bluuebunny/crossref_metadata_2025 huggingface dataset:
A Human Brain-Chip for Modeling Brain Pathologies and Screening Blood–Brain Barrier Crossing Therapeutic Strategies
Authors: Chim Shek Man , Howell Kristen , Kokkosis Alexandros , Zambrowicz Brian , Karalis Katia , Pavlopoulos Elias
Published: October 2024

Background/Objectives: The limited translatability of preclinical experimental findings to patients remains an obstacle for successful treatment of brain diseases. Relevant models to elucidate mechanisms behind brain pathogenesis, including cell-specific contributions and cell-cell interactions, and support successful targeting and prediction of drug responses in humans are urgently needed, given the species differences in brain and blood-brain barrier (BBB) functions. Human microphysiological systems (MPS), such as Organ-Chips, are emerging as a promising approach to address these challenges. Here, we examined and advanced a Brain-Chip that recapitulates aspects of the human cortical parenchyma and the BBB in one model. Methods: We utilized human primary astrocytes and pericytes, human induced pluripotent stem cell (hiPSC)-derived cortical neurons, and hiPSC-derived brain microvascular endothelial-like cells and included for the first time on-chip hiPSC-derived microglia. Results: Using Tumor necrosis factor alpha (TNFα) to emulate neuroinflammation, we demonstrate that our model recapitulates in vivo-relevant responses. Importantly, we show microglia-derived responses, highlighting the Brain-Chip’s sensitivity to capture cell-specific contributions in human disease-associated pathology. We then tested BBB crossing of human transferrin receptor antibodies and conjugated adeno-associated viruses. We demonstrate successful in vitro/in vivo correlation in identifying crossing differences, underscoring the model’s capacity as a screening platform for BBB crossing therapeutic strategies and ability to predict in vivo responses. Conclusions: These findings highlight the potential of the Brain-Chip as a reliable and time-efficient model to support therapeutic development and provide mechanistic insights into brain diseases, adding to the growing evidence supporting the value of MPS in translational research and drug discovery.
Experimental State Observer of the Population Inversion of a Multistable Erbium-Doped Fiber Laser
Authors: Magallón-García Daniel Alejandro , López-Mancilla Didier , Jaimes-Reátegui Rider , García-López Juan Hugo , Huerta Cuellar Guillermo , Ontañon-García Luis Javier , Soto-Casillas Fabian
Published: October 2024

In this work, numerical and experimental implementation of a state observer applied to an erbium-doped fiber laser (EDFL) has been developed. The state observer is designed through the mathematical model of the EDFL to estimate the non-measurable variable; however, in numerical estimation, the state variables can be measurable given the mathematical model. Only the laser intensity variable was experimentally measured. The state observer estimated the population inversion through the obtained experimental laser intensity time series fitted with their numerical laser intensity using the mean square error (MSE) tool. A bifurcation diagram of the population inversion time series local maximum was built from the state observer. The state space of the experimental laser intensity versus observed population inversion was built.
Aqueous Extracts of Rhus trilobata Inhibit the Lipopolysaccharide-Induced Inflammatory Response In Vitro and In Vivo
Authors: Rodríguez-Castillo Alejandra Jazmín , González-Chávez Susana Aideé , Portillo-Pantoja Ismael , Cruz-Hermosillo Eunice , Pacheco-Tena César , Chávez-Flores David , Delgado-Gardea Ma. Carmen E. , Infante-Ramírez Rocío , Ordaz-Ortiz José Juan , Sánchez-Ramírez Blanca
Published: October 2024

Chronic noncommunicable diseases (NCDs) are responsible for approximately 74% of deaths globally. Medicinal plants have traditionally been used to treat NCDs, including diabetes, cancer, and rheumatic diseases, and are a source of anti-inflammatory compounds. This study aimed to evaluate the anti-inflammatory effects of Rhus trilobata (Rt) extracts and fractions in lipopolysaccharide (LPS)-induced inflammation models in vitro and in vivo. The aqueous extract (RtAE) and five fractions (F2 to F6) were obtained via C18 solid-phase separation and tested in murine LPS-induced J774.1 macrophages. Key inflammatory markers, such as IL-1β, IL-6, TNF-α, and COX-2 gene expression were measured using RT-qPCR, and PGE2 production was assessed via HPLC-DAD. The in vivo effects were tested in an LPS-induced paw edema model in Wistar rats. Results showed that RtAE at 15 μg/mL significantly decreased IL-1β and IL-6 gene expression in vitro. Fraction F6 further reduced IL-1β, TNF-α, and IL-6 gene expression, COX-2 expression, and PGE2 production. In vivo, F6 significantly reduced LPS-induced paw edema, inflammatory infiltration, and IL-1β and COX-2 protein expression. Chemical characterization of F6 by UPLC/MS-QTOF revealed at least eight compounds with anti-inflammatory activity. These findings support the anti-inflammatory potential of RtAE and F6, reinforcing the medicinal use of Rt.
Preparation and Properties of Cyano-Functionalized Graphitic Nanoplatelets for High-Performance Acrylonitrile Butadiene Styrene Resin
Authors: Yoon Seo-Jeong , Lee Se-Jung , Baek Jae-Hoon , Kim Tae-Hee , Jeon In-Yup
Published: October 2024

Cyano-functionalized graphitic nanoplatelets (CyGNs) are synthesized by means of a mechanochemical reaction between graphite and acrylonitrile. The resulting CyGNs exhibit excellent mechanical properties and are highly dispersible in various solvents (i.e., THF). Due to their chemical compatibility (specifically, cyano functional groups), the CyGNs serve effectively as a reinforcing filler for acrylonitrile butadiene styrene (ABS) resin. Consequently, compared to pure ABS, CyGN&ABS-X demonstrates improved mechanical properties and better thermal stability. Notably, the CyGN&ABS-1 specimen exhibits significant enhancements in the tensile strength (26 ± 1 MPa), Young’s modulus (992 ± 71 MPa), and tensile toughness (22 ± 3 MPa), representing increases of approximately 130.6%, 19.2%, and 59.6%, respectively, over pure ABS. This underscores the ability of a mechanochemical reaction to directly modify the functional groups of graphitic nanoplatelets (GnPs) as fillers, facilitating their strong compatibility with a variety of polymers, including copolymers.
Dynamic Response Analysis of Corroded Pipelines Containing SCCO2 under Rockfall Impact
Authors: Wang Yanxin , Gu Xiaoting , Xia Yicun
Published: October 2024

Carbon capture, utilization, and storage (CCUS) technologies are crucial for reducing CO2 emissions. Currently, subsea CO2 storage is considered a highly feasible CCUS method. With the development of marine CCUS projects, impact loads from ship anchoring and marine debris, combined with internal corrosion defects in CO2 transport pipelines, significantly increase the risk of pipeline failure. This represents a major challenge for offshore SCCO2 pipelines. To investigate the stress–strain response of corroded pipelines under impact loads, a pipeline model with corrosion defects under rockfall impact conditions was established using ABAQUS 2014 finite element software. By varying factors such as the rock mass, impact velocity, drop point, and defect area, a single-variable analysis was conducted to explore the dynamic response of the pipeline. The results indicate that the rock mass and impact velocity are the key factors affecting pipeline stress, while the drop point and defect area have minimal impacts. Additionally, when the pipeline reaches yield failure, the effects of these factors become negligible.
Dynamic Multi-Factor Correlation Analysis for Prediction of Provincial Carbon Emissions in China’s Bohai Rim Region
Authors: Qi Yanfen , Zhang Xiurui , Zhang Jiaan , Sun Yu
Published: October 2024

This study presents a dynamic multi-factor correlation analysis method designed to predict provincial carbon dioxide emissions (CDE) within China’s Bohai Rim region, including Tianjin, Hebei, Shandong, and Liaoning. By employing the sliding window technique, dynamic correlation curves are computed between various influencing factors and CDE at different time intervals, thereby facilitating the identification of key feature attributes. A novel metric, the Consistency Index of Influencing Factors (CIIF), is introduced to evaluate the consistency of these factors across regions. Furthermore, the Accurate Predictive Capability Indicator (APCI) is defined to measure the impact of different feature categories on the prediction accuracy. The findings reveal that models relying on a single influencing factor exhibit limited accuracy, whereas combining multiple factors with diverse correlation features significantly improves the prediction accuracy. This study introduces a refined analytical framework and a comprehensive indicator system for CDE prediction. It enhances the understanding of the complex factors that influence CDE and provides a scientific rationale for implementing effective emission reduction strategies.
Citric Acid-Based Solutions as Decontaminant Mouthwash in Titanium and Dental Prostheses Materials in Implantoplasty Processes
Authors: Fernández-Garrido Pilar , Fernández-Dominguez Pedro , Fernández De La Fuente Laura , Manso De Gustin Barbara , Varona José Felipe , Bosch Begoña M. , Gil Javier , Fernández-Domínguez Manuel
Published: October 2024

The machining of implants and parts for dental prostheses to eliminate biofilm in the implantoplasty process causes a loss of mechanical properties and also characteristics of the surfaces, making tissue regeneration difficult. In the present work, treatments consisting of elements that can reduce infection, such as citric acid and magnesium, together with elements that can improve cell adhesion and proliferation, such as collagen, are proposed for implant–crown assembly. Titanium, zirconia, composite (PMMA + feldspar) and cobalt–chromium discs were immersed in four different solutions: 25% citric acid, 25% citric acid with the addition of collagen 0.25 g/L, 25% citric acid with the addition of 0.50 g/L and the latter with the addition of 1% Mg (NO3)2. After immersion was applied for 2 and 10 min, the roughness was determined by interferometric microscopy and the contact angle (CA) was evaluated. Human fibroblastic and osteoblastic line cells (HFFs and SaOS-2) were used to determine cell viability and proliferation capacity. Cell binding and cytotoxicity were determined by resazurin sodium salt assay (Alamar Blue) and cell morphology by confocal assay (immunofluorescence F-actin (phalloidin)) after 3 days of incubation. For the evaluation of bacterial activity, the bacterial strains Sptreptococcus gordonii (Gram+) and Pseudomonas aeruginosa (Gram−) were used. The antibacterial properties of the proposed treatments were determined by means of the resazurin sodium salt (Alamar Blue) assay after 1 day of incubation. The treatments considerably decreased the contact angle of the treated samples with respect to the control samples. The treatments endowed the surfaces of the samples with a hydrophilic/super-hydrophilic character. The combination of elements proposed for this study provided cell viability greater than 70%; considering the absence of cytotoxicity, it therefore promotes the adhesion and proliferation of fibroblasts and osteoblasts. In addition, it also endows the surface with antibacterial characteristics against from Gram+ and Gram− bacteria without damaging the cells. These results show that this mouthwash can be useful in oral applications to produce a new passivation layer that favors the hydrophilicity of the surface and promotes cellular activity for the formation of fibroblasts and osteoblasts, as well as showing bactericidal activity.
What Triggers Mental Disorders? Examining the Role of Increasing Relationships between Self-Regulatory Efficacy Expectations and Behavioral Intensity
Authors: Schetter Elisabeth (Lisa) , Schwinger Malte
Published: October 2024

Background: Extreme promotion and prevention focus (foci) of the value need can lead to mental disorders due to a reinforcement mechanism between efficacy expectations (EEs) and behavioral intensity (BI) that then sets in. A reliable measurement instrument capturing the onset of this reinforcement could facilitate disorder prevention. Additionally, the needs for truth and control may also trigger mental disorders in extremes of their foci, though these foci lack conceptualization. Thus, designing foci for each need, we developed both an item pool to assess EEs and BI of all foci across all needs and a procedure for compiling group-specific scales from it to capture EE–BI correlations for preventive purposes. We examined both the overall suitability of the pool and of the procedure to compile those scales from it that are reliable, valid, and most probably capable of capturing the EE–BI reinforcement onset in a specific group (here, our calibration sample, N = 198, 77% female). Methods: All eligible scales from the item pool were tested for cubic EE–BI correlations (high majorities of the expected cubic shape indicated item pool suitability), and those yielding the most cubic relationships were assessed in nonlinear PLS structural equation modeling with regard to their significance, reliability, and validity. Results: The item pool and procedure were largely suitable, producing reliable, valid scales where EEs significantly predicted BI cubically. Conclusions: The item pool and the method for identifying group-specific scales mark an important step toward better risk group identification. Further studies are needed to determine their actual predictive relevance for mental disorders.
Mental Imagery between Cognition and Emotion: A Narrative Review
Authors: Boccaccio Francesco Maria , Pennisi Alessia , Guerrera Claudia Savia , Platania Giuseppe Alessio , Torre Vittoria , Varrasi Simone , Vezzosi Venera Francesca , Coco Flavia , Castellano Sabrina , Pirrone Concetta
Published: October 2024

Mental imagery is a cognitive ability that enables individuals to simulate sensory experiences without external stimuli. This complex process involves generating, manipulating, and experiencing sensory perceptions. Despite longstanding interest, understanding its relationship with other cognitive functions and emotions remains limited. This narrative review aims to address this gap by exploring mental imagery’s associations with cognitive and emotional processes. It emphasizes the significant role of mental imagery on different cognitive functions, with a particular focus on learning processes in different contexts, such as school career, motor skill acquisition, and rehabilitation. Moreover, it delves into the intricate connection between mental imagery and emotions, highlighting its implications in psychopathology and therapeutic interventions. The review also proposes a comprehensive psychometric protocol to assess mental imagery’s cognitive and emotional dimensions, enabling a thorough evaluation of this complex construct. Through a holistic understanding of mental imagery, integrating cognitive and emotional aspects, researchers can advance comprehension and application in both research and clinical settings.
Biodegradation Studies of Biobased Mulch Films Reinforced with Cellulose from Waste Mango
Authors: Lorenzo Santiago Miguel Angel , Rendón Villalobos J. Rodolfo , Contreras Ramos Silvia Maribel , Pacheco Vargas Glenda , García Hernández Edgar
Published: October 2024

Excessive use of plastic mulches has triggered a series of environmental problems, primarily due to the large volumes generated and their low or non-existent degradability. For this reason, materials with similar characteristics to synthetic mulches but with a biodegradable character were sought. In this work, mulch films were produced from gelatin/glycerol/cellulose (GelC) and chitosan/glycerol/cellulose (ChiC). Their biodegradation time in soil and photographic analysis using scanning electron microscopy (SEM) were determined. The GelC sample presented a weight loss of 80% at 25 days, compared to 58% for the ChiC sample in the same exposure time. However, the latter was the only sample that could be evaluated up to 70 days, during which it presented its greatest weight loss (97%). The SEM results for both mulch films showed some color changes after 30 days; complete fracturing, growth of mycelium on the surface, and the presence of pores were observed. FTIR spectra revealed a decrease in hydroxyl groups, amides, and carbonyl bands as the number of degradation days increased. Obtaining polymers from waste materials, such as mango, represents an important task to obtain cellulose that can both reinforce and provide biodegradable properties to biobased materials, which can be degraded by microorganisms present in the soil.
Semi-Supervised Encrypted Malicious Traffic Detection Based on Multimodal Traffic Characteristics
Authors: Liu Ming , Yang Qichao , Wang Wenqing , Liu Shengli
Published: October 2024

The exponential growth of encrypted network traffic poses significant challenges for detecting malicious activities online. The scale of emerging malicious traffic is significantly smaller than that of normal traffic, and the imbalanced data distribution poses challenges for detection. However, most existing methods rely on single-category features for classification, which struggle to detect covert malicious traffic behaviors. In this paper, we introduce a novel semi-supervised approach to identify malicious traffic by leveraging multimodal traffic characteristics. By integrating the sequence and topological information inherent in the traffic, we achieve a multifaceted representation of encrypted traffic. We design two independent neural networks to learn the corresponding sequence and topological features from the traffic. This dual-feature extraction enhances the model’s robustness in detecting anomalies within encrypted traffic. The model is trained using a joint strategy that minimizes both the reconstruction error from the autoencoder and the classification loss, allowing it to effectively utilize limited labeled data alongside a large amount of unlabeled data. A confidence-estimation module enhances the classifier’s ability to detect unknown attacks. Finally, our method is evaluated on two benchmark datasets, UNSW-NB15 and CICIDS2017, under various scenarios, including different training set label ratios and the presence of unknown attacks. Our model outperforms other models by 3.49% and 5.69% in F1 score at labeling rates of 1% and 0.1%, respectively.
Diagnosis of Schizophrenia Using EEG Sensor Data: A Novel Approach with Automated Log Energy-Based Empirical Wavelet Reconstruction and Cepstral Features
Authors: Aziz Sumair , Khan Muhammad Umar , Iqtidar Khushbakht , Fernandez-Rojas Raul
Published: October 2024

Schizophrenia (SZ) is a severe mental disorder characterised by disruptions in cognition, behaviour, and perception, significantly impacting an individual’s life. Traditional SZ diagnosis methods are labour-intensive and prone to errors. This study presents an innovative automated approach for detecting SZ acquired through electroencephalogram (EEG) sensor signals, aiming to improve diagnostic efficiency and accuracy. We utilised Fast Independent Component Analysis to remove artefacts from raw EEG sensor data. A novel Automated Log Energy-based Empirical Wavelet Reconstruction (ALEEWR) technique was introduced to reconstruct decomposed modes based on their variability, ensuring effective extraction of meaningful EEG signatures. Cepstral-based features—cepstral activity, cepstral mobility, and cepstral complexity—were used to capture the power, rate of change, and irregularity of the cepstrum of preprocessed EEG signals. ANOVA-based feature selection was applied to refine these features before classification using the K-Nearest Neighbour (KNN) algorithm. Our approach achieved an exceptional accuracy of 99.4%, significantly surpassing previous methods. The proposed ALEEWR and cepstral analysis demonstrated high precision, sensitivity, and specificity in the automated diagnosis of schizophrenia. This study introduces a highly accurate and efficient method for SZ detection using EEG technology. The proposed techniques offer significant improvements in diagnostic accuracy, with potential implications for enhancing SZ diagnosis and patient care through automated systems.
A 3D-Printed Bi-Material Bragg-Based Reflectarray Antenna
Authors: Chekkar Walid , Lanteri Jerome , Malvaux Tom , Sourice Julien , Lizzi Leonardo , Migliaccio Claire , Ferrero Fabien
Published: October 2024

This paper presents a 3D-printed fully dielectric bi-material reflectarray with bandgap characteristics for multi-band applications. To achieve bandgap characteristics, a “1D Bragg reflector” unit cell is used. The latter is a layered structure characterized by a spatial distribution of refractive index that varies periodically along one dimension. By appropriately selecting the dimensions, the bandgap can be shifted to cover the desired frequency bands. To validate this bandgap characteristic, a (121.5 mm × 121.5 mm) with an f/D ratio of 0.5 reflectarray was fabricated. The measured gain at 27 GHz is 27.22 dBi, equivalent to an aperture efficiency of 35.05%, demonstrating good agreement between simulated and measured performances within the frequency range of 26–30 GHz. Additionally, the transparency of the reflectarray was verified by measuring the transmission coefficient, which exhibited a high level of transparency of 0.32 dB at 39 GHz. These features make the proposed reflectarray a good candidate for multi-band frequency applications.
Tracking the Risk of Cardiovascular Disease after Almond and Oat Milk Intervene or Statin Medication with a Powerful Reflex SH-SAW POCT Platform
Authors: Cheng Chia-Hsuan , Yatsuda Hiromi , Chen Han-Hsiang , Young Guang-Huar , Liu Szu-Heng , Wang Robert YL
Published: October 2024

Cardiovascular disease (CVD) represents the leading cause of death worldwide. For individuals at elevated risk for cardiovascular disease, early detection and monitoring of lipid status is imperative. The majority of lipid measurements conducted in hospital settings employ optical detection, which necessitates the use of relatively large-sized detection machines. It is, therefore, necessary to develop point-of-care testing (POCT) for lipoprotein in order to monitor CVD. To enhance the management and surveillance of CVD, this study sought to develop a POCT approach for apolipoprotein B (ApoB) utilizing a shear horizontal surface acoustic wave (SH-SAW) platform to assess the risk of heart disease. The platform employs a reflective SH-SAW sensor to reduce the sensor size and enhance the phase-shifted signals. In this study, the platform was utilized to monitor the impact of a weekly almond and oat milk or statins intervention on alterations in CVD risk. The SH-SAW ApoB test exhibited a linear range of 0 to 212 mg/dL, and a coefficient correlation (R) of 0.9912. Following a four-week intervention period, both the almond and oat milk intervention (−23.3%, p < 0.05) and statin treatment (−53.1%, p < 0.01) were observed to significantly reduce ApoB levels. These findings suggest that the SH-SAW POCT device may prove a valuable tool for monitoring CVD risk, particularly during routine daily or weekly follow-up visits.
Covert Communications in a Hybrid DF/AF Relay System
Authors: Moon Jihwan
Published: October 2024

In this paper, we study covert communications in a hybrid decode-and-forward (DF)/ amplify-and-forward (AF) relay system. The considered relay in normal operation forwards messages from a source node to a destination node in either DF or AF mode on request. Meanwhile, the source and destination nodes also attempt to secretly exchange covert messages such as confidential or sensitive information and avoid detection by the covert message detector embedded on the relay. We first establish an optimal DF/AF mode selection criterion to maximize the covert rate based on the analyses of delay-aware achievable covert rates of individual DF and AF modes. To further reduce the time complexity, we propose a low-complexity selection criterion as well for practical use. The numerical results demonstrate the covert rate gain as high as 50% and running time gain as high as 20% for particular system parameters, which verify the effectiveness of the proposed criteria.
Innovative Digital Phenotyping Method to Assess Body Representations in Autistic Adults: A Perspective on Multisensor Evaluation
Authors: Mourad Joanna , Daniels Kim , Bogaerts Katleen , Desseilles Martin , Bonnechère Bruno
Published: October 2024

In this perspective paper, we propose a novel tech-driven method to evaluate body representations (BRs) in autistic individuals. Our goal is to deepen understanding of this complex condition by gaining continuous and real-time insights through digital phenotyping into the behavior of autistic adults. Our innovative method combines cross-sectional and longitudinal data gathering techniques to investigate and identify digital phenotypes related to BRs in autistic adults, diverging from traditional approaches. We incorporate ecological momentary assessment and time series data to capture the dynamic nature of real-life events for these individuals. Statistical techniques, including multivariate regression, time series analysis, and machine learning algorithms, offer a detailed comprehension of the complex elements that influence BRs. Ethical considerations and participant involvement in the development of this method are emphasized, while challenges, such as varying technological adoption rates and usability concerns, are acknowledged. This innovative method not only introduces a novel vision for evaluating BRs but also shows promise in integrating traditional and dynamic assessment approaches, fostering a more supportive atmosphere for autistic individuals during assessments compared to conventional methods.
Traffic Flow Prediction in 5G-Enabled Intelligent Transportation Systems Using Parameter Optimization and Adaptive Model Selection
Authors: Vo Hanh Hong-Phuc , Nguyen Thuan Minh , Bui Khoi Anh , Yoo Myungsik
Published: October 2024

This study proposes a novel hybrid method, FVMD-WOA-GA, for enhancing traffic flow prediction in 5G-enabled intelligent transportation systems. The method integrates fast variational mode decomposition (FVMD) with optimization techniques, namely, the whale optimization algorithm (WOA) and genetic algorithm (GA), to improve the accuracy of overall traffic flow based on models tailored for each decomposed sub-sequence. The selected predictive models—long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU)—were considered to capture diverse temporal dependencies in traffic data. This research explored a multi-stage approach, where the decomposition, optimization, and selection of models are performed systematically to improve prediction performance. Experimental validation on two real-world traffic datasets further underscores the method’s efficacy, achieving root mean squared errors (RMSEs) of 152.43 and 7.91 on the respective datasets, which marks improvements of 3.44% and 12.87% compared to the existing methods. These results highlight the ability of the FVMD-WOA-GA approach to improve prediction accuracy significantly, reduce inference time, enhance system adaptability, and contribute to more efficient traffic management.
Dynamic Perviousness of Thrombi in Acute Ischemic Stroke Predicts Clinical Outcome after Reperfusion Therapy
Authors: Bertalan Gergely , Krepuska Miklos , Toth Daniel , Madjidyar Jawid , Thurner Patrick , Schubert Tilman , Kulcsar Zsolt
Published: October 2024

Background: Acute ischemic stroke (AIS) is one of the leading causes of death in the industrialized world and causes a heavy personal and economic burden. Thrombus perviousness, measured with pre-interventional computed tomography (CT), is a relatively new imaging biomarker with the potential to estimate clinical outcome in AIS and optimize therapy. However, reported findings on the relationship between thrombus perviousness and clinical parameters in AIS are conflicting. In this study, we investigated the characteristics of the time-resolved contrast agent uptake in thrombi and the predictive potential for clinical outcomes. Methods: We analyzed 55 AIS patients who underwent pre-interventional CT perfusion and recanalization with mechanical thrombectomy. A thrombus with a visible hyperdense artery sign was segmented in 2D. Thrombus standard perviousness was measured as the mean thrombus attenuation increase (TAI) between CT angiography (CTA) and NCCT. For dynamic perviousness, the time-resolved contrast agent uptake curve (CAU) was derived from a 30-phase CT perfusion (CTP) measurement. The rise time (trise) and the TAI increase rate per second (∆d), as well as the time window for the 10th (tW10), 20th (tW20), and 30th (tW30) percentiles of the CAU peak, were calculated. The standard and dynamic perviousness (trise, ∆d, tW10, tW20, and tW30) were analyzed for their associations with clinical outcomes (3-month mRS) with the Wilcoxon signed rank test. Results: Dynamic perviousness was associated with the clinical outcome. The group mean trise and ∆d for thrombi with good clinical outcomes (mRS ≤ 2) were approximately 20% lower (p = 0.04) and 36% higher (p = 0.02) than those for thrombi with poor outcomes (mRS > 2). The time windows for the 10, 20, and 30% maximum contrast agent concentrations in the thrombus were approximately 40% (p = 0.004), 18% (p = 0.02) and 33% (p = 0.004) lower in thrombi with good outcomes than in thrombi with poor outcomes, respectively. Standard perviousness showed no association with clinical outcome. Conclusion: Dynamic perviousness from perfusion imaging retrieves the CAU characteristics of thrombi with greater resolution detail than standard perviousness. Thrombi with relatively fast contrast agent uptake dynamics are more prone to good clinical outcomes than thrombi with slow uptake dynamics.
Risky Sexual Behaviors in Women and Their Relationship with Alcohol Consumption, Tobacco, and Academic Stress: A Multiple Correspondence Analysis Approach
Authors: Luna David , Vargas de la Cruz Ivette , Barrera Hernández Laura Fernanda , Figuerola Escoto Rosa Paola , Gómez Cotero Amalia Guadalupe , Toledano-Toledano Filiberto
Published: October 2024

University women are vulnerable to engaging in risky sexual behaviors (RSBs), which are related to academic stress, alcohol, and tobacco consumption. The aim of this study was to identify profiles of university women who associate RSBs with alcohol consumption, tobacco consumption level, and frequency of academic stress. A total of 534 female university students from Mexican universities answered an online questionnaire with five instruments related to their sexual behavior, alcohol consumption, tobacco consumption, and academic stress. They were studying to become professionals in health sciences, administration and social sciences, engineering, and “others” with grade point averages ranging from 5.7 to 10/10. They had to sign an informed consent and acknowledge having had at least one sexual relationship with anal or vaginal penetration before participating. A multiple correspondence analysis yielded a parsimonious solution with the following three dimensions that explained 38.60% of the variance: 1 “pregnancy”; 2 “number of sexual partners”; 3 “substance use”. Using a point cloud clustering strategy based on the Euclidean distance between categories in a two-dimensional space, five profiles were identified: Conservative and Prudent, Active Promiscuous, Vulnerable Reproductive Health, STI Risk, and Moderate Risk Behaviors. The estimation of ellipses with 95% confidence from the calculation of centroids allowed for the integration of two profiles: Lower probability of RSB and Higher probability of RSB. The contribution of academic stress was null with respect to the model solution, so this variable was discarded. The results identified particular risk profiles in female university students. These findings are useful for the development of differentiated intervention strategies to reduce RSB in this vulnerable group.
Video-Based Analysis of a Smart Lighting Warning System for Pedestrian Safety at Crosswalks
Authors: Pazzini Margherita , Cameli Leonardo , Vignali Valeria , Simone Andrea , Lantieri Claudio
Published: October 2024

This study analyses five months of continuous monitoring of different lighting warning systems at a pedestrian crosswalk through video surveillance cameras during nighttime. Three different light signalling systems were installed near a pedestrian crossing to improve the visibility and safety of vulnerable road users: in-curb LED strips, orange flashing beacons, and asymmetric enhanced LED lighting. Seven different lighting configurations of the three systems were studied and compared with standard street lighting. The speed of vehicles for each pedestrian–driver interaction was also evaluated. This was then compared to the speed that vehicles should maintain in order to stop in time and allow pedestrians to cross the road safely. In all of the conditions studied, speeds were lower than those maintained in the five-month presence of standard street lighting (42.96 km/h). The results show that in conditions with dedicated flashing LED lighting, in-curb LED strips, and orange flashing beacons, most drivers (72%) drove at a speed that allowed the vehicle to stop safely compared to standard street lighting (10%). In addition, with this lighting configuration, the majority of vehicles (85%) stopped at pedestrian crossings, while in standard street lighting conditions only 26% of the users stopped to give way to pedestrians.
Specializing When It Counts: Comparing the Dose–Time Effect of Distance Variety between Swimming and Track Running
Authors: Born Dennis-Peter , Ruiz-Navarro Jesús J. , Lorentzen Jenny , Björklund Glenn
Published: October 2024

Objective: To conduct a longitudinal retrospective analysis, explore the relationship between success at peak performance age and the number of different race distances athletes competed in each year (within-sport distance variety), and compare the dose–time effect of this distance variety throughout the development process between male swimmers and track runners. Methodology: Male swimmers (n = 6033) and track runners (n = 19,278) still competing at peak performance age were ranked, and the number of different race distances was extracted retrospectively for each year until early junior age (13–14-year-old category) from the databases of the European Aquatics and World Athletics federations. Firstly, correlation analysis determined the relationship between ranking at peak performance age and distance variety. Secondly, Poisson distribution provided the probability and dose–time effect of distance variety for becoming an international-class athlete at peak performance age. Results: Generally, correlation analysis revealed low coefficients (r ≤ 0.22) but significant effects (p < 0.001) for larger distance variety and success at peak performance age. Poisson distribution revealed the highest probability of becoming an international-class swimmer when competing in 2–4 race distances at junior age, depending on the primary race distance. The dose–time effect indicated a gradual reduction in the number of race distances as athletes approached peak performance age, narrowing down to 1–2, 2–3, and 3–4 distances for sprint, middle-, and long-distance races, respectively. Track runners exhibited a lower distance variety than swimmers, with a consistent optimum of 1–2 race distances across the age groups. Conclusions: The present findings including data of the most combined race distances for each primary race distance and a comparison between swimming and track running provide new background information to challenge traditional training regimes and help establish new strategies for long-term athlete development.
Supply Chain Relationships, Resilience, and Export Product Quality: Analysis Based on Supply Chain Concentration
Authors: Chen Renhao , Xu Helian
Published: October 2024

Supply chain security plays a critical role in ensuring the stable and continuous operation of society. Moreover, enhancing the quality of export products is crucial for improving environmental sustainability, as it helps reduce waste emissions and other related factors. Therefore, this paper employs data from Chinese A-share-listed companies and customs data from 2001 to 2015 to investigate this relationship. The main findings are as follows: (i) The supply chain concentration negatively impacts the quality of export products, a finding that remains robust after testing. (ii) In some firms, such as those where top executives possess digital-related expertise, the adverse effects of the supply chain concentration are likely mitigated. (iii) The channels through which the supply chain concentration affects export product quality may include firm size, productivity, and supply chain efficiency. (iv) Enhancements in infrastructure resilience, firm structure resilience, and industrial structure resilience through investments in regional fixed assets, overseas subsidiaries, and advancements in industrial structure, respectively, are likely to mitigate the negative impacts of the supply chain concentration. These conclusions may hold significant value for promoting both societal and environmental sustainability.
The Impact of Pollution and Carbon Emission Control on Financial Development, Environmental Quality, and Economic Growth: A Global Analysis
Authors: Ajeigbe Kola Benson , Ganda Fortune
Published: October 2024

The global environment has recently been facing sustainability threats owing to industrial and economic expansions. Accordingly, this study empirically examines the impact of carbon emissions and the directional causality between carbon emissions and environmental quality, financial development, and economic growth. We used data from 65 economies from 2010 to 2021, applying fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) approaches. Generally, the findings from the analysis revealed that the estimated coefficients of carbon emissions were negative and significant across the model, except for greenhouse gas emissions, which produced an insignificant result in developed economies. This result proves that an increase in carbon emissions and other forms of pollution are detrimental to environmental quality, economic growth, and financial development. Further results revealed that fossil fuels are positively and significantly related to the economic growth and financial development of selected countries. Empirical outcomes indicate that ineffective control of environmental pollution and carbon emissions is a major challenge to the economic growth trajectories of the selected countries, especially in emerging economies. The results from directional relationships revealed that bi-directional causality exists between CO2 and GDP; between total greenhouse gas emissions and economic growth, with no directional relationship of CO2 emissions to financial development and vice versa; and economic growth to CO2 emissions from gaseous fuel consumption and vice versa. Generally, this outcome indicates that improved environmental quality control can accelerate economic growth and financial development worldwide. This study provides insights to governments, policymakers, international organizations, researchers, and many other stakeholders. This study suggests that stricter fiscal and monetary policies, laws, and regulations, such as environmental taxes and carbon emission taxes, with strong implementation strategies, especially in emerging economies, are strongly recommended worldwide. Further recommendations suggest the development of technologically innovative policies that can counter all the impacts of devastating human activities on the environment, and these are encouraged. A greater consumption of renewable energy and the use of other innovative machines that are environmentally friendly and can help control various forms of pollution and carbon emissions have been encouraged globally.
Influence of the Configuration of Airport Security Control Systems on the Implementation of Assumptions of the Sustainable Development Policy
Authors: Kierzkowski Artur , Ryczyński Jacek , Kisiel Tomasz , Mardeusz Ewa
Published: October 2024

Research by scientists dealing with sustainable development issues in the aviation industry security focuses on finding solutions that constitute the so-called ‘golden mean’ between appropriate efficiency and high levels of system safety and reliability (including human reliability). The features mentioned above have been repeatedly investigated in various studies, but always individually—to date, no one has proposed a solution indicating the balance point of all the abovementioned features. Here we propose a solution to this research gap: a model for assessing the configuration of airport security control systems. The model allows for the optimal configuration of airport security control systems. The multi-level model validation presented in the article was performed, among others, based on one of the airports in Poland, and showed that the correct configuration of the system can bring energy savings of 913,500 kWh/year in the case of large international airports. Additionally, the article discusses all solutions and modern technologies equipped with devices supporting the passenger and baggage screening process.
Sustainable Modernization of Wastewater Treatment Plants
Authors: Makisha Nikolay , Gulshin Igor
Published: October 2024

This analytical study was conducted on the basis of statistical data from the Russian Federation and technological requirements for WWTP operation. As a case study, a virtual WWTP, which serves a residential area of 31,500 PE (personal equivalent), was considered to solve a task of their potential upgrade. According to the initial data, within modernization, the existing infrastructure of the WWTP should be considered in order to receive wastewater with a reduced flow rate and increased values of pollutant concentrations. Within the analysis, treatment efficiency should correspond to current regulations. Special focus was put on secondary treatment facilities, as they ensure the removal of major contaminants (organic pollution) and nutrients (nitrogen and phosphorus). The results showed that even in the case of a lower flow rate, higher pollutant concentrations demanded a doubled volume of activated sludge reactor to provide the required efficiency. An increase in oxidizing capacity may be ensured through the growth of mixed liquor suspended solids (MLSS) value with simultaneous transition from gravity to membrane sludge separation. A study revealed that an MLSS raised from 3 to 8 g/L allows treatment in the existing tanks to be performed with necessary efficiency. In this case, significant costs for the purchase of membranes are offset by the need for zero additional construction. On the other hand, such a transition leads to an increase in operating costs of 60% (from EUR 0.078 to EUR 0.12/(m3/d)).
Pricing Strategies for O2O Catering Merchants Considering Reference Price Effects and Unconditional Coupons
Authors: Ma Huixian , Xie Jiqing , Dai Debao , Xie Jiaping
Published: October 2024

Coupon marketing is an important promotion model for the O2O catering supply chain. As a well-known catering O2O platform in China, Meituan provides its members with the opportunity to buy unconditional coupons at low prices, and it is very popular with consumers. It is worth studying how catering merchants develop pricing and promotion strategies considering consumers’ reference price effects in two scenarios: participating and not participating in coupon stacking (S-PICS/S-NPICS). In order to explore the pricing mechanism of meals, two models using Stackelberg games are established considering some exogenous variables, such as commission rate, reference price, and sensitivity of consumers to coupon prices. The results show that (1) the reference price has a great influence on the maximum profits of catering merchants, varying in different scenarios; (2) in S-NPICS, the merchants’ maximum profit increases with an increase in the reference price, while, in S-PICS, an increase in the reference price leads to a decrease in merchants’ maximum profit; (3) the profit of merchants in S-PICS is higher than that in S-NPICS, indicating that merchants can benefit from coupon stacking; (4) when the commission rate of the coupons increases, the merchants in both S-PICS and S-NPICS should raise their online meal prices to obtain higher profits. This study provides a balanced reference for pricing strategies and coupon promotion strategies in different scenarios through the use of deduction and simulation methods, which is conducive to the sustainable development of the O2O catering supply chain. As consumers enjoy using these coupons, including unconditional ones, it is suggested that merchants and Meituan should focus on coupon promotion and develop better dining pricing strategies.
MRACNN: Multi-Path Residual Asymmetric Convolution and Enhanced Local Attention Mechanism for Industrial Image Compression
Authors: Yan Zikang , Liu Peishun , Wang Xuefang , Gao Haojie , Ma Xiaolong , Hu Xintong
Published: October 2024

The rich information and complex background of industrial images make it a challenging task to improve the high compression rate of images. Current learning-based image compression methods mostly use customized convolutional neural networks (CNNs), which find it difficult to cope with the complex production background of industrial images. This causes useful information to be lost in the abundance of irrelevant data, making it difficult to accurately extract important features during the feature extraction stage. To address this, a Multi-path Residual Asymmetric Convolutional Compression Network (MRACNN) is proposed. Firstly, a Multi-path Residual Asymmetric Convolution Block (MRACB) is introduced, which includes the Multi-path Residual Asymmetric Convolution Down-sampling Module for down-sampling in the encoder to extract key features, and the Mult-path Residual Asymmetric Convolution Up-sampling Module for up-sampling in the decoder to recover details and reconstruct the image. This feature transfer and information flow enables the better capture of image details and important information, thereby improving the quality and efficiency of image compression and decompression. Furthermore, a two-branch enhanced local attention mechanisms, and a channel-squeezing entropy model based on the compression-based enhanced local attention module is proposed to enhance the performance of the modeled compression. Extensive experimental evaluations demonstrate that the proposed method outperforms state-of-the-art techniques, achieves superior Rate–Distortion Performance, and excels in preserving local details.