bluuebunny/crossref_metadata_2025_split huggingface dataset:
Help-seeking intention for mental illness and associated factors among Dessie town residents in Northeast Ethiopia
Authors: Gelaye Habtam , Andualem Atsedemariam , Beyene Abeba , Gezie Hailemariam 
Published: December 2024

AbstractDespite the increasing global burden of mental illness and the availability of effective evidence-based treatments, many individuals with mental illness do not seek professional help. Therefore, this study aimed to assess help-seeking intention for mental illness and associated factors among Dessie town residents, Northeast Ethiopia, 2021. A community-based cross-sectional study was conducted among 501 Dessie town residents. The data were collected by face-to-face interview. The General Help Seeking Questionnaire was used to assess help-seeking intention. Bivariable and multivariable logistic regression analysis techniques were used. Finally, a statistically significant level was declared at a p-value less than 0.05. Among 501 participants, 67.5% were likely to seek help from health professionals. Being female (AOR = 4.695, 95% CI = 1.63– 13.50), being single (AOR = 0.330, 95% CI = 0.12–0.89), and having good knowledge (AOR = 3.030, 95% CI = 1.25–7.35) were significantly associated with help-seeking intention. This study indicated that the participants’ help-seeking intention was inadequate. Sex, marital status, monthly income, and knowledge of mental illness were found to be associated with help-seeking intentions for mental illnesses. Therefore, community healthcare workers, healthcare administrators, and religious and community leaders should work to enhance the help-seeking intention of the community.
A randomised controlled pilot trial protocol for patient led cognitive gamified training during haemodialysis
Authors: Aksoy Murat , Hunter Samantha , Asghar Aziz U. R. , Bhandari Sunil 
Published: December 2024

AbstractDisruptions in cognitive function have been reported in individuals undergoing haemodialysis and those with chronic kidney disease. This pilot study protocol primarily assesses the feasibility and acceptability of using mobile cognitive gaming apps for patient-led cognitive training during haemodialysis sessions. The protocol consists of three phases: (1) reviewing and evaluating available cognitive gaming apps, (2) conducting focus groups/interviews with people with kidney disease to determine app preferences, and (3) undertaking a quasi-experimental randomised controlled trial to compare cognitive outcomes between a patient-led app intervention group and a standard care control group over four months. Primary outcomes will include changes in cognitive test scores [Montreal Cognitive Assessment (MoCA), Modified Mini-Mental State Exam (3MSE), Rapid Objective Working Memory Assessment (ROWMA)], while secondary outcomes will encompass quality of life measures [Patient-Reported Outcomes Measurement (PROM) Kidney Disease Quality of Life Short Form (KDQoL-SF™) v 1.3, Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Instrument, European Quality of Life Five Dimension (EQ-5D)]. If demonstrated to be effective, this novel method of utilising gamified cognitive training applications could potentially mitigate cognitive decline and improve the well-being of people receiving haemodialysis without necessitating significant clinical resources. The findings from this research will guide the development of a larger definitive randomised trial in the future.
Direct detection of 4-dimensions of SARS-CoV-2: infection (vRNA), infectivity (antigen), binding antibody, and functional neutralizing antibody in saliva
Authors: Mohammadi Aida , Chiang Samantha , Li Feng , Wei Fang , Lau Chang S. , Aziz Mohammad , Ibarrondo Francisco J. , Fulcher Jennifer A. , Yang Otto O. , Chia David , Kim Yong , Wong David T.W. 
Published: December 2024

AbstractWe developed a 4-parameter clinical assay using Electric Field Induced Release and Measurement (EFIRM) technology to simultaneously assess SARS-CoV-2 RNA (vRNA), nucleocapsid antigen, host binding (BAb) and neutralizing antibody (NAb) levels from a drop of saliva with performance that equals or surpasses current EUA-approved tests. The vRNA and antigen assays achieved lower limit of detection (LOD) of 100 copies/reaction and 3.5 TCID₅₀/mL, respectively. The vRNA assay differentiated between acutely infected (n = 10) and infection-naïve patients (n = 33) with an AUC of 0.9818, sensitivity of 90%, and specificity of 100%. The antigen assay similarly differentiated these patient populations with an AUC of 1.000. The BAb assay detected BAbs with an LOD of 39 pg/mL and distinguished acutely infected (n = 35), vaccinated with prior infection (n = 13), and vaccinated infection-naïve patients (n = 13) from pre-pandemic (n = 81) with AUC of 0.9481, 1.000, and 0.9962, respectively. The NAb assay detected NAbs with a LOD of 31.6 Unit/mL and differentiated between COVID-19 recovered or vaccinated patients (n = 31) and pre-pandemic controls (n = 60) with an AUC 0.923, sensitivity of 87.10%, and specificity of 86.67%. Our combo assay represents a significant technological advancement to simultaneously address SARS-CoV-2 infection and immunity, and it lays the foundation for tackling potential future pandemics.
Spatiotemporal patterns and drivers of orchard meadow loss in South Tyrol, Italy
Authors: Schönafinger Alexander , Egarter Vigl Lukas , Tasser Erich 
Published: December 2024

AbstractOrchard meadows, a specific agroforestry system characterised by scattered high-stem fruit trees, are a traditional element of several cultural landscapes in Central Europe and provide important ecosystem services. Since the middle of the 20th century, orchard meadows have drastically declined across Europe. Spatial information on the drivers and patterns of such a decline in several regions in Central Europe is lacking. In this study, we aimed to provide the first detailed insights into the development of orchard meadows in South Tyrol. We assessed the current distribution of orchard meadows in South Tyrol (Northern Italy) and analysed the patterns and drivers of their decline over the last 75 years. Aerial images of the orchard meadows in South Tyrol from the 1950s up to the 2020s were examined, and changes in their distribution were statistically analysed. The results revealed that the historical orchard meadow area in South Tyrol has decreased by more than 6,000 ha (−95%) over the past 75 years, showing one of the largest reductions in Central Europe. Orchard meadow loss was highest at lower elevations (–5,155 ha), shallow slopes (–4,313 ha), and expositions towards the south (–5,035 ha). Orchard meadows have declined due to agricultural intensification towards the establishment of modern fruit orchards (56%) and intensively managed grasslands (8%), urbanisation (23%), and reforestation (6%), and other types of land use/land cover (6.5%). Only 0.5% of the traditional orchard meadows have been preserved. The results suggest that orchard meadows are at a high risk of disappearing from the South Tyrolean landscape, resulting in the loss of genetic diversity of many local or indigenous fruit varieties (especially apples and pears). Immediate action is needed to safeguard the current orchard meadow population and appropriate management measures are needed to highlight the multiple values of orchard meadows and provide a valuable alternative to intensive arable farming.
Numerical proceeding to calculate impurity states in 2D semiconductor heterostructures
Authors: Akimov Volodymyr , Tulupenko Viktor , Demediuk Roman , Tiutiunnyk Anton , Duque Carlos A. , Morales Alvaro L. , Laroze David , Mora-Ramos Miguel Eduardo 
Published: December 2024

AbstractThe article provides and discusses details of numerical proceeding for the expansion method to calculate energy positions and wave functions of the localized and resonant electronic states emerging in quantum well-type semiconductor nanostructures because of perturbation of confined states by the Coulomb potential of the hydrogenic impurity center. Effective mass approximation is used. Several excited both resonant and non-resonant states are calculated and classified for the case of a simple rectangular GaAs/AlGaAs quantum well. Results are compared to the ones in literature.
Analysis of plasmon modes in Bi2Se3/graphene heterostructures via electron energy loss spectroscopy
Authors: Moorsom Timothy , McCauley Mairi , Nizamuddin Bin Muhammad Mustafa Ahmad , Ramadan Sami , Burton Joel , Sasaki Satoshi , MacLaren Donald A. , Petrov Peter K. 
Published: December 2024

AbstractTopological Insulators (TIs) are promising platforms for Quantum Technology due to their topologically protected surface states (TSS). Plasmonic excitations in TIs are especially interesting both as a method of characterisation for TI heterostructures, and as potential routes to couple optical and spin signals in low-loss devices. Since the electrical properties of the TI surface are critical, tuning TI surfaces is a vital step in developing TI structures that can be applied in real world plasmonic devices. Here, we present a study of Bi2Se3/graphene heterostructures, prepared using a low-cost transfer method that reliably produces mono-layer graphene coatings on Bi2Se3 flakes. Using both Raman spectroscopy and electron energy loss spectroscopy (EELS), we show that the graphene layer redshifts the energy of the $$\pi$$ plasmon mode in Bi2Se3, creating a distinct surface plasmon that differs significantly from the behaviour of a TI-trivial insulator boundary. We demonstrate that this is likely due to band-bending and electron transfer between the TI surface and the graphene layer. Based on these results, we outline how graphene overlayers can be used to create tuneable, stable plasmonic materials based on topological insulators.
Investigation of factors affecting the sound absorption behaviour of 3D printed hexagonal prism lattice polyamide structures
Authors: Vašina Martin , Měsíček Jakub , Mánek Martin , Ma Quoc-Phu , Hajnyš Jiří , Petrů Jana 
Published: December 2024

AbstractThe aim of this work is to investigate the sound absorption properties of open-porous polyamide 12 (PA12) structures produced using Selective Laser Sintering (SLS) technology. The examined 3D-printed samples, fabricated with hexagonal prism lattice structures, featured varying thicknesses, cell sizes, and orientations. Additionally, some samples were produced with an outer shell to evaluate its impact on sound absorption. Experiments were conducted using the transfer function method with an acoustic impedance tube in the frequency range of 250 Hz and 6400 Hz. The results showed that the studied geometric factors significantly affected the sound absorption of the PA12 samples. In some cases, the hexagonal prism lattice structures demonstrated relatively high sound absorption properties. Thanks to their properties such as lower weight, recyclability, and resistance to moisture and chemicals, these structures become competitive with commonly used sound-insulating materials, making them promising candidates for sound absorption. Furthermore, numerical simulations using Ansys software confirmed that the sound absorption properties of the open-porous material structures generally increased with higher specific airflow resistance. The findings highlight the advantages of 3D printing technology in producing complex, highly customizable porous structures for noise reduction applications.
Complexity measure in natural time analysis identifying the accumulation of stresses before major earthquakes
Authors: Varotsos Panayiotis A. , Sarlis Nicholas V. , Nagao Toshiyasu 
Published: December 2024

AbstractHere, we suggest a procedure through which one can identify when the accumulation of stresses before major earthquakes (EQs) (of magnitude M 8.2 or larger) occurs. Analyzing the seismicity in natural time, which is a new concept of time, we study the evolution of the fluctuations of the entropy change of seismicity under time reversal for various scales of different length i (number of events). Although the stress might be accumulating throughout the entire process of EQ preparation due to tectonic loading, here we find that the proposed complexity measure reveals different stress accumulation characteristics from those in the long-term background when the system approaches the critical stage. Specifically, we find that anomalous intersections between scales of different i are observed upon approaching a major EQ occurrence. The investigation is presented for the seismicity in Japan since 1984 including the M9 Tohoku EQ on 11 March 2011, which is the largest EQ ever recorded there, as well as for the seismicity before 2017 Chiapas M8.2 EQ, which is Mexico’s largest EQ in more than a century. Based on this new complexity measure, a preprint submitted on 5 December 2023 anticipated the 1 January 2024 M7.6 EQ in Japan.
Constitutive androstane receptor (CAR) functions as a tumor suppressor via regulating stemness in liver cancer
Authors: Bae Sarah Da Won , Nguyen Romario , Yuen Lawrence , Lam Vincent , George Jacob , Qiao Liang 
Published: December 2024

AbstractConstitutive androstane receptor (CAR) is a xenosensor that is almost exclusively expressed in the liver. Studies in rodents suggest an oncogenic role for CAR in liver cancer, but its role in human liver cancer is unclear. We aimed to investigate the functional roles of CAR in human liver cancer with a focus on the liver cancer stem cells. We used bioinformatics to increase our understanding of CAR in human liver cancer and associated stem cell markers. We studied the functional roles of CAR in human liver cancer with a focus on the liver cancer stem cell using siRNA, modulation of CAR activity, and tumorsphere formation assays. We have revealed significant associations between CAR and a wide variety of signalling pathways including stemness signalling. Further in vitro studies have shown that activation of CAR significantly reduces cancer cell stemness and represses proliferation, migration, invasion, and the tumorsphere-forming abilities of liver cancer cells (p < 0.05). Our data demonstrates the unequivocal tumor-suppressive role of CAR in liver cancer. While more detailed mechanistic studies are warranted, the efficacy of CAR xeno-activators in the treatment of advanced hepatocellular carcinoma (HCC) may potentially open a new avenue for liver cancer therapy.
The plausibility of claimed induced seismicity
Authors: Wilkinson Max , Mhana Najwa , Wilson Miles P. , Foulger Gillian R. , Tezel Timur , Gluyas Jon G. 
Published: December 2024

AbstractClaims of industrially induced seismicity vary from indisputable to unpersuasive and yet the veracity of industrial induction is vital for regulatory and operational practice. Assessment schemes have been developed in response to this need. We report here an initial assessment of the reliability of all globally known cases of proposed human-induced earthquakes and invite specialists on particular cases to refine these results. 1235 cases were assessed, requiring over 1000 h of work. From the 881 cases for which scorable evidence is available, we class 87% as ‘Confidently Induced’, 10% as ‘Probably Induced’, 2% as ‘Equivocal’ and < 1% as ‘Confidently Natural’. The most seismogenic activities are fracking, research, geothermal, water reservoir impoundment, conventional oil and gas. Least seismogenic activities are construction, deep penetrating bombs, coal bed methane. 354 cases (29%) lack enough information to be assessable. Future work could include applying data mining techniques including natural language processing and AI to uncover new evidence. Future best practice for rapid assessment of cases would ideally involve an independent panel of scientists who rapidly apply a questionnaire scheme, reach consensus, and inform a response.
Innovative modified-net architecture: enhanced segmentation of deep vein thrombosis
Authors: B. Pavihaa Lakshmi , S. Vidhya 
Published: December 2024

AbstractA new era for diagnosing and treating Deep Vein Thrombosis (DVT) relies on precise segmentation from medical images. Our research introduces a novel algorithm, the Modified-Net architecture, which integrates a broad spectrum of architectural components tailored to detect the intricate patterns and variances in DVT imaging data. Our work integrates advanced components such as dilated convolutions for larger receptive fields, spatial pyramid pooling for context, residual and inception blocks for multiscale feature extraction, and attention mechanisms for highlighting key features. Our framework enhances precision of DVT region identification, attaining an accuracy of 98.92%, with a loss of 0.0269. The model also validates sensitivity 96.55%, specificity 96.70%, precision 98.61%, dice 97.48% and Intersection over Union (IoU) 95.10% offering valuable insights into DVT segmentation. Our framework significantly improves segmentation performance over traditional methods such as Convolutional Neural Network , Sequential, U-Net, Schematic. The management of DVT can be improved through enhanced segmentation techniques, which can improve clinical observation, treatment planning, and ultimately patient outcomes.
Deep reinforcement learning and fuzzy logic controller codesign for energy management of hydrogen fuel cell powered electric vehicles
Authors: Rostami Seyed Mehdi Rakhtala , Al-Shibaany Zeyad , Kay Peter , Karimi Hamid Reza 
Published: December 2024

AbstractHydrogen-based electric vehicles such as Fuel Cell Electric Vehicles (FCHEVs) play an important role in producing zero carbon emissions and in reducing the pressure from the fuel economy crisis, simultaneously. This paper aims to address the energy management design for various performance metrics, such as power tracking and system accuracy, fuel cell lifetime, battery lifetime, and reduction of transient and peak current on Polymer Electrolyte Membrane Fuel Cell (PEMFC) and Li-ion batteries. The proposed algorithm includes a combination of reinforcement learning algorithms in low-level control loops and high-level supervisory control based on fuzzy logic load sharing, which is implemented in the system under consideration. More specifically, this research paper establishes a power system model with three DC-DC converters, which includes a hierarchical energy management framework employed in a two-layer control strategy. Three loop control strategies for hybrid electric vehicles based on reinforcement learning are designed in the low-level layer control strategy. The Deep Deterministic Policy Gradient with Twin Delayed (DDPG TD3) is used with a network. Three DRL controllers are designed using the hierarchical energy optimization control architecture. The comparative results between the two strategies, Deep Reinforcement Learning and Fuzzy logic supervisory control (DRL-F) and Super-Twisting algorithm and Fuzzy logic supervisory control (STW-F) under the EUDC driving cycle indicate that the proposed model DRL-F can ensure the Root Mean Square Error (RMSE) reduction for 21.05% compared to the STW-F and the Mean Error reduction for 8.31% compared to the STW-F method. The results demonstrate a more robust, accurate and precise system alongside uncertainties and disturbances in the Energy Management System (EMS) of FCHEV based on an advanced learning method.
Loss of Hoxa5 function affects Hox gene expression in different biological contexts
Authors: Frenette Béatrice , Guéno Josselin , Houde Nicolas , Landry-Truchon Kim , Giguère Anthony , Ashok Theyjasvi , Ryckman Abigail , Morton Brian R. , Mansfield Jennifer H. , Jeannotte Lucie 
Published: December 2024

AbstractHoxa5 plays numerous roles in development, but its downstream molecular effects are mostly unknown. We applied bulk RNA-seq assays to characterize the transcriptional impact of the loss of Hoxa5 gene function in seven different biological contexts, including developing respiratory and musculoskeletal tissues that present phenotypes in Hoxa5 mouse mutants. This global analysis revealed few common transcriptional changes, suggesting that HOXA5 acts mainly via the regulation of context-specific effectors. However, Hox genes themselves appeared as potentially conserved targets of HOXA5 across tissues. Notably, a trend toward reduced expression of HoxA genes was observed in Hoxa5 null mutants in several tissue contexts. Comparative analysis of epigenetic marks along the HoxA cluster in lung tissue from two different Hoxa5 mutant mouse lines revealed limited effect of either mutation indicating that Hoxa5 gene targeting did not significantly perturb the chromatin landscape of the surrounding HoxA cluster. Combined with the shared impact of the two Hoxa5 mutant alleles on phenotype and Hox expression, these data argue against the contribution of local cis effects to Hoxa5 mutant phenotypes and support the notion that the HOXA5 protein acts in trans in the control of Hox gene expression.
Childhood adversity and peer influence in adolescent bullying perpetration
Authors: Ugwu Lawrence E. , Ramadie Kedibone J. , Ajele Wojujutari Kenni , Idemudia Erhabor Sunday 
Published: December 2024

AbstractBullying among South African adolescents is a critical public health issue. This study explores the relationship between childhood adversity, peer influence, and personality traits in predicting bullying perpetration. Data from 769 high school learners were analysed using Structural Equation Modelling. Findings indicate that childhood adversity predicts bullying perpetration, mediated by peer influence and moderated by personality traits like conscientiousness, extraversion, and emotional stability. These results support Social Learning Theory, emphasising observed behaviours and peer dynamics in bullying. Practical implications include targeted interventions addressing childhood adversity and fostering positive peer interactions and personality development.
Analysing the support mechanisms of the vaginal ring pessary on supine and upright MRI
Authors: van den Noort Frieda , de Alba Alvarez I. , van der Steen A. , Smelt A. D. , Simonis F. F. J. , Grob A. T. M. 
Published: December 2024

AbstractVaginal pessaries have been used for millennia to alleviate symptoms of pelvic organ prolapse (POP). Despite their long-standing use, the success rate of pessary treatment is approximately 60%, and the underlying mechanisms of support are not well understood. This study aims to investigate three previously proposed hypotheses regarding the support mechanisms of pessaries, utilizing supine and upright magnetic resonance imaging (MRI): (1) support by bony structures, (2) support by levator ani muscles (LAM), and (3) the uterus keeping the pessary in place by acting as a lever. Thirty POP patients, with a successful pessary fit for more than 3 months, underwent MRI scans in both upright and supine position. The position of the pelvic bony structures, LAM, uterus, and pessary were analysed by placing corresponding points on these structures and comparing the differences between supine and upright. Also, the angle of the pessary with the horizontal plane of the pelvic inclination corrections system was analysed. Principal component analysis was applied to evaluate how the positions of the LAM and the pessary changed between the two positions. The lowest point of the pessary descends below the lowest point of the bony structures in upright position, disproving the first hypothesis. The pessary significantly descends towards the LAM from supine to upright, but does not drop below it, strengthening the second hypothesis. The pessary angle is below 90° in upright position, the uterus is positioned in the pessary centre and remains constant from supine to upright, strengthening the third hypothesis.