Search Results (285)

University mobility in medium-sized cities faces increasing challenges arising from traffic congestion, urban sprawl, and the limited availability of sustainable transport options. In this context, the bicycle represents an efficient and environmentally low-impact alternative, provided that safe and connected infrastructure exists to facilitate its adoption. This study assesses the potential for bicycle use in the Andean city of Loja, Ecuador, taking as a case study the university community of the Universidad Técnica Particular de Loja (UTPL). Geographic Information Systems (GIS) tools, origin–destination (OD) matrices, and logistic models were integrated to analyze the relationship between three key variables: terrain slope, minimum travel time, and the percentage of protected cycling infrastructure. The results show that protected cycling infrastructure shows the strongest positive association with the modeled probability of use, while slopes greater than 15% and trips longer than twenty minutes are associated with lower modeled probabilities. The geospatial analysis identified priority corridors where improvements in cycling protection would yield higher modeled modal returns. It is concluded that strengthening cycling connectivity and the continuity of protected routes may inform scenario-based planning to support active university mobility, offering a replicable framework for medium-sized cities with similar topographic conditions. Full article

Demand-responsive transport (DRT) services are increasingly recognised as an effective solution for enhancing accessibility, particularly in low-demand and peripheral areas. Existing scientific research has investigated DRT as a feeder service to modal interchange nodes, with a specific focus on railway hubs. In this study, an accessibility indicator is developed to compare direct road-based access to regional hubs with multimodal access combining road and rail, enabled by DRT services. The indicator is derived from a detailed analysis of road travel times and scheduled rail services and is applied within a regional-scale framework. Under the hypothesis that travel originates in the centre of each municipality in the area under consideration, two travel times are calculated: the time for the road alternative, based on the characteristics of the road network, and the time for the combined alternative, based on the attributes of the rail network. The resulting indicator allows for identification of the alternative that is more time-competitive for medium-distance travel on a regional scale and for mapping accessibility to attraction centres on a municipal basis. The methodology is applied to a case study in Sicily, Southern Italy. The analysis considers trips from all Sicilian municipalities to the metropolitan areas of Palermo, Catania, and Messina, assessing both the current situation and future scenarios based on planned railway infrastructure upgrades. The results indicate that, while direct road access remains the most efficient option for a large share of municipalities, the multimodal DRT–rail alternative becomes competitive in areas located near railway stations, particularly under scenarios that include major rail interventions, such as the upgrading and speed enhancement of the Palermo–Catania railway corridor. Full article

Background/Objectives: Severe acquired brain injury (sABI) disrupts early rehabilitation because arousal fluctuates, trunk control is fragile, and agitation limits therapy tolerance; land-based practice is frequently constrained by fall risk and staffing. We aim to reframe aquatic therapy as a programmable multisensory environment to stabilize arousal and support axial alignment before conventional impairment targets are feasible. Here, programmable denotes the deliberate titration and reporting of water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support as intervention inputs. Methods: This perspective integrates principles from neurobehavioral assessment, motor control, and immersion physiology to propose the Arousal–Alignment–Action loop as a falsifiable model and to define manipulable aquatic inputs (water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support) as dosing parameters. We outline a pragmatic testing ladder (within-session micro-experiments, feasibility studies, and embedded evaluations) and a minimal outcomes and confounder set to support cumulative evidence. Results: The framework links state regulation to alignment and goal-directed behavior, specifies predictions that can fail, and highlights boundary conditions (sedation, autonomic instability, pain, recent surgery or wounds, and cervical or cardiopulmonary constraints). A minimal outcome package spanning arousal/responsiveness, trunk control, behavioral dysregulation, participation/tolerance, and basic physiology is proposed, with optional objective adjuncts for mechanism-oriented studies. Conclusions: Treating water as a measurable and titratable medium, rather than a generic modality, may reduce early intensity bottlenecks and improve implementability and comparability of aquatic neurorehabilitation research in medically stable sABI; however, the model is intended as hypothesis-generating until supported by stronger direct clinical evidence. Full article

Intravascular lymphoma (IVL) is an uncommon subtype of non-Hodgkin’s extranodal lymphoma, distinguished by the proliferation of neoplastic cells within the lumen of small- to medium-sized arteries, with various organs recorded as impacted. The objective of this study was to evaluate the current literature about IVL and its involvement in the female genital tract, including an overview of diagnostic methods, imaging, and pathological features, selected therapy modalities, and outcomes in patients afflicted by this malignancy. We performed a narrative review with a systematic identification and presentation of published cases of IVL affecting the female genital tract. A literature search was carried out across PubMed, Scopus, and Web of Science for relevant studies presenting data on IVL affecting the female genital tract. Case reports and series that met predefined inclusion and exclusion criteria specified by the modified PECOS (“Population,” “Exposure,” “Comparison,” “Outcomes,” and “Study design”) framework were included. Patients most commonly presented with abnormal vaginal bleeding, pelvic pain, and B symptoms. Fluorodeoxyglucose positron emission tomography computed tomography (FDG PET/CT), often performed alongside abnormal laboratory findings such as elevated lactate dehydrogenase (LDH), played a key role in raising suspicion for hematologic involvement of the female genital tract and guiding biopsy. Most cases represented B-cell intravascular lymphoma and were treated with Rituximab plus (CHOPR-CHOP) based chemotherapy, frequently combined with hysterectomy. Full article

The reaction of the pyridylalcohol Ph₂C(OH)CH₂-2-py-6-Me (IH) with Me₃Al in refluxing toluene led to the isolation of the dimer [AlMe₂(μ-OC(Me)Ph₂)]₂ (1), whilst at ambient temperature the complex [(I)AlMe₂]·MeCN (2·MeCN) was isolated. Complex 1 is also readily available via the interaction of diphenylethanol and Me₃Al. Similar treatment of iPr₂C(OH)CH₂-2-py-6-Me (IIH) at ambient temperature afforded [(II)AlMe₂] (3). Treatment of IH and IIH with [VO(OiPr)₃] led to oxo-bridged complexes of the type [(VO)(μ₂-O)(I/II)]₂ (I (4·0.67MeCN), II (5)). The molecular structures of 1–5 are reported. These complexes have been employed as catalysts for the ring-opening polymerization (ROP) of the cyclic esters ε-caprolactone (ε-CL) and δ-valerolactone (δ-VL). For aluminium, complex 1/BnOH produced medium- to high-molecular-weight (M_n) PCL at 20 to 110 °C in solution, though some bi-/multi-modal behaviour was observed; for melts the M_n values were toward the lower end. For complexes 2 and 3, far lower M_n values for PCL were observed at 20 °C in solution and as melts, whilst in solution at 110 °C higher M_n values were achieved, though with less control. In general, M_n values for the PCL obtained using the vanadium complexes were low (≤8560 Da for 4, ≤2920 Da for 5). In the case of PVL, 1/BnOH in solution exhibited higher M_n values at lower temperatures with good control, and when employed as a melt, the M_n was toward the higher end (30,830 Da) observed. For 2/BnOH, much lower M_n values (≤2740 Da) were recorded both in solution and as a melt, whilst for 3, high M_n values were only observed in the absence of BnOH. Low M_n values (≤2920 Da) were also observed for the vanadium complexes 4 and 5. Kinetic results (both ε-CL and δ-VL) revealed that the vanadium complexes, particularly 4, outperformed the aluminium complexes. MALDI-ToF spectra revealed the formation of linear PCL polymers with BnO/H end groups for the aluminium/BnOH complexes in solution, and cyclic polymers when employed as melts. For vanadium, cyclic PCL polymers were the major family present. In the case of PVL, linear (BnO/H end groups) and cyclic polymers were observed when employing the Al/BnOH systems, whilst cyclic polymers were observed for vanadium. Copolymerization of ε-CL and δ-VL using 4/BnOH at 110 °C over 24 h led to incomplete conversion and formation of a random-type copolymer. Full article

Production profiling is essential for optimizing production strategies in oil and gas wells. Conventional production logging tools provide only discrete, time-limited measurements and face operational challenges in long or complex horizontal wells. Distributed fiber-optic sensing (DTS/DAS) enables continuous, full-wellbore monitoring but each sensing modality has limitations when used alone: DTS interpretation is influenced by wellbore disturbances and thermal hysteresis, while DAS acoustic energy does not always correspond to actual inflow zones. This study proposes a joint interpretation method integrating DTS-based temperature inversion with DAS frequency-band energy and apparent velocity analysis. DTS data are processed using a coupled wellbore–formation heat-transfer model to obtain segmental flow rates, while DAS data are analyzed using short-time Fourier transform, cross-correlation, and Hough transform to extract positive and negative apparent velocities indicating fluid migration directions. Field results show that high-production intervals at 4126–4486 m correlate with positive apparent velocities, whereas medium-/low-production and shut-in stages exhibit persistent negative velocities linked to backflow and reinjection. The combined interpretation effectively distinguishes reservoir inflow from wellbore flow by jointly constraining thermal response and flow direction, thereby reducing uncertainties associated with single-method analysis. Full article

Light Rail Transit (LRT) and Bus Semirapid Transit (BST) are two different forms of semirapid, medium-capacity transit systems. Over recent decades, there has been an ongoing, unresolved debate on which of these two technologies brings about a higher net contribution to a society’s welfare. This study seeks to shed light on this topic through the design, development, and computational execution of a model specifically devised for forecasting transport-related outcomes that would result from the implementation of either an LRT or BST system in a given corridor. This model dynamically systematizes the mutual interactions between travel demand prognoses, the supply attributes of a typical set of modal alternatives, the valuation of those modal alternatives from travelers’ perspectives, and travelers’ consequent choices, taking into account the specific differences between LRT and BST. Furthermore, the model incorporates a methodological treatment of uncertainty through the application of Monte Carlo random simulation techniques. In practice, the model is applied to a case study based on artificial data representative of usual conditions seen in corridors with enough ridership to consider these transit systems. The specific results indicate that LRT generates a moderately higher benefit for travelers in these circumstances, but this turns into a very slight advantage for BST when the investment costs are deducted. Ultimately, this research will contribute to better-informed decision making when selecting a semirapid, medium-capacity transit system, leading to more efficient budget allocation. Full article

Virtual Reality (VR) has emerged as a powerful medium for immersive human–computer interaction, where users’ emotional and experiential states play a pivotal role in shaping engagement and perception. However, existing affective computing approaches often model emotion recognition and immersion estimation as independent problems, overlooking their intrinsic coupling and the structured relationships underlying multimodal physiological signals. In this work, we propose a modality-aware multi-task learning framework that jointly models emotion recognition and immersion estimation from a graph-structured and symmetry-aware interaction perspective. Specifically, heterogeneous physiological and behavioral modalities—including eye-tracking, electrocardiogram (ECG), and galvanic skin response (GSR)—are treated as relational components with structurally symmetric encoding and fusion mechanisms, while their cross-modality dependencies are adaptively aggregated to preserve interaction symmetry at the representation level and introduce controlled asymmetry at the task-optimization level through weighted multi-task learning, without introducing explicit graph neural network architectures. To support reproducible evaluation, the VREED dataset is further extended with quantitative immersion annotations derived from presence-related self-reports via weighted aggregation and factor analysis. Extensive experiments demonstrate that the proposed framework consistently outperforms recurrent, convolutional, and Transformer-based baselines. Compared with the strongest Transformer baseline, the proposed framework yields consistent relative performance gains of approximately 3–7% for emotion recognition metrics and reduces immersion estimation errors by nearly 9%. Beyond empirical improvements, this study provides a structured interpretation of multimodal affective modeling that highlights symmetry, coupling, and controlled symmetry breaking in multi-task learning, offering a principled foundation for adaptive VR systems, emotion-driven personalization, and dynamic user experience optimization. Full article

Occupant presence is a primary driver of Heating, Ventilation, and Air Conditioning (HVAC) and lighting energy consumption in office environments. Existing occupancy-sensing solutions often rely on privacy-sensitive modalities or require costly infrastructure, limiting their applicability in Small and Medium Offices (SMOs). To address these limitations, this study proposes a lightweight CSI-based occupancy-sensing framework based on a dual-core ESP32-S3 architecture, enabling concurrent CSI processing, environmental sensing, and cloud communication. A multi-stage signal preprocessing pipeline compresses raw CSI streams into a compact $56\times 8$ statistical feature matrix, achieving 98.86% classification accuracy for multi-level occupancy estimation. Compared with image-based baselines such as DenseNet121, the proposed approach reduces input data size to 24 kB and model parameters to 138 K, yielding over 129× reduction in transmission volume without sacrificing performance. These results demonstrate that the proposed framework provides a practical, privacy-preserving, and edge-deployable solution for occupancy-aware energy management in SMOs. Full article

Nonlinear seismic analysis procedures can accurately estimate structural responses but are computationally intensive, making them impractical for engineering design. This study provides the first comprehensive evaluation of N2 and modal pushover analysis for eccentrically braced frames (EBFs), revealing their strengths and limitations in predicting link rotations, shear demands, and drift distribution under Canadian seismic hazards. Analyzed were four-, eight-, and 14-storey chevron EBFs under real and artificial ground motions compatible with the response spectrum of Vancouver, Canada. The findings indicate that inelastic link rotations for all EBFs remain below the design limit of 0.08 rad, except for the upper two floors of the 14-storey EBFs. Seismic analysis reveals that maximum inelastic link shear forces often exceed design recommendations. It is also observed that both the N2 method and MPA procedure could reasonably predict the peak roof displacements for low-rise EBF buildings. In addition, while the MPA procedure provides better predictions of maximum inter-storey drifts over all storeys for medium-to-taller EBFs, inter-storey drifts are not predicted well in the N2 method. Additionally, the current code formula for estimating the fundamental period of EBFs predicts shorter periods than those obtained from analysis. An improved formula for estimating EBF periods is proposed. Full article

The Northeast China Cold Vortex (NCCV) is a crucial local synoptic system influencing the weather and climate of Northeast China. However, the application of artificial intelligence techniques in NCCV prediction remains limited. Based on ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), this study constructs a 23-year multi-modal spatiotemporal sequence dataset of NCCV via an objective identification method, focusing on NCCV trajectory prediction. An improved generative adversarial network model is proposed, which adopts a multi-encoder architecture to extract spatiotemporal features of multi-modal NCCV data and introduces a multi-generator structure to address the insufficient prediction capability of a single generator. A selector module is added to enable the model to adaptively select the optimal generation path. Ablation experiments show that compared with single-trajectory data input, multi-modal data input in our model reduces the average prediction error by 67.96 km, representing a 34.0% improvement, and the 24-h prediction error improvement reaches 39.7%. Ultimately, the proposed model achieves superior prediction accuracy and stability in the NCCV trajectory prediction tasks at 6 h, 12 h, 18 h, and 24 h, with prediction distance errors reduced by 21.4%, 29.2%, 34.0%, and 37.0% compared to LSTM. Full article

The primary focus of enhancing the efficiency of operations in the Industry 4.0 setting is Predictive and Preventive Maintenance (PPM). The paper introduces a predictive-maintenance system based on the Unified Namespace (UNS), which involves real-time sensor measurements, photogrammetry, and modelling of a digital twin to improve fault prediction and responsiveness to maintenance. This experiment was conducted over six months in a medium-sized discrete electromechanical production plant equipped with motors, Variable Speed Drives (VSDs), robot/cobots, precision grip systems, pipework systems, Magnemotion/linear motor drives, and a CNC machine. The continuous data, such as high-frequency vibration, temperature, current, and pressure, were monitored and analysed with machine-learning models, including support-vector machines, Gradient Boosting, long-short-term memory, and Random Forest, through which temporal degradation can be predicted. UNS architecture integrated all sensor and imaging data into a vendor-neutral data model through OPC UA to help ensure that all experiments could be integrated consistently and be updated in real time to real digital twins. The suggested system correctly identified mechanical and electrical failures and predicted failures before they really took place. Consequently, machine downtime was reduced by 42.25%, and Mean Time to Repair (MTTR) by 36%, compared to the prior six-month baseline period. These improvements were associated with earlier anomaly detection and digital-twin-supported pre-inspection. Overall, the findings indicate that the integration of UNS with multi-modal sensing and digital-twin technologies may enhance predictive maintenance performance in comparable industrial settings. The framework provides a data-driven, scalable solution to organisations that aim to modernise their maintenance processes, attain greater reliability and better equipment utilisation, as well as enhanced Industry 4.0 preparedness. Full article

In light of the current eco-social crisis, environmental education must adopt a transformative, critical literacy-based approach grounded in scientific practices to prepare students to address socioenvironmental issues from a systemic perspective. This study, which was conducted with 4th and 6th-grade primary school students (aged 9–12), presents the results of an activity based on a socioscientific issue about the presence of pharmaceuticals in surface water. The aim is to evaluate students’ performance in argumentation, their use of and understanding of the materials from which they extract evidence, and the solutions they propose. To this end, the content (written reports) and discourse (group discussions) were analyzed, and different statistical tests were carried out to compare individual and group performance, as well as performance among educational levels. The results show students in both years tend to perform at a low-to-medium level, with higher performance in 6th grade, but there are no significant differences in most areas. They also use materials in different semiotic modalities; similarly, they experience more difficulty with maps and graphs than with texts and videos. Additionally, they propose solutions from various perspectives. Overall, this approach contributes to the development of scientific reasoning in primary school students and should therefore be incorporated into their classroom culture. Full article

In view of the future estimation of the life-time of 3D printed automotive components, this paper evaluates the thermodynamic stability of controlled-nucleated poly (lactic acid) (PLA), focusing on formulations that maintain good mechanical behavior after 4 years of storage under controlled conditions. PLA with 0.5% D-lactide and low molecular weight, which has optimal melt flow at 3D printing, was nucleated using either a sulfonic acid derivative (heterogeneous nucleation) or a PLA grade with 4% D-lactide (stereocomplex or racemic nucleation). Since the earliest signs of thermodynamic instability manifest as changes in chemical structure, which alters thermal behavior, this study focuses on FTIR, DSC analysis and some functional properties such as impact resistance and heat deflection temperature (HDT). The initial properties were compared with those measured 4 years later. Due to heterogeneous nucleation, the bi-modal melting of neat PLA turned into a mono-modal peak, which remained stable over 4 years. Initially, the mono-modal melting of racemic nucleated PLA transitioned into a bi-modal pattern over time, proving its long-term thermodynamic instability. Because 3D printing requires mono-modal melting, it was concluded that racemic crystallization is unsuitable for the used PLA modification with respect to future 3D printing of medium-life automotive components. Crystallinity shapes long-term mechanical performance; therefore, the process must be conducted under selected conditions. Full article

Background/Objectives: Autologous fat grafting (AFG) is widely used in breast reconstruction; however, graft retention remains unpredictable due to recipient-bed variability. Photoacoustic imaging (PAI) is a contrast-free, noninvasive modality enabling visualization of vascular structures in detail. This study used PAI to visualize and quantitatively assess neovascularization and vascular structure in breasts reconstructed with AFG. Methods: In this retrospective, cross-sectional study, data from eight patients who underwent PAI of both reconstructed and contralateral breasts at least three months after their final AFG procedure for total breast reconstruction were used. Excluding the nipple–areola complex and skin markings, four 3 × 3 cm regions of interest (one per quadrant) were selected in the periareolar region. Vascular density in terms of depth from the skin surface was analyzed in five cases with adequate contact between the device and the skin. Visible vessel diameters within the regions of interest were manually measured and categorized as small, medium, or large to assess distribution patterns. Results: PAI successfully enabled visualization of vascular structures on the reconstructed side in all cases, even at depths greater than 10 mm. In five cases, vascular density in the superficial layer (0–2.5 mm) was higher on the reconstructed side than on the contralateral side. A longer postoperative interval was associated with a higher proportion of small vessels and fewer large vessels. Conclusions: PAI enabled noninvasive visualization of vascular structures consistent with neovascularization on the reconstructed side after AFG. Temporal changes in vessel diameter distribution suggest ongoing vascular remodeling, supporting the potential utility of PAI in assessing vascular structural changes in grafted tissue over time. Full article