bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lens-free reflective topography for super-resolution wafer inspection
Authors: Lee Myungjun , Lee Hojun , Sung Jangwoon , Park Seungbeom , Shin Junho , Kim Hyungjin , Kim Wookrae 
Published: October 2023

Abstract
The demand for high-resolution and large-area imaging systems for non-destructive wafer inspection has grown owing to the increasing complexity and extremely fine nature of semiconductor processes. Several studies have focused on developing high-resolution imaging systems; however, they were limited by the tradeoff between image resolution and field of view. Hence, computational imaging has arisen as an alternative method to conventional optical imaging, aimed at enhancing the aforementioned parameters. This study proposes a method for improving the resolution and field of view of an image in a lens-less reflection-type system. Our method was verified by computationally restoring the final image from diffraction images measured at various illumination positions using a visible light source. We introduced speckle illumination to expand the numerical aperture of the entire system, simultaneously improving image resolution and field of view. The image reconstruction process was accelerated by employing a convolutional neural network. Using the reconstructed phase images, we implemented super-resolution topography and demonstrated its applicability in wafer surface inspection. Furthermore, we demonstrated an ideal diffraction-limited spatial resolution of 1.7 m over a field of view of 1.8 1.8 mm2 for the topographic imaging of targets with various surface roughness. The proposed approach is suitable for applications that simultaneously require high throughput and resolution, such as wafer-wide integrated metrology, owing to its compact design, cost-effectiveness, and mechanical robustness.
Factors associated with thoughts of death and suicidal ideation owing to human relations, health, and financial problems in community-dwelling residents of a rural town in Japan
Authors: Morikawa Kozue , Nomura Kyoko , Onozawa Daisuke , Sasaki Hisanaga , Morikawa Yoshiki 
Published: October 2023

Abstract
Objective
To identify factors associated with thoughts of death and suicidal ideation among rural residents in Japan.
Methods
In 2015, a cross-sectional home visit survey was conducted in a rural town in Akita Prefecture. A total of 1,844 residents aged ≥ 20 years answered a questionnaire about thoughts of death and suicidal ideation in the past month. Multivariate logistic regression analyses were used to investigate socioenvironmental factors associated with suicidal ideation in models according to accompanying reasons for human relations problems (HRP), health problems (HP), and financial problems (FP).
Results
In total, 218 (men 9.4%, women 13.8%) had thoughts of death and suicidal ideation with accompanying reasons for HRP (5.6%), HP (6.1%), and FP (3.9%). The risk factors were Kessler Psychological Distress Scale scores ≥ 9 in models with HRP, HP, and FP or without no accompanying reasons; being a woman in models of HP and FP or without accompanying reasons; current smoking without accompanying reasons; absence of a person for help in a model of FP; absence of family member for help in a model of HRP or without accompanying reasons; and absence of social network and cohesion in a model of HRP. The mitigating factor were being optimistic in models of HRP, and HP or without accompanying reasons; being aged 70–79 in models of HRP and HP; and being aged ≥ 80 in a model of HRP.
Conclusions
Thoughts about death and suicidal ideation among rural residents in Japan were associated with multifactorial and socio-environmental factors.
Navigating the nuances: comparative analysis and hyperparameter optimisation of neural architectures on contrast-enhanced MRI for liver and liver tumour segmentation
Authors: Quinton Félix , Presles Benoît , Leclerc Sarah , Nodari Guillaume , Lopez Olivier , Chevallier Olivier , Pellegrinelli Julie , Vrigneaud Jean-Marc , Popoff Romain , Meriaudeau Fabrice , Alberini Jean-Louis 
Published: October 2023

Abstract
In medical imaging, accurate segmentation is crucial to improving diagnosis, treatment, or both. However, navigating the multitude of available architectures for automatic segmentation can be overwhelming, making it challengingto determine the appropriate type of architecture and tune the most crucial parameters during dataset optimisation.To address this problem, we examined and refined seven distinct architectures for segmenting the liver, as well as liver tumours, with a restricted training collection of 60 3D contrast-enhanced magnetic resonance images (CE-MRI) from the ATLAS dataset. Included in these architectures are convolutional neural networks (CNNs), transformers, and hybrid CNN/transformer architectures. Bayesian search techniques were used for hyperparameter tuning to hasten convergence to the optimal parameter mixes while also minimising the number of trained models. It was unexpected that hybrid models, which typically exhibit superior performance on larger datasets, would exhibit comparable performance to CNNs. The optimisation of parameters contributed to better segmentations, resulting in an average increase of 1.7% and 5.0% in liver and tumour segmentation Dice coefficients, respectively.In conclusion, the findings of this study indicate that hybrid CNN/transformer architectures may serve as a practical substitute for CNNs even in small datasets. This underscores the significance of hyperparameter optimisation.
A Systematic Solution for Social Media Usage of Students With the Help of Random Sampling Method
Authors: Senthamaraiselvi S. , Sundaram K. Meenakshi 
Published: October 2023

Abstract
Web-based entertainment assumes a gigantic part in human existence. Online entertainment use has developed quickly throughout recent many years. Because of its development, it is exceptionally famous for correspondence among understudies. Web-based entertainment enormously affects understudy accomplishment. This study investigates the subtleties of information assortment on the effect of virtual entertainment on understudy training. Scientists made a poll and gathered an example of data from understudies. This examination study was led among the understudies at the Vivekananda School for Womens and Excel College for Commerce and science at Namakkal. This concentrate momentarily portrays how the review survey was created and the information gathered.
Plant mycorrhizal functional type shapes nitrogen availability in a regenerating forest
Authors: Welker Les , Ward Elisabeth B. , Bradford Mark A. , Ferraro Kristy M. 
Published: October 2023

Abstract
Background and Aims
In closed-canopy, mature forests, tree and shrub mycorrhizal associations are important controls on soil nitrogen availability. Whether these plant-fungal effects are observed in forests at earlier successional stages following disturbances such as harvests or windstorms is largely unexplored. We quantify differences in soil nitrogen availability under an ectomycorrhizal tree (Betula lenta) and an ericoid mycorrhizal shrub (Kalmia latifolia) and explore the potential for known underlying mechanisms, such as the availability of soil carbon, to explain the patterns we observe.
Methods
We measure potential net nitrogen mineralization and nitrification rates, as well as variables associated with carbon availability, for incubated soil samples collected from under ecto- or ericoid mycorrhizal plants within a recently harvested temperate forest.
Results
Net nitrogen mineralization and nitrification rates were lower under the regenerating ericoid mycorrhizal shrub compared to the ectomycorrhizal tree. Yet, soil carbon availabilities were not different under these two plant functional types, suggesting that mechanisms other than carbon accumulation likely create nitrogen limitation under ericoid mycorrhizal plants in early successional forest stands.
Conclusion
Our findings suggest that local heterogeneity in the functional group diversity of plant mycorrhizal associations will be important for understanding differences in nitrogen availability in early versus mid- to late-successional forests and, resultingly, forest ecosystem responses to intensifying disturbance regimes.
Authentication of SSR Molecular Markers Associated with Genetic Male Sterility in Cotton (Gossypium hirsutum L.) Parental Lines
Authors: Patel Himalay R. , Patel D. H. 
Published: October 2023

Abstract

Background Genetic male sterility serves as a highly efficient approach for generating hybrid cotton. In India, successful hybrid cotton development has predominantly relied on the utilization of lines containing the ms5ms6 gene among various identified GMS gene-containing lines. In this current research, the validation of three GMS female lines, along with their fertile counterparts and the original non-GMS parental lines, was conducted using SSR markers with the primers BNL 1227 and NAU 2176.Methods At the Main Cotton Research Station, Athwa Farm, N.A.U, Surat, India, three GMS female genotypes, their corresponding fertile counterparts, and the original parental lines lacking GMS were employed for the validation of molecular markers associated with GMS in cotton. This validation process involved DNA extraction and subsequent PCR amplification.Results Our investigations yielded conclusive evidence regarding the presence of the sterility gene in GMS lines. This demonstrates the genetic purity of the genotypes, and it was observed that the selected primers effectively validated both GMS and their respective original parental groups. Consequently, the primers BNL 1227 and NAU 2176 provide a rapid and dependable method for identifying the genetic male sterility system controlled by the ms5ms6 gene in cotton (G. hirsutum L.). Moreover, they serve as an efficient alternative to the time-consuming and labor-intensive grow-out test (GOT) for cotton.
Transcriptome analysis and identification of the low potassium stress-responsive gene SiSnRK2.6 in foxtail millet (Setaria italica L.)
Authors: Xiaoqian Ma , Ma Xiaoqian , Khan Najeeb Ullah , Dai Shutao , Qin Na , Han Zanping , Guo Bing , Li Junxia 
Published: October 2023

Abstract
Foxtail millet (Setaria italica L.), which originated in China, has typical drought tolerance, barren tolerance, C4 high light efficiency, strong adaptability, and high nutrient utilization characteristics. Nevertheless, the molecular mechanism of its tolerance to low-potassium stress is largely unclear. In this research, the low potassium tolerant variety “Yugu28” was screened out by low potassium stress treatment, and the transcriptome of “Yugu28” under low potassium was comprehensively analyzed. A total of 4254 differentially expressed genes (DEGs) were identified, including 1618 up-regulated and 2636 down-regulated genes, respectively. In addition, there were 302 transcription factor (TF) genes in the DEGs and MYB TFs accounted for the highest proportion, which was 14.9%. After functional analysis of all DEGs, a total of 7 genes directly related to potassium and 50 genes corresponding to hormones were screened. The expression levels of randomly selected 17 DEGs were verified by qRT-PCR and the results coincided well with the RNA-seq analysis, indicating the reliability of our transcriptome data. Moreover, one of the ABA signaling pathway genes, SiSnRK2.6, was identified and selected for further functional verification. Compared with the wild-type, transgenic rice with ecotopic expression of SiSnRK2.6 showed remarkably increased root length and root number, indicating that overexpression of SiSnRK2.6 can enhance the resistance of transgenic plants to low potassium stress.
Perceptions of medical undergraduates toward online anatomy learning during the COVID-19 pandemic
Authors: Zang Ziqi , Li Xinyu , Zhao Yang , Shan Tao 
Published: October 2023

Abstract
Background
During the COVID-19 pandemic, almost all offline lectures and academic meetings were canceled, the 2020 spring semester was delayed, and students remained at home. Online education was widely employed in Chinese universities.
Methods
An online questionnaire was distributed to medical undergraduates. The questionnaire consists of 63 questions and involved students’ basic information, tools for online learning and students’ opinions about online learning and face-to-face learning.
Results
Until the end of this survey, none of our respondents were infected by COVID-19. The average score indicating respondents' preference for online courses was lower than face-to-face classes (6.24 vs. 8.12, p < 0.001). A total of 52.7% of respondents thought that online learning could reduce economic costs. Most of respondents (73.8%) agreed that online learning saved commuting time.
Conclusion
Online learning reduces the commuting time and economic costs. In online learning, lectures can be easily recorded and replayed. The most significant shortcomings include inability to refer to physical specimens, difficulty interacting with equipment or network failures, and a poor atmosphere. The COVID-19 pandemic has provided experience and lessons for online learning.
Application of Machine Learning and Resistivity Measurements for HighResolution 3D Geological Modeling in the Yilan Plain, Taiwan, at the SW Tip of the Okinawa Trough
Authors: Chang Ping-Yu , Puntu Jordi Mahardika , Lin Ding-Jiun , Amania Haiyina Hasbia , Chen Wen-Shan , Lin Andrew Tien-shun 
Published: October 2023

Abstract
This study presents a pioneering investigation into the complex Holocene paleomorphologies of the Yilan Plain, located at the southwestern edge of the Okinawa Trough. We employed a novel approach that synergized resistivity measurements with machine learning techniques to unlock valuable insights into the geological history, sedimentary patterns, and seismic activity of this dynamic region. Our methodology involved the creation of a high-resolution Apparent Geological Model (AGM) through the interpolation of inverted resistivity data and the application of supervised machine learning algorithms. Classification criteria, derived from the relationship between resistivity values and sediment types found in nearby boreholes, were developed using the random forest machine-learning method. The resultant 3D resistivity model was transformed into a clay-sand-gravel model, offering a comprehensive depiction of sediment distribution within the Yilan Plain. Notably, our findings revealed distinct sedimentary patterns. Gravel-dominated regions, characterized by resistivity values above 140 Ohm-m, were identified alongside areas dominated by sand and clay sediments. The Carbon-14 dating ages in the sand sediments exhibited remarkable consistency, shedding light on the depositional history of the region. Furthermore, our research unveiled a previously unknown phenomenon of rapid subsidence in the Yilan
Plain. Through meticulous analysis and correction for sea-level changes, we estimated an average subsidence rate of approximately 7.7 mm/year. This subsidence was punctuated by abrupt events around 8000-9000 years BP and 3000-3500 years BP, associated with a sudden 10-meter depth increase. These events suggested a potential link to prehistoric seismic activity, with variable subsidence rates between episodes hinting at recurrent active seismic periods every 4000-5000 years. In conclusion, our multidisciplinary approach has provided unprecedented insights into the Holocene paleo-morphologies of the Yilan Plain. By combining resistivity measurements, machine learning, and geological analysis, we have enriched our understanding of the region's geological history, sedimentary dynamics, and seismic behavior. These findings not only contribute to the knowledge of Yilan's past but also offer vital data for future environmental and geological studies in similarly dynamic regions.
A Case-Inspired Exploration of Renin Mutations in Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD): Not All Paths Lead to the ER.
Authors: Niedbalska-Tarnowska Joanna , Jakubowska Anna , Majkowski Michał , Pęcherz Michalina , Medyńska Anna , Mroczek Robert , Kiliś-Pstrusińska Katarzyna , Cebrat Małgorzata , Łaszkiewicz Agnieszka 
Published: October 2023

Abstract
Background:
Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD) results from mutations in various genes, including REN, UMOD, MUC1, and HNF1B. ADTKD-REN is often characterized as a proteinopathy that triggers the endoplasmic reticulum stress (ERS) cascade, potentially sharing similarities with ADTKD-UMOD and ADTKD-MUC1 at the cellular level. Inspired by a patient with a W17R mutation, we aimed to investigate ERS activation caused by this and two other renin variants (W10R and L381P). Additionally, we explored potential molecular commonalities with other TKD forms, specifically ADTKD-HNF1B and MITKD (Mitochondrially Inherited Tubulointerstitial Kidney Disease).
Methods:
We established stable cell lines expressing wild-type renin and its mutated forms: W17R, W10R, and L381P. Using luciferase reporter constructs, RT-qPCR, and confocal imaging, we conducted tests to evaluate ERS activation, TGFβ upregulation, and the cellular localization of various renin variants.
Results:
The L381P line exhibited signs of ERS activation and transcriptional upregulation of MANF (mesencephalic astrocyte-derived neurotrophic factor) and CRELD2 (cysteine-rich with EGF-like domains 2). ERS activation was not observed in the W17R line, while the W10R line displayed intermediate features. None of the lines upregulated TGFβ. Importantly, the W17R variant was misdirected to the mitochondria.
Conclusion:
Individuals with the L381P mutation may benefit from research on ADTKD-UMOD and ADTKD-MUC1 treatments. The pathogenic mechanism of the W17R mutation involves mitochondria rather than the ER pathway, thus may potentially overlap with MITKD. We propose testing CRELD2 and MANF as markers to target therapies for a specific subgroup of ADTKD-REN patients.
Applying Deep Learning for automated visual verification of manual bracket installations
Authors: Quantrill Liam , Oyekan John , Turner Christopher , Tiwari Ashutosh 
Published: October 2023

Abstract

In this work, we explore a deep learning based automated visual inspection and verification algorithm, based on the Siamese Neural Network architecture. This is explored alongside the typical Convolutional Neural Network. Consideration is also given to how the input pairs of images can affect the performance of the Siamese Neural Network, dependent on the nature of the dataset used. A case study is provided from the aircraft manufacturing industry focusing on the visual inspection of wing bracket installations. A novel voting scheme specific to the Siamese Neural Network which sees a single model vote on multiple reference images is validated in this work. The results obtained show great potential for the use of the Siamese Neural Network for automated visual inspection and verification tasks in aircraft manufacturing and similar industries where there is often a scarcity of training data available.
Alfalfa perimeter strips reduce Lygus lineolaris populations in June-bearing strawberry fields
Authors: Hetherington Matthew C. , Fox Matthew , Johnson Megan , Lopina Allison , Mechelke Emma , Weissner Morgan , Guédot Christelle 
Published: October 2023

Abstract
Lygus lineolaris Palisot de Beauvois (Hemiptera: Miridae) is the primary insect pest of strawberry in eastern and central North America. Strategies to minimize L. lineolaris colonization of strawberry at bloom and peak fruit susceptibility without impacting pollinator health must be developed. To this end, we examined the potential of alfalfa perimeter strips to reduce L. lineolaris populations in June-bearing strawberry fields. Over a three-year experiment, L. lineolaris densities and beneficial arthropod abundance were monitored on three commercial strawberry farms where alfalfa was established as a trap crop near strawberry plots. Alfalfa perimeter strips were found to concentrate L. lineolaris populations and led to a 36% reduction in L. lineolaris densities in adjacent strawberry plots compared to controls. When a protein immunomark-capture experiment was conducted to examine the extent of movement between the alfalfa strips and adjacent strawberry plots, it was determined that approximately three times as many L. lineolaris migrated from strawberry to alfalfa than vice versa. Moreover, adult females were overrepresented among immigrants to alfalfa, suggesting that alfalfa may be a preferred oviposition site for L. lineolaris. While the presence of alfalfa perimeter strips increased beneficial arthropod abundance and diversity in experimental plots overall, most effects were limited to the alfalfa strip itself, with little spillover into adjacent strawberry plots. These data suggest that preferential utilization of alfalfa by L. lineolaris underlies the observed population reductions and that alfalfa perimeter strips act as a trap crop in June-bearing strawberries.
Nomograms for Predicting Overall and Progression-Free Survival in Patients with Surgical Lip Squamous Cell Carcinoma
Authors: Saad Hassan A. , Baz Azza , Riad Mohamed , Eraky Mohamed E , El-Taher Ahmed k , Farid Mohamed I , Sharaf Khaled , Said Huda E. M. 
Published: October 2023

Abstract
Context
Receiving a personalized forecast for lip squamous cell carcinoma (LSCC) is crucial. This study aimed to develop predictive models for postoperative prognosis prediction in LSCC patients.
Methods
Two medical institutes provided 136 postoperative LSCC patients diagnosed between April 2015 and July 2022. The patients were randomly assigned to training and validation groups at a 7:3 ratio. Based on the results of univariate and multivariate Cox regression analyses, two nomograms were made to predict overall survival (OS) and progression-free survival (PFS) in LSCC patients who had surgery.
Results
According to univariate and multivariate Cox regression analyses, a lower pathological grade, being older than 70 years, having a higher T-stage, positive lymph node metastasis (LNM), perineural invasion (PNI), vascular invasion (VI), and positive surgical margin were all independent predictors of a lower OS. The independent predictors of worse PFS included higher pathological grade, age ≥ 70 years, higher T-stage, LNM, PNI, and positive surgical margins. Two nomograms were created based on the data above to forecast the 3- and 5-year OS and PFS rates in patients with LSCC. In the training group, the C-indices for the OS and PFS nomograms were 0.865 and 0.801, respectively, whereas those in the validation group were 0.915 and 0.815, respectively. The calibration curves demonstrated a reasonable degree of agreement between the observed survival rates and the predictions.
Conclusions
Curve analysis revealed superior performance of the nomogram compared to other related predictors. Kaplan-Meier curves showed statistical distinctions between the high-, medium-, and low-risk groups. In summary, With a good clinically personalized applicability value, this retrospective study developed and validated two nomograms for predicting OS and PFS in patients with postoperative LSCC.