bluuebunny/crossref_metadata_2025 huggingface dataset:
Unemployment Rate Prediction Using a Hybrid Model of Recurrent Neural Networks and Genetic Algorithms
Authors: Mero Kevin , Salgado Nelson , Meza Jaime , Pacheco-Delgado Janeth , Ventura Sebastián
Published: April 2024

Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to make short-term estimates, assess economic health, and make informed monetary policy decisions. This paper proposes the innovative GA-LSTM method, which fuses an LSTM neural network with a genetic algorithm to address challenges in unemployment prediction. Effective parameter determination in recurrent neural networks is crucial and a well-known challenge. The research uses the LSTM neural network to overcome complexities and nonlinearities in unemployment predictions, complementing it with a genetic algorithm to optimize the parameters. The central objective is to evaluate recurrent neural network models by comparing them with GA-LSTM to identify the most appropriate model for predicting unemployment in Ecuador using monthly data collected by various organizations. The results demonstrate that the hybrid GA-LSTM model outperforms traditional approaches, such as BiLSTM and GRU, on various performance metrics. This finding suggests that the combination of the predictive power of LSTM with the optimization capacity of the genetic algorithm offers a robust and effective solution to address the complexity of predicting unemployment in Ecuador.
Assessment of Sugar-Related Dietary Patterns to Personality Traits and Cognitive–Behavioural and Emotional Functioning in Working-Age Women
Authors: Garbacz Agnieszka , Stelcer Bogusław , Wielgosik Michalina , Czlapka-Matyasik Magdalena
Published: April 2024

This cross-sectional study investigated interactions among sugar-related dietary patterns (DPs), personality traits, and cognitive–behavioural and emotional functioning. The study involved working-age women aged 18–54. Data were collected between Winter and Spring of 2020/21. The survey was conducted using anonymised questionnaires. The ten-item personality inventory (TIPI-PL) was used to examine personality traits based on the Big Five personality trait model. A three-factor eating questionnaire (TFEQ-13) was used to measure the following eating behaviours: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE). The KomPAN questionnaire collected the frequency of the intake. Dietary patterns (DPs) were derived by principal component analysis (PCA). A logistic regression (OR) was applied to verify the associations among the DPs, personality traits, and cognitive–behavioural and emotional functioning. Three DPs were identified: sweet-Western (SWDP), pro-healthy (PHDP), and dairy (DDP). Women with high conscientiousness were less likely, by 33%, to adhere to the upper tercile of the SWDP and 80% more likely to the upper tercile of the PHDP. Elevated CR intensity increased by almost twofold (OR: 1.93; p < 0.001) the likelihood of high adherence to the SWDP. The high intensity in the EE decreased by 37% (OR: 0.63; p < 0.01) the likelihood of increased adherence to the SWDP. Personality traits and eating behaviours significantly correlated with the extracted SWDP.
Phase Separation Study on the Storage of Technically Specification Natural Rubber Modified Bitumen
Authors: Ibrahim Bahruddin , Wiranata Arya , Zahrina Ida , Sentosa Leo , Nasruddin Nasruddin , Muharam Yuswan
Published: April 2024

Overloading and climate change are often problems in pavement structures. For this reason, hard asphalt binders have high softening points, are elastic, and have good adhesion, which is needed to improve pavement performance. Asphalt binder performance can be enhanced by adding additives such as natural rubber or natural-rubber-modified asphalt. However, natural-rubber-modified asphalt shows poor storage stability problems. This is due to differences in density and viscosity between the constituent components of natural-rubber-modified asphalt. This study examines the phase separation mechanism in technically specified natural rubber (TSNR) modified asphalt. Prediction of the optimum storage length of modified asphalt before phase separation occurs, using a combined incompressible Navier–Stokes and phase field model and carried out with COMSOL Multiphysics software version 5.5. Experimental validation was conducted at TSNR levels of 8, 10, and 12% at 160 °C for 48 h, with and without sulfur. The simulation showed that the asphalt modified with TSNR experienced phase separation after 12 h of storage at 160 °C under conditions without stirring. This aligns with the experimental results, which showed phase separation at 160 °C after 48 h. Adding sulfur additives did not have much effect on improving storage stability. The combined incompressible Navier–Stokes and phase field model accurately describes the phase separation in TSNR-modified asphalt. The results of this research recommend that the industry store natural-rubber-modified asphalt in a constantly stirred condition to prevent phase separation of modified asphalt. In addition, the results of this research help the industry predict or increase the homogeneity of polymer-modified asphalt production and save time and costs.
Rotational Convolution Design in Convolutional Neural Networks for Direct 3D Electromagnetic Tomography
Authors: Zhao Pengfei , Liu Ze
Published: April 2024

The three-dimensional (3D) reconstruction of Electromagnetic Tomography (EMT) is an important task for many applications, such as the non-destructive testing of inner defects in rail systems. Additionally, image reconstruction algorithms utilizing deep learning methods have been verified to be useful in recent years. Therefore, the interpretability of deep learning is a question that is relevant to its application in other areas. This paper proposes an innovative rotational convolution pattern, Conv-P, for convolutional neural network (CNN) image reconstruction in a 3D EMT system. This pattern is based on the projection relationships inherent in tomographic imaging, where each convolution is performed on adjacent projections along the excitation rotation direction. The advantage of this pattern is that it can generate the convolution process by utilizing the 3D structural information from real sensors. To verify the effectiveness of this convolution pattern, we constructed a 3D dual-layer 16-coil EMT model and tested its image reconstruction performance. The results demonstrate that, compared with two common convolution patterns, Conv-P achieves a 4.7% and 4.1% increase in the Image Correlation Coefficient (CC), a 19.8% and 13.1% reduction in the Relative Image Error (IE), a 0.67% and 1.59% increase in the Peak Signal-to-Noise Ratio (PSNR), and a 3.24% and 0.74% increase in the Structural Similarity Index Measure (SSIM).
The Influence of the Matrix Grain Size and Mineral Addition on Improving the Knock-Out Properties of Molding Sands with an Inorganic Binder
Authors: Bobrowski Artur , Drożyński Dariusz , Grabowska Beata
Published: April 2024

This article presents the results of tests of molding and core sands with inorganic binders incorporating a mineral in the form of raw perlite ore. This material serves to reduce the final strength, thereby improving the knock-out properties. The assumption was made that the selection of the optimal fraction of the loosening additive, tailored to the grain size of the matrix of the molding sand used in foundries, could significantly affect its mechanical and technological parameters. The tests were conducted on molding sands prepared using three quartz sands with the addition of perlite ore of different grain sizes. In addition to determining the final tensile strength, the permeability and grindability of the molding sands were assessed. The results indicated that the raw perlite ore significantly reduced the final strength of the molding sands in each considered system, with the best efficiency achieved when using finer fractions. Moreover, the mineral’s addition had a minor impact on the technological properties of the molding sands, such as permeability and grindability.
Provably Secure ECC-Based Anonymous Authentication and Key Agreement for IoT
Authors: Hu Shunfang , Jiang Shaoping , Miao Qing , Yang Fan , Zhou Weihong , Duan Peng
Published: April 2024

With the rise of the Internet of Things (IoT), maintaining data confidentiality and protecting user privacy have become increasingly challenging. End devices in the IoT are often deployed in unattended environments and connected to open networks, making them vulnerable to physical tampering and other security attacks. Different authentication key agreement (AKA) schemes have been used in practice; several of them do not cover the necessary security features or are incompatible with resource-constrained end devices. Their security proofs have been performed under the Random-Oracle model. We present an AKA protocol for end devices and servers. The proposal leverages the ECC-based key exchange mechanism and one-way hash function-based message authentication method to achieve mutual authentication, user anonymity, and forward security. A formal security proof of the proposed scheme is performed under the standard model and the eCK model with the elliptic curve encryption computational assumptions, and formal verification is performed with ProVerif. According to the performance comparison, it is revealed that the proposed scheme offers user anonymity, perfect forward security, and mutual authentication, and resists typical attacks such as ephemeral secret leakage attacks, impersonation attacks, man-in-the-middle attacks, and key compromise impersonation attacks. Moreover, the proposed scheme has the lowest computational and communication overhead compared to existing schemes.
i-ISSUES—Industrial-Interoperable Safe and Secure Urban Energy Systems
Authors: Pastor Raúl , Fraga Anabel , Larrañeta José Javier
Published: April 2024

Urban planners are involved in designing future urban energy systems as a part of their path toward decarbonization or Net Zero targets before 2050. In this process, new energy and information flows between industrial and urban regions should be considered, as well as safety and security managerial aspects regarding the existing and new infrastructures. This research aims to help engineering professionals and public planners define new collaboration dynamics to make industrial energy systems safer, more secure, and interoperable, surpassing the existing knowledge. Firstly, several recent R&D aspects are analyzed, demonstrating the organizational gap and providing early integration or knowledge reuse opportunities from R&D projects. After that, the authors present a model called Industrial-Interoperable Safe and Secure Urban Energy Systems (i-ISSUES), a multi-disciplinary approach combining classic urban energy planning, information technology use, safety and security management, and systems engineering as the integrated disciplines. The model detects research trends, providing a first set of readings with some improvements.
A Method for Underwater Biological Detection Based on Improved YOLOXs
Authors: Wang Heng , Zhang Pu , You Mengnan , You Xinyuan
Published: April 2024

This article proposes a lightweight underwater biological target detection network based on the improvement of YOLOXs, addressing the challenges of complex and dynamic underwater environments, limited memory in underwater devices, and constrained computational capabilities. Firstly, in the backbone network, GhostConv and GhostBottleneck are introduced to replace standard convolutions and the Bottleneck1 structure in CSPBottleneck_1, significantly reducing the model’s parameter count and computational load, facilitating the construction of a lightweight network. Next, in the feature fusion network, a Contextual Transformer block replaces the 3 × 3 convolution in CSPBottleneck_2. This enhances self-attention learning by leveraging the rich context between input keys, improving the model’s representational capacity. Finally, the positioning loss function Focal_EIoU Loss is employed to replace IoU Loss, enhancing the model’s robustness and generalization ability, leading to faster and more accurate convergence during training. Our experimental results demonstrate that compared to the YOLOXs model, the proposed YOLOXs-GCE achieves a 1.1% improvement in mAP value, while reducing parameters by 24.47%, the computational load by 26.39%, and the model size by 23.87%. This effectively enhances the detection performance of the model, making it suitable for complex and dynamic underwater environments, as well as underwater devices with limited memory. The model meets the requirements of underwater target detection tasks.
Use of Bottom Ash from a Thermal Power Plant and Lime to Improve Soils in Subgrades and Road Embankments
Authors: Vega-Zamanillo Ángel , López-López Leticia , López-López Esteban , Calzada-Pérez Miguel Ángel
Published: April 2024

The present study has focused on stabilizing the soils of the embankments and improving the mechanical properties of gravel in subbases of pavements with different contents of bottom ash from thermal power plants and low percentages of lime. The density, humidity, simple resistance strength and bearing capacity of the new materials resulting from this combination have been studied. The results indicated that the optimal proportion of bottom ash added to the analyzed soil is 15%, while the optimal addition of lime is 1% for application in embankments and 2% for application in road subgrades. In clay soil that has a low simple resistance strength when 25% of bottom ash is added without lime, it can double the resistance. In the case of the gravel evaluated, it was found that the optimal ratio between the addition of bottom ash and lime is 6.5. In conclusion, it can be noted that soil that does not have any resistance when certain percentages of bottom ash are added, its properties are improved to be used in embankments.
Contrails and Their Dependence on Meteorological Situations
Authors: Kameníková Iveta , Nagy Ivan , Hospodka Jakub
Published: April 2024

Contrails created by aircraft are a very hot topic today because they contribute to the warming of the atmosphere. Air traffic density is very high, and current forecasts predict a further significant increase. Increased air traffic volume is associated with an increased occurrence of contrails and induced cirrus clouds. The scientific level of contrails and their impact on the Earth’s climate is surprisingly low. The scientific studies published so far are mainly based on global models, in situ measurements, and satellite observations of contrails. The research is based on observations of contrails in flight paths in the vicinity of Děčín and Prague, and the collection of flight and meteorological data. It focused on the influence of the meteorological situation on the formation of persistent contrails. The collected data on contrails and meteorological variables were statistically processed using machine learning methods for classification models. Several models were developed to predict and simulate the properties of contrails as a function of given air traffic and meteorological conditions. The Random Forests model produced the best results. Dependencies between meteorological conditions, formation, and contrail lifetime were found. The aim of the study was to identify the possibility of using available meteorological data to predict persistent contrails.
An Assessment of the Coupled Weather Research and Forecasting Hydrological Model on Streamflow Simulations over the Source Region of the Yellow River
Authors: Chen Yaling , Wen Jun , Meng Xianhong , Zhang Qiang , Li Xiaoyue , Zhang Ge , Chen Run
Published: April 2024

The Source Region of the Yellow River (SRYR), renowned as the “Water Tower of the Yellow River”, serves as an important water conservation domain in the upper reaches of the Yellow River, significantly influencing water resources within the basin. Based on the Weather Research and Forecasting (WRF) Model Hydrological modeling system (WRF-Hydro), the key variables of the atmosphere–land–hydrology coupling processes over the SRYR during the 2013 rainy season are analyzed. The investigation involves a comparative analysis between the coupled WRF-Hydro and the standalone WRF simulations, focusing on the hydrological response to the atmosphere. The results reveal the WRF-Hydro model’s proficiency in depicting streamflow variations over the SRYR, yielding Nash Efficiency Coefficient (NSE) values of 0.44 and 0.61 during the calibration and validation periods, respectively. Compared to the standalone WRF simulations, the coupled WRF-Hydro model demonstrates enhanced performance in soil heat flux simulations, reducing the Root Mean Square Error (RMSE) of surface soil temperature by 0.96 K and of soil moisture by 0.01 m3/m3. Furthermore, the coupled model adeptly captures the streamflow variation characteristics with an NSE of 0.33. This underscores the significant potential of the coupled WRF-Hydro model for describing atmosphere–land–hydrology coupling processes in regions characterized by cold climates and intricate topography.
A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia
Authors: Taylor Rachel , Marshall Andrew G. , Crimp Steven , Cary Geoffrey J. , Harris Sarah
Published: April 2024

The increasing frequency and duration of severe fire events in Australia further necessitate accurate and timely forecasting to mitigate their consequences. This study evaluated the performance of two distinct approaches to forecasting extreme fire danger at two- to three-week lead times for the period 2003 to 2017: the official Australian climate simulation dynamical model and a statistical model based on climate drivers. We employed linear logistic regression to develop the statistical model, assessing the influence of individual climate drivers using single linear regression. The performance of both models was evaluated through case studies of three significant extreme fire events in Australia: the Canberra (2003), Black Saturday (2009), and Pinery (2015) fires. The results revealed that ACCESS-S2 generally underestimated the spatial extent of all three extreme FBI events, but with accuracy scores ranging from 0.66 to 0.86 across the case studies. Conversely, the statistical model tended to overpredict the area affected by extreme FBI, with high false alarm ratios between 0.44 and 0.66. However, the statistical model demonstrated higher probability of detection scores, ranging from 0.57 to 0.87 compared with 0.03 to 0.57 for the dynamic model. These findings highlight the complementary strengths and limitations of both forecasting approaches. Integrating dynamical and statistical models with transparent communication of their uncertainties could potentially improve accuracy and reduce false alarms. This can be achieved through hybrid forecasting, combined with visual inspection and comparison between the statistical and dynamical forecasts. Hybrid forecasting also has the potential to increase forecast lead times to up to several months, ultimately aiding in decision-making and resource allocation for fire management.
Generalized Limit Theorem for Mellin Transform of the Riemann Zeta-Function
Authors: Laurinčikas Antanas , Šiaučiūnas Darius
Published: April 2024

In the paper, we prove a limit theorem in the sense of the weak convergence of probability measures for the modified Mellin transform Z(s), s=σ+it, with fixed 1/2<σ<1, of the square |ζ(1/2+it)|2 of the Riemann zeta-function. We consider probability measures defined by means of Z(σ+iφ(t)), where φ(t), t⩾t0>0, is an increasing to +∞ differentiable function with monotonically decreasing derivative φ′(t) satisfying a certain normalizing estimate related to the mean square of the function Z(σ+iφ(t)). This allows us to extend the distribution laws for Z(s).
The Expression of Serglycin Is Required for Active Transforming Growth Factor β Receptor I Tumorigenic Signaling in Glioblastoma Cells and Paracrine Activation of Stromal Fibroblasts via CXCR-2
Authors: Manou Dimitra , Golfinopoulou Maria-Angeliki , Alharbi Sara Naif D. , Alghamdi Hind A. , Alzahrani Fatimah Mohammed , Theocharis Achilleas D.
Published: April 2024

Serglycin (SRGN) is a pro-tumorigenic proteoglycan expressed and secreted by various aggressive tumors including glioblastoma (GBM). In our study, we investigated the interplay and biological outcomes of SRGN with TGFβRI, CXCR-2 and inflammatory mediators in GBM cells and fibroblasts. SRGN overexpression is associated with poor survival in GBM patients. High SRGN levels also exhibit a positive correlation with increased levels of various inflammatory mediators including members of TGFβ signaling pathway, cytokines and receptors including CXCR-2 and proteolytic enzymes in GBM patients. SRGN-suppressed GBM cells show decreased expressions of TGFβRI associated with lower responsiveness to the manipulation of TGFβ/TGFβRI pathway and the regulation of pro-tumorigenic properties. Active TGFβRI signaling in control GBM cells promotes their proliferation, invasion, proteolytic and inflammatory potential. Fibroblasts cultured with culture media derived by control SRGN-expressing GBM cells exhibit increased proliferation, migration and overexpression of cytokines and proteolytic enzymes including CXCL-1, IL-8, IL-6, IL-1β, CCL-20, CCL-2, and MMP-9. Culture media derived by SRGN-suppressed GBM cells fail to induce the above properties to fibroblasts. Importantly, the activation of fibroblasts by GBM cells not only relies on the expression of SRGN in GBM cells but also on active CXCR-2 signaling both in GBM cells and fibroblasts.
On Interactions of Sulfamerazine with Cyclodextrins from Coupled Diffusometry and Toxicity Tests
Authors: Sofio Sara P. C. , Caeiro André , Ribeiro Ana C. F. , Cabral Ana M. T. D. P. V. , Valente Artur J. M. , Canhoto Jorge , Esteso Miguel A.
Published: April 2024

This scientific study employs the Taylor dispersion technique for diffusion measurements to investigate the interaction between sulfamerazine (NaSMR) and macromolecular cyclodextrins (β-CD and HP-β-CD). The results reveal that the presence of β-CD influences the diffusion of the solution component, NaSMR, indicating a counterflow of this drug due to solute interaction. However, diffusion data indicate no inclusion of NaSMR within the sterically hindered HP-β-CD cavity. Additionally, toxicity tests were conducted, including pollen germination (Actinidia deliciosa) and growth curve assays in BY-2 cells. The pollen germination tests demonstrate a reduction in sulfamerazine toxicity, suggesting potential applications for this antimicrobial agent with diminished adverse effects. This comprehensive investigation contributes to a deeper understanding of sulfamerazine–cyclodextrin interactions and their implications for pharmaceutical and biological systems.
Hyaluronic Acid Prevents Fusion of Brain Tumor-Derived Spheroids and Selectively Alters Their Gene Expression Profile
Authors: Arutyunyan Irina , Soboleva Anna , Balchir Dorzhu , Jumaniyazova Enar , Kudelkina Vera , Elchaninov Andrey , Fatkhudinov Timur
Published: April 2024

Hyaluronic acid (HA), a major glycosaminoglycan of the brain extracellular matrix, modulates cell behaviors through binding its receptor, Cd44. In this study, we assessed the influence of HA on high-grade brain tumors in vitro. The model comprised cell cultures derived from six rodent carcinogen-induced brain tumors, forming 3D spheroids prone to spontaneous fusion. Supplementation of the standard culture medium with 0.25% HA significantly inhibited the fusion rates, preserving the shape and size uniformity of spheroids. The 3D cultures were assigned to two groups; a Cd44lo group had a tenfold decreased relative expression of Cd44 than another (Cd44hi) group. In addition, these two groups differed by expression levels of Sox2 transcription factor; the correlation analysis revealed a tight negative association for Cd44 and Sox2. Transcriptomic responses of spheroids to HA exposure also depended on Cd44 expression levels, from subtle in Cd44lo to more pronounced and specific in Cd44hi, involving cell cycle progression, PI3K/AKT/mTOR pathway activation, and multidrug resistance genes. The potential HA-induced increase in brain tumor 3D models’ resistance to anticancer drug therapy should be taken into account when designing preclinical studies using HA scaffold-based models. The property of HA to prevent the fusion of brain-derived spheroids can be employed in CNS regenerative medicine and experimental oncology to ensure the production of uniform, controllably fusing neurospheres when creating more accurate in vitro brain models.
Analyzing Patterns of Service Utilization Using Graph Topology to Understand the Dynamic of the Engagement of Patients with Complex Problems with Health Services
Authors: Bambi Jonas , Santoso Yudi , Moselle Ken , Robertson Stan , Rudnick Abraham , Chang Ernie , Kuo Alex
Published: April 2024

Background: Providing care to persons with complex problems is inherently difficult due to several factors, including the impacts of proximal determinants of health, treatment response, the natural emergence of comorbidities, and service system capacity to provide timely required services. Providing visibility into the dynamics of patients’ engagement can help to optimize care for patients with complex problems. Method: In a previous work, graph machine learning and NLP methods were used to model the products of service system dynamics as atemporal entities, using a data model that collapsed patient encounter events across time. In this paper, the order of events is put back into the data model to provide topological depictions of the dynamics that are embodied in patients’ movement across a complex healthcare system. Result: The results show that directed graphs are well suited to the task of depicting the way that the diverse components of the system are functionally coupled—or remain disconnected—by patient journeys. Conclusion: By setting the resolution on the graph topology visualization, important characteristics can be highlighted, including highly prevalent repeating sequences of service events readily interpretable by clinical subject matter experts. Moreover, this methodology provides a first step in addressing the challenge of locating potential operational problems for patients with complex issues engaging with a complex healthcare service system.
Colorimetric and Electrochemical Dual-Mode Detection of Thioredoxin 1 Based on the Efficient Peroxidase-Mimicking and Electrocatalytic Property of Prussian Blue Nanoparticles
Authors: Kim Jeong Un , Kim Jee Min , Thamilselvan Annadurai , Nam Ki-Hwan , Kim Moon Il
Published: April 2024

As a potent detection method for cancer biomarkers in physiological fluid, a colorimetric and electrochemical dual-mode sensing platform for breast cancer biomarker thioredoxin 1 (TRX1) was developed based on the excellent peroxidase-mimicking and electrocatalytic property of Prussian blue nanoparticles (PBNPs). PBNPs were hydrothermally synthesized using K3[Fe(CN)6] as a precursor and polyvinylpyrrolidone (PVP) as a capping agent. The synthesized spherical PBNPs showed a significant peroxidase-like activity, having approximately 20 and 60% lower Km values for 3,3′,5,5′-tetramethylbenzidine (TMB) and H2O2, respectively, compared to those of horseradish peroxidase (HRP). The PBNPs also enhanced the electron transfer on the electrode surface. Based on the beneficial features, PBNPs were used to detect target TRX1 via sandwich-type immunoassay procedures. Using the strategies, TRX1 was selectively and sensitively detected, yielding limit of detection (LOD) values as low as 9.0 and 6.5 ng mL−1 via colorimetric and electrochemical approaches, respectively, with a linear range of 10–50 ng mL−1 in both strategies. The PBNP-based TRX1 immunoassays also exhibited a high degree of precision when applied to real human serum samples, demonstrating significant potentials to replace conventional HRP-based immunoassay systems into rapid, robust, reliable, and convenient dual-mode assay systems which can be widely utilized for the identification of important target molecules including cancer biomarkers.
Independence Threat or Interdependence Threat? The Focusing Effect on Social or Physical Threat Modulates Brain Activity
Authors: Wang Guan , Ma Lian , Wang Lili , Pang Weiguo
Published: April 2024

Objective: The neural basis of threat perception has mostly been examined separately for social or physical threats. However, most of the threats encountered in everyday life are complex. The features of interactions between social and physiological threats under different attentional conditions are unclear. Method: The present study explores this issue using an attention-guided paradigm based on ERP techniques. The screen displays social threats (face threats) and physical threats (action threats), instructing participants to concentrate on only one type of threat, thereby exploring brain activation characteristics. Results: It was found that action threats did not affect the processing of face threats in the face-attention condition, and electrophysiological evidence from the brain suggests a comparable situation to that when processing face threats alone, with higher amplitudes of the N170 and EPN (Early Posterior Negativity) components of anger than neutral emotions. However, when focusing on the action-attention condition, the brain was affected by face threats, as evidenced by a greater N190 elicited by stimuli containing threatening emotions, regardless of whether the action was threatening or not. This trend was also reflected in EPN. Conclusions: The current study reveals important similarities and differences between physical and social threats, suggesting that the brain has a greater processing advantage for social threats.
Can Positive Social Contact Encourage Residents’ Community Citizenship Behavior? The Role of Personal Benefit, Sympathetic Understanding, and Place Identity
Authors: Wang Yaxi , Wu Bo , Li Jiaqi , Yuan Qing , Chen Nan
Published: April 2024

Identified as an increasingly pivotal aspect, the benevolent extra-role characteristic of community citizenship behavior contributes to destination development efficiency and social cohesion. Based on the egoistic–altruistic motivation framework, this study investigated three motivations that propel residents to exercise community citizenship behaviors in a positive social contact context, namely self-focused, other-focused, and place-focused motivation. A conceptual model combined with positive contact, personal benefit, sympathetic understanding, place identity, and community citizenship behavior was developed and tested using partial least squares structural equation modeling (PLS-SEM) through data from 366 residents in Kaifeng, China. The findings showed that of the three motivations for community citizenship behaviors, place identity contributed the most, and personal benefits failed to predict community citizenship behaviors. Furthermore, sympathetic understanding with tourists was most fostered by residents from the perception of positive contact with tourists. These findings offer a novel theoretical framework for scholarly investigation and provide practical insights for tourism managers regarding strategies to influence residents’ community citizenship behavior.
Seismic Damage Probability Assessment of Existing Reinforced Concrete School Buildings in Afghanistan
Authors: Sharafi Sayed Qudratullah , Saito Taiki
Published: April 2024

Existing Reinforced Concrete School buildings with low earthquake resistance may suffer structural failure or severe damage in a catastrophic seismic event. Ascertaining earthquake resistance in existing school buildings is vital to confirming the safety of students, teachers, and all school members. Reinforced concrete (RC) has been used significantly for numerous years as the primary material due to its easy access and low cost-effectiveness in construction. The current research focused on analyzing the existing RC school buildings designed and constructed in various regions of Afghanistan over the last three decades. Seismic fragility curves, which are generated from incremental dynamic analysis (IDA), have been used to evaluate the damage probability of RC school buildings against earthquake ground motions. In this investigation, 34 RC school buildings were selected from an extensive database and subsequently classified as either A-type or B-type based on specific criteria, including design details and construction year. Following this classification, an assessment of the seismic damage probability for these buildings was conducted using probabilistic models based on IDA curves. The results indicate that A-type school buildings with newer construction are less prone to damage compared to B-type school buildings, showing improved resilience. Especially the B-type buildings in seismic Zone-I are found to be highly vulnerable under the maximum considered earthquake scenarios.
Analytical Solution for the Steady Seepage Field of a Foundation Pit in an Anisotropic Layer
Authors: Zeng Yulin , Yang Xinxin , Zhang Chi , Yu Jun
Published: April 2024

The soil piping and drift sand phenomenon is one of the catastrophic failure forms in foundation pit excavations in coastal buildings. Presently, there is a deficiency in the theoretical research regarding the seepage fields around foundation pits, primarily due to the complexity of theoretical solutions given the difficulty in accurately describing the distribution of the groundwater’s hydraulic head in a seepage field. This study proposes an explicit analytical solution for the steady-state seepage field surrounding a foundation pit under anisotropic conditions. A numerical model, constructed with FLAC3D 7.0 software, was utilized to validate the solution presented in this study. The effects of the foundation pit’s width, the distance between the retaining wall and the impervious layer, and anisotropic seepage conditions on the total head are studied through parameter research. The study shows that the flow behavior of a foundation pit is sensitive to parameters such as the anisotropy of the soil layer and the width of the foundation pit. Further, the study also analyzes the influence of the above parameters on the exit gradient and proposes a simplified algorithm for the exit hydraulic gradient at the base of a foundation pit, which can control the error within 5%. This method makes a certain contribution to improving seepage calculations for foundation pits and is applicable to the seepage problem of anisotropic soil layers.
Healing Architecture in Mental Health Facilities in the New European Bauhaus Context
Authors: Jablonska Joanna , Furmanczyk Jozefina
Published: April 2024

The processes of health building design issues overlap, like the complexity of architecture, technology, and protection of human well-being. It becomes necessary to use a holistic and empathized approach. They meet the concept of the New European Bauhaus (NEB) in terms of attention to the aspects of comprehensive design with a focus on humans and their environment. The investigation focused on psychiatric hospitals with an ever-growing demand for treatment places. Accordingly, this article shows the healing architecture’s examination and the environment in healthcare facilities. The POE method was used by investigating the examples. Research contained the technical, functional, spatial, and behavioral qualities of existing psychiatric hospitals. By presenting elements that positively affect the well-being of users, we indicate good practices that bring psycho-physical benefits.
Regional Architecture Building Identity: The Mediating Role of Authentic Pride
Authors: Cao Zihao , Mustafa Muhizam , Mohd Isa Mohd Hafizal
Published: April 2024

The impact of regional architecture on residents’ identities varies, involving complex emotional aspects. We conducted an in-depth study of the deep connection between regional architecture and identity in China’s Huizhou and Minnan regions, highlighting its key role in stimulating authentic pride. Initially, we carried out a survey among 433 residents from both regions using questionnaires to obtain quantitative data, revealing the mediating role of authentic pride. Subsequently, we conducted in-depth interviews with 20 residents from 4 villages of the 2 regions, and the coding results explained the multidimensional reasons behind the quantitative analysis outcomes. This research not only deepened the understanding of how regional architecture impacts identity recognition but also highlighted the urgency of preserving regional culture under the pressures of globalization and modernization. Moreover, this study provided strong reasons for the preservation of architectural heritage, emphasizing its importance as a cornerstone of identity and a means to enhance community cohesion.
Immunotherapy of Hematological Malignancies of Human B-Cell Origin with CD19 CAR T Lymphocytes
Authors: Khvorost Darya , Kendall Brittany , Jazirehi Ali R.
Published: April 2024

Acute lymphoblastic leukemia (ALL) and non-Hodgkin’s lymphoma (NHL) are hematological malignancies with high incidence rates that respond relatively well to conventional therapies. However, a major issue is the clinical emergence of patients with relapsed or refractory (r/r) NHL or ALL. In such circumstances, opportunities for complete remission significantly decline and mortality rates increase. The recent FDA approval of multiple cell-based therapies, Kymriah (tisagenlecleucel), Yescarta (axicabtagene ciloleucel), Tecartus (Brexucabtagene autoleucel KTE-X19), and Breyanzi (Lisocabtagene Maraleucel), has provided hope for those with r/r NHL and ALL. These new cell-based immunotherapies use genetically engineered chimeric antigen receptor (CAR) T-cells, whose success can be attributed to CAR’s high specificity in recognizing B-cell-specific CD19 surface markers present on various B-cell malignancies and the subsequent initiation of anti-tumor activity. The efficacy of these treatments has led to promising results in many clinical trials, but relapses and adverse reactions such as cytokine release syndrome (CRS) and neurotoxicity (NT) remain pervasive, leaving areas for improvement in current and subsequent trials. In this review, we highlight the current information on traditional treatments of NHL and ALL, the design and manufacturing of various generations of CAR T-cells, the FDA approval of Kymriah, Yescarta Tecartus, and Breyanzi, and a summary of prominent clinical trials and the notable disadvantages of treatments. We further discuss approaches to potentially enhance CAR T-cell therapy for these malignancies, such as the inclusion of a suicide gene and use of FDA-approved drugs.
Reconfigurable Liquid Crystal Elastomer Director Patterns for Multi-Mode Shape Morphing
Authors: Zeng Xianbing , Zhou Tianfeng , Li Lei , Song Juncai , Duan Ruijue , Xiao Xiang , Xu Baiqian , Wu Guanghao , Guo Yubing
Published: April 2024

Liquid crystal elastomers (LCEs) are a monolithic material with programmable three-dimensional (3D) morphing modes stemming from their designable non-uniform molecular orientations (or director). However, the shape morphing mode is generally fixed when director patterns of LCEs are determined. Multi-mode shape morphing is difficult to achieve since director patterns cannot be reconfigured. Herein, we demonstrate the ability to reconfigure LCE director patterns and initial shapes—and thus shape morphing modes—by the manual assembly and de-assembly of LCE pixels. We measured the mechanical properties of LCEs with and without UV glue and found their Young’s moduli were 9.6 MPa and 11.6 MPa. We firstly fabricate LCE pixels with designed director fields and then assemble 24 pixels with required director fields into an LCE film with a designed director pattern, which corresponds to a programmed shape morphing mode. We further exhibit that we can de-assemble the LCE film back into original pixels or new pixels with different shapes and then re-assemble them into a new film with a different initial shape and director pattern, which corresponds to a second programmed shape morphing mode. Principally, we can have a large amount of shape morphing modes if we have enough pixels. The demonstrated capability of multi-mode shape morphing enhances functions of LCEs, which broadens their applications in soft robotics, programmable origami/kirigami, responsive surfaces, and so on.
The International Master of Advanced Studies (MAS) in Sleep Medicine of the Universities of Bern and Svizzera Italiana
Authors: Bassetti Claudio L. A. , Sohm Felicitas , Adamantidis Antoine , Schindler Kaspar , Barazzoni Fabrizio , Manconi Mauro
Published: April 2024

Introduction: Sleep–wake circadian disorders (SWCDs) are very frequent and linked to major negative effects on the body, mental health, the brain, and on occupational and societal health. The prevention, diagnosis, and treatment of SWCDs and the promotion of sleep health require the sufficient education of general practitioners, specialists, and other health professionals. Unfortunately, education at pre- and postgraduate level is insufficient in most countries across the world. Aims and methods: This article describes the historical context, basic considerations, and methodological approach for the creation of the International Postgraduate Sleep Master by the University of Bern and Svizzera Italiana. Results: The postgraduate Master, which was launched in 2017, is a part-time, flexible course, taken over 2 ½ years, which targets health professionals, scientists, and technicians. After an initial introduction, which is the same for everybody (“common trunk”), the course can be individualized. The 12 modules of the Master include online lectures, schools, internships in a sleep center (in one of our 15 partner universities), case discussions and interactive sessions with students and internationally recognized experts from over 20 countries across the world, and culminates with a Master thesis. The program covers sleep–wake circadian biology; the management of SWCDs; disturbances of consciousness and sleep-related epilepsies; novel approaches in sleep medicine (e.g., clinical trials, telemedicine, data science, artificial intelligence); and topics of increasing relevance (e.g., neurodegenerative disorders, gender and diversity, sleep health, new technologies, artificial intelligence, professional and societal implications). Students are encouraged to also take “crash courses” in preparation for the national, European, and World sleep examinations. Conclusion: The Postgraduate University Sleep Master of the Universities of Bern and Svizzera Italiana offers a unique part-time, (mainly) virtual opportunity to acquire state-of the art knowledge, skills, and professional experiences to prepare for a clinical or scientific career in sleep medicine for physicians, scientists, and other health professionals.
Cardiac Magnetic Resonance Imaging as a Risk Stratification Tool in COVID-19 Myocarditis
Authors: Nedeljkovic-Arsenovic Olga , Ristić Arsen , Đorđević Nemanja , Tomić Milenko , Krljanac Gordana , Maksimović Ruzica
Published: April 2024

The aim of this retrospective study was to identify myocardial injury after COVID-19 inflammation and explore whether myocardial damage could be a possible cause of the persistent symptoms following COVID-19 infection in previously healthy individuals. This study included 139 patients who were enrolled between January and June 2021, with a mean age of 46.7 ± 15.2 years, of whom 68 were men and 71 were women without known cardiac or pulmonary diseases. All patients underwent clinical work-up, laboratory analysis, cardiac ultrasound, and CMR on a 1.5 T scanner using a recommended protocol for morphological and functional assessment before and after contrast media application with multi-parametric sequences. In 39% of patients, late gadolinium enhancement (LGE) was found as a sign of myocarditis. Fibrinogen was statistically significantly higher in patients with LGE than in those without LGE (4.3 ± 0.23 vs. 3.2 ± 0.14 g/L, p < 0.05, respectively), as well as D-dimer (1.8 ± 0.3 vs. 0.8 ± 0.1 mg/L FEU). Also, troponin was statistically significantly higher in patients with myocardial LGE (13.1 ± 0.4 ng/L) compared to those with normal myocardium (4.9 ± 0.3 ng/L, p < 0.001). We demonstrated chest pain, fatigue, and elevated troponin to be independent predictors for LGE. Septal LGE was shown to be a predictor for arrhythmias. The use of CMR is a potential risk stratification tool in evaluating outcomes following COVID-19 myocarditis.
Clinical and Microbiologic Analysis of Klebsiella pneumoniae Infection: Hypermucoviscosity, Virulence Factor, Genotype, and Antimicrobial Susceptibility
Authors: Hyun Miri , Lee Ji Yeon , Kim Hyun Ah
Published: April 2024

Hypervirulent Klebsiella pneumoniae (KP) is defined according to hypermucoviscosity or various virulence factors and is clinically associated with community-acquired liver abscess (CLA). In this study, we investigated the clinical and microbiological characteristics of KP and significant factors associated with hypervirulence. The clinical characteristics, antimicrobial susceptibility, hypermucoviscosity, serotypes, hypervirulence-related genes, and biofilm formation of 414 KP isolates collected from the Keimyung University Dongsan Hospital between December 2013 and November 2015 were analyzed according to CLA. Significant risk factors for hypervirulent KP (HvKP) associated with CLA were investigated using logistic regression analysis. Notably, 155 (37.4%) isolates were hypermucoviscous, and 170 (41.1%) harbored aerobactin. CLA was present in 34 cases (8.2%). Epidemiology and treatment outcomes did not differ significantly between the CLA and non-CLA groups. The CLA group had significantly higher antibiotic susceptibility, K1/K2, rmpA, magA, allS, kfu, iutA, string test-positive result, and biofilm mass. Multivariate logistic regression revealed rmpA (OR, 5.67; 95% CI, 2.09–15.33; p = 0.001), magA (OR, 2.34; 95% CI, 1.01–5.40; p = 0.047), and biofilm mass >0.80 (OR, 2.13; 95% CI, 1.00–4.56; p = 0.050) as significant risk factors for CLA. rmpA was identified as the most significant risk factor for CLA among KP strains, implying that it is an important factor associated with HvKP.