bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the Efficiency and Stability of MAPbI3 Perovskite Solar Cells by Dipeptide Molecules
Authors: Li Mingya , Yue Ziyao , Ye Zecong , Li Huixue , Luo Huanting , Yang Qing‐Dan , Zhou Yecheng , Huo Yanping , Cheng Yuanhang 
Published: January 2024

AbstractPassivating the electronic defects of metal halide perovskite is regarded as an effective way to improve the power conversion efficiency (PCE) of perovskite solar cells (PVSCs). Here, a series of dipeptide molecules with abundant ─C═O, ─O─ and ─NH functional groups as defects passivators for perovskite films are employed. These dipeptide molecules are utilized to treat the surface of prototype methyl ammonium lead iodide (MAPbI3) films and the corresponding PVSCs exhibit enhanced photovoltaic performance and ambient stability, which can be ascribed to: 1) the ─C═O and ─O─ can interact with the undercoordinated Pb2+ ions and the ─NH groups can form hydrogen bonds with the I− ions, passivating the defects in perovskite film and reducing charge recombination in PVSCs; 2) the long alkyl chain of dipeptide molecules increases the hydrophobicity of the perovskite surface and thus enhance the stability of PVSCs. The passivated MAPbI3‐based PVSCs exhibit a champion PCE of 20.3% and retain 60% of the initial PCE after 1000 h. It is believed that the defects passivation engineering using polypeptide moleculars can be applied in other perovskite compositions for high device efficiency and stability.
The use of S460 steel grade in the construction of OHL transmission towers
Authors: Labocha Slawomir , Tibolt Mike , Ochojski Wojciech , Chrzanowski Maciej 
Published: January 2024

AbstractThe article describes structural solutions and specialised testing of innovative steel lattice towers intended for 400 kV overhead line (OHL). A unique aspect of the preformed research is the use of S460 steel grade in the structure of such transmission towers. This new series of towers was developed in reference to current EN 50341‐2‐22:2016 standard that introduces higher safety standards for OHL towers. A full‐scale prototype was developed and analysed, where the verification of the standard load‐bearing capacity was done and proceeded by the destructive test in order to determine the ultimate capacity of the new tower typology. The article presents the obtained results, the justification for the use of S460 steel grade and a comparative analysis with the classical engineering procedures. A good agreement between a theoretical model and the test results is demonstrated.
Mast cell tumour‐associated osteolysis in a Shiba dog
Authors: Maeda Kenichi , Sakonju Iwao , Kakizaki Takehiko , Iwai Satomi , Okano Shozo 
Published: January 2024

AbstractA 13‐year‐old, female Shiba dog presented with elevation of the right pelvic limb and swelling of the thigh. The right pelvic limb was severely swollen, and subcutaneous haemorrhaging was observed. Radiographs showed bone resorption in the stifle joint region. Fine‐needle aspiration cytology of the stifle was consistent with a mast cell tumour. Computed tomography was performed, and the affected limb was amputated. The histo‐pathological diagnosis was mast cell tumour, and the femur and tibia were found externally lysed with an internal invasion of tumour cells. The safety margins were secured, but the tumour had infiltrated the lymph nodes. Hence, the patient was treated with chemotherapy. There was no tumour recurrence or metastasis for 201 days after surgery, but the patient died. To our knowledge, no case of osteolysis due to mast cell tumour has been reported, making this a very rare case.
Charging solid partitions
Authors: Galakhov Dmitry , Li Wei 
Published: January 2024

Abstract
Solid partitions are the 4D generalization of the plane partitions in 3D and Young diagrams in 2D, and they can be visualized as stacking of 4D unit-size boxes in the positive corner of a 4D room. Physically, solid partitions arise naturally as 4D molten crystals that count equivariant D-brane BPS states on the simplest toric Calabi-Yau fourfold, ℂ4, generalizing the 3D statement that plane partitions count equivariant D-brane BPS states on ℂ3. In the construction of BPS algebras for toric Calabi-Yau threefolds, the so-called charge function on the 3D molten crystal is an important ingredient — it is the generating function for the eigenvalues of an infinite tower of Cartan elements of the algebra. In this paper, we derive the charge function for solid partitions. Compared to the 3D case, the new feature is the appearance of contributions from certain 4-box and 5-box clusters, which will make the construction of the corresponding BPS algebra much more complicated than in the 3D.
Some Properties of Affine $${\mathcal {C}}$$-semigroups
Authors: García-García J. I. , Marín-Aragón D. , Sánchez-Loureiro A. , Vigneron-Tenorio A. 
Published: January 2024

AbstractNumerical semigroups have been extensively studied throughout the literature, and many of their invariants have been characterized. In this work, we generalize some of the most important results about symmetry, pseudo-symmetry, or fundamental gaps, to affine $${\mathcal {C}}$$
C
-semigroups. In addition, we give algorithms to compute the tree of irreducible $${\mathcal {C}}$$
C
-semigroups and $${\mathcal {C}}$$
C
-semigroups with a given Frobenius vector.
On Continuous Parameter Dependence of Roots of Analytic Functions
Authors: Möller Manfred 
Published: January 2024

AbstractLet $${\mathcal {A}}_n(\Omega )$$

A
n

(
Ω
)

be the set of analytic functions on a domain $$\Omega $$
Ω
of the complex plane which have n roots in $$\Omega $$
Ω
, counted with multiplicity. In this note we consider functions in $${\mathcal {A}}_n(\Omega )$$

A
n

(
Ω
)

which depend continuously on a parameter. A simple short proof shows that the set of roots in the Hausdorff metric depends continuously on the parameter. If the parameter space is connected and all roots are known to lie in one of two disjoint open subsets $$\Omega _1$$

Ω
1

, $$\Omega _2$$

Ω
2

of the complex plane, then the number of the roots, counted with multiplicity, in $$\Omega _1$$

Ω
1

and $$\Omega _2$$

Ω
2

, respectively, is independent of the parameter. Each set of roots generates a unique monic polynomial. It is shown that the map which associates with each function in $${\mathcal {A}}_n(\Omega )$$

A
n

(
Ω
)

the corresponding monic polynomial is continuous when $${\mathcal {A}}_n(\Omega )$$

A
n

(
Ω
)

is equipped with the topology of uniform convergence on compact subsets of $$\Omega $$
Ω
. Possible applications are indicated.
Effects of particle damper design parameters on the damping performance of laser powder bed fused structures
Authors: Ozcevik Birol , Soylemez Emrecan , Bediz Bekir , Simsek Ugur 
Published: January 2024

AbstractParticle dampers (PD), a passive damping technology, absorb energy from particle-particle and particle-cell wall interactions originating from friction and collision. PDs offer advantages such as design simplicity, low cost, applicability in harsh conditions, and flexibility to be used in a wide frequency band range. Additive manufacturing, specifically the powder bed fusion process, can fabricate structures with integrated PDs in a single printing process, eliminating the need to implement external dampers. However, the dynamic behavior of PDs must be determined to utilize their full potential. In this study, we examined 16 cases of integrated PDs by varying specific parameters including size, number, and locations on the structure to understand the effects of these parameters on the dynamic behavior of the first and second modes of the structure. Modal tests were conducted on additively manufactured samples to extract frequency response functions and calculate modal parameters (natural frequency and damping ratio) using the rational fraction polynomial method, studying the effects of PDs. The results showed that the damping performance of the parts was increased by a factor of up to 10 using body-integrated PDs compared with the fully fused specimen. The effectiveness of body-integrated PDs was shown to be strongly dependent on their volume and location. For instance, the damping generally increased as the volume fraction increased, which also reduced the total weight of the specimens by up to 60 g. Furthermore, the damping performance significantly increased for a specific mode when the PDs were located near the maximum displacement regions.
Enhancing paranasal sinus disease detection with AutoML: efficient AI development and evaluation via magnetic resonance imaging
Authors: Cheong Ryan Chin Taw , Jawad Susan , Adams Ashok , Campion Thomas , Lim Zhe Hong , Papachristou Nikolaos , Unadkat Samit , Randhawa Premjit , Joseph Jonathan , Andrews Peter , Taylor Paul , Kunz Holger 
Published: January 2024

Abstract
Purpose
Artificial intelligence (AI) in the form of automated machine learning (AutoML) offers a new potential breakthrough to overcome the barrier of entry for non-technically trained physicians. A Clinical Decision Support System (CDSS) for screening purposes using AutoML could be beneficial to ease the clinical burden in the radiological workflow for paranasal sinus diseases.

Methods
The main target of this work was the usage of automated evaluation of model performance and the feasibility of the Vertex AI image classification model on the Google Cloud AutoML platform to be trained to automatically classify the presence or absence of sinonasal disease. The dataset is a consensus labelled Open Access Series of Imaging Studies (OASIS-3) MRI head dataset by three specialised head and neck consultant radiologists. A total of 1313 unique non-TSE T2w MRI head sessions were used from the OASIS-3 repository.

Results
The best-performing image classification model achieved a precision of 0.928. Demonstrating the feasibility and high performance of the Vertex AI image classification model to automatically detect the presence or absence of sinonasal disease on MRI.

Conclusion
AutoML allows for potential deployment to optimise diagnostic radiology workflows and lay the foundation for further AI research in radiology and otolaryngology. The usage of AutoML could serve as a formal requirement for a feasibility study.
Inter-individual, hemispheric and sex variability of brain activations during numerosity processing
Authors: Zang Zhongyao , Chi Xiaoyue , Luan Mengkai , Hu Siyuan , Zhou Ke , Liu Jia 
Published: January 2024

AbstractNumerosity perception is a fundamental and innate cognitive function shared by both humans and many animal species. Previous research has primarily focused on exploring the spatial and functional consistency of neural activations that were associated with the processing of numerosity information. However, the inter-individual variability of brain activations of numerosity perception remains unclear. In the present study, with a large-sample functional magnetic resonance imaging (fMRI) dataset (n = 460), we aimed to localize the functional regions related to numerosity perceptions and explore the inter-individual, hemispheric, and sex differences within these brain regions. Fifteen subject-specific activated regions, including the anterior intraparietal sulcus (aIPS), posterior intraparietal sulcus (pIPS), insula, inferior frontal gyrus (IFG), inferior temporal gyrus (ITG), premotor area (PM), middle occipital gyrus (MOG) and anterior cingulate cortex (ACC), were delineated in each individual and then used to create a functional probabilistic atlas to quantify individual variability in brain activations of numerosity processing. Though the activation percentages of most regions were higher than 60%, the intersections of most regions across individuals were considerably lower, falling below 50%, indicating substantial variations in brain activations related to numerosity processing among individuals. Furthermore, significant hemispheric and sex differences in activation location, extent, and magnitude were also found in these regions. Most activated regions in the right hemisphere had larger activation volumes and activation magnitudes, and were located more lateral and anterior than their counterparts in the left hemisphere. In addition, in most of these regions, males displayed stronger activations than females. Our findings demonstrate large inter-individual, hemispheric, and sex differences in brain activations related to numerosity processing, and our probabilistic atlas can serve as a robust functional and spatial reference for mapping the numerosity-related neural networks.
The association between depression and alcohol use among pregnant adults in the USA
Authors: Chapman Madison , Bandoli Gretchen , Goldenberg Shira M. 
Published: January 2024

Abstract
Background
The prevalence of alcohol use among pregnant women aged 18–44 years old increased in recent years. The influence of mental health issues on an individual’s likelihood to use alcohol during pregnancy has not been thoroughly investigated. This study will examine the association between experiencing a major depressive episode (MDE) in the past year and past-month alcohol use among pregnant women using the 2011–2020 National Survey on Drug Use and Health (NSDUH).

Methods
Pregnant women between the ages of 18 and 44 years old were included in the study for analysis. Multivariable logistic regression analysis was used to examine the association between past-year MDE and past-month alcohol use adjusting for age, race/ethnicity, marital status, and employment status. Additional logistic regression analysis was performed to investigate whether this relationship differed by trimester of pregnancy.

Results
A total of 6745 participants were included in the analytic sample. The prevalence of past-year MDE and past-month alcohol use was 7.67% and 9.15% respectively. Logistic regression analysis showed past-year MDE was significantly associated with past-month alcohol use in pregnant women adjusting for age, race/ethnicity, marital status, and employment status (aOR = 1.96; 95% CI, 1.34–2.87). This relationship became stronger in second and third trimesters of pregnancy.

Conclusions
This study showed a positive association between MDE and past-month alcohol use among pregnant women, with strongest effect estimates in the third trimester. These findings may inform approaches for improved screening guidelines and health education for individuals who may be at higher risk of prenatal alcohol use.
13C dicarboxylic acid signatures indicate temporal shifts in catchment sediment sources in response to extreme winter rainfall
Authors: Upadhayay Hari Ram , Joynes Adrian , Collins Adrian L. 
Published: January 2024

AbstractRainfall and land-use interactions drive temporal shifts in suspended sediment sources, yet the magnitude of such changes remains poorly understood due to the lack of land-use specific source tracers. We investigated α,ω-dicarboxylic fatty acid root-specific biomarkers, as diagnostic tracers for apportioning sources of time-integrated suspended sediment samples collected from a grassland dominated agricultural catchment in the southwest of England during the wet winter period. Applying fatty acids-specific stable carbon isotope analysis and a Bayesian isotope mixing model, we show that stream banks contributed most of the sediment in the early winter, i.e. October–December, while winter cereal-dominated arable land contributed more than half of the sediment during the late winter, i.e. January–March. The dominant sediment source shifted in conjunction with a period of prolonged consecutive rainfall days in the later period suggesting that intervention required to mitigate soil erosion and sediment delivery should adapt to changing rainfall patterns. Our novel findings demonstrate that isotopic signatures of α,ω-dicarboxylic fatty acids are promising tracers for understanding the resistance of agricultural soils to water erosion and quantifying the interactive effects of extreme rainfall and land use on catchment sediment source dynamics.
Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data
Authors: Rimpler Aljoscha , Siepe Björn S. , Rieble Carlotta L. , Proppert Ricarda K. K. , Fried Eiko I. 
Published: January 2024

AbstractEcological Momentary Assessment (EMA) is a data collection approach utilizing smartphone applications or wearable devices to gather insights into daily life. EMA has advantages over traditional surveys, such as increasing ecological validity. However, especially prolonged data collection can burden participants by disrupting their everyday activities. Consequently, EMA studies can have comparably high rates of missing data and face problems of compliance. Giving participants access to their data via accessible feedback reports, as seen in citizen science initiatives, may increase participant motivation. Existing frameworks to generate such reports focus on single individuals in clinical settings and do not scale well to large datasets. Here, we introduce FRED (Feedback Reports on EMA Data) to tackle the challenge of providing personalized reports to many participants. FRED is an interactive online tool in which participants can explore their own personalized data reports. We showcase FRED using data from the WARN-D study, where 867 participants were queried for 85 consecutive days with four daily and one weekly survey, resulting in up to 352 observations per participant. FRED includes descriptive statistics, time-series visualizations, and network analyses on selected EMA variables. Participants can access the reports online as part of a Shiny app, developed via the R programming language. We make the code and infrastructure of FRED available in the hope that it will be useful for both research and clinical settings, given that it can be flexibly adapted to the needs of other projects with the goal of generating personalized data reports.
Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks
Authors: Langener Anna M. , Bringmann Laura F. , Kas Martien J. , Stulp Gert 
Published: January 2024

AbstractSocial interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. Digital phenotyping is a commonly used technology to assess a person's social behavior objectively. The experience sampling method (ESM) can capture the subjective perception of specific interactions. Lastly, egocentric networks are often used to measure specific relationship characteristics. These different methods capture different aspects of the social context over different time scales that are related to well-being, and combining them may be necessary to improve the prediction of well-being. Yet, they have rarely been combined in previous research. To address this gap, our study investigates the predictive accuracy of mood based on the social context. We collected intensive within-person data from multiple passive and self-report sources over a 28–day period in a student sample (Participants: N = 11, ESM measures: N = 1313). We trained individualized random forest machine learning models, using different predictors included in each model summarized over different time scales. Our findings revealed that even when combining social interactions data using different methods, predictive accuracy of mood remained low. The average coefficient of determination over all participants was 0.06 for positive and negative affect and ranged from − 0.08 to 0.3, indicating a large amount of variance across people. Furthermore, the optimal set of predictors varied across participants; however, predicting mood using all predictors generally yielded the best predictions. While combining different predictors improved predictive accuracy of mood for most participants, our study highlights the need for further work using larger and more diverse samples to enhance the clinical utility of these predictive modeling approaches.
Damage observations of RC buildings from 2023 Kahramanmaraş earthquake sequence and discussion on the seismic code regulations
Authors: Vuran Eren , Serhatoğlu Cavit , Timurağaoğlu M.Ömer , Smyrou Eleni , Bal İhsan E. , Livaoğlu Ramazan 
Published: January 2024

AbstractKahramanmaraş Earthquake Sequence of 6th of February is the deadliest earthquake that happened in Turkey in the era of instrumental seismology, claiming more than 55 thousand lives and leaving torn down cities and towns behind. More than 450 km long lateral strike-slip fault ruptured during these catastrophic earthquakes. As a result, more than 38 thousand buildings collapsed causing life losses. Considering that the large share of the Turkish building stock consists of RC buildings, the vulnerable RC building stock is the main responsible for this picture. Deficiencies of the Turkish RC building stock are well known since they manifested themselves several times in the past earthquakes. However, considering the improvements in the seismic codes and the seismic hazard maps achieved in the last two decades, the widespread collapse of buildings constructed after year 2000 was rather unexpected. Some of the observed structural damage patterns are similar to those observed also in the pre-2000 buildings in recent earthquakes, however, some other types of damages, such as out-of-plane bending and shear failures or shear-friction capacity failure of RC walls, brittle fracture and bond-slip failure of reinforcement, tension failure of beams and slabs are usually not witnessed. This paper presents a carefully selected set of examples comparing the pre-2000 and post-2000 building damages and collapses, also referring to a detailed summary and comparison of the code developments in Turkey.
A methodology for analysing the impacts of climate change on maritime security
Authors: Brennan James , Germond Basil 
Published: January 2024

AbstractThis paper presents a methodology for developing a social Cumulative Effects Assessment (CEA) which analyses the impacts of climate change on maritime crime and maritime insecurities. The use of a CEA methodology, including the use of the Effect to Impact Pathway will enable mapping the relationships between certain ‘Activities’ (e.g. human-induced emissions of greenhouse gasses), the ‘Pressure’ engendered (e.g. warming sea temperatures) and their ‘Impacts’ (e.g. food shortages) via ‘Receptors’ (e.g. fishing communities) on specific sectors of society (in this case maritime migration and maritime crime, e.g. illegal fishing). This paper provides a Proof of Concept (PoC) for using such a methodology and shows the applicability of a multidisciplinary approach in understanding causal chains. In this PoC, the authors are generating a Non-Geographic Assessment Map that investigates the ‘Impacts’ that the human-induced greenhouse gas emissions have on maritime security. The proposed analytical tool can then be applied in further studies to assess the dependencies and synergies between climate change and the occurrence of maritime insecurity.