Search Results (243)

The Automatic Identification System (AIS) is a maritime radio system that regularly broadcasts vessel data, such as the vessel’s identification, position, course and speed. For modulation, the AIS standard defines Gaussian minimum shift keying (GMSK) as an easy to implement modulation scheme with constant envelope, meaning that a GMSK complex baseband signal carries information solely in its phase. AIS does not use any forward error correction (FEC) mechanism. In this paper we propose to extend GMSK with amplitude modulation, leading to multi-amplitude Gaussian minimum shift keying (MA-GMSK). The additional modulation of the amplitude increases the spectral efficiency so that additional information, i.e., additional bits can be transmitted. We use the increased spectral efficiency to implement FEC, where we transmit the redundancy bits of a systematic channel code via the additional amplitude modulation in the proposed MA-GMSK scheme. With this approach, the proposed MA-GMSK signal can be processed by off-the-shelf AIS receivers, thus demonstrating empirical standard compatibility with the tested receivers. Based on simulations and experimental results, we propose a suitable MA-GMSK modulation parameter setting and evaluate the packet error rate (PER) performance accordingly. To verify standard compatibility, we examine the performance of commercially available AIS receivers fed with MA-GMSK signals. Using the proposed modulation and coding scheme, an advanced MA-GMSK receiver including FEC provides performance improvements up to 3 dB in the required signal-to-noise ratio (SNR) compared to state-of-the art AIS using uncoded GMSK. Full article

Emergency responders face a high risk of musculoskeletal disorders (MSDs), particularly lower back injuries, due to frequent patient-handling tasks performed in awkward and dynamic postures. This aim of study is to utilize dual motion capture systems integrated with a digital human modeling (DHM) ergonomics tool to evaluate the biomechanical effects of two common two-person carrying techniques: facing forward and facing each other. Twenty-two participants lifted a 25 kg mannequin while wearing Xsens motion sensors, and lumbar forces and joint angles were analyzed using Siemens Jack software (v9.0). Peak compressive and anterior–posterior (AP) shear forces, along with trunk, hip, and knee joint angles, were examined. Compressive forces ranged from approximately 948.6 to 2955.6 N, and AP shear forces ranged from 286.0 to 827.0 N. Mean compressive and AP shear forces were higher during the facing-each-other task (1977.3 N and 595.0 N) than during the facing-forward task (1596.0 N and 462.0 N). Males experienced higher spinal loads than females across both tasks. The facing-each-other technique was associated with greater hip flexion, lower knee flexion, and reduced trunk flexion, whereas the facing-forward technique resulted in less hip flexion, greater knee flexion, and greater trunk flexion. Overall, under the conditions of the present study, the facing-forward technique was associated with lower lumbar loading indicators. Integrating motion capture with DHM offers a valuable approach for evaluating realistic rescue tasks and can inform ergonomic training strategies for emergency responders. Full article

Snakebite envenoming causes an estimated 138,000 deaths annually worldwide, with approximately 75% of fatalities occurring prior to arrival at definitive medical care. Even in regions where antivenom is available in hospitals, the absence of treatment options before a victim can reach definitive care results in delays of many hours before therapy is initiated. Manufacturing complexity, region-specific products, and the risk of anaphylaxis further limit the availability and use of antivenom in many regions. Reducing the persistently high mortality of snakebite envenoming requires both novel scientific approaches and partnerships that extend beyond traditional disciplinary and funding silos. This article describes the collaboration between Ophirex, a Public Benefit Corporation developing the oral secretory phospholipase A2 (sPLA2) inhibitor varespladib, and the United States military, which has identified a capability gap in snakebite treatment for forward-deployed personnel. The partnership was driven by a shared requirement for a shelf-stable, easy-to-administer, snake-species-agnostic therapy suitable for use prior to definitive medical care. A central insight of the program was that military operational requirements and global public health needs converged around the same product characteristics, enabling a strategically aligned development effort. From early proof-of-concept studies through regulatory pathway definition and advanced development, the Military–Ophirex partnership integrated operational requirements, regulatory planning, and iterative risk mitigation to advance manufacturing, nonclinical, and clinical development. This work provides both practical insights into complex drug development and a case study in how structured partnerships can carry innovation through translation in underfunded and operationally challenging conditions. Full article

Structural Equation Modeling (SEM) is a key framework for analyzing complex economic relationships involving latent variables, mediation effects, and endogeneity, yet the choice between frequentist and Bayesian estimation remains theoretically and practically contested, especially in settings with non-stationary data and small samples. This study provides a formal comparison of the two approaches by formulating SEM as a probabilistic graphical model and deriving the corresponding estimation procedures, identifiability conditions, and uncertainty measures. We examine asymptotic properties of frequentist estimators and posterior consistency in Bayesian SEM, with particular attention to integrated time-series SEM applications such as shadow economy estimation. The analysis shows that while both approaches converge under large-sample conditions, important differences arise in finite samples. Bayesian methods exhibit more stable point estimates through coherent uncertainty quantification, particularly when prior information regularizes an otherwise ill-conditioned likelihood. Under model misspecification, Bayesian posteriors concentrate around the pseudo-true parameter defined by the Kullback-Leibler projection, providing a probabilistic representation of misspecification uncertainty through posterior spread—an advantage over frequentist inference, which typically conditions on the maintained model as exact. These findings carry direct implications for empirical economic modeling under realistic data constraints. In settings where sample sizes are small, identification is weak, and model uncertainty is substantial, conditions that routinely characterize macroeconomic research, the choice of inferential framework is not a matter of philosophical preference but a determinant of whether policy-relevant conclusions can be credibly defended. Bayesian SEM offers a principled and transparent path forward in precisely these conditions. Full article

Taking Dachen Village in Jiangshan, Zhejiang Province, as an example, this paper discusses the application of digital intelligence technology innovation in the protection of rural cultural architectural heritage. After reviewing the relevant literature on the digital protection of traditional village cultural heritage, this research applied new technologies, such as big data screening and computer clusters, to develop a visual digital intelligence display platform for Dachen Village. The research results show the innovation, experience, and interactivity of digital intelligence technology. This research proposes the use of digital intelligent classification preservation, digital museum construction, and the intelligent development of planning circle websites to protect rural cultural heritage effectively. This paper addresses four core academic gaps in the current research on the “digital-intelligent preservation of traditional villages”: fragmented technological applications, lack of public participation, separation of tangible and intangible heritage, and the absence of replicable models. It proposes a “low-threshold, full-process, replicable” digital-intelligent preservation approach, providing dual reference for both theoretical and practical aspects in subsequent research. It also calls for public participation in jointly inheriting and carrying forward the treasures of human historical civilization. Full article

The aim of this research is to formulate and analyze a modified $S{I}_{p}IVR$ mathematical model to study the transmission dynamics of poliovirus and assess the impact of vaccination on disease control. The proposed model extends classical SEIV-type frameworks by incorporating a recovered compartment with long-term immunity and by replacing the traditional exposed class with a pre-infectious compartment ($I_p$) that captures silent viral shedding during the incubation phase of poliovirus. This modification addresses the critical epidemiological feature that individuals can transmit the virus before showing symptoms while maintaining biological accuracy in compartment definition. Several fundamental analytical properties are rigorously established, including positivity, boundedness, and the existence of a biologically meaningful invariant region. The basic reproduction number $R_0$ is derived using the next-generation matrix approach, and comprehensive stability analysis is carried out. The analysis shows that the DFE is locally and globally asymptotically stable whenever $R_0<1$. Using center manifold theory, a forward bifurcation is rigorously demonstrated, indicating that disease persistence emerges smoothly as $R_0$ crosses unity. Local and global sensitivity analyses of the basic reproduction number $R_0$ identify critical epidemiological parameters, and points to vaccination coverage and transmission rates as key drivers of outbreak dynamics. Numerical simulations confirm the analytical results and illustrates two different epidemiological scenarios, one with $R_0<1$, and another with $R_0>1$ along with neural network analysis by using the same data from both cases in a built-in function package in MATLAB-2020 software. It utilizes all of its hidden layers to check the data used by the model for validation performance and training and to find the absolute and mean squared errors. It also shows how vaccination suppresses the spread of infection. These findings provide a strong mathematical basis for public health policy, offering strategic insight into how vaccination campaigns might be optimized to accelerate progress toward global polio eradication. Full article

To investigate the heat-generation mechanisms of journal bearings under different whirl motion and to clarify the corresponding temperature distribution characteristics, a computational fluid dynamics-based method was developed. The model incorporates temperature-dependent lubricant viscosity and employs an unsteady dynamic-mesh updating approach based on structured grids, enabling the automatic iterative tracking of the journal center during whirl motion. A thermal-effect analysis model that accounts for journal whirl trajectories was thereby established. The whirl orbit shape is characterized using elliptical eccentricity, and the effects of whirl direction, elliptical eccentricity, and whirl frequency on the circumferential temperature and pressure distributions of the journal are examined. Results show that under forward whirl, increasing whirl frequency and elliptical eccentricity initially enhances and then weakens local hydrodynamic pressure and viscous shear dissipation in the oil-film convergent region, producing pronounced first-order circumferential temperature nonuniformity and a high risk of thermal bending at intermediate frequencies. Under backward whirl, hydrodynamic effects are reduced and heat generation shifts from localized concentration to global shear dissipation, forming a relatively uniform second-order circumferential temperature field. Increasing elliptical eccentricity causes the whirl orbit to become more linear, improving load-carrying capacity and heat-transfer performance and thereby mitigating thermally induced vibration and oil-film whirl instability. Full article

Milk tea is a globally popular new-style tea beverage product. In recent years, the industry has achieved rapid development in terms of scale expansion and quality iteration and upgrading. The flavor quality and product stability have become the focus of attention and research hotspots in this field. The chemical foundation of milk tea flavor, processing methods, and flavor quality evaluation approaches are thoroughly elaborated. The chemical basis of tea-based, milk-based, and milk tea flavors is systematically summarized, primarily including the analysis of key flavor compounds and the interactions between tea-based and milk-based substances. Subsequently, the tea-based production methods, mixed processing techniques, and factors influencing storage and preservation of milk tea are discussed. Furthermore, evaluation methods for milk tea flavor quality, including traditional sensory evaluation and intelligent assessment techniques are systematically outlined. This review not only summarizes the recent research progress but also looks forward to the interdisciplinary work that needs to be carried out in the future. These efforts aim to provide information on the transformation from the research stage of tea milk product formulas to the development of solutions with controllable quality. Thus, they offer valuable theoretical guidance for the formation and regulation of tea milk flavor and quality as well as the development of new products. This work aims to provide theoretical insights and technical support for the translation from laboratory formulations to quality-controlled industrial solutions. Full article

A three-dimensional frequency-domain ship-motion solver based on the Rankine source method is extended to predict added resistance in waves. Although middle-field formulations have been used mainly in time-domain Rankine panel methods, a middle-field evaluation is implemented here within a frequency-domain Rankine source framework and its validity is examined, including low-speed conditions where the enforcement of radiation conditions is challenging. To enhance robustness at low forward speeds, a hybrid radiation technique is incorporated. Convergence studies are carried out for the free-surface and radiation-boundary discretization, as well as for the control-surface resolution and the clearance distance, and practical numerical settings for added-resistance computations are established. The approach is first verified for Wigley III hulls by comparing motion RAOs and added resistance with published experimental and numerical results. It is then validated for the blunt KVLCC2 hull at the design speed and at low speeds (0 and 4 knots) against published measurements and calculations. Further validations are conducted for additional hull forms (Wigley I, KCS, S-175, and Series 60). The results indicate that the proposed frequency-domain Rankine source method with middle-field evaluation and hybrid radiation yields consistent predictions of motion responses and added resistance over a range of speeds and hull forms, while retaining computational efficiency. Full article

The efficient and timely management of human evacuation during emergency events is an important area of research where the Internet of Things (IoT) can be of great value. Significant areas of application for optimum evacuation strategies include buildings, sports arenas, cultural venues, such as museums and concert halls, and ships that carry passengers, such as cruise ships. In many cases, the evacuation process is complicated by constraints on space and movement, such as corridors, staircases, and passageways, that can cause congestion and slow the evacuation process. In such circumstances, the Internet of Things (IoT) can be used to sense the presence of evacuees in different locations, to sense hazards and congestion, to assist in making decisions based on sensing to guide the evacuees dynamically in the most effective direction to limit or eliminate congestion and maximize safety, and notify to the passengers the directions they should take or whether they should stop and wait, through signaling with active IoT devices that can include voice and visual indications and signposts. This paper uses an analytical queueing network approach to analyze an emergency evacuation system, and suggests the use of the Pull Policy, which employs the IoT to direct evacuees in a manner that reduces downstream congestion by signalling them to move forward when the preceding evacuees exit the system. The IoT-based Pull Policy is analyzed using a realistic representation of evacuation from an existing commercial cruise ship, with a queueing network model that also allows for a computationally very efficient comparison of different routing rules with wide-ranging variations in speed parameters of each of the individual evacuees.Numerical examples are used to demonstrate its value for the timely evacuation of passengers within the confined space of a cruise ship. Full article

This study takes a further step forward in the analytical treatment of Langmuir–Hinshelwood (LH) kinetics for heterogeneous catalysis by deriving its closed-form solution. Unlike previous studies, we present a general solution that does not impose severe restrictions on the experimental conditions. This solution not only recovers the typical first- and zeroth-order regimes but also enables the simultaneous determination of the reaction rate constant and absorption–desorption equilibrium constant, unlike the traditional approaches to this equation, which needed additional isotherm experiments. The final solution requires a fine mathematical treatment for its numerical implementation, but enhanced approximations of the closed-form solution overcome this problem without losing the main advantage of calculating both constants at the same time. A parameter called “critical time” has been introduced, whose calculation allows us to distinguish quantitatively between kinetic regimes. Finally, the validation of these approximations has been carried out with experiments on zinc oxide and anatase (TiO₂) under different conditions. Anatase experiments undoubtedly show a first-order tendency, regardless the quantity of powder. On the other hand, the degradation regime of the ZnO case cannot be easily ascribed to the zeroth or first order by simple inspection, but the model can mathematically rule out the zeroth order and confirm that it undergoes first-order degradation. Full article

Insufficient physical activity (PA) is a significant health challenge among working-age populations. This study aimed to develop context-specific processes to promote PA among adults aged 35–60 years. A participatory action research approach was conducted across seven provinces in upper southern Thailand. The study consisted of three phases: (1) preparation and situation analysis, (2) development and implementation of PA promotion programs, and (3) program evaluation and lessons learned. In Phase 1, the working-age population was categorized into four groups: Group 1: PA occupation and exercise; Group 2: PA occupation but non-exercise; Group 3: non-PA occupation but exercise; Group 4: non-PA occupation and non-exercise. In Phase 2, an exercise program and PA tracking guide were developed and implemented over a 6-month period. In Phase 3, based on the complete-case analysis, 175 participants enrolled, with 101 (57.7%) and 100 (57.1%) remaining at 3 and 6 months, respectively. Based on the last observation carried forward analysis (n = 175 across the 6 months), the proportion achieving global recommended PA levels and time spent in weekly moderate- to vigorous-intensity PA increased significantly in the non-exercise groups (Groups 2 and 4). All participants in the exercise groups (Groups 1 and 3) met the recommended PA level at baseline; however, this level was not maintained at the endpoint. The context-based PA promotion programs improved PA participation among non-exercise working-age adults. Future research should identify strategies to enhance program uptake and sustain engagement. Full article

The development of modern machining and manufacturing industry puts forward higher requirements for the machining accuracy of machine tools. The thermal error of the machine tool spindle directly affects the accuracy of the machined workpiece. To improve the accuracy of thermal error prediction, this paper conducts temperature field analysis for the thermal error of the machine tool spindle and employs the Whale Optimization Algorithm (WOA) to optimize the temperature field parameters, aiming to establish a spindle temperature field model. This approach avoids the problem that traditional measurement methods cannot obtain the temperature of key rotational positions of the spindle and provides a new method for the selection of temperature-sensitive points in the thermal error measurement process. Initially, a spindle Product of Exponentials (POE) error model is constructed to map the five errors of the spindle to three-dimensional vectors in the machine tool space. Subsequently, the Whale Optimization Algorithm (WOA) is used to optimize the physical parameters of the spindle, and the optimal spindle temperature field model is determined. The calculated spindle thermal error data and temperature field model data are input into the OLGWO-SHO-CNN model for training. Finally, a case study is carried out on a machining center, and the trained model is used to perform compensation verification under constant and variable speed conditions, respectively. The experimental results show that under the constant speed condition, the compensation rates of the X-axis, Y-axis, and Z-axis are 77.2%, 73.1%, and 88.7%, respectively; under the variable speed condition, the compensation rates of the X-axis, Y-axis, and Z-axis are 74.7%, 78.2%, and 88.0%, respectively. The compensation results indicate that the established spindle temperature field model and the OLGWO-SHO-CNN model have good robustness and accuracy. Full article

This article applies Causal Layered Analysis (CLA) to four Italian Alpine contexts to examine how narratives and metaphors can shape territorial development. We combined long-term ethnography (approximately 128 days of participant observation) with analysis of documents and media (2010–2025) relating to the four territories and interpreted the results through the four levels of CLA: litanies, systems, worldviews, and myths/metaphors. Two dominant metaphors, “mountain-as-playground” (exogenous) and “mountain-as-heritage” (endogenous), seem to underpin the discourses about tourism and local development. We identify signals of a third metaphor, the “open-hybrid-village”, where multiple forms of belonging and contribution (resident collective ownerships, returnees, extended stay visitors) sustain the local economy and stewardship. The approach is interpretative, and the transferability of results is limited by the selection of cases and the availability of data; however, triangulation and distinct levels support the internal consistency and replicability of the method in other contexts. We conclude that making imaginaries explicit can broaden the variety of thinkable futures and the space of options before investments become dependent on the path taken. We suggest integrating CLA into participatory foresight to enrich and share forward-looking visions on which to negotiate long-term landscape planning and thresholds for tourism carrying capacity. Full article

The surface–borehole transient electromagnetic method (TEM) employs surface-based transmission and downhole reception to collect electromagnetic data. This configuration offers distinct advantages over traditional TEM approaches by effectively attenuating surface electromagnetic noise and cultural interference, leading to enhanced signal strength and vertical resolution. As a result, it has emerged as a key technique for the exploration of deep mineral resources. Although a relatively comprehensive three-dimensional (3D) theoretical system for surface–borehole TEM has been established, most existing studies remain focused on forward modelling, with inversion interpretation receiving comparatively limited attention. In this study, a one-dimensional (1D) inversion algorithm for surface–borehole TEM data is developed. The approach begins with forward modelling based on numerical simulation, followed by the integration of a prior model to formulate an objective function. Optimization is carried out using the Broyden–Fletcher–Goldfarb–Shanno (quasi-Newton) method. A parameter transformation approach was further applied to convert the constrained inversion into an unconstrained optimization problem. The effectiveness of the proposed algorithm is validated through inversions performed on synthetic data derived from theoretical models. This method offers a reliable interpretation tool for practical surface–borehole TEM applications and provides a theoretical basis for the design and optimization of related instrumentation. Full article