bluuebunny/crossref_metadata_2025_split huggingface dataset:
Memory, trauma, and self: Remembering and recovering from sexual abuse in psychedelic-assisted therapy
Authors: Rose Jarrett Robert 
Published: October 2024

AbstractBackground and AimsThis article examines the therapeutic potential of psilocybin in addressing Post-Traumatic Stress Disorder as the result of sexual abuse. PTSD is a prevalent form of mental distress resistant to most conventional treatment methods.MethodsThrough an in-depth analysis of the narratives of two individuals with longstanding, treatment-resistant mental health conditions, who participated in a weeklong group-based psychedelic retreat involving psilocybin, the study unveils the intricate interplay between psychedelic-assisted therapy, memory, and narrative in the healing process.ResultsThe research findings suggest that beyond the commonly acknowledged therapeutic effects of psychedelic drugs, psilocybin can facilitate the retrieval of repressed or forgotten traumatic memories, allowing for conscious awareness, recognition, and reconciliation. A noteworthy aspect of the healing progression observed is the re-narration of one's identity and biographical circumstances following the recovery of unresolved traumatic memories.ConclusionsThis study underscores the importance of memory and self-narrative in the therapeutic landscape of psychedelic-assisted therapy for trauma. The article concludes by advocating for continued exploration in future research regarding the complex dynamics of memory and self-narrative in the healing journey within psychedelic science and trauma studies.
Os benefícios da leitura compartilhada de livros para o desenvolvimento linguístico-cognitivo de crianças com Transtorno do Espectro Autista
Authors: Silveira Diele Martins , Pereira Aline Elisabete 
Published: October 2024

O presente artigo visa demonstrar os benefícios da leitura compartilhada (LC) de livros para o desenvolvimento linguístico-cognitivo de crianças com Transtorno do Espectro Autista (TEA) durante a primeira infância. Para isso, se apoia no conceito de leitura compartilhada (LC), proposto por Gabriele Morais (2017) e explica e caracteriza o TEA, com base em Liberalesso (2020) e Stravogiannis (2023). Trata-se de um pesquisa documental em duas bases de dados eletrônicas: SciELO e Portal de Periódicos Capes, a partir dos DECs: “leitura compartilhada”; “desenvolvimento linguístico-cognitivo”; “Transtorno do Espectro Autista”; em português, inglês e espanhol, com combinação do operador booleano “AND”. Foram considerados aptos à análise estudos publicados no período de 2013 a 2024, com o foco em participantes de 0 a 6 anos. Os resultados revelaram que, no Brasil, não há pesquisas sobre o tema envolvendo, especificamente, crianças autistas, e o número de estudos realizados com crianças típicas é escasso, considerando-se as bases de dados selecionadas. Por outro lado, em outros países, esse tema é bastante explorado, apresentando uma variedade de pesquisas com crianças neurotípicas e, especialmente, com crianças TEA. Portanto, foi necessário recorrer a outras fontes de pesquisa para obter dados sólidos que confirmam a eficácia da prática de LC para o desenvolvimento linguístico-cognitivo de crianças autistas, fato que abre possibilidades para futuras investigações, especialmente no âmbito nacional.
The Third-Person Effect and Islamic Religiosity: Perceptions of Moral and Non-Moral Issues on Social Networking Sites among IIUM Students
Authors: Bawazir Ala , Same'e Somia Abdul , Mansoor Hasan M. 
Published: October 2024

Third-Person Effect theory (TPE) postulates that audiences deny the media's direct impact on themselves but perceive the same media as having a larger impact on others. This study examines TPE and its relationship with Islamic religiosity in shaping perceptions of moral and non-moral issues on social networking sites (SNS) among students at the International Islamic University Malaysia (IIUM). Another objective of this study is to determine how students perceive the effect of moral and non-moral issues in SNS on themselves compared to others. This study employed a quantitative design, with 357 students from the IIUM serving as respondents. The findings indicate that participants perceive moral issues as affecting others more than themselves, which is consistent with TPE. However, non-moral issues are perceived as influencing both the self and others. The results also indicate that Islamic religiosity positively affects the perceived impact of moral issues on others and non-moral issues on oneself in SNS. The data were analyzed using SPSS, with paired t-tests comparing self versus others' perceptions of moral and non-moral issues on SNS. The findings confirm that students perceive moral issues as having a greater impact on others than on themselves, aligning with TPE. Conversely, non-moral issues are perceived as influencing both the self and others, demonstrating SPE. The study also reveals that Islamic religiosity positively influences the perceived effect of moral issues on others and non-moral issues on oneself in SNS.
Glucose Detection Based on Light Reflection in Modulated Optical Fibers for Continuous Diabetes Monitoring
Authors: Gianti Mahmudah Salwa , Fauzi Ahmad , Wahid Muhammad Rizalul , Ridwan Taufik , Mulya Tri Seda 
Published: October 2024

<span lang="EN-US">Diabetes mellitus is a chronic disease characterized by elevated blood glucose levels. Approximately 463 million adults worldwide have diabetes, and nearly half of them remain undiagnosed. Early diagnosis and treatment of diabetes are crucial to prevent serious complications. Continuous glucose monitoring (CGM) offers numerous advantages over traditional fingertip blood glucose measurements. CGM allows patients to track their glucose levels in real time, identify patterns, and adjust their diet and medication appropriately. This research presents a novel optical fiber-based glucose sensor utilizing the macrobending modulation technique. This method offers several advantages, including ease of use, low cost, and strong signal generation. The sensor exploits the refractive index difference between the glucose solution and the optical fiber. Variations in glucose concentration induce changes in the refractive index, which are converted into voltage signals. The sensor exhibits a sensitivity of 337 mV/decade and demonstrates a linear relationship between the voltage signal and glucose concentration within the range of 0-10 mM. The macro bending-modulated optical fiber sensor shows potential as a simple, cost-effective, and efficient CGM tool. Further research is necessary to enhance the sensor's sensitivity and stability and to evaluate its performance in biological samples. </span>
Food Image Segmentation based on Deep and Shallow Dual-branch Network
Authors: Xiao Zhiyong , Li Yang , Deng Zhaohong 
Published: October 2024

Abstract

Food image segmentation is an important research area within the fields of computer vision and machine learning. Traditional methods often input high-resolution food images at large sizes directly into network models, which leads to high computational costs. Additionally, effectively distinguishing between different foods with similar appearances and the same food in different forms poses a significant challenge. This paper introduces a dual-branch structure network based on Swin Transformer and convolutional neural networks (FDSNet), which significantly reduces the computational costs of processing large-size input images. Furthermore, this study introduces a multi-scale feature fusion technique that effectively integrates feature information from different scales and levels, enabling the model to more accurately segment and recognize different foods. Our method can more precisely perform food image segmentation, helping people improve their diets and manage health better. Training and testing on the FoodSeg103 and UECFoodPixComplete public food datasets have shown that our model achieves mean Intersection over Union (IoU) scores of 47.34 and 75.89, respectively, demonstrating higher accuracy and computational efficiency compared to other methods.
Trapping and imaging dynamic battery nanointerfaces via electrified cryo-EM
Authors: Li Yuzhang , Wang Chongzhen , Kim Jung Tae , Yuan Xintong , Kim Jin Koo , Liu Bo , Zhao Dingyi , Mecklenburg Matthew 
Published: October 2024

Abstract

The electrified interface between a liquid and a solid underpins diverse phenomena, from ion-transfer during battery operation to action potentials enabling biological communication. However, conventional tools are blind to the nanoscale dynamics of this metastable interface, leaving key gaps in our understanding. We introduce electrified cryogenic electron microscopy (eCryo-EM), a tool that rapidly freezes and kinetically traps these dynamic states during battery operation for nanoscale imaging. This allows quantification of early-stage growth kinetics of the solid electrolyte interphase (SEI) that governs battery performance. We discover an ultrathin inorganic layer (<2 nm) within the SEI interior that is found to control ion and electron transport, revising our understanding of battery calendar aging, rate performance, and SEI growth mechanism. Slower growth kinetics of this inner SEI layer correlates with improved battery performance, providing new insight into enhancing the passivation properties of this interior structure. Our work establishes eCryo-EM as a foundational technique to image the electrified liquid-solid interface, which has broad impact spanning electrochemistry and biology.
Does the Psychological Capital of Government Employees Affect Job Performance?——A Survey of 2357 Government Employees in China
Authors: Jia Liangting , Zhang Peng 
Published: October 2024

Abstract

As China advances the construction of a modern national governance system and governance capacity, improving the job performance of government employees is a crucial component. On the basis of positive psychology theory, this paper conducts an empirical study on the impact of psychological capital on job performance by surveying 2,357 government employees. We also examine whether psychological capital affects job performance through job engagement and whether job satisfaction plays a moderating role. The results indicate that the psychological capital of government employees has a significant positive effect on their job performance. Psychological capital can enhance job performance by improving job engagement. As job satisfaction increases, the positive impact of psychological capital on job performance also strengthens. In addition, female, highly educated and post-1990s government employees tend to have relatively higher job performance and job satisfaction. Based on these findings, it is recommended that the government implement targeted psychological capital training and development programs to improve the overall work efficiency and service quality of government employees.
Melatonin-Induced Enhancement of Drought Tolerance in Okra: A Detailed Analysis of Physiological, Biochemical, and Metabolic Adaptations
Authors: Aswathi Gopal , Ravichandran Veerasamy , Vijayalakshmi Dhashnamurthi , Senthil Alagarsamy , Arul Loganathan , Radhamani Sengodan , Jagadeeswaran Ramasamy , Pitchaimuthu Mottaiyan 
Published: October 2024

Abstract

As climate change intensifies, drought stress presents a critical challenge for horticultural crops like okra (Abelmoschus esculentus). The effectiveness of melatonin in reducing drought stress is investigated in this study. The treatments include: Absolute control (fully irrigated), control (Drought D), Drought and seed treatment with 100 µM melatonin (MT- ST), Drought and foliar spray of 100 µM melatonin (MT- FS), and drought stress with combined effect of seed treatment and foliar spray of 100 µM melatonin (MT - ST + FS). Physiological parameters such as photosynthetic rate, stomatal conductance, transpiration rate, Fv/Fm ratio, and chlorophyll content values were evaluated, alongside biochemical parameters including malondialdehyde, proline content, membrane stability index and antioxidant enzyme activities such as catalase and peroxidase were quantified. Melatonin supplemented as seed treatment and foliar spray enhanced both physiological and biochemical parameters including antioxidant activity compared to drought control (D). Metabolite profiling identified bioactive compounds (mainly carbohydrates and amino acids) contributing to drought tolerance in okra. The results highlights that application of 100 µM melatonin via seed treatment and foliar spray enhances drought tolerance in okra, suggesting its potential to enhance crop resilience under water-deficit conditions.
The NME7 gene is involved in the kinetics of glucose regulation
Authors: Vejražková Daniela , Včelák Josef , Vaňková Markéta , Lukášová Petra , Svojtková Michaela , Grimmichová Tereza , Kvasničková Hana , Tura Andrea , Šedová Lucie , Šeda Ondřej , Chocholová Denisa , Kočová Kateřina , Bendlová Běla 
Published: October 2024

Abstract

The shape of the glycemic curve during the oral glucose tolerance test (OGTT) can predict type 2 diabetes mellitus (T2DM). Given that T2DM is common in several ciliopathies, the NME7 gene (non-metastatic cells 7), encoding a recognized member of the ciliome, was included in our panel of 19 candidate genes for glucose metabolism disturbances. The aim was to find out whether the variability of any of the genes is associated with the shape of the 3-hour glycemic curve. The study included 1,262 OGTT curves categorized into four groups according to their shape: monophasic, biphasic, triphasic and more complex multiphasic. Among all tested genes, only NME7 variants showed significant results. In the group with a biphasic trajectory, which is characterized by certain health benefits, we saw higher frequencies of wild-type homozygotes of the three linked NME7polymorphisms rs10732287 (p<0.01), rs4264046 (p=0.01) and rs10800438 (p=0.03). In contrast, two other variants of this block, rs4656659 (p=0.01) and rs2157597 (p=0.05), showed lower proportion of wild-type homozygotes among biphasic trajectories. In conclusion, a cluster of five linked NME7 polymorphisms showed strong association with a biphasic glycemic curve. Given the compelling health benefits associated with a biphasic curve, variability in the NME7 gene represents another piece of the complex mosaic influencing healthy energy processing.
A Causality Dilemma – Association of COVID-19 severity with 10-years risk of Cardiovascular Diseases in Western Indians
Authors: Shah Komal , VP Varna , Sharma Kamal , Pandey Shubhangini , Shukla Aakansha , Shah Hasmukh , Saxena Deepak 
Published: October 2024

Abstract

Background Relationship between COVID-19 and Cardiovascular diseases (CVD) is complex which still lacks clarity on causality. Present study aimed to compare CVD risk of hospitalized and non-hospitalized COVID patients.
Methods Current cross-sectional study included, 943 participants reporting a history of RT-PCR confirmed COVID-19 infection from Western India. After obtaining written consent, details of demographic, chronic disease history, anthropometric parameters were recorded and blood sugar, lipid, hs-CRP, NT-proBNP, QRISK score were assessed. Results Out of 943, 824 (85.6%) recovered with home isolation (group 1), whereas 119 (14.4%) participants required hospitalized (group 2). Demographic characteristics were comparable between the groups, however mean blood pressure and other anthropometric parameters were higher (p<0.05) in hospitalized patients as compared to their counterparts. Slightly greater proportion of new hypertensive (18.5% vs 16.5%) and diabetic (2.3% vs 1.2%) cases were reported in hospitalized patients. Mean blood sugar, lipids, hs-CRP and NT-proBNP were higher (p<0.05) in group 2. 10-years CVD risk was almost double in hospitalized patients as compared to home isolated patients (12.1±5.9% vs 6.2±2.6%; p<0.05).
Conclusion The study clearly indicates that patients with history of severe COVID infection are prone to CVD and requires clinical attention, however causality between the two still needs further studies.
Learning a Photorealism Score for 2D Images Extracted from a Railway Driving 3D Simulator]{Learning a Photorealism Score for 2D Images Extracted from a Railway Driving 3D Simulator
Authors: Muzeau Julien , Faure-Vincent Denis , Ladret Patricia , Caplier Alice 
Published: October 2024

Abstract

3D modeling consists in describing objects thanks to a cloud of points in the three-dimensional space. It is ubiquitous nowadays and employed in many different fields such as video games, animation movies, architecture or medical applications. Subsequently, 2D images are retrieved from such 3D models through a process called 3D rendering. Recent hardware and software developments allow to approximate the real-world physics in an ever more precise manner. However, the question of the photorealism of such images remains. In this paper, we investigate in particular the photorealism of images extracted from 3D railway driving simulators. Two contributions are detailed in this article. First, we propose a CNN-based method designed to associate a photorealism score to any simulated image. It specifically quantizes the perceptual difference between computer-generated railroad images and natural ones. The second and main contribution of this work consists in the conception and implementation of a subjective experiment conducted so as to perceptually validate the aforementioned score. Human annotators are asked to specify which of two displayed images is more photorealistic, repeated over several pairs of images. After analysing the results, we conclude that a 96\% correlation exists between the proposed photorealism score and human visual perception.
Optimizing the Figure of Merit for DGTFET Ferroelectric Devices Using a Machine Learning-using Genetic Algorithm
Authors: Guenifi Naima , Chabane Houda , Rahi Shiromani Balmukund , Dibi Kadidja 
Published: October 2024

Abstract

In this research, we conducted in-depth analysis of the application of ferroelectric tunneling (FeTFET) for emerging complex neural networks. We explored the use of Neural Networks (ANN) to optimize the IOFF-state current in a dual-gate FeDGTFET tunnel transistor structure, incorporating innovative materials such as ferroelectric BaTiO3 and hafnium dioxide HfO2 as a high permittivity gate oxide. This study considered specific features of the FeDGTFET structure, including doping and permittivity, while examining the complex interactions between synapses, weights, and dendrites within this configuration. By applying the back-projection algorithm based on gradient descent principles, we aimed to minimize model error and adjust structure parameters for improved accuracy. Subsequently, we used fitting techniques to align the model with experimental data, considering the unique properties of the high permittivity oxides. Finally, utilizing a genetic algorithm (GA), we optimized the model to predict IOFF current with enhanced accuracy, assessing performance through metrics such as Mean Squared Error (RMSE) and R-squared (R²) value. The results of this study demonstrate that the GA-Optimized Neural Network model shows promising potential for predicting IOFF current in FET tunnel transistors based on BaTiO3 ferroelectrics and high permittivity oxides. The database was integrated through a communication interface between TCAD-SILVACO and Matlab.
Monitoring the impact of EU F-gas regulation on HFC-134a emissions through a comparison of top-down and bottom-up estimates.
Authors: Annadate Saurabh , Mancinelli Enrico , Gonella Barbara , Moricci Federica , O’Doherty Simon , Stanley Kieran , Young Dickon , Vollmer Martin , Cesari Rita , Falasca Serena , Giostra Umberto , Maione Michela , Arduini Jgor 
Published: October 2024

Abstract

HFC-134a is the most prevalent hydrofluorocarbon used as a replacement for ozone-depleting CFCs and HCFCs. Due to its high global warming potential, it is regulated under various European and global frameworks, underscoring the importance of tracking its emissions. Emissions derived by the commonly used, bottom-up, methodology are affected by a certain degree of uncertainty. The bottom-up estimates can be aided with an independent top-down estimate based on atmospheric observations combined with an atmospheric transport model. This study presents HFC-134a emissions for Europe, with a specific focus on Italy, from 2008 to 2023. The emissions were estimated using a Bayesian inversion methodology, based on atmospheric observations collected at four European stations. Our analysis reveals a slightly increasing trend in HFC-134a emissions for Italy from 2008 to 2015 of 0.17 Gg/yr, followed by a steady decrease thereafter, highlighting the effect of European regulation on fluorinated gases that came into force in 2014. We observed a reduction in HFC-134a emissions in the Po Basin inferred from the inversion method for 2020, likely due to mobility restrictions imposed during the COVID-19 pandemic. The observed mild seasonality in emissions may be partly attributed to higher air-conditioning activity during summer. A comparison with the Italian national emission inventories showed that the iterative bottom-up estimates improved, with 2024 national emissions aligning with our inversion results. This study emphasises the need for collaboration between the two independent approaches to enhance the accuracy of emission estimates. Such cooperation is crucial to narrowing the gap in quantifying emissions of potent greenhouse gases and effectively assessing the progress of international policies and regulations.
Supersensitive photonic crystal fiber device (PCFD) for the accurate determination of sugar concentration (SC) in an aqueous solution
Authors: Hasanein Mahmoud Abu , Daher Malek G. , Faragallah Osama S. , Armghan Ammar , Almawgani Abdulkarem H. M. , Upadhyay Anurag , Singh Shivam 
Published: October 2024

Abstract

Presently, photonic crystal fiber devices (PCFDs) have gotten a grand importance in various research arenas as a result of their valuable advantages in different applications. One of the most central applications is their usage as detectors to sense several analytes and this is for the reason that these PCFDs are described by high precision and rapidity in sensing process. In this effort, a PCFD is projected as a detector to determine various SCs in an aqueous solution. COMSOL Multiphysics version 5.6 with the finite element approach (FEA) and perfectly matched sheet (PMS) boundary circumstance is expended to build and examine the suggested PCFD. Zeonex matter is exploited in our PCFD owing to its small absorption loss. Several PCFD configurations are studied at x and y-axis. Most optical factors for the suggested PCFD are analyzed and compared together for each SC at the different PCFD configurations and both polarizations. All these factors are analyzed in the frequency scale from 1.0 to 2.5 THz. The highest relative sensitivity (RSE) values are 99.42% for SC of 30% at y-polarization and optimum + 2% configuration. It is proved that enlarging the dimensions of the core zone compared to the zone of the air holes leads to an improvement in the RSE. Also, this PCFD revealed incredibly tiny values of CLS and EMLS. Moreover, all the other optical factors appeared the adeptness of the suggested PCFD in determining the various SCs in the aqueous solution.