bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Health Literacy and Patient Activation Levels Among Patients with Glaucoma: A Cross-Sectional Study
Authors: Tsichla Lοukia , Patelarou Evridiki , Detorakis Efstathios , Tsilibaris Miltiadis , Patelarou Athina , Christodoulakis Antonios , Dokoutsidou Eleni , Giakoumidakis Konstantinos
Published: November 2024

Background: Chronic diseases are major causes of morbidity, disability, and death worldwide. In many cases, they are potentially preventable and treatable. Glaucoma is one of the leading causes of morbidity and blindness, and its early recognition can help reduce the adverse outcomes of the disease. Health illiteracy among these patients and the absence of self-management of these dis-eases are barriers to effective management worldwide. Therefore, the present study aimed to calculate the level of health literacy and activity level of patients’ activation in self-management, and to explore the link between them among patients with glaucoma in outpatient clinics.
Material and methods: Convenience sampling of patients with glaucoma attending the outpatient ophthalmology clinics of a university hospital in Heraklion-Greece was performed. Convenience sampling was used to recruit a total of 312 participants. Data were collected between November 2023 and May 2024. The Patient Activation Measure-13 (PAM-13) questionnaire, in its Greek ver-sion, was used to evaluate patients’ activation level in self-management, whereas the Greek ver-sion of the European Health Literacy Survey Questionnaire 16 (HLS-EU-16) was used to assess health literacy.
Results: Participants were classified as level 1(disengaged & overwhelmed) level in self-management (= 40.7, SD: ±29.9) and a sufficient health literacy level (= 10.7, SD ±3.7). However, there was no statistically significant relationship between health literacy levels and patient activation in self-management (p=0.602).
Conclusions: Our findings indicate that patients with glaucoma have low to moderate levels of health literacy and self-management activation, further there is no significant association between these two factors. Multifaceted interventions could be essential for enhancing patients’ activation. Further research involving larger sample sizes, multi-center studies, and interventional design is needed.
Incidence and Predictors of Acute Kidney Injury Following Advanced Ovarian Cancer Cytoreduction at a Tertiary UK Centre: An Exploratory Analysis and Insights from Explainable Artificial Intelligence
Authors: Ratcliffe Elizabeth , Devlin Ciara , Munot Sarika , Broadhead Timothy , Thangavelu Amudha , Quaranta Michela , Nugent David , Kalampokis Evangelos , Jong Diederick De , Laios Alexandros
Published: November 2024

Background/Objectives: The incidence of acute kidney injury (AKI) following advanced epithelial ovarian cancer (EOC) surgery has not been extensively studied. This study aimed to investigate the incidence of AKI and identify preoperative and intraoperative predictors in patients undergoing advanced EOC cytoreduction using both traditional statistics and Artificial Intelligence (AI) modelling. Methods: Retrospective data was collected for 134 patients with a suspected or confirmed diagnosis of advanced EOC (FIGO Stage III-IV) who underwent surgical cytoreduction between January 2021 and December 2022 at a UK tertiary referral centre. AKI was diagnosed according to the KDIGO criteria. Data on 22 patient variables were extracted, including age, Charlson Comorbidity Index (CCI), procedure length, surgical complexity, and length of hospital stay. Logistic regression analysis was used for feature selection to identify AKI predictors, and an extreme gradient boost (XGBoost) model was applied to all variables related to AKI events. Results: The incidence of postoperative AKI was 6.72% (n=9). Predictive factors for AKI included younger age (OR = 0.942, p=0.037), lower CCI (OR = 0.415, p=0.015), longer procedure duration (OR = 1.006, p=0.019), and greater surgical effort (OR = 1.427, p=0.007). Patients with perioperative AKI experienced a doubling in the length of hospital stay (p=0.008). Mortality rates were similar between patients with and without AKI. AI-driven algorithms highlighted the complexity of AKI prediction and provided individual risk profiles, enabling future stratification and prompting different frequencies of AKI monitoring following cytoreduction. Conclusions: Predicting AKI is a complex task. This study found a lower-than-expected incidence of AKI following advanced EOC cytoreductive surgery. AKI is linked to heightened surgical risk-taking, underscoring the need for improved guidelines focusing on postoperative monitoring for targeted patients. Artificial Intelligence offers the potential for personalized AKI prediction.
Exploring Literacy and Knowledge Gaps and Disparities in Genetics and Oncogenomics Among Cancer Patients and the General Population: A Scoping Review
Authors: Nikitara Katerina , Cardoso Maria Luis , Vicente Astrid , Batalha Silva Rasga Célia Maria , De Angelis Roberta , Morel Zeina Chamoun , De Nicolo Arcangela , Nomikou Maria , Karamanidou Christina , Kakalou Christina
Published: November 2024

BACKGROUND: Genetic and genomic literacy is pivotal in empowering cancer patients and citizens to navigate the complexities of omics sciences, resolve misconceptions surrounding clinical research and genetic/genomic testing, and make informed decisions about their health. In a fast-evolving scenario where routine testing has become widespread in healthcare, this scoping review aimed to identify current literacy and knowledge gaps among cancer patients and citizens on matters related to genetics and genomics. METHODS: Adhering to the PRISMA framework, the review included 43 studies published between January 2018 and June 2024, which evaluated the understanding of genetics and genomics among cancer patients, caregivers, and citizens. RESULTS: Although the selected studies had significant heterogeneity in populations and evaluation tools, our findings indicate inadequate literacy levels, with citizens displaying lower proficiency than cancer patients and caregivers. The review highlighted consistent knowledge gaps in understanding the genetic and genomic underpinnings of diseases, encompassing misconceptions about mutation types and inheritance patterns, limited awareness of available genetic testing options, and difficulties in interpreting test results. Ethical and privacy concerns and the psychological impact of genetic testing were also common, highlighting the imperative need for effective communication between healthcare providers and patients. CONCLUSIONS: Given the dynamic nature of genomic science, the review underscores the need for continuously evolving educational programs tailored to diverse populations. Our findings could guide the development of educational resources addressed explicitly to cancer patients, caregivers, and the lay public.
Cosmic Blueprint: The Physical Foundation of the Organizing Principle Behind Matter Self-Assembling, Life, Intelligence, Consciousness, and Evolution
Authors: Chiarelli Piero , Chiarelli Simone
Published: November 2024

In this study, we develop an extremal principle governing the far-from-equilibrium evolution of a system composed of structureless particles, utilizing the stochastic generalization of the quantum hydrodynamic analogy with random curvature wrinkles due to the gravitational background noise (GBN). For a classical phase, where quantum correlations decay over distances shorter than the average inter-molecular separation, the far-from-equilibrium kinetic equation can be formulated as a Fokker-Planck equation. We derive the velocity vector in phase space that maximizes the dissipation of a function analogous to energy, termed stochastic free energy. In quasi-isothermal, far-from-equilibrium states without chemical reactions—where elastic molecular collisions dominate—the maximum SFED reduces to Sawada's principle of maximum free energy dissipation. However, in the presence of chemical reactions or significant thermal gradients, this principle is violated, as additional dissipative contributions emerge, linking the true maximum to stochastic free energy dissipation. The study also shows that Malkus and Veronis's principle of maximum heat transfer is a special case of the theory. Generally speaking. as systems strive for maximum SFED, they progress toward equilibrium by transitioning through increasingly ordered states, facilitating self-organization of matter. Nonetheless, the self-organization in fluids and gases is insufficient to form complex living structures, requiring a series of additional conditions such as the need of solid rheological properties, united to the need of information storing. The work highlights synergistic effects and efficiency-enhancing tendencies driving evolution, revealing new analogies between biological and social systems. Furthermore, it suggests that natural intelligence, as well as the consciousness, are inherent characteristics of the universe's physics, though certain side effects of the natural selection complicate the advancement toward efficiency and prosperity. The theory demonstrates that the ordering process is not continuous but experiences catastrophic events and collapses, which lead to the formation of new, more efficient systems. Finally, contemporary social behaviors are analyzed from the standpoint of the theory, including aspects such as monetary inflation control, economic expansion-recession cycles and the alternation between war and peace, providing insights on how to better address current challenges.
Enhancing Communication Networks in the New Era with Artificial Intelligence: Techniques, Applications, and Future Directions
Authors: El-Hajj Mohammed
Published: November 2024

Artificial intelligence (AI) is transforming communication networks by enabling more efficient data management, enhanced security, and optimized performance across diverse environments, from dense urban 5G/6G networks to expansive IoT and cloud-based systems. Motivated by the increasing need for reliable, high-speed, and secure connectivity, this study explores key AI applications, including traffic prediction, load balancing, intrusion detection, and self-organizing network capabilities. Through detailed case studies, we illustrate AI’s effectiveness in managing bandwidth in high-density urban networks, securing IoT devices and edge networks, and enhancing security in cloud-based communications through real-time intrusion and anomaly detection. Our findings demonstrate AI’s substantial impact on creating adaptive, secure, and efficient communication networks, addressing both current challenges and future demands. Key directions for future work include advancing AI-driven network resilience, refining predictive models, and exploring ethical considerations for AI deployment in network management.
Comprehensive Study on Endocrine Disruptor Removal from Wastewater Using Different Microalgae Species
Authors: García Noelia , Rodríguez Rosalía , Vicente Gemma , Espada Juan J. , Bautista Luis Fernando
Published: November 2024

The concentration of endocrine disruptor compounds (EDC) in wastewater is increasing, posing significant risks to living organisms. This study concerns the simultaneous degradation of a variety of EDCs from wastewater, including methylparaben (MeP), propylparaben (PrP), butylparaben (BuP), benzophenone (BP), bisphenol A (BPA) and estrone (E), in the presence of the microalgae Scenedesmus sp. or Chlorella vulgaris. The potential for abiotic removal of these EDCs and the underlying degradation mechanisms were also studied. The presence of microalgae significantly enhanced the degradation of parabens, achieving complete removal within 7 days, primarily through the mechanism of biodegradation. BPA removal was also improved by microalgae, reaching 82% and 90% within 7 days with Scenedesmus sp. and C. vulgaris, respectively. BP degradation was predominantly abiotic, accomplishing 95% removal in 7 days. E degradation was mainly abiotic, achieving approximately 40% within 7 days, with a notable contribution from a biodegradation mechanism in the later stages, accounting for 27% and 40% of the final total removal in the presence of Scenedesmus sp. and C. vulgaris, respectively. This study provides insights into the mechanism of EDC degradation by microalgae, highlighting the potential of Scenedesmus sp. and C. vulgaris for removing a mixture of EDCs from wastewater.
Integrating ESG Principles into Smart Logistics:Toward Sustainable Supply Chains
Authors: Leogrande Angelo
Published: November 2024

The integration of Environmental, Social, and Governance (ESG) principles into smart logistics represents a transformative approach to supply chain management, offering solutions that address
6critical challenges in sustainability, ethical labor practices, and transparency. With the increasingawareness of climate change, social inequalities, and governance issues, companies worldwide areturning to advanced technologies such as artificial intelligence (AI), big data, blockchain, and theInternet of Things (IoT) to embed ESG principles into their logistics operations. This article exploresthe role of smart logistics in promoting sustainability and aligning supply chains with ESG goals. Ithighlights the environmental aspect by showcasing how AI and big data-driven route optimizationcan reduce fuel consumption and lower carbon emissions. The use of electric vehicles (EVs) andhybrid trucks is also discussed, particularly for last-mile deliveries, as part of efforts to minimize thecarbon footprint of logistics operations. Additionally, smart warehouses equipped with IoT devices,automation, and AI-driven systems significantly contribute to improving energy efficiency andreducing waste, further advancing the sustainability agenda. Social responsibility in the context ofESG is equally emphasized, particularly regarding labor practices in global supply chains.Technologies such as blockchain enhance transparency by allowing companies to trace the origin ofproducts and verify adherence to fair labor standards. AI and data analytics are also crucial formonitoring supplier compliance with social standards, reducing risks associated with unethicalpractices. Governance, the third pillar of ESG, plays a critical role in promoting transparency andaccountability across supply chains. Smart technologies help improve oversight, ensure compliancewith regulatory requirements, and mitigate risks related to corruption and fraud. In conclusion, thearticle underscores the importance of integrating ESG principles into smart logistics as a strategicimperative for companies looking to enhance their competitiveness, resilience, and long-term successin the global marketplace.
Evaluation of the Quality of Results of Lung Cancer Surgery in France Using the PMSI National Database
Authors: Bernard Alain , Cottenet Jonathan , Quantin Catherine
Published: November 2024

Background. Given the complexity of lung cancer surgery, this study aims to provide an overview of hospitals authorised to perform lung cancer surgery in France, and assess their performance focusing on severe post-operative complications and 30-day in-hospital mortality based on the Clavien-Dindo classification (grade>2). Methods. We included all patients (N=64,304) who underwent pulmonary resection for lung cancer from the French hospital database (2019–2023). To quantify variations within regions, we used the ratio of the 90th to the 10th decile of the standardised outcome rate of the hospitals. We used a hierarchical logistic regression model to estimate the adjusted odds ratio (aOR) according to the number of annual procedures. We then used the results of this modeling to see how the standardised rate estimate might evolve after simulating a new organisation of hospitals authorised to perform this surgery. Results. A total of 18,151 patients (28%) had severe complications (Clavien-Dindo>2). Compared to hospital performing less than 100 procedures/year, the risk of severe complications was significantly reduced for hospitals performing between 101 and 250 procedures (aOR=0.83[0.77-0.89]) and more than 250 procedures/year (aOR=0.85[0.77-0.93]). A simulation of hospital reorganisation, using 100 procedures/year as the threshold value shows that this would have prevented 477 severe complications over the period. Conclusion. This study shows inequalities in performance indicators between hospitals in each French region. The influence of the volume of activity raises questions about the need to restructure the offer of care for complex surgeries such as lung cancer surgery.
Biofuel Combustion in Oxy-Thermal Processes for Industrial Furnaces
Authors: Ioana Adrian , Paunescu Lucian , Volceanov Eniko , Constantin Nicolae , Canuta (Bucuroiu) Ionela Luminita
Published: November 2024

The last decades have offered new challenges to researchers worldwide through the problems our planet is facing both in the environment protection field and the need to replace fossil fuels with new environmentally friendly alternatives. Bioenergy as a form of renewable energy is an acceptable option from all points of view and biofuels due to their biological origin have the ability to satisfy the new needs of humanity. By releasing some non-polluting combustion products into the atmosphere, biofuels have already been adopted as additives in traditional liquid fuels, being intended mainly for internal combustion engines of automobiles. The current work proposes an extension of biofuels application in combustion processes specific to industrial furnaces. This technical concern is not found in the literature, except for achievements of the research team involved in this work, which has performed previous investigations. A 51.5 kW-burner was designed to operate with glycerine originating from triglycerides of plants and animals, mixed with ethanol, an alcohol produced by the chemical industry recently used as an additive in gasoline for automobile engines. Industrial oxygen was chosen as the oxidizing agent necessary for the liquid mixture combustion, allowing to obtain much higher flame temperatures compared to the usual combustion processes using air. Mixing glycerine with ethanol in 8.8 ratio allowed growing flame stability, accentuated also by creating swirl currents in the flame through the speed regime of fluids at the exit from the burner body. Results were excellent both through the flame stability and low level of polluting emissions.
Optimizing Tuberose Production Using Mycorrhiza and Biostimulants to Enhance Drought Tolerance
Authors: Mahdyh Saravani , Boogar Abdolrahman Rahimian , Aran Mehdi , Ramezan Dariush , Zargar Meisam , Diakite Simbo
Published: November 2024

Water deficit can significantly limit the sustainable production of plants, resulting in reduced growth, development, and flowering. Previous studies have shown that the use of biostimulants improves plant stability and promotes growth under low irrigation conditions. The study aims to evaluate the effects of biostimulators on the growth, development and flowering of tuberose (Polianthes tuberosa L.) under water deficit conditions. The experiment was conducted using a completely randomized design with three replications in pots and eight treatments: four irrigation regimes (100%, 80%, 60%, and 40%), and four biostimulant treatments (foliar application of seaweed extract at concentrations of 500, 1000, and 2000 ppm, humic acid at concentrations of 150, 300, and 600 ppm, inoculation of the bed with mycorrhiza, and a control treatment without biostimulators). The length, diameter, fresh and dry weight of the flower pedicel, the number of leaves per plant, the fresh and dry weight of the leaves, stem and root of each plant, as well as the content of photosynthetic pigments, phenol, proline, carbohydrates and flavonoids were measured. The results of this study showed that the growth and development of tuberoses were positively affected by different irrigation levels and biostimulants. The highest morphological characteristics were observed in plants irrigated at 100% field capacity. In contrast, the irrigation regime treatment of 40% of the field capacity combined with 600 mg/liter of humic acid had the most detrimental effect on plant growth indicators. Under stress conditions, the plant also exhibited increased levels of proline, carbohydrates, and flavonoids, which are commonly used as indicators of stress tolerance.
Based a Machine Learning Approach to Investigate the Factors Influencing Nirmatrelvir/ritonavir Exposure in Human Plasma: A Multicenter, Observational Study
Authors: Fan Jing , Xie Jiao , Zhang Daoming , Chen Junjie , Zhang Runcong , Fan Weibin , Wang Yan , Sun Liang , Lin Nengming , Yu Yuetian , Lin Bin
Published: November 2024

Objectives: Nirmatrelvir/ritonavir (N/R) is an effective drug for treating COVID-19. However, there is currently a lack of evidence for therapeutic drug monitoring of N/R, which may increase the risk of adverse drug reactions and compromise its efficacy. Methods: In this study, we retrospectively analyzed data from 139 patients in two center who were prescribed N/R. We collected baseline data from all patients and monitored nirmatrelvir and ritonavir concentrations on the third day of medication. We conducted a logistic regression analysis to investigate the relationship between drug concentration and prognosis. We also analyzed the correlations among features and used a random forest model to select significant factors that affect drug exposure. Subsequently, we constructed an XGBoost model to predict drug concentration using the selected features. Results: Our findings indicated that the concentration of N/R could not predict patient outcomes. We also identified potential factors that affect N/R concentration, including estimated glomerular filtration rate, creatine kinase, aspartate aminotransferase, alanine aminotransferase, lymphocytes, and platelet count. Ultimately, the evaluation of the predictive model resulted in a mean absolute error (MAE) of 0.717, mean squared error (MSE) of 1.328, root mean squared error (RMSE) of 1.152, and coefficient of determination (R-squared) of 0.779. The prediction model performs well and can provide risk prediction for medication management for N/R, as well as assist in personalized medication. Conclusions: We identified a set of variables that affect the treatment of N/R through therapeutic drug monitoring and established a machine learning model to identify drug risks. This provides a reference for clarifying the significance of therapeutic drug monitoring for N/R treatment and the subsequent development of multivariate prognostic models.
The Palliation of Advanced Pancreatic Cancer: Evolution From Surgery to Minimally Invasive Modalities
Authors: Masood Muaaz , Irani Shayan , Fotoohi Meharan , Wancata Lauren , Krishnamoorthi Rajesh , Kozarek Richard A.
Published: November 2024

Pancreatic cancer is an aggressive malignancy, and the current 5-year survival rate in the United States, according to the Surveillance, Epidemiology, and End Results Program data, approximates 12%. Although the current standard for resectable pancreatic cancer most commonly includes neoadjuvant chemotherapy prior to a curative resection, surgery in the majority of patients has historically been palliative. The latter interventions include open or laparoscopic bypass of the bile duct or stomach in cases of obstructive jaundice or gastric outlet obstruction, respectively. Non-surgical interventional therapies started with percutaneous transhepatic biliary drainage (PTBD), both as a palliative maneuver in unresectable patients with obstructive jaundice and to improve liver functions in patients in whom surgery was delayed. Likewise, interventional radiologic techniques included placement of plastic and ultimately self-expandable metal stents (SEMS) through PTBD tracts in patients unresectable for cure as well as percutaneous cholecystostomy in patients who developed cholecystitis in the context of malignant obstructive jaundice. Endoscopic retrograde cholangiopancreatography (ERCP) and stent placement (plastic/SEMS) was subsequently used both preoperatively and palliatively, and this was followed by, or undertaken in conjunction with, endoscopic gastro-duodenal SEMS placement for gastric outlet obstruction. Although endoscopic ultrasound (EUS) was initially used to cytologically diagnose and stage pancreatic cancer, early palliation included celiac block or ablation for intractable pain. However, it took the development of lumen-apposing metal stents (LAMS) to facilitate a myriad of palliative procedures: Cholecystoduodenal, choledochoduodenal, gastrohepatic and gastroenteric anastomoses for cholecystitis, obstructive jaundice, and gastric outlet obstruction, respectively. In this review, we synopse these procedures which have variably supplanted surgery for the palliation of pancreatic cancer in this rapidly evolving field.
Progenitor Cells, Microglia, and Non-coding RNAs: Orchestrators of Glioblastoma Pathogenesis and Therapeutic Resistance
Authors: Husain Adil , Ahmad Firoz , Pandey Sandeep , Upadhyay Tarun Kumar , Kang Sojin , Choi Min , Choi Jinwon , Park Moon Nyeo , Kim Bonglee
Published: November 2024

Abstract
Glioblastoma (GB) remains a major challenge owing to its extremely aggressive nature and resistance to conventional therapies. This review focuses on the intricate roles of progenitor cells, microglia, and non-coding RNAs (ncRNAs) in orchestrating GB pathogenesis and therapy resistance. Glioma stem cells (GSCs), derived from progenitor cells, are important drivers of tumor initiation and recurrence and exhibit remarkable plasticity and resistance to treatment. Microglia, the immune cells of the brain, are hijacked by GB cells to create an immunosuppressive microenvironment that supports tumor growth and resistance to therapy. ncRNAs, including microRNAs and long noncoding RNAs (lncRNAs), regulate multiple resistance mechanisms by modulating gene expression and influencing the interactions between progenitor cells and microglia. This review highlights new insights into these interconnected signaling pathways and explores potential therapeutic strategies targeting these molecular players to overcome treatment resistance and improve outcomes in patients with GB.
Keywords: Microglia; Non-coding RNA; Glioblastoma; Progenitors Cells, Glioma, Stem Cells.
Sintering with Soda and Leaching of Wolframite Cakes
Authors: Baimbetov Bolotpay , Tazhiyev Yeleussiz , Yeleuliyeva Akmaral , Moldabayeva Gulnara , Dauletbakova Adelya , Yakov Yelena , Taimassova Akbota
Published: November 2024

The study focuses on the processing of tungsten raw materials through various operations, including sintering, leach-ing, purification, and the production of technical tungstic acid. Modern research aims to enhance these processes, particularly the sintering of wolframite concentrates with alkali metal compounds and the leaching of concentrates and cakes. Experiments revealed that reactions between tungsten minerals and soda from Akchatau ores commence at temperatures above 520-550 °C, intensifying between 750-850 °C. The concentrates were sintered at 750, 800, and 850 °C with a soda excess coefficient of 1.05 to 1.2 to evaluate the effect on sodium tungstate extraction. Water leaching was conducted under a prob-abilistic-deterministic experimental design, analyzing five factors at four levels. The tungsten extraction was assessed based on solution density and the composition of the insoluble residue. Data processing established polynomial trends for tungsten trioxide extraction, and a material balance for sinter leaching was calculated from experiments using 100 g samples with a liquid-to-solid ratio of 2:1. The findings can be applied to improve tungsten processing technologies.
Divergent Effects of Circoviridae Capsid Proteins on Type I Interferon Signaling
Authors: Kosaka Anon H , Huang Chen-Yu , Lu Zih-Ying , Hsing Hua-Zhen , Choonnasard Amonrat , Ringo Rissar Siringo , Chuang Kuo Pin , Saito Akatsuki
Published: November 2024

Viruses in the Circoviridae family can infect both mammals and birds. Porcine circovirus type 2 (PCV2) significantly affects the livestock industry by causing porcine circovirus-associated diseases, such as postweaning multisystem wasting syndrome, respiratory disease complex, and dermatitis nephropathy syndrome. Additionally, beak and feather disease virus in parrots, canine circovirus in dogs, and columbid circovirus (pigeon circovirus) in racing pigeons induce immunosuppression, followed by secondary infections in these hosts. Although the PCV2 capsid protein has been demonstrated to inhibit type I interferon (IFN) signaling, the molecular mechanisms of Circoviridae-induced immunosuppression are largely unknown. In this study, we examined whether these functions are conserved across Circoviridae capsid proteins. Our results illustrated that although the nuclear localization of capsid proteins is conserved, their effects on IFN-β signaling vary by species, revealing the diverse roles of Circoviridae capsid proteins in modulating immune responses.
Training Profiles, Efficacy Perceptions, and Outcomes of Non-Invasive Neuromodulation: An Exploratory Study among Practitioners
Authors: Campos Laura Oliveira , Botim Bianca Rossi , Cunha Mayra Evelise , Campos Denys Batista , Barbosa Michelle Almeida , Gama Gabriela Lopes , Barbosa Alexandre Carvalho
Published: November 2024

Advances in non-invasive neuromodulation (NM) have enabled practitioners to modulate neural activity safely, offering a promising approach to treating neuropsychiatric and neurological conditions. This study aimed to analyze the training profiles of NM practitioners and assess their perceptions of NM’s clinical efficacy, safety, and patient satisfaction. An online survey was conducted among 117 practitioners in various healthcare fields, using the Clinical Global Impression (CGI) scale to gauge outcomes. Findings indicate that 99.13% of practitioners perceive NM as effective, with high rates of patient improvement in quality of life and symptom management. The study underscores the importance of standardized NM training protocols to enhance therapeutic outcomes.
Using Random Forest for Delineation of Dimension Stone Qarries. Mapping of the Santa Eulália Plutonic Complex (Portugal)
Authors: Silva Marcelo , Roseiro José , Nogueira Pedro , Gonçalves Mário A. , Henriques Renato
Published: November 2024

The Santa Eulália Plutonic Complex is a large granitoid ring-complex exhibiting several granite facies, gabbro-diorite rocks and roof pendants from the country rocks. This lithologic variability crossed with the spatial distribution of each lithotype within the complex enables the grouping of the different magmatic rocks in: G0 group (“pink-reddish” granites in an external belt), G1 group ("greyish” granites in the inner part”) and M group (gabbro and diorite as enclaves in the eastern regions of the G0 group). All these groups host facies of interest for dimension stones due to their aesthetic value and, therefore, a systematic thematic mapping has been conducted and refined throughout the years. In this work we verify the applicability of Sentinel-2 multispectral images combined with Random Forest as a classification methodology to distinguish the different gran-itoid groups and support large-scale lithological mapping. The results show overall accurate outline of the facies, with areas corresponding to the G0 group displaying good predictions, areas representing the G1 group moderately good predictions, and areas established for the M group poor predictions, obtaining Producer’s accuracies of ~82%, ~60%, and ~30%, respectively.
Stable Reusability of Nanocellulose Aerogels with Amino Group Modification in Adsorption/Desorption Cycles for CO2 Capture
Authors: Valdebenito Fabiola alejandra , Azócar Laura , Elgueta Elizabeth , Nisar Muhammad , Narvaez Ana , Valerio Oscar , Lira Sebastian , Sandoval Franco , Muñoz Robinson , Concha Valentina Rivera , Quezada Carolina , Albornoz Camila
Published: November 2024

This study evaluated the stability and reusability of amino-functionalized nanocellulose aero-gels as CO₂ adsorbent materials. The modified aerogels, synthesized via a controlled silylation using N-[3-(trimethoxysilyl) propyl] ethylenediamine (DAMO), demonstrated excellent thermal stability up to 250°C (TGA) and efficient CO₂ adsorption through chemisorption, which was the main adsorption mechanism. The performance of the aerogels was assessed using both, adsorp-tion isotherms and the decay pressure technique, revealing that CO₂ adsorption capacity in-creased with higher amino group loading (4.62, 9.24, and 13.87 mmol of DAMO). At 298 K and 4 bar, CO₂ adsorption capacity increased proportionally with the amino group concentration, reaching values of 3.17, 5.98, and 7.86 mmol of CO₂ g-1 polymer, respectively. Furthermore, over 20 adsorption/desorption cycles, the aerogels maintained 95% CO₂ desorption at ambient tem-perature, indicating their potential for industrial use. These findings highlight the aerogels suitability as stable, reusable materials for large scale CO₂ capture and storage technologies.
Application of an Ensemble Stationary-based Category-based Scoring Support Vector Regression to Improve Drought Prediction in the Upper Colorado River Basin
Authors: Bazrkar Mohammad Hadi , Han Heechan , Abitew Tadesse , Park Seonggyu , Zamani Negin , Jeong Jaehak
Published: November 2024

Recent above-normal temperatures, which exacerbated the impacts of precipitation deficits, are recognized as the primary driver of droughts in the Upper Colorado River Basin (UCRB), USA. This research aims to enhance drought prediction models by addressing structural changes in non-stationary temperature time series and minimizing drought misclassification through the ES-CBS-SVR model, which integrates ESSVR (Bazrkar and Chu, 2021) and CBS-SVR (Bazrkar and Chu, 2022). The research investigates whether this coupling improves prediction accuracy. Furthermore, the model's performance will be tested in a region distinct from those originally used, to evaluate its generalizability and effectiveness in forecasting drought conditions. We used a change point detection technique to divide the non-stationary time series into stationary subsets. To minimize the chances of drought mis-categorization, category-based scoring was used in ES-CBS-SVR. In this study, we tested and compared the ES-CBS-SVR and SVR models in the Upper Colorado River Basin (UCRB) using data from the Global Land Data Assimilation System (GLDAS) where the periods 1950-2004 and 2005 – 2014 used for training and testing, respectively. The results indicated that ES-CBS-SVR outperformed SVR consistently across for more the drought indices used in this study in a higher portion of the UCRB. This is mainly attributed to variable hyperparameters (regularization constant and tube size) used in ES-CBS-SVR to deal with structural changes in the data. Overall, our analysis demonstrated that the ES-CBS-SVR can predict drought more accurately than traditional SVR in a warming climate.
Control of Active and Reactive Power of an On-Board Bus Connected with a Photovoltaic Converter Under Conditions of Voltage Frequency Change
Authors: Binkowski Tomasz , Beňa Ľubomír , Medveď Dušan , Pijarski Paweł
Published: November 2024

Decarbonization of energy systems is forcing the development of renewable energy generation and consumption technologies. Photovoltaic systems are used in almost every industrial field, including autonomous power systems. Such systems are used, for example, on ships, space vehicles, or flying platforms. The use of energy generated from renewable sources requires a grid converter. To effectively use clean renewable energy, it is necessary to properly control power. In such a case, the precise synchronization of the converter with the grid becomes a key challenge. When the converter is connected to voltage with constant frequency, the synchronization process does not cause a problem. In the case of connecting the grid inverter to buses with changing voltage frequency, known synchronization algorithms become unsuitable. It has been shown that the use of frequency variation information causes deviations from the unit amplitude of synchronization signals, so a new system was proposed for adapting to variable frequency using a generalized second-order integrator. As a result, synchronization signals of unit amplitude were obtained. With the proposed method, the proportional resonant controller was able to control the active and reactive components of the current even with changes in voltage frequency, by adapting the resonant frequency.
Innovative Approaches in Non-Traditional Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms
Authors: Özer Özgür , Ozturk Harun Kemal
Published: November 2024

In this study, a general description of geothermal power plants is provided, and the optimization methods used are summarized. Following the review of these optimization methods, the advantages of heuristic methods and the success of the developed models are demonstrated. The challenges in optimizing geothermal systems, including the limitations due to the complexity and the use of multiple parameters, are discussed. Heuristic methods, particularly the widely used artificial neural networks and genetic algorithms, are explained in general terms. The application of artificial neural networks and genetic algorithms in the optimization of geothermal power plants is elucidated with the help of literature. Recent studies highlight that the combined use of artificial neural networks and genetic algorithms can produce faster and more consistent results. This demonstrates the benefits of using non-traditional methods for geothermal resource utilization and power plant optimization. An innovative optimization method has been developed using the operational data of an ORC geothermal power plant in the city of Izmir. The developed calculation method has identified the optimal operating conditions that provide a 39.41% increase in net power output. The plant's gross power generation has been increased from 4,943 kW to 6,624 kW.
A Snow-based Hydroclimatic Aggregate Drought Index for Snow Drought Identification
Authors: Bazrkar Mohammad Hadi , Zamani Negin , Chu Xuefeng
Published: November 2024

Climate change has increased the risk of snow drought, which is associated with the deficit in snowfall and snowpack. The objectives of this research are to improve drought identification in warming climate by developing a new snow-based hydroclimatic aggregate drought index (SHADI) and to assess the impacts of snowpack and snowmelt in drought analyses. To derive the SHADI, an R-mode principal component analysis is performed on precipitation, snowpack, surface runoff, and soil water storage. Then, a joint probability distribution function of drought frequencies and drought classes, conditional expectation, and k-means clustering are used to categorize droughts. The SHADI was applied to the Red River of the North Basin (RRB), a typical cold climate region, to characterize droughts in a mostly dry period from 2003 to 2007. The SHADI was compared with the hydroclimatic aggregate drought index (HADI) and the U.S. drought monitor (USDM) data. Cluster analysis was also utilized as a benchmark to compare the results of HADI and SHADI. SHADI showed better alignment with cluster analysis results than HADI, closely matching the identified dry/wet conditions in the RRB. The major differences between SHADI and HADI were observed in cold seasons and in transition periods (dry-to-wet or wet-to-dry). The derived variable threshold levels for different categories of drought based on the SHADI were close to, but different from those of HADI. SHADI can be used for short-term lead prediction of droughts in cold climate regions and, in particular, can provide an early warning for drought in the warming climate.
Porous Polymers Based on PSU and PSU-TMA with Grafted Zirconium-Organic Moieties: Synthesis and Application for Removal of Arsenite and Arsenate Water Pollutants
Authors: Montella Alessio Vincenzo , Bastianini Maria , Sisani Michele , Sgreccia Emanuela , Di Vona Maria Luisa , Narducci Riccardo
Published: November 2024

Porous organic polymers (POPs), based on polysulfone (PSU) and covalently linked zirconium-organic moieties have been applied for the first time to Arsenic removal in wastewater. The synthesis involved anchoring a synthon molecule onto PSU, followed by MOF assembly and subsequent quaternization (QA) with trimethylamine (TMA). Two samples Zr-POP and Zr-POP-QA are characterized by NMR, FTIR, and titration. The efficiency of As uptake is revealed by ICP. The study is carried out at different pH (3, 7, and 12) to vary the charge of Zr-organic moieties and the charge of arsenite and arsenate species. Two concentrations (0.5 and 1 mM) of As (III) and As (V) are used. The results show that Zr-POP at pH 3 has a removal efficiency (RE%) of 77% for As (V), in agreement with the positive charge present in the Zr-framework at this pH. At neutral pH the As (III) sorption is also relevant. Zr-POP-QA at pH 12 shows, thanks to the positive charge on the ammonium moieties, a RE% of As (III) equal to 35%. The kinetic of processes, performed on the most promising system, i.e. Zr-POP at pH 3 for As(V), shows a plateau already after 8 hours with a second-order law. The regeneration of the material is also evaluated. According to the results, these materials are serious candidates in the removal of heavy metals in wastewater.
Identification of Pseudomonas protegens and Bacillus subtilis Antimicrobials for Mitigation of Fuel Biocontamination
Authors: Barry Schroeder Amanda L. , Reed Adam M. , Radwan Osman , Bowen Loryn L. , Ruiz Oscar N. , Gunasekera Thusitha S. , Hoffmann Andrea
Published: November 2024

Hydrocarbon fuel biofouling and biocorrosion requires expensive cleanup of aviation infrastructures unless appropriate sustainment measures are applied. Alternative to current chemical biocides used in fuel sustainment, the identification of novel biological control agents offers promising alternatives. In this study, 493 microbial fuel isolates from our in-house repository were screened to identify new endogenously produced antimicrobial compounds. Using agar plug screening, liquid culture growth testing, and Jet A fuel culture assays, the two fuel isolate strains Pseudomonas protegens #133, and Bacillus subtilis # 232 demonstrated promising biocontrol activity against bacteria, yeast and filamentous fungi. Mass spectrometry analysis (LC-MS/MS) of #232 culture filtrate identified several common lipopeptide antimicrobials including gageostatin C, gageopeptin B, and miscellaneous macrolactins. In contrast, LC-MS/MS identified the siderophore pyochelin as one of the predominant compounds in #133 culture filtrate with previously demonstrated antimicrobial effect. Jet fuel microbial consortium culture testing of #133 culture filtrate including flow-cytometry live/dead cell mechanism determination demonstrated antimicrobial action against Gram-positive Gordonia sp. bacteria. The study concludes that antimicrobial compounds secreted by #133 have bactericidal effect against Gordonia sp. and cause cell death through bacterial lysis and membrane damage with potential applications in biocidal treatment of hydrocarbon-based aviation fuels.
Mapping Antimalarial Drug Resistance in Mozambique: a systematic review of Plasmodium falciparum Genetic Markers Post-ACT Implementation
Authors: Chaves Celso Raul Silambo , da Silva Clemente , Salamandane Acácio , Nogueira Fatima
Published: November 2024

Malaria continues to be a significant public health burden in many tropical and subtropical regions. Mozambique ranks among the top countries affected by malaria, where it is a leading cause of morbidity and mortality, accounting for 29% of all hospital deaths in the general population and 42% of deaths amongst children under five. This review presents a comparative analysis of data on five critical genes associated with antimalarial drug resistance: pfmdr1, pfcrt, pfk13, pfdhfr and pfdhps, along with copy number variation (CNV) in genes pfmdr1 and pfpm2/3. These are genes associated with parasite response to currently used for antimalarials to treat uncomplicated P. falciparum malaria in Mozambique. The review synthesizes data collected from published studies conducted in Mozambique after the introduction of ACTs (2006) up to June 2024, highlighting the presence or absence of mutations in these genes across Mozambique. We aimed at mapping the prevalence and distribution of these molecular markers, across the country, in order to contribute to the development of targeted interventions to sustain the efficacy of malaria treatments in Mozambique. Four databases were used to access the articles: PubMed, Science direct, Scopus and Google scholar. The search strategy identified 132 studies addressing malaria and antimalarial resistance. Of these, 112 were excluded for various reasons, leaving 20 studies to be included in this review. Children and pregnant women represent the majority of target groups in studies on all types of antimalarials. Most studies (87.5%) were conducted in the provinces of Maputo and Gaza. The primary alleles re-ported were pfcrt CVMNK, and in the most recent data, its wild-type form was found in the majority of patients. Low prevalence of mutations in the pfk13 gene, were identified reflecting the effectiveness of ACTs. In pfk13 only mutation A578S was reported, in Niassa and Tete. Regarding CNVs were observed in studies carried out in the south of Mozambique, for pfmdr1 with a frequency of 1.1-5.1% and pfpm2 with a frequency of 1.1-3.4%. This review indicates that molecular markers linked to malaria resistance show considerable variation across provinces in Mozambique, with most up-to-date data accessible for Maputo and Gaza. In contrast, provinces such as Zambezia and Inhambane have limited data on several genes, while Nampula lacks data on all drug resistance markers. Our review reveals that gene mutations associated with antimalarial resistance, vary considerably by province in Mozambique, with more up-to-date data available for Maputo and Gaza. Other provinces, including Zambezia, Inhambane, and Cabo Delgado, have limited data on several genes, while Nampula entirely lacks data on all drug resistance molecular markers.