bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sister Mary Joseph’s nodule as a first sign of an advanced left colon adenocarcinoma, an exceptional clinical situation: A Case Report.
Authors: Zabeirou Aliou , Younssa Hama , Adam Saidou , Didier Lassey James , Younoussa Moussa , Rachid Sani 
Published: February 2024

Abstract
Background
Sister Mary Joseph’s nodule is a malignant metastatic umbilical nodule. Sister Mary Joseph Dempsey (1856–1939) was the first to notice the association between intra-abdominal or pelvic cancers and metastatic umbilical nodules. It is a rare clinical sign but an important physical finding as it is a sign of an advanced stage of malignancy with a poor prognostic.
Case Presentation:
We report the case of a 34-year-old female with a 2-month history of an umbilical nodule (2cm) admitted to the emergency department for acute bowel obstruction. A CT scan showed a thickening of the descending colon wall associated with peritoneal carcinomatosis and a large nodule of carcinomatosis that compressed the last ileal loop, responsible for bowel obstruction. A CT scan also showed an enhanced umbilical mass infiltrating the abdominal wall. Palliative surgery was indicated in emergencies to manage bowel obstruction. Surgical exploration revealed generalized peritoneal carcinomatosis and a large nodule of carcinomatosis obstructing the last ileal loop. Ileostomies and biopsies of the carcinomatosis were performed. Histopathological examination of the carcinomatosis biopsy revealed a moderately differentiated adenocarcinoma of colic origin. The patient was referred to the oncology department for chemotherapy with good courses.
Conclusion
Sister Mary Joseph’s nodule is a rare first manifestation of colon cancer. The diagnosis is often difficult, which causes delays in the diagnosis. Early detection requires the biopsy of any nodule or umbilical mass to determine its nature. Conservative treatment should be preferred at surgical treatment, except in emergency surgical indications.
Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer
Authors: Li Jie , Xu Siyi , Zhu Feng , Shen Fei , Zhang Tianyi , Wan Xin , Gong Saisai , Liang Geyu , Zhou Yonglin 
Published: February 2024

:
Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection
of gastric cancer forms the cornerstone of precision medicine. Several studies
have been conducted to investigate early biomarkers of gastric cancer using genomics,
transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances
associated with various omics are concurrently altered during gastric cancer development.
Furthermore, environmental exposures and family history can also induce
modifications in endogenous substances. Therefore, in this study, we primarily investigated
alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA,
and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels
in the context of GC development, employing genomics, transcriptomics, proteomics,
and metabolomics. Additionally, we elucidate the impact of exposure factors, including
HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic
biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine
learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the
biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and
metabolomics; ii) the influence of environmental exposure and family history on multiomics
data; iii) the integrated analysis of multi-omics data using machine learning techniques.
Physicochemical Characteristics and Antioxidant Activity of Some
Algerian Extra Virgin Olive Oils (Olea europaea L.)
Authors: Saoudi Boudjema , Tichati Lazhari , Lachraf Azzeddine , Kuddus Mohammed , Touarfia Moundji , Haberra Soumaya 
Published: February 2024

Background::
The present work was conducted to investigate the quality and antioxidant properties of some Algerian extra virgin olive oils (EVOOs).

Objective::
In this paper, the physicochemical characteristics and antioxidant properties of four
EVOOs of monovarietal samples (Chemlal) from East Algeria were studied.

Methods::
Physicochemical characteristics, which include free acidity, peroxide index, saponification index, specific extinction coefficients, water content, refractive index, relative density,
and chemical composition, in addition to their antioxidant activity, were investigated based on
DPPH free radical-scavenging activity (DPPH-SA).

Results::
The results of physicochemical and quality parameters proved that all samples are
EVOOs with highly nutritious and health benefits for the consumer, as per the recommendation
of the International Olive Council (IOC). The results showed that the olive oils from the southern arid region of Algeria (Sahara), have a high antioxidant activity than the samples from the
Northern regions.

Conclusion::
These findings revealed a significant influence of geographic location on the
chemical characteristics and antioxidant activities of olive oil from the same cultivar (Chemlal). These olive oils from the arid Saharan region may be used as a functional food with great
antioxidant potential.
Ankle Fusion Rates using Composite Peptide-enriched Bone Graft
Authors: McKinnon Luke S. , Symes Michael J. , Wines Andrew , Mittal Rajat 
Published: February 2024

Introduction
Joint fusion is a widely accepted treatment option for debilitating arthritis and deformity in the foot and ankle. Autologous bone grafting has long been accepted as the gold standard form of bone grafting; however, it can still be associated with non-union. This study aims to investigate joint fusion rates using Composite Peptide Enhanced Bone Graft (CPEBG) as an adjunct during ankle fusion surgery.

Methods
Data was collected retrospectively for patients over the age of 18 years, undergoing ankle fusion between June 2016 and August 2020 with autologous bone graft and CPEBG. All patients had their primary or secondary procedure performed by a single surgeon with follow-up at 6 and 12 months post-operatively. Data included baseline demographic data and procedural characteristics. The primary endpoint was to assess joint union at 6 and 12 months, respectively. Secondary objectives included post-operative pain, mobility and the use of walking aids.

Results
Radiographic union rates for the primary group were 40/48 (83%) and 43/48 (90%) at 6 and 12 months and 2/3 (67%) and 3/3 (100%) at 6 and 12 months for the secondary group, respectively. The overall non-union rate for primary ankle fusions was 8%, while no non-unions were observed in the secondary group.

Conclusion
CPEBG in foot and ankle fusion procedures yields similar union rates compared to other graft options. Further well-designed randomised control trials are warranted to confirm these findings.
Studying the Response of Anethum graveolens L. to the Stress of Salinity and Foliar Spray with Alhagi Maurorum Aqueous Extract
Authors: Neamah Wurood Hantoosh , Hasan Fatimah Ali , Jasim Fatimah Mahdi , Hachim Aqila Jumaah 
Published: February 2024

Background
Weed infestation and salinity are both biotic and abiotic stresses that are highly present in the Basrah governorate in Iraq and widely influence crop growth

Methods
The present work was conducted to evaluate the effect of salinity at (0, 6, 12 dS/m) and aqueous extract of Alhagi maurorum at (0, 3 g/L) on growth and biochemical parameters as well as phytocomponents of Dill plant Anethum graveolens L.

Results
Results revealed that growth parameters and photopigment content increased with salinity at 12 dS/m and reduced with Alhagi maurorum aqueous extract. Besides that, carbohydrate content was reduced with both stresses, and proline content increased with Alhagi maurorum aqueous extract. GC-MS chromatogram of Anethum graveolens methanolic extract displayed high alteration in phytocomponents quantity post salinity and camelthorn extract treatments.

Conclusion
Current work inferred that the Dill plant has high tolerance properties to salinity contrary to weed infestation stress. Stresses combination declined growth parameters and reduced metabolite content of Dill plants.
Factors Predicting Safe Motorcyclist Riding Behaviors among Thai Undergraduates
Authors: Tanaporn Phankam , Sarunya Benjakul , Mondha Kengganpanich 
Published: February 2024

Background
Despite the nationwide enforcement strategies in place to prevent road accidents, including wearing a helmet, not riding a motorcycle while drunk, using a safe motorcycle, obtaining a motorcycle license and avoiding speeding, accidents still occur, particularly among young motorcyclists.

Objectives
The study aimed to describe the level of behaviors and factors affecting safe motorcyclists' riding behaviors.

Methods
The cross-sectional study with single-stage cluster sampling was conducted to select 326 students in years 1–4 of the 1st semester of every faculty at Phranakhon Si Ayutthaya Rajabhat University. Data were collected using online self-administered questionnaires from December 2022 to January 2023. Descriptive and inferential statistics, including the Chi-square test, Pearson correlation coefficient and Stepwise multiple regression analysis, were used to analyze the data.

Results
Most respondents had safe motorcyclist riding behaviors at a safe level (54.6%), good knowledge-related traffic rules (41.1%), a positive attitude towards behaviors (67.8%) and a high level of support from influencing groups as subjective norms on behaviors including family members (69.6%), friends (58.3%) and favorite celebrities who participated in a road safety campaign (48.4%). Most had high perceived behavioral control (53.1%) and behavioral intention (64.7%). Eight factors were significantly associated with safe motorcyclist riding behaviors: student’s year, having a motorcycle driving license, driving a motorcycle after alcohol drinking, attitude towards behaviors, subjective norms concerning behaviors, perceived behavioral control, and behavioral intention. Based on the results, four factors could significantly predict safe motorcyclist riding behaviors up to 45.6% (Nagelkerke R2 = 0.456, p <0.001) composed of perceived behavioral control, having a motorcycle driving license, behavioral intention and subjective norm influenced by friends.

Conclusion
The study could provide valuable input for institutional administrators and related organizations to formulate policies promoting safe riding behaviors among motorcyclist students. Additionally, these results may be beneficial in organizing awareness-raising campaigns to prevent motorcycle-related accidents and monitor the process of acquiring a motorcycle driving license.
Detection of False Data Injection Attacks on Distributed Energy Resources Integration into Distribution Networks
Authors: Chen Mingliang , Xie Guoqiang , YU Yingting , Zeng Chuanhan , Xu Zaide , Li Yuan , Li Yuancheng 
Published: February 2024

Background:
Compared with the traditional power system, the large-scale access of
distributed energy resources in the new power system has a great impact on the structure and operation
mode of the power grid, and it is also more susceptible to device-level and network-level
FDI attacks.

Objective:
In order to improve the accuracy and precision of detecting false data injection attacks
in distributed energy resources integration into distribution networks and to further explore time
series modeling methods for measurement data, it is helpful for the FDIAs detection method to be
widely adopted and applied in new power systems.

Method:
To address false data injection attacks on distributed energy resource integration into
distribution grids within new power systems, a data-driven time series anomaly detection method
is employed. Firstly, time-aware shapelets are extracted from time series data, and then the shapelet
evolution graph is constructed to capture the correlation between the shapelets. Finally, time
series representation vectors are learned using segment embeddings derived from the shapelet
evolution graph through the DeepWalk algorithm. These representation vectors are then input into
a BO-XGBoost anomaly detector, facilitating the detection of FDIAs.

Results:
After multiple rounds of parameter tuning, the parameters of Shapelet quantity (K=40)
and segment length (L=4) achieved an accuracy of 92.8% in FDIA detection. Comparative experimental
results with different algorithms indicate that, compared to other unsupervised learning
methods, this approach exhibits an accuracy improvement of 20-40%. In the case of BOXGBOOST,
it achieves a 5% increase in accuracy compared to the unmodified XGBOOST.

Conclusion:
The experimental results indicate that this method can effectively detect false data
injection attacks on the integration of distributed energy resources into distribution grids within
new power systems. This model significantly enhances detection accuracy and precision while
also imparting physical significance to the dynamic evolution of time series models.
Narrative Literature on Breastfeeding Counseling during COVID-19: A South African Case of Primary Healthcare
Authors: Mphasha Mabitsela Hezekiel 
Published: February 2024

Background
Infant and young child feeding (IYCF) is vital to improve child survival and promote healthy growth and development. However, during the coronavirus-19 (COVID-19) pandemic, access to healthcare facilities or IYCF educational campaigns was limited since the focus was on managing the pandemic. Skin-to-skin contact between mother and child is the core of IYCF guidelines, yet COVID-19 regulations encourage social distancing and separation. The aim of this review was to describe challenges and lessons drawn during the COVID-19 pandemic in the delivery or promotion of IYCF.

Methods
This is a narrative literature review, which does not require seeking any ethical approvals. Publications related to the stated key search items, written in English, were included in this review study. Data was sourced from various sources, such as Scopus/Elsevier, ScienceDirect, and PubMed databases, as well as World Health Organization and United Nations Children's Funds. Search items used included IYCF promotion and services during COVID-19.

Results
A total of 43 publications were included in this review. Findings of the literature showed that there were fears of mother-to-child transmission of COVID-19 and poor feeding practices. The use of IYCF services was also limited.

Conclusion
For future COVID-19 waves and similar pandemics, the social distancing and separation of mother to child should not occur since there is minimal risk of transmission of COVID. Therefore, skin-to-skin contact and overall breastfeeding should be promoted. The IYCF guidelines should be reviewed to focus on personal hygiene practices, such as routine soap use and disinfecting of food preparation areas.
KIJANI App to Promote Physical Activity in Children and Adolescents: Protocol for a Mixed Method Evaluation
Authors: Willinger Laura , Böhm Birgit , Schweizer Florian , Reimer Lara Marie , Jonas Stephan , Scheller Daniel A , Oberhoffer-Fritz Renate , Müller Jan 
Published: February 2024

BackgroundThe prevalence of physical inactivity among children and adolescents is alarmingly high despite the well-documented and comprehensive benefits of regular physical activity (PA). Therefore, PA promotion should start early in childhood and adolescence. Although reducing recreational screen time in children and adolescents is an urgent concern, digital approaches have the potential to make activity promotion attractive and age appropriate for the target group. KIJANI is a mobile app approach to promote PA in children and adolescents via gamification and augmented reality.ObjectiveThis study protocol aims to describe the KIJANI intervention in detail, as well as the evaluation approach.MethodsKIJANI is based on the concept that virtual coins can be earned through PA, for example, in the form of a collected step count. With these coins, in turn, blocks can be bought, which can be used to create virtual buildings and integrate them into the player’s real-world environment via augmented reality. PA of users is detected via accelerometers integrated into the smartphones. KIJANI can be played at predefined play locations that were comprehensively identified as safe, child-friendly, and attractive for PA by the target group in a partner project. The evaluation process will be divided into 2 different stages. The phase-I evaluation will be a mixed methods approach with one-on-one semistructured interviews and questionnaires to evaluate the user experience and receive feedback from the target group. After the implementation of results and feedback from the target group, the phase-II evaluation will proceed in the form of a 2-arm randomized controlled trial, in which the effectiveness of KIJANI will be assessed via objectively measured PA as well as questionnaires.ResultsThe study received ethical approval from the ethical board of the Technical University of Munich. Participants for the phase-I evaluation are currently being recruited.ConclusionsThe study will help to determine the efficacy, applicability, and user experience of a gamified activity promotion application in children and adolescents. Overall, digital health approaches provide easy and wide reachability at low cost and are age appropriate and attractive for the target group of adolescents. Strategies have to be developed to apply digital health approaches in the best possible way for activity promotion.International Registered Report Identifier (IRRID)DERR1-10.2196/55156
Research and realization of computer image recognition system based on digital projection technology
Authors: Ma Qian 
Published: February 2024

Abstract
In this paper, the image Gabor features extracted by Gabor wavelet are fused with the image grayscale map to construct the enhanced Gabor features, and then combined with the characteristics of Gabor wavelet and convolutional layer, the Gabor feature extraction module, parallel convolution module and spatial transformation pooling module are designed. The corresponding Gabor convolutional layer and Gabor convolutional neural network are constructed using the appropriate module in accordance with the image recognition task application scenario. The convex set projection image super-resolution reconstruction method is used in this paper to improve the resolution of images with low resolution. The construction of a computerized image recognition system involves combining a Gabor convolutional neural network and a convex set projection method. This system has been tested and found to have a recognition accuracy of 93.5% for object images. This system’s ability to accurately recognize low-resolution shadow-obscured face images is possible thanks to using the convex set projection method to reconstruct the image and recognize it accurately with an accuracy of up to 93.85%. This system’s recognition performance for complex images has been proven through experiments.
Development trend and strategic positioning of China’s digital trade in the context of the Internet
Authors: Chu Xiwei , Wang Jingbu 
Published: February 2024

Abstract
In the context of the rapid development of the Internet, the digital economy pattern and the rule game of digital trade are becoming more and more intense. This paper constructs a competitiveness analysis model through the development of digital trade and combines the entropy value method and gray correlation to construct a comprehensive measurement model of the development level of digital trade. Similarly, it utilizes the Tel index as a gauge of the development space difference and develops a global autocorrelation model to examine its influences. An analysis of the positioning of China’s digital trade development trend is performed based on this basis. The average annual growth rate of digital trade development is 0.133, and through the correlation test of regression analysis, the per capita GDP is significant at 5% significance level with a coefficient of 0.0961. while the digital trade export value is significant at 1% significance level with a coefficient of 0.358, however, the degree of openness to the outside world is significant at 1% significance level, but the value is a negative one as −0.1585, which validates that Digital trade is carried by the Internet, and its transaction process is relatively less dependent on the logistics of goods in reality. By measuring the development level of digital trade, it is possible to propose better strategies for strategic development planning.
Analyzing the efficacy of Higher Vocational Online-Offline Blended Teaching using Koch’s Model
Authors: Yang Xingbo 
Published: February 2024

Abstract
With the development of the Internet, the traditional offline teaching mode cannot fully meet the current teaching needs, and mixed-mode teaching with informationization characteristics has received widespread attention. By combining the BTS subjective empowerment method and fuzzy comprehensive evaluation method, this paper creates the BTS-entropy weight-fuzzy comprehensive evaluation model for online and offline hybrid teaching. Based on Koch’s model, the evaluation index system of online blended teaching is constructed from four levels: reaction, learning, behavior, and result. On this basis, the four levels of Koch’s model were empirically analyzed to calculate the online and offline blended teaching effect of the school, taking six majors of School J as an example. The results are as follows: from the point of view of the coefficient of variation of the reaction layer, the coefficient of variation of each index is less than 15%, and the consistency is high. From the learning layer scores, the coefficient of variation of the learning layer indicator scores of each major is 10% < 15% and the coefficient of variation of the behavior layer indicators from each major is 19% > 15%, which indicates that the degree of dispersion of each major in the behavior layer is higher, and the variability of the total scores of each major is larger. The coefficient of variation of the outcome layer indicators is 3.8% <15%. To sum up, Koch’s model can provide more exact assessments of the effectiveness of mixed teaching in higher vocational education and provide effective feedback in real-time.
The Construction of Online Education Quality Evaluation System Based on Intelligent Algorithm
Authors: Xiao Xianfang 
Published: February 2024

Abstract
With the development of the network, online education breaks the defects of time and space, and becomes a way that more and more students choose to learn. This paper combines grey correlation analysis, optimizes BP neural network using PSO particle algorithm, and constructs GRA-PSO-BP model. The initial education evaluation indexes are improved by this intelligent algorithm model to construct an online education quality evaluation system, and then the optimized index system is used as a guide to evaluating the online education quality using this model. The results show that: the dispersion of the data of each index is R
2 = 0.92, which is greater than 0.75, and there is a strong connection between the indexes. The results show that the dispersion of the data of each index is greater than 0.75, and there is a strong connection between the indexes. The 10 colleges and universities scored 3.77, which is a satisfactory grade. The online education quality of these 10 colleges and universities are ranked from high to low as G5, G10, G9, G4, G6, G1, G3, G2, G7 and G8. The intelligent algorithm model and online education quality evaluation index system constructed in this paper can provide help for online education quality evaluation.