bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification of n × (n − 1) Incidence Matrices of Gracefully Labeled Simple Graphs
Authors: Dagal Keneth Adrian , Hugo Kristoffer Karan 
Published: January 2024

Abstract

This paper presents the distribution of simple graphs with $n$ vertices and $n-1$ edges that admit graceful labeling. This is achieved through a classification table, which considers the graph's diameter (or longest cycle) and the number of isolated vertices. We determine the degree sequences by utilizing the incidence matrices of the labeled graphs mentioned above and subsequently arrange the collection on this classification table. Using the table, we investigate the impact of degree sequences on the diameter (or the longest cycle) value and the existence of isolated vertices.
Disposal of grass clippings from sports turfs - effect of fertilization on gaseous emissions and pollution in leachate
Authors: Sobol Łukasz , Koziel Jacek A. , Stegenta-Dąbrowska Sylwia 
Published: January 2024

Abstract
Abstract:
Mowing sports turfs and grass surfaces generates waste biomass in the form of grass clippings. Biomass composting is commonly practiced generating nutrient-rich soil amendments. However, decomposing biomass can have adverse environmental effects such as gaseous emissions and nutrient leaching. This research investigated: (1) the kinetics of CO, CO2, and O2 emissions during the decomposition of grass clippings, (2) the leaching potential of organic and nitrogen compounds in the initially decomposed grass clippings. Grass clippings from the mowing of four football fields with different levels of nitrogen fertilization and agrotechnical treatments were studied over three periods characteristic of the league season. The results showed that grass clippings from sports turfs can generate up to 5 times more CO emissions compared to previous research. CO2 production and O2 consumption were relatively similar for all seasons, except for clippings from the unfertilized pitch. No significant differences in gaseous emissions were observed between variants with different levels of nitrogen fertilization and season, which can probably be explained by using turf pesticides, widely known as substances that strongly affect microbes growing in the soil. Clippings from low-fertilized or non-fertilized grass were more likely to have a higher leachability potential. Results confirm that the proper timing of fertilization and irrigation during the growing season can limit and control leaching from grass clippings.
Horto-Taxonomical studies on Bougainvillea: Pollen grain characters
Authors: Datta Subodh Kumar , Datta Kalyani 
Published: January 2024

Abstract

Horto-taxonomical characterization of Bougainvillea is most important for the correct identification of cultivars and Plant Variety Rights (PVR). Different parameters have already been standardized for characterization. In Bougainvillea, there is always the development of new and novel varieties through classical breeding, sports, selection, and induced mutagenesis. The new varieties differ from the original variety mostly in one promising character for commercial utilization. All these factors have led to a lot of confusion in the identification of these cultivars. Many times the same cultivar has been differently named at different places and in some cases even the same name has been given to cultivars of different origins. This study aims to verify the taxonomic usefulness of the pollen grain morphological characters at a variety level. 83 cultivars were selected and pollen morphological characters were investigated and found a wide range of variations in pollen grain ornamentations at the variety level. The structural diversity in pollen structure within the varieties is recommended as an important tool in addition to other techniques for the identification and classification of the varieties.
GLAE: Global-local Feature Autoencoder for Image Logical Anomaly Detection
Authors: Peng jianjie , Ye Junyong , Zhuang Jiafeng , Li Yuan , Zhang Hubin 
Published: January 2024

Abstract

Self-supervised anomaly detection in industrial images holds significant practical value. While existing anomaly detection models excel in numerous public benchmarks, their substantial computational complexity and inability to detect logical anomalies hinder their widespread practical application. To address this issue, we proposes a global-local feature autoencoder (GLAE) for anomaly detection, which can be seamlessly integrated into the lightweight student-teacher (S-T) framework in parallel. GLAE uses a novel global feature extractor as the encoder (GFencoder), comprising solely of simple convolutions. This significantly reduces the computational cost while effectively capturing the global semantic information of the image, enabling the completion of global-local information reconstruction for the image. During the training stage, the student and GLAE were exclusively trained on normal samples, and they were unable to accurately capture the local or global features of abnormal samples during testing. By computing the feature distance between the teacher, student, and autoencoder, the local and global anomalies of the image were determined. We evaluated our method using three industrial anomaly detection dataset collections, and GLAE demonstrated state-of-the-art (SOTA) performance in image-level logical anomaly detection, efficiently handling anomalies with less than 7 ms latency on an NVIDIA RTX 3090 GPU. This establishes it as a cost-effective solution applicable in industrial scenarios, and it introduces a new approach for utilizing convolution to extract global features from images.
A New Dataset for Video-based Cow Behavior Recognition
Authors: Li Kuo , Fan Daoerji , Wu Huijuan , Zhao Aruna 
Published: January 2024

Abstract

A new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper.The dataset consists of ranch monitoring footage collected by 7 cameras, including 687 video segment samples and 206100 image samples, covering five daily behaviors of cows. These behaviors were selected because of the need for ranch farming. The video collection is completed by a fixed camera installed by oneself, ensuring that the monitoring coverage of the ranch is not affected by blind spots.The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model.The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28\% on the test set. The dataset will be made freely available to researchers world-wide. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.
Unveiling the Adaptive Reading Strategy Framework: A Grounded Theory Exploration
Authors: Wudneh Asalefew , Woemego Elias 
Published: January 2024

Abstract

This study utilized a Grounded Theory approach to explore reading strategies employed by EFL participants in various reading tasks. The research design involved the use of reading tasks, think-aloud protocols, and note-taking as data sources. The collected data underwent rigorous coding procedures, leading to the iterative data analysis process. Through this analysis, the study generated the "Adaptive Reading Strategy Framework," which encompasses strategies aimed at enhancing reading efficiency, metacognitive awareness, comprehension, and strategic reading. The framework emphasizes the deliberate selection and adaptation of specific techniques based on individual strengths and weaknesses. The research findings shed light on the intentional utilization of reading strategies and their impact on cognitive flexibility. By actively engaging in metacognitive processes and employing diverse reading strategies, learners can optimize their reading outcomes across different contexts. The Adaptive Reading Strategy Framework contributes to the understanding of effective reading practices and provides guidance for educators and learners seeking to improve reading proficiency.
METTL3 Deficiency Aggravates Hepatic Ischemia/Reperfusion Injury in Mice by Activating the MAPK Signaling Pathway
Authors: Gao yang , Wang Min , Qin Renyi , Zhao Chunle , Gong Jun 
Published: January 2024

Abstract

Inflammatory responses, apoptosis, and oxidative stress, are key factors that contribute to hepatic ischemia/reperfusion (I/R) injury, which may lead to the failure of liver surgeries, such as hepatectomy and liver transplantation. The N6-methyladenosine (m6A) modification has been implicated in multiple biological processes, and its specific role and mechanism in hepatic I/R injury require further investigation. This study focused on the role of RNA methylase METTL3 in hepatic ischemia-reperfusion injury. Dot blotting analysis was used to profile m6A levels in liver tissues at different reperfusion time points in hepatic I/R mouse models. Hepatocyte-specific METTL3 knockdown (HKD) mice were used to determine the function of METTL3 during hepatic I/R. RNA sequencing and western blotting were performed to assess the potential signaling pathways involved with the deficiency of METTL3. Finally, AAV8-TBG-METTL3 was injected through the tail vein to further elucidate the role of METTL3 in hepatic I/R injury. We found that the m6A modification levels and the expression of METTL3 were upregulated in mouse livers during hepatic I/R injury. METTL3 deficiency led to an exacerbated inflammatory response and increased cell death during hepatic I/R, whereas overexpression of METTL3 reduced the extent of liver injury. Bioinformatic analysis revealed that the MAPK pathway was significantly enriched in the livers of METTL3-deficient mice. METTL3 protected the liver from I/R injury, possibly by inhibiting the phosphorylation of JNK and ERK, but not P38.
The Credit Card Debt Puzzle: New Facts and Theory
Authors: Aubyn Carolyn St 
Published: January 2024

Abstract

Simultaneously holding liquid assets and credit card debt is known as the credit card debt, or co-holding, puzzle. Around 45% of households in the US Panel Study of Income Dynamics (2010-2014) fall into this category. I revisit the puzzle from the perspective of the degree of co-holding and show around 40% of co-holders hold between 2 and 200 times more liquid assets than credit card debt. This new fact has implications for co-holding explanations based on liquidity. I propose an alternative explanation in which consumers value money and thus dislike making payments. This explanation has applications to a range of consumer choices, such as Buy Now Pay Later and the credit card premium.
JEL Classifications: D11, D12, D14, G51
Decision Procedure for Temporal Logic Using Cyclic Sequent Calculi
Authors: Alonderis R. , e A. Pliuškevičien˙ , Giedra H. 
Published: January 2024

Abstract
In this paper we continue our earlier investigation into backward proof-search of se-quents of propositional linear discrete tense logic with the unary temporal operators using loop-type sequent calculi. The present paper deals with loop checking in backward proof-search. Backward proof-search is inefficient if loop checks are performed every time a next sequent is obtained. We show that loop checks can be restricted to certain paths of backward proof-search trees, or sometimes omitted altogether. Moreover, some more efficient techniques can be used instead of a comparison of sequents in loop checking. For example, we show that an occurrence of a sequent of a certain form or a rule application in a path in a backward proof-search tree indicates that there are no derivation loops in this path. Also an occurrence of a formula of certain type in the terminal sequent of a derivation loop allows us to determine the type of this derivation loop, no further examination of the loop is needed. In general, we consider techniques that allow us to reduce global condition checks during backward proof-search. Using results obtained in the present paper and in our earlier works, we give a rather detailed description of a decision procedure for sequents of the logic under consideration.
Application of Convolutional Neural Networks for Windthrow and Windbreak Timber Volume Estimation in the Stare Jabłonki Forest District
Authors: Mielczarek Dominik , Najman Krzysztof 
Published: January 2024

Abstract

Over the past decade, the number of recorded tornadoes in Poland has been increasing. Catastrophic phenomena are becoming cyclical in nature. The rising incidence of extreme weather events is believed to be attributable to climate change. Hurricane damage poses challenges for forest managers, as uprooted trees block forest access roads, while unlocalized ones lose their industrial usefulness. Prompt acquisition of information on the scale of damage facilitates precise planning of hurricane recovery work. The aim of the study entails an attempt to estimate the volume of timber, based on selected artificial intelligence methods. The topic of harvested timber volume estimation has been inspired by the growing number of hurricane disasters in Poland. The study propounds a method based on a UAV campaign of aerial imaging, involving the use of post-wind damage data. Owing to its low complexity, the proposed method allows for prompt delivery of a complete set of information.
Augmenting Heat Transfer of Shell and Tube Heat Exchanger – A Cfd Analysis Approach
Authors: Duraisamy Jagadeesh , Mahendaran Vivekanandan , Nallasivam Kawin 
Published: January 2024

Abstract
A shell and tube heat exchanger journal that has undergone experimental analysis is used as a guide. There are four different segmental baffle layouts employed in the referred journal. The four types of baffle layouts are flower segmental baffle (FSB), hybrid segmental baffle (HSB), staggered single segmental baffle (SSSB), and conventional single segmental baffle (CSSB). STHX using CSSB by itself was examined in this paper. Since heat transmission is the foundation for the shell and tube heat exchanger's (STHX) performance. We added twisted tape inside the tube and used helical baffles in place of the traditional baffles to improve it. In this research, four varieties of STHX have been constructed and simulated. The STHX with helical baffle, STHX with helical baffle and twisted tape, and STHX with CSSB and twisted tape are the four variants. For the chosen shell and tube heat exchanger, theoretical calculations are performed, and the outcomes are compared with the experimental journal. The STHX was created and simulated in the HTRI Xchanger suite using the theoretically derived value. The STHXs are created and put together in SolidWorks, and then the file is exported to FLO EFD for CFD analysis.Four STHX configurations' simulation results were compared, and it was found that the new configurations—STHX with helical baffle, STHX with twisted tape, and STHX with CSSB and twisted tape—had a noticeably better heat transfer enhancement. For every test situation, STHX with a helical baffle and twisted tape arrangement had a greater impact on improving heat exchanger performance than the other configurations.
Genome wide identification of bromelain-like cysteine proteases in Puya raimondii
Authors: Castro-Cabrera Inelvis , Torre Martha Hernádez de la , Chandía Daniela Romero , Leone Jorge Dagnino , Reyes Marta Fernández 
Published: January 2024

Abstract

Bromelains are cysteine proteases of the papain family (C1A subfamily). These enzymes are of great commercial value due to their applications in the food, pharmaceutical and biotechnological industries. In plants, they play an important role in multiple physiological processes from germination to senescence, mainly in the defense of plants against biotic and abiotic stresses. In this study, we used available data from the P. raimondii genome (Bioproject PRJNA639677) to identify genes encoding bromelain-type proteases. Six bromelain-like nucleotide sequences are postulated in P. raimondii draft genome. Hormone, stress and light responsive elements in the PrBLCPs sequences were detected. The theoretical molecular weights of the proteins putatives PrBLCPs in P. raimondii range from 36643.21-45761.20 Da and theoretical isoelectric point 5.05 to 8.63. Multiple primary sequence alignments and structural model prediction demonstrate that P. raimondii putative proteases are very similar to A. comosus fruit bromelain (O23791) recognized in the SwissProt/Uniprot database. Phylogenetic relationships between the bromelain-like putative cysteine proteases of P. raimondii and the bromelain proteases of A. comosus placed the PrBLCPs in two subclades, although with very short phylogenetic distances between them. The results of this study provide valuable information for future genomic studies of bromelain family genes in the genus Puya. In addition, it aids in the understanding of the regulatory mechanisms of these proteases and their roles in plant stress tolerance.
Medical Record Level-Evaluation of Impact of Demographic and Socioeconomic Factors on Pediatric Neuro-Oncology Outcomes at Children's Hospital Colorado
Authors: Pool Alexandra , Kuna Elizabeth Molina , Anderson-Mellies Amy , Kreis Alexandra , Marable Marcus , Fraley Claire , Pacheco Daniel , Green Adam L. 
Published: January 2024

Abstract

Purpose
A medical record-level cohort study to investigate demographic and socioeconomic factors influencing treatment, timing of care, and survival outcomes in pediatric patients diagnosed with central nervous system (CNS) tumors.
Methods
Using electronic health records of patients at Children's Hospital Colorado from 1986–2020, we identified 898 patients treated for CNS tumors. The primary outcomes of interest were 5-year survival, timing of diagnosis, and treatment. Multivariable logistic regression and Cox regression were used to identify covariates associated with our outcomes of interest.
Results
We found that age, race, tumor type, diagnosis year, and social concerns influenced receipt and timing of treatment. Age, race, patient rural vs. urban residence, and tumor impacted survival outcomes. Time to presentation and treatment were significantly different between White and minority patients. American Indian/Alaska Native and Black patients were less likely to receive chemo compared to White patients (OR 0.28, 0.93 p = 0.037, < 0.001). Patients with 3 + social concerns were more likely to survive after 5 years than children with no or unknown social concerns (OR 1.84, p = 0.011). However, with an adjusted hazards ratio, children with 2 social concerns were less likely to survive to 5 years than children with no or unknown concerns (OR 0.58, p = 0.066).
Conclusions
Demographic and socioeconomic factors influence timing of care and survival outcomes in pediatric patients with CNS tumors. Minority status, age, social factors, rural, and urban patients experience differences in care. This emphasizes the importance of considering these factors and addressing disparities to achieve equitable care.
Secure Quantum Circuit Compilation Methodology for Untrusted Compilers
Authors: Das Subrata , Ghosh Swaroop 
Published: January 2024

Abstract

The success of quantum circuits in providing reliable outcomes for a given problem depends on the gate count and depth in near-term noisy quantum computers. A circuit (that implements a given function) with a low gate count and short depth is more likely to give a correct solution than the circuit variant with a higher gate count and depth. As such, quantum circuit compilers that decompose high-level gates to native gates of the hardware and optimize the circuit play a key role in quantum computing. However, the quality and time complexity of the optimization process can vary significantly especially for practically relevant large-scale quantum circuits. As a result, third-party (often less-trusted/untrusted/unreliable) compilers have emerged, claiming to provide better and faster optimization of complex quantum circuits than so-called trusted compilers. However, untrusted compilers, with their varying adversarial motives ranging from semi-honest to malicious can pose severe security risks such as the theft of sensitive intellectual property (IP) embedded within the quantum circuit. We propose an obfuscation technique for quantum circuits using randomized reversible gates to protect them from such attacks during compilation. The idea is to insert a small random circuit into the original circuit and send it to the untrusted compiler. Since the circuit function is corrupted, the adversary (i.e., an untrusted compiler) may get incorrect IP. However, the user may also get incorrect output post-compilation (even though highly optimized). To circumvent this issue, we concatenate the inverse of the random circuit in the compiled circuit to recover the original functionality. We demonstrate the practicality of our method by conducting exhaustive experiments on a set of benchmark circuits and measuring the quality of obfuscation by calculating the Total Variation Distance (TVD) and Degree of Functional Corruption (DFC) metrics. Our method achieves TVD of up to 1.92, indicating substantial functional corruption, and performs at least 2x better than a previously reported obfuscation method. We also attained a DFC as low as -0.75, approaching the -1 score that represents maximal functional corruption, further ensuring the robustness of our proposed method against IP theft. We also propose a novel adversarial reverse engineering (RE) approach to extract the IP and show that the proposed obfuscation is resilient against RE attacks. The proposed technique introduces minimal degradation in fidelity ( ~ 1% to ~ 3% on average).
Application of Light Image Enhancement Based on Multimode Image Fusion in Sculpture Virtual Design Visualization System
Authors: Zhang Rongxue , Wang Hongjiang 
Published: January 2024

Abstract

In the field of virtual sculpture design, although there are some 3D production software with free form functions, their operation methods differ greatly from the habits of professional sculptors. Therefore, this article proposes a sculpture virtual design visualization system based on multimodal image fusion to address the limitations of traditional sculpture design methods, improve design efficiency and quality. This article collects multimodal image data of real sculptures, analyzes and processes these data using computer vision and image processing techniques, and extracts key features. Using image fusion technology to fuse multiple image features into a comprehensive design image. Finally, the design images are presented to designers and users through virtual reality technology, achieving visualization of sculpture design. Through experimental verification, this system can effectively fuse multimodal images and generate realistic and detailed sculpture design images. The system also provides an interactive operation interface, allowing designers and users to freely manipulate and observe sculpture design through the controller, providing designers and users with a more intuitive and comprehensive visual experience.