Vopson and Lepadatu recently proposed the Second Law of Infodynamics. The law states that while total entropy increases, information entropy declines over time. They state that the law has applications over a wide range of disciplines, but they leave many key questions unanswered. This article analyzes and reformulates the law based on the thermocontextual interpretation (TCI). The TCI generalizes Hamiltonian mechanics by defining states and transitions thermocontextually, with respect to an ambient-temperature reference state. The TCI partitions energy into ambient heat, which is thermally random and unknowable, and exergy, which is knowable and usable. The TCI is further generalized here to account for a reference observer’s actual knowledge. This enables partitioning exergy into accessible exergy, which is known and accessible for use, and configurational energy, which is knowable but unknown and inaccessible. The TCI is firmly based on empirically validated postulates. The Second Law of thermodynamics and its information-based analogue, MaxEnt are logically derived corollaries. Another corollary is a reformulated Second Law of Infodynamics. It states that an external agent seeks to increase its access to exergy by narrowing its information gap with a potential exergy source. The principle is key to the origin of self-replicating chemicals and life.

Respiratory diseases are common in rabbits, but subclinical conditions can be challenging to diagnose and may cause respiratory problems during anesthesia. CT is the preferred method for diagnosing lung diseases, but anesthesia can alter lung volume and cause lung lobe collapse. In this study, seventeen healthy 5-month-old male New Zealand white rabbits underwent thoracic CT scans under different conditions. Rabbits were sedated with midazolam and butorphanol and scanned in a sphinx position they were then anesthetized with dexmedetomidine and ketamine and scanned again in sternal recumbency during spontaneous breathing. Lastly, apnea was induced using intermittent positive pressure ventilation (IPPV) for a final scan. Lung volume and density were measured using the 3D Slicer software, with thresholds set between -1050 and -100 Hounsfield Units (HU). Sedated animals had significantly higher total lung volume (69.39±10.04 cm³) than anesthetized (47.10±9.28 cm³) and anesthetized in apnea rabbits (48.60±7.40cm³). Mean lung attenuation during sedation was -611.26 HU (right) and -636.00 HU (left). After anesthesia induction, values increased to -552.75 HU (right) and -561.90 HU (left). Following apnea induction, attenuation slightly decreased to -569.40 HU (right) and -579.94 HU (left). The results indicate that sedation may be preferable for rabbit lung CT to minimize anesthesia-related changes.

A Berry geometrical phase is identified in a strongly metastable system containing dynamically responsive clathrate hydrate structures within a crystal-fluid material. High energy degeneracy in the associated chemistry produces local stability and false vacuum conditions that lead to non-extensive and non-additive contributions in the fundamental thermodynamic relation. Application of Ginzburg-Landau theory and the scaling laws reveals a coherence length and a penetration depth for a macro-scale dual superconductor. The coherence length determines non-extensive volume changes whilst its inverse gives the Higgs mass. The penetration depth determines the extent of QCD vacuum suppression whilst its inverse gives the vector boson mass together with indirect manifestation as non-additive hyperbolic curvature. Simultaneous emergence of the Ginzburg-Landau superconducting phase transition is consistent with gauge-invariant coupling of the scalar field to the Yang-Mills action in QCD. The discovery of an energy gap in the gradient energy term of the system Lagrangian is associated with a critical correlation length revealed in the transition from a gapped to a gapless superconducting state. Together with the emergence and absorption of the Higgs-like scalar field, a mechanism for describing a renormalized QCD mass gap arises.

This study investigates the time-resolved aerodynamics in the cavity regions of a full-scale, high-speed low-pressure turbine stage representative of geared turbofan engines. The turbine stage is tested in the von Karman Institute’s short-duration rotating facility at different purge rates (PR) injected through the upstream hub cavity. Spectra from the shroud and downstream hub cavity show perturbations linked to blade passing frequency and rotor speed. Asynchronous flow structures associated with ingress/egress mechanisms are observed in the rim seal of the purged cavity. At 0% PR, the ingress region extends to the entire rim seal, and pressure fluctuations are maximized. At 1% PR, the instability is suppressed and the cavity sealed. At 0.5%, the rim-seal instability exhibits multiple peaks in the spectra, each corresponding to a state of the instability. Kelvin-Helmholtz instabilities are identified as trigger mechanisms. A novel technique, based on the properties of the cross-power spectral density, is developed to determine speed and wavelength of the rotating structures, achieving higher precision than the commonly used cross-correlation method. Moreover, unlike the standard methodology, this approach allows to calculate the structure characteristics for all the instability states. Spectral analysis at the turbine outlet shows that rim-seal-induced instabilities propagate into regions occupied by secondary flows. A methodology is proposed to quantify the magnitude of the induced fluctuations, showing that the interaction with secondary flows amplifies the instability at the stage outlet.

Enterprise Systems (ES), including Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM), play a critical role in streamlining processes, integrating data, and enhancing decision-making across executive, managerial, and operational levels in organizations. These systems facilitate real-time information flow, improve coordination, and increase efficiency. This systematic review aims to identify the success factors and reasons for failure in the implementation of Enterprise Systems across various organizational levels, drawing from empirical research and case studies. A systematic search of databases such as Google Scholar, Web of Science, and Scopus was conducted. The review examined key factors influencing ES success, including top management support, user involvement, clear objectives, and change management. Failures were linked to misalignment with business goals, insufficient training, and poor communication. Studies were selected based on eligibility criteria, including publication date (within the last 20 years) and relevance to ES implementation. Out of the 64 studies reviewed, 76% focused on Small and Medium-sized Enterprises (SMEs), while 12% specifically addressed small businesses. The analysis revealed that 46% of the studies emphasized the role of ES in strategic planning at the executive level, 34% examined ES's impact on managerial performance in SMEs, and 20% explored the alignment of ES with business strategy. The review also found that on-premises solutions dominated ES implementation (67%), followed by cloud-based solutions (33%). Key success factors identified were organizational readiness, strategic alignment with business goals, and user engagement. Common failure causes included insufficient training (35%), lack of organizational readiness (28%), and poor change management (22%). This review provides insights into the critical success factors for ES implementation and common pitfalls. Findings emphasize the need for strategic alignment, comprehensive training, and stakeholder involvement at all organizational levels. These results offer a roadmap for organizations to optimize future ES implementations and ensure long-term sustainability through effective planning and change management.

Drought stress is a major issue in agriculture, as it is becoming more prevalent due to climate change and can reduce crop yields significantly. Low water amounts, particularly at the flowering stage, limit plants from undergoing typical growth and reproductive development, including gametogenesis, fertilization, and embryogenesis. Therefore, it is important that rice growers have a method of quickly determining whether or not their crops are undergoing drought stress to enact mitigation strategies. This study aims to use machine learning computer vision to accurately detect drought stress in plants. Before I developed models, I conducted data pre-processing on images of Setaria plants with varying water contents. Then, I built several machine learning models, including K-Nearest-Neighbors, Decision Tree, Logistic Regression, and ResNet 18. I then assessed the effectiveness of these models by calculating their accuracy scores. I found that K-Nearest-Neighbors, Decision Tree, and Logistic Regression models obtained 80.2%, 70.7%, and 75.9% accuracy scores, respectively, while ResNet18 obtained a very high accuracy of 97.3%. Therefore, these models can serve as a promising future solution for non-invasively detecting drought stress in rice plants, potentially saving crop producers millions of dollars in yield.

This article is dedicated to critically appraising the current knowledge and advancements in rediscovering a thematic religious and cultural route that traverses European continental territories, from the Baltic regions to Rome, known as Romea Strata. This spiritual, diverse, and interreligious project combines two approaches: the historical and heritage fashioners. The article assesses secondary sources that clarify a scientific background, discussing the historicity of Romea Strata’s direction from Tallinn to Rome, through European capitals and minor localities. Mobility in space motivated by culture and faith is a human phenomenon. Historical knowledge of this phenomenon constitutes an important theme for understanding the different potentials of intercultural dialogue, as a strong awareness of the heritage capabilities motivates communities to collaborate on a sustainable development project.

In this study, the asymmetric effect of oil and natural gas price shocks on the trade balance of 11 CESEE countries was estimated. These countries are net importers of oil and natural gas, and price shocks are often the cause of imbalances in trade. Quarterly data for the period 1994Q1 to 2023Q4 and nonlinear ARDL model were used. In the long run, a significant asymmetric effect due to the oil price shock on the trade balance of Bulgaria, Czechia, Latvia and Slovenia was found, as well as a significant asymmetric effect due to the natural gas price shock on the trade balance of Croatia. Also in the long run, a significant asymmetric effect due to wholesale prices on the trade balance of Romania, Bulgaria and Croatia was found as well as a significant asymmetric effect due to industrial production on the trade balance of Croatia, Czechia and Latvia was found, in addition to a significant asymmetric effect due to the exchange rate on the trade balance of Czechia, Poland and Romania.

Objective : Children < 15 years old are thought to be the most vulnerable group to contracting the infection than adults due to their immature or developing immunity. We investigated whether index patient child leprosy are associated with parental education, parental unemployment, parental income, household crowding, inadequate ventilation household contacts, neighbours contact and nutritional deficiency in Dili, Liquica, Manatuto, Baucau, RAEOA. Methods: We designed matched case-control study. Cases were fathers of children with leprosy under 15 years old while controls were non random sample of children without leprosy who live in the same household and neighbourhood with child leprosy < 15 years who have the same age and gender with child leprosy. The case-to-control ratio was 1:2. We identified the factors that significantly differed between the cases and controls in a multivariable binary logistic regression analysis and reported the odds ratio (OR) and 95% confidence interval (CI)Results: We found similar demographic among the 40 cases and 80 controls. The research results indicated that out of the 8 variables examined, 4 variables household contacts, household crowding, inadequate ventilation, and nutritional deficiency were significant risk factors (P value < 0.005). In a multivariate analysis, household contact was identified as a significant factor in the occurrence of leprosy in children under 15 years old (P value = 0.003, AOR = 3.788, 95% CI: 1.593–9.003)Conclusion: Considering that household contacts consist of a recognizable group of individuals under 15 years old with a high risk of disease, as they live in close proximity to a source of infection, it is essential to focus on education, routine screening, and the application of chemoprophylactic protocols towards leprosy prevention among household contacts, especially blood relatives.

Interest in leadership skills and leadership development is burgeoning both in academic circles and business organizations. Leadership research has produced a large number of leadership models. The distinctions between leadership and management, skills required for leadership, and methods of leadership development are ongoing areas of study. An attempt is made to provide an overarching theory that showcases some crucial distinctions. The proposed theory holds that ‘managing’ is about improving a situation, and ‘leading’ is about improving a situation by stretching oneself either by exploiting unique personal characteristics or by exploring underdeveloped skills and/ or enabling others and organizations to do the same. Thus, leadership is an act of self-expansion, and everyone can lead, including followers. Leadership development requires a series of acts of leading and learning, leading to leadership positions in a Darwinian process. Thus, at the heart of leadership is experimentation, and hence, it can be rightly called the art of management. What leaders do successfully today becomes management science tomorrow. The ever-growing list of leadership skills and leadership theories with more prosocial views is evidence of leadership in theory and practice. We also propose holistic leadership as a new type of leadership.

Methylene blue is a cationic organic dye found in wastewater, groundwater, and surface water, due to industrial release in the environment. This emerging pollutant is very persistent and, depending on the doses, can harm human and environmental health. In this work, a Surface Plasmon Resonance Biosensor using a BK7 prism with a coating of 3 nm chromium and 50 nm of gold in the Kretschmann configuration was developed for the detection of methylene blue, using for the first time, laccases immobilized on a gold surface as bio-receptors for this organic dye. The enzyme immobilization through carbodiimide bonds, using EDC/NHS crosslinkers, and allowed to analyze samples with minimal preparation. The method was validated, achieving a LOD of 4.61 mg L-1 and LOQ of 15.37 mg L-1, a working range from 0-100 mg L-1, and a R2=0.9614 in a real-time analysis. A sample of rainwater spiked with methylene blue was analyzed, and a recovery of 122.46 ± 4.41% was obtained.

In the rapidly evolving field of natural language processing (NLP), the processing of the Chinese language, with its unique complexities, presents significant challenges, especially in the context of Large Language Models (LLMs) like LLaMA2. These challenges are further exacerbated by the presence of non-standardized text prevalent across digital Chinese content. To address these challenges, this paper proposes a novel hybrid approach that seamlessly integrates deep contextual embeddings with Convolutional Neural Networks (CNNs) to enhance the processing of standardized Chinese text. Our approach involves a multi-stage process wherein deep contextual embeddings are first utilized to capture the nuanced semantic relationships within text. Following this, CNNs are employed to identify and exploit structural and syntactic patterns, facilitating a comprehensive understanding of the text. This hybrid model significantly improves LLaMA2’s efficiency and accuracy across various Chinese text processing tasks by ensuring that both semantic depth and structural nuances are accurately captured. The effectiveness of our model is demonstrated through rigorous testing across several benchmarks, showcasing its superiority in processing Chinese text with enhanced accuracy and speed. This research not only contributes to the advancement of text processing capabilities of LLMs but also opens new avenues for their application in tasks such as automated translation and sentiment analysis.

Wasp venom allergy can trigger severe allergic reactions, and predicting these acute responses remains challenging. This study evaluates the utility of immune system indexes, particularly the eosinophil-basophil/lymphocyte (EBLR) and eosinophil-basophil-platelet/lymphocyte (EBP/L) ratios, in assessing the severity of allergic reactions in patients with wasp venom allergy. A total of 61 patients with confirmed wasp venom allergy were categorized according to the Mueller scale, which classifies the severity of allergic reactions. Blood samples were analyzed for total and specific IgE levels, alongside a range of hematological and biochemical parameters. The study found significant differences in the EBLR and EBP/L indexes between patients with mild (Mueller I-II) and severe (Mueller III-IV) allergic reactions, with higher values indicating more severe responses. However, no significant differences were observed in other immune indexes, such as PLR, NLR, SII, and SIRI, or in additional blood parameters. These findings suggest that the EBLR and EBP/L ratios may serve as useful markers for predicting the severity of allergic re-actions in patients with wasp venom allergy. This is the first study to establish such a link, alt-hough further research with larger cohorts is necessary to confirm these results and their poten-tial application in clinical settings.

Reviewed the research progress of Newton’s iterative methods for nonlinear equation. Convergence with second order, third order, fourth order, fifth order, sixth order, seventh order, eighth order and ninth order Newton’s iterative methods are given in turn, and the efficiency index of these iterative methods are analyzed. Numerical experiments show that the convergence process of the three Newton iterative methods, and the results indicate that the convergence of the higher-order Newton’s method can be well demonstrated only when the initial point is close to the root.

For the first time porous tungsten coatings were obtained by vacuum annealing of coatings consisting of both lead solution in β-W and a mixture of Pb solution in β-W and pure lead. Electron-microscopic studies of the obtained coatings before and after vacuum annealing at 800 оС for 1 hour and 6 hours were carried out. The formation of a new phase of tungsten with an octa-lattice and parameter a = 0.4878±0.0005 nm was recorded.

Background: This study evaluates Endoscopic Sinusectomy procedures performed by young and experienced surgeons to compare outcomes achieved by young surgeons to those obtained by experienced surgeons. Methods: From a prospectively maintained database, patients with chronic non recurrent pilonidal disease who underwent Endoscopic Sinusectomy since 1 September 2011 to 31 December 2021, were enrolled. After the propensity score analysis, 200 patients were involved and divided in the group of procedures performed by young surgeons and the group performed by experienced surgeons. Results: About recurrence rate at 1-year follow up (7% vs. 10%, p=0.45) and 5-years follow-up (12.5% vs. 17.5%, p=0.53) and about time off from work (3.54±1.65 vs. 3.61±1.61, p=0.78) no significant results were found. About operative time (30.44±5.57 vs. 43.43±3.83, p=0.004), infection rate (4% vs. 14%, p = 0.013), time to healing of wound (27.89±11.06 vs. 42.22±13.63, p=0.002) and incomplete healing of wound rate (3% vs. 11%, p=0.027) statistically significant differences were found. The multivariate analysis demonstrated that being young surgeons influences the above-mentioned significant results and that the mean distance between lateral orifice and midline impacts on the recurrence rate at 1- and 5-years follow-up for both experienced surgeons’ (p=0.001 and p=0.009) and young surgeons’ procedures (p=0.001 and p=0.003). Conclusions: The recurrence rate doesn’t increase during the training but an adequate training path to perform endoscopic technique is need. A call to perform high-quality randomized controlled studies for establishing how many surgeries are required to be proficient and to outline the ideal endoscopic technique training path.

Bacterial infection of the lower respiratory tract frequently occurs in mechanically ventilated pa-tients and may develop into life-threatening conditions. Yet existing diagnostic methods have moderate sensitivity and specificity, which results in the overuse of broad-spectrum antibiotics administrated prophylactically. This study aims to evaluate the suitability of volatile bacterial me-tabolites for breath-based test diagnosing Ventilation-Associated Pneumonia (VAP). The in vitro experiments with pathogenic microorganisms most prevalent in VAP patients (i.e., Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa) were performed to identify bacteria-derived metabolites using specially designed cultivation system enabling headspace sam-pling for GC-MS analysis. Thirty-nine compounds were found to be significantly metabolized by tested species and, therefore, selected for monitoring in the exhaled breath of critically ill, me-chanically ventilated (MV) patients. The emission of volatiles from medical respiratory devices was investigated to estimate the risk of spoiling breath results with exogenous pollutants. Bacterial metabolites were then evaluated to differentiate VAP patients from non-infected MV controls using receiver operating characteristic (ROC) analysis, with AUC, sensitivity, and specificity calculated. Nine bacterial metabolites that passed verification through a non-parametric ANOVA test for significance and LASSO penalization were identified as key discriminators between VAP and non-VAP patients. The diagnostic model achieved an AUC of 0.893, with sensitivity and specificity values of 87% and 82.4%, respectively, being competitive with traditional methods. Further vali-dation could solidify its clinical utility in critical care settings.

Object: Due to the fact that glioma surgery requires manipulation of the brain parenchyma and the expression of inflammatory mediators, there is often a possibility of central nervous system (CNS) infection occurring after surgery. Previous studies on CNS infections related to neurosurgery have uniformly explored the risk factors for CNS infections in all neurosurgery surgeries that require craniotomy, but have not explored the risk factors and clinical characteristics of CNS infections after glioma resection. Methods: We included patients who underwent glioma resection from January 2015 to March 2023, systematically recorded population characteristics, clinical, surgical, laboratory and survival data, analyzed high-risk factors for postoperative CNS infections, summarized cerebrospinal fluid characteristics, antibiotic use, and explored whether CNS infections affects the long-term prognosis of glioma patients after surgery. Results:All 337 patients underwent glioma resection, and 61 patients (18.1%) developed CNS infections after surgery. Ventricle Opening, post-op other systemic infections, post-op maximum cavity diameter, and peripheral blood Monocyte% are independent risk factors for postoperative CNS infections. The median protein content in cerebrospinal fluid of patients with CNS infections is 1.73g/L ([IQR] 1.03-3.06), the median glucose content is 2.7mmol/L ([IQR] 1.90-3.70), and the median WBC is 1478×106cells/L ([IQR] 467-4204.25×106), with a median percentage of multinucleated cells of 84.1% ([IQR] 74.55% -90.83%). Meropenem and Vancomycin are the most commonly used antibiotics, with an average usage time of 7.79 days and 8.41 days, respectively. Survival analysis suggests that the occurrence of CNS infections does not affect the long-term prognosis of glioma patients after surgery. Conclusions: This study separately explored the risk factors for CNS infections in patients with glioma after surgery, instead of all diseases which need craniotomy，and summarized their cerebrospinal fluid characteristics and antibiotic use. Although CNS infection is only one of the possible complications during the treatment of gliomas, we believe that this will make a certain contribution to neurosurgeons' individualized prevention, diagnosis, and treatment of patients in the diagnosis and treatment of gliomas.

Purpose: Report of a novel genetic variant in a family with an unusual clinical presentation of posterior polymorphous corneal dystrophy (PPCD). Methods: Documentation of clinical findings of the anterior and posterior segments using slit lamp analysis and imaging tools (Scheimpflug imaging, optical coherence tomography), along with documentation of best spectacle corrected visual acuity (BSCVA; LogMAR). Next-generation sequencing (NGS) of the genes of interest was performed by the IDTxGen® sytem (Inherited Disease Panel v1.0 and sequencing on an Illumina NextSeq® 500) based on DNA extracted from peripheral blood lymphocytes. Data analysis was performed using the SeqNext module of the SEQUENCE Pilot software (version 5.1.0, JSI Medical Systems). A histological examination of four corneas in both patients (father and son) was carried out by hematoxylin-eosin (HE) staining. Results: A novel heterozygous variant in the ZEB1 gene was identified in a 41-year-old man and his 13-year-old son. The 2-bp duplication in exon 8 results in a frameshift and a premature stop codon (p.(Asp883Argfs*39)), predicted to result in nonsense-mediated decay (NMD) and to lead to functional impairment of the ZEB1 protein. The variant was classified as likely pathogenic applying the American College of Medical Genetics and Genomics (ACMG) criteria. The variant is located in the penultimate 3´base pairs of the ZEB1 gene. The C-terminus of the ZEB1 gene encodes the C2H2-type protein domains of the ZEB1 zinc finger transcription factor protein which are relevant in epithelial-mesenchymal transition (EMT) by mediating the transition between cell lineages. The patients presented with an unusual symmetrical crescent-shaped bullous edema with a temporal focus with retrocorneal snail-track-like changes. Histological examination of all hematoxylin-eosin (HE) stained samples revealed a peripheral multilayer of endothelial cells adjacent to the trabecular meshwork (TMW), along with a central reduction of corneal endothelial cells and a pathological thickening of Descemet's membrane of up to 18.7 m. Conclusions: We report a novel variant of dominantly inherited PPCD3. Pathological production of a protein with an effect on the transition between cell lineages could explain the pathogenic epithelial transformation of the corneal endothelium, characterized by snail-track-like retrocorneal changes with a symmetric temporal crescent-shaped corneal edema.

We propose the Ramsey approach for the analysis of behavior of isolated mechanical systems containing interacting particles. The total momentum of the system in the frame of the center of masses is zero. The mechanical system is described by the Ramsey, bi-colored, complete graph. Vectors of momenta of the particles pi serve as the vertices of the graph. We start from the graph representing the system in the frame of the center of masses, the momenta of the particles in this system are pcmi. If (pcmi(t)∙pcmj(t))≥0 is true, vectors of momenta of the particles numbered i and j are connected with the red link; if (pcmi(t)∙pcmj(t))&lt;0 takes place, the vectors of momenta are connected with the green link. Thus, the complete, bi-colored graph emerges. Consider the isolated system built of six interacting particles. According to the Ramsey Theorem, the graph inevitably comprises at least one monochromatic triangle. The coloring procedure is invariant relatively rotations/translations of frames; thus, the graph representing the system contains at least one monochromatic triangle in any of frames emerging by rotation/translation of the original frame. This gives rise to the novel kind of a mechanical invariant. Similar coloring is introduced for the angular momenta of the particles. However, the coloring procedure is sensitive to Galilean/Lorenz transformations. Extensions of the suggested approach are discussed.

The chemical profiles of young and mature wines produced from three grape varieties Merlot, Mavrud and Sauvignon blanc were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy and advanced statistical methods. Moreover, grape ales, a hybrid of beer and wine, were subjected to analysis in order to facilitate a comparison of their composition with that of traditional wines. A total of 37 compounds were identified and quantified, and orthogonal partial least squares discriminant analysis (OPLS-DA) models were employed to distinguish the chemical profiles of young and mature wines, as well as those of grape ales. The findings demonstrate that the fermentation and aging processes result in the formation of distinctive chemical signatures in wines, with key compounds such as shikimic acid and fructose contributing to this differentiation. The identified compounds comprise seven alcohols (2,3-butanediol, glycerol, isobutanol, isopentanol, myo-inositol, 1-propanol, 2-phenylethanol), six organic acids (galacturonic, citric, lactic, malic, shikimic, succinic), three amino acids (alanine, proline, tyrosine), four sugars (arabinose, fructose, galactose), coutaric acid and acetoin. The levels of these 22 components enabled the successful differentiation of young and mature wines among the three grape varieties. These results highlight significant chemical differences between grape ales and wines, thereby underscoring the potential of grape ales as an innovative fermented beverage.

One widely used method to predict concrete strength development based on temperature variations during curing is the equivalent maturity time (te) method. This method uses the activation energy (Ea) as its key parameter, which reflects the cement’s sensitivity to temperature. However, research shows that the Ea value varies depending on factors such as cement type, water-cement ratio, temperature, and additives. The permanent subject of discussion is the question of what value of the Ea parameter should be assumed. In this paper, a new approach is proposed by using a neural network analysis method to develop a strength-temperature-time history model. It was assumed that the ANN-fc% model would have 4 inputs including hydration heat (Q), activation energy (Ea), temperature (T) and time (t). A data set was collected and research was carried out on mortars using: 6 cements, curing temperatures 5-35°C, strength within 90 days. The results showed that the ANN analysis method allows for estimating the relative compressive strength with sufficient accuracy. Input nodes analysis showed that Q influences early strength gain, while Ea affects later strength development. The method of using the ANN model to calculate strength depending on the temperature change during maturation was shown.

The effects of neighboring transitions (ENT) on electromagnetically induced transparency (EIT), electromagnetically induced absorption (EIA), and the conversion between EIA and EIT in a degenerate multi-level system of 87Rb atoms were studied in terms of the angle (θ) between the polarization axes of the coupling and probe beams. The predicted critical values of θ, in which EIT transitioned to EIA, were consistent with the experimental values. In this work these results were systematically confirmed using the calculated spectra by varying the frequency spacings in the excited state of 87Rb via a factor called the ratio. We observed that when the ratio was less than 0.1, the critical angle θc was inverted. This may be attributed to the interplay between the strengths of the EIA and EIT as the ENT varied. We also discovered that by modifying the frequency spacings in the excited state of 87Rb, it becomes feasible to predict ENT and the interplay between EIT and EIA in alkali-metal atoms.

We study whether the center of relativistic energy (CRE) is always constant in an isolated frame of reference (IFR). First, we assume that two objects in a moving isolated frame of reference (MIFR) move parallel to and very close to a coordinate axis from opposite directions and with equal speed. Here each length in the direction of travel of the objects is much longer than that perpendicular to the direction of travel of them, and moreover the latter is negligibly extremely short. Hence, the location of the CRE (LCRE) of the objects is very close to the coordinate axis in initial condition. When they become perfectly symmetric with respect to the coordinate axis, the forces perpendicular to the direction of travel of the objects are applied to each CRE and thereby a perfectly inelastic collision between them occurs on the coordinate axis. The combined object (CO) resulting from the perfectly inelastic collision begins to rotate because each momentum of the objects before the combination between them acts like the moment of force on the CO. For simplicity, we examine the energy distribution of the CO when it becomes perpendicular to the coordinate axis due rotation. The magnitude of velocity of each minute portion (MP) symmetrical with respect to the coordinate axis are different depending on whether the direction of each rotational velocity is the same or opposite to the direction of travel of the MIFR. Then the energy of each MP is not the same. As a result, the LCRE of the CO moves to the direction perpendicular to the coordinate axis, and its LCRE becomes far from the coordinate axis since the length in such direction is long enough. Therefore, we conclude that the LCRE in the MIFR is not necessarily invariant. Second, we suppose a process in which a force causes a negative acceleration on a moving object (MO) and thereafter the MO eventually comes to rest. What is considered here is the LCRE when the MO comes to rest. We pay attention to the position of the force applied to the MO because the transmission time of force (TTF) inside the MO may vary depending on the position of the MO where the force is applied. As a result, we find that the position at which the MO comes to rest differs depending on the TTF inside the MO. Therefore, we conclude that the LCRE in an IFR differs depending on the position of the MO where the force is applied, in other words, it in an IFR is not necessarily uniquely determined.

After the launch of a high-resolution remote sensing satellite, representative spatial quality estimators (RER, FWHM, MTF50, MTFA) are measured from images taken of ground Edge targets. In this work, the best spatial quality estimator is proposed by quantitatively comparing and analyzing the precision between Relative Edge Response (RER), Full Width at Half Maximum (FWHM), MTF value at Nyquist frequency (MTF50), and MTF Area between 0 and Nyquist frequency (MTFA). While the basic method for the measurement of spatial quality estimators on Edge targets is already well established, this work summarizes and explains the uncertain factors and problems in the measurement procedure that affect the accuracy and precision of spatial quality estimators. It also considers how to improve the precision of spatial quality estimators during the measurement procedure. The contents and results of this work were discussed by various satellite development organizations in the Geo-Spatial Working Group within CEOS WGCV IVOS from 2012 to 2019, and the Edge target Spatial quality Measurement Python code (ESMP) was developed in 2019 to reflect the findings of this workshop. Using 483 Edge targets from worldwide images taken by KOMPSAT-3A, which has been in operation since 2017, the results obtained via ESMP show that the precision of RER, FWHM, and MTFA are approximately three to four times higher than that of MTF50 when comparing the Coefficient of Variance (CV) statistics.

(1) Background: The androgen receptor (AR) is critical for mediating the effects of androgens. The polymorphic CAGn locus in exon 1 of the AR gene is associated with several diseases, including spinal and bulbar muscular atrophy (SBMA), prostate cancer, and male infertility. This study evaluated the CAGn locus in 9,000 infertile Russian men and 286 fertile men (control group); (2) Methods: The CAGn locus was analyzed using the polymorphism of lengths of amplified fragments method; (3) Results: In the infertile cohort, CAG repeats ranged from 6 to 46, with a unimodal distribution. The number of CAG repeats in infertile and fertile men was 22.15 ± 0.93 and 22.02 ± 1.36, respectively. In infertile men, variants with 16 to 29 repeats were present in 97% of alleles. A complete mutation (≥42 CAG repeats) was found in three patients, while three others had 39-41 repeats. The incidence of SBMA was 1: 3,000 infertile men. Significant differences (p&lt;0.05) were observed between infertile and fertile men in alleles with 21, 24 and 25 repeats; (4) Conclusions: This study revealed certain differences in the CAGn polymorphic locus of the AR gene in Russian infertile and fertile men, and determined the frequency of SBMA in infertile patients.

We have recently shown that the sphere-in-contact model can be used as an educational and research tool in various contexts, such as the visualization of carbon structures (e.g. graphene, carbon nanotubes, carbon nanocones and graphite), heterogeneous catalysts, metal nanoparticles and organic molecules. In this communication we present how it can be used to model the adsorbate structure of a monoatomic element on the hexagonal close-packed surface of the metal. We have used atoms of varying radius to represent the metal surface atoms and the adsorbate atoms. The study reveals that many surface symmetries are possible for a fixed adsorbate coverage by the movement of the adsorbate atoms in response to surface adsorbate-adsorbate repulsions. The movement of the particles (e.g. particle diffusion) can be seen directly in the model and this is caused by the user intervention. This has great educational but also research value as one can directly see how the adsorbate atoms reorder on the surface of a metal. We believe that this model will be useful in the rational design of catalytic materials and materials coatings with new technological applications.

Manganese dioxide (MnO2) has drawn attention as a sensitizer to be incorporated in graphene-based chemoresistive sensors thanks to its promising properties. In this regard, a rGO@MnO2 sensing material was prepared and deposited on two different substrates (Silicon and Kapton). These sensors were exposed to different dilutions of NO2 under dry and humid conditions at room temperature. Other gases or vapours such as NH3, CO, ethanol and H2 were also tested. FESEM, HRTEM, RAMAN and XRD were used to characterize the prepared sensors. The experimental results showed that the incorporation of MnO2 in the rGO material enhanced its response towards NO2. Moreover, this material showed also very good responses toward NH3 both under dry and humid conditions and showed no cross-responsiveness towards other toxic gases.

In the era of deepfakes and AI-generated content, digital image manipulation poses significant challenges to image authenticity, creating doubts about the credibility of image. Traditional image forensic techniques often struggle to detect sophisticated tampering, and passive detection approaches are reactive, verifying authenticity only after counterfeiting occurs. In this paper, we propose a novel full resolution Secure Learned Image Codec (SLIC) designed to proactively prevent image manipulation by creating self-destructive artifacts upon re-compression. Once a sensitive image is encoded using SLIC, any subsequent re-compression or editing attempts will result in visually severe distortions, making the image’s tampering immediately evident. Because the content of a SLIC image is either original or visually damaged after tampering, images encoded with this secure codec hold greater credibility. SLIC leverages adversarial training to fine-tune a learned image codec that introduces out-of-distribution perturbations, ensuring that the first compressed image retains high quality while subsequent re-compressions degrade drastically. We analyze and compare the adversarial effects of various perceptual quality metrics combined with different learned codec. Our experiments demonstrate that SLIC holds significant promise as a proactive defense strategy against image manipulation, offering a new approach to enhancing image credibility and authenticity in a media landscape increasingly dominated by AI-driven forgeries.

Background: In recent years, undernutrition has remained a significant public health issue in Tu-nisia, increasing the risk of illness and mortality in young children. Therefore, this study aims to analyse the prevalence and factors contributing to undernutrition among Tunisian children aged 0-23 months; Methods: The study included 3265 children aged 0-23 months from the 2011-2023 Tunisia Multiple Indicator Cluster Surveys (MICS). Trends and logistic regression analyses were used to determine the prevalence and predictors of undernutrition; Results: The prevalence of stunting, wasting, and underweight in infants and children aged 0-23 months has increased by 3.3%, 0.5%, and 2.1%, respectively. Stunting and underweight were more common among infants aged 0-5 months (11.8% for stunting, 8.9% for underweight, p < 0.01), and first-time mothers (8.3% for stunting, 4.1% for underweight, p < 0.01). In 2023, compared to 2011, the odds of stunt-ing, wasting, and being underweight have increased by 22%, 16%, and 70% respectively. Infants aged 0-5 months had higher odds of undernutrition in all three indices. Children of obese or overweight mothers, and those who started breastfeeding late, were more likely to be stunted. Boys had significantly higher odds of wasting and underweight. Small birth weight, and dura-tion of breastfeeding > 12months had significantly higher odds of being underweight; Conclu-sions: This study shows that infants aged 0-5 months, first-time mothers, boys, and children from poor households in Tunisia are at a higher odd of undernutrition. To address the growing issue of undernutrition in Tunisian children, enhancing maternal and child health and nutrition ser-vices, improve parental education, and implement community-based programs that provide breastfeeding and nutritional education to infants born to new mothers and mothers with high/low BMI is recommended.

The corrugation of the interfaces of the cross-section of hollow core fibers based on the inhibited coupling waveguiding mechanism is modeled and the impact on propagation loss is analyzed. The proposed model is based on a combined use of coupled mode theory and azimuthal decomposition. It shows that such transverse roughness causes coupling between the core modes and the dielectric modes of the cladding and consequently an increase of the fiber loss. The model is validated by comparing theoretical and numerical results obtained by applying both deterministic and stochastic corrugations to tube lattice and nested fibers. Scaling laws and impact of fiber parameters are discussed. The model shows that the loss increase is not directly correlated to the root mean square of the stochastic roughness, but only to the value of the power spectral density in specific spatial frequency ranges.

With increased life expectancy and improved modern lifestyles, there has been a growing concern for health, including the prevention of disease and the improvement of physical appearance. Consumers are increasingly aware of the benefits of using natural ingredients in healthcare products and at the same time are concerned about the challenges of sustainability. In this sense, the use of marine bioactive compounds as cosmetic ingredients and in food supplements has become increasingly popular due to the benefits derived from their various properties. However, some of these compounds have limited use, mainly due to their low stability and poor aqueous solubility, and solutions need to be developed to overcome these limitations. In this sense, the use of lipid nanoparticles, such as solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC), has been explored as these carriers show ability to protect and enhance the absorption of molecules. Several studies have demonstrated the efficacy of encapsulating these compounds and incorporating them into cosmetics and food supplements. However, there is still no global legislation and safety concerns have been raised. Further clinical studies in animals and humans are needed to clarify safety issues.

Fecal contamination is a common cause of impairment of surface waters. In monitoring studies, it usually is assessed by measuring concentrations of fecal indicator bacteria such as Escherichia coli (E. coli), a common monitoring target in freshwater systems. In this study, we assess the advantages and disadvantages of two common methods for monitoring E. coli concentrations at freshwater beaches: Colilert-18®, with a turnaround time of ca. 18 h, and real-time quantitative PCR (qPCR), with a turnaround time of ca. 3–4 h. Based on data comprising 3081 pairs of Colilert-18 and qPCR estimates of E. coli concentrations in split samples from Michigan’s annual beach monitoring program in 2019 and 2020, we found that qPCR monitoring detected a high percentage of exceedances of the state’s water quality standard for E. coli contamination that went undetected on the day of sampling with Colilert-18 monitoring, because qPCR concentration estimates were available on the day of sampling but Colilert-18 estimates were not. However, Colilert-18 data were more useful than qPCR data for statistical comparison of contamination levels at different beaches, probably in part because Colilert-18 data showed a much lower percentage of censored concentration estimates (estimates outside the range of quantification).

This study evaluates groundwater quality in the Nakivale sub-catchment, focusing on the inter-play of anthropogenic and geogenic influences. Hydrochemical analysis of 19 groundwater sam-ples revealed that 90% comply with World Health Organization drinking water standards, alt-hough localized contamination concerns were noted, particularly with total iron, nitrate and magnesium. Groundwater quality index indicated that over 90% of the samples fall within good to excellent quality categories. Alignment of nitrate levels with elevated chloride-bromide ratios suggest human impacts, likely from agricultural runoff and wastewater disposal. The irrigation groundwater quality assessment showed that 94% of samples possess low sodium, and medium to high salinity hazards, which could threaten crop productivity due to increasing osmotic stress. Vulnerability assessments indicated low contamination risks, attributed to overlying impermeable geological features, steeply sloping landscape, slow groundwater recharge, high depth to aquifer and clayey soil cover. The findings underscore the necessity for conjunctive management of water resources, incorporating strategies such as enhanced monitoring of groundwater quality, public education on sustainable practices, and protective measures for recharge zones. By addressing these concerns, the study aims to safeguard groundwater resources for both domestic and agri-cultural purposes, ensuring long-term sustainability in the region.

The article discusses the formation of local electric energy systems (LEES) based on renewable energy sources (RSE) as balancing groups in the electric power system (EPS). These systems can function autonomously, providing electricity even in extreme conditions. LEES incorporate small hydroelectric, photovoltaic, and wind power plants, whose output is unstable due to varying natural conditions. To address this, energy storage systems are included to ensure stability and balance. LEES may vary significantly in terms of reliability, power losses, and quality, making it essential to choose the optimal configuration. Optimizing power supply by focusing on individual indicators is discouraged, as it may negatively affect others. To evaluate LEES performance, an integral indicator has been developed, combining the theory of Markov processes and similarity. This indicator compares actual performance with an "ideal" standard, simplifying the assessment of complex systems. It allows comparison of different transmission and distribution options without needing to evaluate all technical and economic details. The proposed integral indicator effectively reflects real operating conditions and assesses the efficiency, quality, and optimality of power supply, while remaining adaptable to partial indicators.

The purpose of this article is to study a proposal for image processing and machine learning techniques to detect the pest Aleurothrixus floccosus in citrus in the area of Pedregal de Arequipa, Peru. Thus, in the collection of images a type of simple random sampling is adopted for the decrease of the bias in different citrus trees alternating and extracting leaves from the plantation also applying image processing techniques for noise reduction and edge smoothing, segmentation for the detection of the target and using machine learning algorithms that aims to perform the classification of the images, a methodology for the detection of the white fly or Aleurothrixus floccosus is achieved. It is necessary to understand that in the development of the article, it was possible to identify three stages of the pest in the plant, these being the presence of yellow areas, leaf rolling, and secretion of melase, likewise in the process it was possible to obtain a sample of 1200 images.

Housing is the most regulated type of building. Standards significantly influence the design and construction quality, often making universal design more expensive and challenging to implement. This study aims to review current Spanish regulations on accessibility in the housing sector, to promote non-discriminatory and independent access, while ensuring the safety of each resident. The research is exploratory and qualitative, involving a systematic bibliographic review through an exhaustive search of regulations in force until December 2023. In Spain, there are three laws (from 1999, 1960 and 2022), three decrees (from 2006, 2013 and 2015) and a national plan from the regulatory framework. The main regulation, the Technical Building Code, outlines the accessibility, safety and habitability requirements that buildings must adhere to. The most recent is Law 6/2022 on Cognitive Accessibility. Spain has robust legislation with innovative approaches and ambitious goals. However, there is a lack of societal awareness that housing is a fundamental right and that the regulations must be upheld. Several proposals for improvement have been made. These suggested changes address the specific challenges of each region and promote more inclusive and adaptable projects for all people from the early stages of design.

Angola has an enormous agricultural potential, but the challenge remains how the country can transform potential into real growth. This study is designed to analyze the impact of the agricultural sector on economic growth in Angola and suggest recommendations for a better policy framework of the agricultural sector for a structural growth of the economy. Annual time-series data from 1993 to 2022 were used. The ARDL and EC model were applied to analyze both long and short-term relationships, as well as different statistical and econometric tests were used to examine the significance of the input data and model results, including various diagnostic tests and the Granger causality test. The study findings show stronger evidence of a long-run relationship between the dependent and independent variables than in the short run. Short run results show to be statistically insignificant. Agricultural value added shows the best reaction in all lags involved, indicating that economic growth would, caeteris paribus, respond positively to improvement in agricultural performance in Angola, although delayed by 3 years. Agricultural value-added development would improve both the contribution of agricultural employment and agricultural exports towards economic growth, as well contribute to a better rural development in Angola.

The Balanced Scorecard (BSC) is a widely recognized strategic performance metric that has been extensively studied in large corporations but remains underexplored in the context of Small and Medium-sized Enterprises (SMEs). Understanding the effectiveness of BSC in aligning performance metrics with strategic goals and enhancing performance management in SMEs is critical for fostering growth and competitive advantage. This systematic review aims to evaluate the effectiveness of the Balanced Scorecard in measuring performance and strategy execution within SMEs, particularly focusing on financial and non-financial outcomes such as employee motivation, customer satisfaction, and business sustainability. A systematic review was conducted following the PRISMA framework, incorporating 136 studies sourced from Google Scholar, Web of Science, and SCOPUS. Eligibility criteria focused on publications from the last ten years that address the implementation of BSC in SMEs. Quantitative, qualitative, and mixed-method studies were included, with 49.63% of studies using quantitative methods, 26.67% qualitative, and 23.70% mixed-methods. Risk of bias was assessed using the Chrohane tool, revealing high risks in 90 studies due to incomplete outcome data and selective reporting. The review found that 74% of studies adopted a holistic approach by focusing on all four BSC perspectives (Financial, Customer, Internal Processes, and Learning and Growth). ROI emerged as the most frequently discussed key performance indicator, addressed in 36.84% of publications, while customer satisfaction and employee engagement were covered in 26.32% each. Geographic disparities were observed, with most of the research concentrated in Asia and Europe (40%) and only 8% in Africa. Despite positive outcomes such as improved business sustainability and competitive advantage (38.52% of studies), challenges persisted, including poor strategy execution and limited resources, necessitating careful customization of BSC to SME-specific contexts. The Balanced Scorecard demonstrates significant potential in enhancing performance management and strategic execution within SMEs, particularly when tailored to address unique constraints such as resource limitations. This review highlights the need for further research to standardize key performance indicators and explore sector-specific applications. By addressing these gaps, the BSC can be more effectively utilized to drive growth, agility, and long-term competitive advantage in SMEs.

The evolution and acceleration of the effects of climate change on the water cycle demand adaptation and mitigation plans. Consequently, the implementation of public policies (management, governance, and strategy) regarding flood risk management or prevention (such as levee heights and spillway dimensions of dams) is based on the characterization of flood hazards. This requires understanding extreme climate phenomena and conducting a rigorous probabilistic analysis of hydrometric data. This study aims to estimate the flood quantiles for lake Nokoue. To achieve this, the adopted methodology involved fitting the Generalized Extreme Value (GEV) distribution, the Gumbel distribution, and the Generalized Pareto (GPA) distribution to the annual maximum water levels of lake Nokoue from 2015 to 2022. We estimated experimental probabilities using the Weibull formula. The assessment of the fit quality of the theoretical probability distributions to our data sample indicated that the Gumbel distribution was the most suitable, with a root mean square error (RMSE) of 0.0724, compared to 0.0754 and 0.0761 for the GEV and GPA distributions, respectively. The position and scale parameters (φ; α) of the Gumbel distribution were estimated to be 3.802 and 0.249, respectively. This allows for the calculation of the probability of an extreme water level occurring within a return period in a single day. Thus, the extreme water levels (flood quantiles) associated with return periods of 10, 50, and 100 years, as determined by the Gumbel distribution, are 4.36m, 4.77m, and 4.95m, respectively. These values are of crucial importance for the design of flood prevention structures (infrastructure) intended to mitigate flood risk.

Reactive oxygen species (ROS) are essential molecules involved in intercellular communication, signal transduction and metabolic processes. Abiotic stresses cause accumulation of excess ROS in plant cells. The issues of regulation of antioxidant protection of plants by natural and synthetic compounds with antioxidant activity still remain one of the important and relevant areas of fundamental and applied research. Glutathione (GSH) plays an important role in stress resistance and redox homeostasis of the cell and effectively protects the cell from stress-induced generation of ROS. An increase in the GSH content in plant cells can contribute to an increase in plant resistance to various types of stressors. However, an increase in the GSH content in plants can negatively affect their growth and development. We have shown that growing Nicotiana tabacum in the presence of tetrapeptide AEDL contributes to an increase in the GSH content by 3.24 times. At the same time, the tobacco plant was more developed, especially its root system. A scheme of the mechanism of regulation of the redox balance in the stem cell niche and the participation of the peptide AEDL and GSH in the regulation of the fate of stem cells was proposed.

Diabetic retinopathy is a prevalent complication of type 2 diabetes mellitus, characterized by progressive damage to retinal structure and function. Photobiomodulation therapy, using near-infrared light, has been proposed as a non-invasive intervention to mitigate retinal damage, but has been tested generally with short-term stimuli. This study aimed to evaluate the effects of prolonged photobiomodulation on retinal structure and function in a type 2 diabetes mouse model. Transgenic LepRdb/J (db/db) mice and their heterozygous controls were exposed to photobiomodulation therapy via LED devices emitting 654 nm light for 12 hours daily over ten weeks. Retinal function was evaluated by flash electro-retinography, while structural changes were assessed through histology and immuno-histochemistry to detect astro- and microgliosis. At 33 weeks of age, db/db mice were obese and severely diabetic, but exhibited only incipient indicators of retinal deterioration. Electroretinogram b-wave peak latencies were prolonged at intermediate flash intensities, while the outer plexiform layer displayed significantly elevated IBA1 expression. Photo-biomodulation therapy prevented these two markers of early retinal deterioration, but had no effect on other morphological and functional parameters. Photobiomodulation is well-tolerated and maintains potential as a complementary treatment option for diabetic retinopathy, but requires further optimization of therapeutic settings and combinatory treatment approaches.

ECMO is becoming widely used as a life saving measure for critically ill patients. However, there is limited data on pharmacokinetics and dosing of beta-lactam antibiotics in ECMO. In this study, we evaluated the serum concentrations of cefepime in patients on ECMO to determine the impact of ECMO circuitry and to guide therapeutic dosing. Methods: Patients 19 years or older admitted to the ICU, treated with ECMO and beta-lactam antibiotics for presumed or docu-mented infection, were enrolled. Three blood samples (peak, midpoint, trough) were obtained before ECMO (pre-ECMO) and during ECMO (intra-ECMO) at steady state. Results: Eight pa-tients met inclusion criteria; six received cefepime. All patients were male. Average ±SD age was 45.8±14.7. Four patients received ECMO for severe SARS-CoV-2 infection, and one each for Pneumocystis pneumonia and influenza A infection. Mean ±SD APACHE II and SOFA scores prior to ECMO were 24.6±7.1 and 11.0±3.9, respectively. All but one received venovenous (VV) ECMO. Cefepime 1 gram every 6 hours intravenously over 2 minutes was administered to all patients before and during ECMO. Cefepime concentrations were fit to a one-compartment model and area under the serum-concentration time curve averaged ± SE 204.6 ± 51.2 pre-ECMO and 344.7 ± 51.5 mg*h/L intra-ECMO, p>0.05. No patients displayed signs of cefepime neurotoxi-city. Patients received ECMO for 43.1± 30 days. All patients expired. Cefepime dosed at 1 gram every 6 hours intravenously appears to achieve therapeutic levels for critically ill patients on ECMO.

Background/Objective: In recent studies, it has been shown that dietary bioactive compounds can produce health benefits, however, it is not known whether an improvement in solubility can enhance their biological effects. Thus, the aim of this work was to study whether co-amorphous (CoA) of naringenin or fisetin with enhanced solubility modify glucose and lipid metabolism, thermogenic capacity and gut microbiota in mice fed a high-fat, high-sucrose (HFSD) diet. Methods: Mice were fed with a HFSD with or without CoA-naringenin or CoA-fisetin for 3 months. Body weight, food intake, body composition, glucose tolerance test, hepatic lipid composition and gut microbiota were assessed. Results: CoA-naringenin demonstrated significant reductions in fat mass gain, improved cholesterol metabolism, and enhanced glucose tolerance. Mice treated with CoA-naringenin gained 45% less fat mass and exhibited improved hepatic lipid profiles, with significant reductions in liver triglycerides and cholesterol. Additionally, both CoA-flavonoids increased oxygen consumption (VO2), contributing to enhanced energy expenditure and improved metabolic flexibility. Thermogenic activation, indicated by increased UCP1 and PGC-1α levels, was observed with CoA-naringenin, supporting its role in fat oxidation and adipocyte size reduction. Further, both CoA-flavonoids modulated gut microbiota, restoring diversity and promoting beneficial bacteria, such as Akkermansia muciniphila, linked to improved metabolic health. Conclusions: These findings suggest that co-amorphous naringenin or fisetin offer promising applications in improving solubility, metabolic health, and thermogenesis, highlighting their potential as therapeutic agents against obesity and related disorders.

The paper introduces an approach to extract information from measurements and generate new load cycles for electrical energy storage systems. Load cycle analysis is performed using rainflow counting, which helps evaluate data and identify stress factors. Load cycle generation can involve clustering methods, random micro-trip methods, and machine learning techniques. The study utilises the Random Pulse Method (RPM) and presents an improved version called the Gradient Random Pulse Method (gradRPM) that allows control over stress factors such as the gradient of the State of Charge (SOC). Another method called Information Maximizing-Recurrent Conditional Generative Adversarial Network (Info-RCGAN) has been developed, and it utilises a deep learning algorithm for data-driven load profile generation with control over stress factors. The results demonstrate the effectiveness of the gradRPM and Info-RCGAN methods in generating load profiles based on the given parameters. The findings provide valuable insights into designing simulation data or testing data for electrical energy storage applications, aiding in improving and understanding system behaviour and requirements.

Biomedical sensors have revolutionized healthcare by offering advanced tools for real-time disease diagnosis, continuous monitoring, and effective treatment. These sensors encompass various technologies, including biosensors, nanotechnology-based sensors, flexible and wearable devices, and more, all of which have played a pivotal role in modernizing medical practices. This review delves into the evolution, types, and technological advancements, along with their broad applications in healthcare, such as in molecular informatics, genomics, proteomics, and personalized medicine. The primary objective of this review is to provide a comprehensive overview of the current landscape, highlighting the latest technological innovations, diverse applications, and potential future trends. The review seeks to demonstrate the critical role these sensors play in enhancing diagnostic accuracy, treatment efficacy, and overall patient care. This review methodically examines various biomedical sensor technologies, focusing on advancements such as microfabrication techniques, nanotechnology, and the development of biocompatible materials. The analysis also covers the miniaturization of sensors, their portability, and the integration of these devices with the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) to improve healthcare outcomes. These sensors are widely used in wearable and implantable devices for continuous monitoring of vital signs, disease diagnosis, and therapeutic interventions. Notable applications include diabetes management, cardiovascular monitoring, and cancer detection. Emerging trends are set to further enhance the capabilities and applications of these sensors. Despite challenges such as biocompatibility, data privacy, and regulatory hurdles, ongoing research and innovation will likely overcome these barriers, ensuring that biomedical sensors, improve patient outcomes, and facilitate more personalized medical interventions.

This exploratory study investigates the use of Generative Artificial Intelligence (GenAI) tools in developing strategy practices for nanostores — i.e., small independent grocery retailers — to enhance their competitiveness while contributing to community sustainability. Nanostores, particularly in emerging countries, face intense competition and rapidly changing trends. By leveraging their proximity to consumers in neighbourhoods, these stores adopt various strategies, such as offering complementary services, integrating technology, and adapting business models. While existing literature highlights the broader economic, social, and environmental roles of nanostores, there is limited comprehensive research on how they may simultaneously contribute to their competitiveness and communities’ sustainability. This study employs a 'thing ethnography' approach, using GenAI tools —i.e., ChatGPT 3.5 and Microsoft Copilot— to explore potential strategy practices for these shops, and reflect on their possible use for strategy ideation and implementation. Key findings suggest that prioritising local sourcing, understanding local preferences, flexible inventory management, efficient retail operations, in-store sustainable practices, promoting healthy lifestyles, and diverse community engagement are crucial for success. However, the study also acknowledges the limitations of GenAI tools, including possible bias and the need for result validation. By aligning with these evolving requirements, nanostores can strive in neighbourhoods and decisively promote sustainable communities.

This study investigates student performance with the aim to forecast students' academic outcomes using data analytics and machine learning techniques. There is a big drop out per cent especially in the technological study programs at the universities, however, focusing on the successful study process there is important to analyze and to predict some risks on students’ to assure low dropout percent. While Student Performance Prediction (SPP) has potential benefits, such as personalized learning and early interventions, several challenges make the task complex in relation to (1) data quality and availability and (2) incomplete and inconsistent data. Predicting performance requires a range of different data types: academic records, attendance, and engagement in class, socio-economic background, and even behavioral factors. Moreover, according to the fourth Sustainable Development Goal (SDG) we focus on the quality in education.This paper presents a case study of data mining method for SPP by using classification, regression, and clustering are generally used in education to predict student’s performance which is important to control drop out of studies percent. The case presented is to predict risks and to assure academic success and quality based on the CRISP-DM data mining.

Periodontics is a complex field characterized by a constantly growing body of research, posing a challenge for researchers and stakeholders striving to stay abreast of its evolving literature. Tradi-tional bibliometric surveys, while accurate, are labor-intensive and not scalable to meet the demands of such rapidly expanding domains. The aim of this study was to explore the uses of a top-ic-modeling algorithm to investigate the structure of the periodontics research field. To this purpose, we employed BERTopic to automatically sift through a substantial corpus of periodontics manu-scripts published in MEDLINE from 2009 to 2024 and identify topics using two sets of settings, to get a broader and high detailed view of the field, respectively. BERTopic identified and categorized 31 topics, unveiling the internal structure and the relations between publication macroareas. When we used the high granularity settings, we identified 2428 topics, which revealed hotspots within the field. Specific regression highlighted novel research areas such as artificial intelligence and exo-somes. In conclusion, BERTopic offers a flexible tool to provide insights into periodontics, its most recent trends, and serve as a useful instrument to approach the field and direct future research.

The efficiency and the flame stabilization are two of the main parameters in the design of combustors according to the current policies imposed to the commercial aircraft industry. An alternative for flame stabilization and high efficiency in the combustion process in combustors is the concept of trapped vortex combustor (TVC). The objective of this study is to determine the optimal location and size of the injection holes for the airflow supplied to a TVC by means of a numerical simulation for non-reactive flow. The results showed a two vortex flow structures in the cavity that change their size and intensity according to the allocation and size of the injection holes. The total pressure lost, flow stability, velocity distribution, vortex size and intensity were the parameters for evaluating the different configurations. The optimal behavior was for a set of air injection holes at the top fore wall of the cavity in combination with a second set located at the bottom of the after wall.

Clinical microbiology studies and systematic reviews have largely concluded that SARS-CoV-2 RNA is rarely present in the urine of COVID-19 patients. Thus, wastewater surveillance has largely focused on human stool and defecation as the relevant matrix and behavior. But, the over-performance of wastewater testing during near-source surveillance, especially in settings where on-site defecation is presumed to be de minimis such as aircraft and non-residential schools, suggests the possibility of SARS-CoV-2 RNA input from a non-fecal source. To revisit the possibility of urine as an explanation, data was compiled from 45 studies reporting on SARS-CoV-2 RNA in the urine of 1,924 COVID-19 patients. In general, the reporting quality was low with most studies (86.7%) failing to report even basic details such as the volume of urine collected. Only 11 reported quantitative data and of these only a single study reported its experiments to the standards established for publication of quantitative PCR data. Taking the data at its face value, the pooled prevalence of urinary SARS-CoV-2 RNA shedding was 11.3% (95%CI: 8.4 - 14.3), which roughly agrees with previous analyses. However, the percentage of variability in the estimate attributable to heterogeneity between studies (I² = 93.66%) warrants careful consideration. Notably, for the 8 studies reporting sufficient workflow information, the observed urinary RNA shedding prevalence was normally distributed (r² = 1.00) as a function of the volume of urine being assayed in a single PCR reaction (i.e., the equivalent sample volume, ESV). The study achieving the highest ESV (83.3 µL of urine) detected SARS-CoV-2 RNA in urine sediments of 95.5% of COVID-19 patients. Conversely, during two studies achieving ESVs of only 2 µL and 11.7 µL of urine, SARS-CoV-2 RNA was not detected in the urine of 72 and 132 patients, respectively. For wastewater surveillance of COVID-19, these observations suggest the rarity of SARS-CoV-2 RNA in urine may be a methodological artifact. Further, the data on which rarity is presumed are of low quality. Beyond COVID-19, the findings demonstrate that clinical studies, by virtue of their design to answer clinically relevant questions, could produce datasets subject to large biases that make them less useful when assessing the feasibility of wastewater surveillance of infectious agents. Wastewater surveillance practitioners must carefully consider the appropriateness and limitations of clinical data considering the important differences between the methods and aims of the two disciplines. Given the great potential of wastewater testing, clinical and environmental microbiologist should collaborate to produce robust quantitative datasets for reliable feasibility assessments for both community and near-source public health surveillance.

Mitral valve disease is a common heart disease in dogs. The aim of this study was to describe the cases of dogs that underwent mitral valve repair via a V-clamp device and to provide long-term follow-up data on cardiac function after mitral valve repair. Four dogs with mitral valve regurgitation who experienced coughing, and dyspnea underwent surgical mitral valve repair between December 2023 and March 2024. The patients were evaluated via transthoracic and transesophageal echocardiography. Echocardiography revealed mitral valve leaflet regurgitation. Mitral valve repair was performed under general anesthesia using a V-clamp device introduced through an introducer wire guide. Echocardiography was conducted at baseline and during the 6-month follow-up. Blood analysis results after surgical repair were normal. Follow-up echocardiography revealed no complications related to the procedure, with all dogs demonstrating improved respiratory signs and quality of life after repair. No adverse reactions were reported after surgery. A V-clamp device was used to repair mitral valve regurgitation in four dogs. Mitral valve repair via a V-clamp device is another treatment option for mitral valve disease in dogs.

The different sociocultural context and lifestyle may influence oral health. To evaluate the interference of these factors, we conducted a quantitative-qualitative cross-sectional study. The research was carried out in a private dental office, in an urban area, and in the Family Health Unit (USF), in a rural area. Fifty patients of each location participated on the research. A semi-structured questionnaire covering sociocultural profile, oral hygiene habits, drug consumption, use of medicinal plants, and antibiotics usage was applied. Also, laboratory tests to evaluate the tendency to have dental decay and Streptococcus sp colony counting was performed. There was no significant difference between patients in the two groups regarding gender, race, marital status, type of residence, number of residents in the same household, and type of employment. Private clinic participants were more prone to consuming alcohol and/or cigarettes and reported to brush the teeth more often. There was no association between salivary acidity and higher biofilm bacterial density. The usage of medicinal plants was more evident in the public service. Data presented here revealed that social inequality between private and public dental assistance are greater from the point of view of investment in public health for the population with difficult access and not from cultural or educational level diversity.

Lightweight concrete is a promising alternative in modern construction due to its reduced weight and potential to improve thermal and structural efficiency. Incorporating sustainable materials, such as nopal mucilage and aloe vera, can optimize its properties, promoting more eco-friendly practices in the industry. This study evaluates six concrete mixtures using different dosages of tuff, expanded clay, nopal mucilage, and aloe vera. Physical and mechanical tests were conducted, and the results revealed varied behaviors: mixtures with aloe vera showed extremes in water absorption and consistency, with tuff being very fluid and expanded clay having good workability. Mixtures with nopal mucilage were drier and less workable. In contrast, mixtures with expanded clay showed higher bulk density and variations in consistency and water absorption. Compressive strength varied depending on the lightweight agents used: mixtures with nopal mucilage-expanded clay and aloe vera-expanded clay showed moderate strengths, suggesting that these combinations can improve the strength of lightweight concrete. The different lightweight agents also affected the thermal and physical properties and the fractal dimension of the mixtures, indicating a greater structural complexity and better heat retention in combinations of expanded clay with nopal mucilage or aloe vera.

Wind turbines are associated with noise pollution and make a significant impact on social and environmental stability. The surrounding activities affect the noise pollution in residential locations. It is significantly important that wind power asset owners proactively consider the impact to the surrounding environment while constructing and in the operational phase of wind farms. This will enable the investigation of potential solutions for mitigating public inconvenience. Regulatory authorities regularly demand that asset owners take noise level measurements to investigate the consequences to the public and the environment from wind farms; however, the local authorities do not consider low-frequency noise generation. This manuscript presents a noise risk assessment approach using fuzzy set theory. In this study, two wind farms were selected which are located in the north-central region of Sri Lanka and studied during the southwest monsoon, northeast monsoon and inter-monsoon seasons. Noise data were collected from wind turbines near the residential areas to investigate their impact on the environment and society. To perform noise risk assessment proactively in populated areas, and to identify the risk, a fuzzy logic-based expert system was presented in this study.

We present a 53-year-old male with a history of relapsed refractory multiple myeloma (RRMM) with t(11;14) treated with venetoclax, carfilzomib and dexamethasone (VenKd), resulting in tumor lysis syndrome (TLS) with subsequent renal failure. Repeat marrow biopsy showed no monoclonal plasma cells but extensive fibrosis. Venetoclax was reintroduced after two months with marrow recovery. Venetoclax was titrated from 200 to 400 mg daily alongside IV fluids and allopurinol without TLS recurrence. Here, we highlight the importance of risk stratification, dose titration, and TLS prophylaxis with venetoclax use in RRMM.

Background: Neurofeedback (NFB) or EEG-Biofeedback is a non-invasive therapeutic method, based on the theory of operating conditioning, and designed to change the functioning of the brain by sending feedback that provides positive or negative reinforcement. The goal is to teach the patient how to perceive specific cortical activation states and how to achieve them on purpose. NFB has been used to treat various mental disorders, including Post-traumatic Stress Disorder (PTSD). Traditional treatments for PTSD have several limitations; very few individuals are willing to relive the traumatic experience. Placing itself as an effective alternative, Neurofeedback allows the unresponsive patient to recourse to an alternative intervention to relieve their symptoms without reliving the anguish of trauma, consequently presuming a lower percentage of drop-out. Considering the importance of integrated approaches to clinical practice, NFB was integrated with Trauma-Informed Motivational Interviewing (TIMI). The TIMI approach is a new therapeutic paradigm for clinical interviews that aims to help users work through their trauma and transform it from a point of weakness to a point of strength. Integrating TIMI with NFB can help overcome the current trend of passive implementation of intervention tools, leading to greater user responsiveness and fewer residual symptoms. To improve treatment adherence, moreover, it has been suggested to incorporate Virtual Reality (VR) into the NFB system. VR, through the "sense of presence," provides a more immersive experience than 2D visualization, potentially resulting in faster cortical training. Lastly, the research protocol aims to focus on a population at high risk of PTSD that is often overlooked in research, such as workers who are victims of occupational PTSD.Methods: The study design involves in-depth analysis of a specific clinical case. Baseline measurements were taken for enrollment and at the following time points: T1 (pre-treatment), T2 (post-treatment), and T3 (follow-up). These measurements included various psychometric assessments to evaluate PTSD symptoms, treatment acceptability, safety, and adherence, as well as biological measures related to the brain's electrophysiological activity.Results and Conclusion: Our research reveals that the synergy between virtual reality-mediated Neurofeedback and trauma-motivational interviewing produces significant results. TIMINB stands out as a low-cost, effective, and completely risk-free procedure. This approach could represent a groundbreaking innovation in the field of Cyberpsychology and psychological therapies.

Speech Sound Disorders (SSDs) are prevalent communication problems in children that pose significant barriers to academic success and social participation. Accurate diagnosis is key to mitigating life-long impacts. We are developing a novel software solution -- the Speech Movement and Acoustic Analysis Tracking (SMAAT) system to facilitate rapid and objective assessment of motor speech control issues underlying SSD. This study evaluates the feasibility of using automatically extracted 3-Dimensional (3D) facial measurements from single 2-Dimensional (2D) front-facing video cameras for classifying speech movements. Videos were recorded of 51 adults and 77 children between 3 and 4 years of age (all typically developed for age) saying 20 words from the mandibular and labial-facial levels of the Motor-Speech Hierarchy Probe Wordlist (MSH-PW). Measurements around the jaw and lips were automatically extracted from the 2D video frames using a state-of-the-art facial mesh detection and tracking algorithm, and each individual measurement was tested in a Leave-One-Out Cross-Validation (LOOCV) framework for its word classification performance. Statistics were evaluated at the alpha = 0.05 significance level and several measurements were found to exhibit significant classification performance in both the adult and child cohorts. Importantly, measurements of depth indirectly inferred from the 2D video frames were among those found to be significant. The significant measurements were shown to match expectations of facial movements across the 20 words, demonstrating their potential applicability in supporting clinical evaluations of speech production.

This study examines compliance behaviour in the context of environmental tax policies, highlighting the essential role that these policies play in achieving the objectives of sustainable development. Environmental taxes are crucial instruments to reduce environmental damage and increase energy efficiency. Nevertheless, taxpayer compliance, which is impacted by several variables, including social acceptability, regulatory quality, and perceptions of fairness, is a key component of these policiesʹ efficacy. In contrast to earlier research, which frequently concentrated on certain tax kinds or discrete policy mechanisms, this study takes a broad approach, looking at a range of environmental taxation instruments. Emerging trends, significant factors influencing compliance behaviour, and noteworthy contributions from eminent authors and organizations are all identified by means of bibliometric and scientometric analyses. In order to create fair and effective environmental tax policies, interdisciplinary approaches and international collaboration must be used. Along with presenting policies to improve environmental regulation compliance, the study offers insightful advice for businesses that can help them innovate toward sustainability and adjust to shifting policy. It also provides a solid theoretical base for future researchers by highlighting important areas that require more investigation, especially when it comes to the wider effects of environmental taxes on various industries.

Background/Objective: Women treated with large loop excision of the transformation zone (LLETZ) for cervical intraepithelial neoplasia 2-3 (CIN2+) remain at CIN2+ risk for many years. We assessed the role of high-risk human papillomavirus (HR-HPV), surgical margins, and LLETZ characteristics in long-term risk of CIN2+. Methods: A retrospective observational study was performed on 432 women with histological diagnosis of CIN2+ who were treated with LLETZ from 1996 to 2020 and followed-up until October 2021 at Hospital Bellvitge in Barcelona, Spain. Age, surgical margins, 6-month HR-HPV, excision type, and cone volume/dimensions were ana-lyzed in association with follow-up detection of CIN2+. The cumulative probability of follow-up detection of CIN2+ was calculated by Kaplan-Meier and Cox models. Results: CIN2+ was detected in 7.4% of cases, with over 90% found within 5 years post-LLETZ. HR-HPV (HR = 7.36, 95% CI = 3.55-15.26), involved margins (HR = 3.94, 95% CI = 1.68-9.25), uncertain margins (HR = 4.42, 95% CI = 1.55-12.55), and age ≥ 35 years (HR = 2.92, 95% CI = 1.19-7.13) were predictors of follow-up detection of CIN2+. Type 3 excision (p-value = 0.035) and cone length (p-value = 0.010) correlated with clear margins. The negative predictive value (NPV) of both negative HR-HPV post-LLETZ and clear margins was 98.7%. Conclusions: Negative HR-HPV post-LLETZ and clear margins provide stronger reassurance against follow-up detection of CIN2+ than LLETZ characteristics. Larger ex-cisions in older women likely reduced the risk of involved margins. Close surveillance, including repeated HR-HPV testing within the first 5 years post-LLETZ, is crucial.

The integration of robotics in the garment industry remains relatively limited, primarily due to the challenges in the highly deformable nature of garments. The objective of this study is thus to explore a vision-based garment recognition and environment reconstruction model to facilitate the application of robots in garment processing. Object SLAM (Simultaneous Localization and Mapping) was employed as the core methodology for real-time mapping and tracking. To enable garment detection and reconstruction, two datasets were created: a 2D garment image dataset for instance segmentation model training and a synthetic 3D mesh garment dataset to enhance the DeepSDF (Signed Distance Function) model for generative garment reconstruction. In addition to garment detection, the SLAM system was extended to identify and reconstruct environmental planes, using the CAPE (Cylinder and Plane Extraction) model. The implementation was tested using an Intel Realsense® camera, demonstrating the feasibility of simultaneous garment and plane detection and reconstruction. The study shows improved performance in garment recognition with the 2D instance segmentation models and enhanced understanding of garment shapes and structures with the DeepSDF model. The integration of CAPE plane detection with SLAM allows for more robust environment reconstruction, capable of handling multiple objects. The implementation and evaluation of the system highlights its potential for enhancing automation and efficiency in the garment processing industry.

This study systematically investigates the effects of different anode work function metals (Ti/Au and Ni/Au) on the transport and temperature characteristics of β-Ga2O3 based Schottky barrier diodes (SBD), junction barrier Schottky diodes (JBSD), and P-N diodes (PND), utilizing Sentaurus TCAD simulation software for mechanistic analysis. From the perspective of transport characteristics, it is observed that the SBD exhibits a lower turn-on voltage and a higher current density. Notably, the turn-on voltage (Von) of the Ti/Au anode SBD is merely 0.2 V, marking the lowest recorded value in the existing literature. Furthermore, our study reveals that the turn-on voltages of the two types of PNDs are nearly identical, confirming that the contact between the anode metals and NiOx is ohmic contact, and the contact between Ni/Au and NiOx exhibits a lower contact resistance. The Von, current density, and variation rate of the JBSD lie between those of the SBD and PND. In terms of temperature characteristics, all diodes can work at 200 °C, with both current density and Von showing a decreasing trend as the temperature increases. Among them, the PND with a Ni/Au anode exhibits the best thermal stability, with reductions in Von and current density of 8.20% and 25.31%, respectively, while the SBD with a Ti/Au anode shows the poorest performance, with reductions of 98.56% and 30.97%. Finally, the reverse breakdown (BV) characteristics of all six devices are tested. The average BV for the PND with Ti/Au and Ni/Au anodes reach 1575 V and 1550 V, respectively. Moreover, although the Von of the JBSD decreases to 0.24 V, its average BV is approximately 220 V. This study demonstrates that β-Ga2O3 based power diodes continue to exhibit excellent characteristics and application prospects in terms of low turn-on voltage.

In this paper, we explore a straightforward two-step method to produce high purity, vertically aligned multi-walled carbon nanotubes (MWCNTs) via chemical vapor deposition (CVD). Two distinct solutions are utilized for this CVD method: a catalytic solution consisting of ferrocene and acetonitrile (ACN), and a carbon source solution with camphor and ACN. The vapors of the catalytic solution inserted in the reaction chamber through external boiling, result in a floating catalyst CVD approach that produces vertically aligned MWCNTs in a consistent manner. MWCNTs are grown in a conventional CVD horizontal reactor, at 850°C under atmospheric pressure, and characterized by Raman spectroscopy, Scanning Electron Microscopy (SEM) and Thermogravimetric Analysis (TGA). Coating the MWCNTs with polymethyl methacrylate (PMMA) while still on the Si substrate, retains the structure and results in a flexible, conductive thin film suitable for electrodes. The film is 62 μm thick and stable in aqueous solutions, capable of withstanding further processes such as electropolymerization with polyaniline, to be used for energy storage applications.

This paper discusses the problem of the fastest motion of an object in a curved earth tunnel. By establishing a mathematical model and applying the Python visualization toolkit, the analytical expression of the brachistocentre is derived, and the physical meaning of the integral constant C is analyzed . The study found that under certain conditions, a curved tunnel can provide a shorter travel time than a straight tunnel, which challenges intuitive cognition . At the same time, this research method that combines mathematical software and physical models can help students better expand their thinking about physical models, making complex expanded physical models easy to understand and master .

This study investigated the integration of indigenous knowledge with modern Customer Relationship Management (CRM) practices in the Indian banking sector. Through a comprehensive analysis of secondary data from industry surveys, government reports, and academic studies (2018-2023), we explored how this integration impacts customer satisfaction, loyalty, and financial inclusion. Our findings reveal that banks that incorporate indigenous practices experience a 25% increase in customer satisfaction scores, 30% lower churn rates, and 20% higher cross-selling success. Financial inclusion metrics have improved significantly, with rural account ownership increasing from 70% to 85% (2018-2023). We identify five key areas of indigenous knowledge integration: personalized relationship management, community-centric banking, vernacular communication, cultural event-based products, and traditional value-aligned services. Despite the challenges in technology integration and staff training, the successful implementation demonstrates the potential of this approach. This study concludes that integrating indigenous knowledge with CRM practices leads to more culturally relevant and effective banking services, contributing to India's financial inclusion and economic development goals. This study provides a framework for banks to create inclusive strategies that are potentially applicable to other sectors in culturally diverse markets.

Objectives: We aimed to assess the relationship between circulating extracellular vesicles (EVs), hypoxia-related proteins and conventional risk factors of the life threatening coro-nary artery disease (CAD) to find more precise novel biomarkers. Methods: Patients were categorized based on coronary CT angiography (CCTA). Patients with a Segment Involvement Score (SIS) > 5 were identified as CAD patients. Individuals with a SIS < 5 were considered as control subjects. Characterization of EVs and analysis of plasma concentration of GDF15 were performed by multicolor or bead-based flow cytom-etry. Plasma protein levels of PYGM, clusterin, CPN1 were determined by ELISA. Multiple logistic regression was used to determine the association of the biomarkers with the CAD outcome after accounting for established risk factors. The analysis was built in 3 steps: first, we included the basic clinical and laboratory variables (Model 1), then we integrated the plasma protein values (Model 2), and finally complemented it with the circulating EV pattern (Model 3). To assess the discrimination value of the models, an area under the re-ceiver operating curve was calculated and compared across the three models. Results: The AUC values were 0.68, 0.77 and 0.84 in Models 1, Model 2 and Model 3, re-spectively. The variables with the greatest impact on the AUC values were Hemoglobin 0.2 (0.16-0.26) in Model 1, CPN1 0.12 (0.09-0.14) in Model 2, and circulating CD41+/CD61+ EVs 0.31 (0.15-0.5) in Model 3. Correlation analysis showed a significant impact of circu-lating CD41+/CD61+ platelet-derived EVs (p=0.03, r=-0.4176) in Model 3. Conclusion: Based on our results, the circulating EV profile can be used as a supportive biomarker along with the conventional laboratory markers of CAD, and it enables a more sensitive, non-invasive diagnostic analysis of CAD.

Simple and complex clustered DNA damage represent critical initial damage caused by radiation. In this paper a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: A) direct damage of sugar-phosphate moieties leading to SSB, B) OH^- radical formation with subsequent SSB and BD formation, C) direct damage to DNA bases, and D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for relative location of SSB using a <10 bp criteria for double strand break (DSB), and for the possible success of radical attack to lead to SSB or BD. Model predictions for electrons, ⁴He and ¹²C ions are compared to experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.

This study investigates the rapid growth of the e-commerce industry in Nepal while examining the associated security challenges. By analyzing factors driving e-commerce development, identifying prevalent threats, and evaluating existing security measures, this research aims to provide a comprehensive understanding of Nepal's e-commerce landscape. This research uses a combination of quantitative and qualitative data to better understand the complex relationship between e-commerce and security threats.E-commerce security is paramount for protecting online transactions. It ensures data integrity, prevents unauthorized access, and maintains confidentiality. While e-commerce offers opportunities for the banking industry, it also introduces security risks like hacking. Effective e-commerce security requires a coordinated approach, combining technical solutions with robust management practices. Key findings from this research are expected to inform the development of robust strategies to mitigate security threats and cultivate a secure e-commerce ecosystem in Nepal. By addressing the challenges and opportunities presented by e-commerce, Nepal can harness its potential for economic growth and development while ensuring a safe and secure online environment for consumers and businesses.

This study assesses the social, economic, and environmental effects of harvesting timber from the Kambui Hills forest reserve in Sierra Leone, a part of the Gola rain forest, a biodiversity hotspot along the upper Guinea forest zone that stretches through the Manor River Union basin of the Republics of Guinea, Sierra Leone and Liberia. The study area covers an area of 40 kilometers in length and five kilometers in breadth (20,348 hectares of land), with a population of 45,562 residents [1]. A ten-year time series data from 2010 to 2021 is used for this research. The data is processed using EViews 10 statistical software package in a regression analysis. The data set is collected from Food and Agriculture Organization Statistics of the United Nations (FAOSTAT); International Timber Trade Organization (ITTO); and Statistical Office of the European Union (EUROSTAT). A set of specified variables such as primary literacy Level, carbon emissions, inflation, unemployment, Gross Domestic Product (GDP), Exports, and natural resource rent are used to determine the socio-economic and environmental impacts of harvesting timber within the study area. The environmental impacts results from the regression analysis confirmed that R² or the coefficient of determination is 0.5734, which shows that 57 % of the dependent variable is significantly explained by the independent variables in the model. Similarly, the economic impact shows an R² of 0.8596, which indicates that 86 % of the dependent variable is explained by the independent variables in the model. In the same vein, the social impacts showed an R-square of 0.9667. This is statistically significant as 97 % of the dependent variable is explained by the independent variables in the model. Thus, the regression models confirmed the socio-economic effects of harvesting timber and its environmental impact on the residents of the forest area investigated. This study will conclude with recommendations to the relevant stakeholders in Sierra Leone.

Climate change remains a pressing global issue affecting sectors including agriculture and forest resources in countries such as Uganda. This research focused on exploring the viewpoints of youth in Uganda concerning adapting to climate change and their interest in getting involved in agroforestry transition. By conducting a survey involving 1138 participants from the youth demographic group aimed to gather information about their level of hopefulness towards climate adaptation efforts and how they perceive the impact of farming practices and deforestation. Furthermore, the study aimed to evaluate youth willingness to participate in agroforestry (WTP) initiatives. The study used descriptive statistics as well as Ordinary Least Squares (OLS) to analyze the collected data. We found that most participants are climate change hopeful about adapting to climate change (89%). This positive and highly significant outlook is closely related to their willingness to participate in agroforestry adaptation efforts (0.0001). Moreover, a high percentage of participants (92%) acknowledged how farming practices such as cultivation and livestock rearing can degrade land significantly. Whereas Gender, Age and Employment were found to be highly and positively significant regarding youth’s WTP in agroforestry (0.0001), Income was not. Incorporating indigenous practices and encouraging meaningful involvement from policymakers can empower the youth and strengthen community-led initiatives to address environmental decline effectively. This research highlights the capacity of youth engagement in steering successful climate resilience measures via agroforestry practices in Uganda.

Outlier detection is a critical technique across various domains, including statistics, data science, machine learning, and finance. Outliers, data points that differ significantly from the majority, can indicate errors, anomalies, or even new insights. This article provides an in-depth exploration of the primary techniques used to detect outliers, categorized into statistical methods, machine learning-based approaches, and proximity-based methods. We discuss the advantages, limitations, and specific use cases of each technique, highlighting their applicability to different types of datasets. The goal is to equip practitioners with a better understanding of how to identify and handle outliers effectively in real-world data analysis.

Rhoptry proteins of the RhopH complex (RhopH1/Clag, RhopH2 and RhopH3) participate in the formation of new permeability pathways for nutrient uptake in Plasmodium falciparum infected erythrocytes. RhopH proteins associate with the Maurer’s clefts (MC) during transport to the host cell membrane and interact with the cytoskeleton. However, the role of specific MC proteins facilitating rhoptry protein interaction and trafficking is unknown. The major interaction with MCs occurs with RhopH3. Dual roles ascribed to RhopH3 include functions in host cell invasion and formation of the plasmodial surface anion channel (PSAC). The topological orientation and organization of the RhopH3-MC membrane interaction in the host cell cytoplasm has not been described. In this study, we performed biochemical analysis to investigate the topology and trafficking of RhopH3 and Pf130 from the parasite to the erythrocyte cytoplasm using streptolysin O (SLO) permeabilization and protease treatment of infected erythrocytes. We investigated Pf130, a soluble protein previously identified by monoclonal antibodies and shown by immunoelectron microscopy (IEM) to be distributed underneath knobs and associated with the MC in infected erythrocytes. Pf130 is expressed early in the erythrocytic cycle and persists to the schizont stage. Immunofluorescence and confocal microscopy show that Pf130 is a resident MC protein due to its colocalization with the MC protein REX-1. Immunofluorescence assay (IFA) showed colocalization of Pf130 with RhopH3 in the cytoplasm of SLO permeabilized and trypsin treated infected erythrocytes. These novel findings show that both proteins were protected from protease digestion demonstrating that conformational changes are required to transport the RhopH proteins through association with the MC as integral membrane proteins.

Anomaly detection is crucial in large-scale industrial manufacturing as it helps detect and localise defective parts. Pre-training feature extractors on large-scale datasets is a popular approach for this task. Stringent data security, privacy regulations, high costs and acquisition time hinder the development of large-scale datasets for training and benchmarking. Despite recent work focusing primarily on the development of new anomaly detection methods based on such extractors, not much attention has been paid to the importance of the data used for pre-training. This study compares representative models pre-trained with fractal images against those pre-trained with ImageNet, without subsequent task-specific fine-tuning. We evaluated the performance of eleven state-of-the-art methods on MVTecAD, MVTec LOCO AD, and VisA, well-known benchmark datasets inspired by real-world industrial inspection scenarios. Further, we propose a novel method to create a dataset by combining the dynamically generated fractal images creating a ``Multi-Formula'' dataset. Even though pre-training with ImageNet leads to better results, fractals can achieve close performance to ImageNet under proper parametrisation. This opens up the possibility for a new research direction where feature extractors could be trained on synthetically generated abstract datasets mitigating the ever-increasing demand for data in machine learning while circumventing privacy and security concerns.

In plants, melatonin (MT) and abscisic acid (ABA) are conventionally treated as molecules mitigating stress responses. To understand the mechanisms of ABA–MT interplay, we examined the effects of ABA and MT treatment in loss-of-function ABA and MT mutants exposed to high light (HL) stress. ABA constantly suppressed ASMT encoding N-acetylserotonin methyltransferase in the context of differential responses of other MT biosynthesis genes in both wild type (WT) and mutants. However, this response was absent in the mutant with the disrupted ABI4. Given that the ASMT promoter region contains several potential ABI4-binding elements, these data suggest that ASMT can be a potential target gene for ABI4. A role for ABI4 in the interactions between ABA and MT is supported by the finding that ABI4 is constitutively derepressed in the MT signaling mutants cand2 and gpa1, which exhibited elevated steady state levels of ABI4 transcripts and were not regulated by either stress or melatonin. In addition, the abi4 mutant showed increased modulations in the expression of the MT catabolic genes M2H and M3H in response to ABA treatment inferring that this transcription factor is a negative regulator of ABA-dependent changes in MT content. Furthermore, all tested mutants with impaired ABA synthesis or signaling displayed elevated steady state MT levels compared to WT, while MT treatment contributed to downregulation of key ABA synthesis and signaling genes. Collectively, our results suggest that ABA and melatonin act antagonistically modulating the expression of ABA and MT signaling and metabolism genes.

In a sports hall, three different groups of young adults played the "bluegill game" (a Prisoner's Dilemma-like sports game). The present study's objective was to measure the extent of cooperative behaviour in a group of 25 team sports players. To maximise gains, a player had to adopt selfish tactics half the time. The group of team sports players came closest to this mixed-strategy Nash equilibrium (chi2=4.07 in a logistic regression, p&lt;0.05). The two control groups (23 individual sports players and 24 non-sportspeople) were found to be significantly more cooperative. The altruistic players kept the game alive while working towards their own defeat. We discuss how the "bluegill game" model can be broadened to other social situations. In these non-collaborative, non-zero-sum games, cooperation is an irrational choice on the individual level but is essential on the group level.

Deep learning methods have been widely applied to time series classification tasks. Although deep learning methods perform excellently on these tasks, they require much training data. Labeling time series data for training is very time-consuming and labor-intensive. Active learning can be used to select the most informative data for labeling in time series classification tasks to save human labeling efforts. In this paper, we propose a new active learning (AL) framework for time series data. First, a temporal classifier for pixel-level temporal classification tasks is designed. Next, We propose an effective active learning method to select informative time series samples for labeling, which combines representativeness and uncertainty. For representativeness, We use the K-shape method to cluster time series data. For uncertainty, we construct an auxiliary deep network to evaluate the uncertainty of unlabeled data. The features of the middle hidden layer with rich temporal information of the classifier will be fed into the auxiliary deep network, which is equipped with a self-attention mechanism to utilize the temporal dependencies of time series data fully. Then, we define a new loss function with the aim of improving the deep model’s performance. Finally, the proposed method in this paper was evaluated on two temporal remote-sensing image datasets. The results demonstrate a significant advantage of our method over other approaches to time series data. Code is available at https://github.com/Fighting-Golion/time_series_active_learning

Background: Menstruation is a natural physiological process experienced by 1.8 billion girls, and pre-menopausal women globally, and can be experienced about 300 times in a woman’s lifetime. Even though menstruation is a sign of normal female reproductive functions and marks an important transition into womanhood for adolescent girls, it is bounded by several taboos, myths, misbeliefs, or misconceptions in low-and middle-income countries including Ghana. Hence, the topic and cultural practices around menstruation are rarely discussed, and the experiences of young girls during menarche and early menstrual life remain poorly captured. This study explored the cultural construction of menstruation in the Ghanaian context. Methods: This study was qualitative and adopted an exploratory study design. We used purposive and convenience sampling procedures for sampling five Senior High Schools and participants in the Volta Region of Ghana. 15 Focus Group Discussions (FGD) were conducted. This comprised five FGDs for female students, five FGDs for teachers, and five FGDs for parents. For each of the FGDs, 10 to 12 participants were sampled to participate in the discussion. Data were audio-recorded, transcribed, translated, and imported into MAXQDA qualitative analysis software 2022 version for analysis. Data were coded and analyzed using a thematic analysis. Results: We found that there are a myriad of socio-cultural beliefs and practices that are associated with menstruation in Ghana. These beliefs such as menstrual blood is unclean and practices like celebration of menarche, and upholding some menstruation-related cultural/tribal taboos including household restrictions, religion, and social restrictions were identified. Our findings revealed that myths have long enveloped the facts about menstruation. Conclusion: Cultural and social practices regarding menstruation depend on girls’ education, attitude, family environment, culture, and beliefs, pointing to the need for public health officials in the Ghanaian society to provide more culturally oriented education to the general public on menstruation and the impact of some conservative socio-cultural practices on the menstrual health of adolescents.

Incorporating sewage sludge (SS) into soils presents a cost-effective and environmentally friendly option compared to conventional farming practices. However, SS could be perceived as a double-edged sword, as it may contain a broad spectrum of contaminants, posing threats to soil, underground waters, food chains and human health. Even from an epidemiology perspective, the COVID-19 pandemic has instigated debates regarding the potential health risks associated with SS. The handling of SS is emerging as a significant issue in the European Union (EU), primarily due to its increasing utilization and the presence of contaminants such as heavy metals (HMs), microplastics (MPs), Pharmaceuticals in the Environment (PIE), and personal care products (PSPs). The Council Directive 86/278/EEC governs the limits of HMs when SS is utilized in agriculture. However, the Directive is enacted diversely throughout EU member states (MS), with their national legislations highlighting differences, gaps and various approaches in implementing the Council Directive. The Directive, which has been in force since 1986, has not undergone any significant revisions until the recent disclosure of a revised version in May 2023. The executive summary of the evaluation of the Council Directive 86/278/EEC (SWD-2023) – {final 158} specifies maximum concentrations of six HMs in SS among its regulatory measures. This article delves into capturing the current legal framework that defines and delimits the processes and obligations of EU MS regarding SS's management, treatment, and agriculture amendment. The primary objective is to explore the qualitative and quantitative differences/discrepancies between the MS National legislation and point out discontinuities and gaps, thus setting forward a cohesive step for future revisions and updates of the relevant legislation. Part of the article's results reflect the different approaches to permissible limits of HMs concentrations in the EU MS and between international organizations such as the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). Moreover, the total absence of MPs and other Common Soil Pollutants (antibiotics, pharmaceuticals, etc.) limit values are evidence of the gaps in the current legislative framework.

Insects, nematodes, and aquatic animals face several biotic and abiotic stressors that can significantly affect their fitness – specifically damaging their cellular proteins' competent functional nature. In response, they have evolved sophisticated stress-responsive mechanisms. Certain endogenous proteins, known as small heat shock proteins (sHSPs), serve to maintain the stability and function of proteins under stress. Since the identification of the first sHSPs, an increasing number of sHSPs, mainly due to the new robust sequencing tools, continue to be identified and reported to play a critical role in the organism’s response to stress. This review explores and summarizes the contributions of the sHSPs implicated in stress response. Understanding their function is crucial for advancing our knowledge in agricultural pest management, climate change adaptation, and biotechnology.

The relationships between the relative abundances of chemical elements and their second ionization potentials, as well as their condensation temperatures, were analyzed using four published homogeneous abundance surveys of halo and thin disk stars. We selected 932 stars with effective temperatures ranging from 4900 K to 5900 K and used the abundances of 10 chemical elements common across all surveys: Mg, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, and Ni. The correlation coefficients between the relative abundances of these elements and their second ionization potentials and condensation temperatures were investigated in relation to metallicity and the stars' location in the Galaxy. The observed correlations may result from certain physical processes, such as the accretion of interstellar gas onto stellar atmospheres. We also analyzed the dependencies of relative abundances on second ionization potentials based on published abundance patterns in five halo stars. Evidence of charge-exchange reactions in the atmospheres of these stars was found. For more accurate determination of stellar ages from the abundance ratios of radioactive and stable chemical elements in stellar atmospheres, processes such as charge-exchange reactions and dust-gas separation should be considered in future detailed investigations. Additionally, changes in the chemical abundances in the atmospheres of halo stars after crossing the Galactic plane were found to be possible.

The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is in its 5th year and is being maintained by the inability of current spike-alone based COVID-19 vaccines to prevent transmission leading to the continuous emergence of variants and sub-variants of concern (VOCs). This underscores the critical need for next-generation broad-spectrum pan-Coronavirus vaccines (pan-CoV vaccine) to break this cycle and end the pandemic. The development of a pan-CoV vaccine offering protection against a wide array of VOCs requires two key elements: (1) identifying protective antigens that are highly conserved between passed, current and future VOCs; and (2) developing a safe and efficient antigens deliver system for induction of broad-based B- and T-cell immunity. This review will (1) present the current state of antigen delivery platforms involving a multifaceted approach, including bioinformatics, molecular and structural biology, immunology, and advanced computational methods; (2) discuss the challenges facing development of safe and effective antigen delivery platforms; and (3) highlight the potential of nucleoside-modified mRNA encapsulated in lipid nanoparticles (LNP) as the platform that is well suited to the needs of a next-generation pan-CoV vaccine, such as the ability to induce broad-based immunity and amenable to large-scale manufacturing to safely provide durable protective immunity against current and future Coronavirus threats.

Functional graded materials (FGMs) have been successfully applied in improving the insulation performance of insulators, yet there is currently no relevant literature on their application in dry-type transformers. Therefore, it is meaningful to study on the feasibility of using FGMs to improve the insulation performance of dry-type transformers through research on electric field distribution. This paper sets FGMs in the dry-type transformer spacer only or both spacer and winding end to change the relative permittivity values in the corresponding areas. By comparing the electric field distribution characteristics on the inner and outer surfaces of the high-voltage coil and the lower surface of the spacer of the dry-type transformer under each control method with the case without setting FGMs, the study found that when FGMs were only set on the spacer, the control methods set in this paper could not improve the electric field distribution of the transformer. When FGMs are employed at the spacers and end windings, two modulation strategies can mitigate the electric field intensity on the outer surface of high-voltage windings. Specifically, a continuous increase in relative permittivity can reduce the electric field intensity by 34.02%, while an initial decrease followed by an increase can result in a reduction of 13.58%. This paper provides theoretical guidance for insulation design of transformers with high voltage levels of 66 kV and above, especially as transformers with high voltage levels face greater challenges in regulating surface electric fields.

This article affords the question of methane emissions in the context of the ESG framework at the global level. The World Bank ESG-Environmental, Social, and Governance database was used. The data refers to 193 countries for a period between 2011 and 2020. The econometric models used are Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled Ordinary Least Squares-OLS, and Weighted Least Squares-WLS. The impact of methane on the ESG model was calculated through three equations capable of analyzing the impact of methane emissions, respectively, con-cerning the E-Environmental, S-Social, and G-Governance components of the ESG model. The re-sults show that methane emissions tend to increase even in the improvement of ESG conditions at world level.

Lithium has long been recognized for its therapeutic efficacy in the treatment of manic-depressive illness (MDI). Additionally, numerous reports highlight its protective properties against cell insults, with a remarkable majority of these effects documented in neurons. Utilizing the major mechanisms of its action, we bring insights that explain lithium's ability to preferentially promote survival in neurons. Specifically, we explore its interactions with magnesium at protein binding sites, with a particular focus on its impact on glycogen synthase kinase 3 beta (GSK3β). We propose that lower intracellular free magnesium levels in the brain, coupled with the higher expression of GSK3β, which is an enzyme whose activity is magnesium-dependent, amplify its impact on brain cells, promoting neuronal survival.

Analysis of the construction of tall buildings is important because of the changes in the microclimate in its vicinity. Ensuring wind comfort and pedestrian safety are critical requirements in urban environments. This paper reports on the wind flow field at the main campus of the Dhaka University of Engineering & Technology (DUET), Gazipur, using computational fluid dynamics (CFD) to investigate pedestrian wind comfort and safety. The simulations were conducted in ANSYS Fluent employing the Reynolds-averaged Navier-Stokes (RANS) equation. The vertical profile of the streamwise wind speed was validated using the existing observations. The results revealed that the wind speed at the building corners was higher than the air inlet velocity, whereas the wind speeds in the walkways among the buildings were found to vary. The velocity vectors surrounding the building were densely packed, with a recirculation vortex formed in the upstream flow. Furthermore, walkways can display a lower mean wind velocity coupled with high turbulence kinetic energy (TKE). The turbulent kinetic energy is seen to be as high as 1.52 m2 s-2 which exceeds the threshold limit, while wind velocity is 1.81 m/s at the same point. These findings highlight potential pedestrian safety risks and underscore the need for urban design enhancements.

Lung cancer is one of the deadliest cancers, leading to about 125,070 deaths in the U.S. each year. Survival rates depend on the type and spread of cancer, with localized non-small cell lung cancer (NSCLC) having a 5-year survival rate of 64%. High mortality is primarily due to late detection and the older age of patients, making surgery too risky. As a result, preventative measures like vaccines are crucial. This paper reviews the literature on CIMAvax-EGF, an EGF-based vaccine for lung cancer, evaluating its preventive potential, impact on survival in advanced NSCLC, and effect on lung cancer mortality in combination with other therapies. CIMAvax-EGF is a promising vaccine targeting the Epidermal Growth Factor (EGF), which promotes cancer cell growth. The vaccine prevents EGF from binding to its receptor by inducing anti-EGF antibodies, potentially halting cancer progression. It shows significant potential for treating advanced NSCLC, with vaccinated patients having a median overall survival of 12.43 months compared to 9.43 months in unvaccinated individuals. A Phase III trial showed that 78.8% of patients had a good antibody response (GAR), leading to longer survival. CIMAvax-EGF is well-tolerated, with mild to moderate side effects, and its efficacy is enhanced when combined with other therapies, such as immune checkpoint inhibitors. Given its ability to target cancer's underlying mechanisms and boost other treatments, CIMAvax-EGF represents a significant advancement in the fight against lung cancer. Administering this vaccine preventively and during treatment could be a major step in reducing lung cancer mortality.

Objective: Repetitive transcranial magnetic stimulation (rTMS) shows promise as an aphasia treatment, however its physiological mechanisms in people with aphasia (PWA) remain largely unclear. Electroencephalography (EEG) could be used to explore rTMS mechanisms. The present study investigated the acute effects of rTMS in PWA on: 1) an EEG measure of language (N400 event-related potential); and 2) picture naming. Methods: Eleven people with chronic non-fluent or anomic aphasia (64 ± 10.13 years old; 8 males; 37.27 ± 20.64 months since stroke) received one session of 1-Hz rTMS and one session of sham to the right pars triangularis at 80% resting motor threshold (RMT). N400 mean amplitude and picture naming accuracy were compared before and after each session. Results: No acute changes were observed in N400 mean amplitude or picture naming accuracy as compared to sham (p > 0.05; BF₁₀ < 0.33). Conclusions: Results suggest that language networks underlying the N400 are not altered following one session of 1-Hz rTMS in PWA. Significance: Although EEG could be useful for assessing physiological mechanisms of rTMS in PWA, the N400 does not appear to be a viable measure of acute 1-Hz rTMS effects, at least when delivered at 80% RMT in a single session.

Background/Objectives: Malnutrition significantly hinders the recovery of patients undergoing convalescent rehabilitation. Proper nutritional management can improve rehabilitation outcomes. This study aimed to establish a novel nutritional screening method (J-Method) specifically for convalescent rehabilitation patients and compare it to the widely used Mini Nutritional Assessment Short Form (MNA-SF). Methods: We developed the J-Method for convalescent rehabilitation settings and compared its results with that of the MNA-SF. The J-Method comprised six items derived from various nutritional screening methods and obtained solely from medical records, without patient interviews. Data were collected from 148 patients aged > 65 years with cerebrovascular diseases admitted to a convalescent rehabilitation ward (CRW). Nutritional status was evaluated using the J-Method and MNA-SF, and results were compared. Results: The J-Method more precisely identified patients as malnourished than the MNA-SF. The results of nutritional screening using the J-Method identified patients in need of nutritional management intervention and suggested that, to improve the rehabilitation effect, nutritional management should be initiated in an acute hospital before admission to a CRW. Conclusions: The J-Method may be more effective than the MNA-SF for nutritional screening in convalescent rehabilitation settings as it provides a more accurate assessment of malnutrition without requiring patient interviews.

Aging is a common global challenge. The World Health Organization has released the guide “Global Age-Friendly Cities: An equitable, inclusive and sustainable place” in which it is stated that age-friendly recreational landscapes are one of the important elements for cities and communities to create suitable leisure and social activities for older people. As a healthy green living room at the doorstep, residential green space is of great significance for building age-friendly recreational landscapes in residential green spaces. In this paper, based on the perspective of the demand of older adults for residential green space recreational landscapes, we use the systematic literature review method to comprehensively and deeply comb and summarize the existing research results and put forward China’s future key research directions in this field in a comparative analysis. The study found that: 1. The research heat in this direction has been high in the past five years, and the amount of literature in China and the United States is the highest. 2. The main disciplines involved in the study are landscape architecture, public health, and sociology, and the amount of literature in the direction of public health in international journals is the most, and the papers in the direction of landscape architecture in China are the most. 3. The main research methods used are quantitative research, which accounts for 58% of the literature, and questionnaire surveys, which account for 51% of the literature. 4. The main independent variables involved are green space area, walking environment, recreational and health facilities, community participation, etc., and the main dependent variables are satisfaction, frequency of green space use, physical and mental health, community cohesion, and sense of well-being. 5. The five main theories involved are demand theory, ecology theory, health promotion theory, environmental psychology, and environmental gerontology theory. International literature is mostly studied from health promotion theory and ecological theory, and Chinese literature is mostly studied from the perspective of need theory. 6. Measurement indexes are different in diverse disciplines, among which the direction of landscape architecture mainly explores the influence of green space safety, accessibility, multi-functionality, environmental aesthetics, and recreational facilities on the satisfaction, and happiness of older adults from the perspective of green space planning and design. In the direction of public health, the impact of green space on the physical, psychological, and social health of older adults is mainly explored from the perspectives of green space areas, neighborhood environments, and community participation.

In this investigation, four distinct by-products of natural materials were used to compose a mix for rammed earth construction. The mix of these materials, which have various granulometry, affords many potential combinations, making the analysis of different combinations highly complex. The Taguchi method, a statistical approach renowned for significantly reducing the number of ex-periments in complex systems, was employed to address this challenge. Each of the four ma-terials was assessed across four different levels, with moisture content also factored in as a pa-rameter within the statistical analysis. Two separate studies were conducted to obtain two optimal com-binations of the materials to enhance the dry density and the Unconfined Compressive Strength (UCS). Taguchi method demonstrated its efficacy in predicting the optimal combination of mix-tures for enhancing both objective parameters. A natural by-product mix demonstrated its po-tential for use as a building material. The enhancement of the dry density due to a modification of the mix’s Particle Size Distribution (PSD) did not produce a direct improvement in the mix UCS. The factor to be prioritized should be the mechanical strength, rather than the dry density of the sample.

Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently. Breast cancer subtyping based on estrogen receptor (ER) status is crucial for determining prognosis and treatment. This study uses metabolomics data from plasma samples to detect metabolite biomarkers that could distinguish ER-positive from ER-negative breast cancers in a non-invasive manner. The dataset includes demographic information, ER status, and metabolite levels from 188 breast cancer patients and 73 healthy controls. Supervised, unsupervised, and ensemble machine learning (ML) algorithms were applied to identify key metabolites associated with ER status, including Support Vector Machines (SVM), Multidimensional Scaling (MS), Logistic Regression (LR), and Ensemble learning. The most informative feature set, containing 28 biomarkers and two demographic factors, achieved an impressive 96% accuracy and an area under the curve (AUC) of 93% using the Logistic Regression model. These results suggest that ML has great promise for identifying specific metabolites linked to ER expression, paving the development of a novel analytical tool that can minimize current lab challenges such as analytical sample handling, subjective results interpretation, biological heterogeneity of the tumor in a non-invasive and efficient manner aiding in more precise diagnosis of breast cancer.

Pancreatic cancer, one of the deadliest cancers worldwide, necessitates improved therapeutics due to its low survival rate (12% in 5 years) and typically late-stage diagnosis [1]. This malignancy tends to present asymptomatically until advanced stages, leading to high rates of metastasis and limiting surgical options [2]. Genetic mutations in key genes like KRAS, CDKN2A, TP53, and SMAD4 are central to pancreatic cancer pathogenesis, driving uncontrolled cell proliferation and making treatment difficult [3]. Current treatment modalities include surgery, chemotherapy, radiation, and emerging immunotherapies. Surgery, particularly the Whipple procedure, offers the only potential cure but is applicable in just 15-20% of cases due to the late diagnosis [4]. Chemotherapy, though commonly used, offers limited long-term survival benefits [5]. Radiation therapy has seen advancements with techniques like stereotactic body radiation therapy (SBRT), which shows promise in reducing toxicity and improving outcomes [6] . Immunotherapy, particularly mRNA vaccines, has demonstrated potential in prolonging recurrence-free survival (>18 months), especially when combined with traditional therapies (13.4 months with surgical resection alone) [7] . Combinations of different treatments have been found to be effective. The challenge of early pancreatic cancer diagnosis mirrors the difficulty of disease management. Prophylactic immunotherapies, like vaccines, could offer a crucial breakthrough for prevention and recurrence reduction. As pancreatic cancer remains difficult to treat effectively, continued research and development in preventative and therapeutic strategies are essential to improving outcomes

Objective:This study aims to evaluate the impact of drug-eluting bead transarterial chemoembolization (DEB-TACE) compared to conventional transarterial chemoembolization (cTACE) in patients with hepatocellular carcinoma (HCC), with a specific focus on liver fibrosis progression. By utilizing propensity score matching (PSM), the study seeks to examine the effects of both treatments on liver fibrosis and survival rates, providing evidence to inform clinical decision-making. Methods:This retrospective analysis included HCC patients who underwent DEB-TACE or cTACE at Xuzhou Cancer Hospital between October 2020 and September 2023. Propensity score matching (PSM) was employed to ensure comparability between the two groups based on baseline characteristics, with a 1:1 matching ratio. The primary endpoints included liver fibrosis markers (such as hyaluronic acid, type III procollagen, type IV collagen, and laminin), liver function trends (ALT, AST, TBIL, ALB), and adverse events. Kaplan-Meier methods were used to evaluate progression-free survival (PFS) and overall survival (OS). Results:After PSM, 92 patients were included (46 in the DEB-TACE group and 46 in the cTACE group). Results demonstrated that the DEB-TACE group showed superior outcomes in reducing liver fibrosis markers (e.g., PC-III, IV-C, and LN) compared to the cTACE group. Additionally, the incidence of nausea, vomiting, and postoperative pain was significantly lower in the DEB-TACE group (p < 0.001). Kaplan-Meier analysis revealed that PFS and OS were significantly longer in the DEB-TACE group compared to the cTACE group (p < 0.05). Multivariate logistic regression analysis further confirmed the independent protective effect of DEB-TACE in reducing liver fibrosis progression (OR = 2.39, p = 0.044). Conclusion:This study confirms the advantages of DEB-TACE in treating patients with intermediate to advanced HCC, particularly in slowing liver fibrosis progression and improving survival outcomes. The use of propensity score matching enhances the reliability of these findings. Future studies should continue to explore the potential of DEB-TACE in broader patient populations to optimize treatment strategies for HCC.

CO2-soluble surfactant foam systems have garnered significant attention in the fields of enhanced oil and gas recovery, environmental protection, and greenhouse gas emission reduction. This review provides a comprehensive explanation of the basic theory of CO2-soluble surfactant foam, the mechanism of enhanced oil recovery, and the classification and application of various CO2-soluble surfactants.The mechanism of enhanced oil recovery by CO2-soluble surfactant foam involves the effective reduction of CO2 fluidity, the decrease in oil-air flow ratio, and the stabilization of the displacement front. Foam plays a vital role in mitigating the issues of channeling and gravity separation often caused by simple CO2 injection. The reduction in gas fluidity can be attributed to the increase in apparent viscosity and trapped gas fraction.Future research should prioritize the development of more efficient and environmentally-friendly CO2-soluble surfactants. It is essential to further explore the advantages and challenges associated with their practical applications in order to maximize their potential impact.

The Influenza A Virus (IAV) represents an enveloped, positive-sense and single-stranded RNA-based virus that infects mammals mainly via the respiratory system, although other bodily systems are also infected and undergo various extents of inflammatory pathogenesis. There are two well-known strains of IAV that cause life-threatening disease in mammals; H1N1 and H5N1, and the first strain caused the 1918 IAV H1N1 pandemic that claimed between 30 and 50 million human lives. Due to the significant ability of IAV to evade important immune recognition, the virus was observed to favour the onset of secondary microbial infections (i.e. bacterial or fungal), as the overall performance of the immune system became transiently weakened during the viral infection. During the IAV H1N1 pandemic, many patients died as a result of bacterial pneumonia, as pathogenic bacteria, such as Streptococcus pneumoniae and Haemophilus influenzae, gained a wider opportunity to colonise and infect vital areas of the lower respiratory tract, and such a phenomenon led to the excessive, prophylactic usage of antibiotics due to the increased levels of panic, which in turn favoured the natural selection of bacteria with genes that became resistant to such antibiotics. Antibiotics might be required for usage solely when bacteria are known to be colonising vital areas of the human body, and this aspect is tricky, as microbial colonisation as such is asymptomatic and screening is consequently rare. Recently, new variants of the avian IAV H5N1 strain were transmitted from live, infected birds to mammals, including humans in some isolated cases, and given that there have already been several zoonotic spillover events overall since the beginning of 2023, we are rapidly approaching the time when a zoonotic spillover into humans will mark the first epidemic outbreak of the avian flu in humans. A lethality rate of approximately 60% was projected by the World Health Organization, as the virus was shown to favour the development of life-threatening hyper-inflammatory responses at the levels of alveolar tissues constituted by Type II pneumocytes. There are hints that novel variants of H5N1 are capable of infecting the intestinal layer, as recently, two dolphins died as a result of ingesting infected birds within the area of the British Isles. IAV is known to suppress the production and transmission of Type I Interferons by expressing various non-structural proteins (NSPs), such as NSP1, which was found to be also packaged into exosomes and transmitted to neighbouring uninfected cells, thereby preventing them from responding to the virus in the first place. Additionally, it was determined that NSP1 induces the apoptosis of the cells it is produced in and the neighbouring ones it enters via induced paracrine signalling, and such an aspect may only emphasise upon the critical role that early innate immune stimulation plays in preventing the development of severe respiratory illness afterward, given the context of increased viral ability of suppressing the production of first-line and second-line signals. A more pronounced rate of innate immune evasion would probably be observed in H5N1 IAV infection than in the infection caused by recent variants of H1N1 IAV. The H5N1 strain of IAV was also found to secrete a higher concentration of NSP1 than SARS-CoV-2, indicating the existence of an association to the greater mortality rate of H5N1 IAV infection. A direct, prophylactic stimulation of the interferon system using a reduced oral or nasal dosage of recombinant anti-inflammatory and anti-viral interferon glycoproteins may represent the most viable approach to prevent an emergence of a life-threatening H5N1 IAV pandemic. A similar non-invasive approach could be developed for a Marburg Virus (MARV) and a Nipah Virus (NiV) infection of humans, as risks of the emergence of a Marburg epidemic and also of a Nipah epidemic may be substantial at this stage as well. Clinical testing of clinical approaches as such could be of critical importance at the moment. Animals could also benefit from related clinical approaches. Somatic natural and adaptive lymphocytes treated with IFN I and III could also constitute a substantial approach of immunisation and heavily favour an indefinite shift in the evolutionary battle between the host organism and microbes of public health concern, as IFN I and III could improve the immunity of T-lymphocytes against HIV infection and even improve the performance of the mentioned types of immune cells during other types of infections. Likewise, a combination of all intellectual and clinical efforts implicating a shift of scientific and medical focus toward natural immunity in vaccine-related research could be a wise method in making the best efforts to prevent or alleviate the effects of a possible future pandemic, given the highly significant and diverse abilities of microbial “intelligence” to effectively hijack the natural immune system, many times causing severe implications upon the quality of the overall immune response against such microbes.

Rapid weight loss strategies (including fasting and dehydration) and weight cycling (losing and gaining weight repeatedly) are acknowledged problems in sports with weight categories, including judo. While extreme fasting, especially if combined with dehydration and intense physical activity, may harm health and development, particularly of children and teenagers engaging in judo competitions, there is substantial evidence for positive health effects of other forms of fasting. Here we aim to provide an updated overview on potential health risks associated with extreme dietary strategies in judo and put them in context with health-promoting fasting approaches. We conclude that the literature on long-term health consequences of fasting in judo are scarce. This applies specifically to the potential association with eating disorders. Many reports highlight short-term risks of rapid weight loss, however, vulnerability and protection factors remain poorly understood. Rigorous scientific studies are needed to disentangle the factors that render fasting in judo healthy or hazardous, considering long-term effects both for somatic and mental health. We argue that better understanding of weight management in judo may be used to prevent health risks for athletes and possibly also to propose novel weight management strategies to overweight individuals.

Text-to-image tasks have gained significant progress, where vivid images are generated from detailed text descriptions. However, existing studies overlook scenarios where the provided text is sparse, neglect the investigation of human preferences, and fail to acknowledge the diversity of aesthetic opinions. To address those issues, we develop a methodology called personalized short-text-to-image generation through aesthetic assessment and human insights. We develop a Personality Encoder (PE) to extract personal information and establish the Big-Five personality traits-based Image Aesthetic Assessment model (BFIAA) for predicting specific human aesthetic preferences. Utilizing the BFIAA model, we fine-tune the Stable Diffusion model to align it more closely with human preferences. Our experiments demonstrate that our BFIAA model can truly reflect human aesthetic preference and the adapted generation model can generate personalized images more preferred by humans.

This research aimed to explore the effects of Silicon (Si) on managing hydrogen peroxide levels, photosynthetic pigment content, nutrient accumulation, and the production of root and shoot dry biomass in salt-stressed sunflower (Helianthus annuus L.) plants. Conducted in a glasshouse, the experiment followed a completely randomized block design in a factorial arrangement (2 × 2) and five replicates. Pots were divided into two groups: non-salt stressed, and salt stressed (100 mM NaCl), both with Si (2 mM as stabilized sodium and potassium silicate) and without Si. The study found that Si effectively reduced hydrogen peroxide concentration and enhanced photosynthetic pigments, nutrient status, and plant growth. The results showed that Si alleviated salt stress effects in sunflower plants by significantly lowering hydrogen peroxide levels and increasing photosynthetic pigments and nutrient accumulation, leading to greater root and shoot dry biomass. These findings indicate that adding Si to the growth medium is crucial for enhancing resistance to salt-induced ionic and osmotic stress, making it a promising strategy for improving crop growth and management in saline conditions.

Wideband signal detection and identification are crucial for military and civilian fields such as communication reconnaissance and spectrum security. This paper systematically sorts out the mainstream technologies of wideband signal detection and identification, and expounds the main current short-wave wideband signal detection and identification work from three perspectives: traditional expert feature methods, combination of expert features and machine learning, and wideband signal detection and identification based on deep learning. Particularly, this paper focuses on the processing methods of current key signals such as short burst signals and frequency hopping signals, as well as the latest deep learning methods in the past five years. Finally, the shortcomings of the existing broadband signal detection and identification methods are summarized, and the future trend is predicted.