bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sentinental Analysis for Finding the Imapct of Medical Data Breaches on Chronic Diseases Using Tomek Link Method
Authors: S Tamilarasi , Pavithra S , Chawla Divyansh , Agarwal Khushi , Chowdhry Harshit 
Published: September 2023

Abstract
The study focuses on the impact of medical data breaches on chronic diseases. The research involves the collection and analysis of data from online health forums, social media posts, patient surveys, and demographic, medical history, and biometric data. To analyze the sentiments and effects of data breaches using deep learning techniques such as Tomek link method, metagenomics, and polysegmentation. A proposed Sentiment analysis along with Tomek link method, are used to extract the sentiment of the text data and also understand the patients opinion and emotion towards medical data breaches. The data is integrated with the dataset used for predicting chronic diseases with the help of metagenomics and polysegmentation method, which is used to identify the impact of medical data breaches on chronic diseases. The proposed model performance is assessed using cross-validation and testing on a separate dataset and also our framework achieves better results with improved parameters F1 score is 98.82 percent.
Mean computed tomography Value to predict Spread through air spaces in clinical N0 lung adenocarcinoma
Authors: Yamamoto Marino , Tamura Masaya , Miyazaki Ryohei , Okada Hironobu , Wada Noriko , Toi Makoto , Murakami Ichiro 
Published: September 2023

Abstract

Background The aim of this study was to assess the ability of radiologic factors such as mean computed tomography (mCT) value, consolidation/tumor ratio (C/T ratio), solid tumor size, and standardized uptake (SUV) value to predict the presence of spread through air spaces (STAS) of lung adenocarcinoma.Methods A retrospective study was conducted on 118 patients those diagnosed with clinically without lymph node metastasis and having a pathological diagnosis of adenocarcinoma after undergoing surgery. Receiver operating characteristics (ROC) analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict STAS. Univariate and multiple logistic regression analyses were performed to determine the independent variables for the prediction of STAS.Results Forty-one lesions (34.7%) were positive for STAS and 77 lesions were negative for STAS. The STAS positive group was strongly associated with a high mCT value, high C/T ratio, large solid tumor size, large tumor size and high SUV. The mCT values were − 324.9 ± 19.3 HU for STAS negative group and − 173.0 ± 26.3 HU for STAS positive group (p < 0.0001). The ROC area under the curve value of the mCT value was the highest (0.738), followed by SUV (0.720), C/T ratio (0.665), solid tumor size (0.649). Multiple logistic regression analyses using the preoperatively determined variables revealed that mCT value (p = 0.013) was independent predictive factors of predicting STAS. The maximum sensitivity and specificity were obtained at a cutoff value of -251.8 HU.Conclusions The evaluation of mCT value was useful for predicting the presence of STAS and may potentially contribute to the selection of suitable treatment strategies.
Whole exome sequencing and polygenic assessment of a Swedish cohort with severe developmental language disorder
Authors: Yahia Ashraf , Li Danyang , Lejerkrans Sanna , Rajagopalan Shyam , Kalnak Nelli , Tammimies Kristiina 
Published: September 2023

Abstract
Background
Developmental language disorder (DLD) overlaps clinically, genetically, and pathologically with other neurodevelopmental disorders (NDD), corroborating the concept of the NDD continuum. There is a lack of studies to understand the whole genetic spectrum in individuals with DLD.
Methods
Previously, we recruited 61 probands with severe DLD from 59 families and examined 59 of them and their families using microarray genotyping with a 6.8% diagnostic yield. Herein, we investigated 53 of those probands using whole exome sequencing (WES). Additionally, we used polygenic risk scores (PRS) to understand the within family enrichment of neurodevelopmental difficulties and examine the associations between the results of language-related tests in the probands and language-related PRS.
Results
We identified clinically significant variants in five probands, resulting in a 9.4% (5/53) molecular diagnostic yield. Those variants were in CHD3, PAK2, MED13, PLCB4, and TNRC6B. We also prioritized additional variants for future studies for their role in DLD, including high-impact variants in PARD3 and DIP2C. PRS did not explain the aggregation of neurodevelopmental difficulties in these families. However, we detected positive associations between neurodevelopmental difficulties and PRS for educational attainment and cognitive performance within the families (p = 0.006 and 0.02, respectively). We did not detect significant associations between PRS for language quantitative measures and their corresponding PRS.
Conclusion
Our results support using WES as the first-tier genetic test for DLD as it can identify monogenic DLD forms. Large-scale sequencing studies for DLD are needed to identify new genes and investigate the polygenic contribution to the conditions.
Construction of luciferase-expressing Neospora caninum and drug screening
Authors: Wang Fei , Xue Yangfei , Pei Yanqun , Yin Meng , Sun Zhepeng , Zhou Zihui , Liu Jing , Liu Qun 
Published: September 2023

Abstract
Background: Neospora caninum is an apicomplexan parasite which is particularly responsible for abortions in cattle and neuromuscular disease in dogs. New therapeutics are urgently needed to control Neosporosis due to the limited effectiveness of currently available drugs. Luciferase-based assays are potentially powerful tools in the search for antiprotozoal compounds, permitting the development of faster and more automated assays. The aim of this study was to construct a luciferase-expressing N. caninum and evaluate anti-N. caninum drugs.
Methods: The CRISPR/Cas9 was used to construct the luciferase-expressing N. caninum (Nc1-Luc). After testing the luciferase expression and phenotype of Nc1-Luc strains, we determined the drug sensitivity of Nc1-Luc strains by treating them with known positive or negative drugs and half-maximal inhibitory concentration (IC50) calculation. Then the selective pan-RAF inhibitor TAK-632 was evaluated for anti-N. caninum effects using Nc1-Luc by luciferase activity reduction assay and other in vitro and in vivo pharmacodynamic studies.
Results: The phenotypes and drug sensitivity of Nc1-Luc strains were consistent with those of the parent strains Nc1, and Nc1-Luc strains can be used to determine IC50 for anti-N. caninum drugs. Using Nc1-Luc strains, TAK-632 showed promising activities against N. caninum, with an IC50 of 0.6131 mM and a selectivity index (SI) of 62.53. In vitro studies showed that TAK-632 inhibited invasion, proliferation and divison of N. caninum tachyzoites. In vivo studies showed that TAK-632 attenuated the virulence of N. caninum in mice and significantly reduced the parasite burdens in the brain.
Conclusions: In conclusion, a luciferase-expressing N. caninum strain was successfully constructed, which provides an effective tool for drug screening and related research on N. caninum. In addition, TAK-632 was found to inhibit the growth of N. caninum, which could be considered as a candidate lead compound for new therapeutics for neosporosis.
Interference Minimized Delay Reduction Based Routing Protocol (IMDRRP) For Wireless Ad Hoc Networks
Authors: Thenmozhi M. , Devaraju S. , Somasundaram A. , Jawahar S. 
Published: September 2023

Abstract
A wireless ad hoc network paves way for many real time applications. Delay consideration over the transmission is the critical part of research which helps better packet delivery. Over the wireless medium interference is the common phenomenon which significantly reduces the performance and life time of the network. In this research work, delay reduction is focused along with minimizing interference in wireless ad hoc network scenario. The proposed protocol is termed as interference minimized delay reduction-based routing protocol (IMDRRP). Minimum interference, average interference and route interference are estimated. After that single – hop topology is constructed and then delay constrained spanning tree mechanisms are used. IMDRRP is evaluated for performance in terms of throughput, average energy consumption and delay. From the simulation results, it is inferred that, IMDRRP performs better with the chosen compared protocols.
Most Probable Dynamics of the Single-Species with Allee Effect under Jump-Diffusion Noise
Authors: Tesfay Almaz , Yuan Shenglan , Tesfay Daniel , Brannan James 
Published: September 2023

Abstract
We investigate the most probable phase portrait (MPPP) of a stochastic single-species model with the Alleeeffect using the non-local Fokker-Planck equation (FPE). This stochastic model is driven by non-Gaussianas well as Gaussian noise. It has three fixed points in the deterministic case. One of them is the unstablestate which lies between the two stable equilibria. We focus on the transition pathways from the extinctionstate to the upper fixed stable state for the transcription factor activator in a single-species model. This helpsus to study the biological behavior of species. The most probable path is obtained from the solution of thenon-local Fokker-Planck equation corresponding to the population system of the single-species model, andthe corresponding maximum possible stable equilibrium state is determined. We also acquire the Onsager-Machlup function for the stochastic model and solve the corresponding most probable paths. The numericalsimulation manifests that: (i) When non-Gaussian noise is presented in the system, the maximum of thestationary density function is located at the most probable stable equilibrium state; (ii) If the initial valueincreases from extinction state to the upper stable state, the most probable trajectory goes to the maximallikely equilibrium state, in our case it lies between 9 and 10; (iii) The most probable paths increase to stablestate quickly, then maintain a nearly constant level, and approach to the upper stable equilibrium state astime goes on. These numerical experiment findings accelerate growth for further experimental study, inorder to achieve good knowledge about dynamical systems in biology.
2020 MSC: 39A50, 45K05, 65N12
Cross-sectional Study of Pharmacovigilance Knowledge, Attitudes, and Practices Based on Structural Equation Modeling: A Case Study of Healthcare Personnel and the Public in Yunnan Province
Authors: Qin Dan , Li Fan , Yang Jian 
Published: September 2023

Abstract
Background: This study used SEM to investigate pharmacovigilance knowledge, attitudes, and practices among healthcare personnel and the public in Yunnan Province and explored the relationships between them. Demographic characteristics were also examined for their impact on knowledge, attitudes, and practices. The study aims to inform the development of policies and education programs aimed at improving pharmacovigilance.
Methods: This cross-sectional study used a survey design, with healthcare personnel and the public in Yunnan Province as the research subjects, and data were collected using a questionnaire survey. Data analysis and statistical description were performed using SPSS 27.0, and structural equation modeling (SEM) was constructed and analyzed using AMOS 26.0.
Results: This study collected 209 public questionnaires and 823 healthcare personnel questionnaires. The public's average pharmacovigilance knowledge score was 4.62±2.70, with a total awareness rate of 57.75%, an average attitude score of 31.99±4.72, a total holding rate of 91.40%, and an average behavior score of 12.07±4.96, with a total execution rate of 75.44%. The average pharmacovigilance knowledge score of healthcare personnel was 4.38±3.06, with a total awareness rate of 87.60%; the average attitude score was 27.95±3.34, with a total holding rate of 93.17%; and the average behavior score was 7.75±2.77, with a total execution rate of 77.50%. Both public and healthcare personnel KAP models showed a significant positive correlation between pharmacovigilance knowledge, attitude, and behavior. Demographic characteristics had no statistical significance on public pharmacovigilance knowledge, attitude, and behavior, while they had a positive impact on healthcare personnel's pharmacovigilance knowledge, attitude, and behavior, except for gender.
Conclusion: This study revealed that the current status of pharmacovigilance knowledge, attitude, and behavior among healthcare personnel and the public in Yunnan Province is not optimistic, with significant differences between the two groups. The SEM results show that there is a significant positive correlation between knowledge, attitude, and behavior, and demographic factors such as age, occupation, and highest education level have an impact on the KAP of pharmacovigilance. Therefore, it is necessary to strengthen pharmacovigilance education, improve the public's awareness and understanding of pharmacovigilance, and promote the reasonable and safe use of drugs.
Speech Emotion Recognition in Conversations Using Artificial Intelligence: A Systematic Review and Meta-Analysis
Authors: Alhussein Ghada , Ziogas Ioannis , Saleem Shiza , Hadjileontiadis Leontios 
Published: September 2023

Abstract
Purpose:
Manifestations of emotion in social conversational interactions stand at a focal point in the rapidly growing affective computing area, with applications in healthcare, education and human-computer interaction. Artificial intelligence (AI) holds great potential in modelling the challenging dynamic nature of affect in speech conversation. In this paper, we analyze and criticize latest trends and open problems through a systematic review and multi-subgroup meta-analysis of AI approaches for emotion recognition in conversation (ERC).
Methods:
We adopt the PRISMA-DTA guidelines toward analysis of AI-driven speech ERC. A comprehensive database search through predefined query strings and selection criteria allowed for data extraction of essential diagnostic performance parameters. We analyze salient patterns related to methodological quality and risk of bias. Univariate random-effects models are then designed with a multi-subgroup perspective, centered around affective annotations models, while encompassing the ERC parameters of modalities, feature extraction and conversation style.
Results:
51 studies were systematically reviewed for qualitative analysis, whereas 27 articles were included in the meta-analysis. Diagnostic test performance manifested with high heterogeneity, with intriguing insights regarding affective state annotation, input modality, feature extraction methods, and dataset conversation style.
Conclusion:
Our research contributes fine-grained insights as recommendations that tackle open-problems in ERC. While providing valuable information on diagnostic performance of AI in speech ERC, we underscore the imperative need for further advancements in annotations and models capable of handling diverse emotional expressions.
Application of Maximum Overlap Discrete Wavelet Transform and Machine Learning to Improved Daily Rainfall Prediction Modeling
Authors: KÜLLAHCI Kübra , ALTUNKAYNAK Abdüsselam 
Published: September 2023

Abstract
Rainfall is an important phenomenon for various aspects of human life and the environment. Accurate prediction of rainfall is crucial for a wide range of sectors, including agriculture, water resources management, energy production, disaster management, and many more. The ability to predict rainfall in an accurate fashion enables stakeholders to make informed decisions and take necessary actions to mitigate the impacts of natural disasters, water scarcity, and other issues related to rainfall. In addition, advances in rainfall prediction technologies have the potential to contribute to sustainable water management and the preservation of water resources by providing the necessary information for decision-makers to plan and implement effective water management strategies. Hence, it is important to continuously improve the accuracy of rainfall prediction. In this paper, the integration of the Maximum Overlap Discrete Wavelet Transform (MODWT) and machine learning algorithms for daily rainfall prediction is proposed. The main objective of this study is to investigate the potential of combining MODWT with various machine-learning algorithms to increase the accuracy of rainfall prediction and extend the forecast time horizon to three days. In addition, the performances of the proposed hybrid models are contrasted with the models hybridized with commonly used discrete wavelet transform (DWT) algorithms in the literature. For this, daily rainfall raw data from 3 rainfall observation stations located in Türkiye are used. The results show that the proposed hybrid MODWT models can effectively improve the accuracy of precipitation forecasting, based on model evaluation measures such as mean square error (MSE) and Nash-Sutcliffe coefficient of efficiency (CE). Accordingly, it can be concluded that the integration of MODWT and machine learning algorithms have the potential to revolutionize the field of daily rainfall prediction.
Cardiac Metastasis from Cervical Cancer: A Case Report and literature review Cardiac Metastasis from Cervical Cancer: A Case Report and literature review
Authors: Sun Zhaochen , Xiang Dan , Jiang Junyan , 陈 一天 
Published: September 2023

Abstract
Heart metastasis in cervical cancer is an exceptionally uncommon occurrence. Given the early onset of obscure clinical presentations and complex imaging features of cardiac tumors, cases diagnosed before death are exceedingly rare. In this report, we present a case of cervical cancer with cardiac tumor metastasis diagnosed pre-mortem, and conducted a review of the current literature. The following conclusions were drawn: (1) The incidence of cardiac metastasis is influenced by clinical stage and treatment modality at initial diagnosis. (2) The prognosis for patients with cervical cancer heart metastasis is poor, and those with severe complications struggle to accrue benefits from active treatment. (3) When cervical cancer patients present with unexplained dyspnea, cardiac color ultrasound and enhanced chest CT should be performed to rule out tumor cardiac metastasis.
Predicting long term breast cancer risk using longitudinal mammographic screening history
Authors: Tan Tao , Wang Xin , Gao Yuan , Su Ruisheng , Zhang Tianyu , Han Luyi , Teuwen Jonas , Kroes Jaap , D'Angelo Anna , Drukker Caroline , Schmidt Marjanka , Beets-Tan Regina , Karssemeijer Nico , Mann Ritse 
Published: September 2023

Abstract
Risk assessment of breast cancer (BC) seeks to enhance individualized screening and prevention strategies. Recent deep learning (DL) risk models based on mammography have shown superiority in short-term risk prediction compared to traditional risk factor-based models. However, these models primarily rely on single-time exams, which emphasize the detection of existing lesions and may ignore the temporal changes in breast tissues. In this study, we present the Multi-Time Point Breast Cancer Risk Model (MTP-BCR), a novel temporospatial DL risk model that integrates traditional BC risk factors and longitudinal mammography data to identify subtle changes in breast tissue indicative of future malignancy. Utilizing a large inhouse dataset comprising risk factors and 171,168 mammograms involving 9,133 women, we evaluate the performance of the MTP-BCR model in long-term risk prediction. Our model demonstrates a significant improvement in 10-year risk prediction with an area under the receiver operating characteristics (AUC) of 0.80, outperforming the traditional BCSC 10-year risk model, our pure image model (without risk factors), and is also superior to other SOTA methods at 5-year AUC in various screening cohorts. Furthermore, MTP-BCR provides unilateral breast-level predictions with AUCs up to 0.81 and 0.77 for 5-year and 10-year risk assessments, respectively. External validation in the public CSAW-CC dataset demonstrates the consistent advantage of our multi-time point-based model compared to the single-time point-based method. For the prediction of breast cancer recurrence, our MTP-BCR obtains a 5-year AUC of 0.71 which also surpasses other methods. The heatmaps derived from our model may help clinicians better understand the progression from normal tissue to cancerous growth, enhancing interpretability in breast cancer risk assessment.
Microbial associations of geographical races Hippophae rhamnoides L. under conditions of different soil-climate zones
Authors: Ларина Г.Е. , Серая Л.Г. 
Published: September 2023

Облепиху крушиновидную ( Hippоphae rhamnoides L.) применяют в агролесомелиорации эродированных земель и озеленении населенных пунктов, а также при создании промышленных плантаций. Облепиха относится к актиноризным растениям, у которых формируются бактериосимбиотрофические отношения корневой системы и почвенных микроорганизмов, представителей порядка актиномицетов (Actinomycetales) рода Frankia . В условиях разных почвенно-климатических зон в местах роста облепихи происходит селектирование ассоциативной микробиоты. Показаны различия в составе и структуре разных микробиомов в корневой зоне облепихи для прибалтийского, сибирского, среднеазиатского и кавказского климатипов. Определены факторы (эдафические и биологические условия), лимитирующие рост облепихи в разных почвенно-климатических условиях. Показано, что в искусственных насаждениях облепихи создаются благоприятные условия для накопления и роста почвенных патогенов из рода Alternaria , Fusarium , Rhizopus , а также большого набора плесневых грибов из рода Aspergillus , Clonostachys , Cunninghamella , Mucor , Humicola , Penicillium , Paecilomyces.
Sea buckthorn ( Hippophae rhamnoides L.) is used in agroforestry of eroded lands and landscaping of settlements, as well as in the creation of industrial plantations. Sea buckthorn belongs to actinorhizal plants that form bacteriosymbiotrophic relationships between the root system and soil microorganisms, representatives of the actinomycetesorder ( Actinomycetales ) of the genus Frankia . Under the conditions of different soil-climatic zones in the places of sea buckthorn growth, the associative microbiota is selected. Differences in the composition and structure of different microbiomes in the root zone of sea buckthorn for the Baltic, Siberian, Central Asian and Caucasian climatypes are shown. The factors (edaphic and biological conditions) limiting the growth of sea buckthorn in different soil and climatic conditions were determined. It has been shown that favorable conditions are created in artificial plantations of sea buckthorn for the accumulation and growth of soil pathogens from the genus Alternaria , Fusarium , Rhizopus , as well as a large set of mold fungi from the genus Aspergillus , Clonostachys , Cunninghamella , Mucor , Humicola , Penicillium , Paecilomyces.