Search Results (4,221)

Visual perception is fundamental to robotic manipulation for recognizing objects, goals, and contextual details. Third-person cameras provide global views but can miss contact-rich interactions and require calibration. Wrist-mounted egocentric cameras reduce these limitations but introduce occlusion, motion blur, and partial observability, which complicate visuomotor learning. Furthermore, existing perception modules that rely solely on pixels or fuse imagery with proprioception as flat vectors do not explicitly model structured scene representations in dynamic egocentric views. To address these challenges, a multi-slot attention fusion encoder for egocentric manipulation is introduced. Learnable slot queries extract localized visual features from image tokens, and Feature-wise Linear Modulation (FiLM) conditions each slot on the robot’s joint states, producing a structured slot-based latent representation that adapts to viewpoint and configuration changes without requiring object labels or external camera priors. The resulting structured slot-based latent representation is used as input to a Soft Actor–Critic (SAC) agent, which achieves a higher mean cumulative return than pixel-only CNN/DrQ and state-only baselines on a ManiSkill3 egocentric manipulation task. Probing experiments and real-camera evaluation further show that the learned representation remains stable under egocentric viewpoint shifts and partial occlusions, indicating robustness in practical manipulation settings. Full article

In the contemporary digital landscape, AI (Artificial Intelligence) emerged as a pivotal tool in enhancing the defense technologies developed across the entire network infrastructure. As reliance on AI-based decision-making grew, so did the imperative need for interpretability, transparency, and trustworthiness, leading to the development and integration of XAI (eXplainable Artificial Intelligence). This research paper provides a comprehensive overview of the current state of the art in XAI approaches that can be effectively implemented for network traffic monitoring, especially in critical digital infrastructures. The main contribution of this research article consists of the comparative analysis of the XAI SHAP (Shapley Additive Explanation) method applied to different datasets obtained from real-time network traffic monitoring, utilizing several representative parameters, which demonstrates the performance, vulnerabilities, and limitations of the proposed method, and also the security implications of the system resources from a cybersecurity perspective. Experimental results show that Ethernet networks offer higher predictability and clearer decision boundaries. Consequently, they are a safer solution for deployment in sensitive network architectures. In contrast, BYOD (Bring Your Own Device) Wi-Fi environments exhibit greater randomness. Full article

Traditional pedestrian routing algorithms typically minimize physical distance or travel time, often overlooking contextual factors that influence route choice in digitally connected environments. As public WiFi infrastructure becomes increasingly prevalent in smart-city districts and university campuses, digital connectivity may influence pedestrian mobility decisions. This study introduces P-WARP, a multi-factor routing and inference framework that reconstructs latent pedestrian preferences by integrating physical effort, environmental walkability, and WiFi connectivity within a unified semantic graph. The empirical analysis is conducted on the Chiang Mai University campus, a digitally connected environment serving as a smart campus testbed. The framework integrates heterogeneous spatial datasets, including OpenStreetMap topology, Shuttle Radar Topography Mission elevation data, environmental walkability grids, and WiFi roaming logs collected via a custom mobile sensing application from 21 volunteers across 71 verified walking trips. Two routing strategies are evaluated: a Global Static Model, representing infrastructure-based connectivity assumptions, and a Trip-Centric Dynamic Model, incorporating realized connectivity histories. Model parameters are calibrated using Bayesian Optimization with five-fold cross-validation. Results show that incorporating realized connectivity reduces trajectory reconstruction error by 6.84% relative to the baseline. The learned parameters reveal a notable detour tolerance, suggesting that stable digital connectivity can influence pedestrian route choice in digitally instrumented environments. Full article

Background: Main risk factors associated with the development of sarcopenia (coexistence of muscle mass loss and dysfunction) are a sedentary lifestyle coupled with obesity. Associated mitochondrial dysfunction leads to energy deficits and perturbations in the balance between protein synthesis and degradation, thereby triggering muscle dysfunction or atrophy. Aside from exercise, which is challenging to implement and maintain, particularly in women, treatments for diminishing sarcopenia are scarce. The objective of the present study was to evaluate the effect of the flavanol (−)-epicatechin (EC) in a hypercaloric diet-induced obese female rat model. Muscle strength and endurance, as well as relative mitochondrial DNA content in skeletal muscle, were assessed. Methods: Female rats were fed a hypercaloric diet to induce obesity, as evidenced by increases in body weight, Lee index, and lipid profile alterations, and by abdominal fat accumulation, and to promote a sarcopenic phenotype. Functional tests of grip strength and mobility (treadmill) were performed. Mitochondrial relative content was evaluated by measuring the ratio of mtDNA/nuclear DNA, and the expression of genes related to mitochondrial biogenesis (Pgc1-α, Tfam), fusion (Mfn1 and Opa1), fission (Drp1 and Fis1), and mitophagy (Pink1 and Pkn), and function; citrate synthase and Ucp3 were also evaluated. Results: A significant decrease in mobility and strength was observed in obese female rats, accompanied by reduced mitochondrial numbers, activity, and dynamics, but not by changes in muscle size or weight. Treatment with EC induced mitochondrial biogenesis and positive changes in mitochondrial dynamics (fission and fusion) and activity, as measured indirectly by changes in citrate synthase and Ucp3 expression. Discussion: Results reinforce the potential of EC as a modulator of mitochondrial function in dysfunctional conditions associated with obesity, thereby attenuating the mechanisms underlying sarcopenia. Full article

Localization and navigation techniques have become fundamental for modern lives, while achieving accurate results indoors still remains a significant challenge. The widespread adoption of smart devices, and especially smartphones, has increased the need for accurate and robust pedestrian dead reckoning systems that operate in infrastructure-less environments. Pedestrian dead reckoning’s primary challenge is maintaining accuracy despite varying smartphone placements (attitudes) and the noisy, low-cost inertial measurements units. In this work, a comprehensive pedestrian dead reckoning framework is presented that integrates advanced step counting and heading estimation techniques. For step detection and counting, we propose a robust step counting algorithm that utilizes the optimum fusion of the raw IMU readings, i.e., accelerometer, linear accelerometer, gyroscope, and magnetometer readings, each broken down into three degrees of freedom for different body placements and walking speeds. Furthermore, to address the critical issue of heading estimation, we propose the heading estimation axis mapping (HEAT-MAP) algorithm, which dynamically adjusts the sensor axes in response to the smartphone’s orientation, ensuring a consistent coordinate frame and reducing heading drift. Moreover, to eliminate cumulative pedestrian dead reckoning errors, the system incorporates an adaptive weighted fusion mechanism with Wi-Fi fingerprinting. Experimental results demonstrate that this integrated system significantly improves the overall trajectory accuracy, providing a high-precision, attitude-unconstrained solution for real-time indoor pedestrian navigation. Full article

Sewerage systems are among the most fundamental and indispensable components of urban infrastructure. However, inadequate management can result in malfunctions and subsequent rehabilitation processes, leading to various negative consequences. Identifying areas at high risk of failure and conducting system-based inspections can significantly improve the performance of sewer networks. This study identified and categorized 33 criteria that could cause sewer system failures: structural, operational, hydraulic and environmental defects. A Bayesian network (BN) model was developed to determine dependencies between the criteria, quantify uncertainty, investigate new information about the structural condition of assets and calculate the effects and sensitivities of the criteria on the probability of failure. A probability-based risk assessment model was then created using a fuzzy inference system (FIS) to predict risk levels in sewerage systems under different combinations of physical and operational conditions and hydraulic and environmental effects. A case study was performed on a sewer network in Malatya, Turkey, determining its failure probability to be 76.6%, placing it in the high-risk category. When the probability of pipe failure was set to 100% in the Bayesian network model to evaluate the relative influence of different criteria, the most influential factors were identified as flow velocity (74.8%), clogging (71.4%), and failure rate (71.1%). Thanks to the flexible structure of BNs, the proposed model is expected to be useful for performing risk analyses in systems involving uncertainty or missing data. It can also be used to prioritize rehabilitation, inspection and maintenance programs, improve infrastructure service quality and ensure system reliability in urban sewerage systems. Full article

Artificial intelligence (AI) is propelling space exploration into a new era. Synergistic breakthroughs in chip design and high-speed communications have facilitated the large-scale deployment of on-board satellite computing. Assessing the reliability of these systems via fault injection (FI) remains difficult due to the massive computational demands of Convolutional Neural Networks (CNNs) and the complex architectures of Neural Processing Units (NPUs). This research presents a high-precision, efficient FI methodology specifically tailored for NPU architectures to optimize both evaluation accuracy and execution efficiency. Implementing a hierarchical injection strategy to identify fault-sensitive layers minimizes computational overhead while ensuring statistical validity. Experimental results on the ResNet-50 network demonstrate that the proposed methodology constrains accuracy degradation to less than 0.1% while achieving a 60.80% reduction in total execution time. Full article

Flexible interconnection systems (FISs) improve distribution flexibility, yet they remain vulnerable to pronounced nonlinear instability and potentially severe DC-link voltage collapse during large disturbances such as constant power load (CPL) surges. Conventional linear control methods are often unable to prevent deep transient voltage dips under these conditions. To address this issue, this paper proposes a novel large-signal stability criterion based on mixed potential function (MPF) theory. Unlike conventional Lyapunov-based approaches, the proposed formulation explicitly incorporates the dynamics of the DC capacitor, thereby enabling the derivation of a closed-form stability boundary. On this basis, the proportional gains of the outer voltage loop are first optimized to guarantee an adequate static stability margin. Subsequently, a power differentiation feedforward control strategy is developed. Rather than passively counteracting transients, the proposed method dynamically adjusts the DC voltage reference according to the rate of change in power, thereby actively reshaping the transient trajectory. In this way, the simple PI control framework is preserved while avoiding the heavy computational burden associated with advanced methods such as model predictive control. Simulation results show that the proposed strategy increases the permissible CPL step power by 8.7%, from 92 kW to 100 kW. Moreover, under severe load surges and weak grid conditions, the method prevents voltage collapse and maintains the transient trajectory above the practical 600 V safe-operation threshold. This computationally efficient strategy significantly improves the robustness and continuity of operation of practical FISs. Full article

Many IoT systems require real-time communication, which imposes strict timing constraints on data transmission and stresses network propagation models. These systems need to address these communication requirements using wireless networks and also manage quality of service. While Software-Defined Wireless Networks (SDWNs) offer a compelling alternative for these scenarios, they lack dynamic mechanisms to autonomously adapt network behavior to fluctuating operational conditions. In order to do that, this paper builds on the authors’ previous work and shows how to implement Context-Aware Software-Defined Wireless Networks (CA-SDWNs) that use a self-adapting traffic management strategy to deal with dynamic real-time requirements. In particular, it adapts the medium access protocol parameters to changes in the operational context using an intelligent agent in the control loop of the network. We implement the CA-SDWN model using the NS-3 simulator, and that implementation is made available for researchers and developers through an open-source library. The model is evaluated using several SDWNs that operate under dynamic conditions. The experimental results show how incorporating artificial intelligence into the control loop enables the use of the context information to enhance the predictability of the medium access protocol parameters, thus handling different traffic QoS according to the demand of IoT applications. It represents a clear contribution for researchers and developers of these systems when they have to deal with QoS and real-time constrained communication in SDWNs implemented on WiFi. Full article

Introduction: Various scoring systems are applied to burn patients to assess the perioperative and mortality risks as well as comorbidities. Objective: The purpose of this study was to compare the predictive accuracies for mortality of different scoring systems: the Abbreviated Burn Severity Index (ABSI), Bogenhausen ABSI (BABSI), American Society of Anesthesiologists (ASA) classification, Charlson Comorbidity Index (CCI) and modified Frailty Index-5 (mFI-5). Materials and Methods: We retrospectively analyzed 644 burn patients treated at one burn center between September 2018 and May 2022. Results: Median scores were 5 (range: 1–16), 5 (range: 2–17.5), 2 (range: 1–5), 0 (range: 0–14) and 0 (range: 0–5) for the ABSI, BABSI, ASA, CCI and mFI-5, respectively. Significantly different median score results were observed between survivors and non-survivors: ABSI: 5 vs. 10; BABSI: 5 vs. 10.5; ASA: 2 vs. 4; CCI: 0 vs. 5; and mFI-5: 0 vs. 2 (p < 0.001 for all scores). Predictive accuracies were excellent for the BABSI (AUC = 0.963), ABSI (AUC = 0.952), and ASA (AUC = 0.916), whereas fair predictive accuracies were found for the CCI (AUC = 0.851) and mFI-5 (AUC = 0.760). Good calibration was observed for the BABSI, ABSI, CCI, and mFI-5, whereas calibration was poor for the ASA. Conclusion: All five scores significantly differentiate between survivors and non-survivors. However, the strongest discriminatory power and best calibration for mortality prediction were observed for the BABSI and ABSI scores. Therefore, the application of both scores is recommended in daily routine. Full article

This article reads the recent Chinese sci-fi blockbuster franchise The Wandering Earth (2019) and The Wandering Earth II (2023) as linked thought experiments about planetary survival as governance. It argues that the franchise operationalizes survival through administrative techniques that allocate life chances and format subjects for compliance, including selection policy, evaluative procedures, and computational judgment. Drawing on feminist social reproduction theory, affective and emotional labor scholarship, and critical posthumanism, the article shows how the films redistribute life-making work under catastrophe by routing care, sacrifice, and intergenerational continuity through gendered paternal figures. Fathers become the privileged conduits through which attachment is rendered socially legible as authorized labor, while other forms of care remain structurally secondary unless crisis forces their instrumental uptake. At the same time, the franchise is preoccupied with the limits of procedural governance. Across both installments, paternal attachment repeatedly appears as a governance problem: it cannot be fully stabilized as procedure yet becomes actionable at system stress points. The survival regime thus depends on a recurrent sequence of emergency recruitment followed by retroactive legitimation, whether through official affect, selective recognition, containment, or memorialization. Full article

Puccinia striiformis f. sp. elymi (Pse) is a specialized forma specialis of stripe rust infecting Elymus dahuricus, yet its mitochondrial evolution remains poorly understood. In this study, we assembled the complete mitogenome of Pse using PacBio HiFi sequencing, yielding a circular mitogenome of 72,952 bp. This reveals a striking asymmetric evolutionary pattern with a 28.34% genomic contraction compared to the wheat stripe rust P. striiformis f. sp. tritici (Pst-CYR32). Our analysis demonstrates that this streamlining is strictly driven by a massive and systematic loss of mitochondrial introns. The Pse mitogenome exhibits negative GC-skew (−0.0184) consistent with strand-asymmetric mutational pressure, while maintaining a strictly conserved and syntenic complement of all 14 core protein-coding genes (PCGs), alongside 24 tRNAs and 2 rRNAs. Phylogenomic analysis positions Pse as sister to the Pst clade with strong support (100% bootstrap). A 748-bp SNP cluster within nad4 (14.2% sequence divergence versus 3.1% genome-wide average) provides a candidate molecular marker for lineage differentiation, pending population-level validation. This study establishes a genomic foundation for investigating mitochondrial reductive evolution in host-specialized rust lineages, highlighting the dynamic role of introns in driving organellar genome size variation. Full article

The present study evaluated the effects of dietary inclusion of Hermetia illucens (HI) and Tenebrio molitor (TM) larvae meals at 2% and 4% on growth performance, carcass yield, meat quality, blood parameters, and intestinal morphometry in broiler chickens. A total of 1750 one-day-old male Ross 308 broilers were assigned to five dietary treatments: a Control diet, or diets containing 2% or 4% of HI meal (HI2, HI4) or TM meal (TM2, TM4). Growth performance, feed intake (FI), feed conversation ratio (FCR), and mortality were unaffected by dietary treatments. Breast yield increased significantly in insect-fed groups (29.2–29.9%) compared with Control (27.6%). Birds fed HI4 exhibited lower breast pH (5.77 vs. 5.89) and increased cooking loss (29.2% vs. 27.3%), suggesting reduced WHC within acceptable ranges. Thigh meat showed dose-dependent lipid accumulation in insect-fed birds. Serum total cholesterol increased in TM-fed birds with elevated HDL-cholesterol, while LDL-cholesterol remained unaffected. TM meal specifically induced shorter ileal length compared with Control and HI-fed groups. Overall, both full-fat insect meals can be safely incorporated at low inclusion levels without adverse effects on broiler growth, health, or carcass quality. Full article

Background/Objectives: Food insecurity remains a growing public health concern among university populations, particularly international students who often face financial constraints, limited social support, and cultural adaptation challenges. This study investigated the association between food insecurity and dietary diversity among international students in Hungary, a population for whom empirical evidence remains limited. Methods: A cross-sectional survey was conducted among 380 international university students using a structured questionnaire comprising sociodemographic items, the Food Insecurity Experience Scale (FIES), and a quantitative Food Frequency Questionnaire (FFQ). Dietary diversity was assessed through Food Group Diversity Score (FGDS) and Food Variety Score (FVS). Statistical analyses included chi-square tests, ANOVA, correlation analyses, and multiple regression using IBM SPSS 28.0. Results: Overall, 62% of participants experienced food insecurity, with 25% moderately and 20% severely food insecure, while 17% were classified as mildly food insecure. While 97% achieved high dietary diversity, only 31% exhibited high food variety. Group comparisons indicated differences in FGDS across food security categories (p = 0.006), whereas FVS did not differ significantly (p = 0.411). In multivariable regression models adjusting for socioeconomic and behavioural factors, food security status was not independently associated with FGDS or FVS. However, scholarship status, monthly income, employment, and meal skipping were significant predictors of dietary diversity indicators. Conclusions: These findings suggest that while food insecurity is prevalent among international students, socioeconomic resources and behavioural factors may play a more prominent role in shaping dietary diversity outcomes. Universities and policymakers should prioritise equitable food access, culturally inclusive meal services, and ongoing monitoring of student food security to promote nutrition equity and academic well-being. Full article

The effects of three metabolizable energy (ME) levels and the use of guanidinoacetic acid (GAA) were evaluated on broiler performance and nutrient digestibility from 1 to 35 d of age. In total, 1944-d-old Ross AP95 male broilers were randomly distributed to six treatments (12 replicates/treatment). Diets were formulated to contain three ME levels (standard energy [SE], −50 kcal/kg reduced energy [−50 RE] and −100 kcal/kg reduced energy [−100 RE]) in all feeding phases with or without GAA inclusion. For the nutrient-metabolizable analysis, 960-day-old male broilers were separately raised in floor pens until 14 d of age and randomly distributed to six treatments (16 replicates/treatment). Data were analyzed with ANOVA and Tukey’s test at p ≤ 0.05. There was a significant interaction for the feed conversion ratio (FCR) at 21 days, in which the PC diet showed better FCR when GAA was included. In the evaluation of the main effects, an effect of metabolizable energy (ME) was observed on body condition score (BCS) at 7 and 21 days, feed intake (FI) at 21 and 35 days, and feed conversion ratio (FCR) at 21 days, with the PC diet showing better FCR and lower FI. An effect of GAA was observed on feed conversion ratio at 21 days, with the inclusion of GAA in the diet showing better FCR. In conclusion, broilers fed SE diets with GAA, beyond better performance, had improved AME and AMEn compared to broilers fed RE diets without GAA in starter diets. Full article