bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Monitoring of Tool Wear and Quality Control of Roughness with Roundness in CNC Turning
Authors: Tangjitsitcharoen Somkiat 
Published: August 2024

Abstract

This paper integrates an in-process monitoring of tool wear with a quality control of roughness and roundness of machined parts in CNC turning, which are the critical parameters. The Daubechies wavelet transform has been applied to decompose the dynamic cutting forces in order to classify the signals of the tool wear, the average surface roughness, the surface roughness, and the roundness. The decomposed cutting forces are normalized to predict those parameters regardless of cutting conditions by taking the ratio of decomposed cutting forces. Firstly, the ratio of average variance of decomposed feed force to that of decomposed main force is proposed to estimate the tool wear. Secondly, the areas of those decomposed feed force and decomposed main force have been proposed and taken into the ratio to forecast the average surface roughness and the surface roughness concurrently. Lastly, the roundness error is calculated simultaneously by utilizing the ratio of average variance of decomposed redial force to that of decomposed feed force. The exponential function is adopted to represent the relations of the tool wear, the average surface roughness, the surface roughness, the roundness, and all proposed ratios of decomposed cutting forces, respectively. The new cutting tests are conducted to verify all obtained models. The experimentally obtained results showed that the tool wear declines as the ratio of average variance of decomposed feed force to that of decomposed main force increases. The average surface roughness and the surface roughness tend to decrease while the ratio of decomposed feed force to decomposed main force progresses. On the other hand, the roundness error becomes larger when the ratio of average variance of decomposed redial force to that of decomposed feed force escalates. It is concluded that the tool wear, the average surface roughness, the surface roughness, and the roundness can be monitored and controlled at the same time during the in-process CNC turning, which has never been done and developed before. The highest benefit of the proposed system can enhance the quality of machined parts and lead to the higher productivity.
Contrasting Tracheal, Bronchus, and Lung Cancer Burdens and Care Quality: A Comparative Analysis of China and Global Trends
Authors: Lin Xiuquan , Liu Shiwen , Ding Yating , Zhao Jianhui , He Fei , Zhong Wenling 
Published: August 2024

Abstract

Background
This study aims to explore the temporal trends of tracheal, bronchus, and lung cancer burden in Fujian Province, China, and globally. Additionally, changes in attributable risk factors and the quality of care were evaluated.
Methods
Based on data from the Fujian Provincial Center for Disease Control and Prevention and the Global Burden of Disease (GBD), the age-standardized rates (ASRs) of incidence, death, and disability-adjusted life years (DALY) were collected and analyzed. Joinpoint regression analysis and age-period-cohort models were used to estimate temporal trends, and principal component analysis is used to estimate the quality-of-care index (QCI).
Results
In 2019, the ASRs of incidence, death, and DALYs in 2019 were 39.08, 35.29, and 778.39 per 100,000 in Fujian Province, respectively. From 1990 to 2019, ASRs increased, with average annual percent changes (AAPCs) of 1.08 (95% confidence interval [CI]: 0.77 to 1.38), 0.65 (95% CI: 0.35 to 0.95), and 0.18 (95% CI: -0.07 to 0.42), respectively. When analyzed age, the burden sharply increased after age 50. By gender, the ASRs of male incidence, death, and DALY in Fujian Province were all over 3-folds higher than in females. However, females burden showed increasing trend from 2015 to 2019. While DALY ASRs attributed to ambient particulate matter pollution increased significantly, solid fuels in households decreased compared to 1990. Moreover, we founded that QCI increased with age. The temporal trends indicated decrease in QCI from 1990 to 2019.
Conclusion
The burden of tracheal, bronchus, and lung cancer in Fujian Province remained significant. Smoking, secondhand smoke, and ambient particulate matter pollution were the main risk factors. The quality of care for patients needed improvement.
Association of platelet count with 28-day mortality in medical-surgical ICU patients with sepsis: a multicenter retrospective cohort study
Authors: Ma Yue-Lian , Chen Xiong , He Hai-Yang 
Published: August 2024

Abstract

Background
The association between platelet count and 28-day mortality in medical-surgical intensive care unit (ICU) patients with sepsis remains inconclusive. The aim of this study was to investigate whether platelet count is associated with 28-day mortality in these patients.
Methods
This retrospective cohort study extracted 6,122 adult patients with sepsis in medical-surgical ICU from the eICU Collaborative Research Database (eICU-CRD). The logistic regression models were used to estimate the covariates and investigate the relatioshiop between platelet count and 28-day mortality rate. Then, a generalized additive model (GAM) was used to investigate the dose-response relationship between the platelet count (every 10-unit change in platelet count) and 28-day mortality rate. Moreover, a two-piece-wise linear regression model was applied to assess the threshold effect of the platelet count and 28-day mortality rate.
Results
After adjustment for the covariates, the platelet count had a nonlinear relationship with 28-day mortality (P < 0.001). On the left side of the inflection point (platelet count < 127 x10ˆ9/L), an increase of 10 in the platelet count was associated with a 10% decreased risk 0f 28-day mortality rate (OR = 0.90, 95% CI = 0.87–0.93, P < 0.001). Nevertheless, when the platelet count ≥ 127 x10ˆ9/L, every 10-unit increase in platelet count was not significantly associated with 28-day mortality rate.
Conclusion
The relationship between platelet count and 28-day mortality rate in medical-surgical ICU patients with sepsis was nonlinear. This indicates that low platelet count may receive attention in medical-surgical ICU patients with sepsis.
Safety and efficacy of pemetrexed for patients with non-small cell lung cancer in the setting of renal impairment: a retrospective study
Authors: Shima Yusuke , Yoshida Hironori , Suminaga Keiichiro , Yoshida Hiroshi , Hashimoto Kentaro , Ogimoto Tatsuya , Hosoya Kazutaka , Ajimizu Hitomi , Funazo Tomoko , Nomizo Takashi , Ozasa Hiroaki , Hirai Toyohiro 
Published: August 2024

Abstract

Background
Pemetrexed is a key treatment for non-small-cell lung cancer (NSCLC), with its usage on the rise. However, due to treatment-related fatality in a patient with severe renal impairment observed during an initial clinical trial, such patients have been excluded from further studies. Consequently, there is limited data on the safety and efficacy of pemetrexed for these patients. This study aims to assess the use of pemetrexed in this patient group within a clinical setting.
Methods
We conducted a retrospective analysis of lung cancer patients treated with pemetrexed at Kyoto University Hospital from April 2008 to April 2023. Patients were categorized into groups receiving pemetrexed with platinum (n = 349) and pemetrexed-alone (n = 142) groups. Both groups were subdivided into creatinine clearance (CCr) > 45 and ≤ 45 subgroups, and safety and efficacy were compared between the subgroups. The chi-squared test was used to evaluate the correlation between renal impairment and adverse events. Univariate and logistic regression analyses identified independent risk factors for severe adverse events (SAEs) related to renal impairment. We also analyzed progression-free survival (PFS) and overall survival (OS) using log-rank tests.
Results
A significant increase in the incidence of grade ≥ 3 anemia was observed in the CCr ≤ 45 subgroups of both the platinum-concomitant and the pemetrexed-alone groups (p = 0.03 and p < 0.01, respectively). No significant differences were noted for other SAEs. Multivariate analysis showed that baseline hemoglobin levels were an independent predictor of grade ≥ 3 anemia across both treatment groups, alongside a baseline CCr ≤ 45 mL/min in the pemetrexed-alone group. No significant differences were observed in overall response rates, PFS, or OS between the CCr > 45 and CCr ≤ 45 subgroups in either treatment group.
Conclusions
While severe anemia was more common in patients with renal impairment, the efficacy of treatment did not differ, indicating that pemetrexed remains a viable treatment option for this population with proper management.
Evaluation of Drought Tolerance of Rice Landraces in Mid-Hills of Nepal Using Drought Tolerant Indices
Authors: Shrestha Prabin , Kandel Bishnu Prasad , Dhakal Merina , Karanjit Ritika , Shrestha Prajwal , Poudel Ankur 
Published: August 2024

Abstract

Drought is a critical abiotic stress that affects rice yield. There is typically a limited and irregular pattern of rainfall in mid-hill regions, which leads to drought conditions that significantly impact rice production. Therefore, our study aimed to identify the best-performing landraces of rice and determine suitable drought indices. For these, 17 different rice landraces grown in the mid-hills were selected. A two-factorial (genotype and moisture stress) completely randomized design with two replications was carried out at the Lamjung Campus in the spring of 2023. Drought stress resulted in a wide range of yield reductions, from 10–69%. Our findings revealed significant differences in the agro morphological traits of rice. A strong and positive correlation was found between grain yield and drought indices, tolerance indices (TOLs), mean productivity indices (MPs), geometric mean productivity (GMP), harmonic means (HMs), yield indices (YIs), and stress tolerance indices (STIs) under various drought stress conditions. Among these indices, the Juhari landrace performed well in terms of MP, GMP, STI, HM, and YI. Principal component analysis (PCA) clustered drought indices into two groups (PC1 and PC2). Of these, PC2 was found to be better because of its high yield potential. Further screening using the ranking method and cluster analysis identified Juhari, Kathe, Manamure, and Pahele as high-quality drought-tolerant genotypes. Based on our findings, we recommend cultivating Juhari in drought-prone regions within the mid-hill region. In conclusion, our study highlights the importance of indices such as the MPI, STI, GMP, HM, and YI as important instruments for drought screening. Our study highlighted the importance of choosing suitable drought-tolerant landraces that exhibit improved yield and stability under adverse conditions.
Prompting large language models to extract chemical‒disease relation precisely and comprehensively at the document level
Authors: Chen Mei , Zhang Tingting , Wang Shibin 
Published: August 2024

Abstract

Currently, the intricate relationships between chemicals and diseases have increasingly been revealed and documented in many academic studies. However, constrained by the scarcity of high-quality annotated data, document-level relation extraction techniques based on deep learning are plagued by ambiguity and one-sidedness, severely impeding further automatic in-depth analysis of these relationships. In this study, we harness the advanced reading comprehension capabilities and extensive world knowledge of LLMs to innovatively construct precise and comprehensive zero-shot prompt workflows for extracting chemical‒disease relationships on the basis of the patterns of LLM-based relation extraction, the attributes of chemical‒disease relationships, and the linguistic features of biomedical literature. Evaluations of the enhanced chemical‒disease relation (CDR) datasets demonstrate that the F1 scores for the workflows in precise extraction can reach 87% and can reach 73% for comprehensive extraction. Additionally, we investigate the pivotal factors that influence LLMs' ability to extract complex relations, offering crucial insights for relation extraction across diverse fields.
A novel approach to the comprehensive evaluation of geology- engineering dual sweet spots in tight gas reservoirs in the LX area of China
Authors: Liu Yi , Liu Shanyong , Lou Yishan , Yin Biao , Zhang Yan 
Published: August 2024

Abstract

The LX tight gas reservoir displays significant heterogeneity, with a lack of alignment between engineering treatment and geological evaluation, leading to an unsatisfactory development outcome. Focusing on the Shihezi Formation of LX, a new comprehensive evaluation method is proposed for identifying sweet spots, taking into consideration both geological and engineering factors. The objective function utilized is post-frac production, and the grey correlation method was employed to quantitatively characterize the weight coefficients of geological and engineering parameters. The dual sweet spots index F was obtained through a normalized process. Utilizing the Petrel integrated exploration and development platform, the dual sweet spots index was incorporated into the geological model using coarse-interpolation. Subsequently, a dual sweet spots evaluation model was established to enhance the overall assessment process. The findings indicate the following: (1) There is a strong correlation between open flow production and the F-value, and the model's predicted value closely aligns with the actual value. (2) A section with an F-value greater than 0.5 is identified as the optimal sweet spot, prioritizing development in this area. Sections with F-values within the range of 0.3 to 0.5 may be considered for fracturing but are not the primary choice. Sections with an F-value below 0.3 are deemed inefficient areas. (3) Based on the dual sweet spots evaluation model, it is recommended to focus on single layers He2, He5, and He6 in the LX area due to their superior quality compared to other layers. The research results offer crucial technical support for assessing fracability in this region, and hold significant importance for the selection of fracturing wells and the optimization of frac design.
FEAtl: A Comprehensive web-based Expression Atlas for functional genomics in Tropical and Subtropical Fruit Crops
Authors: Roy Anupama , Chaurasia Himanshushekhar , Kumar Baibhav , Kumari Naina , Jaiswal Sarika , Srivast Manish , Iquebal Mir Asif , Angadi Ulavappa B , Kumar Dinesh 
Published: August 2024

Abstract

Background
Fruit crops, including tropical and subtropical fruits like Avocado (Persea americana), Fig (Ficus carica), Date Palm (Phoenix dactylifera), Mango (Mangifera indica), Guava (Psidium guajava), Papaya (Carica papaya), Pineapple (Ananas comosus), and Banana (Musa acuminata) are economically vital, contributing significantly to global agricultural output, as classified by the FAO's World Programme for the Census of Agriculture. Advancements in next-generation sequencing, have transformed fruit crop breeding by providing in-depth genomic and transcriptomic data. RNA sequencing enables high-throughput analysis of gene expression, and functional genomics, crucial for addressing horticultural challenges and enhancing fruit production. The genomic and expression data for key tropical and sub-tropical fruit crops is currently lacking a comprehensive expression atlas, revealing a significant gap in resources for horticulturists who require a unified platform with diverse datasets across various conditions and cultivars.
Results
The Fruit Expression Atlas (FEAtl), available at http://backlin.cabgrid.res.in/FEAtl/index.php, is a first-ever extensive and unified expression atlas for tropical and subtropical fruit crops developed using 3-tier architecture. The expressivity of coding and non-coding genes, encompassing 2,060 RNA-Seq samples across 91 tissue types and 177 BioProjects, it provides a comprehensive view of gene expression patterns for different tissues under various conditions. FEAtl features multiple tabs that cater to different aspects of the dataset, namely, Home, About, Analyze, Statistics, and Team and contains seven central functional modules: Transcript Information, Sample Information, Expression Profiles in FPKM and TPM, Functional Analysis, Genes Based on Tau Score, and Search for Specific Gene. The expression of a transcript of interest can be easily queried by searching by tissue ID and transcript type. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.
Conclusions
This atlas represents a groundbreaking compilation of a wide array of information pertaining to eight distinct fruit crops and serves as a fundamental resource for comparative analysis among different fruit species and is a catalyst for functional genomic studies.
OZ-001 suppresses the growth of triple-negative breast cancer and pancreatic cancer via targeting STAT3 phosphorylation and calcium signaling pathway
Authors: Kim Jisun , Kim Hyun-Kyoung , Lee SunHye , Yu Young-Jin , Ullah Ahsan , Kim Eui Yun , Yoo Ho , Chae Han-Jung 
Published: August 2024

Abstract

Background
Triple-negative breast cancer (TNBC) and pancreatic ductal adenocarcinoma (PDAC) are characterized by uncontrolled tumor growth, high risk of recurrence and resistance to chemotherapy, and poor prognosis. OZ-001 is a small molecule that exhibits a unique dual mechanism of action by blocking T-type Ca2+ channels and targeting signal transducer and activator of transcription 3(STAT3) activation. This characteristic shows promise in addressing the urgent need for effective treatments in TNBC and PDAC. The study aimed to elucidate the anticancer characteristics, efficacy, and underlying mechanism of action of OZ-001. The finding could provide valuable insights into its therapeutic potential for treating aggressive and poor-prognosis malignancies.
Methods
The anticancer activities of OZ-001 were evaluated using MDA-MB-231 human TNBC cells and MIA PaCa-2 PDAC cells. In this study, cell viability, apoptosis, protein characterization, and cell cycle analysis were done to understand the influence of OZ-001 on MDA-MB-231 and MIA PaCa-2 cells. Additionally, protein affinity and intracellular calcium measurements were measured to evaluate the functional mechanism of OZ-001 targeting STAT3 and T-type calcium channels. Further, TNBC and PDAC animal models were developed using MDA-MB-231 and MIA PaCa-2 xenograft mice to assess the anticancer effects of OZ-001.
Results
The study observations revealed that the OZ-001 molecule induced caspase-dependent MDA-MB-231 and MIA PaCa-2 cell death via B-cell lymphoma 2(BCL-2) family proteins. OZ-001 selectively regulated cell viability by suppressing STAT3 phosphorylation-linked genes such as survivin, Mcl-1, and Cyclin D1. Specifically, OZ-001 blocked the T-type calcium channels, which reduced intracellular calcium levels and activated cell death pathways in TNBC and PDAC. Further, oral administration of OZ-001 suppressed tumor growth in MDA-MB-231 and MIA PaCa-2 xenograft mice, which could be attributed to reduced STAT3 phosphorylation and decreased tumor growth.
Conclusion
The study findings revealed that OZ-001 inhibits the phosphorylation of STAT3 and T-type calcium channels against TNBC and PDAC. These findings suggest the potential therapeutic application of OZ-001 as an alternative anticancer molecule.
A parameter recovery assessment of a wide class of evidence accumulation models of decision-making
Authors: Murrow Matthew , Holmes William 
Published: August 2024

Abstract

Computational modeling has become indispensable in investigating the dynamics of decision making processes. A prominent category of models in this domain are Evidence Accumulation Models (EAMs), which model both the decisions people make and the time they take. Many variations have been proposed which modify the drift rate, diffusion rate, and decision thresholds, encoding increasingly complex dynamics into the EAM framework. However, adding model features complicates parameter recovery, making model interpretation more difficult. In this work, we perform a parameter recovery study to a variety of common binary choice EAMs, identify the specific challenges for each, and explore how to improve their parameter recoverability. Though previous studies have addressed this question, they have been piecemeal in nature, with different groups applying different computational methods to study different models. We aim to unify this body of literature using the best currently available computational methods. Further, we present the first, to our knowledge, Bayesian analysis of diffusion conflict models. Our purpose here is to be thorough, not exhaustive or comprehensive. With this in mind, this article catalogues a number of results, some previously shown and some new. Further, it illustrates different approaches to model analysis. This article is intended to be a resource for researchers interested in utilizing EAMs for studying decision-making processes, providing insights into the challenges associated these models, how to analyze them in light of those challenges, and examples of how to address those challenges.
A Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests
Authors: Sarkheil Hamid , Rostamian Emad , Rahbari Shahrokh , Lak Razieh 
Published: August 2024

Abstract

The pressing concerns associated with climate change underscore the critical need for environmental conservation and sustainable resource management. As technological and industrial advancements continue to drive an escalating demand for materials, the extraction of which often involves mining, the imperative to explore novel methodologies for assessing and mitigating the environmental impact of such operations becomes evident. This study proposes a novel approach utilizing fuzzy logic to calculate the Forest Health Index (FHI), introducing both a Fuzzy Constructive FHI and a Fuzzy Destructive FHI index, each ranging from 0 to 100. The disparity between these indices, ranging from − 100 to 100, elucidates the overall forest health index. The study employs the Sungun copper mine as a case study, situated within the Arasbaran environmental protected area, which necessitates the application of forest-smart mining regulations and policies. To examine the impact of mining operations on forest health, remote sensing is employed to identify potential porphyry copper mineralization areas and to visualize deforestation trends at the Sungun copper mine from 2008 to 2023. Vegetation indices are utilized to estimate the Forest Health Index (FHI) through remote sensing methodologies, incorporating a combination of expert opinions and guest numbers to assess variables influencing the FHI (Forest Health Index). Results indicate that the Forest Health Index (FFHI) for Sungun is 2.1 (interpreting as rather low constructive fuzzy forest health index). For broader case studies, maximum and minimum FFHIs (Fuzzy Forest Health Index) were observed in Merian (37.92 interpreting as rather average constructive fuzzy forest health index) and Nimba Range Mineral Province (NRMP) (-25.7 interpreting as rather low/average destructive fuzzy forest health index), respectively. The outcomes emphasize the importance of implementing forest-smart mining practices to mitigate the adverse effects of mining activities on the Arasbaran forest and promote conditions conducive to forest health. It is better to diminish high road density, forest fragmentation and total deforestation along with improve forest core, forest connectivity and secondary forestry.