bluuebunny/crossref_metadata_2025 huggingface dataset:
“I have some wishes, which are actually demands.” A qualitative mixed methods study on the impact of consumerism on the therapeutic relationship in mental healthcare
Authors: Krikken Mulders L. T. E. , Tonkens E. H. , Trappenburg M. J.
Published: November 2024

Introduction

Alongside the logic of care, many Western welfare states have introduced market elements or a logic of choice in their healthcare systems, which has led to consumerist behavior in patients. For the medical field, it is well documented how consumerism creates complex ethical dilemmas and undermines ways of thinking and acting crucial to healthcare. Little is known about these dynamics in mental healthcare.

Methods

This study used a qualitative mixed methods design, combining 180 online patient narratives (blogs) with 25 interviews with therapists in a grounded theory approach.

Results

Findings show that articulate behavior can be divided into two categories: assertive and adamant. While assertive behavior is understood as an integral, reciprocal part of therapy and is stimulated by therapists, adamant or consumerist behavior is experienced as damaging the relationship—the “commodity” the patient is seeking to obtain, as the single most important predictor of treatment success. Findings also show that articulate behavior in both varieties takes a different shape over time during the course of treatment.

Discussion

Adamant behavior clashes with the internal logic of care, which is especially problematic in mental healthcare where the relationship with one's therapist is key to successful treatment. Therefore, patients should be taught and helped to display assertive behavior without resorting to adamancy. Individual therapists cannot achieve this alone; this endeavour should be supported by their organizations, societal beliefs about therapy and policy choices.
Residents’ perceptions of urban nature and nature-based solutions in Ouagadougou
Authors: Combary Youmanli Enok Ferdinand , Atchrimi Bernard Tossou
Published: November 2024

With rapid urban growth posing major environmental and social challenges, nature-based solutions (NbS) are at the heart of urban strategies for sustainability and resilience. They help to maintain biodiversity and respond to contemporary climatic and societal challenges. To be best planned and implemented, they need to consider geographical and socio-cultural contexts, including the local perceptions and experiences of residents. Lack of information on social aspects and absence of data are often obstacles to implementation. This article is part of a study on the challenges and opportunities of implementing nature-based solutions for sustainable urban development in Ouagadougou. This study aimed to explore how socio-demographic factors influence perceptions and experiences of urban nature, and to identify implications for urban planning and the implementation of nature-based solutions. Questionnaire surveys were conducted among 401 people, with different socio-demographic profiles and different places of residence. Group interviews with 20 people were then conducted to triangulate the collected data to understand the different interactions between the residents and urban nature. The main results show that, overall, residents perceive urban nature positively. Perceptions and experiences of nature vary considerably according to respondents’ socio-demographic profiles and proximity to green spaces. The study also identified the need for appropriate maintenance and management, as well as participatory planning to align nature-based solutions with residents’ expectations, with a focus on benefits. The recommendations offered to practitioners, planners, and those involved in urban development for implementing nature-based solutions and identifying limitations, such as a lack of revenue data, provide a solid basis for future action.
Do Primates Make Friends Like Humans?
Authors: Roberts Anna Ilona
Published: November 2024

Have you ever wondered what skills you need to make friends? How your brain processes the information that you need to make friends? What features of your daily life make having friends difficult? Primates are the mammals that are most similar to us in the animal kingdom. Primates face similar challenges to humans when it comes to making friends. Primates must understand the goals and intentions of others to make friends. However, the stress they experience in their environments can make understanding others’ goals and intentions difficult. Stress causes primates to switch from understanding goals to understanding behavior alone, meaning they respond only to input from their senses. To overcome this challenge, primates use sounds and gestures when making friends. These are called intentional communication, and they motivate animals to figure out the goals of other animals by using their knowledge of past interactions. Knowing how primates communicate to make friends can help us to understand how humans make friends, too.
Impact of biological sex, concussion history and sport on baseline NeuroTracker performance in university varsity athletes
Authors: Acquin Jean-Michel , Desjardins Yannick , Deschamps Alexandre , Fallu Étienne , Fait Philippe , Corbin-Berrigan Laurie-Ann
Published: November 2024

This study aimed to assess the impact of biological sex, concussion history, and type of sport on the baseline NeuroTracker performance, a test/train three-dimensional multiple object tracking paradigm used in sport contexts, in university level varsity athletes. A total of 136 university level varsity athletes participating in male ice hockey, male or female soccer, female volleyball, and mixed biological sex cheerleading underwent preseason NeuroTracker baseline assessments. Significant differences in NeuroTracker performance were observed based on biological sex (p < 0.01) and type of sport played (p < 0.05). Male athletes and hockey players demonstrated higher NeuroTracker performance compared to their counterparts. However, no significant differences were found in NeuroTracker performance based on the history of concussion. Thus, factors such as biological sex and type of sport played may influence baseline NeuroTracker performance.
Timing of Dose Reductions and Survival Outcomes in Metastatic Breast Cancer Patients Treated with Cyclin-Dependent Kinase 4/6 Inhibitors
Authors: Kubilay Tolunay Pınar , Kurt İnci Bediz , Usta Şura , Topkaç Ali , Karabuğa Berkan , Aydemir Ergin , Öner İrem , Akay Hacan Büşra , Ateş Öztürk , Karaçin Cengiz , Yalçıntaş Arslan Ülkü
Published: November 2024

Background/Objectives: Dose reductions in CDK4/6 inhibitors, such as ribociclib and palbociclib, are often necessary due to treatment-related toxicities in patients with advanced breast cancer. This study aims to evaluate the impact of the timing of dose reductions on progression-free survival (PFS) and overall survival (OS) in a real-world cohort. Methods: This single-center, retrospective study included patients treated with ribociclib or palbociclib between 2019 and 2023 at a cancer center in Turkey. Dose reductions due to drug-related toxicities were recorded, and survival outcomes were analyzed. Patients were categorized based on the timing of dose reductions: within the first 3 months (early) and after 3 months (late). Results: Among 392 patients (mean age 57.13 years), 16.8% had dose reductions within 3 months, 21.7% had late dose reductions, and 61.5% had no dose reductions. The mPFS was 14.26 months for early dose reductions, 33.12 months for late dose reductions, and 20.6 months for no dose reductions (p < 0.001). The mOS was 37.12 months for early dose reductions, not reached for late dose reductions, and 57.76 months for no dose reductions (p < 0.001). Hematological toxicity, primarily neutropenia, was the most common cause of dose reductions. The ECOG performance status, line of therapy, and CDK4/6 inhibitor type were also significant predictors of PFS and OS. Conclusions: Early dose reductions in CDK4/6 inhibitors negatively affect PFS and OS, highlighting the importance of maintaining treatment intensity in the first 3 months. However, late dose reductions do not negatively affect progression-free survival (PFS) or overall survival (OS), with late dose reductions associated with better outcomes. Prospective studies in larger patient populations will further clarify our knowledge on this subject.
Panel Temperature Dependence on Atmospheric Parameters of an Operative Photovoltaic Park in Semi-Arid Zones Using Artificial Neural Networks
Authors: Montecinos Sonia , Rodríguez Carlos , Torrejón Andrea , Cortez Jorge , Jaque Marcelo
Published: November 2024

The performance of photovoltaic solar panels is influenced by their temperature, so there is a need for a tool that can accurately and instantly predict the panel temperature. This paper presents an analysis of the panel temperature’s dependence on atmospheric parameters at an operational photovoltaic park in the semi-arid north of Chile using Artificial Neural Networks (ANNs). We applied the back-propagation algorithm to train the model by using the atmospheric variables tilted solar radiation (TSR), air temperature, and wind speed measured in the park. The ANN model’s effectiveness was evaluated by comparing it to five different deterministic models: the Standard model, King’s model, Faiman’s model, Mattei’s model, and Skoplaki’s model. Additionally, we examined the sensitivity of panel temperature to changes in air temperature, TSR, and wind speed. Our findings show that the ANN model had the best prediction accuracy for panel temperature, with a Root Mean Squared Error (RMSE) of 1.59 °C, followed by Mattei’s model with a higher RMSE of 3.30 °C. We also determined that air temperature has the most significant impact on panel temperature, followed by TSR and wind speed. These results demonstrate that the ANN is a powerful tool for predicting panel temperature with high accuracy.
Research Trends of Thermogravimetric Pyrolysis of Carnauba (Copernicia prunifera) and Thermokinetic Models Based on a Brief Bibliometric Investigation
Authors: Ribeiro Filho Manoel , Medeiros Samuel , Lopes Ada , Cruz Glauber , Rios Maria
Published: November 2024

This study presents a brief bibliometric investigation of thermogravimetric pyrolysis of carnauba biomass (Copernicia prunifera), a palm tree native to northeastern Brazil belonging to the Arecaceae family. The objective was to analyze the scientific production and methods used to evaluate the kinetic parameters of biomass pyrolysis. An analysis was conducted using the Scopus, ScienceDirect, and Web of Science databases, and VOSviewer and Bibliometrix software. The methodology allows the generation of clusters and tables of scientific production, including authors, co-authors, affiliations, institutions, journals, and keywords. The search yielded 1983 articles, and after the application of exclusion criteria, 919 articles were retained, forming the basis for the bibliometric analysis. It provided an overview of thermogravimetric pyrolysis of carnauba research and identified areas that require further study. It also identified which universities and researchers have devoted the most effort to this area of research, the key findings, and areas that require further investment to complement existing research. Additionally, the study indicated the suitability of the Friedman method for determining kinetic parameters in biomass pyrolysis.
Study of Combustion Process Parameters in a Diesel Engine Powered by Biodiesel from Waste of Animal Origin
Authors: Łagowski Piotr , Wcisło Grzegorz , Kurczyński Dariusz
Published: November 2024

The use of biofuels is one way to reduce the increasingly visible harmful effects of diesel engines on the environment. At the same time, it is also a way to gradually reduce dependence on depleting oil resources. New sources for biodiesel production are currently being sought out. The authors of this article have produced esters from animal fat waste, obtaining a biofuel that can power diesel engines while obtaining a way to manage unnecessary waste. For this to be possible, it is necessary to confirm the possibility of using such biofuel to power compression ignition engines. To this end, it is moribund to conduct experimental tests on an engine dynamometer. The results of such studies made it possible to determine how such esters affect the parameters of the combustion process, which was the goal of the authors of this paper. In order to determine the effect of this biofuel on the parameters of the combustion process, indicator graphs of the pressure course in the engine cylinder were recorded. On their basis, heat release characteristics were drawn up and their most important indicators were determined. In addition, the parameters of the indicator charts were determined, such as the maximum pressure and the degree of its build-up during the combustion process. These tests were carried out on a Perkins 1104D-E44TA compression ignition engine, which is widely used in the construction industry as well as in agriculture. In order to be able to compare these results with diesel fuel, the same tests, under the same conditions, were carried out while feeding the engine with diesel fuel. It is worth noting that the tested esters were produced using a reactor designed and built by one of the co-authors of this publication. This reactor is used for the non-industrial production of biofuels from oils of various origins. Studies have shown that feeding the engine with esters results in an increase in the maximum fuel consumption of about 15%. This is dependent on the load and speed. Indicator graphs and their analysis indicated that feeding the engine with esters at lower loads results in higher maximum combustion pressures, depending on the engine load, compared to diesel fuel values by a maximum of about 10%. The calculated values of the degree of pressure increase during the combustion process showed that feeding the engine with esters at most loads results in an increase of up to 40% maximum. This is especially the case for a speed of 2200 rpm. In the case of parameters related to heat release characteristics, the relationship is the opposite, and feeding the engine with esters compared to diesel fuel results in higher maximum amounts and rates of heat release. These values are higher for esters from 20 to 40%. In addition, the percentage burnout of the fuel dose confirmed the information found in other publications that feeding the engine with biofuels causes faster combustion compared to diesel.
Clean Energy and Carbon Emissions in Mexico’s Electric Power Sector: Past Performance and Current Trend
Authors: Probst Oliver
Published: November 2024

The concept of clean energy was introduced by the Mexican authorities as part of the wholesale electricity market with the objectives of both measuring the progress in decarbonization and fostering emission-free and low-emission technologies. In the present work, the evolution of clean energy production for the period 2017–2023, corresponding to seven full years of operation of the electricity market, was analyzed and compared to official targets. Emission of greenhouse gases (GHGs) was calculated from fuel consumption statistics. The consistency between electricity generation and fuel consumption data has been assessed. The projected short-term evolution of electricity generation and GHG emissions through 2026, locked in by decisions in the recent past, was modeled and discussed. A reduction in carbon intensity from 0.56 gCO2,eq to 0.46 g CO2,eq was found for the 2017–2022 period, in qualitative agreement with official figures, mainly due to the large-scale introduction of wind and solar, as well as some displacement of coal- and fuel oil-fired generation. Total GHG emissions reached a minimum of about 150 Gt CO2,eq/a in 2020–2021; emissions are projected to rise to 190 Gt CO2,eq in 2026, due to a strong rise in natural gas-fired generation from combined-cycle plants and the largely stalled development of wind and solar plants. Clean energy figures were found to decouple from emissions and can therefore not be considered a good proxy for decarbonization. A recent roadmap presented by the incoming federal government does, however, indicate a change in policies which might bring Mexico back on track towards the decarbonization of the electric power sector.
Recent Advances in Wastewater Electrocoagulation Technologies: Beyond Chemical Coagulation
Authors: Jo Sangyeol , Kadam Rahul , Jang Heewon , Seo Dongyun , Park Jungyu
Published: November 2024

This review provides a comprehensive analysis of the recent research trends and application cases of chemical coagulation (CC) and electrocoagulation (EC), which play a crucial role in wastewater treatment. In particular, the principles and process performances of the EC technologies are comparably reviewed with traditional CC technologies. EC offers the advantage of reducing the use of chemical agents and minimizing sludge generation compared to CC. Moreover, recent research cases have demonstrated its effectiveness in removing pollutants from wastewater. With increasing water consumption due to industrial development, the application of coagulation processes in wastewater and sludge treatment is expected to expand to minimize environmental impact. This review provides insights into the current status and future development direction of CC and EC technologies and can serve as foundational information for more efficient and environmentally friendly coagulation systems.
CXCL10, SCGN, and H2BC5 as Potential Key Genes Regulated by HCV Infection
Authors: Yıldırım Çiğdem , Yay Fatih , İmre Ayfer , Soysal Orçun , Yıldırım Hasan Çağrı
Published: November 2024

Introduction: Hepatitis C infections are the main causes of fatal clinical conditions such as cirrhosis and HCC development, and biomarkers are needed to predict the development of these complications. Therefore, it is important to first determine which genes are deregulated in HCV-cells compared to healthy individuals. In our study, we aimed to identify the genes that are commonly upregulated or downregulated in HCV-infected cells using two different databases. Material and Method: In this study, differentially expressed genes (DEGs) that were commonly upregulated or downregulated were identified using publicly available databases GSE66842 and GSE84587. Afterwards, the interactions of DEG products with each other and other proteins were examined using the STRING database. Enrichment analyses of DEGs were performed using the Enrichr-KG web tool including the Gene Ontology Biological Process, KEGG, Jensen_DISEASES and DisGeNET libraries. miRNAs targeting DEGs were detected using miRDB and TargetScanHuman8.0. Results: In HCV-infected cells, the CXCL10 expression is increased in both databases, while the SCGN and H2BC5 (HIST1H2BD) expression is decreased. No direct interaction was found among CXCL10, SCGN, H2BC5 in the top ten proteins. CXCL10 is a member of Hepatitis C and viral protein interactions with cytokine and cytokine receptor KEGG pathways. H2BC5 is a member of viral carcinogenesis KEGG pathways. Predicted overlapping miRNAs targeted by common DEGs were as follows: 59 were where CXCL10 was the estimated target, 22 where SCGN was the estimated target and 29 where H2BC5 (HIST1H2BD) was the estimated target. Conclusions: Our study identified genes that were upregulated or downregulated in HCV-infected cells in both databases and miRNAs associated with these genes, using two different databases. This study creates groundwork for future studies to investigate whether these genes can predict HCV prognosis and HCV-associated HCC development.
In Vitro and Computational Response of Differential Catalysis by Phlebia brevispora BAFC 633 Laccase in Interaction with 2,4-D and Chlorpyrifos
Authors: Ayala Schimpf Alan Rolando , Ortellado Laura Ester , Gamarra Marcelo Daniel , Fonseca María Isabel , Zapata Pedro Darío
Published: November 2024

Enzymes secreted by white rot fungi (WRF), such as laccase, offer a promising approach for the treatment of hazardous xenobiotic compounds. This study conducted a comprehensive analysis of the impact of the pesticides 2,4-dichlorophenoxyacetic acid (2,4-D) and chlorpyrifos on the laccase of Phlebia brevispora BAFC 633 through in vitro and bioinformatics analyses. The fungal strain was shown to be tolerant to both pesticides, with notable morphological and ultrastructural alterations in the mycelium. Laccase activity and two isoenzymes (53 and 70 kDa) were detected in all initial treatments. The laccase was concentrated for subsequent catalytic evaluation in the presence of both pesticides, showing high stability at a pH of 3.6 and a temperature range of 50–60 °C. The lacI gene, corresponding to this laccase, was modeled, and its structure revealed a defined catalytic pocket validated with a drug score of 0.61. Molecular docking estimated affinity energies of −5.06 and −9.41 Kcal mol−1 for 2,4-D and chlorpyrifos, respectively. Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) analysis through 250 ns of molecular dynamics revealed stronger hydrophobic interactions of laccase with chlorpyrifos and highlighted the importance of residue His460 in stabilizing both complexes. Understanding the impact of these agrochemicals on the catalytic function of laccase is crucial for developing future biotechnological strategies involving this enzyme.
Modeling Clustered DNA Damage by Ionizing Radiation Using Multinomial Damage Probabilities and Energy Imparted Spectra
Authors: Cucinotta Francis A.
Published: November 2024

Simple and complex clustered DNA damage represent the critical initial damage caused by radiation. In this paper, a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: (A) direct damage of sugar-phosphate moieties leading to SSB, (B) OH− radical formation with subsequent SSB and BD formation, (C) direct damage to DNA bases, and (D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for the relative location of SSB using a ≤10 bp criteria for a double-strand break (DSB) and for the possible success of a radical attack that leads to SSB or BD. Model predictions for electrons, 4He, and 12C ions are compared to the experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.
New Insights into Kidney Diseases
Authors: Katayama Kan , Dohi Kaoru
Published: November 2024

Chronic kidney disease (CKD) is a lifestyle-related disease affecting about 9% of the global population as of 2017 [...]
Heterogeneous Group of Genetically Determined Auditory Neuropathy Spectrum Disorders
Authors: Buianova Anastasiia A. , Bazanova Marina V. , Belova Vera A. , Ilyina Galit A. , Samitova Alina F. , Shmitko Anna O. , Balakina Anna V. , Pavlova Anna S. , Suchalko Oleg N. , Korostin Dmitriy O. , Machalov Anton S. , Daikhes Nikolai A. , Rebrikov Denis V.
Published: November 2024

Auditory neuropathy spectrum disorder (ANSD) is often missed by standard hearing tests, accounting for up to 10% of hearing impairments (HI) and commonly linked to variants in 23 genes. We assessed 122 children with HI, including 102 with sensorineural hearing loss (SNHL) and 20 with ANSD. SNHL patients were genotyped for common GJB2 variants using qPCR, while ANSD patients underwent whole exome sequencing, with variants analyzed across 249 genes. Homozygous GJB2 variants were found in 54.9% of SNHL patients. In 60% of ANSD patients, variants were detected in OTOF (25%), CDH23, TMC1, COL11A1, PRPS1, TWNK, and HOMER2 genes, including eight novel variants. Transient evoked otoacoustic emissions testing revealed differences at 4000 Hz (p = 0.0084) between the ANSD and SNHL groups. The auditory steady-state response (ASSR) test showed significant differences at 500 Hz (p = 2.69 × 10−4) and 1000 Hz (p = 0.0255) compared to pure-tone audiometry (PTA) in ANSD patients. Our questionnaire shows that the parents of children with SNHL often report an improved quality of life with hearing aids or cochlear implants, while parents of children with ANSD frequently experience uncertainty about outcomes (p = 0.0026), leading to lower satisfaction.
DRB1, DRB2 and DRB4 Are Required for an Appropriate miRNA-Mediated Molecular Response to Osmotic Stress in Arabidopsis thaliana
Authors: Pegler Joseph L. , Oultram Jackson M. J. , Grof Christopher P. L. , Eamens Andrew L.
Published: November 2024

Arabidopsis thaliana (Arabidopsis) double-stranded RNA binding (DRB) proteins DRB1, DRB2 and DRB4 perform essential roles in microRNA (miRNA) production, with many of the produced miRNAs mediating aspects of the molecular response of Arabidopsis to abiotic stress. Exposure of the drb1, drb2 and drb4 mutants to mannitol stress showed drb2 to be the most sensitive to this form of osmotic stress. Profiling of the miRNA landscapes of mannitol-stressed drb1, drb2 and drb4 seedlings via small RNA sequencing, and comparison of these to the profile of mannitol-stressed wild-type Arabidopsis plants, revealed that the ability of the drb1 and drb2 mutants to mount an appropriate miRNA-mediated molecular response to mannitol stress was defective. RT-qPCR was next used to further characterize seven miRNA/target gene expression modules, with this analysis identifying DRB1 as the primary DRB protein required for miR160, miR164, miR167 and miR396 production. In addition, via its antagonism of DRB1 function, DRB2 was shown by RT-qPCR to play a secondary role in regulating the production of these four miRNAs. This analysis further showed that DRB1, DRB2 and DRB4 are all required to regulate the production of miR399 and miR408, and that DRB4 is the primary DRB protein required to produce the non-conserved miRNA, miR858. Finally, RT-qPCR was used to reveal that each of the seven characterized miRNA/target gene expression modules responded differently to mannitol-induced osmotic stress in each of the four assessed Arabidopsis lines. In summary, this research has identified mannitol-stress-responsive miRNA/target gene expression modules that can be molecularly manipulated in the future to generate novel Arabidopsis lines with increased tolerance to this form of osmotic stress.
Brain Amyloid-β Peptide Is Associated with Pain Intensity and Cognitive Dysfunction in Osteoarthritic Patients
Authors: Wen Chun-Hsien , Kang Hong-Yo , Chan Julie Y.H.
Published: November 2024

Considerable studies have demonstrated that osteoarthritis (OA) is a risk factor for dementia. The precise mechanisms underlying the association between OA and increased risk for cognitive dysfunction, however, remain unclear. This study aimed at exploring the associations between pro-inflammatory cytokines/chemokines, biomarkers of Alzheimer’s disease (AD), pain intensity, and cognitive decline in knee joint OA patients. A total of 50 patients (26 in OA group and 24 in non-OA control group) were enrolled in this prospective, observational study. The visual analogue scale (VAS) score for pain intensity and Cognitive Abilities Screening Instrument (CASI) score for cognitive functions were examined in both groups. The plasma and cerebrospinal fluid (CSF) levels of pro-inflammatory molecules (IL-1β, IL-6, TNF-α, fractalkine, BDNF, MCP-1, and TGF-β), as well as biomarkers of AD (Aβ40, Aβ42, total-tau, and phospho-tau), were measured by multiplex immunoassay. Correlations among plasma or CSF biomarkers and questionnaire scores were assessed using Pearson’s correlation coefficient and simple linear regressions. There were more patients in the OA group whose CASI cutoff percentiles were <P5 or at P5 than in the control group. VAS pain scores were negatively correlated with cognitive domains, including total score, short term memory, attention, mental manipulation, abstract thinking, and judgment, of the CASI score. VAS scores were positively correlated with fractalkine, Aβ40, and Aβ42 in CSF of OA patients. The CSF levels of Aβ40 and Aβ42 in OA patients were negatively correlated with attention and abstract scores in CASI. The findings of this study suggest that knee OA is associated with poor cognitive performance, and this association is particularly pronounced in OA patients with chronic pain. Higher levels of brain AD biomarkers, such as Aβ40 and Aβ42, may partially mediate this relationship.
Improved RT-DETR for Infrared Ship Detection Based on Multi-Attention and Feature Fusion
Authors: Liu Chun , Zhang Yuanliang , Shen Jingfu , Liu Feiyue
Published: November 2024

Infrared cameras form images by capturing the thermal radiation emitted by objects in the infrared spectrum, making them complex sensors widely used in maritime surveillance. However, the broad spectral range of the infrared band makes it susceptible to environmental interference, which can reduce the contrast between the target and the background. As a result, detecting infrared targets in complex marine environments remains challenging. This paper presents a novel and enhanced detection model developed from the real-time detection transformer (RT-DETR), which is designated as MAFF-DETR. The model incorporates a novel backbone by integrating CSP and parallelized patch-aware attention to enhance sensitivity to infrared imagery. Additionally, a channel attention module is employed during feature selection, leveraging high-level features to filter low-level information and enabling efficient multi-level fusion. The model’s target detection performance on resource-constrained devices is further enhanced by incorporating advanced techniques such as group convolution and ShuffleNetV2. The experimental results show that, although the enhanced RT-DETR algorithm still experiences missed detections under severe object occlusion, it has significantly improved overall performance, including a 1.7% increase in mAP, a reduction in 4.3 M parameters, and a 5.8 GFLOPs decrease in computational complexity. It can be widely applied to tasks such as coastline monitoring and maritime search and rescue.
Capitalising on the Floristic Survey as a Non-Destructive Line of Evidence for Mineral Potential Modelling: A Case Study of Bauxite in South-Western Australia
Authors: Trotter Lewis , Wardell-Johnson Grant , Grigg Andrew , Luxton Sarah , Robinson Todd P.
Published: November 2024

While geobotanists have long used plant occurrence to locate subsurface resources, none have utilised floristic surveys as evidence in models of mineral potential. Here, we combine plant species distributions with terrain metrics to produce predictive models showing the probability of bauxite presence. We identified nineteen taxa with statistically significant associations with known bauxite deposits and identified eleven terrain metrics from previous studies. We grouped variables into three variable sets (floristic, topographic, and topo-flora) and produced mineral potential models for each using four algorithms or approaches: (a) a generalised linear model (GLM); (b) random forest (RF); (c) maxent (ME); and (d) a heterogenous stacking ensemble (GLM-RF-ME). Overall, the random forest model outperformed all algorithms including the ensemble based on the area under the curve (AUC) metric. The floristic set of variables outperformed the topographic set (AUC: 0.86 v 0.82). However, together they had the greatest predictive capacity (AUC: 0.89). Six taxa, including Banksia grandis, Leucopogon verticillatus, and Persoonia longifolia, were indicators of bauxite presence, while five other taxa, including Xanthorrhoea preissii and Hypocalymma angustifolium, were associated with bauxite absence. Important topographic variables were topographic wetness, landscape position, and valley depth, which characterised bauxite locations as being well drained, in the upper slope positions of subdued hills, and at some distance from valleys. The addition of floristic surveys provides a new line of evidence about the overlying botanical life that tolerates, accumulates, or avoids bauxite or associated minerals. As opposed to drilling, both datasets can be collected and interrogated at low cost and without impact to the surrounding environment. These data are valuable additions to future applications of mineral potential modelling.
Strong Convergence of Truncated EM Method for Stochastic Volterra Integral Differential Equations with Hölder Diffusion Coefficients
Authors: Feng Juanting , Zhang Qimin
Published: November 2024

The strong convergence of numerical solutions is studied in this paper for stochastic Volterra integral differential equations (SVIDEs) with a Hölder diffusion coefficient using the truncated Euler–Maruyama method. Firstly, the numerical solutions of SVIDEs are obtained based on the Euler–Maruyama method. Then, the pth moment boundedness and strong convergence of truncated the Euler–Maruyama numerical solutions are proven under the local Lipschitz condition and the Khasminskii-type condition. Finally, the convergence rate of the truncated Euler–Maruyama method of the numerical solutions is also discussed under some suitable assumptions.
Using the Theozyme Model to Study the Dynamical Mechanism of the Post-Transition State Bifurcation Reaction by NgnD Enzyme
Authors: Hou Yaning , Chen Jingyun , Liu Weizhe , Zhu Gaohua , Yang Qianying , Wang Xin
Published: November 2024

Post-transition state bifurcation (PTSB) is a fundamental process in which a single transition state leads to multiple products. This phenomenon is important in both biological and chemical contexts and offers valuable insights into reaction mechanisms and their applications. The theozyme model, which focuses on key residues within enzymes, offers a computationally efficient method for studying these processes while preserving the enzyme’s catalytic properties. This approach enhances our understanding of how enzymes stabilize and direct the transition state, thereby influencing product distribution and selectivity. In this study, we investigate the dynamics and regulatory mechanisms of the PTSB reaction catalyzed by the enzyme NgnD. The enzyme NgnD facilitates a cycloaddition reaction that produces both [6 + 4] and [4 + 2] adducts, with a preference for the [6 + 4] adduct. By analyzing the potential energy surface, bond length distribution, and interactions between the theozyme and the ambimodal transition state, we elucidate the role of the enzyme’s active site residues in determining product selectivity. We illustrate how these key residues contribute to the formation of different adducts, providing insights from various perspectives. Using theozyme models, we propose how the four most influential active residues collectively might control the direction of adduct formation through their cumulative effects.
Compline in Melkite Alexandria, Contained in MS Sinai Arabic 232 (13th c.)
Authors: Wade Andrew
Published: November 2024

This article is the latest in a series examining the offices in the Horologion of Sinai Arabic 232 (13th century). This Book of Hours has its origin in Melkite Alexandria and has never been studied before, nor indeed have the Arabic Books of Hours, in general. The article presents an English translation of the Office of Compline from this manuscript (apart from the psalms, which are simply indicated), with comments and identification of the individual texts. Features of particular interest are the extra saints in the intercessions, different psalms and prayers from the modern rite, and the series of common troparia at the end. The additional saints in the intercessions pose a conundrum: whereas the analysis of Matins, the Hours, and Vespers has suggested that this is an Arabic Melkite Horologion from Alexandria that must have been received from Jerusalem c. the 7th century and then underwent both Alexandrian (Coptic) influences and later Byzantinisation which did not entirely eliminate more archaic elements from Jerusalem such as the tri-ode system at Matins, the choice of additional saints suggests a double provenance from both Alexandria and Sinai. We therefore suggest that the Horologion was brought from Alexandria and underwent some degree of adaptation on Sinai without eliminating all the specifically Alexandrian features.
A General Super-Resolution Approach Integrating Physical Information for Temperature Field Measurement
Authors: Chen Sheng , Su Zhixuan , Dai Min , Xue Chenyang , Tao Jiping , Hai Zhenyin
Published: November 2024

In industrial measurement, temperature field measurement typically relies on thermocouples and spectroscopic techniques. These traditional methods often suffer from insufficient precision, resulting in prevalent low-resolution measurements in real thermal scenarios. To address this challenge, we propose a novel general super-resolution approach for temperature field measurement in various thermal scenarios, leveraging the low-resolution (LR) data obtained from sensor array technology. The method incorporates skip connections and multi-path learning, along with physical information loss, to enhance accuracy. To validate the effectiveness of the approach, simulations across three two-dimensional thermal scenarios are conducted: the heating process in silicon chips, the thermodynamic process of hot and cold water mixing, and the convective heat transfer phenomena involved in metal sheet dissipation under airflow. The results show that the learning model can accurately predict the HR temperature. The proposed approach offers a pathway for generating HR solutions, bypassing traditional time-consuming simulation processes while ensuring data accuracy. By utilizing a fixed model and a lightweight physical loss function, we simplify the deployment process, facilitating applications in computational fluid dynamics (CFD) solutions, engineering measurements, and related fields.
Advances in Data Pre-Processing Methods for Distributed Fiber Optic Strain Sensing
Authors: Richter Bertram , Ulbrich Lisa , Herbers Max , Marx Steffen
Published: November 2024

Because of their high spatial resolution over extended lengths, distributed fiber optic sensors (DFOS) enable us to monitor a wide range of structural effects and offer great potential for diverse structural health monitoring (SHM) applications. However, even under controlled conditions, the useful signal in distributed strain sensing (DSS) data can be concealed by different types of measurement principle-related disturbances: strain reading anomalies (SRAs), dropouts, and noise. These disturbances can render the extraction of information for SHM difficult or even impossible. Hence, cleaning the raw measurement data in a pre-processing stage is key for successful subsequent data evaluation and damage detection on engineering structures. To improve the capabilities of pre-processing procedures tailored to DSS data, characteristics and common remediation approaches for SRAs, dropouts, and noise are discussed. Four advanced pre-processing algorithms (geometric threshold method (GTM), outlier-specific correction procedure (OSCP), sliding modified z-score (SMZS), and the cluster filter) are presented. An artificial but realistic benchmark data set simulating different measurement scenarios is used to discuss the features of these algorithms. A flexible and modular pre-processing workflow is implemented and made available with the algorithms. Dedicated algorithms should be used to detect and remove SRAs. GTM, OSCP, and SMZS show promising results, and the sliding average is inappropriate for this purpose. The preservation of crack-induced strain peaks’ tips is imperative for reliable crack monitoring.
Study on the Optimization of b-Value for Analyzing Weld Defects in the Primary System
Authors: Jung Do-Yun , Choi Young-Chul , Chung Byun-Young
Published: November 2024

This study presents a method to add a crack analysis algorithm to the Acoustic Leak Monitoring System (ALMS) to detect and evaluate the crack growth process in the primary system piping of nuclear power plants. To achieve this, a fracture test was conducted by applying stepwise loading to welded specimens that simulate the cold leg section, and acoustic emission (AE) signals were measured in relation to the increase in strain using an AE testing system. The experimental results indicated that the stability and instability of cracks could be assessed through the Kaiser effect and the Felicity effect when detecting crack growth using AE signals. Additionally, by utilizing both root mean square (RMS) and amplitude parameters simultaneously to calculate the b-value, it was confirmed that the RMS-based b-value minimizes the effects of AE signal attenuation and allows for a more stable assessment of crack progression. This demonstrates that the RMS, which reflects signal energy, is effective for real-time monitoring of the crack growth state. Finally, the results of this study suggest the potential for real-time crack monitoring using AE data in piping systems of critical structures, such as nuclear power plants; by adding a simple AE analysis method to the ALMS system, a practical approach has been derived that enhances the safety of the structure and allows for quantitative assessment of crack progression. Future research is expected to further refine the AE parameters and algorithms, leading to the advancement of safety monitoring systems in various industrial settings.
Monitoring Biochemical Changes of Neuroblastoma Cells in Early Stages After X-Ray Exposure by Using Fourier-Transform Infrared Spectroscopy
Authors: Esposito Rosario , Portaccio Marianna , Meschini Roberta , Delfino Ines , Lepore Maria
Published: November 2024

X-ray radiation treatments are largely adopted in radiotherapy, and Fourier-transform infrared microspectroscopy (μ-FTIR) has already been demonstrated to be a useful instrument for monitoring radiotherapy effects. Previous works in this field have focused on studying the changes occurring in cells when they are fixed immediately after the irradiation or 24 and 48 h later. In the present paper, changes occurring in SH-SY5Y neuroblastoma cells in the first hours after the irradiation are examined to obtain information on the processes taking place in this not-yet-investigated time window by using μ-FTIR. For this purpose, cell samples were fixed immediately after X-ray exposure, and 2 and 4 h after irradiation and investigated along with unexposed cells. Different data analysis procedures were implemented to estimate the changes in lipid, protein, and DNA spectral contributions. The present investigation on the effects of X-ray in the first hours after the exposure is helpful for better describing the processes occurring in this time window that offer the possibility of a timely check on the efficacy of X-ray treatments and can potentially be applied for planning personalized treatment as required by the most advanced medical therapy.
A Tensor Space for Multi-View and Multitask Learning Based on Einstein and Hadamard Products: A Case Study on Vehicle Traffic Surveillance Systems
Authors: Hermosillo-Reynoso Fernando , Torres-Roman Deni
Published: November 2024

Since multi-view learning leverages complementary information from multiple feature sets to improve model performance, a tensor-based data fusion layer for neural networks, called Multi-View Data Tensor Fusion (MV-DTF), is used. It fuses M feature spaces X1,⋯,XM, referred to as views, in a new latent tensor space, S, of order P and dimension J1×⋯×JP, defined in the space of affine mappings composed of a multilinear map T:X1×⋯×XM→S—represented as the Einstein product between a (P+M)-order tensor A anda rank-one tensor, X=x(1)⊗⋯⊗x(M), where x(m)∈Xm is the m-th view—and a translation. Unfortunately, as the number of views increases, the number of parameters that determine the MV-DTF layer grows exponentially, and consequently, so does its computational complexity. To address this issue, we enforce low-rank constraints on certain subtensors of tensor A using canonical polyadic decomposition, from which M other tensors U(1),⋯,U(M), called here Hadamard factor tensors, are obtained. We found that the Einstein product A⊛MX can be approximated using a sum of R Hadamard products of M Einstein products encoded as U(m)⊛1x(m), where R is related to the decomposition rank of subtensors of A. For this relationship, the lower the rank values, the more computationally efficient the approximation. To the best of our knowledge, this relationship has not previously been reported in the literature. As a case study, we present a multitask model of vehicle traffic surveillance for occlusion detection and vehicle-size classification tasks, with a low-rank MV-DTF layer, achieving up to 92.81% and 95.10% in the normalized weighted Matthews correlation coefficient metric in individual tasks, representing a significant 6% and 7% improvement compared to the single-task single-view models.
THz Polarimetric Imaging of Carbon Fiber-Reinforced Composites Using the Portable Handled Spectral Reflection (PHASR) Scanner
Authors: Xu Kuangyi , Harris Zachery B. , Vahey Paul , Arbab M. Hassan
Published: November 2024

Recent advancements in novel fiber-coupled and portable terahertz (THz) spectroscopic imaging technology have accelerated applications in nondestructive testing (NDT). Although the polarization information of THz waves can play a critical role in material characterization, there are few demonstrations of polarization-resolved THz imaging as an NDT modality due to the deficiency of such polarimetric imaging devices. In this paper, we have inspected industrial carbon fiber composites using a portable and handheld imaging scanner in which the THz polarizations of two orthogonal channels are simultaneously captured by two photoconductive antennas. We observed significant polarimetric differences between the two-channel images of the same sample and the resulting THz Stokes vectors, which are attributed to the anisotropic conductivity of carbon fiber composites. Using both polarimetric channels, we can visualize the superficial and underlying interfaces of the first laminate. These results pave the way for the future applications of THz polarimetry to the assessment of coatings or surface quality on carbon fiber-reinforced substrates.
Bubble Behavior and Surface Liquid Film Characteristics of Air Bubbles Crossing the Oil–Water Interface
Authors: Li Yixin , Jiang Bin , Xiao Xiaoming , Yang Na , Sun Yongli , Zhang Luhong
Published: November 2024

The interaction of bubbles with phase interfaces is an important phenomenon in science and industry. In this paper, the variation in bubble behavior and the characteristics of surface liquid film formation and shedding at the oil–water interface are investigated using bubble visualization high-speed photography and numerical simulation. The results show that the bubble rise trajectories can be divided into three different sets when the bubbles rise in a system composed of two mutually incompatible liquids, and the bubble shapes are more stable in white oil compared to water. During the passage of the bubble across the oil–water interface, the water phase is entrained to form a liquid film covering the bubble. We found that the change in the bubble liquid film and the collapse process of the water column are closely related to the bubble size. The trends of Eotvos (Eo) numbers for bubbles of different diameters in the oil–water coexistence system are approximately the same, with the Eo numbers of larger bubbles being much larger than those corresponding to smaller bubbles, from the beginning to the end. After crossing the oil–water interface, the Eo number of larger-diameter bubbles keeps fluctuating over a long distance before finally stabilizing. The Eo number of small-diameter bubbles remains essentially stable after crossing the oil–water interface.