Search Results (1,084)

Background/Objectives: Dementia, characterised by cognitive decline, significantly impacts language abilities. While the risk of dementia increases with age, it often manifests years before clinical diagnosis. Identifying early warning signs is crucial for timely intervention. Previous research has demonstrated that changes in language, such as reduced vocabulary diversity and simpler sentence structures, may be observed in individuals with dementia. This study investigates the potential of linguistic analysis to detect early signs of cognitive decline by examining the writing of Sir Terry Pratchett, a renowned author diagnosed with Posterior Cortical Atrophy (PCA), typically a form of dementia caused by Alzheimer’s disease. Methods: This study analysed 33 Discworld novels by Terry Pratchett, comparing linguistic features before and after a potential turning point identified through analysis of adjective type-token ratios (TTR). Results: A significant decrease in lexical diversity (TTR) was observed for nouns and adjectives in later works. Total wordcount increased, while lexical diversity decreased, suggesting a shift towards simpler language. This shift coincided with a decrease in adjective TTR below a defined threshold, occurring approximately ten years before Pratchett’s formal diagnosis. Conclusions: These findings suggest that subtle changes in linguistic patterns, such as decreased lexical diversity, may precede clinical diagnosis of dementia by a considerable margin. This research highlights the potential of linguistic analysis as a valuable tool for early detection of cognitive decline. Further research is needed to validate these findings in larger cohorts and explore the specific linguistic markers associated with different types of dementia. Full article

Mathematical models for infectious diseases, particularly autonomous ODE models, are generally known to possess simple dynamics, often converging to stable disease-free or endemic equilibria. This paper investigates the dynamic consequences of a crucial, yet often overlooked, component of pandemic response: the saturation of public health testing. We extend the standard SIR model to include compartments for ‘Confirmed’ (C) and ‘Monitored’ (M) individuals, resulting in a new SICMR model. By fitting the model to U.S. COVID-19 pandemic data (specifically the Omicron wave of late 2021), we demonstrate that capacity constraints in testing destabilize the testing-free endemic equilibrium ($E_1$). This equilibrium becomes an unstable saddle-focus. The instability is driven by a sociological feedback loop, where the rise in confirmed cases drive testing effort, modeled by a nonlinear Holling Type II functional response. We explicitly verify that the eigenvalues for the best-fit model satisfy the Shilnikov condition (${\lambda }_u>{\lambda }_s$), demonstrating the system possesses the necessary ingredients for complex, chaotic-like dynamics. Furthermore, we employ Stochastic Differential Equations (SDEs) to show that intrinsic noise interacts with this instability to generate ’noise-induced bursting,’ replicating the complex wave-like patterns observed in empirical data. Our results suggest that public health interventions, such as testing, are not merely passive controls but active dynamical variables that can fundamentally alter the qualitative stability of an epidemic. Full article

Existing buildings consume a large portion of the total current energy production, especially in developing countries such as Egypt. Increasing energy demand, coupled with decreasing availability and increasing cost of conventional non-renewable energy resources, have encouraged a “building green” retrofit trend in order to maximize the energy performance of the built environment. This paper outlines the development of an Energy Retrofit Decision-Support System (ERDSS) for hot, arid climates that models building retrofit scenarios and determines the impact of each retrofit measure on the overall energy consumption of a proposed building retrofit program. The methodology combines building an energy simulation with a database-driven, budget-constrained optimization framework based on the Savings-to-Investment Ratio (SIR) to evaluate and prioritize retrofit measures. In addition, ERDSS determines the impact of each retrofit measure on the overall energy consumption of a proposed building retrofit program, ranks the retrofit measures according to their Savings-to-Investment Ratio (SIR) and uses optimization to develop a suggested retrofit program for a given budget. ERDSS is applied on a case study of an education building in New Cairo, Egypt, in order to illustrate the performance of the framework. Results show that savings for the commissioned retrofit, standard retrofits, and deep retrofits reached 15 percent, 35 percent, and 45 percent, respectively. Full article

Objectives: Among people with HIV (PWH), the epidemiology of malignant tumors has shifted from AIDS-defining malignancies (ADMs) to non-AIDS-defining malignancies (NADMs). This study examined temporal changes in the standardized incidence ratio (SIR) of malignant tumors in an HIV cohort in Japan. Methods: A retrospective cohort study was conducted of 3793 men treated for HIV at Osaka National Hospital between 2007 and 2024. Diagnoses of malignant tumors were identified from medical records and the expected numbers of cases were calculated using cancer incidence rates for the general male population of Japan. SIRs and 95% confidence intervals (CIs) were calculated and temporal changes across four periods (2007–2011, 2012–2016, 2017–2020, and 2021–2024) were evaluated using the p for trend. Results: The overall SIR for malignant tumors decreased from 5.12 (95% CI: 4.02–6.43) in 2007–2011 to 0.86 (95% CI: 0.64–1.14) in 2021–2024, mainly owing to a decline in ADMs (SIR: 111.93 to 5.70), including Kaposi’s sarcoma (SIR: 4269.39 to 547.26) and AIDS-related lymphoma (SIR: 62.18 to 3.13). The overall SIR for NADMs was similar to that of the general population (1.04; 95% CI: 0.89–1.22), and decreased from 1.64 to 0.69, but the risks of anal cancer (SIR 40.63) and oral/pharyngeal cancer (SIR 3.16) remained high. Conclusions: Among men with HIV in Japan, the overall risk of ADMs and NADMs has decreased; however, the risk of specific NADMs remains high. Cancer prevention strategies for PWH need to focus on high-risk NADMs. Full article

Obesity is among the top contributing factors for non-communicable chronic disease development and has attained menacing global proportions, affecting approximately one of eight adults. Phytochemicals that support energy metabolism and prevent obesity development have been the subject of intense research endeavors over the past several decades. Cycloastragenol is a natural triterpenoid compound and aglycon of astragaloside IV, known for activating telomerase and mitigating cellular aging. Here, we aim to characterize the effect of cycloastragenol on lipid metabolism in a glucose-induced obesity model in Caenorhabditis elegans. We assessed the changes in the body length, width, and area in C. elegans maintained under elevated glucose through automated WormLab system. Lipid accumulation in the presence of either cycloastragenol (100 μM) or orlistat (12 μM), used as a positive anti-obesity control drug, was quantified through Nile Red fluorescent staining. Furthermore, we evaluated the changes in key energy metabolism molecular players in GFP-reporter transgenic strains. Our results revealed that cycloastragenol treatment decreased mean body area and reduced lipid accumulation in the C. elegans glucose-induced model. The mechanistic data indicated that cycloastragenol suppresses the nuclear hormone receptor family member NHR-49 and the delta(9)-fatty-acid desaturase 7 (FAT-7) enzyme, and activates the 5′-AMP-activated protein kinase catalytic subunit alpha-2 (AAK-2) and the protein skinhead 1 (SKN-1) signaling. Collectively, our findings highlight that cycloastragenol reprograms lipid metabolism by down-regulating the insulin-like receptor (daf-2)/phosphatidylinositol 3-kinase (age-1)/NHR-49 signaling while simultaneously enhancing the activity of the AAK-2/NAD-dependent protein deacetylase (SIR-2.1) pathway. The anti-obesogenic potential of cycloastragenol rationalizes further validation in the context of metabolic diseases and obesity management. Full article

In this paper, a dual-band bandpass filter with a wide upper stopband is proposed and designed by integrating stepped-impedance resonators (SIRs) and a low-pass filter. The operating center frequencies of the designed dual-band filter are targeted at 2.5 GHz and 5.35 GHz, respectively, to meet the frequency requirements of typical wireless communication scenarios. Notably, the filter achieves a wide upper stopband ranging from 6.1 GHz to 25 GHz, which can effectively suppress unwanted high-frequency interference signals within this frequency range and avoid mutual interference with other high-frequency communication systems. And it exhibits insertion losses of 0.12 dB (2.5 GHz) and 0.6 dB (5.35 GHz) in its two passbands to ensure minimal useful signal attenuation. The simulation results agree well with the measured results. Full article

We explore a rigorous formulation of agent-based SIR epidemic dynamics as a discrete-state Markov process, capturing the stochastic propagation of infection or an invading agent on networks. Using indicator functions and corresponding marginal probabilities, we derive a hierarchy of evolution equations that resembles the classical BBGKY hierarchy in statistical mechanics. The structure of these equations clarifies the challenges of closure and highlights the principal problem of systemic complexity arising from stochastic but generally not fully chaotic interactions. Monte Carlo simulations are used to validate simplified closures and approximations, offering a unified perspective on the interplay between network topology, stochasticity, and infection dynamics. We also explore the impact of lockdown measures within a networked agent framework, illustrating how SIR dynamics and structural complexity of the network shape epidemic with propagation of the COVID-19 pandemic in Northern Italy taken as an example. Full article

Aim: To explore the association between urinary stone cultures and infectious complications following PCNL. Materials and Methods: An observational case–control study was conducted in patients undergoing PCNL. The assessment included demographic parameters, medical history, urinalysis, and urine culture and blood testing. Pre-operatively, urinary stone samples were collected for cultures. Post-operatively, patients were observed for infectious complications such as fever and/or SIRS. Patients were divided into two groups based on the presence or absence of infected renal calculi. Patient characteristics, stone factors, and intra-operative and post-operative findings were studied in relation to stone culture. Descriptive statistics was used to present the data and the SPSS software was used for analysis. Results: From December 2023 to March 2025, a total of 126 patients were included in the study. A total of 16 patients (12.6%) had a positive stone culture. Statistical significance was found upon the comparison of stone culture with gender (p = 0.046), chronic kidney disease (p = 0.002), pre-operative urine culture (p = 0.001), pre-operative haemoglobin (g/dL) (<0.001), pre-operative S. creatinine (mg/dL) (p = 0.038), stone volume (mm³) (p = 0.012), CROES score (p = 0.023), SIRS (p = 0.001), and AKI (p = 0.021). Conclusions: Infected renal calculi identified by positive stone cultures were strongly associated with infective complications such as fever and SIRS following PCNL. E. Coli was the dominant bacteria present in both bladder urine and renal stone culture. The occurrence of infectious complications despite the administration of pre-operative antibiotics highlights the antibiotic resistance patterns noted among the cultured bacteria. The pre-operative factors identified to be associated with a positive stone culture could potentially be used for predicting infected stones, thereby improving outcomes. Full article

Background/Objectives: Acute Pancreatitis (AP) is an unpredictable inflammatory disease associated with high morbidity and significant mortality, particularly in severe forms. Early death is primarily linked to Systemic Inflammatory Response Syndrome (SIRS) and Multi-Organ Failure (MOF). The objective of this study was to identify objective clinical and laboratory predictors of early and one-year mortality in AP patients and to evaluate the prognostic accuracy of commonly used severity scoring systems. Methods: This prospective, observational study enrolled 50 adult patients admitted to the Intensive Care Unit (ICU) at the University Hospital Center Bežaniska Kosa. Patients with chronic pancreatitis, trauma-induced AP, or late presentation were excluded. Severity scores (APACHE II, BISAP, Ranson, Pancreas) and biomarkers (C-reactive protein, Procalcitonin) were collected at admission (0 h) and dynamically at 48 h, 72 h and day 7. Endpoints were early (in-hospital) and one-year mortality. Results: Overall mortality was 16% (n = 8). Mortality was significantly associated with sepsis/septic shock (p < 0.001), severe AP (p = 0.001), prolonged mechanical ventilation, and ICU stay. At admission, APACHE II (AUROC 0.813) and BISAP (AUROC 0.807) showed good accuracy. Reassessment at 48 h markedly improved prediction: APACHE II achieved excellent value (AUROC 0.917), and the Ranson score became a strong predictor (p < 0.001). Procalcitonin (PCT) was identified as a significant and superior predictor of mortality from 48 h onwards (p < 0.001), outperforming CRP. One-year survival was significantly shorter among patients with sepsis, septic shock, severe AP, and prolonged ICU stay. Conclusions: Dynamic assessment using clinical scoring systems, particularly APACHE II and BISAP within the first 48 h, provides reliable mortality prediction in acute pancreatitis. The presence of sepsis, severe disease, and the need for prolonged organ support are key mortality determinants. Serial PCT monitoring offers sensitive, incremental value for risk stratification and guiding intensive care decisions in both short- and long-term outcomes. Full article

Inflammatory diseases are common in companion dogs. Although white blood cell (WBC) count and C-reactive protein (CRP) are routinely used to assess systemic inflammation, their individual prognostic value remains limited. The erythrocyte sedimentation rate (ESR), reflecting red blood cell aggregation driven by plasma proteins, has long been applied in human medicine as both an inflammatory and prognostic marker. This study evaluated the prognostic utility of ESR in dogs, including clinically healthy and diseased populations. Associations between ESR, other inflammatory markers, and age were examined, and its role as an independent predictor of mortality and optimal clinical cut-off were determined. A subgroup of dogs meeting the systemic inflammatory response syndrome (SIRS) criteria were also analyzed to assess the latter’s usefulness in acute settings. A total of 350 dogs were enrolled: 241 diseased and 109 healthy. ESR was measured using an automated analyzer. Receiver operating characteristic (ROC) curve analysis, expressed as the area under the curve (AUC), evaluated diagnostic accuracy, followed by Kaplan–Meier survival and Cox proportional hazard analyses. ESR values were significantly higher in the disease group than in the healthy group (p < 0.0001). ESR showed fair to good prognostic accuracy for mortality in both the overall cohort (AUC = 0.776 [95% CI: 0.709–0.842]) and the SIRS subgroup (AUC = 0.846 [95% CI: 0.747–0.946]). An ESR cut-off of 18 mm/h was associated with mortality in SIRS dogs with 87.5% specificity. In the multivariate analysis, ESR showed an independent association with mortality (hazard ratio 1.013 [95% CI: 1.004–1.022], p = 0.004). These findings support ESR as a practical and independent prognostic marker for risk stratification in dogs with systemic inflammation. Full article

This study is one of the first comprehensive assessments of soil carbon dynamics on the Black Sea coast of Russia, focusing on the role of soils in the terrestrial carbon cycle and the greenhouse gas balance of sub-Mediterranean ecosystems. Our integrated approach combined soil classification with the analysis of the distribution of organic and inorganic carbon, as well as the measurement of microbial biomass and respiration. Soil respiration components, including substrate-induced respiration (SIR) and basal respiration (BR), as well as greenhouse gas (carbon dioxide (CO₂) and methane (CH₄)) dynamics, were evaluated using a combination of laboratory and field measurements. Our results revealed significant differences between natural Rendzic Leptosols and terraced Skeletic Rendzic Leptosols (Technic and Transportic types). The latter contained higher organic carbon stocks (up to 25 kg m⁻²) associated with buried humus horizons, whereas the former were dominated by inorganic carbon accumulation. Microbial biomass carbon (MBC) ranged from 113 to 1119 µg C g⁻¹ of soil and decreased with depth. Basal respiration averaged 0.39 ± 0.30 µg C–CO₂ g⁻¹ h⁻¹. CO₂ emissions were strongly correlated with soil temperature (r = 0.65, p < 0.05) and negatively correlated with soil moisture, reflecting the predominant influence of abiotic factors. Seasonal chamber observations confirmed that these soils consistently function as CH₄ sinks, with negative CH₄ fluxes recorded across all seasons. Thus, Rendzic Leptosols on the Black Sea coast serve as significant CO₂ sources and stable CH₄ sinks simultaneously, and anthropogenic terracing enhances their potential for organic carbon sequestration. These findings refine our understanding of the carbon balance in sub-Mediterranean forest soils and highlight their dual role in greenhouse gas dynamics under changing climate conditions. Full article

In continuous-variable quantum key distribution (CV-QKD) systems, information reconciliation (IR) is a crucial step that significantly affects the secret key rate (SKR). The fixed-rate error-correcting codes used in IR are highly sensitive to changes in the signal-to-noise ratio (SNR) and cannot maintain a high reconciliation efficiency in practical CV-QKD systems. To address this issue, we first propose a rate-adaptive IR protocol, namely Threshold-based IR (TIR), which changes the code rate of low-density parity-check (LDPC) codes by selectively revealing bits with lower reliability and adjusting their log-likelihood ratios (LLRs). Then, we propose a rate-adaptive IR protocol, namely Sorting-based IR (SIR), which not only adjusts the code rate according to variations in SNR, but also enables the CV-QKD systems to achieve high reconciliation efficiency over a wide range of SNRs. Furthermore, we perform an analysis of the protocols in terms of code rate, reconciliation efficiency, and complexity. The simulation results demonstrate that the proposed protocols outperform other rate-adaptive IR protocols, achieving a reconciliation efficiency higher than 98.5% in the SNR range below −20 dB and maintaining a certain SKR in long-distance transmission. Full article

With the development of the internet and the increasing maturity of social media ecosystems, online collective actions within digital social networks have become more frequent and exhibit new patterns. Research on the mechanisms and governance of online collective action has become a crucial aspect of corporate crisis management. This study constructs an online social network with scale-free (BA) characteristics, defines individual properties and interaction rules based on the SIR model, and simulates the outbreak and intervention of online collective actions. The findings indicate that netizens with similar cognitions spontaneously form virtually clustered groups under the influence of triggering events, progressing through emotional arousal, emotional expression, and emotional mobilization, ultimately leading to large-scale online collective action. Collective actions initiated by opinion leaders tend to be more widespread, sudden, and persistent. To mitigate online collective actions, companies should enhance the transparency of core event information, promptly address the demands of action groups, soothe public sentiment, respond to societal concerns, and strengthen guidance over opinion leaders in public discourse. Full article

The modern world has had a long and uneasy relationship with the nostalgic past, with the line between the harmless and the harmful in this relationship often difficult to parse. This article looks at a particular microcosm of nostalgic medievalism in nineteenth century popular culture—selections from the work of prominent editorial cartoonist Sir John Tenniel in Punch that combine gothic imagery with depictions of modern science and technology—through the literary critical theoretical framework of nostalgia theory, connecting it with strong societal forces in his time. Full article

The outbreaks of large-scale epidemics, such as COVID-19 in 2019–2022, challenge modelers. Beside the effect of the incubation period of the virus, the delay property of detection should be also stressed. This kind of memory effect affects the entire change rate, which cannot be reflected by the conventional instantaneous derivative. The fractional derivative (FD) meets this request to some extent. Yet the shortcoming of it limits its usage. Through a strict modeling approach, a new susceptible–infective–removed (SIR) model with the memory-dependent derivative (MDD) has been constructed. The numerical simulations indicate that (1) the neglecting of the incubation period may underestimate the number of susceptible individuals and overestimate the infected ones; (2) the neglecting of the treatment period may badly overestimate the removed individuals; (3) the consequence of tardy detection intervention may be very serious, and the infectious rate may increase rapidly with a postponed peak time; and (4) the SIR model with the FD yields bad estimations, not only in the primary stage but also in the subsequent evolution. Due to the reasonability of the new SIR model with the MDD, it is suggested to epidemic researchers. Full article