bluuebunny/crossref_metadata_2025 huggingface dataset:
Local connections among excitatory neurons underlie characteristics of enriched environment exposure-induced neuronal response modulation in layers 2/3 of the mouse V1
Authors: Wagatsuma Nobuhiko , Terada Yuka , Okuno Hiroyuki , Ageta-Ishihara Natsumi
Published: February 2025

Environmental enrichment, an enhancement in the breeding environment of laboratory animals, enhance development of the cortical circuit and suppresses brain dysfunction. We quantitatively investigated the influences of enriched environment (EE) exposure, on responses in layers 2/3 (L2/3) of the primary visual area (V1) of mice. EE modifies visual cortex plasticity by inducing immediate early genes. To detect this, we performed immunostaining for the immediate early gene product c-Fos. EE exposure significantly increased the number of neurons with high c-Fos fluorescence intensity compared with those of mice under standard housing (SH). In contrast, there was no significant difference in the number of neurons exhibiting low c-Fos intensity between the SH and EE exposure groups. To further investigate the mechanism of modulation by EE exposure, we developed a microcircuit model with a biologically plausible L2/3 of V1 that combined excitatory pyramidal (Pyr) neurons and three inhibitory interneuron subclasses. In the model, synaptic strengths between Pyr neurons were determined according to a log-normal distribution. Model simulations with various inputs mimicking physiological conditions for SH and EE exposure quantitatively reproduced the experimentally observed activity modulation induced by EE exposure. These results suggested that synaptic connections among Pyr neurons obeying a log-normal distribution underlie the characteristic EE-exposure-induced modulation of L2/3 in V1.
A prospective comparison of Scheimpflug-based anterior segment imaging systems in normal and abnormal corneas: Oculus Pentacam vs. Remidio Visionix VX650
Authors: Kumar Sonam , Negiloni Kalpa , Gupta Parul Chawla , K Ranjitha , N Neha , Parthasarathy Rao Divya , Damani Jyothi , Thakur Ritika , Ballae Ganesh Rao Shonraj , Duggal Mona
Published: February 2025

Purpose

Advancements in anterior segment imaging have significantly improved the precision of corneal diagnostics, aiding ocular conditions management. The study evaluated the agreement between two Scheimpflug devices—Pentacam and Remidio Visionix 650 (VX650)—in assessing corneal and anterior chamber parameters in patients with and without corneal abnormalities.

Materials and methods

This prospective study at a tertiary eye care hospital measured pachymetry values (central corneal thickness, thinnest point), front corneal surface parameters (keratometry, curvature, astigmatism), back corneal surface parameters (elevation, curvature) and anterior chamber parameters (depth, volume, angle). Bland-Altman analysis assessed agreement between the devices, and the Intraclass Correlation Coefficient (ICC) evaluated VX650’s repeatability.

Results

Of the 202 patients (mean age was 25 ± 4.33 years), 141 eyes were classified as normal and 61 as abnormal (41 keratoconus, 17 post-LASIK, 3 post-ICL). Bland-Altman analysis showed good agreement between Pentacam and VX650 for anterior segment parameters. The VX650 measured marginally thicker corneal thickness (mean difference of central corneal thickness (CCT) of -4.0 ± 6.3 µm). Statistically significant differences in apical corneal thickness were noted for post-refractive surgery patients. K1 and K2 values showed significant variations in keratoconus but were not clinically significant. Anterior chamber depth was similar between devices, though volume differences were observed post-surgery. ICC indicated good to excellent repeatability (above 0.75) for most parameters.

Conclusion

Remidio Visionix VX650 showed good agreement with Pentacam for key anterior segment measurements, confirming its reliability for corneal diagnostics. Additionally, its multifunctional capabilities offer potential for streamlining workflows, especially in clinics seeking efficient, comprehensive eye assessments.
Integration of multi-omics profiling reveals an epigenetic-based molecular classification of lung adenocarcinoma: implications for drug sensitivity and immunotherapy response prediction
Authors: Wang Ning , Li Yinan , Wang Yaoyao , Wang Wenting
Published: February 2025

Background

Lung adenocarcinoma (LUAD) remains a major cause of cancer-related mortality worldwide, with high heterogeneity and poor prognosis. Epigenetic dysregulation plays a crucial role in LUAD progression, yet its potential in molecular classification and therapeutic prediction remains largely unexplored.

Methods

We performed an integrated multi-omics analysis of 432 LUAD patients from TCGA and 398 patients from GEO datasets. Using consensus clustering and random survival forest (RSF) algorithms, we established an epigenetic-based molecular classification system and constructed a prognostic model. The model’s performance was validated in multiple independent cohorts, and its biological implications were investigated through comprehensive functional analyses.

Results

We identified two distinct molecular subtypes (CS1 and CS2) with significant differences in epigenetic modification patterns, immune microenvironment, and clinical outcomes (P = 0.005). The RSF-based prognostic model demonstrated robust performance in both training (TCGA-LUAD) and validation (GSE72094) cohorts, with time-dependent AUC values ranging from 0.625 to 0.694. Low-risk patients exhibited enhanced immune cell infiltration, particularly CD8+ T cells and M1 macrophages, and showed better responses to immune checkpoint inhibitors. Drug sensitivity analysis revealed subtype-specific therapeutic vulnerabilities, with low-risk patients showing higher sensitivity to conventional chemotherapy and targeted therapy.

Conclusion

Our study establishes a novel epigenetic-based classification system and predictive model for LUAD, providing valuable insights into patient stratification and personalized treatment selection. The model’s ability to predict immunotherapy response and drug sensitivity offers practical guidance for clinical decision-making, potentially improving patient outcomes through precision medicine approaches.
Harnessing machine learning and AI-driven analytics to identify novel drug targets and predict chemotherapy efficacy in NSCLC
Authors: Qin Shaojia , Deng Biyu , Mo Dan , Zhang Zhengyou , Wei Xuan , Ling Zhougui
Published: February 2025

Introduction

Non-small cell lung cancer (NSCLC) constitutes the majority of lung cancer cases and exhibits marked heterogeneity in both clinical presentation and molecular profiles, leading to variable responses to chemotherapy. Emerging evidence suggests that mitochondria-derived RNAs (mtRNAs) may serve as novel biomarkers, although their role in predicting chemotherapy outcomes remains to be fully explored.

Methods

In this study, peripheral blood mononuclear cells were obtained from NSCLC patients for analysis of the mtRNA ratio (mt_tRNA-Tyr-GTA_5_end to mt_tRNA-Phe-GAA), while thoracic CT images were processed to derive an AI-driven BiomedGPT variable. Although individual clinical factors (Sex, Age, History_of_smoking, Pathological_type, Stage) offered limited predictive power when used in isolation, their integration into a random forest model improved sensitivity in the training set, albeit with reduced generalizability in the validation cohort. The subsequent integration of the BiomedGPT score and mtRNA ratio significantly enhanced predictive performance across both training and validation datasets.

Results

An all-inclusive model combining clinical data, AI-derived variables, and mtRNA biomarkers produced a risk score capable of discriminating patients into high- and low-risk groups for progression-free survival and overall survival, with statistically significant differences observed between these groups.

Discussion

These findings highlight the potential of integrating mtRNA biomarkers with advanced AI methods to refine therapeutic decision-making in NSCLC, underscoring the importance of combining diverse data sources in precision oncology.
Who is serving whom? Exploring the mechanisms linking technology dependence to work engagement
Authors: Žiedelis Arūnas , Urbanavičiūtė Ieva , Lazauskaitė-Zabielskė Jurgita , Jakštienė Rita
Published: February 2025

As technological advances increasingly shape the world of work, it is becoming clear that the impact of increased employee dependence on technology for task completion may have ambivalent effects. While successfully mastered technological tools make the work more engaging by enabling a simpler and more efficient implementation of tasks, the necessity to keep up with technological progress imposes additional demands to adopt innovations and limits the freedom of choice about how work is performed. With this study, we sought to unravel whether the effect of technology dependence at work on employee autonomy satisfaction and subsequent work engagement is conditional and depends on increased learning demands. A heterogeneous sample of 753 employees participated in the survey. We used conditional process analysis to test our hypotheses. Results revealed that it is not dependence on technology itself that is relevant for autonomy and work engagement, but rather its combination with intensified learning demands. For employees who reported fewer learning pressures, technology dependence was an enabling (i.e., facilitating autonomy satisfaction) factor, associated with higher work engagement. Conversely, for those who experienced greater learning demands, technology dependence was associated with lower autonomy satisfaction and lower work engagement.
Are individual differences in personality associated with COVID-19 infection? Examining the role of normative, maladaptive, and dark personality traits using structural equation modeling
Authors: Pourdehghan Parandis , Pincus Aaron L. , Mohammadi Mohammad Reza
Published: February 2025

Objective

During the COVID-19 pandemic, people’s behaviors have been considered an important factor in the spread of coronavirus. This situation led us to examine the role of personality in human behavior and its outcomes during the pandemic. This study examined the effect of normative, maladaptive, and dark personality traits on the probability of COVID-19 infection as mediated by psychological and behavioral responses to the pandemic.

Methods

The data was collected from 740 Iranians (mean age = 33.34) completing Big Five-10, Personality Inventory for DSM-5-Brief Form (PID-5-BF)-Adult, Short Dark Triad (SD3), Depression, Anxiety and Stress Scale - 21 Items (DASS-21), and Protective Behaviors inventories. We used structural equation modeling to fit a model from the personality traits to COVID-19 infection through mediating effects of psychological and behavioral responses using cross-sectional data.

Results

All path models examined fit the data well. The normative traits openness, conscientiousness, neuroticism, introversion, and disagreeableness were positively related to social distancing. The pathological traits antagonism, detachment, negative affectivity, disinhibition, and psychoticism, and dark traits psychopathy, narcissism, and Machiavellianism were negatively associated with social distancing. Finally, social distancing was negatively related to infection rates and fully mediated all personality links with infection (β = −0.17, p < 0.001).

Conclusion

The findings demonstrate that individual differences in personality predict behaviors crucial to pandemic mitigation. Social distancing can be, directly or indirectly, a significant underlying mechanism linking personality traits to the COVID-19 infection. Public health policymakers should consider personality-tailored interventions for maximizing preventive health behaviors and slowing the spread of infection. This knowledge also could contribute to more effective measures to prepare for public health emergencies in the future.
Social connections combat loneliness and promote wellbeing among college students coming out of the COVID-19 pandemic
Authors: Cipolletta Sabrina , Ronconi Lucia , Tomaino Silvia Caterina Maria
Published: February 2025

Introduction

The COVID-19 pandemic impacted young people's mental health but we still need to explore this impact in the long term. The aim of this study is to analyze college students' wellbeing and loneliness in relation to the impact of the COVID-19 pandemic, social support, and the frequency of activities carried out with others following the period of strictest restrictions.

Methods

A total of 291 college students enrolled in an Italian University filled in an online questionnaire including measures of anxiety, depression, life satisfaction, loneliness, perceived social support, and the impact of COVID-19 on their quality of life.

Results

The results showed that the greatest impact of the pandemic related to higher levels of loneliness, anxiety, depression and lower satisfaction with life. Conversely, greater social support and frequency of activities carried out with others were associated with lower levels of loneliness and depression, and higher satisfaction with life. Some differences related to gender and being a long-term international student.

Discussion

These results are important to inform interventions to support college students' wellbeing and foster social connections among them.
Racism in medical education and the entanglement of contents and (con-)texts: a participative reflection on teaching materials and the everyday experiences of racialized students and physicians in Germany
Authors: Vogt Hans , Piberger Patricia , Lazaridou Felicia Boma
Published: February 2025

Background

Institutional racism and racial disparities in healthcare have received greater focus in the public health sciences in recent decades. The role of medical education in this context has been researched in several studies, mostly in the US, but racism in medical education remains largely underresearched in Germany. The aim of this study is to show how racist knowledge and practices exist within German medical care and are systematically transmitted in German medical education, and how this may institutionally reproduce, legitimize, reinforce, and perpetuate disadvantages.

Methods

Based on consultations and preliminary interviews with civic stakeholders and experts, teaching and learning materials in German medical education were randomly sampled. These materials served as a starting point for participative reflection on racist knowledge and practices in German medical education. In the first step, the contents of teaching and learning materials were analyzed to identify terms, themes, or concepts that propagate racist ideas. Thereafter, we sought expert feedback on the analyzed content through one-on-one interviews and focus groups with physicians and medical students who self-identify as affected by racism.

Results

Our study reveals two main findings. First, racist knowledge and practices are systematically transmitted and reproduced at different levels of German medical education. Second, the entanglement of multiple institutional dimensions contributes significantly to the perpetuation and legitimization of racist knowledge and practices in German medical education.

Conclusion

In keeping with the state of research, the study was primarily exploratory in character and may serve as a starting point for future research on institutional racism in German healthcare and medical education. In addition to the findings that can be used to develop further research questions, initial recommendations for action by civil society, institutions, and policymakers may be derived from the interviews and focus group discussions.
The relationship between burnout, sense of coherence and job safety attitudes among nurses after coronavirus disease 2019 in China: a cross-sectional survey
Authors: Xue Fang , Liu Jing , Zhou Tong , Li Xiuchuan , Liu Chunfang , Li Xueer , Li Shuoshuo , Ye Ping , Zhang Jing
Published: February 2025

Objective

To investigate burnout, sense of coherence (SOC), and job safety attitudes among nurses in China after the coronavirus disease 2019 (COVID-19) pandemic.

Methods

This cross-sectional study included 302 front-line nurses from Fangcang shelter hospitals (FSHs) in China. Descriptive, univariate, Pearson’s correlation, and multiple linear regression analyses were conducted to analyze factors related to job safety attitudes of nurses toward FSHs.

Results

The incidence of burnout among nurses in FSHs was 65.2%; 57.9% had a low level of SOC, the score for safety attitude was 74.47 (standard deviation = 13.33), and the agreement rate was 51%. Burnout was negatively correlated with SOC (r = −0.399, p < 0.01) and safety attitudes (r = −0.141, p < 0.05), and SOC was positively correlated with safety attitudes (r = 0.428, p < 0.01). Personal accomplishment, depersonalization, changes in working hours, manageability, and marital status explained 33.8% of the variance in work safety attitudes.

Conclusion

This study investigated the levels of burnout, SOC, and safety attitudes among nurses after COVID-19 in Chinese FSHs for the first time, and analyzed the associated factors. The results are valuable for improving the quality of nursing safety as well as patient safety management in FSHs.
TOCA-IoT: Threshold Optimization and Causal Analysis for IoT Network Anomaly Detection Based on Explainable Random Forest
Authors: Gad Ibrahim
Published: February 2025

The Internet of Things (IoT) is developing quickly, which has led to the development of new opportunities in many different fields. As the number of IoT devices continues to expand, particularly in transportation and healthcare, the need for efficient and secure operations has become critical. In the next few years, IoT connections will continue to expand across different fields. In contrast, a number of problems require further attention to be addressed to provide safe and effective operations, such as security, interoperability, and standards. This research investigates the efficacy of integrating explainable artificial intelligence (XAI) techniques and causal inference methods to enhance network anomaly detection. This study proposes a robust TOCA-IoT framework that utilizes the linear non-Gaussian acyclic model (LiNGAM) to find causal relationships in network traffic data, thereby improving the accuracy and interpretability of anomaly detection. A refined threshold optimization strategy is employed to address the challenge of selecting optimal thresholds for anomaly classification. The performance of the TOCA-IoT model is evaluated on an IoT benchmark dataset known as CICIoT2023. The results highlight the potential of combining causal discovery with XAI for building more robust and transparent anomaly detection systems. The results showed that the TOCA-IoT framework achieved the highest accuracy of 100% and an F-score of 100% in classifying the IoT attacks.
From Waste to Value: Banana-Peel-Derived Adsorbents for Efficient Removal of Polar Compounds from Used Palm Oil
Authors: Channei Duangdao , Jannoey Panatda , Thammaacheep Punyanuch , Khanitchaidecha Wilawan , Nakaruk Auppatham
Published: February 2025

The banana chip industry generates significant quantities of waste, including banana peels and used palm oil, which present both environmental and economic challenges. This study explored converting banana peel waste into porous adsorbents via chemical and thermal activation using sulfuric acid (S-BP) and 5% w/v acetic acid (A-BP) as activating agents. Characterization using field emission scanning electron microscopy (FESEM) and Brunauer–Emmett–Teller (BET) analysis revealed notable morphological distinctions and enhanced porosity. The BET surface areas of S-BP and A-BP were 338.959 m2/g and 201.722 m2/g, respectively, significantly higher than that of calcined banana peel (C-BP) at 3.202 m2/g. Despite the higher surface area of S-BP, A-BP, prepared under milder acetic acid conditions, was further investigated for adsorption studies. A-BP effectively reduced the free fatty acids (FFAs) in used palm oil from 3.108% to 1.69% within 30 min. Adsorption isotherms favored the Freundlich model (R2 = 0.9115), indicating multilayer adsorption behavior. The adsorption energy derived from the Dubinin–Radushkevich (D–R) model was determined to be 2.61 J/mol, indicating that the adsorption process primarily occurs through physisorption. This study highlights a sustainable approach to waste management and resource recovery, promoting circular economy principles in the banana chip industry.
Advancements in Vibration Testing: Effects on Thermal Performance and Degradation of Modern Batteries
Authors: Sabeel Khursheed , Al-Greer Maher , Bashir Imran
Published: February 2025

Lithium-ion cells are increasingly being used as central power storage systems for modern applications, i.e., e-bikes, electric vehicles (EVs), satellites, and spacecraft, and they face significant and constant vibrations. This review examines how these vibrations affect the batteries’ mechanical, thermal, and electrical properties. Vibrations can cause structural issues, such as the separation of electrodes and the deformation of separators. These problems raise internal resistance and lead to localized heat generation. As a result, thermal management becomes more complicated, battery aging accelerates, and safety risks arise, including short circuits and thermal runaways. To tackle these challenges, we need more realistic testing protocols that consider the combined effects of vibrations, temperature, and mechanical stress. Improving thermal management systems (TMSs) using advanced cooling techniques and materials, e.g., phase change solutions, can help to alleviate these problems. It is also essential to design batteries with vibration-resistant materials and enhanced structural integrity to boost their durability. Moreover, vibrations play a significant role in various degradation mechanisms, including dendrite formation, self-discharge, and lithium plating, all of which can reduce battery capacity and lifespan. Our current research builds on these insights using a multiscale physics-based modeling approach to investigate how vibrations interact with thermal behavior and contribute to battery degradation. By combining computational models with experimental data, we aim to develop strategies and tools to enhance lithium-ion batteries’ safety, reliability, and longevity in challenging environments.
Development of Mathematical Model for Understanding Microcirculation in Diabetic Foot Ulcers Based on Ankle–Brachial Index
Authors: da Silva Ana Karoline Almeida , Nunes Gustavo Adolfo Marcelino de Almeida , Faria  Rafael Mendes , Fleury Rosa Mário Fabrício , Costa Lindemberg Barreto Mota da , de Faria Newton , da Rocha  Adson Ferreira , Tatmatsu-Rocha José Carlos , Fleury Rosa Suelia de Siqueira Rodrigues
Published: February 2025

This study proposes an innovative mathematical model for assessing microcirculation in patients with diabetic ulcers, using the ankle–brachial index (ABI). The methodology combines Bond Graph (BG) modeling and Particle Swarm Optimization (PSO), enabling a detailed analysis of hemodynamic patterns in a pilot sample of three patients. The results revealed a correlation between ulcer size and reduced ABI values, suggesting that deficits in microcirculation directly impact the severity of lesions. Furthermore, despite variations in ABI values and arterial pressures, all patients exhibited high capillary resistance, indicating difficulties in microcirculatory blood flow. The PSO-optimized parameters for the capillary equivalent circuit were found to be R1=89.784Ω, R2=426.55Ω, L=27.506H, and C=0.00040675F, which confirms the presence of high vascular resistance and reduced compliance in the microvascular system of patients with diabetic foot ulcers. This quantitative analysis, made possible through mathematical modeling, is crucial for detecting subtle changes in microcirculatory dynamics, which may not be easily identified through conventional pressure measurements alone. The increased capillary resistance observed may serve as a key indicator of vascular impairment, potentially guiding early intervention strategies and optimizing diabetic ulcer treatment. We acknowledge that the sample size of three patients represents a limitation of the study, but this number was intentionally chosen to allow for a detailed and controlled analysis of the variables involved. Although the findings are promising, additional experimental validations are necessary to confirm the clinical applicability of the model in a larger patient sample, thus solidifying its relevance in clinical practice.
Prenatal Hyperhomocysteinemia Leads to Synaptic Dysfunction and Structural Alterations in the CA1 Hippocampus of Rats
Authors: Postnikova Tatyana Y. , Griflyuk Alexandra V. , Tumanova Natalia L. , Dubrovskaya Nadezhda M. , Mikhel Anastasia V. , Vasilev Dmitriy S. , Zaitsev Aleksey V.
Published: February 2025

Prenatal hyperhomocysteinemia (HCY) is associated with neurodevelopmental deficits, yet its long-term impact on hippocampal synaptic function remains poorly understood. This study examines the effects of moderate maternal HCY on excitatory synaptic transmission in the CA1 region of the dorsal hippocampus in rat offspring at juvenile (P21) and adult (P90) stages. Using field postsynaptic potential (fPSP) recordings, electron microscopy, and Western blot analysis, we observed a significant age-dependent decline in the efficiency of excitatory synaptic transmission in HCY-exposed rats. Electron microscopy revealed structural alterations, including synaptic vesicle agglutination in the stratum radiatum, suggesting impaired neurotransmitter release. Additionally, a significant reduction in pyramidal neuron density was observed in the CA1 region, although seizure susceptibility remained unchanged. Western blot analysis showed altered expression of Synapsin I, indicating presynaptic dysfunction. These findings suggest that moderate prenatal HCY leads to persistent deficits in synaptic transmission and structural integrity, potentially contributing to cognitive impairments in adulthood. Our results highlight the importance of maternal homocysteine levels in shaping hippocampal function and could offer insights into neurodevelopmental disorders associated with metabolic disturbances.
Exploring the Utility of Renal Resistive Index in Critical Care: Insights into ARDS and Cardiac Failure
Authors: Cuttone Giuseppe , Geraci Giulio , La Via Luigi , Sorbello Massimiliano , Pappalardo Federico , Carollo Caterina
Published: February 2025

The renal resistive index (RRI), a Doppler ultrasound-derived parameter measuring renal vascular resistance, has emerged as a promising non-invasive tool to evaluate renal hemodynamics in critically ill patients, particularly those with acute respiratory distress syndrome (ARDS) and heart failure (HF). This narrative review examines the current evidence for RRI measurement in these conditions, exploring its physiological bases, methodology, clinical applications, and limitations. In ARDS, RRI reflects the complex interactions between positive pressure ventilation, hypoxemia, and systemic inflammation, showing a role in predicting acute kidney injury and monitoring response to interventions. In HF, RRI is able to assess venous congestion and cardiorenal interactions and can also serve as a prognostic indicator. Many studies have shown RRI’s superiority or complementarity to traditional biomarkers in predicting renal dysfunction, although its interpretation requires consideration of multiple patient-related factors. Key challenges include operator dependency, lack of standardization, and complex interpretation in multi-organ dysfunction. Future research should focus on measurement standardization, development of automated techniques, investigation of novel applications like intraparenchymal renal resistive index variation, and validation of RRI-guided management strategies. Despite its limitations, RRI represents a valuable tool that offers bedside and real-time insights into renal hemodynamics and potential guidance for therapeutic interventions. Further research is needed to fully clarify its clinical potential and address current limitations, particularly in critical care settings involving multiple organ dysfunction.
Effect of Different Luting Methods on the Microtensile Bond Strength of CAD/CAM Resin Blocks
Authors: Vinagre Alexandra , Delgado Carla , Almeida Gabriela , Messias Ana , Ramos João Carlos
Published: February 2025

The widespread implementation of new CAD/CAM materials has led to the necessity of establishing an adequate luting protocol. The aim of this study was to evaluate the microtensile bond strength (μTBS) and the film thickness of different luting methods on CAD/CAM resin blocks. Five Brilliant Crios CAD/CAM blocks (Coltene/Whaledent) were sequentially sectioned into two halves, air abraded with 50 µm aluminum oxide, and luted according to five different cementation protocols: Brilliant EverGlow (BEG), Brilliant EverGlow with ultrasound application (BEG-US), preheated Brilliant EverGlow (BEG-H), Brilliant EverGlow Flow (BEGF), and Duo Cem® Trans (DC). Subsequently, the blocks were sectioned to obtain rods, which were then submitted to a microtensile bond strength test (n = 20). The surfaces were examined with optical microscopy to determine the failure mode and the bonding interface was assessed with scanning electron microscope (SEM) analysis. Bond strength values were analyzed using one-way ANOVA and Tukey’s post hoc tests (α = 0.05). The bond strength values varied with the different cementation protocols (p < 0.001): BEG (45.48 ± 18.14 MPa), BEG-US (42.15 ± 14.90 MPa), BEG-H (41.23 ± 15.15 MPa), BEGF (58.38 ± 15.65 MPa), and DC (81.07 ± 8.75 MPa). Regarding bond strength, DC presented significantly higher values than all other experimental groups (p < 0.050), whereas all luting methods using BEG presented similar values (p = 0.894). Adhesive failures were the predominant type. On SEM evaluation, all the luting materials presented a tight and homogeneous cement–block interface with variable film thicknesses. In conclusion, among the cementation protocols, the resin cement (DC) rendered the highest bond strength values. SEM analysis revealed that the lowest film thickness was associated with the flowable composite (BEGF).
Correlation of Neuroanatomical Structures Related to Speech in Cerebral Palsy Patients Aged 0–17: A Retrospective MRI Study
Authors: Berk Erhan , Üzümcüoğlu Rümeysa , İnceoğlu Feyza , Aydın Merve , Arpacı Muhammed Furkan , Sığırcı Ahmet , Pekmez Hıdır
Published: February 2025

Background/Objectives: Cerebral Palsy (CP) is a non-progressive clinical condition characterized by secondary issues, including speech impairments. Our study aims to evaluate the volumes of brain areas related to speech in patients diagnosed with CP between the ages of 0–17. Methods: this study includes the images of 84 children: 42 in the control group who applied to the hospital between the specified dates and were reported as healthy by MRI from the patient records, and 42 patients with CP. Results: in the CP group, white and gray matter, cerebrum, cerebellum, thalamus, lobus frontalis, lobus temporalis, lobus parietalis, lobus insularis, gyrus cinguli, and nuclei basales volumes were observed to decrease statistically significantly compared to the control group (p ˂ 0.001). Conclusions: we found a significant decrease in the volumes of speech-related brain areas in CP patients, indicating that CP can significantly impact the brain’s speech-related regions.
Automated R-DAC Layout Design with Parameterized Topology Written in SWA: SoftWare Analog
Authors: Sugawara Mitsutoshi , Susa Hidekana , Mori Kenji , Matsuzawa Akira
Published: February 2025

Leading-edge analog/mixed-signal LSI designs are still hand-crafted using graphic editors. These graphic editors do not include functionality for parameterized topologies in variable designs. Instead of graphic editors, we have developed the SWA (SoftWare Analog) language, which can describe and display placements and routing for analog/mixed-signal LSI layouts with less or similar labor time. By using SWA, we have developed an R-DAC (resistive digital–analog converter) layout with a parameterized topology and various parameters, such as ~1 Gsps, 4~12-bit (upper segment type + lower R-2R type) R-DAC, and 1~3.3 V logic with 1~3.3 Vpp analog output.
Interactions Between Sc2O3 Ceramics and Calcium–Magnesium–Alumina–Silicate (CMAS) at Elevated Temperature
Authors: Mo Zupeng , Mo Zijian , Yu Zhiyun , Cheng Yifan , Miao Yiling , Liang Tianquan
Published: February 2025

The thermochemical interactions of Sc2O3 ceramics with CMAS at 1250 °C and 1300 °C were investigated in this paper. A continuously dense reaction layer (DRL) forms on the surface of the ceramic at the beginning of the reaction within 15 min, and temperature significantly affects the components of the DRL. The DRL is mainly composed of a diopside phase at 1250 °C, whose thickness decreases with reaction time, while it is composed of garnet and minor diopside phases at 1300 °C, and thickens in accordance with the parabolic law with exposure time. The DRL shows good effect on alleviating Mg2+ infiltration and some mitigating effect to Al3+, and relatively inferior resistance to Ca2+ and Si4+ penetration. The concentration of Sc3+ in the residual CMAS increases with reaction temperature and time, and the average contents are about 0.7 at% and 3.7 at% after reactions at 1250 °C and 1300 °C, respectively. The mechanism is discussed systematically.
Understanding Secondary Inservice Teachers’ Perceptions and Practices of Implementing Integrated STEM Education
Authors: Berry Amanda , Carpendale Jared , Mulhall Pamela
Published: February 2025

Integrated STEM (i-STEM) education is attracting attention from educators and researchers worldwide to improve student achievement and engagement in STEM subjects and encourage the take-up of STEM-related careers. Multiple models of STEM integration have been proposed, and how i-STEM is interpreted and enacted in school contexts appears to vary considerably. This article reports the perceptions and practices of a group of Australian secondary school teachers with a commitment to implementing i-STEM in their schools but who have not received any specific professional development in this domain. Through individual, qualitative interviews, the study revealed considerable variation in how the teachers interpreted and enacted i-STEM in their schools. Teachers tended to develop learning activities that prioritized the subject area of their particular expertise and that had only tenuous links to mathematics. They considered i-STEM more engaging for their students than traditional subjects but were constrained in their planning by their various school regimes concerning assessment, curricula, and timetables. These structural and systemic impediments represent a core challenge for STEM teachers and teaching as greater numbers of schools and teachers in Australia are expected to implement some form of i-STEM education. Insights from this study point to the importance of developing support structures that allow for variations in context, as well as teacher interest and experience, yet that embrace a coherent and cohesive view of i-STEM, in the absence of a formal STEM curriculum and available professional development opportunities.
Trends and Applications of Artificial Intelligence in Project Management
Authors: Vergara Diego , del Bosque Antonio , Lampropoulos Georgios , Fernández-Arias Pablo
Published: February 2025

The integration of artificial intelligence (AI) into project management (PM) transforms how projects are planned, executed, and monitored. The main objective of this study is to provide a comprehensive bibliometric analysis exploring trends, thematic areas, and future directions in AI applications in project management by examining publications from the last decade. This research uncovers dominant themes such as machine learning, decision making, information management, and resource optimization. The findings highlight the growing use of AI to enhance efficiency, accuracy, and innovation in PM processes, with recent trends favoring data-driven approaches and emerging technologies like generative AI. Geographically, China, India, and the United States lead in publications, while the United Kingdom and Australia show a high citation impact. The research landscape, including AI-enhanced decision-making frameworks and cost analysis, demonstrates the diversity of AI applications in PM. An increased interest in the use of generative AI and its impact on PM and project managers was observed. This analysis contributes to the field by offering a structured overview of research trends, defining the challenges and opportunities for integrating AI into project management practices and offering perspectives on emerging technologies.
Optimization of Passive Damping for LCL-Filtered AC Grid-Connected PV-Storage Integrated Systems
Authors: Zhang Yue , Song Chenchen , Wang Tao , Wang Kai
Published: February 2025

This paper conducts an in-depth study on the application of inductor-capacitor-inductor (LCL) filters in grid-connected photovoltaic (PV) inverters. First, the resonance issues associated with LCL filters are analyzed, and solutions are discussed, with a focus on the implementation of passive damping strategies. Various passive damping schemes, based on the placement of resistors (R), are compared and analyzed, ultimately selecting the capacitor branch series resistor as the optimal solution. During the design process, multiple parameters, such as total inductance, inverter-side inductance, grid-side inductance, capacitance, and damping resistors, are considered in light of their mutual constraints. Detailed analysis and optimization of these parameters are performed based on steady-state operation, current ripple, and power loss limitations. Finally, it is concluded that the passive damping solution using a series resistor in the capacitor branch meets the requirements for stable operation and efficient filtering. The optimal solutions are identified as R1 = 0, R2 = ∞, R3 ≠ 0, and R4 = ∞, providing a reliable and effective filtering solution for grid-connected PV inverter systems.
Fast Temperature Calculation Method for Spindle Servo Permanent Magnet Motors Under Full Operating Conditions Based on the Thermal Network Method
Authors: Ma Sheng , Li Yijia , Hao Xueyan , Zhang Bo , Feng Wei
Published: February 2025

In CNC machines, the temperature field analysis of spindle servo permanent magnet motors (SSPMMs) under rated load, overload, and weak magnetic conditions is critical for ensuring stable operation and machining accuracy. This paper proposes a temperature calculation method for SSPMMs based on the thermal network method, which is used to quickly evaluate the temperature performance of SSPMMs under different operating conditions during design. This method can calculate the steady-state or transient temperature rise under different operating conditions. First, the electromagnetic performance and heat sources of the SSPMMs were analyzed. Then, based on the thermal network method, the equivalent thermal resistances and equivalent heat dissipation coefficients of the motor components were calculated. By iterating the heat balance equation or solving the heat conduction equation for different operating conditions, the temperature distribution of SSPMMs under different operating conditions was obtained. The accuracy of the thermal network model was validated through temperature analysis using fluid–structure interaction simulations and prototype testing. The results show that the relative error between the winding temperature calculated by the proposed equivalent thermal network model and the measured temperature under different operating conditions is less than 5%. This paper provides a theoretical basis for the thermal management of SSPMM, which can quickly and accurately evaluate the temperature rise in the motor during design.
Successive Approximation and Stability Analysis of Fractional Stochastic Differential Systems with Non-Gaussian Process and Poisson Jumps
Authors: Asthana Nidhi , Nadeem Mohd , Dhayal Rajesh
Published: February 2025

This paper investigates a new class of fractional stochastic differential systems with non-Gaussian processes and Poisson jumps. Firstly, we examine the solvability results for the considered system. Furthermore, new stability results for the proposed system are derived. The findings are established through the application of Grönwall’s inequality, the successive approximation method, and the corollary of the Bihari inequality. Finally, the validity of the results is proved through an example.
Existence of Positive Solutions for a Class of Nabla Fractional Boundary Value Problems
Authors: Dimitrov Nikolay D. , Jonnalagadda Jagan Mohan
Published: February 2025

In this manuscript, we study a class of equations with two different Riemann–Liouville-type orders of nabla difference operators. We show some new and fundamental properties of the related Green’s function. Depending on the values of the orders of the operators, we split our research into two main cases, and for each one of them, we obtain suitable conditions under which we prove that the considered problem possesses a positive solution. We consider the latter to be the main novelty in this work. Our main tool in both cases of our study is Guo–Krasnoselskii’s fixed point theorem. In the end, we give particular examples in order to offer a concrete demonstration of our new theoretical findings, as well as some possible future work in this direction.
Water-Soluble Cu(II) Complexes with Polypyridyl Ligands: Anticancer Activity and DNA Interaction
Authors: dos Santos Herisson F. , da Silva Nádija N. P. , Pereira George B. S. , Lima Mauro A. , Nascimento-Júnior Nailton M. , de Farias Renan L. , Akinyemi Amos O. , Rocha Fillipe V.
Published: February 2025

Background/Objectives: Cu(II) complexes with polypyridine ligands have shown carcinogenic activity already described in the literature and appear as a possible alternative to cisplatin, which has several side effects. In view of this, four Cu(II) complexes with the formulas [Cu(L1)(H2O)2](PF6)2 (A1) and [Cu(L2)(H2O)2](PF6)2 (A2), [Cu(L1)(bipy)](PF6)2 (B1) and [Cu(L2)(bipy)](PF6)2 (B2) were synthesized, where L1 = dipyrido[1,2,5]oxadiazolo[3,4-b]quinoxaline, L2 = 6,7-dicyanodipyrido[2,2-d:2,3-f]quinoxaline, and bipy = 2,2′-bipyridine. Methods: The proposed structures supported characterization techniques (molar conductivity, elemental analyses, absorption spectroscopy in the infrared region, and UV–vis). The interaction of the complexes with DNA was evaluated through an ethidium bromide displacement assay, complemented by theoretical studies using molecular docking. Additionally, the cytotoxic activity of the complexes was tested against DU 145 (prostate tumor), MCF-7 (breast tumor), and PNT-2 (non-tumor prostate) cell lines, with all complexes showing promising results. Results: Among them, complex B1 exhibited the highest number of DNA contacts in molecular docking studies, a binding constant of 3.7 × 106 in the ethidium bromide displacement assay. It was the most selective complex (IS = 5.43) for the DU 145 (prostate tumor) cell line, demonstrating greater selectivity than cisplatin. Conclusions: This study has demonstrated the potential of the Cu(II) complexes obtained, which could be an alternative to platinum complexes in the future
Burden of Informal Caregivers from an HHC Military Hospital in Riyadh, Saudi Arabia: A Cross-Sectional Study
Authors: Costa Daniela Patrícia Santos , Ardah Husam I. , Searya Amjad
Published: February 2025

(1) Background: Home health care (HHC) services guarantee good patient care and family support. Understanding how we can better help our informal caregivers (ICs) by understanding their needs and the burden they experience is crucial. (2) Methods: A cross-sectional study was conducted from June to September 2024 at an HHC facility in Riyadh, Saudi Arabia. The 22-item Zarit Burden Interview (ZBI-22) was used to assess the caregiver burden (CB). ICs of patients with specific diseases (palliative, cancer, chronic, and dementia patients) and other factors were studied to identify any association with informal caregiver burden (ICB). (3) Results: Significant CB was defined as ZBI ≥ 21. The IC (384) participants comprised 119 caregivers of dementia patients, 104 caregivers of chronic patients, 83 caregivers of palliative patients, and 78 caregivers of cancer patients. The total mean of the ZBI-22 score among ICs was 31.66, representing a significant CB. The means by groups were as follows: chronic patients, 38.28; dementia patients, 34.97; cancer patients, 25.21; and palliative patients, 22.94. Other variables, such as the duration of care, education level, relationship with the patient, and unemployment, were associated with CB (p-value < 0.05). (4) Conclusions: The caregivers’ characteristics and the patients’ disease were associated with significant CB. More interventions from healthcare workers to support ICs are essential to release their burden.
Bi-Directional Relationship Between Bile Acids (BAs) and Gut Microbiota (GM): UDCA/TUDCA, Probiotics, and Dietary Interventions in Elderly People
Authors: Francini Emanuele , Badillo Pazmay Gretta V. , Fumarola Stefania , Procopio Antonio Domenico , Olivieri Fabiola , Marchegiani Francesca
Published: February 2025

The gut microbiota (GM), the set of microorganisms that colonizes our intestinal tract, can undergo many changes, some of which are age related. Several studies have shown the importance of maintaining a healthy GM for a good quality of life. In the elderly, maintaining a good GM may become a real defense against infection by pathogens, such as C. difficile. In addition to the GM, bile acids (BAs) have been shown to provide an additional defense mechanism against the proliferation of pathogenic bacteria and to regulate bacterial colonization of the gut. BAs are molecules produced in the host liver and secreted with the bile into the digestive tract, and they are necessary for the digestion of dietary lipids. In the gut, host-produced BAs are metabolized by commensal bacteria to secondary BAs. In general GM and host organisms interact in many ways. This review examines the relationship between GM, BAs, aging, and possible new approaches such as dietary interventions, administration of ursodesoxycholic acid/tauroursodesoxycholic acid (UDCA/TUDCA), and probiotics to enrich the microbial consortia of the GM in the elderly and achieve a eubiotic state necessary for maintaining good health. The presence of Firmicutes and Actinobacteria together with adequate levels of secondary BAs would provide protection and improve the frailty state in the elderly. In fact, an increase in secondary BAs has been observed in centenarians who have reached old age without serious health issues, which may justify their active role in achieving longevity.