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Detecting subclinical cardiotoxicity during immune checkpoint inhibitor therapy: a combined GLS and ECG repolarization analysis
Full text linkPurpose: Immune checkpoint inhibitors (ICIs) can induce subclinical cardiac dysfunction that often goes undetected by conventional monitoring. This study evaluated whether echocardiographic global longitudinal strain (GLS) and electrocardiographic (ECG) repolarization parameters could detect early, subclinical cardiotoxicity in patients with cancer and without pre-existing cardiovascular disease undergoing ICI therapy. Methods: A observational cohort study included 74 patients with cancer treated with ICIs between January 2023 and August 2024. Echocardiographic GLS measurements and detailed ECG analyses were performed at baseline and repeated at 6 months. Cardiotoxicity was defined as a significant reduction in GLS or left ventricular ejection fraction. Correlations between GLS and ECG repolarization parameters were statistically assessed. Results: At 6 months, significant subclinical myocardial impairment was observed, with GLS decreasing from 19.40 ± 1.07% to 17.70 ± 1.62% (p<0.001). Notable ECG changes included increased QT dispersion (40.10 ± 10.55 ms to 50.20 ± 15.30 ms, p=0.001), QTc prolongation (420.45 ± 20.60 ms to 430.75 ± 25.40 ms, p=0.013), increased Tp-e interval (80.21 ± 10.45 ms to 85.30 ± 12.40 ms, p=0.021), and elevated heart rate (72.21 ± 8.40 bpm to 75.35 ± 9.15 bpm, p=0.037). GLS was negatively correlated with QT dispersion (r = -0.845, p < 0.05) and Tp-e intervals (r = -0.478, p = 0.052). Conclusion: GLS and ECG repolarization parameters, particularly QT dispersion and Tp-e intervals, effectively detect subclinical myocardial dysfunction in patients with cancer undergoing ICI therapy. These findings underscore the importance of comprehensive cardiac monitoring to enable early intervention and mitigate cardiotoxicity risk during immunotherapy
Sodium Alginate Carboxymethyl Cellulose Composite Hydrogel Beads for Oral Drug Delivery
No full textBiopolymer-based hydrogels exhibit strong potential for drug delivery applications due to their biocompatibility and ability to achieve various drug release profiles by modifying the polymeric matrix. Among the different delivery routes, oral administration remains the most preferred due to its convenience and high patient compliance. This study aims to synthesize and evaluate composite hydrogel beads for oral drug delivery, using paracetamol as a model drug. Hydrogel beads were prepared using sodium alginate of different viscosities, as well as composite formulations combining sodium alginate and carboxymethyl cellulose (CMC) at varying polymer concentrations. Calcium chloride was employed as an ionic crosslinking agent. The synthesized hydrogels were characterized using Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and X-ray diffraction (XRD). Surface morphology was examined via scanning electron microscopy (SEM). Additionally, the average weight, dimensions, and pH-dependent swelling behavior (in distilled water, PBS pH 7.0, and pH 5.8) were evaluated. The results showed that hydrogel swelling was influenced by environmental pH. Composite hydrogels demonstrated higher drug loading capacities compared to native sodium alginate hydrogels. Drug release studies revealed enhanced release rates in composite formulations, with the release mechanism following the Korsmeyer–Peppas model, indicating diffusion-controlled release. These findings suggest that the developed hydrogels are promising candidates for oral drug delivery, pending further in vivo evaluation
Classification of data anonymization techniques
No full textIn a world where data is becoming more valuable, finding new ways to keep our privacy safe against the tide of tech progress is more important than ever. This chapter dives deep into the world of anonymizing data in plain sight, blending deep thought with real-world uses, especially when it comes to the innovative industries of today and digital security. The chapter delves into the entire realm of data anonymization, encompassing basic techniques such as masking and expanding data, as well as intricate methods such as mathematically guaranteeing privacy and encrypting data while maintaining its usability. The discussion also focuses on how artificial intelligence (AI) is changing the game, making data anonymization more accessible. When talking about the new industrial revolution, it highlights how crucial AI is for making things run smoothly, from the Internet of Things to factories of the future, all while keeping our digital selves under wraps. Moreover, the chapter walks through the minefield of moral and legal rules, stressing the double challenge of following laws like the General Data Protection Regulation and California Consumer Privacy Act and the moral duty to keep individual privacy intact. It thoughtfully weighs the balance between keeping privacy sacred and making the most of data for the good of society and business. This key piece of work weaves together the theory and practice of making data anonymous, shining a spotlight on the vital role of AI and the need to keep evolving to meet the privacy challenges of our digital age. It sets the stage for more studies, policymaking, and ethical discussions on keeping our data safe, showing just how essential these strategies are in our data-soaked world
Selection of a dam site by using AHP and VIKOR: The Sakarya Basin
Full text linkArticle number : 20250175
CODEN : OCPHCThe Sakarya Basin is an important area for water resources and dams in the Northern Anatolia Region, and it also draws attention due to its high population density. Within this context, it is crucial to consider specific criteria such as natural influences and topographic features in the selection of dam sites. This study aims to propose an effective methodology for selecting a site for a new dam in a first-degree earthquake zone, which constitutes the main challenge in the site selection process. The locations of seven dams situated in the Northern Anatolia Earthquake Zone have been evaluated based on six criteria: earthquake, geological and geotechnical properties, valley characteristics, expropriation, environmental impacts, and climate and meteorological conditions. The analytic hierarchy process (AHP) and the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method have been used together as multi-criteria decision-making (MCDM) techniques. The AHP was employed to systematically determine the weights of the criteria based on expert opinions. The VIKOR method provided a foundation for evaluating alternative solutions. The optimal solution closest to the ideal has been achieved. A sensitivity analysis was performed by adjusting the weight of the earthquake criterion, which is of great significance for the study area, by approximately ±10%. The analysis revealed that the criterion weights significantly affect the rankings of the alternative regions. The research findings demonstrate that MCDM can effectively identify the most sensitive areas in the region. It is believed that incorporating the results obtained from MCDM methods into disaster management and urban planning strategies could mitigate the negative impacts of future earthquakes
Securing Identity from Birth: Biometric Fingerprint Algorithms For Robust Childbirth Registration in Ghana
No full textGhana faces persistent challenges in achieving universal birth registration, especially in rural and underserved communities. Traditional paper-based systems remain prone to loss, fraud, and inefficiencies, leaving many children without legal identity and limiting access to critical services such as healthcare and education. This study presents a biometric fingerprint-based childbirth registration system tailored for infants and mothers, designed to integrate with Ghana's national identity framework (Ghana Card). Using a convolutional neural network (CNN)-based fingerprint matching algorithm, our system achieved an identification accuracy of 86.7% for maternal-infant linking during controlled field testing in a selected Chps zone in Aburi, Akwapim South Municipality in the Eastern region in Ghana. The findings demonstrate that early-stage biometric data collection is feasible and reliable within low-resource settings. Ethical consent, data protection, and system misuse were addressed through community engagement protocols and adherence to Ghana's Data Protection Act. The results indicate that implementing a secure biometric registration system can significantly strengthen identity management in Ghana. The study’s primary contribution lies in the development and testing of a context-sensitive biometric algorithm that addresses both technological and infrastructural limitations, offering a scalable and secure model to help Ghana meet Sustainable Development Goal 16.9: ensuring legal identity for all, including birth registration
The comorbidities of hidradenitis suppurativa
No full textHidradenitis suppurativa is a chronic inflammatory disease that dramatically decreases the quality of life of afflicted patients. A number of factors may coexist with hidradenitis suppurativa, including stigmatization, social isolation, tobacco use, alcohol abuse, suicidal ideation, depression, other psychiatric disorders, and medical comorbidities such as obesity, diabetes mellitus, hypertension, dyslipidemia, metabolic syndrome, coronary artery disease, and polycystic ovarian syndrome. These comorbidities should be kept in mind while planning the treatment. A rare but important long-term complication of hidradenitis suppurativa is squamous cell cancer; men with perianal, gluteal, or perineal lesions are at increased risk, and multiple biopsies should be taken in case of any suspicious lesions
Investigation of the Effect of Adding Nitrogen on the Torque Generated by a Four-Cylinder Engine
No full textThe engine's power stroke involves injecting LN2 into the cylinder at the top dead centre, allowing nitrogen and air gas to escape. This process, without combustion, overcomes engine friction losses, enabling intake, compression, and output power. Previous studies have focused on improving diesel engine efficiency by adding materials like hydrogen, NO2, clean gasoline, ammonia, LN2, NO, and NOX and altering engine design and spark plugs. This study explores the potential benefits of liquid nitrogen-fuelled automobile engines despite their past inefficiency and similarity to compressed-air engines due to energy waste. The study underscores the potential of nitrogen gas addition in improving the cleanliness and efficiency of diesel engines, paving the way for further research and advancements. Uses CFD simulations to analyze the impact of nitrogen gas concentration on combustion effectiveness, emissions, and performance metrics of a compression-ignition diesel engine, explicitly focusing on nitrogen oxide and particulate matter emissions and their influence on mixture flow velocity. The addition of nitrogen gas significantly impacts combustion dynamics, altering temperature and pressure patterns. The mass flow rate and velocity are positively correlated, and the crankshaft deforms more rapidly with engine rotational speed. Nitrogen gas concentrations affect deformation and pressure, with higher values observed at 1800 RPM and 2200 RPM. The combustion process can be enhanced by adding hydrogen concentrations, changing engine shapes and designs, or using different fuel types. Nitrogen gas concentrations inversely relate to temperature, with higher concentrations causing lower temperatures, which is consistent with nitrogen gas's primary role in reducing engine temperature. Nitrogen gas concentration is linked to pressure gradients
Evaluating the efficiency of consulting officers in managing the implementation of engineering construction projects in Iraq
No full textThis research examined the engineering projects supervised by Iraqi internal management teams and evaluated the role of consulting firms in this area. The principal elements evaluated in analyzing engineering project execution management tools, methodology, objectives, resources, and success rates were time, cost, quality, and project scope. This research aims to create a detailed inventory of the services, functions, and requirements of the technical control and engineering consulting sectors in relation to national and international standards. This work utilized pertinent data and expert opinions to analyze the operations of consulting companies in Iraq via the Delphi method. The preliminary phase, considering workplace variations, was the creation of a related matrix utilizing local data to determine the relative significance of each component. After evaluating the second phase's data utilizing the Excel-based TOPSIS methodology, the factor ratings were calculated. The AHP-TOPSIS method assessed the ability to reason and resolve difficulties, handle conflicts, additional project expenditures, cost differences across four orders, and financial flow. In assessing variables, here is where the outcomes truly excelled. The research further concludes that the efficiency of consulting officers plays a pivotal role in overcoming the challenges of project execution in Iraq. Their ability to address time, cost, and quality issues directly influences the overall success of engineering construction projects
Numerical investigation of thermal performance enhancement in a newly designed shell and tube heat exchanger using TiO2 nanofluids
No full textThis study investigates the use of titanium dioxide (TiO2) nanofluids to enhance the thermal performance of shell and tube heat exchangers. A comparative computational fluid dynamics (CFD) analysis is conducted using water and a 0.5% TiO2 nanofluid. The heat exchanger is modelled using computer-aided design (CAD), with dimensions closely resembling commercial units. The CFD model is validated through a grid-independence study, with a mesh of 4,112,679 elements yielding grid-independent results. The key findings show that the 0.5% TiO2 nanofluid increases the cold fluid outlet temperature by 11.44% compared to water (36.04°C vs. 33.63°C). The average heat transfer coefficient is enhanced by 12.3% when using the nanofluid. The CFD results are consistent with experimental data, with a maximum deviation of 4.2% in the outlet temperatures. This study demonstrates the successful integration of TiO2 nanofluids with an optimized shell and tube heat exchanger design. The novelty lies in the application of nanofluids to improve the thermal performance of industrial heat exchangers. The presented methodology, combining CAD modelling and CFD analysis, provides a foundation for further optimization and experimental validation of nanofluid-enhanced heat transfer systems
A machine learning and DFT assisted analysis of benzodithiophene based organic dyes for possible photovoltaic applications
No full textWe present a synergistic approach to combine Machine Learning (ML), Density Functional Theory (DFT), and molecular descriptor analysis for designing high-performance benzodithiophene (BDT) based chromophores. A dataset of 366 BDT incorporated moieties is compiled from literature while their molecular descriptors are designed by using Python programming language. Linear and Random Forest Regression models produces best results to predict their exciton binding energy (Eb) with their R-Squared (R2) value 0.87 and 0.94 respectively. Their DFT calculations provides additional features, including molecular charges. Their ML models also reveals that their Eb values are a crucial predictor for their photovoltaic (PV) performance as its lower value could facilitate efficient charge carrier separation. For this, their hydrogen bond acceptors (HBA) and topological polar surface area (TPSA) emerges as key descriptors during their regression analysis. Their DFT validation shows negligible differences in their molecular charges to suggest their electron donor/acceptor moieties can significantly impact their chromophore nature. The current research work is helpful for efficiently screening the suitability of organic chromophores for their PV applications through advanced computational tools