examination of the subject matter. This review emphasizes the rich phytochemical diversity and biological activities found in Endemic Hawaiian plants, showcasing their potential as sources of novel therapeutic agents. Given the unique biodiversity of Hawaii and the cultural significance of these plants, continued scientific exploration, conservation, and sustainable utilization of these valuable resources is necessary to unlock the full potential of these plant species in drug discovery and natural product-based therapeutics. Full article