Fintech's emergence is one of the most significant developments in finance, and its application has been of much interest and popularity in recent decades. This study aims to explore the adoption of fintech in emerging economies by employing a structural equation model. The study's sample population consists of bank clients of Ethiopian commercial banks who have used financial technology platforms for at least one year. The total number of sample sizes is 440. The data collection instrument used for this study is a questionnaire (seven-point likert scales ranging from strongly disagree to strongly agree). Structural equation model (SEM) analysis was implemented using Amos software to examine the relationship between variables. The findings of the study support the hypotheses that various factors, including performance expectancy, effort expectancy, social influence, facilitating condition, traliaility, and user innovativeness, significantly influence the adoption and usage of fintech services. The study recommends that FinTech companies implement pilot programs to allow potential users to trial FinTech services on a limited basis before full commitment. Fintech industries should engage with local communities through events, seminars, and workshops to introduce fintech services. Having community leaders and respected individuals advocate for the technology can enhance acceptance.

Matters relating to preservation of environmental resources and climate change, social inclusion and diversity, and open and sound governance have rapidly gained global attention. However, little is known about the construction industry in meeting the environmental, social and governance (ESG) criteria towards sustainable development. In this study, the purpose is to identify the key ESG indicators for construction development. A systematic literature review was undertaken using data from Scopus, PubMed, Google Scholar, JSTOR, ProQuest, and Web of Science. The results show some of the key ESG indicators as climate resilience and green construction activities (at the project level), and active stakeholder engagement and effective project governance (at the firm level) and meeting environmental and social regulation requirements (industry/national level). The limitation of the article is in the sample size of twenty-six journal articles with future expectation of increment as ESG gain more acceptance in the construction industry. This study will be significant for the design of practice framework and policies on ESG in the construction industry. Comprehensively, this study presents relevant ESG indicators for construction management and presents essential information for future research.

Keywords: municipal solid waste; landfill; greenhouse gas emissions; biodegradable waste; aeration; probiotics; leachate recirculation

The mechanisms of the innate immunity control on equine infectious anaemia virus in asymptomatic horses are not yet widely described. Horse monocytes from peripheral blood can be differentiated in vitro into macrophages, that generally gives rise to mixed populations, morphologically referable to M1 and M2. The addition of specific cytokines or of virus, results in a more specific differentiation. As stated for other species (Crespo et al, 2013), stimulation with equine recombinant cytokine IFNγ polarized horse macrophages towards the M1 phenotype while equine recombinant cytokine IL4 polarized towards the M2 phenotype. EIAV Wyoming and Miami strains infection resulted in morphological transformation of macrophages compatible with the M1 pattern of differentiation. In this study MMP13 represented a reliable target gene to evaluate proinflammatory status of macrophages in horses since IFNγ and EIAV infection considerably increased its expression. A more in-depth study of the expression genes of both cytokine-induced and virus-induced markers of eMDM polarization may help us to understand whether these are the same in the horse as those found in other animal species with similar modes of activation of innate immunity. The identification of the markers of each population of macrophages would allow to analyze the differentiation profiles, and to check the control of virus infectivity in equid populations envisioning therapeutic strategies through the use of this information.

In this work we present a formalism based on scalar Green’s functions to deal with electromagnetic scattering problems. Although the formulations of the Mie theory and Born approximations in terms of electromagnetic scattering are well known and relevant, they have certain disadvantages; complexity, computational time, few symmetries, etc. Therefore, the study with scalar Green’s functions allows dealing with these problems with greater simplicity and efficiency. However, the information provided by the vector formulation is sacrificed. Nevertheless, different cases of electromagnetic scattering of dielectric media with different dimensions, geometries and refractive indices will be presented. Thus, we will be able to verify the capacity of this scalar method in predicting light scattering problems.

Minimally invasive surgery for adult spinal deformities (MIS deformity surgery) utilizes MIS lumbar interbody fusion and percutaneous pedicle screw fixation (PPSF) without posterior corrective osteotomy. While MIS reduces issues associated with open deformity surgery, it has limitations in correcting sagittal imbalance. This review discusses the limitations and solutions of lateral lumbar interbody fusion (LLIF) and introduces our experience in addressing marked sagittal deformities. We reviewed the literature and incorporated our clinical experience to evaluate the efficacy of recent MIS techniques, particularly focusing on oblique lumbar interbody fusion (OLIF) at L1-5 and L5-S1. The use of higher profile and greater angle cages and the application of PPSF with curved rods and percutaneous rod compression were discussed. Advances in MIS techniques, such as OLIF, have enabled significant improvements in increasing disc height and angle. Combining these new techniques and concepts, we successfully corrected marked sagittal deformities using MIS deformity surgery. Early onset of proximal junctional kyphosis was identified as a notable complication. Although recent advancements in MIS deformity surgery have shown promise in correcting sagittal deformities, further clinical experience and data are necessary to enhance outcomes and mitigate complications such as proximal junctional kyphosis.

Unhealthy concentrations of ozone in the Uinta Basin, Utah, can occur after sufficient snowfall and a strong atmospheric anticyclone creates a persistent cold pool that traps atmospheric ozone and its precursors emitted from oil and gas operations. The winter-ozone system has two clear outcomes—occurrence or not—that is well understood by domain experts and supported by archives of atmospheric observations. Rules of the system can be formulated in natural language (“sufficient snowfall and high pressure leads to high ozone"), lending itself to analysis with a fuzzy-logic inference system. This method encodes human expertise as machine intelligence in a more constrained manner than alternative, more complex inference methods such as neural networks, increasing user trustworthiness of our model prototype before further optimization. Herein, we develop an ozone-forecasting system, Clyfar, based on knowledge of system dynamics and informed by an archive of meteorological conditions and ozone concentration. The inference system demonstrates proof-of-concept despite rudimentary tuning. We describe our framework for predicting future ozone concentrations if input values are drawn from numerical weather prediction forecasts as a proxy for observations as the system’s initial conditions. Our model is computationally cheap, allowing us to sample uncertainty with substantially more ensemble members than in traditional NWP. We evaluate hindcasts for one winter, finding our prototype demonstrates promise to deliver useful guidance for users concurrent with optimization of system parameters using machine learning.

Background: Pediatric obesity treatment is based on high-intensity lifestyle counseling. However, high dropout rates and low effectiveness have been reported even in specialized centers. Mobile health technologies have been used in research settings to overcome these limits with contrasting results. This study aims to evaluate the effectiveness of a six-month intervention with a mobile app for the treatment of pediatric obesity at 6 and 12 months of follow-up. Methods: Patients were randomly assigned to standard care or standard care plus mobile app (2:1). The mobile app delivered high-intensity lifestyle counseling for diet and physical activity. Results: Seventy-five subjects were prospectively enrolled. At six months of follow-up, the m-app group showed significantly lower dropout rates compared to standard care(p=0.01). The risk of dropout was significantly higher in controls compared to the intervention group (OR 3.86,95%C.I. 1.39-10.42,p=0.01). After one year of follow-up, we observed lower albeit non statistically significant dropout rates in the m-app compared to the standard care group(p=0.24). No differences were observed in terms of z-score BMI and percentage of BMI reduction between the two groups. Conclusion: our findings suggest that mobile app might help in the clinical management of children and adolescents with obesity in terms of dropout reduction.

This paper delves into the transformative impact of artificial intelligence (AI) in the forklift industry, particularly focusing on logistics and procurement within small and medium-sized enterprises (SMEs) in the field of industrial machinery. The study highlights the growing influence of AI in automating and improving the forklift industry. Using the environmental, social, and corporate governance (ESG) balanced scorecard (BSC), benchmarking, and activity-based management (ABM) models, the paper analyses the risks and the implications of AI integration in the industry in the actual turbulent context. The research highlights the significant shifts in logistics and procurement processes due to AI, projecting a future where forklift operations are deep automatized, leading to a possible loss of forklift operator jobs. A case study of the most relevant Romanian SME in the forklift industry is also presented, examining the company's financial strategies using McKinsey’s 7S framework. The paper concludes with a perspective that, in the future, machines will predominantly operate in roles currently held by humans, significantly altering the industry landscape.

During the last few decades, the main focus of numerus studies has been on the human breast milk microbiota and its influence on the infant intestinal microbiota and overall health. The presence of lactic acid bacteria in breast milk affects both the quantitative and qualitative composition of the infant gut microbiota. The aim of this study was to assess the dominant cultivable rod-shaped lactic acid bacteria, specific for breast milk of healthy Bulgarian women and fecal samples of their infants over the first month of life, in 14 mother-infant tandem pairs. Additionally, we evaluated strain diversity among the dominant newly isolated species. 68 gram-positive and catalase negative strains were subjected to identification by using MALDI-TOF technique. Predominant culturable populations belonging to the rod-shaped lactic acid bacteria have been identified as Lacticaseibacillus rhamnosus, Limosilactobacillus fermentum, Lacticaseibacillus paracasei and Limosilactobacillus reuteri. Also, we confirmed the presence of Lactiplantibacillus plantarum and Lactobacillus gasseri. 27 isolates were selected as representatives and analyzed by 16S rDNA sequencing for strain identity confirmation and a phylogenetic tree based on 16S rDNA gene sequence was constructed. Comparative analysis by four RAPD primers revealed genetic differences between newly isolated L. rhamnosus strains. This pilot study provides data for the current first report concerning investigation on characteristic microbiota of human breast milk and infant feces in Bulgaria.

Nutritional epigenomics is exceptionally important because describes the complex interactions among food compounds and epigenome modifications. A healthy diet can improve the quality of life and, alleviate the progression and symptomatology of many complex diseases such as osteoarthritis (OA). Phytonutrients or bioactive compounds, which are secondary metabolites of plants, can protect against OA by suppressing the expression of inflammatory and catabolic mediators, and modulating epigenetic changes in DNA methylation, histone or chromatin remodelling of key inflammatory genes and noncoding RNAs. The combination of natural epigenetic modulators is crucial because their additive and synergistic effects, safety and therapeutic efficacy, and lower adverse effects than conventional pharmacology in the treatment of OA. In this review, we have summarised the chondroprotective properties of bioactive compounds and nutraceuticals for the management, treatment, or prevention of OA in both human and animal [1]studies. Some of them have been considered as natural epigenetic modulators that can modify the activity of various epigenetic factors and, alter the expression of genes related to inflammation and cartilage destruction. However, this complex pathology with inflammatory mediators has been little studied at the nutriepigenomic level. Further research is needed towards bioactive compounds as epigenetic modulators in OA, likewise, determine their potential value for future clinical applications in OA patients.

Monkeypox (mpox) caused by the monkeypox virus (MPXV) is currently the most common orthopoxvirus (OPXV) zoonotic disease. Since 2022, a multi-country outbreak of mpox has been reported with atypically rapid human-to-human transmission. The present work aimed to investigate the frequency of MPXV and OPXV DNA detection in different clinical materials taken at acute and convalescent phases of the infection in Bulgarian patients. A total of 181 clinical samples from 42 Bulgarian patients with possible mpox infections were tested. Screening for MPXV DNA (F3L gene) and OPXV DNA (rpo18 gene) were performed by real-time PCR assays. Of all tested patients six (14%) were confirmed with mpox infection. MPXV DNA was detected in 23/181 (12,71%) and OPXV DNA in 20/181 (11,05%) clinical samples. All confirmed patients were men who have sex with men, aged 23 to 44 (at an average age of 35,17±7,91 years) and two of them were HIV positive. The commonest clinical features of patients were fever (5/6), vesicular-pustular rash: perianal (6/6), penile (4/6), and limbs (4/6). MPXV DNA was found with the greatest frequency in specimens of vesicle contents and nasal/oropharyngeal swabs in 6/6 and 5/6. OPXV DNA mainly was detected in vesicle contents (6/6), nasal/oropharyngeal swabs (4/6), and urine (4/6). In the collected follow-up samples, MPXV DNA was detected in the highest percentage in the specimen's vesicle contents (6/6) and urine (6/6) and not demonstrated in samples of feces and saliva. The laboratory surveillance of MPXV is critical to contain the outbreak and to elucidate the new fast transmission of the virus.

The current surge in the deployment of web applications underscores the need to consider users' individual preferences in order to enhance their experience. In response to this, an innovative approach is emerging that focuses on the detailed analysis of interaction data captured by web browsers. This data, which includes metrics such as the number of mouse clicks, keystrokes, and navigation patterns, offers insights into user behaviour and preferences. By leveraging this information, developers can achieve a higher degree of personalization in web applications, particularly in the context of interactive elements such as online games. This paper presents the WebTraceSense project, which aims to pioneer this approach by developing a framework that encompasses a backend and frontend, advanced visualization modules, a DevOps cycle, and the integration of AI and statistical methods. The backend of this framework will be responsible for securely collecting, storing, and processing vast amounts of interaction data from various websites. The frontend will provide a user-friendly interface that allows developers to easily access and utilize the platform’s capabilities. One of the key components of this framework is the visualization modules, which will enable developers to monitor, analyse, and interpret user interactions in real-time, facilitating more informed decisions about user interface design and functionality. Furthermore, the WebTraceSense framework incorporates a DevOps cycle to ensure continuous integration and delivery, thereby promoting agile development practices and enhancing the overall efficiency of the development process. Moreover, the integration of AI methods and statistical techniques will be a cornerstone of this framework. By applying machine learning algorithms and statistical analysis, the platform will not only personalize user experiences based on historical interaction data but also infer new user behaviours and predict future preferences. In order to validate the proposed components, a case study was conducted which demonstrated the usefulness of the WebTraceSense framework in the creation of visualizations based on an existing dataset.

The present paper discusses the importance of economic externality and the economic phenomena involved. Section 1 draws on the framework of weak force theory in physics, we propose a new approach of dynamic analysis for economic externality. From a mesoscopic (intermediate scale) perspective, no distinction is made between the macro-demand and individual micro-buyers nor between the macro-supply and individual micro-sellers. Section 2 applies the isospin modeling method to construct two economic isospin models. One is between the achieving impulse and the fear-of-failure impulse, under the effect of economic externality. The other is between the market behavior and market residues, namely, market aftertaste. Section 3 discusses the microstructural properties of the market, including Dirac's equation and the market, Dirac -matrix notation, and the chirality and spin structure of market components. Section 4 discusses the helical structural characteristics of supply chains, including CPT theorems, Penrose zigzag helical processes, and several modeling directions of economic externality and buyer-seller interactions (weak interactions). Section 5 discusses the economic externality and the electroweak model, including extensive externality, externality mediations with Weinberg rotations, and economic analysis using lepton weak currents, including the analysis of lepton neutral weak currents. Finally, Section 6 provides a general discussion on the standard model of economic dynamics.

Background: The incidence of various types of cancer, for example papillary thyroid carcinoma (PTC), is on the rise. Since therapeutic success depends greatly on early diagnosis, reliable diag-nostic biomarkers must be identified and easy-to-apply tools for detecting them must urgently be standardized. Here, we contribute to solving this medical challenge by assessing miRNAs sus-pected of promoting carcinogenesis in extracellular vesicles (EVs) that can be routinely obtained via liquid biopsy. We profit from current progress in cancerology that provides innovations in liquid biopsy and EVs analysis along with identification of miRNAs and chaperone system (CS) components implicated in carcinogenesis. Methods: We measured in EVs obtained from circulat-ing blood plasma from PTC patients the levels of three miRNAs implicated in thyroid cancer, miR-1, miR-206, and miR-221, and most likely involved in the regulation of two members of the CS, Hsp60 and CCT. EVs were isolated from the plasma of patients with PTC and controls with benign goiter (BG), and from the culture medium of a PTC cell line (MDAT32) and were duly characterized. Results: The levels of miRNAs determined by RT-qPCR were consistently higher in PTC patients and decreased down to control levels after thyroidectomy. Bioinformatics showed that the miRNAs target genes were associated to the molecular pathogenesis of PTC. Conclusions: Thus, our exploratory study reaffirms the potential in clinics of the selected miRNAs in EVs as useful biomarkers of PTC easily accessible via liquid biopsy, which is minimally invasive and amenable to periodic repetition, an improvement compared to the established fine-needle aspirate biopsy.

The effective baryon-baryon potential can be derived in the framework of quark model. The configurations with different quark spatial distributions are mixed naturally when two baryons are getting close. The effect of configuration mixing in chiral quark model (ChQM) is studied by calculating the effective potential between two nonstrange baryons in the channels I J = 01, 10 and 03. For comparison the results of color screening model (CSM) are also presented. Generally the configuration mixing will lower the potential when the separation between two baryons is small, and its effect will be ignorable when the separation becomes large. Due to the screened color confinement, the configuration mixing is rather large, which leads to stronger intermediate-range attraction in CSM. while the effect of configuration mixing is small in ChQM due to the quadratic

Aortic stenosis (AS) is a prevalent valvular disorder that often requires surgical aortic valve replacement (SAVR) to alleviate symptoms and improve survival. However, the selection of an appropriate prosthetic valve size is crucial to avoid patient-prosthesis mismatch (PPM), which can lead to suboptimal hemodynamic outcomes. Von Willebrand factor (VWF), a key component of hemostasis, has been shown to be altered in AS patients and may contribute to the hemostatic imbalance observed following valve replacement. This prospective study aimed to investigate the impact of PPM on postprocedural VWF levels in patients undergoing SAVR for severe AS. The study included 31 consecutive patients diagnosed with severe AS who underwent SAVR. By focusing on the relationship between PPM and VWF dynamics, this study sought to provide valuable insights into the potential role of VWF as a marker for hemostatic changes associated with PPM, ultimately informing strategies for optimal valve selection and perioperative management to minimize complications.

Here we will explain the correlation between the Kerr-Newman diagram and the theory: RLC electrical modelling of a black hole and the early universe. We will develop a black hole model that describes and explains both theories. In the development of our analysis, we will emphasize the following conditions: M² > Q² + a², M² = Q² + a² and M² < Q² + a² and we will also analyse the condition in which the mass of a black hole reaches its critical mass M = Mc. We will demonstrate that the interpretation of the Kerr-Newman diagram is equivalent to the interpretation of the theory: RLC electrical modelling of a black hole and the early universe. Finally, we will generalize the proposed model for a black hole and propose a black hole model formed by negative particles, neutroniumd, which after reaching critical conditions of mass, pressure, volume, temperature, density, etc.; decays into a positively charged black hole, protoniu. Let us remember that both models are formed by charged particles of matter (they do not contain antimatter), but their vector configuration means that the net charges of both proposed black holes are zero.

In the contemporary era, the movement for women empowerment is not merely a social cause but a transformative force reshaping societies across the globe. The article "Breaking Barriers: Women Empowerment Transforming Societies in Modern Times Building a Better Future" delves into the multifaceted impact of empowering women, highlighting how it transcends individual upliftment and fosters widespread societal progress. It also delves into the transformative impact of women’s empowerment on societies, highlighting successful initiatives, case studies, and personal narratives that illustrate the journey towards gender parity. It examines the challenges and opportunities in this ongoing struggle, emphasizing the need for continued advocacy, education, and policy reform. By fostering an environment where women can thrive, societies can unlock unprecedented potential and build a better, more prosperous future for all. By examining key areas such as education, economic participation, political representation, and social inclusion, the article elucidates how empowering women leads to more equitable, prosperous, and resilient communities. It underscores the importance of dismantling historical and cultural barriers that have long hindered women's potential, while celebrating the strides made towards gender equality. Furthermore, the narrative showcases inspiring stories of women leaders, entrepreneurs, and change-makers who are spearheading efforts to build a better future for all. This exploration not only emphasizes the moral imperative of gender equality but also its critical role in driving sustainable development and global advancement.

For very first time, we report the synthesis of 8-(2-methoxyphenyl)-6-methyl-2-(1-methyl-1H-benzo[d]imidazol-2-yl)quinoline 1. This was achieved in several steps, including usage of Suzuki reaction for functionalization of 2-(1H-benzo[d]imidazol-2-yl)quinoline moiety. The new compound exhibits blue fluorescence. Its structure was confirmed with 1D- and 2D-NMR spectroscopy, IR-spectroscopy, high-resolution mass spectrometry and X-ray analysis.

Related studies have shown that mitophagy plays a role in the progression of Atherosclerosis (AS). Utilizing GSE43292, GSE100927, and GSE159677 datasets, WGCNA and differential expression analysis identified mitophagy-related module genes and DEGs1, while single-cell analysis screened DEGs2. MR analysis revealed causal AS-linked genes in DEGs1. LASSO and expression validation identified biomarkers, evaluated via ROC curves. Further analyses included GSEA, immune infiltration, ANN, regulatory networks, and drug prediction. Four candidate genes were identified through WGCNA, differential expression analysis and MR analysis. The LASSO analysis identified CD36, IL1RN, and MME as biomarkers, while the MR analysis showed that IL1RN and MME are protective factors and CD36 is a risk factor in AS. The ROC curves disclosed that the ANN model had greater diagnostic power for AS than any other biomarker. The GSEA revealed that the biomarkers were enriched in lysosomes and hematopoietic cell lineage and were significantly positively correlated with monocytes. The regulatory network construct showed that small nucleolar RNA host gene 16 regulates MME via the micro RNAs. This study identified CD36, IL1RN, and MME as biomarkers of mitophagy in AS and indicated that they could be applied in the diagnosis and treatment of this condition.

One of the bottlenecks to bringing new therapies to the clinic has been a lack of vectors for delivering novel therapeutics in a targeted manner. Cell penetrating peptides (CPPs) have received a lot of attention and have been the subject of numerous developments since their identification nearly 3 decades ago. Known for their transduction abilities, they have generally been considered inert vectors. In this review we present a schema for their classification, highlight what is known about their mechanism of transduction, and outline the existing literature, as well as our own experience, vis a vis the intrinsic anti-inflammatory properties that certain CPPs exhibit. Given the inflammatory responses associated with viral vectors, CPPs represent a viable alternative to these vectors; further, the anti-inflammatory properties of CPPs, mostly through inhibition of the NF-κB pathway, are encouraging. Much work in relevant animal models, toxicity studies in large animal models, and ultimately human trials are needed before their potential is fully realized.

This paper presents a co-designed solution aimed at improving community healthcare assistance management. To enhance patients’ self-awareness of their health status, encouraging active participation in care process, and to support nurses in delivering patient-centered care, we have developed an innovative platform with a highly customized app. This platform was designed using a multi-disciplinary bottom-up approach. Patient data collection and processing facilitate the automation of care timeline planning, based on real time patients’ needs and the available resources. To achieve this goal different components have been considered: real-time health data collection and processing, patient care planning, decision support for nurses, secure communication for data transmission, and user-friendly interfaces to ensure easy access to platform functionalities.

: We present first-principles DFT+U investigation of the bulk properties including structural, energetic and mechanical properties for uranium-americium mixed oxides (U, Am)O₂. The various Am aggregation contents have been investigated to better understand the impact of Am in the nuclear fuel UO₂. The supercell defect models at different scales were used to describe the solid solution (U, Am)O₂. The obtained results show that different contents of Am has a significant impact on the volume and energy of the mixed oxides systems. The results on the electronic structure calculations exhibit a narrow band gap owing to the mixing of UO₂ and AmO₂. The mixing enthalpy of the Am aggregation systems are used to describe the phase stability for the solid solution. In particular, mixing enthalpy of the (U, Am)O₂ significantly reduced as the Am content increases. The elastic properties of the (U, Am)O₂ mixed oxides have also been compared as a function of Am content. Moreover, the impacts of the whole Pu aggregation content range on the bulk properties for the (U, Pu)O₂ mixed oxides is also discussed.

In this study, we focus on the vibration-damping devices within the renowned physical experimental apparatus—STM. Utilizing GeoGebra software and Python, we meticulously elucidate the principle by which the vibrations of the damper are damped in a magnetic field, thereby achieving the vibration-damping functionality of the entire system. This approach not only fosters a clear physical conceptualization but also ensures the acquisition of accurate and comprehensive knowledge. Furthermore, the inquiry demonstrates the process of problem clarification facilitated by the use of software tools and then we compare the power of the widlely programming language--Python and the GeoGebra.

Additive manufacturing (AM), commonly known as 3D printing, has revolutionized the production of complex geometries that were once challenging or impossible to achieve through traditional manufacturing techniques. This paper investigates the capabilities of additive manufacturing in producing intricate designs, focusing on the unique advantages and potential applications across various industries. Additive manufacturing enables the creation of complex geometries by adding material layer by layer, allowing for greater design freedom and the ability to produce structures with intricate internal features, complex curves, and lightweight lattice structures. This capability is particularly advantageous in fields such as aerospace, biomedical, and automotive, where weight reduction, customization, and the integration of complex internal channels are critical. The study explores various additive manufacturing technologies, including stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), highlighting their specific strengths and limitations in producing complex geometries. Factors such as material properties, resolution, surface finish, and build size are analyzed to determine the suitability of different AM processes for specific applications. Additionally, the research delves into the design considerations and software tools that facilitate the creation of complex geometries in AM, including generative design and topology optimization. These tools leverage the design freedom offered by AM to optimize structures for weight, strength, and functionality, pushing the boundaries of what is possible in product design. The paper concludes with an examination of the challenges and future directions in the field, such as improving material properties, reducing production costs, and enhancing the accuracy and reliability of AM processes. The potential of additive manufacturing to revolutionize the production of complex geometries is underscored, emphasizing its growing importance in modern manufacturing and its role in enabling innovative solutions across various industries. This abstract provides an overview of the potential and challenges of additive manufacturing for producing complex geometries, suitable for an academic paper or report. If you need more specific information or have a different focus, feel free to ask!

Sepsis, characterized by a dysregulated systemic inflammatory response to infection, remains a significant global health burden, despite substantial advancements in its treatment. An understanding of the underlying mechanisms driving sepsis is crucial for the development of targeted therapeutic strategies. Silent information regulator 1 (SIRT1), a member of the class III histone deacetylases, plays a pivotal role in regulating gene expression by catalyzing the deacetylation of lysine residues on non-histone and histone proteins. With the advancement of sepsis research, SIRT1 has been shown to exert significant anti-inflammatory, anti-oxidative, anti-apoptotic, and metabolic regulatory effects, positioning it as a potential therapeutic target for sepsis. This article reviews the latest progress on research into the signaling pathways modulated by SIRT1 in sepsis and its associated regulatory mechanisms to further elucidate the pathogenesis of sepsis and assist in guiding clinical treatment.

We have synthesized and examined a series of calix[4]arene-based chemosensors containing thiosemicarbazone or thiourea as a binding site and a pyridine-chromophore unit in various conformations. These conformations include pinched cone (I), cone (III and IV), and 1,3-alternate (II and V). Our objective was to assess the binding abilities of these sensors towards anions and cations using different spectroscopic techniques. All receptors demonstrate the ability to recognize cations, with notable distinctions between them. Receptor I demonstrates a broad spectrum of ion recognition, encompassing Ag+, Cu2+, Co2+, Ni2+, and Zn2+. Receptors IV and V also exhibit complex formation with Co2+, Ni2+, and Cu2+ ions. Sensors II and III demonstrate exceptional selectivity for recognizing the copper (II) ion. When studying anions, only receptor I yielded satisfactory results. This is due to the thiosemicarbazone bridge and its spatial orientation in the pinched cone conformation, which allows for an interaction to occur. It is worth noting that sensors IV and V, which are fluorescent molecules due to the triazolo pyridine unit in their structure, exhibit particularly noteworthy behavior. The highest association constant is observed for cobalt (II) complexes, with values of 6.59 and 2.38 (x1012 mol/L)-2 for receptors IV and V, respectively. Our findings indicate that there are no significant differences in selectivity and sensitivity between ca-lix[4]arene receptors in 1,3-alternate and cone conformations.

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.

Several years now, the global scientific community has accepted and recognized the importance of Evidence-based practice (EBP) for Nursing science. The main factor for the implementation of EBP is the competence of undergraduate Nursing students towards EBP, so that they as active nurses be ready for its application in their clinical practice, in order to provide better care for their patients. The aim of the present study is to examine the level of evidence-based practice competency evaluated with the self-reported EBP-COQ questionnaire. A quantitative study based on cross-sectional design was conducted from February to June 2022 in a convenience sample of Greek undergraduate nursing students. The Evidence-Based Practice Competence Questionnaire (EBP-COQ) and a questionnaire on undergraduate students’ gender, age, academic year, and training in the field of research were used. The SPSS 26.0 program was used to perform descriptive, bivariate and multivariate analyses. A total of 175 undergraduate students participated at the Hellenic University Nursing (Greece), specifically from the 2nd and 3rd academic year. The mean score of EBP-COQ for nursing undergraduate students was 3.03 ± 0.26, indicating moderate EBP. Among the EBP-COQ dimensions, the mean scores were obtained 3.03 ± 0.32 for Attitude toward EBP, 3.01 ± 0.49 for Skills in EBP, and 3.03 ± 0.49 for Knowledge in EBP. They were not found significant differences among participants’ mean EBP-COQ scores regarding gender (p = 0.766), age (p = 0.400), academic year (p = 0.153), and training in the field of Research Methodology (p = 0.538). It appears that the level of readiness towards EBP is mediocre between undergraduate nursing students at a university in Greece. Therefore, it is necessary to carry out new studies in the future, so that there is a correct approach of all the elements that contribute to the readiness of Nursing undergraduate students regarding EBP.

The COVID-19 pandemic has triggered seismic shifts in how we work, and organizations behave. It has caused many organizations to transition from an office-centric culture to more flexible ways of working. This shift is necessitated by health conditions and the need for controls. It is also driven by the assumption that remote work or working from home offer a certain assurance of safety for employees against the threat of infection in highly vulnerable office conditions. The shift to remote work has so far been mainly experimental as most businesses continue to learn about what works and what doesn’t. There is also the assumption that all that matters for the efficient operability of a remote work regime is the availability and effectiveness of computing technologies and internet connectivity. Thus, once those supplies are in place remote work is expected to be fully functional and without problems. As learning continues about what works and what doesn’t, it has also become increasingly clear that beyond the threat of covid-19 and the relative safety that individual homes may offer, there are other vulnerabilities which are ignored or underestimated in the process. In most instances, the home environment of the employee, the conditions under which employees operate from home and the health and safety such environments provide (or not) are either ignored or underestimated in discussions around remote work practices. This paper highlights remote work as an emergent practice while exploring associated, but ignored, health and safety issues in employee homes.

The composition of the gut microbiota varies among end-stage renal disease (ESRD) patients on the basis of their mode of renal replacement therapy (RRT), with notably more pronounced dysbiosis in those undergoing hemodialysis (HD). Interventions such as dialysis catheters, unstable hemodynamics, strict dietary restrictions, and pharmacotherapy significantly alter the intestinal microenvironment, thus disrupting the gut microbiota composition in HD patients. The gut microbiota may influence HD-related complications, including cardiovascular disease (CVD), infections, anemia, and malnutrition, through mechanisms such as bacterial translocation, immune regulation, and the production of gut bacterial metabolites, thereby affecting both the quality of life and the prognosis of patients. This review focuses on alterations in the gut microbiota and its metabolites in HD patients. Additionally, understanding the impact of the gut microbiota on the complications of HD could provide insights into the development of novel treatment strategies to prevent or alleviate complications in HD patients.

Background: Tumor mutational burden (TMB) is increasingly recognized as a vital biomarker for predicting the efficacy of immune checkpoint inhibitors (ICIs) in cancer treatment. Despite its growing importance, the effectiveness of TMB as a predictive marker are well established in lung cancer and melanoma but remain ambiguous for breast and prostate cancers. Objective: This study aims to evaluate the role of TMB in predicting response to ICIs across four major cancer types—lung, melanoma, breast, and prostate—and to address the variability in TMB's predictive value in different cancers. Methods: A comprehensive review of the current literature was performed, analysing studies that investigated TMB and its association with ICI therapy outcomes in the specified cancer types. Results: The analysis reveals a strong consensus on the predictive value of TMB in lung cancer and melanoma, where high TMB levels are associated with improved clinical outcomes and better responses to ICIs. In contrast, the evidence for breast and prostate cancers is less conclusive, with variability in results highlighting the need for further research. Specifically, high TMB in these cancers does not consistently predict better responses to ICIs, suggesting that additional biomarkers or refined criteria might be necessary. Conclusion: TMB is a promising biomarker for predicting responses to ICI therapy, particularly in lung cancer and melanoma. However, its predictive value in breast and prostate cancers remains uncertain, underscoring the need for more extensive studies. Future research should focus on standardizing TMB evaluation methods and exploring additional biomarkers to improve treatment personalization and outcomes in these cancer types.

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.

(1) Background: Plasmodium vivax causes the largest malaria burden in Brazil, and chloroquine resistance poses a challenge to eliminating malaria by 2035. Illegal mining in the Roraima Yanomami indigenous territory can lead to the introduction of resistant parasites. This study aimed to investigate mutations in the pvcrt-o and pvmdr-1 genes to determine their potential as predictors of P. vivax chloroquine-resistant phenotypes. (2) Methods: Samples were collected in two health centers of Boa Vista. A questionnaire was completed, and blood was drawn from each patient. Then, DNA extraction, PCR, amplicon purification, and DNA sequencing were performed. After alignment with the Sal-1, the amplified fragment was analyzed. Patients infected with the mutant parasites were queried in the Surveillance Information System. (3) Results: 98% (157/164) of participants were from illegal mining areas. The pvcrt-o was sequenced in 151 samples, and the K10 insertion was identified in 13% of them. The pvmdr1 was sequenced in 80 samples: the MYF haplotype (958M) was detected in 92% of them, the TYF in 8%, while MYL was absent. No cases of recrudescence, hospitalization, or death were found. (4) Conclusions: Mutations in the pvcrt-o and pvmdr-1 genes have no potential to predict chloroquine resistance in P. vivax.

Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized various industries, including the medical field. This technology enables the creation of complex structures layer by layer, offering unprecedented customization and precision. In medical applications, AM has proven transformative in producing patient-specific implants, prosthetics, and anatomical models, facilitating better surgical planning and outcomes. Additionally, it has shown promise in bioprinting, where cells and biomaterials are used to create tissue-like structures for regenerative medicine. The ability to rapidly prototype and manufacture medical devices reduces time and costs, and enhances personalized patient care. This abstract explores the diverse applications, benefits, and challenges of AM in the medical sector, highlighting its potential to revolutionize healthcare and improve patient outcomes.

The integration of Augmented Reality (AR) in e-commerce has emerged as a transformative development, reshaping how consumers interact with online retail environments. This research explores the impact of AR on e-commerce by examining its effects on consumer behavior, purchase decisions, and overall shopping experience. Through a series of interviews with industry experts, the study uncovers key insights into how AR enhances product visualization, leading to improved consumer confidence and a reduction in return rates. The immersive and interactive nature of AR applications has been shown to significantly increase consumer engagement and conversion rates, as users are able to interact with products in a virtual setting that simulates real-world experiences. Despite these advantages, the research also highlights several challenges associated with AR implementation, including the high costs of development and maintenance, difficulties in integrating AR technology with existing e-commerce platforms, and concerns regarding privacy and data security. The study further explores the varying applications of AR across different sectors within e-commerce, such as fashion, furniture, and cosmetics, each benefiting from unique AR functionalities. Looking ahead, the potential for AR to be enhanced by emerging technologies like Artificial Intelligence and the Internet of Things is discussed, with implications for future advancements in the field. Overall, the research demonstrates that while AR offers significant benefits for enhancing online shopping experiences, addressing its associated challenges is crucial for its successful and widespread adoption.

Ferritin is an indirect marker for total body iron stores. Comparison of the ferritin concentrations in the meconium with the concentrations of proteins regulating iron metabolism could aid better understanding of principles behind the adjustment between the fetal iron pool and newborn body size. Ferritin, transferrin, haptoglobin, ceruloplasmin, lactoferrin, myeloperoxidase, neutrophil gelatinase-associated lipocalin (NGAL) and calprotectin concentrations were measured by ELISA in meconium samples from 122 neonates. The neonates were classified according to the meconium ferritin tertiles and the values were collated with the meconium concentrations of other proteins and newborn body weight and length measurements. Increasing ferritin concentrations in meconium in consecutive tertiles (p < 0.05) were parallel to increased NGAL concentrations (p < 0.05). The interrelationships between the meconium concentrations of transferrin, haptoglobin and NGAL as well as between myeloperoxidase, calprotectin and lactoferrin are maintained in all subsequent tertiles of ferritin concentrations, (p < 0.05). In contrast to ferritin, increasing meconium NGAL concentrations in consecutive tertiles were linked to increased concentrations of transferrin, haptoglobin, lactoferrin and myeloperoxidase (p < 0.05) and of calprotectin, ferritin and ceruloplasmin (p < 0.1). Meconium ceruloplasmin concentrations correlate exclusively with neutrophil granule proteins, i.e. myeloperoxidase, NGAL, lactoferrin and calprotectin (p < 0.05). Meconium ferritin concentrations negatively correlates with birth weight (r= -0.20) and length (r= -0.31) of neonates, whereas NGAL concentrations just with birth length (r= -0.26). The remaining proteins did not show such relationships with the size of the newborn. High meconium concentrations of both ferritin and NGAL may specifically characterize neonates of smaller size. High meconium concentrations of both ferritin and NGAL may specifically characterize neonates with lower body measurements. Correlations between meconium transferrin, haptoglobin and NGAL may confirm the interrelationships of these proteins for proper iron control and transport in the intrauterine environment. Meconium ceruloplasmin concentrations may reflect the control of neutrophil activity in utero.

Pagiophloeus tsushimanus, a new record of wood-boring pest first reported in China in 2014, has significantly infested Cinnamomum camphora across various administrative districts in Shanghai. And it shows a concerning trend of spread. The larval stage of the insect, being concealed within the trunks of C. camphora, exhibits characteristics such as hidden activity, strong destructiveness, and difficulty in control. This severely affects the normal growth of the host trees. While the primary host plant for P. tsushimanus is the C. camphora, preliminary observations have shown that the pest can also complete its life cycle on Cinnamomum chekiangensis and Phoebe chekiangensis. Both of them are significant species for urban greening. To explore the host selection preference of this beetle, this study investigates the olfactory selection behavior of adult P. tsushimanus towards C. camphora, C. chekiangensis, and P. chekiangensis. Results from choice tests, no-choice tests, and "Y"-shaped olfactometer experiments indicated that both male and female adults exhibited a feeding preference for C. camphora branches, with females showing a preference for laying eggs on C. camphora branches as well. Behavioral responses demonstrated a positive chemotaxis towards volatiles from C. camphora and a negative chemotaxis towards volatiles from C. chekiangensis and P. chekiangensis. Overall, the findings suggest that both male and female adults have a selective preference for volatiles emitted by C. camphora. These provides a theoretical basis for monitoring and controlling host shift occurrences in P. tsushimanus.

The vaccine industry has undoubtedly contributed massively in the medical world, with hundreds of millions of lives saved as a result of the successful development of prophylactic and therapeutic vaccines against various infectious and oncological diseases. Simultaneously, there has been an ongoing evolutionary battle between polymorphic microbes and the human immune system, and various microbes have developed counter-responses against the human host immune system, by creating diverse “holes” of vulnerability in the innate immune system. Such mechanisms may have resulted due to the lower prophylactic and therapeutic focus upon sharpening the innate immune lines as directly as necessary. The overall objective of vaccine-development should be the sharpening of all immune departments that are targeted by various microbial agents for the purpose of transient innate immune suppression and the distribution of the microbial count/load at a systemic level. Likewise, it could be viable for the clinical research community to start focusing upon filling in the “gaps” of vulnerability that are now present in the pathways responsible for the proper natural immune activation and proportionate signalling toward the adaptive immune system. Perhaps, through such a process, the “road” toward the adaptive immune system, which is “old” and filled with “holes”, could be gradually transformed into a perfectly uniform “highway”, with all the required signals transmitted robustly from the innate to the adaptive immune system, before microbes manage to translate the various pathogenic proteins that transiently prevent such transmission altogether, until it becomes too late for the immune response to possibly develop in a proportionate and non-harmful manner to the organism. Such a scenario would be possible, given that it is almost impossible for human evolutionary growth to eventually stall and not risk experiencing a decrease as a result. Simultaneously, it is important for human society to bind by the principles of maintaining a healthy and nature-friendly lifestyle, given the philosophical quote of “We are what we eat.” The overall objective should be the facilitation of human and animal immune evolution over viral and bacterial molecular self-camouflaging from all possible directions, as a sharper human and animal evolutionary growth resulting from such actions could “cost” the sharper evolutionary growth of microbes as such, given that evolutionary patterns are based upon the models observed in Physics, in Newton’s Third Law of Motion, as well as in the First Law of Thermodynamics, which concerns the Conservation of Energy.

This study investigated the influence of Teacher Availability -TAV (Number of Available Teachers, Teacher Punctuality -TP, Teacher Promptness to Class -TPC) on Student Academic Achievement (SAA) in Public Senior Secondary Schools (PSSS) in Southwestern Nigeria. The descriptive survey research design of correlational type was adopted while the multi-stage sampling procedure was used in the study. A simple random sampling technique was used to select three (Oyo, Ogun, and Ekiti) states out of the six in Southwestern Nigeria, as well as one Senatorial District (SD) from each state. The proportionate-to-size sampling technique was used to select 40% of the Local Government Areas (LGAs) in each SD and 50% (101) of the schools in the sampled LGAs. A class of 3,030 PSSS II was used; 202 Mathematics and English Language teachers and 202 Heads of Department (101 each from Science and Arts) were purposively sampled, while 101 school administrators were enumerated. The instruments were TP ( =0.75); TPC ( =0.82); English Language Achievement Test-ELAT (KR-20=7.47) and Mathematics Achievement Test-MAT (KR-20=7.46). Data were analysed using descriptive statistics. Respondents’ ages were 46.5±5.20 years (teachers) and 17.60±1.60 years (students). There were 59.0% male teachers and 57.0% female students. The SAA (ELAT=45.7% and MAT=38.4%) was low. Also, TAV ( =3.36) was high against the threshold of 2.5, and TAV (ß=0.59, t=7.29) significantly contributed to SAA. Teacher availability influenced the student academic achievement in public senior secondary schools in Southwestern Nigeria. Hence, all the education stakeholders should pay attention to this for improved student academic achievement.

Influencer marketing has become a pivotal component of digital marketing strategies, offering brands a unique way to connect with audiences through trusted voices. However, measuring the return on investment (ROI) from influencer marketing campaigns can be challenging due to the intangible nature of brand influence and engagement. This abstract explores various techniques and strategies to measure and optimize ROI in influencer marketing. Measurement Techniques: The paper delves into both quantitative and qualitative methods for assessing influencer marketing ROI. Quantitative techniques include tracking metrics such as impressions, clicks, conversions, and sales, using tools like Google Analytics and social media insights. Additionally, advanced attribution models, such as multi-touch attribution and econometric modeling, are discussed for more accurately linking influencer activities to business outcomes. Qualitative approaches involve sentiment analysis and brand awareness studies, which help gauge the impact of campaigns on brand perception and customer loyalty. Optimization Strategies: To maximize the effectiveness of influencer marketing, the paper outlines several optimization strategies. These include selecting the right influencers based on audience alignment and engagement rates, setting clear and measurable campaign goals, and employing A/B testing to refine content and strategies. The importance of long-term partnerships and content diversification is also emphasized, as they can enhance authenticity and sustain audience interest. The abstract concludes that a comprehensive approach combining rigorous measurement techniques and strategic optimization can significantly enhance the ROI of influencer marketing campaigns. By continuously analyzing data and refining strategies, brands can better leverage influencer partnerships to achieve their marketing objectives.

The present study aimed to investigate the effect of solution of ethanol extractions of different microalgae species: Spirulina sp., Dunaliella sp. and Chlorella sp. on the accumulation of biologically active compounds in tomato fruits. Ethanol solution as well as treatment with drinking water were used as a control. Tomato cultivar ‘Belle’ F1 (Enza Zaden) was grown in 25 L pots, in peat substrate (pHKCl 5.5, producer Laflora LTd), polycarbonate greenhouse. Chemical composition – total carotenoids, lycopene and β-carotene content, total phenolics and anthocyanins, organic acids, vitamin C as well as dry matter, pH and soluble solids content – was determined in tomato fruits at the stage of full ripen. The influence of tested extracts on biologically active compounds on quality parameters of tomatoes was different, but no negative effect was observed. As only pH values as well as total phenol content and total soluble solids had statistically significant differences, results can be described with genetical stability of the cultivar.

Sarcoglycanopathies are among the most frequent and severe autosomal recessive forms of limb-girdle muscular dystrophies /LGMD/ with childhood onset. Mutations in , , and sarcoglycan genes lead to various kinds of LGMD. We present the clinical variability of LGMD 2C/R5 among a genetically homogeneous group of 56 patients, belonging to 35 pedigrees. Molecular genetic analysis showed thаt all 57 patients were homozygous for C283Y variant. The muscles of the pelvic girdle and the trunk were early and more severely affected, followed by the the shoulder girdle. Macroglossia, hypertrophy of the calves, scapular winging and lumbar hyperlordosis were common in the ambulatory phase. A great variability in the clinical presentation of LGMD 2C/R5 was observed both intra and interfamilial, despite the same underlying molecular defect. Females demonstrated a relatively milder clinical course, compared to males. Mean CK levels were 20 times above normal values. Muscle CT of MRI showed earlier and more severe involvement of the flexor proximal limb muscles in comparison to the extensor ones.

While adeno-associated viral (AAV) vectors are successfully used in a variety of in vivo gene therapy applications, they continue to be hampered by the immune system. Here, we sought to identify innate and cytokine signaling pathways that promote CD8+ T cell responses against the transgene product upon vector administration to murine skeletal muscle. Eliminating just one of several pathways (including DNA sensing via TLR9, IL-1 receptor signaling, and possibly endosomal sensing of double-stranded RNA) substantially reduced the CD8+ T cell response at lower vector doses but was surprisingly ineffective at higher doses. Using genetic, antibody-mediated, and vector engineering approaches, we show that blockade of at least two innate pathways is required to achieve an effect at higher vector doses. Concurrent blockade of IL-1R1>MyD88 and TLR9>MyD88>IFN I>IFNaR pathways was often but not always synergistic and had limited utility in preventing antibody formation against the transgene product. We further provide evidence that CpG depletion of vector genomes and inclusion of TLR9 inhibitory sequences can have a synergistic effect. However, even low-frequency CD8+ T cell responses could eliminate transgene expression. Thus, innate immune avoidance/blockade strategies, albeit helpful, may not be sufficient to prevent destructive cellular responses in muscle gene transfer because of redundancy of immune activating pathways.

Abstract—Image processing is a computationally intensive task that can benefit significantly from parallel techniques. In this study, we evaluate the efficiency of image processing using parallel techniques compared to sequential techniques. We use Dask to parallelize the loading and processing of images and compare the execution times for various image processing techniques, including smoothing, edge detection, rotation, and thresholding. The results show that parallel processing significantly reduces execution time compared to sequential processing.

Chronic kidney disease (CKD) is a growing public health issue with significant morbidity and mortality rates. Traditional diagnostics, with about 70% accuracy, often delay CKD detection, highlighting the need for more efficient methods. Recent studies indicate a potential link between CKD and auditory health, yet this relationship remains underexplored due to methodological challenges and the complexity of establishing causality. Our research utilizes data spanning from 2000 to 2020 from the National Health and Nutrition Examination Survey (NHANES), covering 12,392 participants, including 2,060 diagnosed with CKD. Through meticulous analysis employing logistic regression and Mendelian randomization, we have unearthed novel insights into the bi-directional associations between hearing impairment and CKD. Furthermore, we developed and validated a machine learning model that surpasses traditional diagnostic approaches in terms of accuracy and predictive power. These findings highlight the innovative integration of auditory examinations with demographic data to enhance CKD detection. Our approach demonstrates the potential of machine learning in transforming diagnostic methodologies, thus offering a significant advancement in the field of nephrology and public health.

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and serve crucial regulatory functions in both animals and plants. Nevertheless, there is limited understanding of lncRNAs and their patterns of expression and roles in sharks. In the current study, we systematically identified and characterized lncRNAs in the blue shark Prionace glauca from four tissues (liver, spleen, muscle, and kidney) using high-throughput sequencing and bioinformatics tools. A total of 21,932 high confidence lncRNAs were identified with 8,984 and 3,067 stably and tissue-specific expressed lncRNAs, respectively. In addition, a total of 45,007 differentially expressed (DE) lncRNAs were obtained among tissues, with kidney versus muscle having the largest numbers across tissues. DE lncRNAs trans target protein-coding genes were predicted, and functional gene ontology enrichment of these genes showed GO terms such as muscle system processes, cellular/metabolic processes, and stress and immune responses, all of which correspond with the specific biological functions of each tissue analyzed. These results advance our knowledge of lncRNAs in sharks and present novel data on tissue-specific lncRNAs, providing key information to support future functional shark investigations.

Medication adherence is a vexing challenge with nonadherence at 50% or greater among US adults. With most medications self-administered by patients in the home, home medication management practices, especially where patients store medication in the home and receptivity to guidance from healthcare providers, need to be better understood to improve adherence. We designed and deployed a survey to investigate home medication management. The 1,673 survey respondents reported that the most common home storage locations for medications were nightstand drawers (28%) and atop nightstands (27%). Kitchen cabinets and bathroom vanities were significantly associated with increased odds of having ever forgotten to take a medication. Desks, dining room tables, and nightstand drawers were associated with the greatest statistically significant decrease in odds of having ever forgotten to take a medication. Almost all (96%) respondents were receptive to guidance on medication storage from a healthcare provider. Patients are largely on their own to devise home medication management practices, yet some home storage locations are significantly associated with decreased odds of having forgotten to take a medication. Knowing which practices are associated with adherence may lead to better guidance for patients from healthcare providers and to innovation in the design of medication adherence interventions.

Wastewaters containing synthetic dyes, namely molecules with large aromatic structure which can produce harmful effects on the aquatic environment, are difficult to treat. Accordingly, and based on the adsorption technology, this work proposes the use of porous carbons as adsorbents of a red dye used in the wood industry. Three porous carbonaceous materials with relatively high porosity and tunable pore size were prepared by transformation of a nitrogen-rich precursor, polyacrylonitrile (PAN), at high temperature: N doped carbon (PAN-C), N-doped activated carbon with potassium hydroxide (PAN-C-Act) and N, S-co doped carbon with sulphur (PAN-S-C). Different experiments were planned to study the influence of pH (1.9-2.3, 6-6.8 and 11.8-12.6), solid/liquid ratio (S/L, 0.43-0.53 and 1.73-1.91 g L−1) and initial concentration (24 – 28 mg L−1 and 231 – 285 mg L−1) on the dye removal from aqueous solutions. The best results were found for the activated carbon (PAN-C-Act) at all concentrations and pH essayed. Specifically, the maximum adsorption capacity of 602.3 mg g−1 (99.9%, adsorption yield) was obtained at S/L of about 0.5 g L−1, acid pH, 285 mg L−1 and 48 h. Adsorption kinetics was better explained by the pseudo-second order model. Also, the existence of external mass transfer and intra-particle diffusion was confirmed.

Probiotics are living microbes that provide benefits to the host. The increasing data on health promotion following probiotics administration triggered growing interest among researchers and pharmaceutical companies looking for novel therapeutic or preventive tools. Infections of the lower genital tract in females are caused by a wide range of pathogens, they are widespread, and represent one of the main areas for the use of probiotics and postbiotics. Vulvovaginal candidiasis (VVC) affects 75% of women in their reproductive age at least once during their lifetime. Of these women 5-8% develop the recurrent form (RVVC). The disease onset is triggered by the overgrowth of Candida species on the vaginal mucosa. Here, we evaluated the beneficial properties of the Bacillus coagulans spore-producing LMG S-24828 against C. albicans and C. parapsilosis. Our results show that both alive B. coagulans and its Cell-Free-Supernatant (CFS) exerted antifungal activity against both fungi. Moreover, alive B. coagulans reduced hyphal formation, inhibited C. albicans adhesion to vaginal epithelial cells and showed co-aggregation capacity. Overall, B. coagulans LMG S-24828 exerted a protective effect on vaginal epithelial cells infected with C. albicans. These data suggest that B. coagulans LMG S-24828 may provide benefits in the context of Candida vaginal infections.

This study investigated the effects of icon familiarity on visual search performance. An equal number of familiar and unfamiliar icons were selected as background icons. These background icons were randomly arranged, and a visual search experiment was conducted to locate the target icon. The results showed no significant difference in the time required to find the target icon, regardless of whether the target icon was familiar or unfamiliar. This finding contrasts with previous studies that have suggested a positive effect of target icon familiarity on visual search performance, indicating that the influence of target icon familiarity may not always be consistent and could depend on the characteristics of the background icons. However, when background icons were grouped based on their familiarity, the time taken to locate the target icon was significantly reduced compared to when the icons were randomly arranged. To understand the underlying mechanism of this effect, participants' gaze fixation times were observed. The results revealed that participants spent more time fixating on areas where the target icon was located, rather than on areas without the target icon, suggesting a more efficient visual search process. Moreover, the shorter the visual search time, the higher the proportion of time spent fixating on the area containing the target icon. Additionally, this study examined the contrast ratio between the color of the background space and the dominant color of the target icon, comparing it with the visual search time. The findings indicated that as the contrast ratio increased, the visual search time decreased.

Biodiversity monitoring is a seminal key for understanding the delivery of ecosystem functions and services. Mediterranean forests and woodlands harbor the vast majority of regional vascular plant diversity, and hence, they are a good surrogate for detecting changes in biodiversity linked to global change. In this work, we present a database resulting from the study of vascular plant diversity in multi-scale plots of 0.1 ha, measured around the first decade of this century and located in Mediterranean forest environments. Diversity profiles are calculated from Hill numbers (0, 1 and 2) for local (α) and regional (ϒ) diversity, as well as multiplicative calculation of differential diversity (β). Main Mediterranean forests sampled had a medium coverage of 51 % and stand dominant height of 10.6 m being monospecific in two thirds of the cases. Local diversity reaches its highest values ​​(around 78 species per 0.1 ha) in Holm oak dehesas, with values ​​below 50 species for the set of the most productive forest stands dominated by species of the genus Pinus. As regards the contribution to regional diversity, it is the broadleaf formations that contribute the most, with stone pine forests and dehesas in an intermediate position, and pine forests contributing the lowest in species richness terms.

The environmental vulnerability diagnosis of a river basin depends on a holistic analysis of its environmental aspects and degradation factors. Based on this diagnosis, the definition of priority areas where interventions for environmental recovery should be carried out is fundamental, since financial and natural resources are limited. In this study, we developed a methodology to assess these fragilities using an Environmental Vulnerability Index (EVI) that combines physical and environmental indicators related to the natural sensitivity of ecosystems and their exposure to anthropogenic factors. The EVI developed was applied to the headwater’s region of the São Francisco River basin, Brazil. The proposed index was based on the AHP multi-criteria analysis and was adapted to include four variables representative of the study area: Land Use Adequacy, Burned Area, Erosion Susceptibility and Quantitative Water Balance. The EVI analysis highlighted that the presence of easily erodible soils, associated with sloping areas and land uses above their capacity, generate the most vulnerable areas in the headwaters of the São Francisco River basin. The results of this study indicate where resources should be applied for environmental preservation in the basin under study, directing the allocation of efforts to areas with lower resilience in maintaining ecosystem services.

Synergistic control of emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, identifies and quantifies the synergistic drivers affecting these emission trends. Inventory data show that between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOx emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing-Tianjin-Hebei, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, the high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Introduction; to the best of the authors knowledge no past research has established how illness narrative master plots are expressed initially, and then if, and how they change longitudinally following musculoskeletal trauma. The aim of the current research was able to consider how specific master plots were expressed, interact and change across time following musculoskeletal trauma. Methods; a narrative analysis was undertaken that included individuals who had experienced a musculoskeletal traumatic injury. Individuals were included if they were an inpatient within 4 weeks of the first interview had mental capacity to participate and were able to communicate in English. Three interviews were undertaken (within 4 weeks of injury, 6 and 12 months). A 5-stage categorical form type narrative analysis was performed. Results; Twelve individuals (49.9±17.5 years; 7 male, 5 female) completed interviews at three time points following the trauma event (&lt;4 weeks months, 6 months and 12 months). Three main narratives that appeared to work together to facilitate a positive accommodation of the trauma event into the individual’s life were presented. These included the resumption narrative, the activity narrative and quest narrative. Finally, less often regressive narratives were identified although these narratives were, at times, actively avoided. Discussion; The current results provide important consideration for how narratives are used within clinical practice, in particular the value of how these three narratives could be access and promoted.

Rosemary is one of the most important medicinal plants for natural therapy due to its multiple pharmacological properties, such as antioxidant, anti-inflammatory, neuroprotective, antiproliferative, antitumor, hepato- and nephroprotective, hypolipidemic, hypocholesterolemic, antihypertensive, anti-ischemic, hypoglycemic, radioprotective, antimicrobial, antiviral, antiallergic, wound healing. Our study reports for the first time, over a 12-month period, the identification and quantification of polyphenols and the investigation of the antioxidant and acetylcholinesterase (AChE) inhibitory activity of the Rosmarinus officinalis L. species harvested at flowering from the flora of southwestern Romania (Oltenia Region). Identification and quantification of polyphenolic acids was made by ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS). Total phenolic content was determined using the spectrophotometric method. In situ antioxidant and anticholinesterase activity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and AChE inhibitory assay, respectively, on high-performance thin-layer chromatography (HPTLC) plates. DPPH radical scavenging activity was also assessed spectrophotometrically. The results revealed significant correlations between specific polyphenolic compounds and the measured biological activities, understanding the role of seasonal variations and providing insights into the optimal harvesting times and medicinal benefits of rosemary. Our research brings new information on the phytochemical profile of R. officinalis, as a natural source of polyphenols with antioxidant and AChE inhibitory properties.

Introduction: Study aimed to establish the effect of calcium lactate enamel pretreatment related to different fluoride types and concentrations on enamel uptake of alkali-soluble fluorides. Materials and methods: In a blind and randomized in vitro study, total of 60 teeth are used. First 30 teeth, cut and randomly allocated into one of the following treatment: A) Calcium lactate pretreated followed by 3 different fluoride solution; B) ”Fluoride only” group, slabs are treated with 3 different fluoride solution; C) “Calcium only” group, slabs treated with calcium lactate solution; D) slabs are treated with deionized water (negative control group). The next 30 teeth underwent all above described group procedures, but treated with lower fluoride concentrations. Fluoride was extracted from enamel using 1M KOH solution and analyzed using fluoride ion-specific electrode. Wilcox Matched Pairs test and Friedman ANOVA analyzed the effect of substrate and treatments. Results: The findings revealed that slabs treated with NaF following calcium lactate pretreatment exhibited significantly greater enamel uptake of alkali-soluble fluoride compared to other substrates. This significant effect is not observed at lower fluoride concentrations. Conclusion: The study demonstrates that pretreatment with calcium lactate followed by treatment with NaF at 226 ppm F significantly enhances the uptake of alkali-soluble fluoride in enamel compared to other fluoride type.

The grand antiprism A is an outlier among the uniform 4-polytopes, since it is not obtainable from Wythoff’s construction. Its symmetry group G(A) has been incorrectly described as [[10,2+,10]] or even as an `ionic diminished Coxeter group’. In fact, G(A) is another group of order 400, namely the group ±[D10×D10]·2, in the notation of Conway and Smith.

The perovskite crystal structure has garnered significant attention due to its unique properties and potential applications. Particularly, YTiO3 is a ferromagnetic Mott insulator with strong electron correlation effects and orbital ordering, so it is a good candidate for electronic applications. In this research, we investigate the structural, elastic, and electronic properties of Y1-xSrxTiO3 (x=0.01, 0.10, 0.50, 0.99) perovskites within the Pm3m space group using density functional theory (DFT) to improve mechanical properties while preserving electronic properties. Initial geometry optimizations were performed using the GGA-PBE functional with a 6×6×6 Monkhorst-Pack k-point mesh. The study utilized the CASTEP code with ultrasoft pseudopotentials for DFT calculations. Complete structural relaxations were achieved, and the elastic constants which confirm the mechanical stability of the materials were determined using the finite strain theory. The electronic properties were analyzed through band structure and partial density of states (PDOS) calculations. Despite variations in band structures due to Sr doping, no bandgap was observed, indicating the metallic nature of the compounds. The study highlights that p and d orbitals are predominant in electronic states. The findings suggest that Sr doping significantly influences the elastic properties, making these materials potentially valuable for various applications requiring robust mechanical properties.

Previous studies have examined the impact of Internet use on health in China, but they have not adequately addressed the issue of reverse causality or conducted a detailed analysis of health status. This study uses three waves of longitudinal data from the China Family Panel Studies conducted in 2014, 2016, and 2018 to investigate the association between Internet use and health status in China, aiming to address these gaps. The results indicate that Internet use may improve health status, including self-rated health, mental health, and outpatient visits. These effects vary by gender and age group: the positive effect of Internet use on health outcomes is more pronounced for women, and for middle-aged and older generations, compared to men and younger generations. These findings provide new evidence of the beneficial impact of Internet use on health outcomes in China, suggesting that policies promoting Internet utilization could enhance individuals’ health status, particularly among women and middle-aged and older populations.

This article presents the theoretical study, numerical simulation and the fabrication of a phase shifter and stub resonator in microstrip ridge gap waveguide (MGCW) technology with the use of liquid crystal (LC) in its substrate as a reconfigurable material. The phase shifter and the stub resonator are filled with LC and thanks to LC's dielectric anisotropy properties, the phase shift and resonance response can be easily controlled using an external electric or magnetic bias field. The phase shifter was designed to operate in the range of 10 to 20 GHz and the resonator was designed to operate in the range of 7.8 to 8.8 GHz. The phase shifter's insertion losses, associated with both parallel and perpendicular LC's permittivity, as well as the phase response were computed and measured. Finally, the figure of merit (FoM) was extracted. The resonator's frequency response, associated with both parallel and perpendicular LC's permittivity, was computed. The resonator's frequency responses, provided different polarization voltages, were measured and compared to the simulation results. The technological issues were discussed. The good agreement between simulation and measurement results establishes this technology as a viable approach to the development of RF reconfigurable devices.

Infections are a common post-operative ailment for patients who have received a dental implant or device and can be attributed to biofilm formation in tissue or on the implant. Many current solutions for oral hygiene have side effects and affect the natural oral microbiome. 2-heptylcyclopropane-1-carboxylic acid (2CP) is a medium-chain fatty acid and synthetic diffusible signaling factor that can prevent and disperse biofilm. The purpose of this work was to evaluate an immersion strategy for coating hydroxyapatite (HAp) with 2CP to prevent biofilm attachment on and around natural teeth and dental implants. The release profile of 2CP-loaded and 2CP+oral rinse-loaded HAp coupons (n=6) was assessed by a 3-day exposure to phosphate buffered saline (PBS). Antimicrobial properties against Porphyromonas gingivalis and cytocompatibility of 2CP-loaded HAp coupons (n=4) were also assessed alone and in combination with 0.12% chlorhexidine gluconate oral rinse. The majority of 2CP is released by 12 hours. 2CP, oral rinse, and 2CP+oral rinse significantly reduced P. gingivalis viability, though direct contact assay demonstrates a significant reduction in Saos-2 viability for oral rinse and 2CP+oral rinse coupons. Immersion or rinsing hydroxyapatite with 2CP could inhibit biofilm-associated dental infections and prevent further complications including caries, gingivitis, and peri-implantitis.

The fuel prices are increasing nowadays, causing a burden on the power system. From this, diesel generators that are still in use, must be hybridized with renewable energy (RE) to levelized the overall projects costs. This study aims to schedule an operation of a hybrid system photovoltaic (PV)/ diesel in a remote area which located in Wadi Rum district in Jordan to serve factory load in addition to obtain the best economical system combination that can serve the needs of a continuous electrical load without any interruption. Based on the results of the analysis using HOMER software, the configuration in the system will be a combination between PV modules, and diesel generator. The hybrid system has met the target for electricity production which is documented in upcoming sections.

Midkine (MDK) is a multifunctional heparin-binding growth factor, and has been shown to regulate cell growth, survival and migration. It also plays important roles in several inflammatory diseases such as sepsis. However, the role of MDK in the lungs has not yet been elucidated. In the present study, we investigated the role of MDK in pulmonary inflammation experiments using a mouse lipopolysaccharide (LPS)-induced pneumonia model and human bronchial cells. Wild-type and MDK-deficient mice were injected intratracheally with LPS, and several inflammatory parameters were analyzed. In the wild-type mice, mRNA expression of MDK in lung tissues was significantly increased after intratracheal LPS injection. The MDK-deficient mice showed significantly lower counts of total cells and neutrophils, as well as lower concentrations of neutrophil chemokines, KC and MIP-2 in bronchoalveolar lavage fluid, compared to wild-type mice. Moreover, mRNA expressions of TNF-α, KC and MIP-2 in lung tissues, as well as histopathological lung inflammation score, were significantly lower in the MDK-deficient mice. Furthermore, in in vitro experiments using bronchial epithelial cells, LPS stimulation increased mRNA expression of MDK, and MDK knockdown by siRNA decreased LPS-induced TNF-α and CXCL8 upregulation. These findings suggest that deficiency of MDK attenuates LPS-induced pulmonary inflammation.

Antimicrobial resistance (AMR) is a global threat associated with high morbidity and mortality, particularly in low- and middle-income countries. Inappropriate use of antimicrobials is one of the major drivers of the AMR pandemic. This study aims to evaluate the rate and quality of antimicrobial prescription and use at the University Teaching Hospital of Kigali, a tertiary referral and teaching hospital. A point prevalence survey (PPS) of antimicrobial prescription was conducted using the Global PPS tool, including the healthcare-acquired infections (HAI)-module. On the day of PPS, 39.3% (145/369) of the patients were prescribed at least one antimicrobial. Out of 259 prescribed antimicrobials, 232 (89.6%) were antibacterials of which 151 (65.1%) belonged to the Watch-group of the WHO AWaRe classification. Top three antibiotics prescribed were cefotaxime (87; 37.5%), parenteral metronidazole (31; 13.4%); and meropenem (23; 9.9%). Stop/review of the prescribed antimicrobials was documented in 27/259 prescriptions (10.4%). Surgical prophylaxis (SP) was prescribed for more than one day in 83.3% of 61. Samples for culture were sent for 27.1% (63/232) of all prescribed antibiotics. This PPS showed a high usage of Watch antibiotics, prolonged surgical prophylaxis and other poor-quality indicators. Therefore, there is an urgent need for antimicrobial stewardship interventions.

(1) Background: Youths with multiple risks and severe disadvantages experience poorer health and educational outcomes than less disadvantaged peers. To address problems with coping and self-regulation in this group, mental skills training (MST) approaches more commonly used in sport are an emerging intervention approach. (2) Methods and Results: This narrative review synthesizes literature to explain the need for MST, how it works, and evidence to support it works by focusing on two well evaluated programmes: LifeMatters and My Strengths Training for Life™. (3) Conclusions: To support positive youth development, MST is a strengths-based, flexible and adaptable approach to help fill the shortage of available evidence-based programs for those youths facing multiple disadvantages. The findings of this review may facilitate policy makers, commissioners, program planners, and researchers in the uptake of MST or similar psychoeducational approaches in future.

Background: IL-15 is a homeostatic cytokine for human T and NK cells. However, whether other cytokines influence the effect of IL-15 is not known. We have studied the impact that IL-10, TGF-, IL-17A and IFN- have on the IL-15-induced proliferation of human T cells and the expression of HLA class I (HLA-I) molecules. Methods: Peripheral blood lymphocytes (PBL) were labeled with CFSE, and stimulated for 12 days with IL-15 in the absence or presence of the other cytokines. The proportion of proliferating T cells and the expression of cell surface HLA-I molecules were analyzed by flow cytometry. Results: The IL-15-induced proliferation and expansion of T cells was paralleled by an increase in the expression of HC-10-reactive HLA-I molecules, namely on T cells that underwent ≥5-6 cycles of cell division. Noteworthy, the IL-15-induced proliferation of T cells was potentiated by IL-10 and TGF-β, but not by IL-17 or IFN-, and was associated with a decrease in the expression of HC-10-reactive molecules. Conclusions: The cytokines IL-10 and TGF-β potentiate the proliferative capacity that IL-15 has on human T cells in vitro, an effect that is associated with a reduction in the amount of HC-10 reactive HLA class I molecules induced by IL-15.

Fall armyworm, Spodoptera frugiperda, is one of the major migratory polyphagous insect pests of various crops. The essential nutrient and mineral profile of host plants determines the feeding fitness of herbivorous insects. As a result, growth and development of insects is affected. To determine the effect of nutrient and mineral profile of different host plants (maize, castor bean, cotton, cabbage, okra and sugarcane) on the growth and development of S. frugiperda, biological parameters like larval weight, pupal weight (male/female), feeding and growth indices were calculated. The proximate compositions and mineral contents of the tested host plants showed a significant difference (p&lt;0.5). Better nutrients were observed in castor bean and maize host plants. The growth indices on these host plants also showed the statistical difference (p&lt;0.05) except efficiency of ingested food (p&gt;0.05). The maximum relative growth rate (RGR), relative consumption rate (RCR) and consumption index (CI) were recorded in S. frugiperda larvae that fed on maize and castor bean leaves. Larval, male and female pupal weights were the maximum in the larvae feeding on castor bean host plant. In case of fitness indices, the highest larval growth, pupal growth, standard growth and fitness indices were observed in S. frugiperda larvae that fed on maize. The findings of the present study highlight the dynamic growth and development of S. frugiperda larvae on maize plants and provide novel information based on nutritional ecology to develop sustainable integrated pest management strategies using selective crop rotation and limiting alternative host plants.

Pd EnCat™ 30 is a palladium catalyst broadly used in several hydrogenation and cross-coupling reactions. It is known for its numerous beneficial features, which include high-yielding performance, easy recovery, and reusability. However, the available data regarding its recyclability in Suzuki coupling reactions are limited to a few reaction cycles and, therefore, fail to explore its full potential. Our work focuses on investigating the extent of Pd EnCat™ 30 reusability in Suzuki cross-coupling reactions by measuring its performance according to isolated yields of product. Our findings demonstrate that Pd EnCat™ 30 can be reused over a minimum of 30 reaction cycles, which is advantageous in terms of cost reduction and more sustainable chemical production.

This study evaluated the effect of pig diet supplementation with an Olea europaea L. extract on the muscle fatty acid composition. Ten commercial hybrid pigs (Large White x (Landrace x Duroc)) were randomly assigned to two experimental treatments and fed either a standard diet (C) or diet with olive leaves extract (OL). For 90 days, the OL group received the olive leaf extract (300 mg/head/day), which mainly comprises oleuropein diglucoside, luteolin-7-glucoside, and verbascoside. The phenolic content, antioxidant activity, bioactive molecules’ characterization, and the fatty acids profile of meat and diet were performed. The results indicated that while the OL supplementation did not significantly alter the overall chemical composition of the meat or the pigs' performance, it did modify the lipid profile of the meat. The OL diet results in a significant reduction in SFA and an increase in oleic acid in meat, which correspondingly elevates the total MUFA content. Dietary treatment reduced the sum of n-6 PUFA in the meat of the OL group, and resulted in a significantly lower n-6/n-3 PUFA ratio. Therefore, these findings suggest that incorporating olive leaf extract into the pig diet enhances the nutritional and functional quality of the meat by improving its fatty acid profile.

Breakthrough COVID-19 (occurring in fully vaccinated people) has been described. Data on its characteristics among immune mediated rheumatic disesases (IMRD) patients are scarce. This study describes breakthrough COVID-19 among IMRD patients participating of SAFER-study, a Brazilian multicentric cohort evaluating safety, effectiveness and immunogenicity of SARS-Cov-2 vaccines in autoimmune diseases. Descriptive analysis and a binary logistic regression model, to evaluate predictors of COVID-19-related hospitalization, were performed. P-value < 0.05 was significant. The included 160 patients were predominantly females (83.1%), with mean (SD) age 40.23 (13.19) years. Patients received 2 (19%), 3 (70%) or 4 (11%) vaccine doses. The initial two-dose series was mainly with ChAdOx1 (Oxford/AstraZeneca) (58%) or BBIBP-CorV (Sinopharm-Beijing) (34%). The first booster (n=150) was with BNT162b2 (BioNtech/Fosun Pharma/Pfizer) (63%) or ChAdOx1 (29%). The second booster (n=112) was with BNT162b2 (40%) or ChAdOx1 (26%). COVID-19 hospitalization rate was 17.5%. IMRD moderate/high activity (OR: 5.84, CI: 1.9-18.5, p=0.002) and treatment with corticosteroids (OR: 2.94, CI: 1.02-8.49, p=0.0043) associated with higher odds of hospitalization, while the increasing number of vaccine doses was protective (OR: 0.37, CI: 0.15-0.9, p=0.032). These findings, along with previous reassuring results about the safety of the COVID-19 vaccines, argue in favour of booster vaccination in IMRD patients.

Objective: Interstitial fibrosis / tubular atrophy (IFTA) is a common, irreversible, and progressive form of chronic kidney allograft injury, and it is considered a critical predictor of kidney allograft outcomes. The extent of IFTA is estimated through a graft biopsy, while a non-invasive test is lacking. The aim of this study was to evaluate the feasibility and accuracy of an MRI radiomic-based machine learning (ML) algorithm in estimating the degree of IFTA in a cohort of transplanted patients. Approach: Patients who underwent MRI and renal biopsy within a 6-month interval from 1/1/2012 to 1/3/2021 were included. Stable MRI sequences were selected, and renal parenchyma, renal cortex and medulla were segmented. After image filtering and pre-processing, we computed radiomic features which were subsequently selected through a LASSO algorithm for their highest correlation with the outcome and lowest intercorrelation. Selected features and relevant patients’ clinical data were used to produce ML-algorithms using 70% of the study cases for feature selection, model training and validation with a 10-fold cross-validation, and 30% for model testing. Performances were evaluated using AUC with 95% confidence interval. Main results: 70 coupled tests (63 patients, 35.4% females, mean age 52.2 years) have been included and subdivided into a wider cohort of 50 for training and a smaller cohort of 20 for testing. For IFTA ≥ 25%, AUCs in test cohort were 0.60, 0.59, and 0.54 for radiomic features only, clinical variables only, and combined radiomic-clinical model, respectively. For IFTA ≥ 50%, AUCs in training cohort were 0.89, 0.84, 0.96, and in test cohort were 0.82, 0.83, and 0.86, for radiomic features only, clinical variables only, and combined radiomic-clinical model, respectively. Significance: An ML-based MRI radiomic algorithm showed promising discrimination capacity for IFTA>50%, especially when combined with clinical variables. These results need to be confirmed in larger cohorts.

The transition to renewable energy sources is critical for sustainable development, particularly in rural regions with limited access to electricity. Solar-powered microgrids offer a promising solution for rural electrification by providing reliable, clean energy that can enhance economic opportunities and improve quality of life. This paper presents a techno-economic analysis of solar-powered microgrids for rural areas, evaluating their feasibility, costs, and benefits. The analysis encompasses technological aspects, such as solar panel efficiency, battery storage, and grid management, alongside economic factors including initial investment, maintenance costs, and potential returns. Additionally, the study assesses the social impact of solar-powered microgrids, exploring their effects on local communities, including improvements in education, health, and economic activities. The findings indicate that solar microgrids can be a viable and impactful solution for rural electrification, with significant long-term benefits for both economic development and social well-being.

The detection and recognition of tables in image-based documents is a challenging and essential task for automated data extraction and anal- ysis. This paper introduces a methodology that utilizes Convolutional Neural Networks (CNNs) to address this problem. By harnessing the ro- bust visual recognition abilities of CNNs, the proposed method effectively detects and extracts tables from image-based documents. Additionally, an Encoder-Dual Decoder (EDD) architecture is employed to extract the textual content from table cells, enabling the transformation of visual data into structured, machine-readable formats. This structured data is then further processed using a Vector Space Model (VSM)-based language modeling technique for query-based table retrieval. The methodology’s accuracy is assessed by analyzing the spatial relationships between the extracted cells and comparing them against a pre-defined table structure. The results provide an evidence to the effectiveness of the proposed ap- proach, with an impressive 85% accuracy rate and a corresponding error rate of 15%. This accurate extraction and recognition of tables from image-based documents can significantly enhance applications in data analysis, information retrieval, and knowledge extraction.

Calcretes are indurated terrestrial carbonates that are widespread in arid and semi-arid settings and serve as important archives of present and past environments. Here we use geochemical tools to explore the nature and origin of calcretes documented from tropical Niue Island in the Southwest Pacific. The study recognizes two types of calcretes that differ in their mineral assemblage, microfabrics, elemental chemistry and carbon and oxygen isotopes. The calcretes common in the paleo-lagoon soils consist of 90% low-Mg calcite and ~10% highly weathered Mg-Al silicates. These pedogenic calcretes formed in the soil profiles within the vadose zone and bear the following distinctions: (i) Fe/Al ratio of 0.75, identical to the ratio in soils (Fe/Al=0.76 ±0.5), substantiates the link between the calcretes and soils; (ii) presence of rhizoliths, root voids, micritic nodules and clasts are consistent with a pedogenic calcrete fabric, and (iii) 13C and 18O depletions of -10.6‰ and -5.3‰, respectively, are compatible with carbon sources from microbial and roots respiration, and formation in oxygen isotope equilibrium with vadose waters. Unlike the pedogenic calcrete, a rare calcrete from the coastal terrace contains an exceptionally rare hydrotalcite mineral (65%) coated by microbial films. We contend that the hydrotalcite-rich calcrete was deposited through interaction of dolomite with seawater, similar to the method of producing hydrotalcite in the laboratory. 13C and 18O enrichments of 0.8 to 1.7‰ and -1.0 to -1.6‰, respectively, are in agreement with (i) mixed carbon sources consisting of microbial CO2 degassing, seawater HCO3 and dolomite dissolution, and (ii) oxygen isotope equilibration with a seawater-derived fluid.

This study fabricated piezoelectric fibers of polyvinylidene fluoride (PVDF) with graphene using near-field electrospinning (NFES) technology. A uniform experimental design table U*7 (7^4 ) was applied, considering weight percentage (1-13 wt%), distance between needle and disk collector (2.1-3.9 mm), and applied voltage (14.5-17.5 kV). We optimized the parameters using electrical property measurements and the Kriging response surface method. Adding 13 wt% graphene significantly improved electrical conductivity, increasing from 17.7 μS/cm for pure PVDF to 187.5 μS/cm. The fiber diameter decreased from 21.4 μm in PVDF/1% graphene to 9.1 μm in PVDF/13% graphene. Adding 5 wt% graphene increased the β-phase content by 6.9%, reaching 65.4% compared to pure PVDF fibers. Material characteristics were investigated using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), contact angle measurements, and tensile testing. Optimal parameters included 3.47 wt% graphene, yielding 15.82 mV voltage at 5 Hz and 5 N force (2.04 times pure PVDF). Force testing showed a sensitivity (S) of 7.67493 log(mV/N). Fibers were attached to electrodes for piezoelectric sensor applications. Results affirmed enhanced electrical conductivity, piezoelectric performance, and mechanical strength. The optimized piezoelectric sensor could be applied to measure physiological signals, such as attaching it to the throat under different conditions to measure the output voltage. The force-to-voltage conversion facilitated subsequent analysis.

The medical research field has been tremendously galvanized to improve the prediction of therapy efficacy by the revolution in artificial intelligence (AI). An earnest desire to find better ways to predict the effectiveness of therapy with the use of AI has propelled the evolution of new models in which it can become more applicable in clinical settings such as breast cancer detection. However, in some instances, the U.S. Food and Drug Administration was obliged to back some previously approved inaccurate models for AI-based prognostic models because they eventually produce inaccurate prognoses for specific patients who might be at risk of heart failure. In light of instances in which the medical research community has often evolved some unrealistic expectations regarding the advances in AI and its potential use for medical purposes, implementing standard procedures for AI-based cancer models is critical. Specifically, models would have to meet some general parameters for standardization, transparency of their logistic modules, and avoidance of algorithm biases. In this review, we summarize the current knowledge about AI-based prognostic methods and describe how they may be used in the future for predicting antibody-drug conjugate efficacy in cancer patients. We also summarize findings of recent late-phase clinical trials using these conjugates for cancer therapy.

The dominant part of energy performance of a building consists of consumption of heating and lighting. Both heating and lighting systems of buildings work at their designed efficiency for most of the buildings’ lifetimes. Interference with existing systems is costly considering replacements and construction adjustments. Therefore, considerable effort must be put into the design of these systems during the building design phase. The article is focused on luminaire layout design strategy, which affects the number of luminaires in a building and therefore their power consumption and the sustainability of the building. A genetic algorithm with radiosity implemented has been used to find suitable placements of luminaires of a single type in a model room to decrease the number of luminaires as much as possible. Three outcomes of optimal luminaire layout design are presented in this paper, including design strategy conclusions. Results of calculation outcomes are verified by software DIALux, that is commonly used for designing lighting systems.

This study simulated the effects of direct predatory pressure, indirect predatory pressure, and conspecific injury signals on the sea cucumber (Apostichopus japonicus) to determine changes in the activity of immune defense enzymes (lysozyme, acid phosphatase, alkaline phosphatase) and antioxidant stress enzymes (catalase, superoxide dismutase, malondialdehyde). Samples of sea cucumber juveniles were collected at 3 hours, 12 hours, 72 hours, and 96 hours post-predatory stress, and six enzymes related to immune defense and antioxidant stress were selected for activity assays, namely lysozyme (LZM), acid phosphatase (ACP), alkaline phosphatase (AKP), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA). The results indicated that under direct predatory pressure, the activity of catalase in sea cucumbers was significantly higher than that of the control group at 3 hours (P < 0.05), while the activities of acid phosphatase, alkaline phosphatase, and catalase were significantly lower at 72 hours (P < 0.05). Under indirect predatory pressure, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), the activity of alkaline phosphatase was significantly higher at 72 and 96 hours (P < 0.05), catalase was significantly lower at 72 hours, and the activity of superoxide dismutase was significantly higher at 72 hours (P < 0.05). Under the influence of conspecific injury signals, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), and the activity of superoxide dismutase was significantly higher at 96 hours (P < 0.05). The sea cucumber enhanced its antioxidant capacity 3 hours after facing the predator, while its immune defense mechanism was suppressed at 72 hours. When facing indirect predatory pressure, the sea cucumber may have made immune and antioxidant preparations for the arrival of unknown risks. The experimental results show that predatory pressure has a significant impact on the immune and antioxidant functions of sea cucumbers, which may be related to the physiological state and environmental adaptability of the sea cucumber. This study provides a new perspective for understanding how sea cucumbers cope with predatory pressure in the natural environment and offers theoretical support for the cultivation management of sea cucumbers.

This study aims to evaluate tramadol’s effect during elective ovariectomy in female dogs under general anesthesia with isoflurane, premedicated with 0.025 mg/kg medetomidine IM, 0.2 mg/kg methadone IM and 2 mg/kg ketamine IM. Seventeen female dogs were divided into control (CG) and tramadol (TG) groups. Dogs in the TG also received a 4 mg/kg IV tramadol bolus one minute prior to skin incision. Heart rate (HR), systolic blood pressure, and mean blood pressure were recorded at baseline, skin incision, traction (T1) and clamping (T2) of the right ovarian pedicle, and traction and clamping of the left ovarian pedicle. Tramadol caused a 39.8% (p&lt;0.05) and a 31.9% (p&lt;0.05) HR increase at T1 and T2, respectively, when compared to the CG, which lasted a maximum of eight minutes. Although tramadol has a potential positive chronotropic effect, it can safely provide additional intraoperative analgesia before intense noxious stimuli, for at least seven minutes.

Quantum optimization is a significant area of quantum computing with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational Hamiltonian-based algorithms, struggle on present quantum devices due to noise and decoherence. Existing techniques attempt to mitigate these issues through employing different Hamiltonian encodings or Hamiltonian clause pruning but often rely on optimistic assumptions rather than a deep analysis of the problem structure. We demonstrate how to formulate the problem Hamiltonian for the Quantum Approximate Optimization Algorithm to satisfy all the requirements that correctly describe the considered tactical aircraft deconfliction problem, achieving higher probabilities of measuring solutions compared to previous works. Our results indicate that constructing Hamiltonians from an unconventional, quantum-specific perspective with a high degree of entanglement results in linear number of entangleming gates instead of exponential and superior performance compared to standard formulations. Specifically, we achieve higher probabilities of measuring feasible solutions in 9 out of 9 instances compared to standard Hamiltonian formulations and surpass quadratic programming formulations known from quantum annealers in 7 out of 9 instances. These findings suggest that there is substantial potential for further research in quantum Hamiltonian design and that gate-based approaches may offer superior optimization performance over quantum annealers in the future.

One of the main products of the forest, which has the greatest economic impact, is wood. Due to its characteristics, the wood requires certain types of vehicles for transport it. For this reason, the accessibility of the stands with forest roads plays significant role in the efficiency of the wood logging process, which aims to bring the wood from the forest to the harvesting area located, frequently, next to a permanent transport route. The process of wood transport from the forest initially takes place on forest roads and after that on public roads. The technological process of wood transport represents an important stage in this process, and its good organization can have implications on the final price of the wood material. Based on those mentioned above, the paper aims to highlight the factors that can influence productivity in the case of loading wood in forestry trucks and forestry platforms, in different conditions. Thus, the research was carried out in four counties in Romania and addressed the loading of wood in different forestry trucks and platforms, with or without trailers. Following the evaluation of the work phases specific to the process of round wood loading in vehicles of transport, it was found that sometimes a significant importance is given to the working phases that can be carried out before the loading process, as phases of preparation of the wooden material in order to load it. Also, the facilities of the transport vehicles, the assortments of wood material, as well as the experience of the operators are the main factors that can lead to an increase in productivity.

The intersection of pedagogy and business models offers a compelling framework for enhancing educational outcomes through strategic innovation and operational efficiency. This is the first study that explores integrating value-based business models into pedagogy, proposing four models: Value Positioning (critical thinking, AI-oriented), Value Delivery (actionable thinking, inquiry-oriented), Value Capture (analytical thinking, sustainability-oriented), and Value Propo-sition (creative thinking, project-oriented). These models aim to foster student engagement, op-timize resource allocation, and drive institutional growth, aligning educational objectives with market demands to prepare learners for future workforce challenges. For instance, Business An-alytics courses, under the Value Delivery category, emphasize actionable thinking. It secures low to middle-level jobs but lacking global decision-making power in value positioning for Finland and the UK. Integrating principles of customer-centric design, continuous improvement, and competitive differentiation, educational leaders can create responsive and impactful learning environments. Value-based business models enhance educational practices by providing a structured and quantifiable approach to improving teaching and learning outcomes. A symbiotic relationship between pedagogical theories and business strategies can lead to innovative educa-tional practices, improved student graduation outcomes, and sustainable success for institutions and countries. This alignment ensures educational programs remain relevant to current market needs and adaptable to future challenges and opportunities.

This research aimed to discover how to create a customer experience that includes FEEL, SENSE, THINK, ACT, and RELATE to increase satisfaction with the Subscription Video on Demand (SVoD) application. A descriptive quantitative method was used, and the sample was 423 respondents in Indonesia who had used the application for at least 1 month. Furthermore, this research used probability sampling using a technique for random sampling. Based on the data available, experience accounted for 0.509, or 50.9%, of the application satisfaction. With a beta value of 0.295, the FEEL variable was the only one in this study to significantly and positively affect customer satisfaction; the other variables, SENSE, THINK, ACT, and RELATE, had no discernible effects. It is anticipated that the theoretical foundation provided by this research will be beneficial to the entertainment industry, particularly the SVoD application sector. This includes the product and service development division that focuses on customer inner feelings and emotions.

Ultrasound imaging is a vital imaging tool in musculoskeletal medicine, with the number of publications on ultrasound-guided surgery increasing in recent years. However, ultrasound imaging has drawbacks, such as operator dependency and image obscurity. Artificial Intelligence (AI) and Deep Learning (DL), a subset of AI, can address these issues. DL methods, including segmentation, detection, and localization of target tissues and medical instruments, potentially allow physicians and surgeons to perform ultrasound-guided procedures more accurately and efficiently. This review summarizes recent advances in ultrasound-guided procedures for musculoskeletal diseases and provides a comprehensive overview of the utilization of AI/DL in ultrasound for musculoskeletal medicine, particularly focusing on ultrasound-guided surgery.

Video self-supervised learning (VideoSSL) offers significant potential for reducing annotation costs and enhancing a wide range of downstream tasks in video understanding. The ultimate goal of VideoSSL is to achieve human-level video intelligence across a spectrum of tasks, from low-level tasks such as pixel temporal correspondence to high-level complex spatio-temporal tasks like action recognition. However, most existing VideoSSL methods focus on isolated aspects of this spectrum and fail to integrate different levels of task complexity. Our study presents the first comprehensive survey that connects all families of VideoSSL methods. We provide a detailed review of the full spectrum of VideoSSL, from low to high levels, by conceptually linking their self-supervised learning objectives and including a comprehensive categorization. Our extensive evaluation highlights the strengths and limitations of each SSL objective across various downstream task families. We also detail the challenges in current VideoSSL research such as data curation, interpretability, deployment, and privacy concerns, an area that previous surveys have not thoroughly explored. In addressing these challenges, we recognize the strengths of existing methods in addressing these challenges and outline future directions for research.

This study aims to evaluate the effectiveness of inactivating Salmonella enteritidis in fresh chicken breast by irradiation using a combination of short-wave UV (0, 3, 6, 9, 12 and 15 J / cm2) and a natural antimicrobial such as caffeine (0, 5, 10, 15 and 20 nM/g) as alternative proposals to conventional techniques to reduce pathogens in food. The temperatures used were from 2 to 22°C. The most suitable models were double Weibull in 60% of cases with an adjustment of R2 0.9903-0.9553 and Weibull + cola, in 46.67%, with an adjustment of R2 of 0.9998-0.9981. Noting that the most effective combination in the reduction of Salmonella was 12 J/cm2 of UV light and 15 nM/g of caffeine, with a reduction of 6 CFU/g and an inactivation rate of 0.72. The synergistic effect was observed by increasing caffeine and UV light. Furthermore, the physic-chemical characteristics of the food matrix were not affected by the combination of both technologies. Therefore, these results suggest that this combination can be used in the food industry to effectively inactivate Salmonella enteritidis, without deteriorating product quality.

In this paper, we extend the KdVSKR equations in (1+1)-dimension and (2+1)-dimension to fractional KdVSKR equations with modified Riemann-Liouville derivative. The (2+1)-dimensional KdVSKR equation, which is a recent extension of (1+1)-dimensional KdVSKR equation, can model the resonances of solitons in shallow water. By means of the Hirota bilinear method, finite symmetry group method and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton-cnoidal interaction solution of the (1+1)-dimensional fractional KdVSKR equation has been derived for the first time. For the (2+1)-dimensional frac-tional KdVSKR equation, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. Impact of the fractional order on the shapes of these solutions has been illustrated by figures. Three-wave interaction solutions of fractional systems have not been reported in the existing references. The research idea in this paper can be applied to other fractional differential equations.

Primordial axion stars, hypothetical stars formed from axions, could play an essential role in forming galaxy halos. These stars could have originated in the early universe shortly after the Big Bang. We show that while “normal” axions coalesce into a gravitationally bound Bose-Einstein condensate, forming a dense object - an axion star, the ultralight axions could act as the initial seeds for galaxy halos.

The objective of this study was to investigate the impact of adding fermented herbal extracts (FHE) derived from mulberry leaf (Morus alba), Javanese turmeric (Curcuma xanthorrhiza), and fingerroot (Boesenbergia rotunda) to the diet of tiger shrimp (Penaeus monodon) on their growth, moulting performance, feed efficiency, and nutrient retention. The main feed used in this trial was a commercially manufactured pellet, then five different doses of FHE supplementation were used: 0 mg/kg feed (P0, control), 50 mg/kg feed (P1), 100 mg/kg feed (P2), 150 mg/kg feed (P3), and 200 mg/kg feed (P4). Weight gain, average daily gain, and length gain of shrimps fed P2 was significantly higher than that of those fed the control diet. Similar result was observed in moulting performance. The application of P2 showed superior results in enhancing the FE of cultured shrimp. Thus, the protein and energy retention of P. monodon was significantly better in P2 treatment groups. P0 had the lowest crude protein, while shrimp given P2 and P3 diets had the highest crude protein content of any treatment group. Based on the findings, it is recommended that the juvenile tiger shrimp diet contain 100 mg/kg of FHE for the best effects.

Betel quid (BQ) use disorder (BUD) is prevalent in many Asian countries, impacting approximately 600 million people. We conducted a randomized clinical trial to analyze the impact of MAOA genetic variations on the severity of BQ craving. This was measured using DSM-5 criteria and Yale-Brown Obsessive Compulsive Scale modified for betel-quid (Y-BOCS-BQ). Participants were grouped according to the severity of BUD and MAOA gene single nucleotide polymorphism (SNP) rs5953210 genotypes. Y-BOCS-BQ were assessed at baseline (week 0) and during follow-up at weeks 2, 4, 6, and 8. The AA genotype group showed significantly greater reductions in Y-BOCS-BQ at weeks 2 (p=0.0194), 4 (p=0.0078), 6 (p=0.0277), and 8 (p=0.0376) compared to the GG genotype group. Additionally, within the antidepressant group, the AA genotype showed significant reductions in Y-BOCS-BQ at weeks 2 (p=0.0313), 4 (p=0.0134), 6 (p=0.0061), and 8 (p=0.0241) compared to the GG genotype. Statistical analysis revealed a significant interaction between the treatment and placebo groups based on MAOA genotypes, with the AA genotype in the treatment group exhibiting a more pronounced decrease in Y-BOCS-BQ (p interaction

This paper introduces an innovative approach that enables automated and precise prediction of the steel's chemical composition based on the desired Jominy curve. The microstructure, and in fact the presence of martensite, is decisive for the hardness of the steel, so the study considered the occurrence of this phase at particular distances from the quenched-end of the Jominy sample. Steels for quenching and tempering and case hardening were investigated. With representative collected dataset of hardness values from quenched-end of Jominy specimen, microstructure and chemical composition of steels, the complex regression model was made using supervised artificial neural networks. The balance between cost and required hardenability can be achieved through optimizing the chemical composition of steel. This model of designing steel with required hardenability can be of great benefit in the mechanical engineering and manufacturing industry. The model is verified experimentally.

This research builds on the previously established Peak Density Thickness (PDT) concept for midlatitudes at Millstone Hill by examining its applicability at equatorial latitudes using data from the Jicamarca Incoherent Scatter Radar (ISR) in Lima, Peru. An 18-hour dataset was meticulously analyzed to capture the F2 layer's PDT parameter with high spatial resolution. This study aims to confirm the presence of the PDT phenomenon at equatorial latitudes, utilizing Jicamarca ISR and the co-located Digisonde station. The results indicate that the PDT parameter reaches its peak value around solar noon, consistent with observations at Millstone Hill and high latitudes. Additionally, the Nsumei et al. Vary-Chap topside model was employed to reconstruct the topside ionospheric profile, validating its utility across different latitudes. These findings suggest that incorporating the Peak Density Thickness χ into ionospheric models can enhance the accuracy of topside specifications derived from ground-based ionosonde measurements. This research highlights the significance of the PDT parameter in understanding ionospheric plasma dynamics and improving predictive models of ionospheric behavior.

Recent developments in the quantization of general relativity theory provide a new perspective on matter and even the whole universe. Already in 1922, Eddington suggested that a future quantum gravity theory had to be linked to the Planck length. This is today the main view among many working with quantum gravity. Recently, it has been demonstrated how the Planck length, the Planck time can be extracted from gravity observations with no knowledge of G, ħ or even c. Rooted in this, both general relativity theory and multiple other gravity theories can be quantized and linked to the Planck scale. A revelation from this is that matter seems to be ticking at the reduced Compton frequency, where each tick can be seen as one bit, and one bit corresponds to a Planck mass event. This new way of looking at gravity also can tell us considerably about what quantum gravity computers are and what they potentially can do. We will claim that all quantum gravity and quantum gravity computers are directly linked to the Planck scale and the Compton frequency in matter, something we will discuss in this paper. Quantum gravity computers, we will see, in many ways are nature’s own designed computers with enormous capacity to 3D “print” real time. Basically, we live inside a gigantic quantum gravity computer known as the Hubble sphere, and we even are quantum gravity computers. The observable universe is basically a quantum gravity computer that calculates approximately 10^104 bits per second (bps).

This study explores the application of data mining techniques in marketing strategies, highlighting their impact on customer segmentation, predictive analytics, and personalization. Data mining has emerged as a transformative tool for businesses seeking to enhance their marketing effectiveness by providing deep insights into customer behavior and preferences. Techniques such as clustering, predictive modeling, and personalization are examined for their roles in improving marketing outcomes. Clustering methods, including K-means and hierarchical clustering, enable businesses to categorize customers into meaningful segments, allowing for more targeted marketing efforts. Predictive analytics, utilizing models like decision trees and neural networks, offers the capability to forecast future customer behaviors and trends, thereby optimizing resource allocation and strategy planning. Personalization techniques, such as collaborative filtering and dynamic recommendations, enhance customer engagement by delivering tailored content and offers. Despite these advantages, the study also addresses the challenges associated with data mining, including data privacy concerns, data quality issues, and the shortage of skilled personnel. These challenges underscore the need for effective data management practices and ethical considerations in the application of data mining. Furthermore, the integration of emerging technologies like artificial intelligence and real-time analytics is discussed as a means to overcome existing obstacles and drive future advancements in marketing strategies. The findings underscore the significant role of data mining in revolutionizing marketing practices and highlight the ongoing need for adaptation and innovation in response to evolving market dynamics.

The success of near-infrared spectroscopy (NIRS) analysis hinges on the precision and robustness of the calibration model. Shallow learning (SL) algorithms like partial least squares discriminant analysis (PLS-DA) often fall short in capturing interrelationships between adjacent spectral variables, and the analysis results are easily affected by spectral noise, which dramatically limits the breadth and depth application of NIRS. Deep learning (DL) methods, with their capacity to discern intricate features from limited samples, are progressively integrated into NIRS. In this paper, two discriminant analysis problems including wheat kernels and Yali pears were used as examples, and several representative calibration models to research the robustness and effectiveness of the model. Additionally, this article proposed a near-infrared calibration model, which is based on gramian angular difference field and coordinate attention convolutional neural networks (G-CACNN). The research results show that, compared with SL, spectral preprocessing has a smaller impact on the analysis accuracy of consensus learning (CL) and DL, and the latter has the highest analysis accuracy in the modeling results of using the original spectrum. The accuracy of G-CACNN in two discrimination tasks is 98.48% and 99.39%, respectively. Finally, This research compared the performance of various models under noise to evaluate the robustness and noise resistance of the proposed method.

Background: The Victorian era in Great Britain was a historical period that brought about profound changes for humanity. The confluence of various factors fostered the development of numerous scientific disciplines. In the field of health sciences, Florence Nightingale played a central role. Following her training as a nurse and her role as superintendent during the Crimean War, she made decisive contributions to establishing a public health network. Methods: This is a retrospective historical heuristic and hermeneutic study analyzing documentation of Nightingale's contributions to public health from around 1890 to 1900. The historical method was used to collect, classify, and analyze primary and secondary sources relevant to the study's objectives. Results: Nightingale supported the development of the concept of “health at home” by training women to implement healthy measures that contributed to the well-being of families and communities. Through the training and development of a formal “Health Missioners program”, she provided the necessary guidance to improve the health of rural communities across the English countryside. Conclusion: The role of Health Missioners has persisted, as health visitors continue to visit homes in the United Kingdom. Therefore, the contribution of Florence Nightingale to public health is unquestionable. This study was not registered.

To date, deep-tech entrepreneurship and sustainable entrepreneurship are both attracting the interest of researchers. Indeed, deep-tech is being employed to address future sustainable challenges in the present. Nevertheless, the process of deep-tech startups is filled with distinct obstacles. These types of startups may necessitate more targeted sustainable entrepreneurial process and specialised knowledge compared to conventional technological startups or general sustainable entrepreneurial process. Currently, there are only publications discussing either a sustainable en-trepreneurial process or conventional technical startups. Therefore, the aim of this article is to in-vestigate the process of sustainable entrepreneurs as they transition from startup ventures to scaleup enterprises within the context of deep-tech industry. Based on previous sustainable entre-preneurial processes, a multiple case study was conducted within six deep-tech startups in order to find out the sustainable process pattern. A conceptual model of sustainable entrepreneurial process in deep-tech industry is established including five phases with six activities: (i) Sustainable idea definition; (ii) Sustainable opportunity recognition and evaluation; (iii) Venture launch; (iv.i) Sustainable products/ services development; (iv.ii) New sustainable enterprise financing; and (v) Sustainable enterprise scaleup. This process enables sustainable deep-tech entrepreneurs to necessarily have an overview of key entrepreneurial stages to navigate from the startup to scaleup process.

In Burkina Faso, there is lack of awareness of antibiotics use at community level. In this study, we generate information on the commonly used antibiotics along with the reasons for which they have been used, in rural Burkina Faso. The ‘drug bag’ method, was employed to collect information from 423 households, in the health district of Nanoro. Descriptive analyses were performed using R software version 4.2.1. The number of self-reported antibiotic use on a regular basis was estimated at 3401 of which amoxicillin was reported 367 times (10.8 %), oxytetracycline was reported 288 times (8.5 %), ampicillin, 245 times (7.2 %), metronidazole, 239 times (7 %), and norfloxacin 223 times (6.6 %). Among the health complaints for which amoxicillin was used, wounds accounted for 28.5% (88/309) and gastrointestinal disorders 17.1% (53/309). For oxytetracycline, gastrointestinal disorders accounted for 57.1% (121/212) and wounds 22.64% (48/212). The study highlights the use of antibiotics for a range of health problems within the community, as well as antibiotics that appeared to of importance in people’s life. Further research is essential to elucidating the rationalities and logic reasoning underlying such use of antibiotics.