bluuebunny/crossref_metadata_2025 huggingface dataset:
XSSer: hybrid deep learning for enhanced cross-site scripting detection
Authors: Odeh Ammar , Abu Taleb Anas
Published: July 2024

The importance of an effective cross-site scripting (XSS) detection system cannot be overstated in web security. XSS attacks continue to be a prevalent and severe threat to web applications, making the need for robust detection systems more crucial than ever. This paper introduced a hybrid model that leverages deep learning algorithms, combining recurrent neural network (RNN) and convolutional neural network (CNN) architectures. Our hybrid RNN-CNN model emerged as the top performer in our evaluation, demonstrating outstanding performance across key metrics. It achieved an impressive accuracy of 96.74%, excelling inaccurate predictions. Notably, the precision score reached an impressive 97.78%, highlighting its precision in identifying positive instances while minimizing false positives. Furthermore, the model's recall score of 95.65% showcased its ability to capture a substantial portion of true positive instances. This resulted in an exceptional F1-Score of 96.70, underlining the model's remarkable balance between precision and recall. Compared to other models in the evaluation, our proposed model unequivocally demonstrated its leadership, emphasizing its excellence in detecting potential XSS vulnerabilities within web content.
Addressing the complexities of postoperative brain MRI cavity segmentation–a comprehensive review
Authors: P Sobha Xavier , P K Sathish , G Raju
Published: July 2024

Postoperative brain magnetic resonance images (MRI) is pivotal for evaluating tumor resection and monitoring post-surgical changes. The segmentation of surgical cavities in these images poses challenges due to artifacts, tissue reorganization, and heterogeneous appearances. This study explores challenges and advancements in postoperative brain MRI segmentation, examining publicly accessible datasets and the efficacy of various deep learning models. The analysis focuses on different U-Net models (U-Net, V-Net, ResU-Net, attention U-Net, dense U-Net, and dilated U-Net) using the EPISURG dataset. The training dice scores are as follows: U-Net 0.8150, attention U-Net 0.8534, V-Net 0.7602, ResU-Net 0.7945, dense U-Net 0.83, dilated U-Net 0.80. The study thoroughly assesses existing postoperative cavity segmentation models and proposes a fine-tuning approach to enhance the performance further, particularly for the best-performing model, attention U-Net. This fine-tuning involves introducing dilated convolutions and residual connections to the existing attention U-Net model, resulting in improved results. These improvements underscore the necessity for ongoing research to select and adapt efficient models, retrain specific layers with a comprehensive collection of post-operative images, and fine-tune model parameters to enhance feature extraction during the encoding phase.
Enhancing spyware detection by utilizing decision trees with hyperparameter optimization
Authors: Abualhaj Mosleh M. , Al-Shamayleh Ahmad Sami , Munther Alhamza , Alkhatib Sumaya Nabil , Hiari Mohammad O. , Anbar Mohammed
Published: July 2024

In the realm of cybersecurity, spyware has emerged as a formidable adversary due to its persistent and stealthy nature. This study delves deeply into the multifaceted impact of spyware, meticulously examining its implications for individuals and organizations. This work introduces a systematic approach to spyware detection, leveraging decision trees (DT), a machine-learning classifier renowned for its analytical prowess. A pivotal aspect of this research involves the meticulous optimization of DT's hyperparameters, a critical operation for enhancing the precision of spyware threat identification. To evaluate the efficacy of the proposed methodology, the study employs the Obfuscated-MalMem2022 dataset, well-regarded for its comprehensive and detailed spyware-related data. The model is implemented using the Python programming language. Significantly, the findings of this study consistently demonstrate the superiority of the DT classifier over other methods. With an accuracy rate of 99.97%, the DT proves its exceptional effectiveness in detecting spyware, particularly in the face of more intricate threats. By advancing our understanding of spyware and providing a potent detection mechanism, this research equips cybersecurity professionals with a valuable tool to combat this persistent online menace.
An improved dual vector control for a doubly fed induction generator based wind turbine during asymmetrical voltage dips
Authors: Moumani Youssef , Jabal Laafou Abdeslam , Ait Madi Abdessalam , Boutssaid Rachid
Published: July 2024

This paper introduces a robust and inhanced version of dual control approach based on sequence decomposition loops in order to limit transient over-currents and improving the wind turbine’s operation during asymmetrical voltage dips faults. Indeed, the doubly fed induction generator (DFIG), employed in wind energy conversion system (WECS) to produce electrical energy from wind, highly susceptible to voltage drops, which can cause transient overcurrents in both the stator and the rotor. Without any protection system, these over-currents might damage the DFIG and its converters. The strategy put forward in this work minimizes the consequences of voltage dips on wind system functioning, such as electromagnetic torque fluctuations and it enables wind turbines to maintain electrical connection with the grid in the occurrence of such disturbances. The carried-out results are promising and showed that the proposed control method can effectively minimise the oscillations in electromagnetic torque, reactive power and DC bus voltage during the asymmetrical voltage dip. This analysis also demonstrated its ability to limit the transient over-currents of the DFIG.
CMOS low noise amplifier technologies: trends for enhancing satellite receivers and mobile communications
Authors: Singh Rashmi , Mehra Rjaesh
Published: July 2024

The emerging demand for high-data-rate wireless communication systems and high-resolution radars, particularly in the millimeter-wave (mm-wave) spectrum, has captured significant attention within both the industrial and academic landscape. Recognized as the fundamental building block for satellite receivers, the low noise amplifier (LNA) plays a pivotal role in meeting these growing requirements. In Today's world a continuously increasing number of connected devices and resource-intensive digital content load to an incessant data being generated, transformed, and facilitated. In this paper, authors summarize the different technologies and techniques employed to design various LNAs with enhanced bandwidth, higher gain, low noise figure (NF), minimal power consumption, and less chip area.
Ageing durability of SiR under prolonged voltage stress, contaminant flow and contaminant concentration: a statistical approach
Authors: Nazir Ali Nornazurah , Zainuddin Hidayat , Abd Razak Jeefferie , Farhani Ambo Nur
Published: July 2024

Silicone rubber (SiR) has become a reliable choice for outdoor high voltage (HV) insulation in recent years. However, the durability of these polymeric materials is affected by both electrical and environmental stresses, leading to aging. While prior research aimed at enhancing performance, little focus was placed on identifying the major root causes of aging in these insulators. To delve into the causes, we conducted inclined plane tracking (IPT) tests, varying voltage, flow rate, and contamination concentration. Samples with consistent alumina trihydrate (ATH) filler content were tested under the BSEN 60587 standard. The voltage ranged from 3.5-5.5 kV, flow rate from 0.3-0.9 ml/min, and contamination concentration from 500-4500 µS/cm. A Two-Level Factorial analysis with a design of experiment (DOE) approach was used. The study revealed that contaminant concentration significantly impacted leakage current (LC), followed by contamination flow rate and voltage. Additionally, optimization techniques are used to determine ideal LC values under specific conditions. This study explains how each factor affects LC values, allowing for predictive modelling, which improves our understanding of SiR insulators' durability, optimizes LC in real-world situations, and improves their performance and lifespan.
Effects of DBDS and DBPC antioxidants on the corrosion of copper strips immersed in transformer oil
Authors: Sutan Chairul Imran , Ab Ghani Sharin , Shahril Ahmad Khiar Mohd , Abu Bakar Norazhar , Syahrani Johal Muhammad , Nazri Mohamad Din Mohamad
Published: July 2024

This paper presents the experimental findings on the effects of antioxidants on the corrosion of copper strips immersed in mineral oil (MO)–antioxidant samples. First, the uninhibited MO was mixed thoroughly with dibenzyl disulphide (DBDS) or 2,6-di-tert-butyl-p-cresol (DBPC) at different concentrations (5, 15, 25, 50, and 200 mg/kg) using a hot plate magnetic stirrer set at a temperature of 73 °C and stirring speed of 750 rpm for 15 min. Following this, the MO–antioxidant samples were poured into separate test vessels and copper strips were added into the vessels. Next, each MO–antioxidant sample was blanketed with nitrogen gas, sealed, and placed in a forced convection laboratory oven. The MO–antioxidant samples were then thermally aged at 150 °C for 48 h. The results showed that the acidity of the MO–antioxidant sample decreased with an increase in the antioxidant concentration, regardless whether the antioxidant was DBDS or DBPC. However, the corrosion of the copper strip worsened with an increase in the antioxidant concentration, where DBDS had a higher relative degree of corrositivity to copper compared with DBPC. In addition, the results showed that a DBPC concentration of 25 mg/kg reduced the the acidity of the MO–antioxidant sample and resulted in a moderate tarnish of the copper strip.
Fundamental frequency extraction by utilizing modified BaNa in noisy speech
Authors: Saha Arpita , Parvin Nargis , Rahman Dr. Md. Saifur , Rahman Moinur , Chowdhury Any
Published: July 2024

A sound’s pitch can be largely understood and perceived by using its fundamental frequency. Multiple algorithms have been developed for extracting fundamental frequency, and the choice of which one to employ depends on the noise and features of the signal. Therefore, for an accurate fundamental frequency estimate, the noise resistance of the algorithm becomes even more crucial. Still, many of the most advanced algorithms fail to produce acceptable results when faced with loud speech recordings that have low signal-to-noise ratios (SNRs). In this research paper, we focus on the harmonic selection step in BaNa method, which is one of the vital parts for enhancing the extraction accuracy of fundamental frequency (F0) in noisy situations. BaNa algorithm always emphasizes 5 harmonics on average for both male and female speakers. However, our observation reveals that relying on 5 harmonics is inadequate for male speakers in noisy conditions. Thus, we propose a new idea based on BaNa that separately utilizes the 3 harmonics for male speakers and 5 harmonics for female speakers to achieve accurate pitch extraction within noisy environments. The results demonstrate that our proposed approach attains the lowest rate of gross pitch error (GPE) across various noise types and SNR levels.
Determining the retail sales strategies using association rule mining
Authors: Yanti Roaida , Maradjabessy Prita Nurkhalisa , Qurtubi Qurtubi , Rachmadewi Ira Promasanti
Published: July 2024

Competitive competition in the retail industry requires retailers to maintain improvements and formulate accurate strategies to maintain their competitiveness. A small number of daily visitors visit retail store Y if compared to other retail stores, which leads to decreased store revenue due to the small number of products sold. Therefore, it is crucial to formulate the right business strategy to increase sales by utilizing customer shopping behavior derived from transaction data. The method used is association rule mining (ARM) with a frequent pattern growth (FP-growth) algorithm to determine consumer buying patterns. Data processing results generate five valid rules that meet the specified criteria for an association relationship. Utilization rules are acknowledged by determining retail sales strategies by recommending store layouts, shopping catalogs, and voucher discounts to attract customers.
Addition chain heuristics in application to elliptic curve cryptosystems
Authors: Mohamed Mohamad Afendee , Shawai Yahaya Garba , Derahman Mohd Noor , Mamat Abd Rasid , Mohd Satar Siti Dhalila , Amri Abidin Ahmad Faisal , Abdul Kadir Mohd Fadzil
Published: July 2024

The idea of an addition chain can be applied to scalar multiplication involving huge number operations in elliptic curve cryptosystems. In this article, initially, we study the taxonomy of the addition chain problem to build up an understanding of the problem. We then examine the mathematics behind an optimal addition chain that includes the theoretical boundary for the upper limit and lower limit which laid the foundation for experimentation hereafter. In the following, we examine different addition chain solutions that were used to increase efficiency in scalar multiplication. To avoid any possible confusion, we intentionally separated the discussion into two modules called integer recoding method and chain generator based on the heuristics method. These methods were developed by considering various aspects such as the space within which the operation is executed, the curve that is selected, the formulation to express the original equation, and the choices of operation and arithmetic, all together to improve operational efficiency.
Experimental studies on bagasse ash reinforced with GF and BF-slag in direction towards sustainable development
Authors: Nikhade Harshal Ramesh , Nikhade Anshul Ramesh , Telrandhe Shital , Mandavgade Nitin K , Hatwar Bhushan Yograj
Published: July 2024

To assess the appropriateness of the current by-product for application in building construction and to mitigate potential environmental risks in the context of environmental sustainability, a series of tests were conducted to determine the compressive strength properties of a material composed of glass fiber (GF) strengthened sugar cane bagasse ash (SCA). This material was made from SCA, blast furnace slag (BF-slag), and GF binding with cement. Cylinders were employed to measure the compressive strength of a mixture consisting of water and an SCA ratio of 50%. Cylindrical samples of 150 millimeters in length and 75 millimeters in diameter were utilized to evaluate the compressive strength across curing durations of 7, 14, and 28 days. The present study attempt utilizes mixture ratio percent of 0.15, 0.3, 0.45, 0.6, and 0.75 to perform compressive strength tests. The compressive strength of cylindrical samples ranges from 86.5-801.6 kPa. The density of a cylindrical sample containing 30% cement dropped from 900.1-865 kg/m3. The initial tangent stiffness of the sample ranges from 66-630 MPa. The findings suggest that it is possible to achieve a material with acceptable strength by using SCA ash in combination with BF-slag, strengthened with GF.
A study of smart charging for electric vehicles using constant-current and constant-voltage technology
Authors: Sutikno Tole , Wahono Tri , Ardiansyah Ardiansyah
Published: July 2024

The role of electric vehicles (EVs) is very important in the coming years because of their environmental friendliness and ability to absorb excess electricity from renewable energy sources (RES). Charging EVs will have an immediate negative impact on the power grid. EV smart charging provides a solution to these problems. For sustainable energy management, smart charging technology offers significant advantages in terms of faster charging times and optimized grid usage. By leveraging advanced algorithms and real-time communication capabilities, smart chargers enhance the efficiency, convenience, and environmental sustainability of EV charging infrastructure. Constant-current (CC) and constant-voltage (CV) technologies are essential components of smart charging systems, contributing to improved charging efficiency, battery safety, and grid stability. By regulating the charging process and optimizing power flow, these technologies play a crucial role in advancing the adoption of EVs and promoting sustainable energy management. When advanced CC-CV technologies are added to smart charging systems, the whole paradigm changes. Charging efficiency goes up by 40%, charging time goes down by 50%, and the grid's impact is reduced by 50% through better energy distribution.
Signal processing for abnormalities estimation analysis
Authors: Razman Nur Fatin Shazwani Nor , Nasir Haslinah Mohd , Zainuddin Suraya , Brahin Noor Mohd Ariff , Ibrahim Idnin Pasya , Mispan Mohd Syafiq
Published: July 2024

Pneumonia, asthma, sudden infant death syndrome (SIDS), and the most recent epidemic, COVID-19, are the most common lung diseases associated with respiratory difficulties. However, existing health monitoring systems use large and in-contact devices, which causes an uncomfortable experience. The difficulty in acquiring breathing signals for non-stationary individuals limits the use of ultra-wideband radar for breathing monitoring. This is due to ineffective signal clutter removal and body movement removal algorithms for collecting accurate breathing signals. This paper proposes a breathing signal analysis for non-contact physiological monitoring to improve quality of life. The radar-based sensors are used for collecting the breathing signal for each subject. The processed signal has been analyzed using continuous wavelet transform (CWT) and wavelet coherence with the Monte Carlo method. The finding shows that there is a significant difference between the three types of breathing patterns; normal, high, and slow. The findings may provide a comprehensive framework for processing and interpreting breathing signals, resulting in breakthroughs in respiratory healthcare, illness management, and overall well-being.
Employing transfer learning techniques for COVID-19 detection using chest X-ray
Authors: Garg Preeti , Gautam Madhu , Chugh Bharti , Dwivedi Karnika
Published: July 2024

Coronavirus 2 (SARS-COV-2) is a global emergency that continues to terrify the globe at an alarming rate. Some nations are still combating the virus, attempting to discover infected individuals early on to prevent the infection from spreading. In terms of identifying the pattern in the pictures, radiological patterns have been shown to have greater accuracy, sensitivity, and specificity. Publicly available datasets are used for the implementation. The data is divided into three categories: COVID, normal, and pneumonia patients. Transfer learning is a type of deep learning that allows pre-trained models to be used and achieves high accuracy by detecting various anomalies in limited medical datasets. An image dataset of 1109 pictures was used in this work, and training was done using two distinct models, ResNet50 and InceptionV3, to distinguish the patient categories. For ResNet and InceptionV3, the proposed model has an accuracy of 97.29 and 98.20, respectively, with a sensitivity of 100% for InceptionV3 and a specificity of 99.41% for ResNet50. With a 98.20% accuracy, complete sensitivity, and high specificity, this study presents a deep learning model that gives diagnostics for multiclass classification and attempts to discriminate COVID-19 patients using chest X-ray photos. Other illnesses can also be detected using the proposed model.
Kinetic study and simulation of molybdenum borides for hydrogen evolution reaction
Authors: Ramji Harunal Rejan , Ibidin Muhammad Qhaliff Zainal , Glandut Nicolas , Absi Joseph , Fong Lim Soh
Published: July 2024

This paper presented the kinetic study of molybdenum borides via the Volmer-Heyrovsky-Tafel (V-H-T) mechanistic steps for hydrogen evolution reaction (HER). A theoretical approach was carried out to investigate the kinetic properties of several molybdenum boride materials for HER in 0.5 M H2SO4. Our findings offer definitive proof that the simulated results show that B, Mo, Mo2B, and α-MoB, proceed through V-H mechanistic steps (slower kinetics) while β-MoB and MoB2 exhibit V-H-T mechanistic steps with higher kinetics. The kinetic parameters were determined in terms of the standard rate constant parameters for the Volmer step (kV, k-V), Heyrovsky step (kH, k-H), and rate constant for the Tafel step (kT, k-T). The simulation was able to predict the overpotential at 10 mA/cm2, η10 recorded at approximately 780, 585, 480, 350, 310, and 300 mV for B, Mo, Mo2B, α-MoB, β-MoB, and MoB2 respectively. Based on these findings, the adopted mathematical model shows good coherency to the experimental findings. The simulation work provides a good numerical estimation of the characteristics of the electrocatalyst for HER. This paper successfully elucidated the reaction mechanisms (V-H-T steps) and understood the rate-limiting steps involved in the HER process on Mo-B materials.
Performance evaluation and integration of distortion mitigation methods for fisheye video object detection
Authors: Du John Benedict , Mayuga Gian Paolo , Guico Maria Leonora
Published: July 2024

The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using the longitude-latitude correction with the YOLOv3 object detector provided the best results in terms of accuracy (PASCAL: 68.9%, VOC-360: 75.1%, WEPDTOF: 15.9%) and speed (38 FPS across all test sets) for fisheye footage. After measuring the results to determine the best configuration for video object detection, the researchers also developed a desktop application that incorporates these methods and provides real-time object detection and tracking functions. The study provides a foundation for improving the accuracy and speed of fisheye camera setups, and its findings can be valuable for researchers and practitioners working in this field.
Effect of Intramyocardial Administration of Baculovirus Encoding the Transcription Factor Tbx20 in Sheep With Experimental Acute Myocardial Infarction
Authors: Bauzá María del Rosario , López Ayelén Emilce , Simonin Jorge Alejandro , Cimbaro Francisco Stefano , Scharn Agustina , Castro Araceli , Silvestro Cintia Virginia , Cuniberti Luis Alberto , Crottogini Alberto José , Belaich Mariano Nicolás , Locatelli Paola , Olea Fernanda Daniela
Published: July 2024

Background

Gene therapy has been proposed as a strategy to induce cardiac regeneration following acute myocardial infarction (AMI). Given that Tbx20, a transcription factor of the T‐box subfamily, stimulates cell proliferation and angiogenesis, we designed a baculovirus overexpressing
Tbx20
(Bv‐Tbx20) and evaluated its effects in cultured cardiomyocytes and in an ovine model of AMI.

Methods and Results

Cell proliferation and angiogenesis were measured in cardiomyocytes transduced with Bv‐Tbx20 or Bv‐Null (control). Subsequently, in sheep with AMI, Bv‐Tbx20 or Bv‐Null was injected in the infarct border. Cardiomyocyte cell cycle activity, angioarteriogenesis, left ventricular function, and infarct size were assessed. Cardiomyocytes transduced with BvTbx20 increased cell proliferation, cell cycle regulatory and angiogenic gene expression, and tubulogenesis. At 7 days posttreatment, sheep treated with Bv‐Tbx20 showed increased
Tbx20
, promitotic and angiogenic gene expression, decreased levels of
P21
, increased Ki67‐ (17.09±5.73 versus 7.77±7.24 cardiomyocytes/mm
2
,
P
<0.05) and PHH3 (phospho‐histone H3)‐labeled cardiomyocytes (10.10±3.51 versus 5.23±2.87 cardiomyocytes/mm
2
,
P
<0.05), and increased capillary (2302.68±353.58 versus 1694.52±211.36 capillaries/mm
2
,
P
<0.001) and arteriolar (146.95±53.14 versus 84.06±16.84 arterioles/mm
2
,
P
<0.05) densities. At 30 days, Bv‐Tbx20 decreased infarct size (9.89±1.92% versus 12.62±1.33%,
P
<0.05) and slightly improved left ventricular function. Baculoviral gene transfer‐mediated Tbx20 overexpression exerted angiogenic and cardiomyogenic effects in vitro.

Conclusions

In sheep with AMI, Bv‐Tbx20 induced angioarteriogenesis, cardiomyocyte cell cycle activity, infarct size limitation, and a slight recovery of left ventricular function, suggesting that Bv‐Tbx20 gene therapy may contribute to cardiac regeneration following AMI.
Extracellular RNA Induces Neutrophil Recruitment Via Toll‐Like Receptor 3 During Venous Thrombosis After Vascular Injury
Authors: Najem Maria Y. , Rys Ryan N. , Laurance Sandrine , Bertin François‐René , Gourdou‐Latyszenok Virginie , Gourhant Lénaïck , Le Gall Lauriane , Le Corre Rozenn , Couturaud Francis , Blostein Mark D. , Lemarié Catherine A.
Published: July 2024

Background

Venous thromboembolism is associated with endothelial cell activation that contributes to the inflammation‐dependent activation of the coagulation system. Cellular damage is associated with the release of different species of extracellular RNA (eRNA) involved in inflammation and coagulation. TLR3 (toll‐like receptor 3), which recognizes (viral) single‐stranded or double‐stranded RNAs and self‐RNA fragments, might be the receptor of these species of eRNA during venous thromboembolism. Here, we investigate how the TLR3/eRNA axis contributes to venous thromboembolism.

Methods and Results

Thrombus formation and size in wild‐type and TLR3 deficient (−/−) mice were monitored by ultrasonography after venous thrombosis induction using the ferric chloride and stasis models. Mice were treated with RNase I, with polyinosinic‐polycytidylic acid, a TLR3 agonist, or with RNA extracted from murine endothelial cells. Gene expression and signaling pathway activation were analyzed in HEK293T cells overexpressing TLR3 in response to eRNA or in human umbilical vein endothelial cells transfected with a small interference RNA against TLR3. Plasma clot formation on treated human umbilical vein endothelial cells was analyzed. Thrombosis exacerbated eRNA release in vivo and increased eRNA content within the thrombus. RNase I treatment reduced thrombus size compared with vehicle‐treated mice (
P
<0.05). Polyinosinic‐polycytidylic acid and eRNA treatments increased thrombus size in wild‐type mice (
P
<0.01 and
P
<0.05), but not in TLR3
−/−
mice, by reinforcing neutrophil recruitment (
P
<0.05). Mechanistically, TLR3 activation in endothelial cells promotes CXCL5 (C‐X‐C motif chemokine 5) secretion (
P
<0.001) and NFκB (nuclear factor kappa‐light‐chain‐enhancer of activated B cells) activation (
P
<0.05). Finally, eRNA triggered plasma clot formation in vitro (
P
<0.01).

Conclusions

We show that eRNA and TLR3 activation enhance venous thromboembolism through neutrophil recruitment possibly through secretion of CXCL5, a potent neutrophil chemoattractant.
Deconstructing the Mapper algorithm to extract richer topological and temporal features from functional neuroimaging data
Authors: Haşegan Daniel , Geniesse Caleb , Chowdhury Samir , Saggar Manish
Published: July 2024

Capturing and tracking large-scale brain activity dynamics holds the potential to deepen our understanding of cognition. Previously, tools from topological data analysis, especially Mapper, have been successfully used to mine brain activity dynamics at the highest spatiotemporal resolutions. Even though it is a relatively established tool within the field of topological data analysis, Mapper results are highly impacted by parameter selection. Given that noninvasive human neuroimaging data (e.g., from fMRI) is typically fraught with artifacts and no gold standards exist regarding “true” state transitions, we argue for a thorough examination of Mapper parameter choices to better reveal their impact. Using synthetic data (with known transition structure) and real fMRI data, we explore a variety of parameter choices for each Mapper step, thereby providing guidance and heuristics for the field. We also release our parameter exploration toolbox as a software package to make it easier for scientists to investigate and apply Mapper to any dataset.
Transient destabilization of interhemispheric functional connectivity induced by spreading depolarization
Authors: Lachinova Daria A. , Smirnova Maria P. , Pavlova Irina V. , Sysoev Ilya V. , Vinogradova Lyudmila V.
Published: July 2024

Cortical spreading depolarization (CSD), a slowly propagating wave of transient cellular depolarization, is a reliable cortical response to various brain insults (stroke, trauma, seizures) and underlying mechanism of migraine aura. Little is known about CSD effects on brain network activity. Using undirected (mutual information, MI) and directed (transfer entropy, TE) measures, we studied the dynamics of cross-hemispheric connectivity associated with the development of unilateral CSD in freely behaving rats and the involvement of inhibitory transmission in mechanisms of the coupling changes. We show that the development of CSD in the cortex of one hemisphere is followed by the transient loss of undirected functional connectivity (MI) between ipsilateral and contralateral cortical regions. The post-CSD functional disconnection of the hemispheres was accompanied by an increase in driving force from an unaffected contralateral cortex to an affected one (TE). Mild cortical disinhibition produced by pretreatment with an inhibitory receptor blocking agent (penthylenetetrazole) did not affect CSD but attenuated (MI) or eliminated (TE) the CSD-induced connectivity changes. The effects of CSD on functional connectivity in awake rodents were similar at the individual and group levels, suggesting that the described connectivity response may be a promising network biomarker of CSD occurrence in patients.
Ideas about the Characteristics of Responsibility in Adolescents
Authors: Baranova Victoria A. , Dubovskaya Еkaterina М. , Savina Ol'ga O.
Published: July 2024

Background. The problem of human responsibility arises in a situation of crisis, value and meaning changes in society. The study is focused on identifying ideas about significant criteria and self-assessments of responsible behaviour in middle adolescents. Objectives. The aim of the study is to analyze the concept of responsibility in teenagers. Study Design. The study was carried out in the format of a written survey: identifying the characteristics of a responsible person, self-assessments in terms of significant parameters of responsibility; additionally, information was collected on the participation of adolescents in social practices within the framework of an educational institution. Study Participants. Adolescents aged 13–15 (n = 118, of which 48% are men, 51.6% are women), students of secondary schools took part in the research. Methods. The method of associations and testing was used: 1) a story-reasoning on the topic “A responsible person is…”; 2) modification of the technique “Responsibility as a systemic quality of personality” (Pryadein, 2014); 3) self-assessment on a 7-point scale of responsibility in studies, family, friendship, hobbies and activities. Results. The parameters of responsibility highly rated by adolescents are “Willingness to be responsible for the consequences of one's actions”, “Devotion”, “Development of the ability to empathize, sensitivity to someone else's pain and joy”. Differences between gender groups in the empathy, diligence, initiative, the ability to independently formulate moral duties were revealed. Among the spheres of responsibility manifestation, adolescents rate the educational sphere low, which reflects the educational model of moral education with an emphasis on the transfer of knowledge, rather than on the moral practice. Conclusions. Adolescents' ideas about responsibility are shifted to the area of understanding what responsible behaviour is, rather than to the awareness of their own responsible actions, which shows the separation of the modern education system from life practice. It is important to study the manifestation of responsible behaviour in individual actions and group interaction in social practices.
Media Consumption as a Factor in Young Women Turning to Clinics of Aesthetic Medicine
Authors: Martynov Sergey E. , Arina Galina A.
Published: July 2024

Background. The media environment offers not only reference images of the quality of life, but also numerous ways to achieve them. Currently, the media space is considered as a significant factor in psychological health and well-being, with body image being subject to the maximum degree of “pressure” from media ideals of appearance. This creates conditions for certain behaviour patterns of self-transformation, including the help of modern methods of aesthetic medicine. Objectives. The aim is to study the influence of the stereotype of ideal appearance, broadcast by the media, on the desire and readiness to change one’s appearance in an aesthetic medicine clinic. Methods. Methods specially developed for this study were used: “Media preferences and attitudes towards appearance” and “Choice of aesthetic medicine procedures”. Study Participants. The main group consisted of 144 women (M = 22.5; SD = 4.4, from 18 to 30 years old) who sought medical help at the Institute of Plastic Surgery and Cosmetology; control group involved 164 women (M = 21.15; SD = 3.8, from 18 to 30 years old) who did not contact the medical network with complaints about dissatisfaction with their own appearance. Results. Patients of the aesthetic medicine clinic are characterized by regular consumption of media on fashion and beauty topics, and are also prone to comparison and imitation of media ideals of appearance. Girls who spend a lot of time watching media on fashion and beauty want to devote even more time to this and note that the media influences the intensification of their needs related to changing their appearance. Conclusions. Macrosocial pressure to develop an “ideal self” evokes young women to compare themselves to and imitate ideals of appearance, which increases the desire to change their appearance. women focused on long-term consumption of media stereotypes of ideal appearance show willingness to use more and a wider range of medical interventions to correct their appearance, despite their risks and severity.
Competence in the Context of Subject-Environment Interactions: Experience of Theoretical Comprehension
Authors: Panyukova Julia G. , Alexandrova Elena S.
Published: July 2024

Background. The relevance of this article is substantiated by the high interest of specialists in the field of subject-environment interactions in finding answers to questions about the abilities of the subject to interact with the spatial environment of everyday life, taking into account the psychological resourcefulness of this environment, with a focus on the potential of the spatial conditions of the living environment to ensure positive psychological functioning. Objectives. The article attempts to theoretically substantiate the possibility of using the “competence” construct in order to analyze subject-environment interactions. Methods. The analysis and systematization of theoretical and empirical research in the field of phenomenology of the subject-environment interaction was carried out (G.A. Kovalev, S.K. Nartova-Bochaver, V.I. Panov, etc.) with the focus on the possibility of referring to the methodology of the resource approach in psychology (N.E. Vodopyanova, D.A. Leontiev, V.I. Morosanova, E.A. Sergienko, V.A. Tolochek, S.A. Khazova, etc.), as well as in the field of ecopsychology of everyday life (S.E. Gabidulina, T.V. Drobysheva, A.L. Zhuravleva, O.A. Kaptsevich , S.K. Nartova-Bochaver, I.S. Samoshkina, T.V. Semenova, etc.). Results. Theoretical approaches are singled out, within the framework of which the interaction in the “environment-subject” system is operationalized with an emphasis, firstly, on the potential conditions of the spatial environment, secondly, on the individual psychological possibilities of the subject, in particular, the ability to be the subject of mental activity in determining resourcefulness of spatial environment in everyday life. The research in the field of determining the construct of “psychological resources” was analyzed as well as research connected with the description of psychological resourcefulness for the different types of living environment: urban, living, professional. The research directions of interactions between potential conditions of spatial environment of everyday life and subjectional possibilities of using these conditions as the psychological resource for optimization of psychological functioning were determined. The appeal to the construct of “competence” as a promising theoretical and applied direction of research in the field of the relationship between the subject and the spatial environment of everyday life is indicated. Conclusions. Considering statements of environmental psychology, ecopsycology of development, everyday life psychology, as well as being based on an opportunity to consider spatial environment of everyday life as a resource that is directed to the optimization of psychological well-being of the subject, it is proposed to consider competence in subject-environment interactions as the ability of the subject to transform conditions or potential of the spatial environment of everyday life into psychological resource, necessary to maintain optimal functioning.
Gender Differences in the Relationships Between Empathic Tendencies, Dark Triad Traits and Personality Traits in Student Actors
Authors: Sobkin Vladimir S. , Savchenko Nina L. , Siyan Marina V. , Yakovleva Marina A.
Published: July 2024

Background. There is a contradiction in the results of acting research: empathy plays an important role in the process of artistic transformation, but some anti-empathic traits, such as narcissism and machiavellianism, may also be useful for stage performance. The identification of gender specificity is particularly interesting when examining these personal features in the context of student actors' professional growth. Objectives. The focus is on exploring gender differences in the relationships of empathy and Dark Triad traits with personality traits in student actors. Study Participants. The study involved 43 second-year students of the Acting major, aged 19 to 29 years (21 men, 22 women). Methods. Short Portrait Big Five Questionnaire by M.S. Egorova and O.V. Parshikova, Short questionnaire of the Dark Triad adapted by M.S. Egorova, M.A. Sitnikova, O.V. Parshikova Empathy Questionnaire by A.A. Mehrabian adapted by E.F. Zeer and O.N. Shakhmatova Results. Openness to experience among student actors is associated with narcissism, and neuroticism is associated with emotional empathy, which describes the ability to understand other people's emotions. At the same time, gender differences were found in the specific relationships between empathic tendencies and personality traits. In boys, behavioral empathy, aimed at showing support and help, is associated with extraversion, while in girls, neuroticism is associated with machiavellianism. Conclusions. Several interpretations of the results are presented. Actors who are open to new experiences and experiments in creating images can be narcissistic, since they do not yet have a formed “sense of truth”, and therefore are forced to focus more on external assessment. Also, student actors may feel somewhat exceptional compared to their peers due to the experience gained through their professional activities. The connection between the emotional level of empathy in student actors of both sexes and neuroticism is explained by the fact that good social insight is accompanied by increased anxiety. Gender specific correlations (Machiavellianism with neuroticism in girls and behavioral empathy with extraversion in boys) may reflect the chosen strategies in developing the emotional component of the image, as well as in building relationships in a team.
Validity and Reliability of Four Instruments for E-Cigarette Dependence and Sensory Factors in E-Cigarette Use and Correlations Between These Measurements
Authors: Aslan Banu , Onal Ozgur
Published: July 2024

The study aimed to examine the psychometric properties of Turkish versions of e-FTCD, PS-ECDI, EDS, and SEES. 1050 individuals aged 18+ included to assess validity, reliability, and interrelation among these scales. Scale psychometrics explored using statistical methods, including construct validity, confirmatory factor analysis, and reliability stats. The factor loadings for e-FTCD ranged from 0.528 to 0.939, PS-ECDI from 0.404 to 0.899, EDS from 0.779 to 0.897, and SEES from 0.733 to 0.849. The Cronbach’s alpha coefficients for e-FTCD, PS-ECDI, EDS (4-Item), EDS (8-Item), EDS (22-Item), and SEES were 0.561, 0.805, 0.905, 0.949, 0.984, and 0.934, respectively. The correlations were moderate between SEES and both e-FTCD (0.317) and PS-ECDI (0.394), e-FTCD was strongly correlated with PS-ECDI (0.750) and moderately with EDS versions (0.577–0.586). Correlations between the PS-ECDI and EDS versions ranged from 0.698–0.713. All four tools valid, reliable for 18+ in Türkiye. Also, positive correlation between sensory e-cigarette expectation and dependence.
Caregiving Appraisals and Emotional Valence: Moderating Effects of Activity Participation
Authors: Lee Jeong Eun , Nemmers Natasha Lina , Svec Joseph , Cho Jinmyoung
Published: July 2024

The present study examines the extent to which a two-factor model of affect explains how caregiving appraisals experienced by caregivers influence their own well-being. We used data from three waves of Nation Study of Caregiving (NSOC) to conduct latent growth curve models with the time-varying predictors to investigate the effect of between-person (BP) and within-person (WP) caregiving appraisals on positive and negative affect. Furthermore, we simultaneously modeled WP differences in activity participation and affective experience with multilevel modeling. Then, we tested the moderating effect of activity participation in the association between WP caregiving appraisals and emotional valence. We found that BP and WP caregiving negative appraisal also contribute to caregiver positive affect similar to that of negative affect. Time-varying effects of negative appraisals and emotional valence are consistent with the two-factor model. Future longitudinal investigations could target WP and BP activity participation to alleviate caregiving cognitive appraisal among caregivers.
Computational cross-media research: tracing divergences between normative Dutch television and social media discourses on the ‘refugee crisis’ (2013-2018)
Authors: de Keulenaar Emillie , Poell Thomas , Helmond Anne , Rieder Bernhard , Van Gorp Jasmijn
Published: July 2024

This article examines how the ‘refugee crisis’, sparked by the arrival of refugees from the Syrian civil war and other conflicts around the world, was articulated across Dutch television news programs and social media between 2013 and 2018. This crisis has been described as a key catalyst of the radicalization of European political discourse. Crucially, it took shape during a period of profound transformation of the media landscape, in which mass media lost significant ground to social media as authoritative sources of truth and norms. The research focuses on the crucial but underexplored link between television and social media discourse, which is at the heart of contemporary European public debate. Using a combination of digital methods and NLP techniques, the article compares automatic speech recognition (ASR) transcripts of Dutch televised news on the refugee crisis with responses from publics on Facebook and Twitter. This computational cross-media approach enables a longitudinal analysis of how social media users differ in their interpretation of key events characterizing the crisis, as well as what language is acceptable to debate issues around integration, tolerance and identity. A rejection of mainstream news media editorial guidelines by social media users eventually resulted in their consumption of populist right-wing (‘alternative’) news media and active transgression of anti-discriminatory speech norms.
Bayesian-guided operational modal identification of a highway bridge considering non-uniform sampling
Authors: Wang Zhi-Wen , Liu Jun-Hong , Ding You-Liang , Yang Xiao-Mei , Zheng Xu , Yi Ting-Hua
Published: July 2024

During the structural health monitoring of bridges, it has been observed that the vibration data collected can sometimes be randomly lost or sampled non-uniformly. This leads to a low signal-to-noise ratio in the spectral functions of the measured data, making it difficult to identify weak modes. To address this issue, a framework for operational modal identification is proposed in this study. It utilizes the fast Bayesian fast Fourier transform (FFT) method to estimate the modal parameters of highway bridges considering the non-uniform monitoring data. The initial frequency parameters for the fast Bayesian FFT approach are automatically determined using the proposed autoregressive (AR) power spectral density (PSD)-guided peak picking method. This overcomes the challenge of capturing initial frequencies related to weakly contributed modes. Additionally, the bandwidth parameter for each mode is determined using the modal assurance criterion (MAC) of the first left singular vectors of PSD matrices. Furthermore, when analyzing non-uniform vibration data, it is recommended to use the non-uniform FFT (NUFFT) for calculating PSD functions in order to improve identification accuracy. The proposed method is validated using acceleration data from both a numerical model and a real-world bridge. The results demonstrate that the identification uncertainty of modal parameters increases with higher non-uniform levels.
Regular Physical Activity: A Key to Healthy Living and an Indispensable Pillar of Lifestyle Medicine
Authors: Rippe James M.
Published: July 2024

Individuals who choose to be inactive accept the same increased risk of heart disease as individuals who smoke a pack of cigarettes a day! Unfortunately, between 11%-15% of the adult population still smoke a pack of cigarettes a day, whereas, 60%-80% of adults are either not adequately active or completely inactive. Thus, inactivity carries the same risk as smoking a pack of cigarettes per day and is between 4-5 times more prevalent!