Publication Management System
Not a member yet
3916 research outputs found
Sort by
Polymer Nanocomposite Coatings for CO2 Pipeline Corrosion Control: A Comprehensive Review
Full text linkCarbon dioxide (CO2) is the most significant greenhouse gas, accounting for 77% of global warming and is produced by the combustion of fossil fuels in industries. Carbon capture, storage and utilization (CCUS) is a possible pathway in achieving the emission reduction target set by the Canadian government in 2050. The transportation of the captured CO2 to storage is a critical factor in the CCUS process, which is frequently hindered by corrosion. The impurities in CO2 lead to corrosion risks, which are generally addressed using inhibitors, corrosion-resistant alloys, and polymer coatings in the oil and gas sector. However, CO2 corrosion is more complex than CO2 sweet corrosion. It is difficult to obtain a single inhibitor capable of mitigating CO2 corrosion in pipelines, and corrosion-resistant alloys are too expensive to be used throughout all sections of the pipeline. Polymers are employed as coatings. For gaseous and supercritical CO2, which leads to defects in the coatings, such as blisters and porosity. As a result, researchers have focused on using nanocomposite coatings to control CO2 corrosion. This review paper focused on the interactions of CO2 with impurities on polymer and polymer nanocomposites. In particular, the most commonly used clay and graphene polymer nanocomposites coatings and their interactions with CO2 were discussed. Further, the transport properties of CO2 through polymers and polymer nanocomposites and the interaction mechanism were analyzed. The paper concludes with the processing methods used for the polymer and polymer nanocomposite coatings
Advisory Opinions under Protocol No. 16 to the ECHR. A Theoretical and Empirical Analysis of the Legal Nature of the ‘Questions of Principle’
Full text linkOne of the most significant legal arguments against the ratification of Protocol No. 16 to the European Convention on Human Rights (ECHR) is that advisory opinions issued by the European Court of Human Rights (ECtHR) would pose a threat to national sovereignty and judicial discretion. Several counterarguments have already been examined by scholars. The counterargument that will be demonstrated here is that advisory opinions cannot pose a threat to national sovereignty or judicial discretion because they are issued on ‘questions of principle’. In other words, this means that the requesting domestic highest courts or tribunals keep sufficient margin of discretion, when it comes to the concrete case brought before them. Such hypothesis will be demonstrated from a theoretical perspective, reflecting upon the legal concept of ‘principle’; and through an empirical analysis of the advisory opinions issued so far by the ECtHR. Demonstrating the hypothesis would be relevant in order to allow the States to understand that the ratification of Protocol No. 16 would not pose any threat to the discretion of domestic Courts, neither in theory nor in practice
Exploring the Spatiotemporal Evolution and Influencing Factors of Shooting Incidents in the United States
Full text linkDrawing on data from the Gun Violence Archive, this study employs mathematical statistics, spatial analysis, and regression analysis to investigate the essential characteristics, spatiotemporal distribution, and influencing factors of shooting incidents in the United States from 2014 to 2023. The key findings are as follows:1) Demographically, the victims of shootings are predominantly male and older youths. Notably, indirect victimization is more prevalent among older youths, non-white youths (especially African American youths), those from higher-income households, and urban residents. 2) Temporally, there has been a rising trend in U.S. shootings over the decade from 2014 to 2023, with a pronounced increase during the pandemic period of 2019-2023. On a monthly basis, the incidence of shootings peaks from May to July. 3) Spatially, shooting incidents are largely concentrated in coastal regions, decreasing in frequency towards inland areas. Hotspots for shootings include states such as Texas, California, Louisiana, and Florida, followed by Indiana and New York.4) Various factors significantly influence the occurrence of shooting incidents, including family environment, ethnocultural context, residential conditions, business economy, and economic indicators
Effects of Birth Delivery Mode and Antibiotic Use on Gut Microbiota in Preterm Newborns: A Cohort Study
No full textBackground: The establishment of the gut microbiome begins very early in life. Bacterial colonization is influenced by several factors, especially the mode of delivery and antibiotic intake. In this study, we examined the composition of the neonatal gut microbiota within the first three weeks after birth, focusing on the impact of delivery mode and antibiotic use.
Methods: This cohort study included 29 preterm newborns recruited between the first and second day of life at the National Reference Center for Neonatology and Nutrition. Stool samples were collected from diapers and stored at 4°C for up to 6 hours before being stored at -80°C until analysis. The gut microbiota was identified using RT-PCR targeting four phyla: Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria.
Results: The comparison of gut microbiota by delivery mode shows that the microbiota of newborns delivered by cesarean section was less diverse than that of those delivered vaginally. During the first 48 hours of life, Enterobacteriaceae, including Escherichia coli, were predominantly present in vaginal births, while Enterococcus spp. (25%), Staphylococcus spp. (20%) and Lactobacillus spp. (5%) were present only in vaginal births. From the second week onwards, Bacteroides fragilis (15%) and Bifidobacterium spp. (10%) were mainly present in vaginal births. By the end of the third week, Enterobacteriaceae and Enterococcus spp. were present in all newborns. All newborns received empiric antibiotic therapy upon admission, with 41% receiving antibiotics for more than 5 days.
Conclusion: This study made it clear that microbiota requires time to progress inside the newborn's intestine, depending on the birth mode, either natural or cesarean section
Efficacies of PGF2α, Ovsynch, and CIDR Protocols on Synchronization of Estrus in Buffaloes: A Comparative Study
Full text linkThe present study aimed to compare the efficacies of PGF2α, GnRH, and CIDR on estrus synchronization of native buffaloes in Bangladesh. A total of 93 buffaloes of second to fifth parity were treated either with PGF2α, Ovsynch, or CIDR protocol. In the PGF2α experiment, buffaloes were treated with either 500 μg (n=20) or 875 μg (n=20) of cloprostenol, and artificial inseminations (AI) were done at 72 hrs after PGF2α injection. In the Ovsynch protocol, buffaloes were treated with 200 μg (n=11) or 350 µg (n=16) of GnRH at day 0, followed by 875 µg of PGF2α at day 7, and again 200 μg or 350 µg of GnRH at day 9, and AI was performed at 16 hrs after the second GnRH administration. In the CIDR protocol, a CIDR implant was placed intravaginally for 12 days with either 500 μg (n=13) or 875 μg (n=13) of cloprostenol at 24 hrs before the removal of the CIDR, and AI was performed at 72 hrs after the removal of the CIDR. The results showed that estrus response and conception rates did not differ significantly between PGF2α and GnRH protocols. Higher doses of PGF2α and GnRH did not result in any significant increase in estrus response in buffaloes. CIDR induced estrus in all buffaloes in both doses of PGF2α. Estrus rate was significantly higher (P=0.035) in buffaloes of the CIDR protocol than in the PGF2α and Ovsynch groups. Conception rates of buffaloes did not differ significantly (P=0.823) among the protocols. The calving rates were higher (P=0.278) in buffaloes synchronized with CIDR than in PGF2α and Ovsynch groups. The costs of materials per buffalo synchronized, conceived, and calved were higher in the CIDR protocol and lower in the PGF2α than in other protocols. However, considering all the expenses and calving rates, costs per buffalo calves were cheaper in the CIDR group with a higher dose of PGF2α. In conclusion, CIDR can be applied to increase the reproductive efficiency of buffaloes
Buffalo Healthcare Management Practices in India
Full text linkBackground and Aim: Dairy farming is one of the most important sub-sectors of the Indian farming system. Healthcare management practices play a crucial role in realising the full potential of dairying. Hence, the present study aims to analyse the adaptation of healthcare management practices by the buffalo farmers in the Punjab state of India.
Materials and Methods: A sample size of 397buffalo farmers from three different agro-climatic zones —i.e., Shivalik Foothills, South-West Dry, and Central Plains—was selected using a multistage sampling technique for the year 2019. Descriptive statistics and the Chi-Square test are used for analysis.
Results: Most buffalo farmers adopt general healthcare management practices such as vaccinating their buffaloes against Foot and Mouth Disease and use of anti-parasites for tick eradication, but they are not disinfecting the dairy shed at all. The farmers follow calf and udder healthcare management practices, such as providing bedding material to newborn calves, deworming calves, and udder cleaning. The chi-square test indicates a significant difference across categories regarding the adaptation or non-adoption of certain healthcare practices, such as the source of vaccination, tick solution, bedding material for calves, and deworming of calves.
Conclusion: Buffalo health is not only a veterinary concern but also a socio-economic imperative. While certain healthcare management practices are universally embedded among the farmers, others are constrained by access, awareness, and resource availability, thereby introducing important equity considerations
Global Warming as a Crime against Nature: Identifying the Principal Offenders
Full text linkThis article employs a literature-based methodology, utilising green criminology literature and case examples to examine global warming through the framework of green criminology to assess whether contributions to global warming can be considered a ‘crime against nature’ due to their extensive environmental harm. Such environmental degradation aligns with the concept of ‘ecocide’, which criminalises acts that contribute to extensive damage or loss to the Earth’s ecosystems. The analysis identifies states and corporations as principal perpetrators, highlighting how fossil fuel industries contribute to global warming through environmentally detrimental practices and climate misinformation campaigns. Simultaneously, the actions of the state, such as obstructing climate change policies and appointing industry-affiliated personnel to key regulatory positions, exacerbate the climate crisis. While individual consumer behaviours are also contributory, these actions are largely constrained by the systems that are heavily influenced by state-corporate interests. Reframing global warming as a crime against nature highlights the urgent need for legal accountability and systemic reform to address the climate crisis. Recognition of ‘ecocide’ by the International Criminal Court would enable corporate and state actors to be held accountable for their harmful contribution to global warming
Gender Prediction from Angular and Linear Parameters in Cranium Lateral View by using Machine Learning Algorithms: A Computed Tomography Study
Full text linkThe purpose of the study was to predict a gender by using Machine Learning Algorithms (MLA) with variables of the lateral view of the cranium from Computed Tomography (CT) images.
A total of 5 parameters (3 linear and 2 angular) of the lateral view of the cranium were evaluated on CT images of 200 female and 200 male adult individuals in the present study. These parameter measurements were analyzed with MLA and Logistic Regression (LR), Random Forest (RF), Linear Discriminant Analysis (LDA), K-Nearest Neighborhood (KNN) and Naive Bayes (NB) models were used. Accuracy (Acc), Sensitivity (Sen), Specificity (Spe) and F1 scores (F1) were used as the evaluation criteria in the study.
As a result of MLA, the Acc ratio was found to be 0.77 for the KNN algorithm, 0.84 in the NB algorithm, 0.85 in the LDA algorithm, 0.70 in the RF algorithm and 0.81 in the LR algorithm. As a result of the analysis, 0.85 Acc, 0.85 Sen, Spe 0.85 and 0.85 F1 values were found in the LDA algorithm with the highest accuracy. When the significance level of the variables in the study was examined, it was found that variable A had the best effect.
It was found that the MLA used for the variables of the lateral view of the cranium yielded high accuracy regarding gender and the LDA Model was effective in predicting gender
Development and Validation of a Brief Instrument to Evaluate Primary-Care AMI Management in Mexico
Full text linkThis descriptive cross-sectional study developed and validated an instrument to evaluate the initial management of acute myocardial infarction (AMI) at the primary-care level in Mexico. The instrument was constructed from the Mexican Social Security Institute Infarction Code and the national Clinical Practice Guideline, extracting core elements for first-contact AMI care. Expert judgment guided item selection using the Rovinelli and Hambleton approach, and items with Aiken’s index ≥0.70 were retained. A pilot test with 35 primary-care physicians assessed the preliminary version. The field sample comprised 143 physicians from the 17 municipalities of Tabasco, selected by convenience sampling. Reliability was estimated with Cronbach’s alpha. The pilot version showed α=0.636; after expert validation and refinement—including the addition of two items (on fibrinolytic dosing in adults ≥75 years and post-fibrinolysis protocol)—the final 10-item instrument achieved α=0.817. Corrected item–total correlations improved notably for item 2 (from 0.243 to 0.544), while items 5 and 8 showed the highest values in the final version. Factorability was adequate (KMO = 0.736; Bartlett’s χ²(36) = 83.609, p < 0.001). This brief, context-specific tool shows solid internal consistency and expert-supported content validity for primary-care AMI management; structural and criterion (predictive) validity should be further confirmed
Adversarial Machine Learning in Healthcare: Risks to AI-Driven Diagnostics and Treatment Plans
Full text linkThe rapid integration of artificial intelligence (AI) in healthcare has enhanced diagnostics, predictive analytics, and clinical decision-making. However, AI-driven models, particularly deep learning architectures, remain highly vulnerable to adversarial machine learning (AML) attacks, which can result in misdiagnoses, unsafe treatment recommendations, and compromised patient safety. This study systematically evaluates adversarial risks in medical AI, quantifies their impact on model performance, and assesses the efficacy of defense mechanisms. We analyzed CNNs (medical imaging), RNNs (ECG analysis), and Transformer models (clinical NLP) under FGSM, PGD, and JSMA attacks. Results show that the CNN accuracy of 92% was reduced to 40% under JSMA, ECG-based AI performance dropped by 42% under PGD, and Transformer-based NLP models experienced a 30% decline under FGSM. Defense mechanisms such as randomized smoothing and adversarial training improved accuracy by 15% and 14%, respectively, though at high computational costs (1.8× and 1.5× training overhead). Across five independent trials, all degradations were statistically significant (p< 0.01), and ANOVA with Tukey’s HSD confirmed that randomized smoothing and adversarial training significantly outperformed gradient masking (p< 0.01). These findings demonstrate that medical AI systems are highly susceptible to adversarial manipulation and underscore the necessity of robust, efficient, and regulatory-compliant defenses. Strengthening adversarial resilience is critical to ensuring safe, reliable, and ethically responsible deployment of AI in healthcare