Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management. Full article

To ensure the security of sensitive data, elliptic curve cryptography (ECC) is adopted as an asymmetric method that balances security and efficiency. Nevertheless, embedding messages into elliptic curve (EC) points poses a significant challenge. The intricacies of this process can greatly affect the overall security and efficiency of the cryptosystem, reflecting security vulnerabilities observed in many existing schemes that utilize ElGamal ECC-based encryption. In this paper, we introduce an innovative hash-based technique for securely embedding messages into EC points before encryption. A random parameter and a shared secret point generated through the EC Diffie–Hellman protocol are used to bolster the scheme’s security. The security of the proposed method is evaluated against various attack models; moreover, the complexity, and sensitivity of the encryption scheme, as well as its inputs, are analyzed. The randomness assessment of the ciphertext was performed using the NIST statistical test suite. Additionally, we propose a mechanism to ensure the integrity of the message by securely appending a tag to the ciphertext. As a consequence, a comprehensive analysis of our scheme demonstrates its effectiveness in maintaining data security and integrity against various attack models. The algorithm also meets more criteria such as the strict avalanche criterion, linear complexity, and operability. Full article

Fused Deposition Modeling (FDM) is a well-established manufacturing method for producing both prototype and functional components. This study investigates the mechanical properties of FDM components by material and process-related influencing variables. Tensile tests were conducted on seven different materials in their raw filament form, two of which were fiber-reinforced, to analyze their material-related influence. To cover a wide range from standard to advanced materials relevant for load-carrying components as well as their respective variations, polylactic acid (PLA), 30% wood-fiber-reinforced PLA, acrylonitrile butadiene styrene (ABS), polycarbonate (PC), a blend of ABS and PC, Nylon, and 30% glass-fiber-reinforced Nylon were selected. The process-related influencing variables were studied using the following process parameters: layer thickness, nozzle diameter, build orientation, nozzle temperature, infill density and pattern, and raster angle. The first test series revealed that the addition of wood fibers significantly worsened the mechanical behavior of PLA due to the lack of fiber bonding to the matrix and significant pore formation. The polymer blend of ABS and PC only showed improvements in stiffness. Significant strength and stiffness improvements were found by embedding glass fibers in Nylon, despite partially poor fiber–matrix bonding. The materials with the best properties were selected for the process parameter analysis. When examining the impact of layer thickness on part strength, a clear correlation was evident. Smaller layer thicknesses resulted in higher strength, while stiffness did not appear to be affected. Conversely, larger nozzle diameters and lower nozzle temperatures only positively impacted stiffness, with little effect on strength. The part orientation did alter the fracture behavior of the test specimens. Although an on-edge orientation resulted in higher stiffness, it failed at lower stresses. Higher infill densities and infill patterns aligned with the load direction led to the best mechanical results. The raster angle had a significant impact on the behavior of the printed bodies. An alternating raster angle resulted in lower strengths and stiffness compared to a unidirectional raster angle. However, it also caused significant stretching due to the rotation of the beads. Full article

This paper examines the impact and implications of ChatGPT and other generative AI technologies within the African context while looking at the ethical benefits and concerns that are particularly pertinent to the continent. Through a robust analysis of ChatGPT and other generative AI systems using established approaches for analysing the ethics of emerging technologies, this paper provides unique ethical benefits and concerns for these systems in the African context. This analysis combined approaches such as anticipatory technology ethics (ATE), ethical impact assessment (EIA), and ethical issues of emerging ICT applications with AI (ETICA) with specific issues from the literature. The findings show that ChatGPT and other generative AI systems raise unique ethical concerns such as bias, intergenerational justice, exploitation of labour and cultural diversity in Africa but also have significant ethical benefits. These ethical concerns and benefits are considered crucial in shaping the design and deployment of ChatGPT and similar technologies responsibly. It further explores the potential applications of ChatGPT in critical domain areas such as education, agriculture, and healthcare, thereby demonstrating the transformative possibilities that these technologies can have on Africa. This paper underscores the critical role of AI governance as Africa increasingly adopts ChatGPT and similar AI systems. It argues that a comprehensive understanding of AI governance is essential not only for maximising the benefits of generative AI systems but also for facilitating a global dialogue. This dialogue aims to foster shared knowledge and insights between the Global North and the Global South, which is important for the development and creation of inclusive and equitable AI policies and practices that can be beneficial for all regions. Full article

The aim of this study was to obtain films based on sodium alginate (SA) for disintegration in the oral cavity. The films were prepared with a solvent-casting method, and meloxicam (MLX) as the active ingredient was suspended in a 3% sodium alginate solution. Two different solid-dosage-form additives containing different disintegrating agents, i.e., VIVAPUR 112^® (MCC; JRS Pharma, Rosenberg, Germany) and Prosolve EASYtabs SP^® (MIX; JRS Pharma, Rosenberg, Germany), were used, and four different combinations of drying time and temperature were tested. The influence of the used disintegrant on the properties of the ODFs (orodispersible films) was investigated. The obtained films were studied for their appearance, elasticity, mass uniformity, water content, meloxicam content and, finally, disintegration time, which was studied using two different methods. The films obtained with the solvent-casting method were flexible and homogeneous in terms of MLX content. Elasticity was slightly better when MIX was used as a disintegrating agent. However, these samples also revealed worse uniformity and mechanical durability. It was concluded that the best properties of the films were achieved using the mildest drying conditions. The type of the disintegrating agent had no effect on the amount of water remaining in the film after drying. The water content depended on the drying conditions. The disintegration time was not affected by the disintegrant type, but some differences were observed when various drying conditions were applied. However, regardless of the formulation type and manufacturing conditions, the analyzed films could not be classified as fast disintegrating films, as the disintegration time exceeded 30 s in all of the tested formulations. Full article

Reliable testing of aviation components depends on the quality and configuration flexibility of measurement systems. In a typical approach to test instrumentation, there are tens or hundreds of sensors on the test head and test facility, which are connected by wires to measurement cards in control cabinets. The preparation of wiring and the setup of measurement systems are laborious tasks requiring diligence. The use of smart wireless transducers allows for a new approach to test preparation by reducing the number of wires. Moreover, additional functionalities like data processing, alarm-level monitoring, compensation, or self-diagnosis could improve the functionality and accuracy of measurement systems. A combination of low power consumption, wireless communication, and wireless power transfer could speed up the test-rig instrumentation process and bring new test possibilities, e.g., long-term testing of moving or rotating components. This paper presents the design of a wireless smart transducer dedicated for use with sensors typical of aviation laboratories such as thermocouples, RTDs (Resistance Temperature Detectors), strain gauges, and voltage output integrated sensors. The following sections present various design requirements, proposed technical solutions, a study of battery and wireless power supply possibilities, assembly, and test results. All presented tests were carried out in the Components Test Laboratory located at the Łukasiewicz Research Network–Institute of Aviation. Full article

The Mediterranean diet (MD) and Western diet (WD) are poles apart as dietary patterns. Despite the availability of epidemiological tools to estimate the adherence to MD, to date, there is a lack of combined scores. We developed MEDOC, a food frequency questionnaire (FFQ) designed to calculate a combined adherence score for both diets and validated it on 213 subjects. The test–retest reliability revealed all frequency questions falling within the acceptable range of 0.5 to 0.7 (Pearson correlation coefficient) in younger (<30 years old) subjects, while 1 question out of 39 fell below the range in older (>30 years old) participants. The reproducibility for portion size was less satisfying, with, respectively, 38.2% and 70.5% of questions falling below 0.5 (Cohen’s Kappa index) for younger and older subjects. The good correlation (R = 0.63, p < 0.0001 for subjects younger than 30 years and R = 0.54, p < 0.0001 for subjects older than 30 years, Pearson’s correlation coefficient) between the MEDOC score and the MediDietScore (MDS) confirmed the validity of the MEDOC score in identifying patients who adhere to the MD. Harnessing the capabilities of this innovative tool, we aim to broaden the existing perspective to study complex dietary patterns in nutritional epidemiology studies. Full article

The establishment of net-zero-energy and net-zero-carbon buildings can offer significant opportunities to reduce environmental impact in the building sector. Several successful net-zero-energy buildings highlight the feasibility of reducing energy consumption via energy-efficient strategies and the use of renewable energy technologies. To comprehend the existing innovatory designs, techniques, and practices employed to achieve net-zero-energy buildings, this research aims to review the up-to-date advancements in net-zero-energy building practices. The utilization of embodied carbon assessments to achieve the net-zero status of buildings is explored. The findings indicate an escalating global interest and participation in the field of study, and reveal three major areas related to net-zero-energy buildings: multidisciplinary approaches, energy systems, and guidance, which together cover thirteen subfields. The role of life cycle assessment in buildings is emphasized, offering insights into the role of embodied emissions relative to operational emissions over the entire life cycle of a building. In the end, possible future study directions are outlined, including balancing energy efficiency with sustainability, and assessing the impact of design on emissions and economic outcomes. These areas collectively contribute to transforming sustainable building concepts into reality. Full article

In this study, we explored the resilience of a clubroot resistance (CR) stacking model against a field population of Plasmodiophora brassicae pathotype 3H. This contrasts with our earlier work, where stacking CRaM and Crr1rutb proved only moderately resistant to pathotype X. Canola varieties carrying Rcr1/Crr1^rutb and Rcr1 + Crr1^rutb were repeatedly exposed to 3H at low (1 × 10⁴/g soil) and high (1 × 10⁷/g soil) initial resting spore concentrations over five planting cycles under controlled environments to mimic intensive canola production. Initially, all resistant varieties showed strong resistance. However, there was a gradual decline in resistance over time for varieties carrying only a single CR gene, particularly with Crr1^rutb alone and at the high inoculum level, where the disease severity index (DSI) increased from 9% to 39% over five planting cycles. This suggests the presence of virulent pathotypes at initially low levels in the 3H inoculum. In contrast, the variety with stacked CR genes remained resilient, with DSI staying below 3% throughout, even at the high inoculum level. Furthermore, the use of resistant varieties, carrying either a single or stacked CR genes, reduced the total resting spore numbers in soil over time, while the inoculum level either increased or remained high in soils where susceptible Westar was continuously grown. Our study demonstrates greater resistance resilience for stacking Rcr1 and Crr1^rutb against the field population of 3H. Additionally, the results suggest that resistance may persist even longer in fields with lower levels of inoculum, highlighting the value of extended crop rotation (reducing inoculum) alongside strategic CR-gene deployment to maximize resistance resilience. Full article

This study investigated the influence of microstructure on the performance of Ag inkjet-printed, resistive temperature detectors (RTDs) fabricated using particle-free inks based on a silver nitrate (AgNO₃) precursor and ethylene glycol as the ink solvent. Specifically, the temperature coefficient of resistance (TCR) and sensitivity for sensors printed using inks that use monoethylene glycol (mono-EG), diethylene glycol (di-EG), and triethylene glycol (tri-EG) and subjected to a low-pressure argon (Ar) plasma after printing were investigated. Scanning electron microscopy (SEM) confirmed previous findings that microstructure is strongly influenced by the ink solvent, with mono-EG inks producing dense structures, while di- and tri-EG inks produce porous structures, with tri-EG inks yielding the most porous structures. RTD testing revealed that sensors printed using mono-EG ink exhibited the highest TCR (1.7 × 10⁻³/°C), followed by di-EG ink (8.2 × 10⁻⁴/°C) and tri-EG ink (7.2 × 10⁻⁴/°C). These findings indicate that porosity exhibits a strong negative influence on TCR. Sensitivity was not strongly influenced by microstructure but rather by the resistance of RTD. The highest sensitivity (0.84 Ω/°C) was observed for an RTD printed using mono-EG ink but not under plasma exposure conditions that yield the highest TCR. Full article

Traditional container orchestration platforms often suffer from resource wastage in educational settings, and stateless serverless services face challenges in maintaining container state persistence during the teaching process. To address these issues, we propose a stateful serverless mechanism based on Containerd and Kubernetes, focusing on optimizing the startup process for container groups. We first implement a checkpoint/restore framework for container states, providing fundamental support for managing stateful containers. Building on this foundation, we propose the concept of “container groups” to address the challenges in educational practice scenarios characterized by a large number of similar containers on the same node. We then propose the Rofuse optimization mechanism, which employs delayed loading and block-level deduplication techniques. This enables containers within the same group to reuse locally cached file system data at the block level, thus reducing container restart latency. Experimental results demonstrate that our stateful serverless mechanism can run smoothly in typical educational practice scenarios, and Rofuse reduces the container restart time by approximately 50% compared to existing solutions. This research provides valuable exploration for serverless practices in the education domain, contributing new perspectives and methods to improve resource utilization efficiency and flexibility in teaching environments. Full article

The study aimed to evaluate the effect of storage temperature on quality changes in freeze-dried carrot–orange–ginger (COG) snacks obtained with 2% of apple (AP) or blackcurrant (BP) pomace powder or 1.5% of pectin (LMP). The material was stored at 4, 25 and 40 °C for 1, 3, 6 and 12 months in pouches impermeable to vapour, oxygen and light. Water content and activity, texture, colour, total polyphenol content and antioxidant activity were examined to evaluate the products’ quality. During storage, water content and activity fluctuations were noted, but no critical values were exceeded. Texture properties remained stable in snacks with pomace powders compared to those with pectin, the hardness of which significantly decreased when stored at ambient and elevated temperatures. However, the product with pectin was found to change colour the least over time. The results obtained for chemical properties were not clear, but they strongly indicated the occurrence of the transformation of some chemical compounds. Overall, a lowered temperature helped to maintain the quality of the freeze-dried snacks for the longest time. The presented research contributes to the general knowledge of the behaviour of innovative products with the addition of nonconventional but sustainable compounds, revealing the potential for quality and stability improvements. Full article

Small molecules are significant risk factors for causing food safety issues, posing serious threats to human health. Sensitive screening for hazards is beneficial for enhancing public security. However, traditional detection methods are unable to meet the requirements for the field screening of small molecules. Therefore, it is necessary to develop applicable methods with high levels of sensitivity and specificity to identify the small molecules. Aptamers are short−chain nucleic acids that can specifically bind to small molecules. By utilizing aptamers to enhance the performance of recognition technology, it is possible to achieve high selectivity and sensitivity levels when detecting small molecules. There have been several varieties of aptamer target recognition techniques developed to improve the ability to detect small molecules in recent years. This review focuses on the principles of detection platforms, classifies the conjugating methods between small molecules and aptamers, summarizes advancements in aptamer−based conjugate recognition techniques for the detection of small molecules in food, and seeks to provide emerging powerful tools in the field of point−of−care diagnostics. Full article

Mitochondria-targeted antioxidants (MTAs) have been studied quite intensively in recent years as potential therapeutic agents and vectors for the delivery of other active substances to mitochondria and bacteria. Their most studied representatives are MitoQ and SkQ1, with its fluorescent rhodamine analog SkQR1, a decyl ester of rhodamine 19 carrying plastoquinone. In the present work, we observed a pronounced antibacterial action of SkQR1 against Gram-positive bacteria, but virtually no effect on Gram-negative bacteria. The MDR pump AcrAB-TolC, known to expel SkQ1, did not recognize and did not pump out SkQR1 and dodecyl ester of rhodamine 19 (C12R1). Rhodamine 19 butyl (C4R1) and ethyl (C2R1) esters more effectively suppressed the growth of ΔtolC Escherichia coli, but lost their potency with the wild-type E. coli pumping them out. The mechanism of the antibacterial action of SkQR1 may differ from that of SkQ1. The rhodamine derivatives also proved to be effective antibacterial agents against various Gram-positive species, including Staphylococcus aureus and Mycobacterium smegmatis. By using fluorescence correlation spectroscopy and fluorescence microscopy, SkQR1 was shown to accumulate in the bacterial membrane. Thus, the presentation of SkQR1 as a fluorescent analogue of SkQ1 and its use for visualization should be performed with caution. Full article

In this work, the dynamics of a quantum walker on glued trees is revisited to understand the influence of the architecture of the graph on the efficiency of the transfer between the two roots. Instead of considering regular binary trees, we focus our attention on leafier structures where each parent node could give rise to a larger number of children. Through extensive numerical simulations, we uncover a significant dependence of the transfer on the underlying graph architecture, particularly influenced by the branching rate (M) relative to the root degree (N). Our study reveals that the behavior of the walker is isomorphic to that of a particle moving on a finite-size chain. This chain exhibits defects that originate in the specific nature of both the roots and the leaves. Therefore, the energy spectrum of the chain showcases rich features, which lead to diverse regimes for the quantum-state transfer. Notably, the formation of quasi-degenerate localized states due to significant disparities between M and N triggers a localization process on the roots. Through analytical development, we demonstrate that these states play a crucial role in facilitating almost perfect quantum beats between the roots, thereby enhancing the transfer efficiency. Our findings offer valuable insights into the mechanisms governing quantum-state transfer on trees, with potential applications for the transfer of quantum information. Full article

In this paper, a variable-coefficient Davey–Stewartson (vcDS) system is investigated for modeling the evolution of a two-dimensional wave-packet on water of finite depth in inhomogeneous media or nonuniform boundaries, which is where its novelty lies. The Painlevé integrability is tested by the method of Weiss, Tabor, and Carnevale (WTC) with the simplified form of Krustal. The rational solutions are derived by the Hirota bilinear method, where the formulae of the solutions are represented in terms of determinants. Furthermore the fundamental rogue wave solutions are obtained under certain parameter restrains in rational solutions. Finally the physical characteristics of the influences of the coefficient parameters on the solutions are discussed graphically. These rogue wave solutions have comprehensive implications for two-dimensional surface water waves in the ocean. Full article

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices. Full article

The effects of inoculating lactic acid bacteria (LAB), specifically Lactiplantibacillus plantarum, Latilactobacillus sakei, Latilactobacillus curvatus, and Weissella hellenica on the flavor, texture, and color formation of dry sausages in which NaCl was partially substituted by 40% KCl, were explored in this study. It was found that LAB inoculation increased the presence of ketones, alcohols, acids, esters, and terpenes. It also reduced the pH, moisture, protein, and fat content, improving the b*-value, flavor, and texture of the sausages. Notably, L. sakei inoculation showed the most significant improvement in dry sausages with NaCl substitutes, especially on the reduction of bitterness. Meanwhile, there was a close positive correlation between the LAB count with the alcohols and esters formation of dry sausage with NaCl substitution (p < 0.05). These findings offer insight into improving the product characteristics of dry sausages using NaCl substitutes. Full article

Small object detection poses significant challenges in the realm of general object detection, primarily due to complex backgrounds and other instances interfering with the expression of features. This research introduces an uncomplicated and efficient algorithm that addresses the limitations of small object detection. Firstly, we propose an efficient cross-scale feature fusion attention module called ECFA, which effectively utilizes attention mechanisms to emphasize relevant features across adjacent scales and suppress irrelevant noise, tackling issues of feature redundancy and insufficient representation of small objects. Secondly, we design a highly efficient convolutional module named SEConv, which reduces computational redundancy while providing a multi-scale receptive field to improve feature learning. Additionally, we develop a novel dynamic focus sample weighting function called DFSLoss, which allows the model to focus on learning from both normal and challenging samples, effectively addressing the problem of imbalanced difficulty levels among samples. Moreover, we introduce Wise-IoU to address the impact of poor-quality examples on model convergence. We extensively conduct experiments on four publicly available datasets to showcase the exceptional performance of our method in comparison to state-of-the-art object detectors. Full article

This paper proposes a new static output feedback control method to address the congestion control problem in transmission control protocol networks using active queue management routers. Based on linear matrix inequality optimization, this method determines a static output feedback control law to minimize the norm of the transfer function between the controlled queue length of the buffer and the exogenous disturbance affecting the available link bandwidth. A linear matrix inequality formulation is presented as a sufficient condition to guarantee the closed-loop system’s asymptotic stability while maintaining disturbance rejection within a specified level, regardless of round-trip time delays. The proposed robust static output feedback control eliminates the need to measure or estimate all system states, thus simplifying practical implementation. The effectiveness of the proposed design method is demonstrated by applying it in a practical process, as illustrated through a numerical example. Full article

Pingliang City has a complex topography and diverse soil types. To realize the improvement of soil according to local conditions and the reasonable and sustainable use of soil resources, an evaluation of soil quality in Pingliang City was carried out, based on the soil distribution situation in Pingliang City, adopting a method combining fuzzy mathematics and cluster analysis of the main evaluation factors, such as soil organic matter, topsoil depth, soil erosion intensity, soil moisture regime, effective soil thickness, soil texture, soil profile structure, soil nutrient status and topographical parts, to carry out a comprehensive evaluation. A comprehensive evaluation of soil quality was conducted in seven counties under the jurisdiction of Pingliang City, and the evaluation results were compared and analyzed against the national standard, “Cultivated land quality grade”, to provide a basis for the selection of scientific soil improvement methods. The results of the arable land quality grades indicate that the quality of farmland in Pingliang City is divided into three to ten grades, and the average quality grade of farmland is 6.83, which is in the middle–lower level, and the overall grade distribution shows the characteristics of low in the middle and high in the east and west. The results of fuzzy mathematics combined with cluster analysis indicated the following trends in soil quality for the 12 soil genera: Chuan black gunny soil > yellow moist soil > sandy soil > silt soil > mulching helilu soil> loessal soil> loamy soil > slope loessal soil > arenosol > tillage leaching gray cinnamon soil > calcareous gray cinnamon soil > red clay soil. The results of the combination of fuzzy mathematics and clustering were significantly correlated with the results of the evaluation of the soil quality of arable land; the correlation coefficient was 0.884. This indicates that the method can accurately and objectively review the advantages and disadvantages of arable land soil and can be effectively applied to the evaluation of the soil quality of agricultural soils in other regions. It is a complement to the existing evaluation of the soil quality of arable land and at the same time provides a reference for the improvement of soil quality in agricultural regions. Full article

This paper explores the emerging subject of extracting tannins from various plant sources using deep eutectic solvents (DESs). Tannins are widely used in the food and feed industries as they have outstanding antioxidant qualities and greatly enhance the flavor and nutritional content of a wide range of food products. Organic solvents are frequently used in traditional extraction techniques, which raises questions about their safety for human health and the environment. DESs present a prospective substitute because of their low toxicity, adaptability, and environmental friendliness. The fundamental ideas supporting the application of DESs in the extraction of tannins from a range of plant-based materials frequently used in daily life are all well covered in this paper. Furthermore, this paper covers the impact of extraction parameters on the yield of extracted tannins, as well as possible obstacles and directions for future research in this emerging subject. This includes challenges such as high viscosity, intricated recovery of compounds, thermal degradation, and the occurrence of esterification. An extensive summary of the diversity, structure, biosynthesis, distribution, and roles of tannins in plants is given in this paper. Additionally, this paper thoroughly examines various bioactivities of tannins and their metabolites. Full article