bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rhythm-based Temporal Expectations: Unique Contributions of Predictability and Periodicity
Authors: Solli Sandra , Danielsen Anne , Leske Sabine , Blenkmann Alejandro O. , Doelling Keith B. , Solbakk Anne-Kristin , Endestad Tor 
Published: October 2024

Abstract
Anticipating events and focusing attention accordingly are crucial for navigating our dynamic environment. Rhythmic patterns of sensory input offer valuable cues for temporal expectations and facilitate perceptual processing. Rhythm-based temporal expectations may rely on oscillatory entrainment, where neural activity and perceptual sensitivity synchronize with periodic stimuli. However, whether entrainment models can account for aperiodic predictable rhythms remains unclear. Our study aimed to delineate the distinct roles of predictability and periodicity in rhythm-based expectations. Participants performed a pitch-identification task preceded by periodic predictable, aperiodic predictable, or aperiodic unpredictable temporal sequences. By manipulating the temporal position of the target sound, we observed how auditory perceptual performance was modulated by the target position's relative phase relationship to the preceding sequences. Results revealed a significant performance advantage for predictable sequences, both periodic and aperiodic, compared with unpredictable ones. However, only the periodic sequence induced an entrained modulation pattern, with performance peaking in synchrony with the inherent sequence continuation. Event-related brain potentials corroborated these findings. The target-evoked P3b, possibly a neural marker of attention allocation, mirrored the behavioral performance patterns. This supports our hypothesis that temporal attention guided by rhythm-based expectations modulates perceptual performance. Furthermore, the predictive sequences were associated with enhanced target-preceding negativity (akin to the contingent negative variation), indicating enhanced target preparation. The periodic-specific modulation likely reflects more precise temporal expectations, potentially involving neural entrainment and/or more focused attention. Our findings suggest that predictability and periodicity influence perception through distinct mechanisms.
A New Paradigm for Automated Ground Clutter Removal: Global Regression Filtering
Authors: Hubbert J.C. , Meymaris G. , Romatschke U. , Ellis S. , Dixon M. 
Published: October 2024

Abstract
Ground clutter filtering is an important and necessary step for quality control of ground-based weather radars and this is widely done in the spectral domain via use of the Discrete Fourier Transform (DFT). To accomplish spectral clutter filtering, the I (in-phase) and Q (quadrature) time series are multiplied by a window function, such as the Blackman window, which suppresses clutter leakage. Subsequently, the clutter is filtered from the Doppler spectrum by setting spectral coefficients to zero where there is clutter signal. Recently, it has been shown with simulations that a regression clutter filter is a viable alternative. To demonstrate the regression filter, it is applied to radar data from both National Science Foundation-National Center for Atmospheric Research (NSF-NCAR) S-band polarimetric radar (S-Pol), and NEXRAD (Next Generation Weather Radar). A regression filter can be applied directly to the non-windowed time series data, thus avoiding the signal attenuation from a window function, which is required for spectral domain clutter filters such as GMAP (Gaussian Model Adaptive Processing). It is shown that the regression filter rejects clutter as effectively as the spectral technique, or better, but has the distinct advantage that standard error of estimates of the radar variables are in general improved by about 25% to 50% over a comparable spectral domain filter. The regression filter is straightforward and can be executed in real time.
A data-driven framework for occupancy optimisation strategies towards energy demand reduction in non-domestic buildings
Authors: Soong Evelyn (Yun Min) , Gori Virginia , Oraiopoulos Argyris 
Published: October 2024

Proactive strategies for data-driven operational schedules based on monitored occupancy patters can enable energy demand reduction and optimal resource utilisation. A replicable framework that enables strategic closure of specific thermal zones is introduced and design and operational considerations are discussed. The potential of the framework is illustrated through a case study building, where up to 6% annual energy savings were estimated, highlighting the effectiveness of zone closures. Further findings indicated that total energy savings from the simultaneous closure of multiple zones were marginally larger compared to savings from closing off zones individually, depending on zone capacity and use. Therefore, balanced considerations should take place prior to selecting which zones to close off, also taking into account user acceptability, capacity of systems and controls as well as the internal layout of the building. The research enhances the understanding of the relationship between occupancy and energy demand, while offering recommendations for more energy efficient and sustainable building design and operations that require minimal capital cost. Practical Application: This paper provides design and operational considerations based on a robust and replicable framework for energy savings by optimising operational building schedules based on monitored occupancy patterns. This allows a proactive implementation of data-driven strategies that maximise resource utilisation, such as closure of specific zones during periods of low occupancy, without requiring any physical intervention. The findings on a case study building demonstrate that annual energy savings can be achieved, underscoring the potential for substantial cost reductions and improved energy efficiency. Applications can also extend to optimising energy demand for energy flexibility.
A novel method to predict white blood cells after kidney transplantation based on machine learning
Authors: He Songping , Li Xiangxi , Zhao Zunyuan , Li Bin , Tan Xin , Guo Hui , Chen Yanyan , Lu Xia 
Published: October 2024

Background Abnormal white blood cell count after kidney transplantation is an important adverse clinical outcome. The abnormal white blood cell count in patients after surgery may be caused by the use of immunosuppressive agents and other factors. A lower white blood cell count than normal will greatly increase the probability of adverse outcomes such as infection and reduce the success rate of surgery. Objective To establish a machine learning prediction model of leukocyte drop to abnormal level after kidney transplantation, and provide reference for clinical treatment. Methods A total of 546 kidney transplant patients were selected as the study subjects. The time correlation feature of the ratio of the duration time of each variable to the total time in different intervals was innovatively introduced. Least absolute shrinkage and selection operator algorithm was used for correlation analysis of 85 candidate variables, and the top 20 variables were retained in the end. Eight machine learning algorithms, including Logistic-L1, Logistic-L2, support vector machine, decision tree, random forest, multilayer perceptron, extreme gradient boosting and light gradient boosting machine, were used for the five-fold cross-validation on all data sets, and the algorithm with the best performance was selected as the final prediction algorithm based on the average area under the curve. Results As the final prediction model, the accuracy, sensitivity, specificity and area under the curve values of the multilayer perceptron model in test set were 71.34%, 61.18%, 82.28% and 77.30%, respectively. The most important factors affecting leukopenia after surgery were the proportion of time of lymphocyte less than normal, blood group AB, gender, and platelet CV. Conclusions The multilayer perceptron model explored in this study shows significant potential in predicting abnormal white blood cell counts after kidney transplantation. This model can help stratify risk following transplantation, subject to external and/or prospective validation.
Upregulation of PRRX2 by silencing Marveld3 as a protective mechanism against radiation-induced ferroptosis in skin cells
Authors: Cao Jinming , Wu Mengyao , Mo Wei , Zhao Min , Gu Liming , Wang Xi , Zhang Bin , Cao Jianping 
Published: October 2024

Abstract
Background
Radiation-induced skin injury (RISI) represents a significant complication in patients receiving radiotherapy and individuals exposed to nuclear accidents, characterized by a protracted wound-healing process relative to injuries from other etiologies. Current preventive and management approaches remain inadequate. Consequently, investigating efficacious intervention strategies that target the disease’s progression characteristics holds significant practical importance.

Methods
Small interfering RNA (siRNA) and overexpression plasmid were used to modulate the expression of Marvel domain containing 3 (Marveld3) and paired related homeobox 2 (PRRX2). Protein and mRNA levels were estimated by Western Blot and real-time PCR, respectively. Intracellular levels of Malondialdehyde (MDA), a terminal product of lipid peroxidation, were measured following the manufacturer’s protocol for MDA assay kit. Similarly, intracellular levels of ferrous iron (Fe2+) and reactive oxygen species (ROS) were determined using their respective assay kits. Lipid peroxidation status within the cells was evaluated via BODIPY staining. Immunohistochemistry was conducted to ascertain the expression of PRRX2 in skin tissues collected at various time points following irradiation of rats. The H-score method was used to evaluate the percentage of positively stained cells and staining intensity. RNA sequencing, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted by OE Biotech Company.

Results
In this study, our findings indicated that Marveld3 suppression could effectively inhibit lipid peroxidation levels in irradiated skin cells, concomitantly reducing intracellular Fe2+ content. Additionally, the silencing of Marveld3 effectively abrogated the impact of a ferroptosis agonist on cellular viability, resulting in the upregulation of 66 and 178 genes, as well as the downregulation of 188 and 31 genes in irradiated HaCaT and WS1 cells, respectively. Among the differentially expressed genes, the PRRX2 which was found to be involved in the process of ferroptosis, exhibited statistically significant upregulation. And the upregulation of PRRX2 expression may attenuate radiation-induced lipid peroxidation in skin cells, thereby functioning as a potential stress-responsive mechanism to counteract radiation effects.

Conclusions
This study elucidates the role of Marveld3 in radiation-induced ferroptosis in skin cells. Inhibition of Marveld3 led to the upregulation of PRRX2, which subsequently resulted in a reduction of Fe2+ and ROS levels, as well as the suppression of lipid peroxidation. These effects collectively mitigated the occurrence of ferroptosis.
Digitalization of railway transportation through AI-powered services: digital twin trains
Authors: Sarp Salih , Kuzlu Murat , Jovanovic Vukica , Polat Zekeriya , Guler Ozgur 
Published: October 2024

AbstractDigitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry 5.0 (I5.0) and Circular Economy (CE) model supported by the restorative and long-lasting design of the trains. This transformation necessitates leveraging digitalization and emerging technologies to address the needs of passengers, operators, and maintenance personnel. This article provides a comprehensive review focusing on the application of IoT, AI, CE principles, and digital twin trains to existing railway infrastructure and assets. The analysis delves into developing system architecture for proposed solutions and their impact on operation, maintenance, sustainability, and passenger comfort, supported by track record analysis. The integration of these technologies and concepts, particularly AI-powered services, is anticipated to yield immediate advancements in the digitalization of railway transportation, enhancing efficiency and safety measures.
Critical resistance to carbapenem and aminoglycosides in Pseudomonas aeruginosa: spread of blaNDM/16S methylase armA harboring isolates with intrinsic resistance mechanisms in Kerman, Iran
Authors: Soltani Behnaz , Ahmadrajabi Roya , Kalantar-Neyestanaki Davood 
Published: October 2024

Abstract
Background
Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is one of the main Gram-negative bacterium causes of infections in hospital settings, and the spread of them is a significant challenge to public health.

Methods
A total of 30 non-duplicate isolates of CRPA were collected. Antibacterial susceptibility of isolates to antibiotic agents, AmpC β-lactamase production, and biofilm formation were determined. Minimum biofilm inhibitory concentrations (MBIC) of isolates to cefepime (FEP), imipenem (IPM), ceftazidime (CAZ), and meropenem (MEM) were evaluated with/without cloxacillin (CLX). The carbapenemase and 16 S rRNA methylase genes were identified by PCR, and the transcription levels of oprD, ampC, and mexA genes were determined by quantitative real-time PCR (qPCR). ERIC-PCR was used to detect genetic relationships among isolates.

Results
All isolates were multidrug resistant (MDR) and strong biofilm producers. The resistance genes including blaNDM, blaIMP, blaVIM, blaSIM, blaGES, and armA were detected in 21 (70%), 6 (20%), 3 (10%), 2 (6.6%), 1 (3.3%), and 17 (56.6%) of the isolates, respectively. CLX at 500 and 1000 µg/mL significantly reduced the level of MIC to MEM, IPM, CAZ, and FEP, also at 2000 µg/mL significantly reduced the level of MBIC to MEM, IPM, CAZ, and FEP. In all isolates, the transcription levels of oprD were significantly downregulated as well as significantly increased for ampC and mexA. ERIC-PCR typing results divided 30 isolates into four clusters A to D.

Conclusion
In this study, we reported the spread of different clones of CRPA harboring co-existence of various carbapenemase genes with armA 16 S rRNA methylase for the first time in Kerman, Iran. Also, our isolates had several mechanisms of resistance to carbapenems as well as ability biofilm formation along with resistance to aminoglycosides, the further spread of which could cause serious challenges in our hospital settings. Therefore, serious monitoring is necessary to reduce their prevalence.
Adolescents’ physical activity during and beyond the Covid-19 pandemic: a qualitative study exploring the experiences of young people living in the context of socioeconomic deprivation
Authors: Alliott Olivia , Fairbrother Hannah , van Sluijs Esther 
Published: October 2024

Abstract
Background
Adolescent physical activity levels are low and are shown to decline with age into adulthood. Emerging literature suggests these trends were exacerbated during the Covid-19 pandemic. We aimed to understand, from the perspective of adolescents living in deprived communities, whether the Covid-19 pandemic influenced their physical behaviour and explore their ideas for physical activity promotion moving forward.

Methods
Purposive sampling was used to recruit older adolescents (13-18-year-old) living in one of the 20% most deprived areas in the UK, as defined by the UK Index of Multiple Deprivation. A mix of in-person and online one-to-one semi-structured interviews were conducted between July 2021- March 2022. Interviews were audio-recorded, transcribed verbatim and anonymised. Data were imported into Nvivo software and analysed drawing on Braun and Clarke’s six phases of thematic analysis.

Results
The sample consisted of 16 adolescents and included a mix of genders. The following themes were generated during the data analysis: (1) Physical activity behaviour in everyday life (prepandemic), (2) The impact of Covid-19 on physical activity (during) and (3) Young people’s ideas about physical activity promotion (moving forward). Participants described themselves as inactive, with their activity limited to active travel, informal activity and physical education. Experiences of the pandemic were largely negative, impacting participants’ physical and mental health. Ideas around physical activity promotion ranged from the individual to the societal level.

Conclusions
Our findings suggest the Covid-19 pandemic had a major impact on young people living in the context of socioeconomic deprivation. Physical activity promotion efforts should focus on school-based opportunities and the provision of safe and low-cost opportunities in socioeconomically deprived areas. As we aim to build back from the Covid-19 pandemic, supporting young people living in socioeconomically deprived communities should be prioritised.
Effect of ionizing radiation on the shear bond strength of two different adhesive systems in primary teeth. in-vitro study
Authors: Shahin Nourhan Mahmoud , Nagi Basma Mahmoud , Amin Amin El Sayed , Badran Amira Saad 
Published: October 2024

Abstract
Background
Radiotherapy is a treatment modality used for head and neck cancer patients. It has a negative influence on bonding strength of adhesives. Little information is available about the effect of radiotherapy on bonding strength of adhesives in primary teeth. Therefore, this in vitro study aimed to detect the best adhesive system and ideal time to apply restorations in primary irradiated teeth regarding adhesive shear bond strength.

Methods
Dentin samples from primary teeth were randomly assigned to four groups based on restoration application time and radiation exposure, (G1: control, G2: preradiation, G3: 24 h postradiation, and G4: 6 months postradiation) with 20 samples per group. These groups were further divided into 2 subgroups according to the adhesive system used, with 10 samples per subgroup. (1) 3M™ Single Bond Universal Adhesive (SB), (2) 3M AdperSingle Bond 2 (AS). Samples were exposed to gamma radiation from a cobalt-60 machine. One shot of 60 Gy of radiation was delivered. Then samples were subjected to a shear bond strength test. The load was applied until failure and the maximum load was recorded. Numerical data are presented as mean and standard deviation values, then distributed according to Shapiro–Wilk test or Levene's test and analyzed via two-way ANOVA. The significance level was set at p < 0.05 for all tests. Statistical analysis was performed with R statistical analysis software version 4.4.1 for Windows (Team RC, R: A language and environment for statistical computing. R foundation for statistical computing, 2023).

Results
Compared with the AS subgroup, the SB subgroup presented significantly greater values (p < 0.001). For SB, there was no significant difference among the G1 and G4 groups (p > 0.001). However, there was a significant difference between G1, G2, and G3 (p < 0.001, P = 0.025, P = 0.265 ns respectively), and G3 presented the lowest values. For AS, there was no significant difference between groups G1 and G4 (p =  < 0.001). Compared with the other groups, G3 presented a significant difference (p = 0.265 ns) and the lowest results.

Conclusion
Restorations performed 24 h after radiation had lower bond strength than those performed six months after radiation. Regardless of the adhesive system used, SB performed better than AS in terms of the shear bond strength.
Clinical utility index for root canal sealers
Authors: Chandak Manoj , Patel Aditya , Patel Satyawansingh , Agrawal Paridhi , Chandak Rakhi , Ikhar Anuja 
Published: October 2024

Abstract
Background
Effective endodontic treatment requires the use of a root canal sealer with optimal properties to ensure a hermetic seal, prevent reinfection, and promote healing. Despite the availability of various sealers, a standardized evaluation system still needs to be improved.

Objectives
To develop a Clinical Utility Index (CUI) that systematically evaluates and ranks root canal sealers based on their sealing ability, antimicrobial efficacy, flow rate, and solubility.

Methods
The CUI was developed through a structured process involving expert identification, panel discussions, and the establishment of scoring criteria. Five sealers were evaluated (Sealers A, B, C, D, and E). Mean values for the core properties were calculated, and sealers were ranked accordingly. The total CUI for each sealer was computed based on the assigned scores for each property.

Results
Sealer B achieved the highest CUI at 95%, demonstrating superior performance across all core properties. Sealer C followed with a CUI of 80%, while Sealer A ranked third with 60%. Sealers D and E showed the lowest performance, with CUIs of 30% and 35%, respectively, highlighting deficiencies in multiple properties.

Discussion
The CUI provides a comprehensive evaluation framework for root canal sealers, facilitating informed decision-making by practitioners. Sealer B's high CUI underscores the importance of balancing sealing ability, antimicrobial effect, flow rate, and solubility. The results align with existing literature emphasizing the critical role of these properties in endodontic success.

Conclusion
The CUI offers a robust and balanced method for evaluating root canal sealers, aiding in selecting the most suitable sealer based on empirical data. Future research should refine the index and validate its applicability in diverse clinical scenarios to enhance endodontic treatment outcomes.