bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing Autism Spectrum Disorder Identification with Dimensionality Reduction Technique and K-Medoid
Authors: Martono Galih Hendro , Sulistianingsih Neny
Published: January 2025

This research addresses the challenges of diagnosing and treating Autism Spectrum Disorder (ASD) using dimensionality reduction techniques and machine learning approaches. Challenges in social interaction, communication, and repetitive behaviours characterize ASD. The dimension reduction used in this research aims to identify what features influence autism cases. Several dimension data reduction techniques used in this research include PCA, Isomap, t-SNE, LLE, and factor analysis, using metrics such as Purity, silhouette score, and the Fowlkes-Mallows index. The machine learning approach applied in this study is k-medoid. By employing this method, our goal is to pinpoint the unique characteristics of autism that may facilitate the detection and diagnosis process. The data used in this research is a dataset collected for autism screening in adults. This dataset contains 20 features: ten behavioural features (AQ-10-Adult) and ten individual characteristics. The results indicate that Factor Analysis outperforms other methods based on purity metrics. However, due to data structure issues, the t-SNE method cannot be evaluated using purity metrics. PCA and LLE consistently provide stable silhouette scores across different values. The Fowlkes-Mallows index results closely align, but t-SNE tends to yield lower values. The choice of algorithm requires careful consideration of preferred metrics and data characteristics. Factor analysis is adequate for Purity, while PCA and LLE consistently perform well. This research aims to improve the accuracy of ASD identification, thereby enhancing diagnostic and treatment precision.
Blockchain-based Supply Chain Solution Using IPFS and QR Technology for Traditional Weave in West Nusa Tenggara
Authors: Wijayanto Heri , Andara Melki Jonathan , Wiraguna Diky , Agitha Nadiyasari , Rahaman Mosiur
Published: January 2025

Traditional weaving is a significant cultural heritage in West Nusa Tenggara, Indonesia, renowned for its unique and intricate woven fabrics. However, the industry faces challenges such as product counterfeiting and the need for more transparency in the supply chain, hindering its growth and economic potential. This paper proposes a solution by leveraging blockchain technology to enhance traceability, security, and efficiency throughout the supply chain of traditional woven products. Integrating the InterPlanetary File System (IPFS) and Quick Response (QR) codes further fortifies data integrity and provides consumers with comprehensive product information. A prototype web application is developed, demonstrating the practical implementation of this framework. Rigorous testing of the prototype validates the correct functionality of the proposed solution. This innovative framework aims to safeguard the authenticity and sustainability of the traditional woven products from West Nusa Tenggara, fostering a more competitive and secure industry while preserving cultural heritage.
A Systematic Literature Review of BERT-based Models for Natural Language Processing Tasks
Authors: Fatwanto Agung , Zamakhsyari Fardan , Ndungi Rebbecah
Published: January 2025

Research area in natural language processing (NLP) domain has made major advances in recent years. The Bidirectional Encoder Representations from Transformers (BERT) and its derivative models have been at the vanguard, gaining notice for their exceptional performance across a variety of NLP applications. As a response to this context, hence, this study aims to conduct a systematic literature review on current research in BERT-based models in order to describe their characteristic variations on three frequently demanded natural language processing (NLP) tasks, i.e. text classification, question answering, and text summarization. This study employed a systematic literature review method as prescribed by Kitchenham. We collected 4,120 papers from publications indexed by Scopus and Google Scholar from which 42 complied to our defined review criteria and finally chosen for further analysis. Our review came up with three conclusions. First, in order to select appropriate models for particular NLP tasks, three primary concerns should be considered: i) the type of NLP problem to be resolved (i.e. NLP task to be served), ii) the specific domain to be handled (such as financial, medical, law/legal or others), and iii) the intended language to be applied (such as English or others). Second, learning rate, batch size, and the type of optimizer were the three most considered hyperparameters to be properly arranged in model training. Third, the most widely used metrics for text classification tasks were F1-score, accuracy, precision, and sensitivity (recall), while question answering, and text summarization tasks were mostly used the Exact Match and ROUGE respectively.
Application of Ensemble Machine Learning for Infectious Diseases with Vaccine Intervention: A Global COVID-19 Case Study
Authors: Safitri Egi , Fikri Ruki Rizalnul , Nurlistiani Rini
Published: January 2025

The COVID-19 pandemic has posed significant challenges worldwide, especially in controlling the spread of the disease through vaccination and active case monitoring. This study aims to evaluate the effectiveness of various ensemble machine-learning models in predicting the number of daily vaccinations and the number of active cases of COVID-19 based on global data. The models used include Random Forest, Bagging, Gradient Boosting Machine (GBM), AdaBoost, and XGBoost. The evaluation results show that Random Forest provides the best performance in predicting both the number of daily vaccinations and active COVID-19 cases, with a MSE value of 4.7e+09, MAE of 16,971.1, and RMSE of 68,557.2 for daily vaccinations, as well as an R² Score of 0.989, indicating a high ability to explain data variability. The Bagging model also showed excellent results with MSE of 4.78e+09 and MAE of 17,039.8. In contrast, the AdaBoost model performed the worst in predicting both variables, with an MSE of 5.54e+10 and an MAE of 106,228.6. These findings suggest that Random Forest and Bagging are superior models for predicting the number of daily vaccinations and active COVID-19 cases. This study provides important insights into using machine learning to predict vaccination effectiveness and active case dynamics, aiding decision-making in global pandemic control efforts.
Pembentukan Kata Majemuk Karakter Marvel pada Marvel.com (Pendekatan Morfologi)
Authors: Rahayu Anita , Wibowo Agus Hari
Published: January 2025

The research focused on the analysis of the types and the reasons for the compounding behind the names of Marvel characters on marvel.com. Marvel Comics' character names were the possible linguistics media that created identities for the superheroes and villains that intrigued audiences worldwide. The factors behind the merging phenomenon, according to (Lieber, 2021), are semantic transparency, phonological form, and morphological structure. The types of compounds in this research were exocentric and endocentric, while the reasons behind the compounding were examined. The research applied a descriptive qualitative design with a morphological approach and the analysis employs Spradley's method, specifically ethnographic analysis. The results showed 18 instances of compounding, with 9 of them belonging to endocentric compounds and 8 to exocentric compounds.
SEGURIDAD Y SALUD EN EL TRABAJO PRESUPUESTO JURÍDICO SOCIAL PARA ALCANZAR TRABAJO DECENTE
Authors: Restrepo Pimienta Jorge Luis , Plazas Estepa Rodrigo , Missas Gómez Jorge Eduardo , Lizarazo Mejía Gonzalo
Published: January 2025

Dentro de las relaciones de trabajo, la seguridad y la salud en el trabajo son una herramienta esencial para mantener el orden, la sanidad y la dignidad de los trabajadores, por tanto, existe una tensión en el mundo practico sobre la carencia de la aplicación y el acatamiento normativo en la administración del talento humano; lo anterior expresa de manera precisa las manifestaciones de omisiones fácticas que hacen referir las carencias del término de trabajo decente. Por lo tanto, el presente artículo científico, es el resultado de un proceso de investigación cualitativa con enfoque hermenéutico-documental basado en la observación y el análisis documental, analiza los aportes alsistema de riesgos laborales desde una perspectiva metódica en seguridad y salud en el trabajo. Se concluye que las garantías para alcanzar un trabajo decente radican en los elementos jurídico-sociales, fundamentados en la interpretación de los preceptos jurídicos normativos emanados de la Organización Internacional del Trabajo, así como en la operatividad del sistema de aseguramiento.
IMPLEMENTATION OF BALANCING DATA METHOD USING SMOTETOMEK IN DIABETES CLASSIFICATION USING XGBOOST
Authors: Ratantja Kusumajati Fatwa , Rahmat Basuki , Junaidi Achmad
Published: January 2025

In this research, XGBoost algorithm and the SMOTETomek approach are employed with the objective of enhancing the accuracy of diabetes classification. The study utilises 2,000 patient data points, comprising demographic and medical information, sourced from Kaggle. The dataset employed in this study comprises a number of variables, including pregnancies, glucose levels, blood pressure, skin thickness, insulin levels, Body Mass Index (BMI), diabetes pedigree function, age, and an outcome variable. The latter is a binary classification label, taking on the values 0 and 1. A value of 0 indicates that the patient is not affected by diabetes, whereas a value of 1 indicates that the patient has diabetes. Diabetes represents a significant public health concern in Indonesia. A significant challenge in this study was the imbalanced nature of the dataset, which included a disproportionate number of non-diabetic samples relative to diabetic samples. To address this class imbalance, the researchers employed the SMOTETomek method. SMOTETomek integrates the SMOTE (Synthetic Minority Over-sampling Technique) and Tomek links algorithms to oversample the minority class and remove borderline samples, thereby balancing the class distributions. The SMOTETomek method achieved higher accuracy (95.01%) than SMOTE and the original data (both 92.13%), highlighting the benefits of combining SMOTE with Tomek Links for XGBoost. During testing, SMOTETomek slightly reduced the minority class accuracy (0.97 vs. 0.99 for SMOTE and original data) but maintained strong F1-score and precision, indicating effective handling of data imbalance despite minor trade-offs.
EVALUATION OF PARTICLE SWARM ALGORITHM MODIFICATIONS ON SUPPORT VECTOR MACHINE HYPERPARAMETER OPTIMIZATION TUNING FOR RAIN PREDICTION
Authors: Putri Aina Latifa Riyana , Riyono Joko , Pujiastuti Christina Eni , Supriyadi
Published: January 2025

The Particle Swarm Optimization (PSO) algorithm, though simple and effective, faces challenges like premature convergence and local optima entrapment. Modifications in the PSO structure, particularly in acceleration coefficients (  and ), are proposed to address these issues. Techniques like Time Varying Acceleration Coefficients (TVAC), Sine Cosine Acceleration Coefficients (SCAC), and Nonlinear Dynamics Acceleration Coefficients (NDAC) have been implemented to enhance convergence speed and solution quality. This research evaluates various PSO modifications for improving convergence and robustness in rainfall potential prediction using Support Vector Machine (SVM) classification. The UAPSO-SVM algorithm C=0.82568 and γ=0.01960 excels in initial exploration, discovering more optimal global solutions with smaller variability. In contrast, TVACPSO-SVM shows gradual improvement but requires more iterations for stability, while SBPSO-SVM achieves the fastest convergence at iteration 14 but risks overfitting. Robustness analysis reveals all PSO-SVM variants maintain stable performance despite variations in dataset subset sizes, with accuracy stabilizing after a spike at 20%.. Therefore, PSO modifications enhance convergence speed and resilience to data fluctuations, improving their effectiveness for rainfall prediction.
CLOUD-BASED PREDICTIVE MOBILE APPLICATION FOR ASSESSING HONEY PURITY FROM STINGLESS BEES
Authors: Purwanto Y Aris , Maulana Hata , Hartono W Sony , Sukoco Heru , Diding Suhandy
Published: January 2025

Honey bees have various types and characteristics, one of which is the stingless bee. This type has limitations in producing honey, the selling value of its nest is quite expensive, and the water content in the honey produced is relatively high. The high water content affects the shelf life of this type of honey product, making it a challenge for honey farmers in marketing it. In addition, the dominant sour taste also makes its market increasingly limited or vulnerable to falsification of its purity by irresponsible producers. The use of spectrophotometers is increasingly developing in the food sector, especially in detecting the purity of a food product. The portable type of spectrophotometer also makes it easier to obtain spectrum data for a particular product. A simpler technique that is directly connected to a computer device allows it to be developed into a cloud-based application by providing minimal raw data processing (pre-processing). This study produces an android-based application and a simple cloud-based application architecture, which aims to facilitate the application of a honey purity prediction model from stingless bees. The Android-based application was successfully created by applying 'raw' spectrum data processing from the results of scanning a portable spectrophotometer, and data experiments with the SVM classification model produced an accuracy of 95%. The application of PCA techniques to cloud-based mobile application architecture results in efficient preprocessing of spectrum data.
Water Films, Asphaltenes, and Wettability Alteration
Authors: Kaminsky R. , Radke C.J.
Published: January 2025

We present a transport model for asphaltene diffusion from an oil/water interface through a water film followed by adsorption at a solid/water interface. Using a Langmuir adsorption isotherm, the effect of asphaltene aqueous solubility <md adsorption constant K on equilibration time are established. For K greater than 1 nm and asphaltene solubilities down to 0.1 ppb, adsorption equilibrium, taken to be 1 mg/m2, occurs within a few hours. Negligible asphaltene solubility does not explain why a water film prevents asphaltene adsorption and wettability alteration in reservoir rock.
Long-period oscillations as a proxy of the energy supply to the corona of the Sun
Authors: Nakariakov Valery , Zhong Sihui , Kolotkov Dmitrii
Published: January 2025

Photospheric motions are believed to be a crucial energy source for heating the solar and stellar coronae. Compared to short-period spectral components --- relative to the cutoff period (5 min)--- long-period components of photospheric motions are more energetic and, therefore, more promising candidates for coronal heating. However, whether the energy from these long-period motions can reach the corona remains uncertain. We present the detection of a 50-min decayless kink oscillation of a coronal loop, along with a corresponding oscillation in the photospheric magnetic field at the loop’s footpoint with the same period. This finding indicates that the 50-min photospheric oscillation excites the coronal oscillation, suggesting that energy of long-period motions is indeed transported up to the corona. The observed transfer of the 50-min photospheric oscillation to the corona highlights the potential of low-frequency power in the photosphere as a significant energy source for sustaining the million-degree temperatures in the corona.
A systematic scoping review of how behavioural theories, models, and frameworks have been applied to the design, conduct, analysis or reporting of clinical trials.
Authors: Coffey Taylor , Young Naomi , Gillies Katie
Published: January 2025

Background
Clinical trials provide much of the evidence that guides decision making about treatment and care but are often complicated to deliver. Trials can be thought of as complex systems with interacting individuals, as such behavioural science is a useful lens to investigate how trial processes may be improved. To guide selection of an appropriate behavioural theory, model, or framework to further enhance trial processes, we sought to map their past application within the design, conduct, analysis and reporting of clinical trials.
Methods
A systematic review to investigate scope of trials methods research that had utilised a behavioural theory, model, or framework was conducted through a database search and citation analysis. Publications investigating any part of the trial lifecycle (from design to reporting) through a behavioural lens were included.
Results
A total of 96 studies were included. A majority of these (n = 93, 97%) investigated trial conduct processes, such as recruitment and retention. Three behavioural theories, models or frameworks, the Theory of Planned Behaviour (n = 23, 24%), Social Cognitive Theory (n = 12, 13%), and the Theoretical Domains Framework (n = 30, 31%), accounted for more than two-thirds of those utilised. When compared to key stages of the Knowledge to Action cycle, approaches reported in included studies were most often utilised to “Identify a problem” within trials (n = 40, 42%).
Conclusion
A wide variety of behavioural approaches to study trial conduct were identified. However, the trial processes studied clustered within trial recruitment and largely used a few select approaches. Future research should assess whether these approaches are fit for purpose, as well as prioritising other trial areas for methods research.
Synergistic outcomes for water availability, the environment, and economic output under climate change and adaptation
Authors: Lester Rebecca , Robertson David , Bailey Joel , Dwyer Georgia , Holt Galen , Jalilov Shokhrukh , Shokri Ashkan , Watto Arif
Published: January 2025

Freshwater resources need to simultaneously support environmental and economic outcomes; this is a critical challenge under climate change. Many environmental and economic outcomes have contrasting requirements for water, leading to difficult trade-offs which should be supported by integrated assessments. We analysed the impact of climate change and climate variability on key ecological values and agricultural economic activity simultaneously in a large catchment in Australia and assessed the effect of plausible management adaptation options. Under severe climate change, ecological outcomes were rarely met while the impact on economic outcomes was less severe; annual cropping reliant on low security water allocations was most vulnerable. Under more-likely moderate climate change, altering flow delivery patterns was as effective as altering the total licence volume of environmental water without adversely affecting agricultural benefits. Thus, environmental water management can potentially influence environmental outcomes, while core economic activities continue to be met.
Long-Run Macroeconomic Effects Of Shifting Temperature Anomaly Distributions
Authors: Winter David Joseph , Kiehl Manuela , de Reding Matthew
Published: January 2025

This paper uses panel data on 201 countries from 1960 to 2019 to quantify the long-run macroeconomic effects of climate change-induced shifts in temperature anomaly distributions. We find that rising average temperature anomalies from historical norms caused by global warming have negative, non-linear impacts on GDP growth. By additionally accounting for the full temperature anomaly distribution (volatility, skewness, and kurtosis) across a geospatial grid and across time, our approach is a methodological step towards quantifying the macroeconomic impacts of broader climate change. Projected damages are far greater than estimated in previous studies that have focussed on quantifying the macroeconomic impacts of average temperature levels or volatility/extremes only. We find that 2 to 2.6°C of warming by 2050 could reduce global output by 20 to 40% compared to a scenario where temperatures are held flat at current levels, while warming of 4-5°C by 2100 could lead to more severe damages, consistent with scientific research on mass extinction thresholds and tipping points.
Heavy Mineral Assemblages of Quaternary Alluvial Deposits in Coastal Environment: Their Implication for Depositional environment and Provenance Assessment in Eastern Dahomey Basin Southwestern Nigeria
Authors: Fakolade Richard Omotoso , Ikhane Phillips Reuben , Hao Qingzhen , Guo Zhengtang , Gao Xinbo , Rotimi Isaac Ayodele
Published: January 2025

The rock provenance of eastern Dahomey Basin has not been studied much, leading to insufficient information about the alluvium deposits around the coastal environment of the basin. This has prompted this research to examine the qualitative and quantitative characteristics of heavy minerals in the sediments, with the aim at inferring their provenance, tectonic settings and their economic implications. Thirty (30) sediment samples were collected and subjected to heavy mineral analyses and quantified by viewing under the microscope. The result of heavy mineral analysed under the microscope shows that the heavy mineral assemblages in this study area are dominated by opaque minerals among which is limonite, followed by non-opaque minerals, namely the pyroxene groups (orthpyroxene and clinopyroxene), amphibole group (hornblende, tremolite and actinolite), tourmaline, zircon and rutile. In conclusion, the heavy mineral studies revealed a range of basic and acidic igneous, metamorphic and intermediate rocks coupled with reworked sedimentary deposits in source areas, where there is a mixed depositional environment and varied intensity of weathering. More research work with large amount of samples is recommended to determine the specific source area for the sediments in Eastern Dahomey Basin.
DNA cleavage activity of linear trinuclear copper(II) complexes
Authors: Das Arup Kumar , Karmakar Susnata
Published: January 2025

Metal ions and metal complexes are important components of nucleic acid biochemistry, participating both in the regulation of gene expression and as therapeutic agents. Cu(II) complexes are important for DNA cleavage, which is essential for the development of anticancer drugs and chemotherapeutic agents. For example, a study revealed that a Cu(II) complex caused double-strand DNA nicks, destabilized the DNA molecule, and disrupted the phosphodiester bonds. Here two trinuclear copper (II) complexes ware synthesized and structurally characterized: [CuII3(L2)4(2picolinate)2(OClO3)2](ClO4)2•2CH3COCH3•2CH3OH (1) and [CuII3(L2)4(2,6-dipicolinate)2] (ClO4)2•6MeOH•2H2O (2) (L2 = 1-benzyl-[3-(2'-pyridyl)] pyrazole; 2-picolinate = 2-pyridinecarboxylic acid; 2,6-dipicolinate = 2,6-pyridinedicarboxylic acid). The binding of copper complexes to plasmid DNA (P-DNA) has been investigated via UV-Visible spectroscopy, which revealed that P-DNA can covalently bind to the complexes. P-DNA cleavage was also investigated via agarose gel electrophoresis in the presence and absence of an oxidative agent (H2O2). The effect of the complex concentration on the P-DNA cleavage reaction has also been studied. Both copper complexes show nuclease activity, which significantly depends on the concentrations of the complexes, in the presence of H2O2, likely through an oxidative mechanism whereas they slightly cleave P-DNA in the absence of an oxidative agent.
Combining genetics with real-world patient data enables ancestry-specific target identification and drug discovery in Alzheimer’s disease
Authors: Cheng Feixiong , Hou Yuan , Zhang Pengyue , Li Yichen , Lorincz-Comi Noah , Fan Fan , Song Wenqiang , Fang Xing , Qiu Yunguang , Paz Isabela Rivera , Martin William , Feng Yayan , Zhou Yadi , Xu Jielin , Dou Lijun , Border Jane , Zhang Huawei , Mazique Jena’ N , Hwang Sung Hee , Roman Richard , Tousi Babak , Bekris Lynn , Karavani Ehud , Danziger Michael , Rosen-Zvi Michal , Haines Jonathan , Yu Haiyuan , Pieper Andrew , McReynolds Cindy , Leverenz James , Hammock Bruce , Cummings Jeffrey
Published: January 2025

Although high-throughput DNA/RNA sequencing technologies have generated massive genetic and genomic data in human disease, these findings have not been translated into new patient treatments. To address this problem, we utilized Mendelian randomization (MR) and large patient-level genetic and functional genomic data to evaluate druggable targets using Alzheimer’s disease (AD) as a prototypical example. Specifically, we applied the genetic instruments from 9 expression quantitative trait loci (eQTL) and 3 protein quantitative trait loci (pQTL) datasets across five human brain regions from three human brain biobanks and performed MR in 7 genome-wide association study (GWAS) datasets of European ancestry (EA) and African ancestry (AA), with AD cases and controls. We identified 19 drug targets, including the inflammatory target of epoxide hydrolase 2 (EPHX2) as a potent AD target. We demonstrated that a genome-wide significant and protective variant of p.Arg287Gln in EPHX2 (β = -0.096, PGWAS = 1.08 × 10-11) significantly reduced level of phosphorylated-tau (p-tau181) and the ratio of p-tau181/total tau and increased neuron clump size in patient induced Pluripotent Stem Cells (iPSC)-derived neurons, mechanistically supporting MR results. Pharmacologic inhibition of EPHX2 significantly improved cognitive behaviors in two AD transgenic rodent models (5xFAD and TgF344-AD). We further identified that 12 drugs (i.e., trazodone [ADRA1A] and baclofen [GABBR1]) harboring MR-supported targets are significantly associated with reduced incidence of AD in 111,680 mild cognitive impairment (MCI) patients from the Optum database. Using a new user active-comparator design, we found that usage of trazodone was significantly associated with 22% reduced incidence of AD (hazard ratio [HR] = 0.78, P=6.44x10-6) in people with MCI in the MarketScan database. In summary, combining genetics and real-world patient data identifies ancestry-specific therapeutic targets and medicines for AD and other neurodegenerative diseases if broadly applied.
Comparison of reproductive health literacy and related factors in urban and rural women of reproductive age in Iran 2023
Authors: hamzehgardeshi zeinab , ahmadian maryam , Rezaei Maedeh , Alizadeh Kosar , Shahhosseini Zohreh , Hamzehgardeshi Leila , Golchin Nayereh Azam Hajikhani
Published: January 2025

Background: Reproductive health is a key area of health and an important indicator of the health status of societies. Improving reproductive health literacy is one of the most important strategies to achieve the goals of reproductive health in various groups of women.
Methods: This study is a cross-sectional descriptive analytical study in eligible married women aged 18-49. The reproductive health literacy questionnaire and demographic-social- reproductive characteristics questionnaire were completed by 593 people in person, online and by phone. Simple random sampling with allocation proportional to the size of reproductive age women was done in each center. After collecting the data, it was analyzed by spss 23 software.
Results: The health literacy score for urban and rural women was 118.54 ± 21.38 and 111.40 ± 24.21, respectively, indicating a significant difference (P<0.00). Besides, the percentage of women with favorable literacy in rural are as was higher than in urban areas (70.4% vs. 51.4%). In logistics regression, there was a significant relationship with women's reproductive health literacy score in the city only between breast self-examination (p= 0.009 and OR = 0.4) and in the village between breast examination by physician or midwife (p= 0.003 and OR=0.38), employment of a family member in the health care system (p= 0.000 and OR=0.25) and the number of pregnancies (p= 0.04 and OR= 55).
Conclusion: The results of this study can help health planners and policymakers design and implement more appropriate training and health services by considering the differences in urban and rural areas. In addition, given the importance of behaviors related to reproductive health, encouraging preventive examinations and raising public awareness in this area can help improve reproductive health literacy in women.
Evaluation of the effect of a synthetic analogue of brominated furanone- (z)-4-bromo-5-(bromomethylene)-2(5h)-furanone on the gene expression of fadA of F. nucleatum
Authors: Swathy S , Nisha K J , Shruthi S
Published: January 2025

Fusobacterium nucleatum (F. nucleatum) commonly referred to as a bridging organism acts as a major coaggregation organism linking early and late colonizers. FadA, is an adhesin which is unique to F. nucleatum play an important role in colonization of Fusobacterium in the host. Quorum Sensing (QS) inhibiting agents appears to be a promising approach to control bacterial infections. Aim: To evaluate the effect of a synthetic analogue of brominated furanone- (Z)-4-Bromo-5-(bromomethylene)-2(5H)-Furanone on the gene expression of fadA of F. nucleatum. Material and Methods: 2 mM concentration of the brominated furanone compound was treated with F. nucleatum standard strain ATCC No. 25886 and incubated under anaerobic condition for 24 hours and 48 hours duration. Control sample was treated with only F. nucleatum bacterial cells. Analysis of the expression of fadA gene of F. nucleatum was done using RT-PCR. The 16S rRNA gene was used as a reference for normalization of the gene expression levels. Positive reaction was detected by accumulation of a fluorescent signal in the form of amplification plot obtained in the Realplex software. Statistical analysis used: Relative gene expression was calculated by using 2−∆∆Ct (Livak) method. Results: Compared with control, at 24 hours, the change in fold expression of fadA gene of F. nucleatum of the treated group was 1.602, while at 48 hours, it was 2.063. Conclusions: The synthetic analogue of furanone compound can act on target sites of F. nucleatum thereby inhibiting coaggregation and biofilm formation.
Exploring Attitudes and Needs for Digital Supportive Care in Patients with Cancer and Survivors
Authors: FOURNIER Valentyn , CATON Laura , LAROUSSI-LIBEAULT Lisa , AELBRECHT-MEURISSE Capucine , RYBARCZYK Claire , RICHEZ Louise , MAIEZZA Sophie , DUPREZ Christelle , ANTOINE Pascal , COLLET François , LAMORE Kristopher
Published: January 2025

The literature has reported inequality in access to both medical and psychosocial supportive care in oncology for which digital health technologies may be a suitable solution. Given attitudes could influence acceptability of such tools, this pre-registered qualitative study aimed to investigate patients’ and survivors’ attitudes toward digital psychosocial supportive care interventions and needs. A total of 36 patients (31 female, five male; mean age = 49.86 ± 10.93 years) were recruited. Patients were found to have positive attitudes toward the digitalization of supportive care. However, they had some concerns, including about the complementarity between digital and in-person care and the security of data, which should be considered during the development of interventions. Participants asked for a participative design, transparency during intervention development, and frequent user experience evaluations for tailored interventions. Those findings lead to recommendations for the development of future digital interventions.
Anti-Thermal Quenching in NdIII Molecular Near-Infrared Thermometers Operating at Physiological Temperatures
Authors: Neto Albano , Maldonado María José , Farías-Carreño Patricia , Gil Yolimar , Vega Andrés , de Santana Ricardo , Aravena Daniel , Brites Carlos , Carlos Luís , Vetrone Fiorenzo , Fuentealba Pablo
Published: January 2025

This work showcases the first evidence of the anti-thermal quenching effect on neodymium(III) molecular thermometers working in biological windows within the physiological temperature range. A mononuclear complex, [Nd(L)(NO3)3] (1Nd), where L is a macrocyclic ligand, was synthesized and used as a precursor to develop two novel species: a dinuclear complex, [(Nd(L)(NO3))2(µ-BDC)](NO3)2·H2O (2Nd), linked by 1,4-benzenedicarboxylate (BDC), and a hexameric complex, [(Nd(L))(µ-BTC)(H2O)]6·35H2O (6Nd), formed via linkage with 1,3,5-benzenetricarboxylate (BTC). The thermometric properties were studied in the physiological temperature range (292–332 K), utilizing excitation with an 804 nm laser (first biological window) and monitoring emission bands in the second biological window (908, 1065, and 1340 nm) associated with the 4F3/2→4I9/2, 4I11/2, 4I13/2 transitions, respectively. The thermometric performance was evaluated through deconvolution of the 1065 nm band and the 1065/1340 nm emission ratio. Among the complexes, the hexamer 6Nd exhibited exceptional performance, with Sr of 2.4%K− 1 at 293 K, when LIR of two components was used, positioning it as a high-performance NdIII-based thermometer. All complexes displayed anti-thermal quenching behavior, surpassing the current molecular-based thermometers in the near-infrared region. Theoretical calculations using CASSCF and Boltzmann population models between Kramers doublets of the 4F3/2 level were performed to rationalize the anti-thermal behavior.
Effect of Age and Sex on Vital Signs in dromedary camels (Camelus dromedarius) in the Al-Shwaak Region, Gadarif State, Sudan
Authors: Mohammed Abdullah A.A. , AHMED Musa , Abdel-Rahman Fatima Ezz El-Din , Gabriel Ghufran Abkar , Tola Mohammed Motasum Abass , Maki Mnhal NorrAldeen , Al-Hussein Omar Muhammad Omar , Jabbar Zamzam Hajaj Abdul
Published: January 2025

The dromedary camel (Camelus dromedarius) is renowned for its adaptability to arid and semi-arid environments, making it a cornerstone of livelihoods in these regions. Despite its ecological and economic importance, research on the impact of intrinsic factors, such as age and sex, on camel vital signs remains scarce, particularly in traditional management systems. This study aimed to explore these influences in the Al-Shwaak region of Gadarif State, Sudan. A cross-sectional, descriptive-analytical design was employed from August to September 2024. The study population comprised 230 camels sampled from local livestock markets, reflecting diverse age groups and sexes. Camels were categorized into juveniles (less than five years) and adults (five years or older) to assess age-related differences, and further stratified by sex to examine combined and independent effects on vital signs. Standardized methods were used to measure physiological parameters, including body temperature, pulse rate, respiratory rate, and capillary refill time (CRT). Body temperature was taken with a digital thermometer, pulse rate was determined via arterial palpation or heart auscultation, respiratory rate was assessed by counting chest rises, and CRT was measured through mucous membrane observation. A stratified random sampling approach ensured representative data. Results highlighted significant age-related variations in vital signs. Juveniles exhibited higher body temperatures (37.9°C) than adults (37.5°C), while the overall mean physiological parameters were a body temperature of 37.8°C, pulse rate of 32.25 beats per minute, respiratory rate of 15.6 breaths per minute, and CRT of 2.7 seconds. These findings offer valuable baseline data for monitoring camel health in traditional systems. This study underscores the importance of age- and sex-specific physiological variations in camels, providing critical insights for optimizing health monitoring, husbandry practices, and productivity in camel-rearing systems. By addressing these intrinsic factors, the findings promote sustainable camel production in arid and semi-arid ecosystems.
Relationship between anti-Epstein-Barr virus early antigen diffuse type and restricted type immunoglobulin G antibodies and disease activity and autoantibodies in rheumatoid arthritis a retrospective observational study
Authors: Kitamura Noboru , Nagasawa Yosuke , Akiya Kumiko , Inomata Hirotake , Nakamura Hiddeki
Published: January 2025

Background
This study aimed to examine the relationship of Epstein-Barr virus (EBV) in rheumatoid arthritis (RA) by evaluating disease activity and autoantibody levels in positive and negative cases using the anti-EBV early antigen diffuse type and restricted type (EA-DR) immunoglobulin G (IgG) antibody.
Methods
Patients undergoing RA treatment at our hospital with anti-EBV EA-DR IgG antibodies were selected. We confirmed their age, sex, RA duration, disease activity, laboratory findings, treatment details, and complications in patients with positive or negative anti-EBV EA-DR IgG antibodies and analyzed the relationship between RA activity, autoantibody production, and EBV.
Results
anti-EBV EA-DR IgG antibodies were measured in 70 RA cases (30 positive and 40 negative), with a positivity rate of 43.9%. Among the positive cases, 18 underwent EBV deoxyribonucleic acid polymerase chain reaction, with 14 testing positive. Univariate analysis revealed significantly higher levels of disease activity score in 28 joints with C-reactive protein, peripheral blood lymphocyte count, anti-cyclic citrullinated peptide antibody (ACPA), and rheumatoid factor in anti-EBV EA-DR IgG antibody-positive cases. Multivariate analysis identified peripheral blood lymphocyte count and ACPA levels as significant factors.
Conclusions
Patients with RA who tested positive for anti-EBV EA-Dr IgG antibodies had significantly higher ACPA than those who tested negative.
Is LPBSA the Future of Cancer Diagnosis? Exploring Machine Learning and Nature-Inspired Algorithms for Liver, Breast, and Lung Cancer Detection
Authors: dana  , Tarik
Published: January 2025

Cancer diseases are remaining a leading cause of death in all over the world, this is encouraging the development of advanced diagnostic systems for reliable and accurate detection. The current study investigates the models of traditional machine learning and nature-inspired algorithms for classifying liver, breast and lung cancer cases utilizing structured datasets. More focuses of this research will be on the performance evaluation of five nature-inspired optimizer algorithms like Learner Performance-Based Behavior with Simulated Annealing (LPBSA), Learner Performance-Based Behavior (LPB), FOX Algorithm (FOX), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT). Among these models LPBSA performing the best, consistently obtained the highest accuracy of 92%, sensitivity 94% and specificity 90%, with confusion matrices reflecting minimal false negative and positives. This work contributes to growing adoption of popular algorithms for enhancing healthcare diagnosis and LPBSA can be utilized in other field investigations.
The temporal and spatial dynamic characterization of intestinal microbiota in Taihe Silky Fowl
Authors: Li Wentao , Guo Haoneng , Wu Youping , Wang Yizhen , Lu Zeqing
Published: January 2025

Background
Through large-scale sampling and 16S sequencing at 8 timepoints and 3 intestinal regions (288 samples), this study aimed to systematically elucidated the dynamic characterization in intestinal microbiota and core microbiota of Taihe Silky Fowl, providing a theoretical basis for precise regulation of native microbiota in this precious Chinese local breed through nutritional means.
Results
The results showed that the alpha and beta diversity of intestinal microbiota changed significantly with the different age and intestinal regions. In alpha diversity, Ace index and Shannon index: cecum > rectum > duodenum; Simpson index: cecum > rectum and duodenum. In beta diversity, compared to the duodenum and rectum, cecum samples were more concentrated. The core phylum (top 5) of Taihe Silky Fowl was Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, and Cyanobacteria. The core genus (top 10) was Lactobacillus, Bacillus, Escherichia-Shigella, Alistipes, norank_o__Clostridia_UCG-014, Bacteroides, Faecalibacterium, norank_f__Ruminococcaceae, Enterococcus and Streptococcus. As age increased, the cecal microbiota degree centrality rapidly increased from 0 to 1 weeks old, then rapidly decreased from 1 to 2 weeks old and remained relatively stable from 2 to 21 weeks old, while the betweenness centrality was opposite. Closeness centrality decreased continuously with increasing age. The cecal microbiota function varied at different age, the central functions were nucleic acid metabolism and protein synthesis in 0 weeks old, carbohydrate metabolism and quorum sensing in 9 weeks old.
Conclusions
In conclusion, the structure, composition, and function of intestinal microbiota in Taihe Silky Fowl dynamically changed with age and intestinal regions.
SEMANTIC AND SYNTACTIC PROPERTIES AND COMMUNICATIVE AND PRAGMATIC FUNCTIONS OF VOCALIZED SENTENCES IN MEDIA TEXT
Authors: Bondarenko Olena , Sydorenko Olha
Published: January 2025

The article reveals the semantic and syntactic properties and communicative and pragmatic functions of vocalisations in media texts. The application of a comprehensive methodology for the study of one-part sentences on the basis of the functional-communicative approach has allowed us to determine that among the one-part noun sentences functioning in media speech, vocalisations have the greatest functional potential in the communicative structure of the media text, acting as a means of unfolding the dialogicity of the journalistic text, introducing the category of addressability into the broader context of the communicative situation. On the basis of the functional semantics of the predicate syntax, the following social and communicative types of addressing of a media message have been identified: general addressing (mass addressee, generalised, socially undifferentiated); specific addressing (real addressee, socially differentiated, personally designated); conditional addressing (imaginary addressee, metaphorically personified). General official addressing prevails in media texts. Communicative and pragmatic groups of vocative sentences include the following semantic models: 1) etiquette sentences; 2) classification sentences; 3) characterisation sentences. Vocative sentences are equally characterised by appeal, etiquette, imperative, identification, emotive functions with a slight weakening of the phatic function.
INTERTEXTUALITY AS A CONTENT-BASED FACTOR IN S. RUSHDIE'S NOVEL "THE GOLDEN HOUSE"
Authors: Chornyi Roman
Published: January 2025

This article explores the role of intertextuality as a major semantic element in Salman Rushdie's eleventh novel The Golden House. Intertextuality is one of the key features of modern literature, which has gained great importance in the context of globalization and postmodern approaches of text creation. In the context of the modern cultural environment, which is saturated with various semantic streams, intertextuality acts as a tool for expanding the semantic boundaries of a work and establishing a dialogue between different art forms, stories, and ideas. In the novel The Golden House this is achieved through constant references to literature, mythology, cinema, and politics. This technique allows not only to interpret new meanings but also to establish cultural and historical connections that resonate with contemporary readers. This paper explores how elements of intertextuality function not just as decorative references but as essential components of the story, shaping character and plot development. The main focus is on highlighting intertextuality as a meaningful factor in the novel mainly through the study of connections: with historical events and figures, both past and present(politicians, artists); with cinema (the film The Godfather, the use of cinematic techniques); with literary sources (from the Bible to DC comics). Ultimately, this study highlights the ways in which intertextuality enhances the novel's engagement with modernity, globalism, and the complexity of human experience in an era of cultural fragmentation.
SOME PECULIARITIES OF WRITTEN TRANSLATION OF ENGLISH-LANGUAGE FAIRY TALES
Authors: Chulanova Halyna , Bondareva Anna
Published: January 2025

The article explores the peculiarities of written translation of English-language fairy tales, focusing on preserving their artistic style, wordplay, and cultural elements. Particular attention is given to the works of Lewis Carroll, especially Alice's Adventures in Wonderland, which exemplify textual complexity, absurd humor, and symbolism. The article examines the challenges faced by translators, including the adaptation of culturally marked elements, idioms, and symbols, as well as maintaining the rhythm and stylistic features of the text. Key translation techniques, such as transformation, compensation, and adaptation, are discussed as tools to preserve the authenticity of the text and make it comprehensible to Ukrainian readers. The translation of fairy tales is considered an instrument of intercultural exchange and the promotion of literary heritage, fostering the integration of national traditions into the global cultural space.
Impactos da Pandemia de COVID-19: Desafios e Expectativas de Pessoas com Deficiência Visual no Mercado de Trabalho
Authors: Balsanulfo Santiago Afonso , Zaidan Gomes Monica , Maia de Siqueira José Ricardo , Veiga da Costa Marques José Augusto
Published: January 2025

O mercado de trabalho passou por uma crise nos níveis de empregabilidade em razão da pandemia de COVID-19, com efeitos significativos no desenvolvimento econômico dos países. Dentre os grupos de trabalhadores impactados, aparecem as pessoas com deficiência visual (PcD), cujos riscos são mais elevados pelo reconhecimento tátil no contato com possíveis objetos e aproximação com pessoas contaminadas. A presente pesquisa busca expor o impacto da pandemia no dia a dia e nas rotinas de trabalho das PcD visuais que atuam na área contábil-financeira. Foram feitas 15 entrevistas semiestruturadas com profissionais com baixa visão, cegueira e visão monocular. Os entrevistados acharam positivo o home office, pois houve aumento na qualidade de vida e no tempo para ficar com seus familiares, mas também relataram pontos negativos, como o afastamento social dos colegas, o aumento de carga de trabalho, a dificuldade para fazer atividades físicas e de reabilitação, medo, estresse, ansiedade e outros problemas psicológicos. O estudo contribui para a literatura por descrever como a pandemia afetou as práticas organizacionais e o ambiente de trabalho para PcD visuais. A contribuição prática é fornecer informações sobre as percepções dos profissionais que podem servir de base para a reformulação dos processos organizacionais e de políticas públicas. A contribuição social é auxiliar a romper com crenças, atitudes e comportamentos desfavoráveis à inclusão das PcD visuais na sociedade, em especial no mercado de trabalho contábil-financeiro, por meio do combate a desinformação e ao preconceito.