In Europe, non-residential building stock built before building energy codes consumes more energy and resources than new buildings. Existing educational buildings comprise 17% of this outdated stock. These buildings can be retrofitted to create a conducive learning environment that can improve students’ comfort. Facade renovation has become the first choice for elevating the building performance of the education stock because it is less expensive than other alternatives. This study develops a methodology to optimize facade renovation solutions including: 1) preparation, 2) simulations of the simplified model using local shading, and 3) modelling realistic optimized facade design. This study evaluates visual comfort by considering multiple-dimensional metrics such as useful daylight illuminance (UDI), annual sunlight exposure (ASE), illuminance uniformity and the daylighting factor. The methodology was first applied to improve the facade proposal “Roof to Façade” in the project Waste-based Intelligent Solar Control Devices for Envelope Refurbishment (WiSeR) and simulations with the software DesignBuilder to design tile system facades. The results illustrate that implementing these solutions could efficiently improve indoor visual comfort by considering multiple daylight metrics. Moreover, for a constant gaps surface, the facade distribution with staggered gaps performs better in terms of the daylighting factor, solar gains and uniformity than more continuously connected gaps.

Context: Business Process Automation (BPA) is adopted by organizations to improve efficiency, reduce costs, and increase overall business performance. Traditional Business Process Automation (TBPA) is one of the three approaches employed to develop a BPA. TBPA entails developing BPA in a programming language for integrating the relevant applications in the digital ecosystem to execute a given process. Process variability and practitioner unavailability encumber the requirements specification for TBPA software. Objective: This work proposes a log-based approach for TBPA software to make software more adaptable to process changes and reduce reliance on practitioners, by providing a higher alignment among business process requirements and software architecture, and employing process mining to semi-automatically discover the business process during requirements elicitation. Method: The research conducted a case study in a technology institute to assess the approach and report its results in practice. Results: The results revealed significant improvements in adaptability to business process changes and decreased the time spent with practitioners, and, efficiency in development. The approach also presented limitations, including human intervention to accurately obtain the business process, complexity to trace the process into the architecture, data privacy concerns, and risk of network traffic overload. Conclusion: This research demonstrated the effectiveness of traceability between process requirements and software architecture, as well as the use of logs and process mining. These methods made TBPA software enhanced the software adaptability to changes and minimized the reliance on practitioners during requirements elicitation respectively.

Accurately estimating project duration is critical for the successful delivery of construction projects, particularly in the dynamic and resource-constrained environment of South Africa. This study aims to assess the key factors influencing construction project duration in the South African context through the development of a regression model. By analyzing data from a diverse range of construction projects, the research identifies significant variables such as project size, complexity, location, resource availability, and stakeholder involvement that contribute to delays or expedited completion. The regression model is designed to quantify the impact of these factors, offering a predictive tool that can enhance project planning and scheduling accuracy. The findings provide valuable insights for project managers, contractors, and policymakers, enabling them to make informed decisions that optimize project timelines and improve the overall efficiency of the construction industry in South Africa.

Artificial intelligence (AI), the wide spectrum of technologies aiming to give machines or computers the ability to perform human-like cognitive functions, began in the 40s with the first abstract models of intelligent machines. Soon later in the 50s and 60s machine learning algorithms such as neural networks and decision trees ignited large enthusiasm. More recent advancements include the refinement of learning algorithms, the development of convolutional neural networks to efficiently analyze images, and methods to synthesize new images. The renewed enthusiasm was also due to the increase in computational power with graphical processing units and the availability of large digital databases to be mined by neural networks. AI soon began to be applied in medicine, first through expert systems designed to support the clinician’s decision, and later with neural networks for the detection or classification of malignant lesions in medical images. More recently, the use of natural language processing, recurrent neural networks, transformers and generative models has both improved the capabilities of making an automated reading of medical images and moved AI to new domains, including text analysis of electronic health records, image self-labelling and self-reporting. Thanks to its versatility and impressive results and fueled by the availability of powerful computing resources and open-source libraries, AI is one of the most promising resources for frontier research and applications in medicine.

The literature has addressed the negative impact of poor neonatal conditions (NC) across regions. This has drawn attention to the need to improve NC, particularly in Africa. NC research can make an important contribution. However, there is no study dedicated to this topic in Africa. Through a bibliometric analysis, we arrive at outputs that can inform scientists in planning ongoing or new NC research and those involved in developing and implementing strategies to combat poor NC. Using bibliometrics, the study identified the scientific knowledge on NC between 2000 and 2019, its visibility in the community, the main topics researched, and collaboration patterns.The results show that knowledge on NC has increased between 2000 and 2019, it is concentrated in a few African countries (Egypt, South Africa, Nigeria, Tanzania and Kenya), its visibility is below the world average, in general, maternal mortality is the most researched topic and collaborative activities are frequently, mainly international research collaboration (IRC), being the United States of America (USA) and the United Kingdom (UK) the main partners (they participated in 57% and 28% of all articles with IRC). The collaboration networks are fragile as 43%-67% of all links represent one article in 20 years.Ongoing or new research on NC in Africa should consider the main African players and their partners. There is a need to implement strategies to increase NC knowledge in other African countries, expand and strengthen the collaboration networks and diversify the sources of knowledge.

Accurate determination of an individual’s unique human leukocyte antigen (HLA) allele holds important significance in evaluating the risk associated with autoimmune and infectious diseases, such as human immunodeficiency virus (HIV) infection. Several allelic variants within the HLA system have been linked to either increased protection or susceptibility in the context of infectious and autoimmune diseases. This study aimed to determine the frequency and association of HLA alleles between people living with HIV (PLHIV) as the case group and HIV-uninfected Peruvian individuals with high-risk behavior of sexual transmission diseases as the control group. Whole exome sequencing (WES) was used to determine high-resolution HLA allelotypes using OptiType and arcasHLA tools. The HLA alleles present in HLA classes I (A, B, and C loci) and II (DPA1, DPB1, DQA1, DQB1 and DRB1 loci) were determined in a cohort of 59 PLHIV (cases) and 44 HIV-uninfected individuals (controls). The most frequent HLA alleles were A*02:01, DPB1*04:02 and DQB1*03:419 at 36%, 30% and 28% prevalence in general population. We found that C*07:01 (p = 0.0101; OR = 10.222, 95% IC: 1.40–74.55), DQA1*03:02 (p = 0.0051; OR = 5.297, 95% IC: 1.48–19.02) and DRB1*09:01 (p = 0.0119; OR = 4.788, 95% IC: 1.39–16.44) showed an association with susceptibility to HIV infection, while DQB1*03:419 (p = 0.0478; OR = 0.327, 95% IC: 0.11–0.96) was associated with protection from HIV infection. Our findings contribute to the knowledge of HLA allele diversity in the Peruvian population (around 70% South American indigenous ancestry), lay the groundwork for further valuable large-scale use of HLA typing and offer a novel association of HIV infection that is relevant to vaccine studies.

Additive manufacturing (AM) is a cutting-edge manufacturing technique that allows for the direct creation of complicated objects from digital desktop designs. Among the several AM techniques, the material extrusion technique has gained more attention because of its ability to manufacture complicated objects and customizes profiles at a reasonable costin a shortertime period. The main advantages of this technique are its easier fabrication process and low cost when compared to other well-known AM techniques. Enhancement in mechanical properties plays the key role in the AM objects. So, Incorporating nanofillers or nanoparticles into the basic materials like polymers, carbon ceramic and metal based materials is one of the most promising alternatives. This review attempts to enlighten and inform readers about the basic working principle of material extrusion technique and the many forms of polymer-based additives reported in the literature. This review can guide the readers to compare and assess the uses of polymer based raw materials before on choosing the kind of material be used, as well as it provides a view point on the application of AM by the material extrusion method in different disciplines. Finally, the challenges and upcoming prospects of the material extrusion process are discussed.

Acidic soils limit plant nutrient availability, leading to deficiencies and reduced crop yields. Agricultural liming agents address these issues and are crucial for deploying silicate amendments used in enhanced rock weathering (ERW) for carbon sequestration and emission reduction. Grower recommendations for liming agents are based on the liming index (LI), which combines the neutralizing value (NV) and fineness rating (FR) to predict a mineral’s acidity neutralization relative to pure calcite. However, the LI was originally developed for carbonate minerals, and its applicability to silicates remains uncertain, with studies often yielding inconclusive results on soil carbon and liming efficiency. This study aims to evaluate the liming efficiency of silicates. We determined the LI of five candidate ERW minerals (basalt, olivine, wollastonite, kimberlite, and montmorillonite) and compared them to pure calcite. Post-NV acid digestion, we characterized the minerals and soils, applying nonparametric statistical tests (Wilcoxon, Kendall) to correlate liming results with LI, dosage, and amendment methods. We developed an empirical model incorporating mineralogy and kinetics to explain silicate behavior in liming, considering soil, climate, and crop factors.

Serum amyloid A (SAA) is a small, consisting of 104 residues, protein, which under physiological conditions exists mainly in hexameric form. It belongs to the positive acute-phase proteins, which means that its plasma concentration increases rapidly in response to injury, inflammation, and infection. The accumulation of SAA molecules promotes the formation of amyloid aggregates, which deposit extracellularly in many organs, causing their dysfunction. In our previous work, we successfully designed a peptidomimetic that inhibited the aggregation of amyloidogenic SAA fragments. In the present paper, we show how the same inhibitor, named saa3Dip, affects oligomerization and aggregation processes of MetSAA1.1 protein. The Thioflavin T assay showed that saa3Dip inhibits its fibrillization. The measurement of the internal fluorophore fluorescence (Trp) showed differences that occur in the tertiary structure of MetSAA1.1 in the presence of the inhibitor, which was also confirmed by CD spectra in the aromatic range. FTIR results suggested that saa3Dip can stabilize some fragments of the native structure of MetSAA1.1, which was confirmed by determining the melting temperature (Tm) of the protein-inhibitor complex. AFM images demonstrated that the presence of saa3Dip prevents the formation of large SAA aggregates. Our results suggest that saa3Dip stabilizes the native conformation of MetSAA1.1.

Valles Marineris (VM), the most prominent example of a Martian Valley Network, has been extensively studied for over 50 years, yet no detailed examination of the principal azimuths of the system exists. To address this, two methods are presented to precisely calculate the principal azimuths, a Bezier Spline analysis, and a GIS technique. The medial axis of the main canyon of VM was determined analytically from cubic polynomial splines fitted to 93 coordinate points along both north and south edges of the canyon. These splines were optimized, and medial axis points were calculated through numerical techniques that ensured orthogonality between the tangents of each spline and their connecting normal lines. 1,000 medial axis points were extracted, and various regression models constructed, including fitting to sinusoidal and cubic polynomial curves, achieving accuracies with R² values of 0.98 and 0.99, respectively. Principal azimuths were obtained using the sinusoidal equation with the slope of the tangent at any point x simply determined by the derivative of the curve’s equation. This analytic approach was cross-validated by a GIS method (using QGIS software), where a vector medial axis was obtained which produced principal azimuths that agreed with values from the analytic study with a correlation coefficient of 1.00, and a p value of 6.43e-65. The findings demonstrate that an azimuthal framework can be rigorously constructed as a potential standard reference in VM geoscience, replacing less precise and ambiguous compass bearings with the accurate azimuths necessary for high-resolution spatial analysis for future investigations.

Complexity of issues in cancer research has led to the introduction of powerful computational tools for helping experimental in vivo and in vitro methods. These tools, typically focused on studying cell behavior and dynamic cell populations, range from systems of differential equations solved numerically, to lattice models and agent-based simulations. In particular, agent-based models (ABMs) are increasingly used for they capability to incorporate multi-scale features ranging from the individual up to the population level, thus combining statistically aggregated assumptions with individual heterogeneity. In this work, we present an ABM that simulates tumor progression in a colonic crypt, with the aim of providing an experimental in silico environment for testing results achieved in traditional laboratory research and developing alternative scenarios of tumor development. The model also allows some speculations about causal relationships in biologically inspired systems.

Hybrid Power Switches (HPS) combine the advantages of SiC unipolar and Si bipolar devices and therefore can bridge the gap between these technologies. In this paper, the performance of a hybrid power switch configuration based on the latest SiC MOSFET and Si IGBT technologies is presented. The device is evaluated through experimental measurements of its characteristics under various conditions. The results show the HPS can achieve switching losses as low as a SiC MOSFET while offering the high current capability of the IGBT without significant increase in costs.

Introduction: The care of dependent people is eminently family-oriented, and often, there is a high level of dedication to this family care. Constant and continuous care leads to a series of negative psychological consequences. Social support has been related to improved mental health in family caregivers. We found heterogeneous results regarding the relationship between the types of social support received and the perceived level of support. In addition, to our knowledge, no reviews analyze this relationship among family caregivers. Therefore, we aimed to systematically syn-thesize the relationships between perceived and received social support in informal caregivers. Methodology: We have carried out a quantitative systematic review with meta-analysis, regis-tered in PROSPERO (id: CRD42023470047); the systematic search was carried out in the following databases: PubMed, CINAHL, PsycINFO, and Scopus, until November 2023. After the selection and review of the results, 12 studies were obtained, two of which were eliminated due to a high risk of classification bias. Regarding the results, a medium size positive statistical association was found (r = 0.43). The results were consistent, accurate, and robust. The Trim and Fill test showed a vari-ation of 7%. Subgroup analysis indicated no differences in the age group of the people cared for (adults or children), selection bias, and confounding bias. In conclusion, perceived social support is related to more social support received by family caregivers.

This study investigates the impact of positive childhood experiences (PCEs) on the subjective well-being (SWB) of college students, with psychological resilience as a mediator. A total of 1104 students from four universities in Yunnan Province, China, participated in the study. Using the Positive Childhood Experiences Scale, the Connor-Davidson Resilience Scale (CD-RISC), and the Subjective Well-being Scale, data were collected and analyzed through descriptive statistics and mediation analysis using SPSS and the PROCESS macro. Results indicate that PCEs significantly enhance SWB, and this relationship is partially mediated by psychological resilience. Specifically, psychological resilience accounted for 49.4% of the mediating effect between PCEs and SWB. These findings highlight the importance of fostering resilience to improve well-being in educational contexts. The study provides practical implications for educational interventions aimed at promoting mental health and well-being among college students.

In the current digital era, Enterprise Data Management (EDM) plays a pivotal role in enhancing business performance by ensuring efficient handling of diverse data sources and enabling real-time applications. However, the complexity of managing vast data streams and integrating various systems presents significant challenges for enterprises. These challenges can be mitigated by incorporating APIs and Middleware, APIs help integrate diverse systems, while middleware solutions facilitate communication between different software environments, Cloud-Based Data Platforms such as AWS, Azure, and Google Cloud to offer scalable data storage and processing capabilities, allowing businesses to expand without compromising on performance. This study proposes a systematic review of business performance improvements driven by various types, sources, and real-time applications, highlighting cost efficiency, reliability, and increase in revenue using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the inclusion criteria is bounded by (1) publication date between 2014 to 2024, (2) written in English, (3) research focusing on EDM with an emphasis on types, data sources, and real-time applications, and (4) research work that provides a clear framework for the analysis of EDM’s impact on enhancing business performance. Following this process, 136 eligible research studies were included. The cost of implementation can vary significantly based on the size and complexity of the system. Operational and maintenance costs can vary widely depending on the infrastructure, data storage requirements, and the level of real-time application integrations. As EDM systems scale to accommodate more diverse data sources and real-time analytics capabilities, the associated costs increase accordingly.

The infections of bacterial origin represent a significant problem to public healthcare worldwide both in clinical and community settings. Recent decade was marked by limiting treatment options for bacterial infections due to growing antimicrobial resistance (AMR) acquired and transferred by various bacterial species, especially the ones causing healthcare-associated infections, which has become a dangerous issue noticed by the World Health Organization. Numerous reports shown that the spread of AMR is often driven by several species-specific lineages usually called the ‘global clones of high risk’. Thus, it is essential to track the isolates belonging to such clones and investigate the mechanisms of their pathogenicity and AMR acquisition. Currently, the whole genome-based analysis is increasingly used for these purposes, including epidemiological surveillance and analysis of mobile elements involved in resistance transfer. However, in spite of the exponential growth of available bacterial genomes, their representation usually lack uniformity and availability of supporting metadata, which creates a bottleneck for such investigations. In this dataset, we provide the results of a comprehensive genomic epidemiology analysis of 61,857 genomes of a dangerous bacterial pathogen Klebsiella pneumoniae. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), assignment of the isolates to known global clones, capsular (KL) and lipooligosaccharide (O) types, presence of CRISPR-Cas systems, and cgMLST profiles are given, and the presence of AMR and virulence genes within the genomes is also reported. This dataset will be useful for researchers in the field of K. pneumoniae genomic epidemiology, resistance analysis and prevention measure development.

Introduction & Objectives: Blood cells-(BC)count derived parameters have been inves-tigated in systemic inflammation, cancer, and various cutaneous diseases. Little is known about their usefulness in trichology, especially as prognostic and therapeutic biomarkers. We conducted a retrospective study on patients with not-cicatricial alopecia to assess differences in BC-count. Materials & Methods: Patients with alopecia areata (AA), telogen effluvium (TE), androgenic alopecia (AGA), psoriasis and hidradenitis suppurativa (HS) were included in the study. Baseline complete BC-count and derived parameters (i.e. NLR, PLR, MLR, SII; PIV) were recorded and analyzed for each patient and at different timepoints for AA patients on systemic agents. Results: 170 patients fulfilled inclusion criteria. BC-count and derived values were similar across the not-cicatricial alopecia groups, while general differences were observed compared to psoriasis and HS. TE displayed a closer inflammatory signature to psoriasis with respect to CRP, NLR, MLR, SII and PIV. We also found a significant reduction in RBCs in severe versus patchy-AA and an increase of SII in acute versus chronic AA. Modulation of platelet number and volume could be used as therapeutic marker in AA. Conclusions: In our experience, the BC-count and its derived parameters could represent potential tools in AA and TE.

This study examines the historiography of early Islam by assessing the reliability of Qurʾānic exegeses as sources documenting the early history of Islam and the biography of the Prophet Muḥammad in Mecca. Focusing on Qurʾānic exegetical practices from late antiquity to the medieval period, this article argues that there is a significant discontinuity in how Qurʾānic exegeses align with the historical context of the Qur'an, especially in relation to Meccan sūras such as Q 107. Significantly, this challenges the continuity of tradition, the fundamental concept upon which the “Islamic sciences” are based. This discontinuity is herein revealed through a historical-critical analysis of the exegesis of Q 107:4 that demonstrates how Qurʾānic exegetical practices have reinterpreted and reshaped early Islamic history in response to the pressures of new identity formation and made Qurʾānic exegeses more reflective of the social and political contexts of the exegetes than of the historical milieu of the Qurʾān itself. This analysis contributes to the ongoing discussion of the role exegesis played in reshaping the history of Islam. Indeed, it emphasises the importance of critically evaluating these sources in order to uncover a more nuanced historical narrative of early Islam.

Objective: To explore the effect of time exposure to flat screen electronic devices with LED 14 lighting and the Mediterranean diet on macular pigment optical density (MPOD). Methods: MPOD 15 was measured by heterochromatic flicker photometry in 164 eyes (47 of young women 20-31 years 16 and 35 adult women 42-70 years). Exclusion criteria: evidence of macular degeneration and eyes 17 with cataracts. Data on the use of electronic devices and Mediterranean diet adherence were col- 18 lected through a survey. Nonparametric analysis of variance and independent sample t-tests were 19 used to compare subjects. Results: Significant differences (p<0.01) were found in total time of expo- 20 sure to LEDs (hours per day) between both groups (9.31 ± 3.74 young women vs 6.33 ± 3.64 old 21 women). The MPOD values for the young and adult populations were significantly different: 0.38 ± 22 0.16 and 0.47 ± 0.15 (p<0.01), respectively. When comparing both groups for the same time of expo- 23 sure to LEDs, differences were obtained between MPOD values of both populations: For total expo- 24 sures greater than 6 hours per day, the MPOD values were lower in young women than in adult 25 ones (0.37 ± 0.14 vs 0.50 ± 0.14, p<0.01). On the other hand, a significantly higher adherence was 26 found in the old women in comparison with the young women (OW 9.23± 2.50 vs YW 7.70 ± 2.08, 27 p<0.01), with higher MPOD values, (OW (0.52 ± 0.14) vs (YW (0.34 ± 0.18). Conclusions: Higher 28 MPOD values are observed with decreasing exposure time to electronic devices with LED lighting 29 screens and high adherence to the Mediterranean diet.

Cirrhosis is a critical global health issue, responsible for 2.4% of deaths worldwide in 2019. The Global Burden of Disease Study reported a near doubling of decompensated cirrhosis cases from 1990 to 2017. In the U.S., cirrhosis is the 12th leading cause of death and often requires hospitali-zation and procedural interventions for severe complications such as hepatocellular carcinoma, ascites, hepatic encephalopathy, and variceal bleeding. This study aims to identify racial, ethnic, and socioeconomic disparities in receiving critical interventions among U.S. patients with de-compensated cirrhosis during 2020-2021. We conducted a retrospective cross-sectional analysis using 2020-2021 National Inpatient Sample data of adult patients (≥18 years) with cirrhosis-related and cirrhosis complication-related ICD-10 codes and who underwent procedures for cirrhosis-related indications such as esophagogastroduodenoscopy (EGD) for variceal hemor-rhage, transjugular intrahepatic portosystemic shunt (TIPS) for variceal hemorrhage or refractory ascites, hemodialysis for acute kidney failure or hepatorenal syndrome, and liver transplantation We collected data on patient baseline clinicodemographic and procedural outcomes. Statistical analyses included multivariable logistic regression to assess for associations with outcomes. There were significant disparities in procedure utilization: White and Hispanic patients more likely than Black patients to receive EGD and TIPS, while Black and Hispanic patients had higher odds of receiving hemodialysis. Insurance type also influenced access, with Private/HMO insurance holders having higher odds of undergoing procedures. These findings underscore the need for targeted interventions to address healthcare inequities.

Multidrug-resistant-tuberculosis (MDR-TB) patients are treated with a standardised, short, WHO-regimen, which includes clofazimine (CFZ) and bedaquiline (BDQ) antibiotics. These two antibiotics lead to development of QT prolongation in patients, inhibiting potassium (K+) uptake by targeting the Kv11.1 (hERG) channel of the cardiomyocytes (CMs). However, the involvement of these antibiotics on other K+ transporters of the CMs, as potential mechanisms of QT prolongation, has not been explored. This study determined the effects of CFZ and BDQ on the sodium, potassium-adenosine triphosphatase (Na+,K+-ATPase) activity of CMs, using the rat cardiomyocytes (RCMs). These cells were treated with varying concentrations of CFZ and BDQ individually and in combination (1.25 - 5 mg/L). Thereafter Na+,K+-ATPase activity was determined, followed by intracellular adenosine triphosphate (ATP) quantification and cellular viability determination. Both antibiotics demonstrated dose-response inhibition of the Na+,K+-ATPase activity of the RCMs. The greatest inhibition was demonstrated by combinations of CFZ and BDQ, followed by BDQ alone and lastly CFZ. Neither antibiotic, individually or in combination, demonstrated cytotoxicity under the experimental conditions used. The inhibitory effects of CFZ and BDQ individually and in combination, on the activity of the Na+,K+-ATPase pump of the RCMs highlight the existence of additional mechanisms of QT prolongation by these antibiotics.

This paper presents a novel game-theoretic model simulating the global artificial intelligence (AI) development race among nations. We introduce a dynamic system of equations that captures the complex interplay between a country's development level, investment strategies, market share, and the possibility of technological domination. The model incorporates key features of technological races, including returns subject to diminishing marginal utility, exponentially increasing costs, market dynamics, and strategic investment decisions based on relative market positions. Through Monte Carlo simulations, we analyze various scenarios of the AI race, focusing on the emergence of dominant players and the challenges faced by countries attempting to catch up. Our results indicate a tendency towards oligopolistic market structures, with a few countries achieving technological domination while others struggle to close the gap. The model provides insights into the potential trajectories of global AI development and the conditions under which technological leapfrogging might occur. These findings have implications for policymakers and researchers in understanding the dynamics of technological races and formulating strategies for national AI development.

Chagas disease, caused by Trypanosoma cruzi, leads to severe complications in 30% of infected individuals, including acute myocarditis and chronic fibrosing cardiomyopathy. Despite the significant burden of the disease, there is currently no licensed vaccine available to prevent it. This study aimed to evaluate the mucosal and systemic immunogenicity as well as the prophylactic efficacy of a mucosal vaccine and its impact on both acute and chronic cardiomyopathy. The results showed that nasal administration of Trans-sialidase (TS) plus c-di-AMP (TS+A). TS+A vaccine elicited NALT expression of IFN-γ, IL-17a, and IL-4 mRNA, and nasal-specific IgA production. Ex vivo challenge with TS also triggered enhanced proliferation of lymphocyte from the NALT, sentinel cervical lymph node and spleen. TS+A immunization increased plasma levels of Th1/Th2/Th17 cytokines and an evident cellular response to judge enhanced delayed-type hypersensitivity responses following TS footpad challenge. After oral infection, TS+A-vaccinated mice showed significantly reduced parasitemia and parasite load in heart, muscle and intestine, while markers of hepatic and muscle damage as well as clinical manifestations of acute infection are strongly diminished. TS+A also attenuated acute myocarditis and heart expression of inflammatory markers. The protection conferred by TS+A extended into the chronic phase, where it resulted in a clear reduction in chronic myocarditis, fibrosis, and functional electrocardiographic abnormalities, associated with decreased expression of the pro-fibrotic TGF-β. These results revealed that it is possible to develop a mucosal vaccine against T. cruzi based on TS and c-di-AMP, capable to reduce the development of Chagas cardiomyopathy, the hallmark of Chagas disease.

Limoncella of Mattinata, a rare and ancient Mediterranean citrus fruit, was investigated by sequence analysis of the ribosomal internal transcribed spacer regions, which assigns it as a variety of Citrus medica L. Morphological, chemical, and biomolecular approaches were used to characterize flavedo and albedo, parts usually rich of bioactive compounds. The morphological findings showed albedo and flavedo cellular structures as “reservoirs” of nutritional components. Both albedo and flavedo hydroalcoholic extracts were rich in polyphenols, but they were different in compounds and quantity. The flavedo is rich in p-coumaric acid and rutin, whereas the albedo contains high levels of hesperidin and quercitrin. Antioxidant, anti-inflammatory, and genoprotective effects for albedo and flavedo were found. The results confirmed the health properties of flavedo and highlighted that albedo is also a rich source of antioxidants. Moreover, this study valorizes Limoncella of Mattinata's nutritional properties, cueing its crops' repopulation.

This study is focus on the petrographic properties and geo-mechanical properties of the Inzari formation rocks at Tar Khel Village, District Swabi, Khyber Pakhtunkhwa, and whether they are suitable for use as building materials for structures like bridges, buildings, and roads. Five fresh and large samples have been taken from various areas of this formation. These rock samples were identified as siliciclastic mudstone through a careful petrographic analysis. The test result of physical properties (water absorption, specific gravity, and porosity) and mechanical properties (unconfined compression strength, unconfined tensile strength, Schmidt hammer test, and shear strength) of these rock samples shows as follows: their unconfined compressive strength with between 23 to 94 MPa, their specific gravity values being very high (≥2.78), and their porosity and water absorption values being very low (<1%), imply that the Inzari formation rock can be used as an excellent building material. The rock sample strength variations may be mainly caused by the presence and abundance of stylolite and fractures. Furthermore, the petrographic property analysis of these rock samples indicates that they have the significant amount of micrite and calcite, which are suitable to be use as both asphalt and concrete aggregate. According to this study, the Inzari formation rock is appropriate for use as fine aggregate in concrete, asphalt, and other building materials.

Turgor pressure – the intracellular hydrostatic pressure exerted by the cell protoplast on the cell wall – is of critical physiological importance for all organisms that have the cell wall. However, in mycology there is increasing evidence that turgor pressure is not the only and not always the main factor influencing, for example, the tension of the plasma membrane, the size and shape of non-apical fungal cells, and is not even always the determining factor of apical growth. This paper characterizes various aspects of the curtain model, previously proposed to describe the regulation of plasma membrane tension in the hyphae of basidiomycetes. The current understanding of the four main components of the curtain model are outlined: the driving actin cytoskeleton, the elastic cell wall, tight adhesion of the plasma membrane to the cell wall and macroinvaginations of the plasma membrane. All four elements, summed in the single curtain model, complement or replace the physiological functions of turgor, and allow imagining how a non-apical fungal cell maintains its integrity and physiological functionality under changing osmotic and other conditions. Further experimental confirmation of the curtain model is not only of fundamental importance for mycology, but also opens up new prospects in the development of drugs that control the growth and pathogenicity of filamentous fungi.

The air attenuation of pure tones as a function of temperature and humidity is well known and described in ISO and ANSI standards. However, room acoustic measurements are performed in octave bands, which is the reason for a complicated, nonlinear behavior of the air attenuation. It is known that room acoustic measurement results depend on air temperature and humidity, and these atmospheric data should always be reported in connection with room acoustic measurements. A calculation model for the air attenuation can make it possible to normalize the room acoustic results. For accurate results it is possible to apply a summation method on each time sample in the impulse response. An approximation to the air attenuation at and above 1 kHz is possible by linearization using the pure-tone attenuation of two different frequencies, one frequency valid for the early part of the impulse response, and another frequency valid for the later part of the impulse response. The purpose of the suggested methods is to make it possible to normalize room acoustic measurements to a standard atmosphere.

Beginning in 2022, the Mpox outbreak, formerly known as monkeypox, has since spread to more than 100 countries and is now a global public health concern. This disease, caused by the Mpox virus, is usually mild, and most infected individuals recover within a few weeks without treatment. However, severe cases have been seen especially in children, pregnant women, or immunocompromised individuals. Antiviral medications such as brincidofovir, tecovirimat, and cidofovir were recently approved for Mpox; but these drugs are expensive and not easily obtainable. Therefore, identifying effective and low-cost drugs against Mpox and testing these through clinical trials remains a priority for global health. Drug repurposing is a well-known strategy for redeploying existing licensed drugs for newer indications, allowing for the shortest possible transition from bench to bedside. Recent in silico studies have determined the efficacy of minocycline, oleanolic acid, ursolic acid, and glycyrrhizinic acid against Mpox virus. Notably, oleanolic acid, ursolic acid, and glycyrrhizinic acid are some of the components of Japanese Kampo medicines, which are low-cost medicines prescribed daily in Japan. Thus, minocycline and Japanese Kampo medicines could potentially be used to treat Mpox.

In 2004, a significant portion of the spruce-dominated forests in the Tatra National Park (northern Slovakia) was destroyed by an exceptionally strong windstorm. Our study focused on the status of deadwood and its influence on post-disturbance forest regeneration 18 years after the destruction. Since some disturbed areas were salvaged and others were not, we could compare the situations between these two management approaches. In total, 40 research sites (20 salvaged and 20 unsalvaged) were measured, each represented by four satellite-like plots with a radius of 4 m. We measured the diameters of deadwood and its decay status (classes 1 – 5). At the same time, we recorded the sizes (stem base diameter and height) and species of young trees. The results showed that while salvage conditions and contact with soil stimulated deadwood decomposition, the diameter of logs was not a significant factor. The highest decay class (3.83) was found in deadwood on salvaged areas and attached to the soil, while the lowest decay class (3.10) was found in deadwood on unsalvaged areas and in the case of logs unattached to the soil. While carbon content (based on percentage of wood mass) did not change with decay class, wood density decreased sharply with decay class. Water moisture showed an increasing tendency with decay class. Moreover, our results showed that post-disturbance management influenced forest regeneration. Significantly higher tree diversity was observed in salvaged areas (5.40 species per plot) compared to unsalvaged areas (3.85 species per plot). While areas with logging were predominantly covered by broadleaved species, those without logging were typically dominated by Norway spruce (Picea abies L. Karst). We concluded that although salvage logging decreased the total carbon and water content in deadwood, it can stimulate tree species diversity. Thus, the currently prevailing opinion about the exclusively negative ecological effects of salvage logging should be accepted with caution, and local conditions must be considered before making broad judgments.

Thermomechanical, biocompatibility, durability, workability and economic characteristics are the main criteria for development of dental alloys. In an attempt to provide a noble metal dental alloy without the known adverse metallic elements, a novel alloy was produced with the addition of Germanium (Ge), as a more cost-effective alternative to other precious alloying metals. The objective of this investigation was to analyse the thermomechanical and biocompatibility properties of a high noble Au-Pt-Ge porcelain-fused-to-metal (PFM) alloy. These properties were investigated with DSC analysis, hardness, density and coefficient of thermal expansion (CTE) measurements, as well as with metallographic and SEM/EDX microstructure investigations, with the production of a test PFM dental bridge, static immersion testing for metal ion release, and an in vitro primary biocompatibility testing on human gingival cells. The results of the thermomechanical testing showed alloy properties suitable for dental restorations and clinical use, with somewhat lower hardness, making the alloy not suitable for extensive multiunit fixed restorations. The microstructure investigations showed segregations of Ge in a homogeneous alloy matrix, which reduce the alloy’s mechanical properties. The produced PFM dental bridge shows excellent workability of the alloy in a dental laboratory setting, as well as a high standard of the final dental restoration. The ion release was negligible, well below any harmful quantities, while the cell viability examination showed significantly higher viability ratings on polished alloy samples as compared to as-cast samples. The results showed that a dental substructure in direct contact with oral tissue and fluids should be highly polished.

There are currently no effective screening measures to detect early or occult tubo-ovarian cancers resulting in late-stage detection and high mortality. This work explores whether an optical imaging catheter can detect early-stage tubo-ovarian cancers or precursor lesions where they originate in the fallopian tubes. This device collects co-registered optical coherence tomography (OCT) and autofluorescence imaging (AFI). OCT provides three-dimensional assessment of underlying tissue structures; autofluorescence imaging provides functional contrast of endogenous fluorophores. Ex vivo fallopian tubes (n=28; n=7 cancer) are imaged; we present methods for the calculation of and analyze eleven imaging biomarkers related to fluorescence, optical attenuation, and OCT texture for their potential to detect tubo-ovarian cancers and other lesions of interest. We visualize folded plicae, vessel-like structures, tissue layering, hemosiderin deposits, and regions of fibrotic change. High grade serous ovarian carcinoma appears as reduced autofluorescence paired with homogenous OCT and reduced mean optical attenuation. Specimens containing a cancerous lesion demonstrate significant increase in median autofluorescence intensity and decrease in entropy compared specimens with no lesion. Non-cancerous specimens demonstrate an increase in optical attenuation in the fimbriae when compared to the isthmus or ampulla. We conclude that this approach shows promise and merits further investigation of diagnostic potential.

This paper aims to present a robust computational technique utilizing finite difference schemes for accurately solving time fractional reaction-diffusion models, which are prevalent in chemical and biological phenomena. The time-fractional derivative is treated in the Caputo sense, addressing both linear and nonlinear scenarios. The proposed schemes were rigorously evaluated for stability and convergence. Additionally, the effectiveness of the developed schemes was validated through various linear and nonlinear models, including the Allen-Cahn equation, the KPP-Fisher equation, and the Complex Ginzburg-Landau oscillatory problem. These models were tested in one, two, and three-dimensional spaces to investigate the diverse patterns and dynamics that emerge. Comprehensive numerical results were provided, showcasing different cases of the fractional order parameter, highlighting the schemes' versatility and reliability in capturing complex behaviors in fractional reaction-diffusion dynamics.

Reliable access to electricity has become a necessity worldwide, and without it, no country can operate health systems and achieve sustainable development goals (SDGs). However, while developed countries have been successfully electrified for many decades, most developing countries have fallen short, contributing to significant impacts, particularly the health sector. The present study explores the relationship between electrification and health vulnerability in developing countries between 1990 and 2020 using the Feasible Generalized Least Square (FGLS) approach. The varied electrification across countries motivates the use of non-linear associations between electrification and health vulnerability. We demonstrate that electrification and health vulnerability have an inverted U-shaped association. Further analysis indicates that most developing countries have achieved a mature level of an inverted U-shaped curve, showing a reduction in health vulnerability with increasing electrification. There are few developing countries, mainly African countries, struggling to reach maturity. The results of this study indicate the need for increased access to electrification, in combination with a reduction in the use of biomass and fossil fuel feedstocks, to mitigate health vulnerability in developing countries.

This article compares the predictive capabilities of six models namely the Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), XGBoost, Random Forest (RF) and Deep Neural Network (DNN) to predict the default behaviour of credit card holders in Taiwan using data from the UCI machine learning database. Python programming language was used for data analysis. Statistical methods were compared with machine learning algorithms using the confusion matrix measured in metric terms of prediction accuracy, sensitivity, specificity, precision, G-mean, F1 score, ROC and AUC. The dataset contains 30,000 credit card user’s information with 6636 default observations and 23,364 non-default cases. The study results found that modern machine learning methods outperformed traditional statistical methods in terms of predictive performance measured by F1 score, G-mean and AUC. Traditional methods like logistic regression were marginally better than linear discriminant analysis and support vector machines in terms of predictive performance measured by area under the receiver operating characteristic curve. In the modern machine learning methods, deep neural networks were better in most of the predictive performance metrics than XGBoost and Random Forest methods.

This study investigates the impact of single prolonged stress (SPS), a model of post-traumatic stress disorder (PTSD), on cardiovascular responses, hypothalamic paraventricular nucleus (PVN) activity, and vascular function to elucidate the mechanisms linking traumatic stress to hypertension. Although SPS did not directly cause chronic hypertension in male Sprague Dawley (SD) rats, it induced acute but transient increases in blood pressure and heart rate and significantly altered the expression of hypertension-associated genes, such as vasopressin, angiotensin II type 1 receptor (AT1R), and FOSL1 in the PVN. Notably, mitochondrial reactive oxygen species (mtROS) were predominantly elevated in the pre-autonomic regions of the PVN, colocalizing with AT1R- and FOSL1-expressing cells, suggesting that oxidative stress amplifies sympathetic activation and stress responses. SPS also triggered vascular inflammation, evidenced by increased mRNA levels of pro-inflammatory cytokines (TNFα and IL1β) and inducible nitric oxide synthase (iNOS) in the aorta, and impaired vascular reactivity to vasoconstrictor and vasodilator stimuli, reflecting compromised vascular function. These findings suggest that SPS sensitizes neuroendocrine, autonomic, and vascular pathways, creating a state of cardiovascular vulnerability that could pre-dispose individuals to hypertension when exposed to additional stressors. Understanding these mechanisms provides critical insights into the pathophysiology of stress-related cardiovascular disorders and underscores the need for targeted therapeutic interventions that address oxidative stress and modulate altered PVN pathways to mitigate the cardiovascular impact of PTSD and related conditions.

Modeling dense nonaqueous phase liquids (DNAPLs) contamination in groundwater is challenging because of its multiphase distribution. To understand the research trends of DNAPL modeling in groundwater, a bibliometric analysis was conducted using CiteSpace based on 614 publications from the WoS Core Collection database (1993-2023). The publications were statistically analyzed, and the research hotspots and trends were summarized. The statistical analysis of the publications indicates that: the United States is leading the international research on DNAPL models, followed by China and Canada; collaboration between countries and disciplines in this field needs to be strengthened. The summary of keyword clustering and burst detection reveals that: the current research hotspots focus on multiphase flow models, mass transfer models, back diffusion, and practical applications of the models; the research trends are centered on back diffusion mechanisms, characterization of contamination source zones and prediction of contaminant distribution in real-world sites, as well as the optimization of remediation strategies.

Integrated Fixed Film Activated Sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at the wastewater treatment plant in an office building in Ho Chi Minh City, Vietnam. Experiments were conducted to ascertain the most favorable working conditions, including Hydraulic Retention Time (HRT), alkalinity dosage, and Dissolved Oxygen (DO). According to the study, the IFAS system had the highest nitrogen removal effectiveness when operated at a hydraulic retention time (HRT) of 7 hours, an alkalinity dose of 7.14 mgCaCO3/mgN-NH4+, and a dissolved oxygen (DO) value of 6 mg/L. The nitrification efficiency ranges from 89.2% to 98.8%. The nitrate concentration post-treatment is within the range of 27 – 45 mg/L, which is lower than the allowable discharge limit of 60 mg/L as per Vietnam's wastewater discharge requirements. The research findings have enhanced the efficiency of the office building management process, thereby promoting the sustainable growth of society.

This paper proposes an innovative postulate based on experimental observations, namely, that the speed of light can vary between two inertial reference systems. This postulate is defined as the principle of relative change in the speed of light, which refreshes the concept of absolute speed of light in traditional physics. By integrating the principle of the invariance of the speed of light with the principle of relativity in relativity theory, several important conclusions are derived: space and time must be capable of and proportionally expand and contract. Between two inertial reference systems with different relative speeds of light, objects have an energy difference of k^2 times, which induces a natural tendency for objects to move towards a state of lower energy. The acceleration is only related to the relative change rate of the speed of light in vacuum space and is independent of the mass of the object. The kinetic energy obtained by the object comes from the reduction of internal energy of the object, emphasizing the key role of energy conversion in this process. The paper provides a new theoretical perspective for explaining the physical mechanisms of universal gravitation and dark energy.

Physical activity (PA) benefits are well-established, yet many US adults fail to meet PA guidelines. This is especially true for minorities facing social inequities. This study explored barriers and facilitators to PA among urban Midwestern minorities using a mixed-methods approach framed on the socio-ecological model. A cross-sectional survey was conducted among community-dwelling minorities. Participants were grouped as completing low (LLPA) or high (HLPA) weekly leisure-time PA for comparison. Quantitative analysis included MANOVA, follow-up ANOVAs, and calculation of effect sizes. Qualitative data were assessed using inductive thematic analysis. Twenty-nine adults (44.83% Black, 41.37% Latino) participated in the study. The HLPA group (n = 18) reported higher leisure-time PA (p = 0.001, d = 2.21) and total PA (p = 0.02, d = 1.00) compared to the LLPA group (n = 11). LLPA participants faced more personal barriers to PA (p = 0.02, d = -0.92). Common barriers identified in the interviews included a lack of time and financial costs. Facilitators included social support and available PA facilities. Both groups achieved USPA guidelines through different PA domains. Increasing social support and lowering PA-related costs could enhance participation. Addressing barriers and leveraging existing facilitators are crucial to increasing PA among minorities.

Background: To investigate the association between enteral feeding and the risk of pneumonia in critical care adult patients. Methods: An updated literature review of studies discussing between 2016 and 2023. CINAHL, Cochrane, Embase, PubMed, Scopus, and Web of science databases were used to explore studies regarding our subject, the association between enteral feeding and the risk of pneumonia in critical care adults. Results: Enteral nutrition (EN) has been linked to a significant reduction in pneumonia, as well as shorter ICU or hospital stays, and decreased mechanical-ventilation duration in numerous studies. Conversely, pneumonia risk and other infections, as well as the fatality rate, has been found to increase with EN. Early initiation of EN within 48 hours, along with a low-calorie diet containing (< 600 Kcal/day) demonstrated a notable decrease in the occurrence of Ventilator-Associated Pneumonia (VAP) when contrasted with delayed EN and a high-calorie diet. EN was associated with a marked decrease in adverse events including aspiration pneumonia, emesis, and the escalation of respiratory support. Conclusion: EN is safe and effective in critically ill patients. It is advisable for future research to investigate the monitoring of larger sample sizes to ascertain the most effective feeding methods in the intensive care unit.

Increased platelet activity is a risk factor of thrombotic events in cardiovascular patients. We studied the relationship between platelet function, platelet size and content of reticulated platelets (RP) in patients with coronary heart disease (CHD, n = 55) and acute coronary syndrome (ACS, n = 95) receiving acetylsalicylic acid + clopidogrel or ticagrelor respectively. Control group consisted of patients with risk factors for CHD, but no CHD/ACS and free of antiplatelet drugs (n = 66). Platelet function was evaluated by exposure of activated glycoprotein (GP) IIb-IIIa and P-selectin. In the control group, platelets were activated by TRAP (Thrombin Receptor Activating Peptide) 10 µM, ADP 20, 5, 2.5 µM and in CHD/ACS groups, by TRAP 10 µM, ADP 20, 5 µM (+/- epinephrine 20 µM). Platelet size was assessed by mean volume, % large forms and forward scattering. RP were stained by thiazole orange. In the control group activated GP IIb-IIIa and P-selectin correlated with platelet size and RP content after platelet activation by all agonists. Despite the decrease of platelet activity by antiplatelet drugs, most correlations (primarily for activated GP IIb-IIIa) were preserved in CHD/ACS patients. In conclusion, increased platelet size and RP content are associated with increased platelet activity and reduced efficacy of antiplatelet therapy.

This research explores the feasibility of a data-driven optimization algorithm for placing sparse arrays of artificial hair-cell airflow velocity sensors to enable agile and robust flight-by-feel control of unmanned aircraft. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm exploits the information-rich features of large flow datasets to find a near-optimal set of locations for flow sensors on a wing. The flow information from these sensors can be used to predict flight state parameters such as the angle of attack, mimicking the fly-by-feel control systems observed in nature. We evaluate the effectiveness of this approach for a blunt-edged 45∘ swept delta wing. Exploiting the information in the complex airflow patterns over this wing, the SSPOP algorithm selects a sensor location design point (DP) which reliably ranks within the top 1% of all possible DPs by root mean square error in angle of attack prediction. This performance was consistent across models of various artificial hair lengths, and one model with variable hair lengths. This bioinspired dimension-reducing method for sensor placement optimization exhibits reliability and flexibility benefits when compared with a conventional greedy search algorithm and gradient-based optimization using auto-differentiation. The successful application of SSPOP in complex 3D flows paves the way for experimental evaluation of data-driven sparse sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

Little is known about skeletal muscle thickness, echogenicity, and muscle quality (handgrip strength /muscle thickness) in breast cancer-related lymphedema (BCRL). Using B-mode ultrasound, we recorded the raw radiofrequency data of the affected (AA) and unaffected (UA) arms of women (n=20) with BCRL, and in 20 control women with no lymphedema (CA). The data were converted into images and measurements of skin, subcutaneous fat and muscle thickness were obtained. Within a designated region of interest, muscle echo-intensity was assessed using computer graded grey scale and muscle thickness was measured using ImageJ2. Handgrip strength was measured using standard dynamometry. We found that forearm muscle thickness was similar among AA, UA, and CA. When compared to the unaffected and control arms, the affected arm had a significantly higher (p 0.013) muscle echo-intensity. When compared to the AA, handgrip strength was similar to UA (p 0.401) but lower than CA (p 0.05). We conclude that the use of B-mode ultrasound is a reliable method to assess muscle thickness and EI in BCRL. When comparing AA to UA, the elevated levels of muscle EI in AA did not influence strength or muscle quality. The elevated EI in AA is a marker of abnormal health that needs to be further explored.

This study examines the impact of natural resource exploitation, renewable energy consumption, economic growth, biocapacity, and information and communication technologies (ICT) on the ecological footprint of BRICS+ nations using panel data from 1991 to 2019. Advanced econometric techniques, including FMOLS, DOLS, CCR, and GMM, reveal significant findings relevant to sustainability-focused policymakers. The results show that natural resource exploitation significantly contributes to environmental degradation, while renewable energy consumption mitigates these effects to varying degrees across the studied countries. Although economic growth is crucial, it worsens ecological footprints unless accompanied by sustainable practices. ICT and biocapacity emerge as key factors in promoting environmental sustainability, with ICT enhancing innovation and efficiency to reduce ecological impacts. The study emphasizes the need for tailored policy frameworks that align economic growth with environmental sustainability, advocating for the adoption of renewable energy, eco-innovations, and green finance initiatives suited to the unique conditions of BRICS+ nations. The findings aim to guide policymakers in advancing sustainable development and mitigating the adverse environmental impacts of rapid industrialization and urbanization, while contributing to the global discourse on achieving a balance between economic growth and ecological well-being in developing countries.

Bipolar disorder (BD) is a complex mental health condition characterized by alternating periods of mania and depression. This review provides a comprehensive overview of BD, focusing on its genetics, causal hypotheses, clinical signs and evolution, potential biomarkers with an emphasis on electroencephalography (EEG), and treatment options. Genetic studies have identified several susceptibility genes and polygenic risk scores, highlighting the heritable nature of BD. Various causal hypotheses, including monoamine dysregulation, kindling, circadian rhythm disruptions, and neuroinflammation, have been proposed to explain its pathophysiology. The clinical course of BD is characterized by recurrent episodes of mania/hypomania and depression, with significant heterogeneity among individuals. EEG and other biomarkers hold promise for improving diagnosis, predicting treatment response, and elucidating the neurobiological underpinnings of BD. Current treatment options include pharmacotherapy, psychotherapy, and neuromodulation techniques, which can be tailored to individual needs based on clinical presentation and response to treatment. Future research should focus on identifying more specific biomarkers, developing novel treatments, and optimizing existing therapies to improve outcomes for individuals with BD.

Chronic noncommunicable diseases (NCDs) are responsible for approximately 74% of deaths globally. Medicinal plants have traditionally been used to treat NCDs, including diabetes, cancer, and rheumatic diseases, and are a source of anti-inflammatory compounds. This study aimed to evaluate the anti-inflammatory effects of Rhus trilobata (Rt) extracts and fractions in lipopolysaccharide (LPS)-induced inflammation models in vitro and in vivo. The aqueous extract (RtAE) and five fractions (F2 to F6) were obtained via C18 solid-phase separation and tested in murine LPS-induced J774.1 macrophages. Key inflammatory markers such as IL-1β, IL-6, TNF-α, and COX-2 gene expression were measured using RT-qPCR, and PGE2 production was assessed via HPLC-DAD. The in vivo effects were tested in an LPS-induced paw edema model in Wistar rats. Results showed that RtAE at 15 μg/mL significantly decreased IL-1β and IL-6 gene expression in vitro. Fraction F6 further reduced IL-1β, TNF-α, and IL-6 gene expression, COX-2 expression, and PGE2 production. In vivo, F6 significantly reduced LPS-induced paw edema, inflammatory infiltration, and IL-1β and COX-2 protein expression. These findings support the anti-inflammatory potential of RtAE and F6, reinforcing the medicinal use of Rt.

Tefluthrin (Tef) is categorized as a type-I pyrethroid insecticide, telmisartan (Tel) functions as an angiotensin II receptor blocker, and KB-R7943 was identified as an inhibitor of Na+-Ca2+ exchange process. However, the influence of these compounds on the amplitude and gating properties of voltage-gated Na+ current (INa) in neurons associated with pain signaling remains unclear. In cultured dorsal root ganglion (DRG) neurons, whole-cell current recordings revealed that Tef or Tel increased the peak amplitude of INa, concomitant with an elevation in the time constant of INa inactivation, particularly in the slow component. Conversely, exposure to KB-R7943 resulted in a depression in INa, coupled with a decrease in the slow component of the inactivation time constant of INa. Theoretical simulations and bifurcation analyses were performed on a modeled interneuron in the spinal dorsal horn. The occurrence of INa inactivation accentuated the subthreshold oscillations (SO) in the membrane potential. With an increase in applied current, SO became more pronounced, accompanied by the emergence of high-frequency spiking (HF) with a frequency of approximately 150 Hz. Moreover, an elevation in INa conductance further intensified both SO and HF. Consequently, through experimental and in silico studies, this work reflects that Tef, Tel, or KB-R7943 significantly impacts the magnitude and gating properties of INa in neurons associated with pain signaling. The alterations in INa magnitude and gating in these neurons suggest a close relationship with pain transmission.

Modern advances in technology have increased the demand for traditional accounting systems to be upgraded for real-time data processing, security, and standardized reports. Thus, this paper proposes a new accounting information system that integrates IoT, blockchain, and XBRL. The proposed system aims to automate the accounting process by using IoT to collect data and send it automatically to a blockchain, which acts as a database that will generate journal entries automatically through smart contracts. XBRL will then be used as an output method for standardized financial reports based on the data transferred from the blockchain. This paper uses a qualitative research design based on semi-structured interviews with 13 industry experts from IT engineering, academia, and financial systems analysis. NVivo software was used to conduct a thematic analysis of interview transcripts. The findings revealed the technical feasibility, challenges, and benefits of the proposed integration and identified the most efficient mechanism for data transmission across the three technologies. The paper concluded that while integration complexity and user adoption are challenging, this integrated system can revolutionize accounting by enabling real-time data capture, automation of essential operations, data security, and integrity improvements. To our knowledge, this is the first paper to develop a comprehensive accounting information system framework using IoT, blockchain, and XBRL to automate data collection, improve data security, and streamline financial reporting. The study's potential to impact accounting systems and financial reporting research and practice emphasizes its importance.

An approach to estimate the dynamic characteristic of multilayered three-dimensional cubic quasicrystal cylindrical shells, annular plates, and truncated conical shells with different boundary conditions is presented. These investigated structures can be in a vacuum, totally filled with quiescent fluid, and subjected to internal flowing fluid, in which the fluid is incompressible and inviscid. The velocity potential, Bernoulli’s equation, and impermeability condition have been applied to the shell-fluid interface to obtain an explicit expression, from which the fluid pressure can be converted into the coupled differential equations in terms of displacement functions. The state-space method is formulated to quasicrystal linear elastic theory to derive the state equations for three structures along the radial direction. The mixed supported boundary conditions are represented by means of the differential quadrature technique and Fourier series expansions, respectively. A global propagator matrix, which connects the field variables at the internal interface to those at the external interface for the whole structure, is further completed by joint coupling matrices to overcome the numerical instabilities. Numerical examples show the correctness of the proposed method and the influence of the semi-vertical angle, different boundary conditions, and the fluid debit on the natural frequencies and mode shapes for various geometries and boundary conditions.

The finite volume method (FVM) is a kind of numerical analysis method that can take into account topography and apply local subdivision cells as the finite element method (FEM). The adjoint state method (ASM) can easily calculate the gradient vector of the objective function for the inversion. The author developed a program that applied these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. As a result, it was confirmed that the program can perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity.

Background: The CoBaTrICE initiative standardized intensive care training throughout Europe. Pericardiocentesis, an important yet infrequent operation, poses unique training challenges often unmet by conventional methods. This study evaluates the efficacy of virtual reality (VR) simulations and 3D-printed mannequins in pericardiocentesis training, both crafted from scratch using highly affordable materials and free software. Methods: Thirty-five final-year medical students participated in this prospective, quasi-experimental study. Initially, students underwent VR simulation training, followed by training using 3D-printed self-made mannequins. Learning outcomes were assessed using the Objective and Structured Clinical Examination (OSCE) questionnaire. Heart rate variability (HRV) analysis was employed to monitor stress responses, while the NASA Task Load Index (NASA-TLX) was used to gauge self-perceived difficulty. Results: Although the mannequin model induced more stress reactions, it excelled in tasks requiring fine motor skills, such as correct placement and asepsis maintenance. In contrast, lower NASA-TLX scores indicated that the VR model imposed less mental demand and effort, reflecting a reduced cognitive load. Conclusion: Both VR simulations and 3D-printed mannequins effectively taught pericardiocentesis skills, each offering distinct advantages. Mannequins enhanced fine motor skills, whereas VR reduced cognitive load and increased engagement. The combination of both approaches could maximize training outcomes, particularly in resource-constrained environments, thus broadening access to advanced simulation education.

Pregnancy is associated with significant physiological changes, including alterations in lipid metabolism, which can have implications for both maternal and fetal health. This study aimed to evaluate serum lipid profile variations among healthy Sudanese women during the second and third trimesters of pregnancy. A total of 60 pregnant women, divided equally between the second and third trimesters, were compared with 30 non-pregnant, age-matched controls. Serum levels of total cholesterol, triglycerides, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were measured using a BTS-Biosystem analyzer. The results revealed a statistically significant increase in total cholesterol, triglycerides, LDL, and HDL levels among pregnant women compared to the control group (p < 0.01). Additionally, lipid levels were significantly higher in the third trimester than in the second trimester. A weak positive correlation was found between parity and serum levels of total cholesterol, triglycerides, and LDL, while no significant correlation was observed for HDL. These findings suggest that pregnancy, particularly in the third trimester, is associated with substantial increases in serum lipid levels, highlighting the need for monitoring lipid profiles during pregnancy to manage potential risks of hyperlipidemia and its associated complications.

Endogenous bioelectrical patterns are an important regulator of anatomical pattern during embryogenesis, regeneration, and cancer. While there are three known classes of instructive bioelectric patterns: directly encoding, indirectly encoding, and binary trigger, it is not known how these design principles could be exploited by evolution and what their relative advantages might be. To better understand the evolutionary role of bioelectricity in anatomical homeostasis, we developed a neural cellular automaton (NCA). We used evolutionary algorithms to optimize these models to achieve reliable morphogenetic patterns driven by the different ways in which tissues can interpret their bioelectrical pattern for downstream anatomical outcomes. We found that: (1) All three types of bioelectrical codes allow the reaching of target morphologies; (2) Resetting of the bioelectrical pattern and the change in duration of the binary trigger alter morphogenesis; (3) Direct pattern organisms show an emergent robustness to changes in initial anatomical configurations; (4) Indirect pattern organisms show an emergent robustness to bioelectrical perturbation; (5) Direct and indirect pattern organisms show an emergent generalizability competency to new (rotated) bioelectrical patterns; (6) Direct pattern organisms show an emergent repatterning competency in post-developmental-phase. Because our simulation was fundamentally a homeostatic system seeking to achieve specific goals in anatomical state space, we sought to understand the role of anxiolytics that reduced concern over the distance to those goals. We simulated selective serotonin reuptake inhibitors, which diminished ability of artificial embryos to correctly interpret bioelectric patterns due to an altered organismal reward machinery, leading to higher variance of developmental outcomes, global morphological degradation, and induced in some organisms anatomical bistability. These computational findings were validated by data collected from in vivo experiments in SSRI exposure in planarian flatworm regeneration.

One of the efficient data mining tools is density-based clustering, including the density grid-based clustering. However, a common drawback always existing in clusters made by the density grid-based method is the existence of weakly connected grids deriving mainly from noise. Appearing such an unwanted connection with a high frequency reduces the accuracy of the obtained cluster data space (CDS) and its application efficiency. Here, we present an essential improvement to overcome this problem. First, we describe a concept of the weak-connected grid cell (WCG) and present a fuzzy-type approximation to depict the density-based distribution of data points at grid nodes. Then, we propose a strategy of searching WCG for density grid-based clustering (SWCG-DGB) to set up a CDS, filter noise, and tune the created CDS. A buffer is deployed during this phase to collect border points and filter noise, which improves the computational time significantly, especially for noisy datasets. Results from numerical surveys reflected the compared efficiency of this method in clustering validity, including the accuracy of the number of clusters.

As the smallest member of the fullerene family, C20 is yet to be discovered in planetary nebulae. In this work, we present a quantum chemical study via density functional theory (DFT) on the ionization tolerance of this molecule in the space environment. Considering that the ionization and excitation phenomena play key roles in alerting the lifetime of a molecule, we examined both ground and excited electronic states potential energy surfaces (PES) of C20 and its cations C20q+. Our theoretical results indicate that the C20 cage tolerates a positive charge as high as 13+ via characterizing local minimum geometries on both mentioned electronic states. We also explored theoretically and systematically, scenarios in which the electronic structure of neutral C20 is excited to very high spin multiplicity (beyond triplet state) and local minimum molecular geometries with cage structure are well characterized. We anticipate that such structural resistance to excitation and ionization deliver a prolonged lifetime necessary for the spectroscopic detection of this interesting molecule and its cations in space and potentially in planetary nebulea (PN).

Floods in various regions cause irreparable damage to infrastructure, agricultural lands, and industrial centers. In recent years, due to the effects of climate change and, in particular, the increased activity of the monsoon system in the Balochistan region located in southern Sistan and Baluchestan province, local rivers have overflowed, causing widespread flooding and significant damage. Accurate flood routing not only provides decision-makers with precise information about flood volume and flow behavior but also facilitates planning for effective preventive measures. In this study, the Muskingum-Cunge model was used to simulate floods in eight major rivers of Balochistan, including Kajou, Sarbaz, Nik Shahr, Kehir, Bahu, Sia Jangal, Rapch, and Kamb. The model parameters (K and X) were optimized using two machine learning algorithms: Particle Swarm Optimization (PSO) and Harmony Search (HS). The results showed that in most stations, the PSO algorithm outperformed HS. The algorithms were evaluated using the coefficient of residual mass (CRM), normalized root mean square error (NRMSE), efficiency (EF), and agreement index (d). For instance, at the Kajou station, PSO improved CRM by 0.017, Ef by 0.921, d by 0.982, and NRMSE by 0.099 compared to HS. At the Kamb station, both algorithms yielded comparable results. Considering the overall better performance of the PSO algorithm in most evaluation indices, it can be concluded that this algorithm is a more suitable option for optimizing the parameters of the Muskingum-Cunge model and simulating flood hydrographs with higher accuracy at most of the studied stations.

Accurate, rapid, and stable prediction of electrical energy consumption is essential for decision-making, energy management, efficient planning, and reliable power system operation. Errors in forecasting can lead to electricity shortages, wasted resources, power supply interruptions, and even grid failures. Accurate forecasting enables timely decisions for secure energy management. However, predicting future consumption is challenging due to the variable behavior of customers, requiring flexible models that capture random and complex patterns. Existing forecasting methods, both traditional and modern, have limitations and do not fully meet accuracy expectations. To address these issues, this research introduces a hybrid models that combine FCRBM based forecaster, and GWDO based optimizer, namely FS-FCRBM-GWDO approach to enhance the model performance in STLF have been developed. While some models excel in accuracy and others in convergence rate, both aspects are crucial. The main objective is to create a forecasting model that provides reliable, consistent, and precise predictions for effective energy management. This led to the development of a novel two-stage hybrid model. The first stage predicts electrical energy usage through four modules using deep learning, support vector machines, and optimization algorithms. The second stage optimizes energy management based on predicted consumption, focusing on reducing costs, managing demand surges, and balancing electricity expenses with customer inconvenience. This approach benefits both consumers and electricity corporations by lowering bills and enhancing power system stability. Simulation results validate the proposed model's efficacy and efficiency compared to benchmark models.

The sustainability concept has acquired a variety of meanings according to different currents of thought and the context in which it is used. The aim of this research was to characterize the perception of producers, extension agents and officials regarding sustainable cattle ranching (SCR) in an area where tropical cattle ranching is practiced. A survey was applied to producers chosen through stratified random sampling, and to extension agents and officials selected using the snowball technique. The perception of SCR was determined under two contexts: 1) the idea or interpretation of the individual and 2) the assessment (positive or negative) of this type of cattle ranching (net perception index, NPI). The extension agents oriented their perception of SCR mainly in economic (52.2%) and environmental (47.8%) aspects, similar to the producers (48.4% and 21.3% respectively), while the officials related it more to an environmental dimension (71.4%). It is concluded that the perception of SCR in general is positive, but its conceptualization is differentiated, according to the role the individuals play in the activity, their academic training and their expectations.

1) Background: Overweight children usually have lower levels of physical activity (PA) than their normal-weight peers. Low PA predisposes to increase fat mass in the body. The aim of this study was to evaluate the effectiveness of school-based PA intervention on anthropometric indicators and body composition of overweight and obese children during a two-year observation period, from the age of 10 to 12. (2) Materials and methods: The research included 148 children with overweight or obesity who were born in 2007. There were two groups of children of standard and elevated PA at school (SPA and EPA, 4 and 10 hours of physical education lessons a week, respectively). An anthropometric and body composition measurements were done. Body mass index (BMI), fat mass (FM), fat-free mass (FFM), skeletal muscle mass (SMM) and total body water (TBW) were determined. Totally, 5 measurements were done at intervals of 5–6 months. (3) Results: In EPA, the percentage of obese children decreased from 46% to 35.25%, and in SPA increased from 42.75% to 46%. In EPA, FM decreased from 28.65% to 26.41%, and in SPA increased from 30.31% to 31.75%. The highest increase in FFM was in EPA boys, while SPA boys recorded the highest decrease. In SPA, SMM increased by 0.43% from 38.85% to 39.28%, and in EPA by 2.51% from 40.27% to 42.78%. TBW In EPA slightly increased from 53.26% to 53.59%, and in SPA decreased from 50.70% to 49.93%. (4) Conclusions: The elevated PA at school has a positive effect on the BMI and body composition of children who are overweight or obese. Increasing the mandatory number of physical education lessons in school curricula is an efficient strategy for reducing obesity in school-aged children.

Background/Objectives: Hematopoietic stem cell transplantation (HSCT) in pediatric and young adult (YA) patients can lead to endotheliopathy, such as thrombotic microangiopathy (TMA), sinusoidal obstruction syndrome (SOS), and diffuse alveolar hemorrhage (DAH). Natriuretic peptides have been studied as markers of endotheliopathy and critical illness. We hypothesized that elevation in NT-proBNP was associated with development of endotheliopathy (DAH, SOS, or TMA) in the first 100 days following HSCT in pediatric and YA patients. Methods: IRB exempt status was obtained. This retrospective case-control study reviewed HSCT at our institution from 2016-2020. Cases were selected based on an endotheliopathy diagnosis in the first 100 days after HSCT. Cases were matched with controls. Baseline and near-event NT-proBNP levels were compared between cases and matched controls. Effect of NT-proBNP levels on developing endotheliopathy was estimated using conditional logistic regression. Results: Sixty-two patients were included (31 cases, 31 controls). Near-event NT-proBNP was significantly higher in cases compared to controls (Median: 473 vs. 187 pg/mL, p = 0.03, Wilcoxon rank-sum test), in contrast to comparison in baseline NT-proBNP (Median: 86 vs. 86 pg/mL, p = 0.51). After adjusting for co-variates, association between near-event NT-proBNP and odds of developing endotheliopathy did not achieve statistical significance. However, trends from most common transplant indications suggested an association between elevated near-event NT-proBNP level and endotheliopathy, particularly in acute lymphoblastic leukemia (ALL) patients. Conclusions: NT-proBNP should be studied further as a biomarker for endotheliopathy in pediatric and YA patients undergoing HSCT. This may be particularly relevant for patients undergoing HSCT for ALL.

The advancement of computational drug discovery and design necessitates continuous innovation to enhance the accuracy and scope of predictive models for early-stage drug research and development. This article introduces a novel workflow for in silico generation of structural and intermolecular binding affinity data with reasonable accuracy, combining two computational tools: Modeller and Prodigy. By leveraging synthetic structural and biophysical data, this approach addresses the limitations of existing experimental datasets, generating extensive, high-quantity binding affinity data with reasonable accuracy for biomolecular binding pairs, which broadens the horizon of computational biomolecule design and discovery by enabling extensive exploration of the sequence space of biomolecular binding pairs, and narrows the gap between experimental binding affinity data and its unexplored territories. Overall, this article presents a methodological advance to enhance the accuracy and scope of computational biomolecule discovery and design, paves the way for the development of preclinical candidates with improved efficacy and specificity, and holds transformative potential for further advancements in artificial intelligence-enabled biomolecule discovery and design in the future.

Decidualization of the uterine endometrium is a critical process for embryo implantation in mammals, primarily occurring on gestational day 8 in pregnant mice. However, the interplay between the maternal gut microbiome, metabolism, and the uterus at this specific time point remains poorly understood. This study employed a multi-omics approach to investigate the metabolic, gut microbiome, and transcriptomic changes associated with early pregnancy (gestational day 8 (E8)) in mice. Serum metabolomics revealed a distinct metabolic profile in E8 compared to controls, with differential metabolites primarily enriched in amino acid metabolism pathways. Gut microbial composition showed that E8 mice exhibited higher alpha-diversity and a significant shift of beta-diversity. Specifically, the E8 group displayed a decrease in pathogenic Proteobacteria and an increase in beneficial Bacteroidetes and S24-7 taxa. Transcriptomics identified myriads of distinct gene between E8 and control mice. The differentially expressed genes were enriched in pathways involved in Alanine, Aspartate and Glutamate metabolism, PI3K-Akt signaling, and PPAR signaling pathway. Integrative analysis of the multi-omics data uncovered potential mechanistic relationships among the differential metabolites, gut microbiota, and uterine gene expression changes. Notably, the gene Asns showed strong correlations with specific gut S24-7 and metabolite L-Aspartatic acid, suggesting its potential role in mediating the crosstalk between the maternal environment and embryo development during early pregnancy. These findings provide valuable insights into the complex interplay between the maternal metabolome, gut microbiome, and uterine transcriptome in the context of early pregnancy, which may contribute to our understanding of the underlying mechanisms of embryo implantation and development.

With the increasing awareness of environmental protection, the rotary hearth furnace system has emerged as a key technology that facilitates a win-win situation for both environmental protection and enterprise economic benefits. This is attributed to its high flexibility in raw material utilization, capability of directly supplying blast furnaces, low energy consumption, and high zinc removal rate. However, the complexity of the raw material proportioning process, coupled with its reliance on manual labor, results in a time-consuming and inefficient process. This paper innovatively introduces an intelligent formula method for raw materials based on online clustering algorithms and develops an intelligent batching system for rotary hearth furnaces. Firstly, the ingredients of raw materials undergo data preprocessing, which involves using the Local Outlier Factor (LOF) method to detect any abnormal values, Kalman filtering to smooth the data, and performing one-hot encoding to represent the different kinds of raw materials. Afterwards, the affinity propagation (AP) clustering method is used to evaluate past data on the ingredients of raw materials and their ratios. This analysis aims to extract information based on human experience with ratios and create a library of machine learning formulas. The incremental AP clustering algorithm is utilized to learn new ratio data and continuously update the machine learning formula library. To ensure that the formula meets the actual production performance requirements of the rotary hearth furnace, the machine learning formula is fine-tuned based on expert experience. The integration of machine learning and expert experience has demonstrated good flexibility and satisfactory performance in the practical application of intelligent formulas for rotary hearth furnaces. An intelligent batching system is developed and executed at a steel plant in China. It shows an excellent user interface and has significantly enhanced batching efficiency and product quality.

We used numerical methods to define the normative structure of the different stages of sleep and wake (W) in a pilot study of 19 subjects without pathology (18–64 years old) using a double-banana bipolar montage. Artefact-free 120–240 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum (PS) was calculated via fast Fourier transform and used to compute the areas for the delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands, which were log-transformed. Furthermore, Pearson’s correlation coefficient and coherence by bands were computed. Differences in logPS and synchronization from the whole scalp were observed between the sexes for specific stages. However, these differences vanished when specific lobes were considered. Considering the location and stages, the logPS and synchronization vary highly and specifically in a complex manner. Furthermore, the average spectra for every channel and stage were very well defined, with phase-specific features (e.g., the sigma band during N2 and N3, or the occipital alpha component during wakefulness), although the slow alpha component (8.0–8.5 Hz) persisted during NREM and REM sleep. The average spectra were symmetric between hemispheres. The properties of K-complexes and the sigma band (mainly due to sleep spindles – SSs) were deeply analysed during the NREM N2 stage. The properties of the sigma band are directly related to the density of SSs. The average frequency of SSs in the frontal lobe was lower than that in the occipital lobe. In approximately 30% of patients, SSs showed bimodal components in anterior regions. qEEG can be easily and reliably used to study sleep in healthy subjects and patients.

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is con-structed based on state analysis, considering the operation status of the charging station and users' charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data is established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging station is conducted using the lack of power supply (ENC), evaluating the risk level of each station, and determining the operation and maintenance order. The optimal opera-tion and maintenance model for DC charging stations, aimed at achieving both economic and reliable goals, is constructed to determine the operation and maintenance schedule for each sta-tion. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall ben-efits of operation and maintenance while meeting the required standards.

The intricate relationship between genomic mutations and proteomic network topology represents a frontier in understanding cellular resilience and disease mechanisms. This study presents a novel approach to analyzing how proteomic topological structures evolve and potentially break down in response to accumulating genomic mutations, offering insights into the complex interplay between genetic alterations and protein interaction networks. We developed a computational model simulating a network of ten key proteins (A-J) over 20 discrete time points, each representing a state of increasing genomic mutation load. Our model incorporates dynamic protein interaction strengths that fluctuate in response to simulated genomic alterations and a topological representation of the protein network, allowing for visualization of structural changes. Not forgetting a quantitative measure of network integrity, correlating with the system's ability to maintain function under mutational stress. Our Key findings include: visualization of proteomic network evolution through a series of topological graphs, revealing how genomic mutations progressively alter protein interaction patterns and identification of a critical "breakage point" in the network topology, signifying a threshold where genomic mutations overwhelm the protein network's ability to maintain its functional structure. And also quantification of network properties, including interaction strengths and overall network density, demonstrating the non-linear relationship between genomic mutations and proteomic topological integrity.The observed breakage point may represent a critical threshold in disease progression, where the accumulation of genomic mutations leads to a collapse in the proteomic interaction network, potentially triggering pathological states. This methodology offers a new perspective on the genotype-phenotype relationship, viewing it through the lens of protein network topology. Our approach provides a framework for future studies to analyze how specific genomic mutations might impact proteomic structures, potentially leading to new insights in cancer research, neurodegenerative disorders, and other mutation-driven diseases. It also suggests that maintaining proteomic topological integrity could be a key factor in cellular resilience against genomic instability.

Introduction. Pituitary adenomas constitute the second most frequent neoplasm of the central nervous system and despite the often-indolent behavior of these tumors, patients affected by pituitary adenomas show higher morbidity and mortality rates. Surgery offers good results in terms of symptoms and disease control: the aim of this study was to evaluate how the neurosurgical treatment for the removal of a pituitary adenoma through a trans-sphenoidal approach can modify the patient's hormonal panel and its influence on the overall clinical outcome. Materials and methods. Between January 2018 and September 2021, 69 patients who underwent surgery for pituitary adenoma operated via the trans-sphenoidal approach were enrolled in the study. Clinical and laboratory data included pre- and post-operative hormonal status, assessed before surgery and within the following 48 hours. Results. Remission of endocrinological values outside physiological ranges and resolution of symptoms were considered as favorable outcome. Surgical treatment was statistically significant as factor to normalize the following hormones: ACTH (p = 0.014), TSH (p &lt; 0.0001), fT3 (p &lt; 0.0001), fT4 (p &lt; 0.0001), FSH (p &lt; 0.0001), LH (p = 0.001), testosterone (p = 0.001), prolactin (p &lt; 0.0001), confirming previous literature findings. Furthermore, the association between surgery and resolution of pre-operative visual disturbances was statistically significant (p &lt; 0.0001). Overall, 59% of patients experienced complete or partial remission of the pre-operative endocrinological abnormalities and in 76% their initial symptoms improved. Conclusions. This study confirms, in our experience, the excellent risk-benefit ratio supporting the use of trans-sphenoidal endoscopic surgery as an effective therapeutic approach for the removal of pituitary adenomas with improvement in the post-operative hormonal and clinical status.

Student attrition poses significant societal and economic challenges, leading to unemployment, lower earnings, and other adverse outcomes for individuals and communities. To address this, predictive systems leveraging machine learning and Big Data aim to identify at-risk students early and intervene effectively. This project focuses on extracting key parameters from past dropout data to construct a predictive model and alert authorities to intervene promptly. Two preliminary trials refine machine learning models, establish evaluation standards, and optimize hyperparameters. These trials facilitate systematic exploration of model performance and data quality assessment. Achieving 100% accuracy in dropout prediction, the study identifies academic performance as the primary influencer, with early-year subjects like Mechanics and Materials, Design of Machine Elements, and Instrumentation and Control having significant impact. The longitudinal effect of these subjects on attrition underscores the importance of early intervention. Proposed solutions include early engagement and support or restructuring courses to better accommodate novice learners, aiming to reduce attrition rates.

Histamine (HA), a biogenic monoamine, exerts its pleiotropic effects through four H1R–H4R histamine receptors, which are also expressed in brain tissue. Together with the projections of HA-producing neurons located within the tuberomammillary nucleus (TMN), which innervate most areas of the brain, they constitute the histaminergic system. Thus, while remaining a mediator of the inflammatory reaction and immune system function, HA also acts as a neurotransmitter and a modulator of other neurotransmitter systems in the central nervous system (CNS). Although the detailed causes are still not fully understood, neuroinflammation seems to play a crucial role in the etiopathogenesis of both neurodevelopmental and neurodegenerative (neuropsychiatric) diseases, such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD) and Parkinson's disease (PD). Given the increasing prevalence/diagnosis of these disorders and their socioeconomic impact, the need to develop effective forms of therapy has focused researchers' attention on the brain's histaminergic activity and other related signaling pathways. This review presents the current state of knowledge concerning the involvement of HA and the histaminergic system within the CNS in the development of neurodevelopmental and neurodegenerative disorders.

The emergence of superhydrophobicity-based antibacterial materials represents a promising approach to upholding surface cleanliness and hygiene, effectively preventing bacterial adhesion. This research describes the synthesis of a superhydrophobic coating with antibacterial and bacteriostatic properties using silica nanoparticles (SiO2 NPs) modified with 1H,1H,2H,2H-Perfluorodecyltriethoxysilane (PFDTES). TEM, XRD, EDS, SEM, and FTIR analyses were conducted to study its morphology and surface characterization. Additionally, the coating was applied on glass substrates using the spray coating method, varying the number of layers to evaluate antibacterial and bacteriostatic properties through turbidimetry and inhibition halo measurement techniques. The durability of the coatings was also assessed by exposing them to outdoor conditions for 35 days. This study aimed to evaluate the antibacterial capacity of the superhydrophobic coating and its weather resistance. The results demonstrate that a superhydrophobic coating with a contact angle ≥150° and a sliding angle ≤10° was successfully synthesized using SiO2 NPs smaller than 10 nm modified with PFDTES. The coating exhibited the ability to inhibit bacterial growth by preventing the adhesion of bacteria such as Escherichia coli and Staphylococcus aureus; moreover, the number of layers correlated with enhanced antibacterial properties. The coating also showed good durability under outdoor conditions. These results support the potential application of superhydrophobic coatings to prevent these bacteria from adhering and growing in areas where they can be harmful.

The Colorado and Mississippi River Basins are crucial for water supply, agriculture, and ecological stability in the U.S., yet climate change, water management practices, and energy sector demands pose significant challenges to their sustainability. This paper highlights the potential of leveraging the Voluntary Carbon Market (VCM) to address these challenges by creating new revenue streams and incentivizing sustainable water management practices. The paper provides high-level estimates by extrapolating from existing literature. The results suggests that water projects in these basins could generate over 45 million carbon credits annually, potentially attracting around $4.5 billion in investments over the next decade. However, challenges such as high costs, complex regulations, and stakeholder coordination must be addressed. The paper also identifies opportunities for advancing water resiliency projects, including increasing public awareness, engaging corporations, and utilizing innovative financing mechanisms. Recommendations include promoting the VCM-water relationship, encouraging methodology innovation, developing pilot programs, investing in digital monitoring technologies, and conducting localized analysis to optimize carbon credit potential in water management. By integrating carbon markets with water management strategies, the paper suggests significant contributions to global climate goals and enhanced water resilience in these critical regions.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

The study surveyed the use of academic libraries and information seeking behaviour of students at Lusaka Apex Medical University. The objectives of the study were to determine how often LAMU students used the libraries, to ascertain the purpose for which students used the library and to determine the challenges faced in accessing library services. Using a survey research design, 230 students selected using simple random sampling participated. Findings revealed that there were more male (51.1%) students who participated. The study also found that the majority of students (54.7%) were occasionally using the library. Results on the purpose for using the library showed that the majority (39.6%) were using it to read in order to improve personal competence. In relation to the challenges, majority students (42.6%) stressed the inadequacy of relevant materials. The need for librarians to make themselves available to aid students that seek information for different purposes was recommended. This was seen as a way through which many would have access to the available information in their field. There is a need for proper orientation and sensitization to students on how to access both physical and online materials. This would increase the library use as well as improve the performance of students. Lastly, it was recommended that a study on the digital literacy of students be done in order to ascertain their competence and search skills in sourcing for information.

S6K1 (ribosomal protein S6 kinase beta-1) is a critical serine/threonine kinase involved in the regulation of various cellular processes, including protein synthesis, gene expression, and metabolic homeostasis. The structural complexity of S6K1, with its multiple isoforms and unique kinase domain, allows for diverse functionality across different cellular contexts. In this review, we report the intricate structure of S6K1, highlighting the significance of its kinase domain. Additionally, we explored the tissue-specific expression and subcellular localization of S6K1 isoforms, emphasizing their distinct roles in cellular processes. The regulation of S6K1 extends beyond transcriptional control, with post-translational modifications such as phosphorylation and acetylation playing crucial roles in its activity and stability. The physiological implications of S6K1 are vast, influencing processes from cell growth and protein synthesis to immune responses and muscle hypertrophy. However, dysregulation of S6K1 is implicated in numerous pathological conditions, including cancer Studies reveal that altered S6K1 activity, particularly in its phosphorylation state, can lead to reduced neuronal viability, contributing to the progression of diseases such as Parkinson's. This manuscript synthesizes current knowledge on S6K1, offering insights into its multifaceted roles and highlighting its potential as a therapeutic target in various disease contexts.

Objective: In this study, we investigated vitamin D, inflammatory hematologic ratios such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), MHR and plasma atherogenic index (PAI) and possible relationships with insulin resistance in children. Methods: A total of 210 individuals, including 96 children with insulin resistance and 114 children without insulin resistance, aged 6-18 years, who were admitted to the Pediatric Endocrinology Outpatient Clinic at Medicine Hospital, Istanbul Atlas University were included in our study. Result: NLR, PLR, SII and MHR were significantly higher in patients with insulin resistance compared to those without. Fasting insulin, PAI, HOMA-IR, HOMA- were significantly higher and QUICKI was significantly lower in patients with insulin resistance compared to those without insulin resistance. NLR, SII and MHR were lower in normal vitamin D groups than the others were (p

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, with 25% of patients presenting with metastases; of these, 8% have synchronous liver and peritoneal metastases. Although the concurrent presence of liver and peritoneal metastases was previously considered an absolute contraindication, the feasibility of combined surgery is now being re-evaluated. This study assesses 41 patients who underwent liver surgery for CRC metastases at our center between October 2021 and February 2024. Among these patients, 7 underwent concomitant cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) due to the presence of synchronous liver and peritoneal metastases. We employed simple linear regression to identify parameters that influenced the development of postoperative complications, classified by the Clavien-Dindo (CD) system. The statistical analysis showed only the operative time, the CRS+HIPEC procedure and the length of hospital stay as significative variables on CD outcome, while the different types of liver surgery were not significant. This study suggests that combining liver surgery with CRS+HIPEC may be beneficial for selected patients, potentially improving overall survival without a significant increase in postoperative complications. A multidisciplinary approach is essential to achieve a survival advantage without elevating morbidity rates.

The Gulf of Mannar, a UNESCO World Biosphere Reserve, faces severe overfishing and habitat degradation threats. In this study, we investigate the pivotal role of ecosystem services in sustaining local livelihoods and overall well-being. By conducting a comprehensive survey of 480 respondents across two districts, we gathered extensive data on demographics, livelihoods, fishing practices, reliance on ecosystem services, and community management participation. The analysis reveals a critical dependence on the Gulf's resources (income, food security, traditions) with gender disparities (men fish, women in pre/post-harvest), but fishing is only allowed in the 10km buffer zone (not the core zone). The findings emphasize the promise of community-based strategies, such as Marine Protected Areas and reviving co-management committees, for achieving sustainable fisheries management. However, we also identify gaps, including the need for more nuanced well-being indicators and improved models for community management participation. To address these challenges, we advocate for sustainable fishing practices, tackling social inequities, especially gender disparities in resource access and decision-making, and investing in healthcare, education, and social safety nets for fishing communities. Promoting alternative livelihoods can alleviate pressure on fish stocks, and empowering local communities through capacity building and community-based management initiatives is crucial for ensuring the long-term sustainability of both the Gulf of Mannar ecosystem and the well-being of its dependent communities. This multifaceted approach holds significant promise for balancing ecological health with human prosperity.

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the 10 ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that the cultural scales were correlated with ageism. This is the first study to show that diverse cultural scales are related to multiple dimensions of ageism.

This work focused on the solubility of ethane in three promising ionic liquids {1-Hexyl-3-methylimidazolium bis(trifluormethylsulfonyl) imide [HMIM][Tf2N], 1-Butyl-3-methyl-imidazolium dimethyl-phosphate [BMIM][DMP] and 1-Propyl-3- methylimidazolium bis(trifluoromethyl-sulfonyl)-imide [PMIM][Tf2N]}. The solubilities were measured at 303.15 K to 343.15 K and pressures up to 1.4 MPa using a gravimetric microbalance. The overall ranking of ethane solubility in the ionic liquids from highest to lowest is the following: [HMIM][Tf2N] > [PMIM][Tf2N] > [BMIM][DMP]. The Peng- Robinson equation of state was used to model the experimental data using three different mixing rules: van der Waals one, van der Waals two and Wong-Sandler mixing rules combined with the Non-Random Two-Liquid model. The average absolute deviations for the three mixing rules for the ionic liquids at the three temperatures were (4.39, 2.45 and 2.45) %, respectively. Henry’s Law constants for ethane in [BMIM] [DMP] were the highest (lowest solubility) amongst other ionic liquids studied in this work. The selectivity of CO2 over C2H6 was estimated at the three temperatures and the overall ranking of the selectivity was in the following order: [PMIM][Tf2N] > [BMIM][DMP] > [HMIM][Tf2N]> Selexol. Selexol, a widely used physical solvent in gas sweetening has better selectivity than the three ionic liquids studied. [PMIM][Tf2N], a promising solvent, has the highest selectivity among the three ILs studied, and would therefore be the best choice if in addition to carbon dioxide capture, ethane co-absorption was to be avoided. The enthalpy and entropy of solvation at infinite dilution were also estimated.

In response to the increasing importance of knowledge as a key competitive advantage, the role of knowledge management in value creation cannot be overstated. The International Standards Organization (ISO) has recognized this and announced a Management Standard for Knowledge Management Systems (KMS). This initiative is significant because, by viewing knowledge strategically, organizations are seeking ways to enhance their processes and align them to address their challenges. A synergistic effect can be achieved when another management system highly relevant to KMS is joined and later integrated. This new system is Artificial Intelligence Management (AIMS). The paper is structured as follows: Firstly, we explore knowledge and knowledge management (KM), along with the challenges companies face in implementing and operating KM. Next, we examine the ISO 30401:2018 standard as a guide for KM implementation. Finally, we discuss how ISO 30401:2018 and ISO/IEC 42001:2023 can help solve key organizational problems and support machine learning and knowledge extraction through AI. In conclusion, we summarize the key outcomes of the paper. The main purpose of the paper is to determine how these standards contribute to solving practical problems in the creation and development of a knowledge management system supported by artificial intelligence and to demonstrate their synergistic effect when used together.

Three neutral Pt(II) complexes with diphenylamino-modified 2-phenylpyridine derivatives as cy- clometalating ligands and acetylacetone as the ancillary ligand exhibit aggregation-induced phosphorescent emission (AIPE) properties in THF/H2O. The crystal structures of the complexes highlight the contributions of non-covalent Pt···Pt interactions and hydrogen bonds to the AIPE properties. These AIPE-active Pt(II) complexes 1-3 have been successfully applied to detect picric acid (PA) in aqueous media, affording the lowest limit of detection at 70 nM. Furthermore, three Pt(II) complexes are able to detect PA in common water samples. The quenching of luminescence in the detection can be attributed to photo-induced electron transfer.

Metal additive manufacturing (AM), commonly referred to as 3D printing with metals, is an innovative technology with significant potential to transform industries such as aerospace, automotive, and healthcare. Despite its promise, the field faces several challenges that impact both its technical feasibility and economic viability. This paper explores the primary technical challenges, including material properties and processing complexities, such as the need for precise control of thermal gradients and the mitigation of defects like porosity and residual stresses. Additionally, it addresses the economic barriers, including high initial equipment costs, the need for specialized knowledge, and the relatively slow build speeds compared to traditional manufacturing methods. By examining these challenges, this paper aims to provide a comprehensive overview of the current state of metal additive manufacturing and suggest potential pathways for overcoming these obstacles to facilitate wider adoption and technological advancement in the field.

This study investigates the use of geopolymer technology as an alternative for the management of mine tailings, which is a serious environmental problem in mining environments including that of Arequipa region of Peru. In this study, the mixture of stabilized mine tailings with different percentages of binders (metakaolin and pumice) and their impact on the mechanical, microstructural, and toxicological properties of the synthesized geopolymers were analyzed. The ratios of mine tailings to binder material varied between 100/0 and 0/100. The activation was carried out with an alkaline solution of sodium hydroxide (10M) and sodium silicate (modulus 2.5). 50 mm cubic specimens were fabricated, and 7 mixtures with 3 replicates each were evaluated. The evaluations included compressive strength at 7, 14, 28, and 56 days of curing, chemical analysis by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR), microstructural characterization by Scanning Electron Microscopy (SEM/EDS), thermal behavior by thermogravimetry and differential thermal analysis (TGA/DTA) between 40°C and 1000°C, and toxicological tests by the Toxicity Characteristic Leaching Procedure (TCLP, EPA 1311) to determine the efficiency of immobilization of toxic metals. The results showed good mechanical strength, reaching 25 MPa at 7 days of curing, high microstructural stability with an average pore size of 7.21 μm, and good efficiency in the immobilization of heavy metals in geopolymers composed of 60% - 40% and 70% - 30% of the mine tailings - binders ratio, as the concentrations of As, Cd, Pb, Hg were below the established thresholds, acquiring the classification of non-hazardous materials. Geopolymers with 30 to 50% binder showed good mechanical behavior, microstructural stability, and high efficiency in the immobilization of heavy metals, complying with current regulations. Therefore, these geopolymers are suitable for various applications and in different environmental conditions.

Metal corrosion poses a significant challenge for industries by decreasing the lifespan of materials and escalat-ing maintenance and replacement costs. This study is critically important as it assesses the corrosion resistance properties of annealed steel wire electrodes coated with manganese, employing chronoamperometry and linear voltammetry techniques. The electrodes were immersed in an electrolyte solution and subjected to chronoam-perometry at various voltages (-0.55 V, -0.60 V, and -0.70 V) and durations (60 seconds and 1800 seconds). Sub-sequently, linear voltammetry was performed over a potential range from -0.8 V to 0.8 V to generate Tafel plots. The Butler-Volmer equation was applied to the data obtained to determine the corrosion current density. The re-sults indicate that the optimal conditions for forming a highly effective protective manganese layer occur at a potential of -0.70 V for 1800 seconds. Under these conditions, the electrodes exhibited superior corrosion re-sistance. The study also revealed that shorter durations and less negative potentials led to less effective manga-nese coatings, with higher corrosion rates and reduced stability. These findings are significant for developing ef-ficient corrosion protection methods in industrial and research applications, providing clear parameters for op-timizing the manganese electrodeposition process on annealed steel.

Achieving the best aesthetic result is a key objective of implant-prosthetic therapy. To maximize the aesthetic outcome, ensuring that implant-supported restorations are in harmony with the peri-implant soft tissues and bone is essential. A comparative analysis of zirconia and titanium dental implants revealed that both materials offer high success rates; however, they present distinct advantages and limitations in clinical practice. Titanium implants, with surface modifications but without chemical composition changes, boast remarkable long-term survival. In contrast, zirconia implants, while presenting high aesthetic and biocompatibility qualities, have a relatively high incidence of material-specific failure, ranging from 4% to 2% after 5-10 years. While titanium implants generally show superior long-term performance, zirconia implants benefit from ongoing advancements aimed at improving their osseointegration and longevity. This study emphasizes the need for short-term and long-term studies, complemented by randomized controlled trials (RCTs), which are essential for optimizing implant materials and ensuring patient satisfaction. Continued innovation and research are crucial for advancing dental implant technology and enhancing the quality of life for patients requiring dental restorations. Finally, it is important to understand that all materials have both advantages and disadvantages, so the choice of the optimal material should be based on the specific purpose.

Several technologies have been introduced into neurorehabilitation programs to en-hance traditional treatment of individuals with Spinal Cord Injury (SCI). Their effec-tiveness has been widely investigated but their adoption has not been properly quanti-fied. The aim of this study is to assess the distribution of conventional (Treatment As Usual – TAU) and technology-aided (Treatment With Technologies – TWT) treatments, conveniently grouped based on different therapeutic goals, in a selected SCI unit. Data from 104 individuals collected in 29 months were collected in a custom database and categorized according to both the conventional American Impairment Scale classifica-tion and a newly developed multifactor (MF) clustering approach, that considers addi-tional sources of information (the lesion level, the level of independence in the activi-ties of daily living and the hospitalization duration). Results indicated an average technology adoption of about 30%. Moreover, the MF clusters were less overlapped and the differences in TWT adoption were more pronounced than in AIS-based clus-tering. MF clustering was capable of grouping individuals based both on neurological features and functional abilities. In particular, individuals with motor complete inju-ries were grouped together, whereas individuals with sensorimotor incomplete SCI were collected separately based on the lesion level. Analyzing TWT adoption, we found that in case of motor complete SCI, TWT for muscle tone control and modulation were mainly selected while the other types of TWT were seldom adopted. Even for in-dividuals with incomplete SCI the most frequent rehabilitation goal was muscle tone modulation, regardless of the AIS level, and technologies to improve walking ability and balance control were mainly used for individuals with thoracic or lumbar lesions. Analyzing TAU distribution, we found that the highest adoption of muscle tone mod-ulation strategies was reported in case of individuals with motor complete SCI, i.e. in cases when almost no gait training was pursued. In case of cervical motor incomplete SCI, compared to thoracic and lumbar incomplete SCI, there was a greater focus on muscle tone control and force recruitment in addition to walking, than on balance training.

Understanding the interaction between pharmaceuticals and serum proteins is crucial for optimizing therapeutic strategies, especially in patients with coexisting chronic diseases. The primary goal of this study was to assess the potential changes in binding affinity and competition between glipizide (GLP, a second-generation sulfonylurea hypoglycemic drug) and losartan (LOS, a medication commonly prescribed for hypertension, particularly for patients with concurrent diabetes) with non-glycated (HSA) and glycated (gHSAGLC, gHSAFRC) human serum albumin using multiple spectroscopic techniques (fluorescence, UV-visible absorption, and circular dichroism spectroscopy). The results indicate that FRC is a more effective glycation agent for HSA than GLC, significantly altering the albumin structure and affecting the microenvironment around critical amino acid residues, Trp-214 and Tyr. These modifications reduce the binding affinity of LOS and GLP to gHSAGLC and gHSAFRC, compared to HSA, resulting in less stable drug-protein complexes. The study reveals that LOS and GLP interact nonspecifically with the hydrophobic regions of the albumin surface in both binary (ligand-albumin) and ternary systems (ligand-albumin-ligandconst) and specifically saturate the binding sites within the protein molecule. Furthermore, the presence of an additional drug (GLP in the LOS-albumin complex or LOS in the GLP-albumin complex) complicates the interactions, likely leading to competitive binding or displacement of the initially bound drug in both non-glycated and glycated albumins. Analysis of the CD spectra suggests mutual interactions between GLP and LOS, underscoring the importance of closely monitoring patients co-administered these drugs to ensure optimal therapeutic efficacy and safety. Początek formularzaDół formularza

Arthrospira platensis (Ap) and Bacillus coagulans (Bc) have been successfully used to develop functional foods, but not a combination of both regarding functional implications in nutritional value and antioxidant capacity. This work aimed to develop an artisanal wheat flour pasta with egg using 5% A. platensis and 1% B. coagulans GBI 6068 (Bc+Ap). Uncooked pasta was characterized regarding nutritional value; furthermore, total phenolic content, antioxidant capacity (by ABTS and FRAP), pigment content (chlorophyll a + b, and total carotenoids), colorimetry assay, textural profile analysis, buffering capacity and probiotic viability were carried out on uncooked and cooked pasta to assess the changes induced by cooking. The Bc+Ap pasta showed enhanced nutritional value with a significant increase in protein content (30.61%). After cooking, the pasta increased phenolic content (14.22% mg GAE/g), antioxidant capacity (55.59% µmol Trolox Equivalents/g and 10.88% µmol Fe+2/g) for ABTS and FRAP respectively, pigment content (6.72 and 1.17 mg/100g), for chlorophyll a+b and total carotenoids respectively, but relative positive impacts on colorimetric parameters in contrast to control (wheat flour pasta). Furthermore, Bc+Ap showed improved firmness (59%, measured in g), buffer capacity (87.80% μmol H+(g × ΔpH)−1), and good probiotic viability (7.2 ± 0.17 log CFU/g) after the cooking process.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

Exosomes, nanoscale extracellular vesicles, are a hot area of investigation in the biomedical field, as they have been shown to play a crucial role in the physiology of numerous tissues, including bone. This study explores the landscape of exosome-based bone regeneration research using infometric techniques. By relying on BERTopic, an advanced topic modeling algorithm, we analyzed a comprehensive corpus of scientific literature to identify key themes and trends in exosome research in the bone regeneration field. We then extracted significant concepts from the abstracts of the corpus and we used them to create knowledge graphs using GPT 3.5 turbo Large Language Model, to map the distribution of information within this domain. The resulting ide-oscape highlights the key ideas that aggregate most of the recent research in the area, from mesenchymal stem cell-derived exosomes to engineered exosome-integrated biomaterials. This exploration provides a holistic view of the field and uncovers its emerging trends, providing useful insight to guide future research directions.

The article considers the issues of ensuring operational performance and environmental sustainability of marine diesel engines by using biodiesel fuel. The research was conducted on 5S60ME-C8 MAN-B&W Diesel Group and 6DL-16 Daihatsu Diesel marine diesel engines, which were operated using RMG380 petroleum fuel and B10 and B30 biodiesel fuels. The efficiency of biofuel usage was assessed based on environmental (reduced nitrogen oxide concentration in exhaust gases) and economic (increased specific effective fuel consumption) criteria. It was found out that the use of B10 and B30 biofuels provides reduction of nitrogen oxides concentration in exhaust gases by 14.71–25.13 %, but at the same time increases specific effective fuel consumption by 1.55–6.01 %. Optimum fuel injection advance angles were determined that ensure the best thermal energy, economic and environmental performance of diesel engines. The optimum angle of biofuel supply advance is determined experimentally and should correspond to the limits recommended by the diesel engine operating instructions. It has been proven experimentally that the use of biofuel increases the environmental sustainability of marine diesel engines by 13.75–29.42 %. It increases the diesel engines environmental safety in case of emergency situations, as well as accidental and short-term emissions of exhaust gases with an increased content of nitrogen oxides into the atmosphere - phenomena that are possible in starting modes of diesel engine operation, as well as in modes of sudden load changes. It is the increase in the environmental friendliness of marine diesel engines in the case of using biofuel that is the most positive criterion and contributes to the intensity of biofuel use in power plants of sea vessels.

Brazil is the world leader in pesticide consumption, and its indiscriminate use puts farmers’ health at risk. The CYP2C9 gene stands out for encoding the CYP2C9 enzyme, which metabolizes several endogenous substrates and specific xenobiotics, especially pesticides. Our goal is to study the risk of pesticide use, espe-cially the herbicide glyphosate, in the development of diseases and the association with two CYP2C9 poly-morphisms, in farmers living in the southern region of Espírito Santo state, Brazil. The allelic frequency of CYP2C9*1, CYP2C9*2 and CYP2C9*3 was determined in blood samples from individuals exposed or not to pesticides using real-time PCR. 304 blood samples were analyzed, dividing CYP2C9 genotypes into three metabolization classes: normal, intermediate, and slow. Our results show that normal metabolizers are more vulnerable to diseases such as blood pressure changes and cardiovascular and kidney problems, while in-termediate metabolizers show an association with attention deficit disorder and miscarriages, suggesting that farmers in the studied region developed symptoms correlated to the CYP2C9 genotype they have. This work is pioneering in associating specific genetic variations and health risks with pesticide exposure, em-phasizing the importance of personalized medicine and stricter regulation of pesticide use for public health and occupational safety.

Cardiac arrest may cause significant hypoxic-ischemic injury leading to coma, seizures, myoclonic jerks, or status epilepticus. Mortality is high but accurate prognostication is challenging. A multimodal approach is employed, in which electroencephalograph (EEG) forms a key part with several recognised patterns of prognostic significance. In this retrospective study, clinical and qualitative features of the EEG of patients admitted to the Intensive Care Unit (ICU) at Kingston General Hospital following cardiac arrest from 2017-2020 were reviewed. The study included 81 adult patients (>18 years). Outcome was assessed using the Cerebral Performance Category as 1-2 (favourable) or 3-5 (unfavourable). EEG patterns were divided into groups within the highly malignant, malignant, and benign patterns described in the literature. There were a wide range of causes and 22% had a favourable outcome. Highly malignant, malignant, and benign patterns were associated with survival in 0%, 78% and 100% respectively and favourable outcomes in 0%, 44% and 100%. All patients with seizures died and 94% with myoclonus had unfavourable outcomes. In contrast, EEG reactivity and improvement on follow-up EEG was associated with a favourable outcome. In conclusion, highly malignant EEG, seizures and myoclonus were associated with unfavourable outcome, while patient with malignant EEG had better outcome.

General derivation of the well-known Ren-Otsuka relation, 1/α (dTo)/dx=-α/β (where To, x, α and β(>0) are the transformation temperature, the composition, as well as the composition and temperature coefficient of the critical shear constant, c’, respectively) for shape memory alloys, SMAs, is provided based on the similarity of interatomic potentials in the framework of dimensional analysis. A new dimensionless variable, to(x)=(To (x))/(Tm (x) ), describing the phonon softening (where Tm is the melting point) is introduced. The dimensionless values of the heat of transformation, H, and entropy, S as well as the elastic constants c’, c44, A=c44/c' are universal functions of to(x) and have the same constant values at to(0) within sub-classes of host SMAs having the same type of crystal symmetry change during martensitic transformation. The ratio of (dto)/dx and α has the same constant value for all members of a given sub-class and relative increase of c’ with increasing composition should be compensated by the same decrease of to. In the generalized Ren-Otsuka relation the anisotropy factor, A appears instead of c’ and α as well as β are the differences of the corresponding coefficients for the c44 and c’ elastic constants. The obtained linear relation between h and to rationalizes the observed empirical linear relations between the heat of transformation measured by DSC (QAM) and the martensite start temperature, Ms.

Understanding and addressing dehumanization in healthcare is crucial due to its pro-found impact on patient care, ethical implications on patient dignity and autonomy, and its potential to affect the psychological well-being of healthcare professionals. The primary aim of this study was to establish reliable and valid instruments measuring two different types of dehumanization, namely animalistic dehumanization (i.e., stripping one of their uniquely human characteristics) and mechanistic dehumanization (i.e., stripping one of their human nature characteristics) among healthcare professionals. In a cross-sectional validation study among healthcare professionals, we tested measures of both animalistic and mechanistic dehumanization, focusing on dehumanization of patients (hetero-dehumanization) and oneself (self-dehumanization), respectively. All measures were developed and validated based on a concept analysis, a literature review, and an appraisal of pre-existing scales. The research was conducted among 400 nurses and medical doctors employed in Greek public hospitals. Coefficient Validity Ratio re-sults showed that 100% of items were acceptable for both measures. The newly estab-lished and validated hetero-dehumanization scale encompassed two-factors (factor 1: animalistic dehumanization, factor 2: mechanistic dehumanization, Cronbach’s alpha was equal to 0.86 for each measure). The self-dehumanization scale was a mono-factorial measure mechanistic dehumanization (Cronbach’s alpha = 0.97). Two validated measures of (self and hetero-) animalistic and mechanistic dehumanization measures were developed for the assessment of dehumanization among health profes-sionals, which will form the basis for future research in this important scientific field.

Pharmacist-prescribed hormonal contraception (HC) is supported by a majority of pharmacists and pharmacy students; however, few studies have evaluated perceptions of non-community pharmacists, or differences in geographic areas. The primary objective of this study is assess differences between community and non-community pharmacists in perceptions of pharmacist HC prescribing. Secondary objectives include assessment of community pharmacist interest in prescribing HC, and differences in perceptions between pharmacists in metropolitan and nonmetropolitan areas. A survey was emailed in early 2022 to 2592 Georgia pharmacists, with Likert questions assessing interest, perceptions, comfort, and perceived barriers regarding pharmacist prescribed HC. Completed survey response rate was 11.8%. Regardless of practice site, a majority agreed pharmacists are well-trained to prescribe HC (Community 61.8% vs. Non-community 68.1%, p=0.25) and provision of HC services is within the pharmacist’s scope (Community 73.6% vs. Non-community 74.2%, p=0.90). Overall metropolitan and non-metropolitan community pharmacists' perceptions were similar, however more metropolitan pharmacists believed pharmacists are well trained to prescribe HC (66.7% vs 48.7%, p=0.049) and that it is within their scope of practice (78.1% vs. 61.5%, p=0.045). In summary, the majority of pharmacists, regardless of practice type, believe that pharmacists are prepared to prescribe HC and it is a part of pharmacist’s professional scope of practice.

Photodynamic therapy has emerged as a non-invasive treatment modality for various diseases, leveraging photosensitizing compounds to induce localized cytotoxicity upon light activation. This review explores the isolation and characterization of photosensitizing compounds sourced from microalgae, focusing on their potential applications in photodynamic therapy. Microalgae represent a rich source of bioactive molecules, including chlorophylls, phycobiliproteins, and carotenoids, which exhibit inherent photosensitizing properties. Methodologies for the extraction and purification of these compounds from different microalgal species are discussed, emphasizing the importance of optimizing extraction techniques to enhance yield and purity. Characterization techniques such as UV-Vis absorption spectroscopy, fluorescence spectroscopy, and mass spectrometry are highlighted for elucidating the chemical structures and photophysical properties of isolated compounds. Furthermore, the review examines the photodynamic efficacy of microalgae-derived photosensitizers through in vitro and in vivo studies, assessing their cytotoxic effects on cancer cells and antimicrobial activity against pathogens. The integration of microalgae-derived photosensitizers into PDT protocols represents a promising avenue for developing sustainable and effective therapeutic strategies, underscoring the potential of these natural compounds in advancing biomedical applications.

The Fading Affect Bias (FAB) occurs in autobiographical memory when unpleasant emotions fade faster than pleasant emotions and the phenomenon appears to be a form of emotion regulation. As emotion regulation is positively related to problem-solving, the current study examined FAB in the context of problem-solving. In-person and online studies asked participants to provide basic demographics, describe their problem-solving abilities, and rate various healthy and unhealthy variables including emotional intelligence and positive problem-solving attitudes. Participants also completed an autobiographical event memory form for which they recalled and described 2 pleasant and 2 unpleasant problem-solving and non-problem-solving events and rated the initial and current affect and rehearsals for those events. We found a robust FAB effect that was larger for problem-solving events than for non-problem-solving events in Study 1 but not in Study 2. We also found that FAB was positively related to healthy variables, such as grit, and negatively related to unhealthy variables, such as depression. Moreover, many of these negative relations were inverted at high levels of positive problem-solving attitudes, and these complex interactions were partially mediated by talking rehearsals and thinking rehearsals.

The whimsical Las Vegas/Monte Carlo cubic dice are generalized to construct the combinatorial problem of enumerating all n-dimensional hypercube dice, and dice of other shapes that exhibit cubic, icosahedral and higher symmetries. By utilizing powerful generating function techniques for various irreducible representations, we derive the combinatorial enumerations of all possible dice in n-dimensional space with hyperoctahedral symmetries. Likewise a number of shapes that exhibit icosahedral symmetries such as a truncated dodecahedron and a truncated icosahedron are considered for the combinatorial problem of dice enumerations with the corresponding shapes. We consider several dice with cubic symmetries such as truncated octahedron, dodecahedron and Rubik’s cube shapes. It is shown that all enumerated dice are chiral and we provide the counts of chiral pairs of dice in the n-dimension space. During the combinatorial enumeration, it was discovered that two different shapes of dice exist with the same chiral pair count culminating into the novel concept of isochiral polyhedra. The combinatorial problem of dice enumeration is generalized to multi-coloring partitions. Applications to chirality in n-dimension, molecular clusters, zeolites, mesoporous materials, cryptography and biology are also pointed out. Applications to nonlinear n-dimensional hypercube and other dicey encryptions are exemplified with romantic, clandestine messages; “I love U” and “V Elope at 2”.

Background: Diagnosis of acute kidney injury (AKI) relies on serum creatinine (SCr) changes. This study investigated if urinary aminopeptidases are early and predictive biomarkers of cardiac surgery associated-AKI (CSA-AKI). Methods: Glutamyl aminopeptidase (GluAp), alanyl aminopeptidase (AlaAp), dipeptidyl peptidase-4 (DPP4), proteinuria, albuminuria, N-acetyl-β-D-glucosaminidase (NAG) and neutrophile gelatinase-associated lipocalin (NGAL) were measured in urine samples from 44 patients at arrival in Intensity Care Unit (ICU) after cardiac surgery. Sensitivity, specificity, positive and negative predictive value for diagnosis of stages 1, 2 and 3 of AKI were analyzed for the highest quartile of each marker. We also studied the relationship with SCr after surgery, 6- and 12-months glomerular filtration rate (GFR) and other long-term events over the next 5 years. Results: GluAp diagnosed the maximal number of patients that developed stage 2 or 3 of AKI, increasing diagnostic sensitivity from 0 to 75 %. Besides, GluAp and DPP4 was related to the decrease in GFR at 6- or 12-months after surgery. Conclusions: Urinary aminopeptidases are a potential tool for the early diagnosis of CSA-AKI, being GluAp the most effective marker for diagnosing stages 2 or 3 of AKI at ICU admission. GluAp and DPP4 serve as predictive biomarkers for the decrease in GFR.