Search Results (8)

Temperature and humidity excursions during transport accelerate quality loss in fresh produce. This study develops and validates a self-contained Internet of Things (IoT) platform for in-transit monitoring and energy-aware operation. The battery-powered device operates independently of vehicle power and continuously logs temperature, relative humidity, GPS position, and onboard power draw. Power budgeting combines firmware-level deep-sleep scheduling with a LiFePO₄ battery pack, enabling uninterrupted operation for up to four days. Using ∼10,000 time-stamped observations collected over four consecutive days in a standard dry truck (non-commercial validation), we trained and compared Gradient Boosting Machine (GBM), Random Forest (RF), and Linear Regression (LR) models to predict energy consumption under varying environmental and routing conditions. GBM and LR achieved high explanatory power ($R^2\approx 0.88$) with a mean absolute error of 0.77 A·h, while RF provided interpretable feature importance data, identifying temperature as the dominant driver, followed by trip duration and humidity. The end-to-end system integrates an EMQX MQTT broker, a Laravel web application, MongoDB storage, and Node-RED flows for real-time dashboards and multi-day historical analytics. The proposed platform supports proactive decision-making in perishable logistics, with the AI analysis validating that the collected time-aligned on-route data can configure sampling/transmit cadence to preserve autonomy under stressful conditions. Full article

This study introduces a machine learning–driven extended reality (XR) interaction framework that leverages electroencephalography (EEG) for decoding consumer intentions in immersive decision-making tasks, demonstrated through functional food purchasing within a simulated autonomous vehicle setting. Recognizing inherent limitations in traditional “Preference vs. Non-Preference” EEG paradigms for immersive product evaluation, we propose a novel and robust “Rest vs. Intention” classification approach that significantly enhances cognitive signal contrast and improves interpretability. Eight healthy adults participated in immersive XR product evaluations within a simulated autonomous driving environment using the Microsoft HoloLens 2 headset (Microsoft Corp., Redmond, WA, USA). Participants assessed 3D-rendered multivitamin supplements systematically varied in intrinsic (ingredient, origin) and extrinsic (color, formulation) attributes. Event-related potentials (ERPs) were extracted from 64-channel EEG recordings, specifically targeting five neurocognitive components: N1 (perceptual attention), P2 (stimulus salience), N2 (conflict monitoring), P3 (decision evaluation), and LPP (motivational relevance). Four ensemble classifiers (Extra Trees, LightGBM, Random Forest, XGBoost) were trained to discriminate cognitive states under both paradigms. The ‘Rest vs. Intention’ approach achieved high cross-validated classification accuracy (up to 97.3% in this sample), and area under the curve (AUC > 0.97) SHAP-based interpretability identified dominant contributions from the N1, P2, and N2 components, aligning with neurophysiological processes of attentional allocation and cognitive control. These findings provide preliminary evidence of the viability of ERP-based intention decoding within a simulated autonomous-vehicle setting. Our framework serves as an exploratory proof-of-concept foundation for future development of real-time, BCI-enabled in-transit commerce systems, while underscoring the need for larger-scale validation in authentic AV environments and raising important considerations for ethics and privacy in neuromarketing applications. Full article

After a mine-fire accident occurs, a large number of emergency resources need to be allocated to rescue those involved in the mine-fire accident. The allocation of emergency resources for mine-fire accidents has the characteristic of being a complex system with strong uncertainty. To investigate the impact of various variables on the allocation of emergency resources in mine-fire situations, this paper analyzes the relevant factors that influence the process of allocating emergency resources during mine fires. It defines the variables of the mine-fire emergency resource-allocation system based on relevant assumptions. Causal loop and stock flow diagrams are drawn to illustrate the relationships between the variables and the system dynamics equation. Finally, a system dynamics model for mine-fire emergency resource allocation is established. The Vensim software was used to simulate the model of a mine-fire emergency rescue. The simulation produced curves for the evolution rate of the fire, the arrival rate, the demand for emergency resources, in-transit resources, arrival, and the usage of resources during the emergency. The results indicate a positive correlation between the quantity of emergency resources in-transit and the arrival rate of emergency resources: they are positively correlated with the amount of emergency-management investment. Additionally, the duration of the maximum quantity of emergency resources in-transit is positively correlated with the length of the emergency resource-allocation route. On the other hand, the evolution rate of the mine fire and the arrival rate of its emergency resources are negatively correlated with the level of emergency management. The evolution rate of the mine fire becomes larger and the damage caused by the mine-fire accident is greater when the decision-making ability of commanders is at a low level. Full article

Type I contextuality or inconsistent connectedness is a fundamental feature of both the classical as well as the quantum realms. Type II contextuality (true contextuality or CHSH-type contextuality) is frequently asserted to be specific to the quantum realm. Nevertheless, evidence for Type II contextuality in classical settings is slowly emerging (at least in the psychological realm). Sign intransitivity can be observed in preference relations in the setting of decision making and so intransitivity in decision making may also yield examples of Type II contextuality. Previously, it was suggested that a fruitful setting in which to search for such contextuality is that of decision making by collective intelligence systems. An experiment was conducted by using a detailed simulation of nest emigration by workers of the ant Temnothorax albipennis. In spite of the intransitivity, these simulated colonies came close to but failed to violate Dzhafarov’s inequality for a 4-cyclic system. Further research using more sophisticated simulations and experimental paradigms is required. Full article

Stage III melanoma includes nodal metastasis or in-transit disease. Five-year survival rates vary between 32% and 93%. The identification of high-risk patients is important for clinical decision making. We demonstrated previously that ≥1 circulating tumor cells (CTCs) at baseline was associated with recurrence. In this study, we investigated how frequently CTCs were identified prior to radiologically detected recurrence. Stage III patients (n = 325) had imaging at baseline and q 3 months. Baseline and q 6–12 months blood draws (7.5 mL) were performed to identify CTCs up to 3.5 years from diagnosis. CTC assessment was performed using the immunomagnetic capture of CD146-positive cells and anti-MEL-PE. The presence of one or more CTCs was considered positive. We analyzed the cohort of patients with relapse confirmed by radiologic imaging. CTC collection dates were assessed to determine the lead time for CTC detection. CTC-negative patients were significantly less likely to relapse compared to patients positive for CTCs (p-value < 0.001). Within the 325-patient cohort, 143 patients (44%) had recurrence, with a median follow-up of 52 months from diagnosis. The cohort (n = 143) with positive imaging and CTC results revealed 76% of patients (108/143) had CTC+ results before the radiological identification of relapse. The median time between positive CTC and positive imaging was 9 months. CTCs were positive in >75% of patients prior to relapse at a median of 9 months before radiologic detection. Full article

Expected utility theory (EUT) is currently the standard framework which formally defines rational decision-making under risky conditions. EUT uses a theoretical device called von Neumann–Morgenstern utility function, where concepts of function and random variable are employed in their pre-set-theoretic senses. Any von Neumann–Morgenstern utility function thus derived is claimed to transform a non-degenerate random variable into its certainty equivalent. However, there can be no certainty equivalent for a non-degenerate random variable by the set-theoretic definition of a random variable, whilst the continuity axiom of EUT implies the existence of such a certainty equivalent. This paper also demonstrates that rational behaviour under utility theory is incompatible with scarcity of resources, making behaviour consistent with EUT irrational and justifying persistent external inconsistencies of EUT. A brief description of a new paradigm which can resolve the problems of the standard paradigm is presented. These include resolutions of such anomalies as instant endowment effect, asymmetric valuation of gains and losses, intransitivity of preferences, profit puzzle as well as the St. Petersburg paradox. Full article

Hierarchy is a key characteristic of any complex system. This paper explores which notions of hierarchy are being used in the field of organization and management studies. Four distinct types of hierarchy are identified: a ladder of formal decision-making authority, a ladder of achieved status, a self-organized ladder of responsibility and an ideology-based ladder. A social mechanism-based perspective serves to define and distinguish these four types. Subsequently, the typology is further developed by comparing the four hierarchy types in terms of their tacit/explicitness, (in)transitivity and behavior- versus cognition-centeredness. This article contributes to the literature by dissecting the general metaphor of hierarchy into four different constructs and their social mechanisms, which serves to create a typology of the various ways in which complex social systems can be characterized as hierarchical. This typology can inform future research drawing on any type of hierarchy. Full article

The transitivity of preferences is one of the basic assumptions used in the theory of games and decisions. It is often equated with the rationality of choice and is considered useful in building rankings. Intransitive preferences are considered paradoxical and undesirable. This problem is discussed by many social and natural scientists. A simple model of a sequential game in which two players choose one of the two elements in each iteration is discussed in this paper. The players make their decisions in different contexts defined by the rules of the game. It appears that the optimal strategy of one of the players can only be intransitive (the so-called relevant intransitive strategy)! On the other hand, the optimal strategy for the second player can be either transitive or intransitive. A quantum model of the game using pure one-qubit strategies is considered. In this model, an increase in the importance of intransitive strategies is observed: there is a certain course of the game where intransitive strategies are the only optimal strategies for both players. The study of decision-making models using quantum information theory tools may shed some new light on the understanding of mechanisms that drive the formation of types of preferences. Full article