Search Results (19)

Decision management is the systems engineering life cycle process for making program/system decisions. The purpose of the decision management process is: “…to provide a structured, analytical framework for objectively identifying, characterizing and evaluating a set of alternatives for a decision at any point in the life cycle and select the most beneficial course of action”. Systems engineers and systems analysts need to inform decisions in a digital engineering environment. This paper describes a Decision Analysis Data Model (DADM) developed in model-based systems engineering software to provide the process, methods, models, and data to support decision management. DADM can support digital engineering for waterfall, spiral, and agile development processes. This paper describes the decision management processes and provides the definition of the data elements. DADM is based on ISO/IEC/IEEE 15288, the INCOSE SE Handbook, the SE Body of Knowledge, the Data Management Body of Knowledge, systems engineering textbooks, and journal articles. The DADM was developed to establish a decision management process and data definitions that organizations and programs can tailor for their system life cycles and processes. The DADM can also be used to assess organizational processes and decision quality. Full article

Spiral fractures are a frequent clinical manifestation of child abuse, particularly in non-ambulatory infants. Approximately 50% of fractures in children under one year of age are non-accidental, yet differentiating between accidental and abusive injuries remains challenging, as no single fracture type is diagnostic in isolation. The objective of this study is to investigate the biomechanics of spiral fractures in immature long bones and the role of the periosteum in modulating fracture behavior under torsional loading. Methods: Paired metatarsal bone specimens from immature sheep were tested using controlled torsional loading at two angular velocities (90°/s and 180°/s). Specimens were prepared through potting, application of a base coat, and painting of a speckle pattern suitable for high-speed digital image correlation (HS-DIC) analysis. Both periosteum-intact and periosteum-removed groups were included. Results: Spiral fractures were successfully induced in over 85% of specimens. Digital image correlation revealed localized diagonal tensile strain at the fracture initiation site, with opposing compressive zones. Notably, bones with intact periosteum exhibited broader tensile stress regions before and after failure, suggesting a biomechanical role in constraining deformation. Conclusion: This study presents a novel integration of high-speed digital image correlation (DIC) with paired biomechanical testing to evaluate the periosteum’s role in spiral fracture formation—an area that remains underexplored. The findings offer new insight into the strain distribution dynamics in immature long bones and highlight the periosteum’s potential protective contribution under torsional stress. Full article

Understanding the dynamics of public opinion formation in digital environments is crucial for managing technological communications effectively. This study investigates stance interactions and opinion reversal phenomena in technical discourse through analysis of the Manus AI controversy that generated approximately 36,932 social media interactions during March 2025. Employing an integrated methodology combining Large Language Model (LLM)-enhanced stance detection with agent-based modeling (ABM), we reveal distinctive patterns challenging traditional public opinion theories. Our cross-correlation analysis identifies significant lagged interaction effects between skeptical and supportive stances, demonstrating how critical expressions trigger amplified counter-responses rather than inducing silence. Unlike prior conceptualizations of counter-silencing that emphasize ideological resistance or echo chambers, our notion of the “counter-spiral of silence” specifically highlights lagged emotional responses and reactive amplification triggered by minority expressions in digital technical discourse. We delineate its boundary conditions as arising under high emotional salience, asymmetrical expertise, and platform structures that enable real-time feedback. The agent-based simulation reproduces empirical patterns, revealing how emotional contagion and network clustering mechanisms generate “counter-spiral of silence” phenomena where challenges to dominant positions ultimately strengthen rather than weaken those positions. These findings illuminate how cognitive asymmetries between public expectations and industry realities create distinctive discourse patterns in technical contexts, offering insights for managing technology communication and predicting public response trajectories in rapidly evolving digital environments. Full article

In the European Green Deal and Renovation Wave framework, cities should be more self-sufficient and sustainable, promoting investment in the regeneration and maintenance of the built and natural heritage. The New European Bauhaus reinforces this vision, promoting the value of beauty as a product of environmental harmony/sustainability and participation. Many cities are already working to improve infrastructure and public services, with the aim of creating better socio-economic and environmental conditions in urbanised areas. At the same time, they aim to increase and relocate attractiveness and competitiveness to less densified rural areas, and to reduce overcrowding problems in cities. The aim is to propose a virtuous model of circular regeneration, by identifying virtuous strategies of the regeneration of rural villages capable of aligning the transformation of the built environment with climate objectives, social cohesion and local economy strengthening, and the integration of historical and identity values. Rural villages in marginal areas are left behind places. They require new economic development strategies, grounded in a circular bio-economy model for reducing/avoiding spiraled down processes. The application of European evaluation criteria to the main topic literature background allowed for the construction of a virtuous practices observatory about regenerated rural villages, which is elaborated using registry, systemic, and analytical/analysis forms. From the ex-post evaluation analysis of the case studies, it was possible to identify a number of dimensions/clusters in which investment is being made today for the regeneration of rural villages. By reasoning on the investment clusters, it was possible to identify a circular regeneration model for rural villages, transferable to other realities in order to implement the broader vision of circular settlement development. The “Rural Village Regeneration Model” represents an operational tool for regional transformation, suitable for reactivating lost connections between rural villages and larger towns in functional areas, characterised by greater self-sufficiency and exploration of the potential of digital tools to improve services, connections, infrastructure, and cooperation. Full article

As technology advances, so does digital farming, revolutionizing the industry. Drones, sprayers equipped with GPS and other sensors, combine harvesters, and other machinery can greatly improve agricultural productivity. This paper studies the impact of the straw baler screw conveyor on the efficiency of the baler. Via theoretical analysis, GA—BP (Genetic Algorithm—Back Propagation) simulation, and comparative experiments, the structural parameters and rotational speed of the spiral shaft in the screw conveying device are optimized. In this paper, we analyze the force and velocity components acting on the straw, give the design principles for the screw’s conveying parameters under the premise of ensuring maximum conveying capacity and minimum power consumption, and determine the optimal design variables, objective functions, and constraints according to the specific optimization problem; we establish a specific mathematical model, and introduce algorithm optimization for nonlinear problems with many variables and large amounts of calculations. In MATLAB, an optimization calculation and analysis were performed. The optimization results of the traditional BP (Back Propagation) and GA—BP were compared. It was proven that GA—BP could effectively compensate for the deficiencies of the BP neural network and substantially enhance the model’s accuracy. Through an analysis of the optimization results, the conclusion of attaining the optimization objective was drawn. Specifically, when the outer diameter of the spiral for screw conveyance in the straw baler was $\mathrm{D}=320 \mathrm{mm}$, the pitch was $\mathrm{S}=200 \mathrm{mm}$, and the rotational speed of the pickup shaft was $n=138 r/\min$, the straw baler could achieve the maximum conveying capacity and the minimum power consumption. At this moment, the power consumption was $\mathrm{P}=0.079 \mathrm{kW}$, and the conveying capacity was ${\mathrm{Q}}_{\mathrm{m}}=23.98 \mathrm{t}/\mathrm{h}$. Subsequently, the optimization results were contrasted with those of other mainstream domestic models, and a comparative experiment was conducted. The experimental results indicated that the model’s prediction results were reliable and exhibited higher efficiency compared to other combinations. The results could provide a reference for the research on screw conveyance of balers. Full article

Polar ring galaxies (PRGs) are unusual relative to common galaxies in that they consist of a central host galaxy—usually a gas-poor, early-type S0 or elliptical galaxy—surrounded by a ring of gas, dust and stars that orbit perpendicular to the major axis of the host. Despite the general quiescence of early-type galaxies (ETGs) and the rings’ lack of spiral density waves, PRGs are the sites of significant star formation relative to typical ETGs. To study these structures and improve PRG statistics, we obtained and analyzed infrared (IR) images from the Infrared Array Camera (IRAC) aboard the Spitzer Space Telescope, and combined these IR data with archival optical data from both the Sloan Digital Sky Survey and the Hubble Space Telescope, and with optical imaging data we obtained with the Gemini South Observatory. We performed structural decomposition and photometry for five PRGs, and fit the spectral energy distributions (SEDs) of each PRG component to estimate the stellar masses, ages, and other physical properties of the PRG components. We show that PRC B-12 and PRC B-22, both lacking previous analysis, obey trends commonly observed among PRGs. We find that the stellar masses of polar rings can be a significant fraction of the host galaxy’s stellar masses (∼10–30%). We note, however, that our estimates of stellar mass and other physical properties are the results of SED fitting and not direct measurements. Our findings corroborate both previous theoretical expectations and measurements of existing samples of PRGs and indicate the utility of SED fitting in the context of these unusual galaxies, which historically have lacked multi-wavelength photometry of their stellar components. Finally, we outline future improvements needed for more definitive studies of PRGs and their formation scenarios. Full article

Recently, the analysis of emotions in social media has been considered a significant NLP task in digital and social-media-driven environments due to their pervasive influence on communication, culture, and consumer behavior. In particular, the task of Aspect-Based Emotion Analysis (ABEA), which involves analyzing the emotions of various targets within a single sentence, has drawn attention to understanding complex and sophisticated human language. However, ABEA is a challenging task in languages with limited data and complex linguistic properties, such as Korean, which follows spiral thought patterns and has agglutinative characteristics. Therefore, we propose a Korean Target-Attention-Based Emotion Classifier (KOTAC) designed to utilize target information by unveiling emotions buried within intricate Korean language patterns. In the experiment section, we compare various methods of utilizing and representing vectors of target information for the attention mechanism. Specifically, our final model, KOTAC, shows a performance enhancement on the MTME (Multiple Targets Multiple Emotions) samples, which include multiple targets and distinct emotions within a single sentence, achieving a 0.72% increase in F1 score over a baseline model without effective target utilization. This research contributes to the development of Korean language models that better reflect syntactic features by innovating methods to not only obtain but also utilize target-focused representations. Full article

A novel approach for the fracture characterization of soft adhesive materials using spiral cracking patterns is presented in this study. This research particularly focuses on hydrocarbon polymeric materials, such as asphalt binders. Ten different asphalt materials with distinct fracture characteristics were investigated. An innovative integrated experimental–computational framework coupling acoustic emissions (AE) approach in conjunction with a machine learning-based Digital Image Analysis (DIA) method was employed to precisely determine the crack geometry and characterize the material fracture behavior. Cylindrical-shaped samples (25 mm in diameter and 20 mm in height) bonded to a rigid substrate were employed as the testing specimens. A cooling rate of −1 °C/min was applied to produce the spiral cracks. Various image processing techniques and machine learning algorithms such as Convolutional Neural Networks (CNNs) and regression were utilized in the DIA to automatically analyze the spiral patterns. A new parameter, “Spiral Cracking Energy (E_Spiral)”, was introduced to assess the fracture performance of soft adhesives. The compact tension (CT) test was conducted at −20 °C with a loading rate of 0.2 mm/min to determine the material’s fracture energy (G_f). The embrittlement temperature (T_EMB) of the material was measured by performing an AE test. This study explored the relationship between the spiral tightness parameter (“b”), E_Spiral, G_f, and T_EMB of the material. The findings of this study showed a strong positive correlation between the E_Spiral and fracture energies of the asphalt materials. Furthermore, the results indicated that both the spiral tightness parameter (“b”) and the embrittlement temperature (T_EMB) were negatively correlated with the E_Spiral and G_f parameters. Full article

Image encryption based on chaotic maps is an important method for ensuring the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed that employs a compound chaotic map and random cyclic shift. First, a new hybrid chaotic system is designed by coupling logistic, ICMIC, Tent, and Chebyshev (HLITC) maps. Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and approximate entropy illustrate that the new hybrid chaotic map has better chaotic performance. Then, the proposed HLITC chaotic system and spiral transformation are used to develop a new chaotic image encryption scheme using the double permutation strategy. The new HLITC chaotic system is used to generate key sequences used in the image scrambling and diffusion stages. The spiral transformation controlled by the chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments on statistical analysis, key sensitivity, and key space analysis were conducted. Experimental results show that the proposed encryption scheme has good robustness against brute-force attacks, statistical attacks, and differential attacks and is more effective than many existing chaotic image encryption algorithms. Full article

Background: The scientific literature was reviewed to determine the state of the art regarding innovative educational practices that employ mobile health applications with the aim of establishing healthy habits in the adolescent population, following a strategy based on spiral curriculum. Methods: The search was conducted in the WOS, Scopus and PubMed databases, discarding any articles that were not published in English, Spanish or French. The search was limited to studies performed in the last 6 years, that is, from 1 January 2017 to 18 March 2023. Results: From the initial sample of 132 articles selected, the final sample included 9 articles that met the eligibility criteria after a more exhaustive analysis. This systematic review identified one application (11.11%) with topics about sex and reproductive health, two applications (22.22%) that tackled mental health, six applications (66.66%) with topics about nutrition, three applications (33.33%) that contemplate physical activity, and two applications (22.22%) with aspects related to the prevention of harmful habits. The results show a positive relationship between the use of mobile health applications used as innovative didactic resources and the establishment of healthy habits in the adolescent population. Conclusions: Digital devices have been incorporated to the lives of humans as fundamental tools for their daily living. Specifically, adolescents are especially attracted to mobile phones. If this resource is used in this population to improve health, it is possible to attain very satisfactory objectives. The results of this review indicate that these devices can be used as a didactic resource in the promotion of health by implementing healthy habits at early ages, thereby contributing to the prevention of chronic diseases in future adulthood. Full article

Leveraging low-cost drone technology, specifically the DJI Mini 2, this study presents an innovative method for creating accurate, high-resolution digital surface models (DSMs) to enhance topographic mapping with off-the-shelf components. Our research, conducted near Jena, Germany, introduces two novel flight designs, the “spiral” and “loop” flight designs, devised to mitigate common challenges in structure from motion workflows, such as systematic doming and bowling effects. The analysis, based on height difference products with a lidar-based reference, and curvature estimates, revealed that “loop” and “spiral” flight patterns were successful in substantially reducing these systematic errors. It was observed that the novel flight designs resulted in DSMs with lower curvature values compared to the simple nadir or oblique flight patterns, indicating a significant reduction in distortions. The results imply that the adoption of novel flight designs can lead to substantial improvements in DSM quality, while facilitating shorter flight times and lower computational needs. This work underscores the potential of consumer-grade unoccupied aerial vehicle hardware for scientific applications, especially in remote sensing tasks. Full article

Loop-mediated isothermal amplification (LAMP) is a rapid and high-yield amplification technology for specific DNA or RNA molecules. In this study, we designed a digital loop-mediated isothermal amplification (digital-LAMP)-functioning microfluidic chip to achieve higher sensitivity for detection of nucleic acids. The chip could generate droplets and collect them, based on which we could perform Digital-LAMP. The reaction only took 40 min at a constant temperature of 63 °C. The chip enabled highly accurate quantitative detection, with the limit of detection (LOD) down to 10² copies μL⁻¹. For better performance while reducing the investment of money and time in chip structure iterations, we used COMSOL Multiphysics to simulate different droplet generation ways by including flow-focusing structure and T-junction structure. Moreover, the linear structure, serpentine structure, and spiral structure in the microfluidic chip were compared to study the fluid velocity and pressure distribution. The simulations provided a basis for chip structure design while facilitating chip structure optimization. The digital-LAMP-functioning chip proposed in the work provides a universal platform for analysis of viruses. Full article

This study aimed to isolate and characterize Treponema spp. from bovine digital dermatitis (BDD)-infected dairy cattle. Seven isolates were characterized in this study. Isolates exhibited slow growth, and colonies penetrated the agar and exhibited weak β-hemolysis. Round bodies were observed in old and antibiotic-treated cultures. Cells ranged from 9–12 µm in length, 0.2–2.5 µm in width, and were moderately spiraled. The 16S rRNA analysis revealed the isolates as Treponema phagedenis with >99% sequence homology. Isolates had alkaline phosphatase, acid phosphatase, β-galactosidase, N-acetyl-β-glucosaminidase, esterase (C4), esterase lipase (C8), naphthol-AS-BI-phosphohydrolase, and β-glucuronidase activities. Low concentrations of ampicillin, erythromycin, and tetracycline were required to inhibit the growth of isolates. Formic, acetic, and butyric acids were produced, while propionic acid was significantly utilized, indicating its essentiality for treponemal growth. The isolates shared the same characteristics and, therefore, were considered as a single strain. Isolate HNL4 was deposited as a representative isolate (Treponema phagedenis KS1). The average nucleotide identity of strain KS1 showed a small difference with the human strain (99.14%) compared with bovine strain (99.72%). This study was the first to isolate and characterize Treponema phagedenis from BDD in Korea and, hence, it delivered pathogenicity-related insights and provided valuable information that can be used for the management of BDD. Full article

The simultaneous and independent measurements of two-dimensional (2D) displacements are significant for 2D positioning. Here a planar inductive sensor which is based on the principle of electromagnetic induction is proposed. The sensor is composed of a primary coil and a secondary coil. The primary coil consists of an array of planar spiral coils which are arranged as an m × n matrix. The primary coil is supplied with 4 kHz alternating current to generate an array of pulsating magnetic field. The secondary coil contains four spiral coils which are arranged as a 2 × 2 matrix. Thereby, four roads of modulated signals whose amplitudes vary with displacements of the secondary coil along x- and y-axis are induced. An algorithm based on the Coordinate Rotation Digital Computer algorithm is introduced to resolve the planar displacements. The structure and working principle of the sensor are proposed firstly. Then, the finite element analysis of the electromagnetic model and the numerical simulation of the algorithm are given. An experiment has been performed on a sensor prototype and the results show that the proposed scheme is feasible. Measurement error analysis of the sensor has been pursued at the end of the paper. Full article

Nowadays, an important research effort in healthcare biometrics is finding accurate biomarkers that allow developing medical-decision support tools. These tools help to detect and supervise illnesses like Parkinson’s disease (PD). This paper contributes to this effort by analyzing a convolutional neural network (CNN) for PD detection from drawing movements. This CNN includes two parts: feature extraction (convolutional layers) and classification (fully connected layers). The inputs to the CNN are the module of the Fast Fourier’s transform in the range of frequencies between 0 Hz and 25 Hz. We analyzed the discrimination capability of different directions during drawing movements obtaining the best results for X and Y directions. This analysis was performed using a public dataset: Parkinson Disease Spiral Drawings Using Digitized Graphics Tablet dataset. The best results obtained in this work showed an accuracy of 96.5%, a F1-score of 97.7%, and an area under the curve of 99.2%. Full article