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This paper investigates five different different Auto Regressive Moving Average (ARMA) and Generalized Auto Regressive Condition-al Heteroscedacity (GARCH models (GARCH, exponential GARCH or EGARCH, integrated GARCH or IGARCH, Component GARCH or CGARCH and the Glosten-Jagannathan-Runkle GARCH or GJR-GARCH) along with six distributions (normal, Student’s t, GED and their skewed forms), which are used to estimate the price dynamics of the Bulgarian stock index SOFIX. We use the best model to predict how much time it will take, after the latest crisis, for the SOFIX index to reach its historical peak once again. The empirical data cover the period between the years 2000 and 2024, including the 2008 financial crisis and the COVID-19 pandemic. The purpose is to answer which of the five models is the best at analysing the SOFIX price and which distribution is most appropriate. The results, based on the BIC and AIC, show that the ARMA(1,1)-CGARCH(1,1) specification with the Student’s t-distribution is preferred for modelling. From the results obtained, we can confirm that the CGARCH model specification supports a more appropriate description of SOFIX volatility than a simple GARCH model. We find that long-term shocks have a more persistent impact on volatility than the effect of short-term shocks. Furthermore, for the same magnitude, negative shocks to SOFIX prices have a more significant impact on volatility than positive shocks. According to the results, when predicting future values of SOFIX, it is necessary to include both a first-order autoregressive component and a first-order moving average in the mean equation. With the help of 5000 simulations, it is estimated that the chances of SOFIX reaching its historical peak value of 1976.73 (08.10.2007) are higher than 90% at 13.08.2087. Full article

Objectives: We aimed to evaluate and compare the diagnostic capacity of five cognitive screening tests for the diagnosis of mild cognitive impairment (MCI) in patients consulting by memory loss. Methods: A cross-sectional study involving 140 participants with a mean age of 74.42 ± 7.60 years, 87 (62.14%) women. Patients were classified as MCI or cognitively unimpaired according to a comprehensive neuropsychological battery. The diagnostic properties of the following screening tests were compared: Mini-Mental State Examination (MMSE), Addenbrooke’s Cognitive Examination III (ACE-III) and Mini-Addenbrooke (M-ACE), Memory Impairment Screen (MIS), Montreal Cognitive Assessment (MoCA), and Rowland Universal Dementia Assessment Scale (RUDAS). Results: The area under the curve (AUC) was 0.861 for the ACE-III, 0.867 for M-ACE, 0.791 for MoCA, 0.795 for MMSE, 0.731 for RUDAS, and 0.672 for MIS. For the memory components, the AUC was 0.869 for ACE-III, 0.717 for MMSE, 0.755 for MoCA, and 0.720 for RUDAS. Cronbach’s alpha was 0.827 for ACE-III, 0.505 for MMSE, 0.896 for MoCA, and 0.721 for RUDAS. Correlations with Free and Cued Selective Reminding Test were moderate with M-ACE, ACE-III, and MoCA, and moderate for the other tests. The M-ACE showed the best balance between diagnostic capacity and time of administration. Conclusions: ACE-III and its brief version M-ACE showed better diagnostic properties for the diagnosis of MCI than the other screening tests. MoCA and MMSE showed adequate properties, while the diagnostic capacity of MIS and RUDAS was limited. Full article

Social isolation is a global problem with far-reaching consequences. Nevertheless, various solutions can address it. Building social infrastructure is important for preventing isolation. In this study, we aimed to understand the impact of urban infrastructure on social isolation using social surveys and statistical data from South Korea. A multilevel logistic model identified the infrastructure characteristics required to solve social isolation by adding regional-level data to individual-level data. The analysis showed that, at the individual level, gender, age, marital status, and household income were significant, whereas at the regional level, the ratio of single-person households, access to traditional markets, and the capital region status areas were significant. The findings suggest that social infrastructure can impact social isolation. Hence, it is important to plan urban spaces and design infrastructure to help alleviate social isolation. Full article

Maintaining agricultural machinery is crucial for efficient mechanized farming. Specifically, diagnosing faults in rolling bearings, which are essential rotating components, is of significant importance. Domain-adaptive technology often addresses the challenge of limited labeled data from a single source domain. However, information transfer can sometimes fall short in providing adequate relevant details for supporting target diagnosis tasks, leading to poor recognition performance. This paper introduces a novel fault diagnosis model based on a multi-source locally adaptive graph convolution network to diagnose rolling bearing faults in agricultural machinery. The model initially employs an overlapping sampling method to enhance sample data. Recognizing that two-dimensional time–frequency signals possess richer spatial characteristics in neural networks, wavelet transform is used to convert time series samples into time–frequency graph samples before feeding them into the feature network. This approach constructs a sample data pair from both source and target domains. Furthermore, a feature extraction network is developed by integrating the strengths of deep residual networks and graph convolutional networks, enabling the model to better learn invariant features across domains. The locally adaptive method aids the model in more effectively aligning features from the source and target domains. The model incorporates a Softmax layer as the bearing state classifier, which is set up after the graph convolutional network layer, and outputs bearing state recognition results upon reaching a set number of iterations. The proposed method’s effectiveness was validated using a bearing dataset from Jiangnan University. For three different groups of bearing fault diagnosis tasks under varying working conditions, the proposed method achieved recognition accuracies above 99%, with an improvement of 0.30%-4.33% compared to single-source domain diagnosis models. Comparative results indicate that the proposed method can effectively identify bearing states even without target domain labels, showcasing its practical engineering application value. Full article

Cancer is a complex disease that affects millions of people and remains a major public health problem worldwide. Conventional cancer treatments, including surgery, chemotherapy, immunotherapy, and radiotherapy, have limited achievements and multiple drawbacks, among which are healthy tissue damage and multidrug-resistant phenotype onset. Increasing evidence shows that many plants’ natural products, as well as their bioactive compounds, have promising anticancer activity and exhibit minimal toxicity compared to conventional anticancer drugs. However, their widespread use in cancer therapy is severely restricted by limitations in terms of their water solubility, absorption, lack of stability, bioavailability, and selective targeting. The use of nanoformulations for plants’ natural product transportation and delivery could be helpful in overcoming these limitations, thus enhancing their therapeutic efficacy and providing the basis for improved anticancer treatment strategies. The present review is aimed at providing an update on some phytocompounds (curcumin, resveratrol, quercetin, and cannabinoids, among others) and their main nanoformulations showing antitumor activities, both in vitro and in vivo, against such different human cancer types as breast and colorectal cancer, lymphomas, malignant melanoma, glioblastoma multiforme, and osteosarcoma. The intracellular pathways underlying phytocompound anticancer activity and the main advantages of nanoformulation employment are also examined. Finally, this review critically analyzes the research gaps and limitations causing the limited success of phytocompounds’ and nanoformulations’ clinical translation. Full article

In the last few years, blockchain has emerged as a cutting-edge technology whose main advantages are transparency, traceability, immutability, enhanced efficiency, and trust, thanks to its decentralized nature. Although many people still identify blockchain with cryptocurrencies and the financial sector, it has many prospective applications beyond digital currency that can serve as use cases for which traditional infrastructures have become obsolete. Governments have started exploring its potential application to public services provision, as confirmed by the increasing number of adoption initiatives, projects, and tests. As the current public administration is often perceived as slow, bureaucratic, lacking transparency, and failing to involve citizens in decision-making processes, blockchain can establish itself as a tool that enables a process of disintermediation, which can revolutionize the way in which public services are managed and provided. In this paper, we will provide a survey of the main application areas which are likely to benefit from blockchain implementation, together with examples of practical implementations carried out by both state and local governments. Later, we will discuss the main challenges that may prevent its widespread adoption, such as government expenditure, technological maturity, and lack of public awareness. Finally, we will wrap up by providing indications on future areas of research for blockchain-based technologies. Full article

The concept of “creative tourism”, emerging at the century’s start, responds to the “creative turn” in tourist destinations, aligning with the evolving creative class, clusters, and cities. This study employs a bibliometric analysis to examine the evolution and academic focus on creative tourism over the past two decades. Using databases like Scopus and Web of Science, we analyzed key trends, thematic developments, and the impact of creative industries on tourism. Our study reveals significant growth in creative tourism research, emphasizing creativity’s role in enhancing tourism experiences and formulating sustainable, culturally rich models. It underscores the importance of integrating creative industries into tourism and the positive impact on local economies and community development. This analysis not only maps the academic trajectory of creative tourism but also highlights its practical implications for future tourism management and sustainable community development. Full article

Inflammatory cytokines are involved in attention deficit hyperactivity disorder (ADHD), a highly prevalent neurodevelopmental disorder. To quantify the baseline levels of pro- and anti-inflammatory cytokines and their changes after methylphenidate (MPH), a total of 31 prepubertal children with ADHD were recruited and subclassified into only two ADHD presentations—ADHD attention deficit (n = 13) or ADHD combined (n = 18). The children were also screened for oppositional defiant conduct disorder (ODCD) and anxiety disorder. Blood samples were drawn at 09:00 and after 4.63 ± 1.87 months of treatment. Four pro-inflammatory cytokines (interleukin-1beta (IL-1β), IL-5, IL-6, tumor necrosis factor-alpha (TNF-α)) and three anti-inflammatory cytokines (IL-4, IL-10, IL-13) were measured using a Luminex^® assay. For statistics, a factorial analysis was performed in Stata 15.1. Overall, there were no statistically significant differences in the interleukin (IL) values induced by treatment. When grouped by presentation, the differences were present almost exclusively in ADHD-AD, usually with a profile opposite to that observed in ADHD-C, and with interactions between comorbid factors, with IL-1β (p = 0.01) and IL-13 (p = 0.006) being the ones reaching the greatest statistical significance. These differences are probably related to the ODCD factor, and they disappear after treatment. In conclusion, the changes observed in cytokine levels in prepubertal children only in the ADHD-AD presentation are probably related to comorbidities (specifically ODCD) and are mitigated after treatment. Full article

Data mining has achieved great success in air traffic management as a technology for learning knowledge from historical data that benefits people. However, data mining can rarely be embedded into the trajectory optimization process since regular optimization algorithms cannot utilize the functional and implicit knowledge extracted from historical data in a general paradigm. To tackle this issue, this research proposes a novel data mining-based trajectory generation method that is compatible with existing optimization algorithms. Firstly, the proposed method generates trajectories by combining various maneuvers learned from operation data instead of reconstructing trajectories with generative models. In such a manner, data mining-based trajectory optimization can be achieved by solving a combinatorial optimization problem. Secondly, the proposed method introduces a majorization–minimization-based adversarial training paradigm to train the generation model with more general loss functions, including non-differentiable flight performance constraints. A case study on Guangzhou Baiyun International Airport was conducted to validate the proposed method. The results illustrate that the trajectory generation model can generate trajectories with high fidelity, diversity, and flyability. Full article

In recent years, the environmental impact of pharmaceutical residues has emerged as a pressing global concern, catalyzed by their widespread usage and persistence in aquatic ecosystems. Among these pharmaceuticals, acyclovir (ACV) stands out due to its extensive prescription during medical treatments for herpes simplex virus, chickenpox, and shingles, as well as its heightened usage amidst the COVID-19 pandemic. ACV is excreted largely unchanged by the human body, leading to significant environmental release through wastewater effluents. The urgency of addressing ACV’s environmental impact lies in its potential to persist in water bodies and affect aquatic life. This persistence underscores the critical need for effective degradation strategies that can mitigate its presence in aquatic systems. This study focuses on employing sodium hypochlorite as an oxidative agent for the degradation of ACV, leveraging its common use in wastewater treatment plants. Our research aims to explore the kinetics of ACV degradation, identify and characterize its degradation byproducts, and optimize the conditions under which complete degradation can be achieved. By assessing the efficiency of sodium hypochlorite in real wastewater samples, this study seeks to provide practical insights into mitigating ACV contamination in aquatic environments. The novelty of this research lies in its comprehensive approach to understanding the degradation pathways of ACV and evaluating the feasibility of using sodium hypochlorite as a sustainable solution in wastewater treatment. By addressing the environmental concerns associated with ACV and offering practical solutions, this study contributes to the broader goal of sustainable pharmaceutical waste management and environmental stewardship. Full article

Heat dissipation significantly limits semiconductor component performance improvement. Thermal management devices are pivotal for electronic chip heat dissipation, with the enhanced thermal conductivity of materials being crucial for their effectiveness. This study focuses on single-crystal diamond, renowned for its exceptional natural thermal conductivity, investigating diamond microchannels using finite element simulations. Initially, a validated mathematical model for microchannel flow heat transfer was established. Subsequently, the heat dissipation performance of typical microchannel materials was analyzed, highlighting the diamond’s impact. This study also explores diamond microchannel topologies under high-power conditions, revealing unmatched advantages in ultra-high heat flux density dissipation. At 800 W/cm² and inlet flow rates of 0.4–1 m/s, diamond microchannels exhibit lower maximum temperatures compared to pure copper microchannels by 7.0, 7.2, 7.4, and 7.5 °C, respectively. Rectangular cross-section microchannels demonstrate superior heat dissipation, considering diamond processing costs. The exploration of angular structures with varying parameters shows significant temperature reductions with increasing complexity, such as a 2.4 °C drop at i = 4. The analysis of shape parameter k_i indicates optimal heat dissipation performance at k_i = 1.1. This research offers crucial insights for developing and optimizing diamond microchannel devices under ultra-high-heat-flux-density conditions, guiding future advancements in thermal management technology. Full article

Background: The long-term effect of the 2019 coronavirus (COVID-19) pandemic is not fully known. Severe cases of COVID-19 have resulted in disability that can be assessed in a biopsychosocial manner with the International Classification of Functioning, Disability and Health with the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) questionnaire. This study aimed to evaluate the long-term effects on disability of COVID-19 three years after post-acute rehabilitation using WHODAS 2.0. Methods: This single-center cohort study included patients with severe COVID-19 who underwent immediate post-discharge post-acute rehabilitation intervention. Three years later, patients were assessed via telephone using the WHODAS 2.0 questionnaire. Results: Of the 69 patients identified in the hospital database, 27 responded. A total of 16 patients refused to respond due to emotional distress. The mean age was 63.4 ± 8.6 years, 81.5% were independent in the community, 55.3% had been previously admitted to the ICU, and the median rehabilitation hospitalization duration was 18 (11.5,24) days. Comorbidities included type 2 diabetes mellitus (DM) (55.5%), grade 2 high blood pressure (62.9%), pressure ulcers (37%), peripheral neurologic deficits (62.9%), and central neurological deficits (14.8%). ICU admission was significantly correlated with advanced rehabilitation needs (measured by the level of the rehabilitation (p < 0.01) and longer hospitalizations (measured by total days in the hospital (p< 0.001). The overall disability score was 35.09%, significantly influenced by DM and central neurological deficits. Conclusions: Central neurological deficits and DM are associated with higher disability scores. Tailored rehabilitation programs, ongoing medical assessment, integrated care models, and patient education are essential for improving long-term outcomes after COVID-19 disease. Full article

Alveolar type 2 epithelial (AT2) cells synthesize surfactant protein C (SPC) and repair an injured alveolar epithelium. A mutated surfactant protein C gene (Sftpc^L184Q, Gene ID: 6440) in newborns has been associated with respiratory distress syndrome and pulmonary fibrosis. However, the underlying mechanisms causing Sftpc gene mutations to regulate AT2 lineage remain unclear. We utilized three-dimensional (3D) feeder-free AT2 organoids in vitro to simulate the alveolar epithelium and compared AT2 lineage characteristics between WT (C57BL/6) and Sftpc^L184Q mutant mice using colony formation assays, immunofluorescence, flow cytometry, qRT-PCR, and Western blot assays. The AT2 numbers were reduced significantly in Sftpc^L184Q mice. Organoid numbers and colony-forming efficiency were significantly attenuated in the 3D cultures of primary Sftpc^L184Q AT2 cells compared to those of WT mice. Podoplanin (PDPN, Alveolar type 1 cell (AT1) marker) expression and transient cell count was significantly increased in Sftpc^L184Q organoids compared to in the WT mice. The expression levels of CD74, heat shock protein 90 (HSP90), and ribosomal protein S3A1 (RPS3A1) were not significantly different between WT and Sftpc^L184Q AT2 cells. This study demonstrated that humanized Sftpc^L184Q mutation regulates AT2 lineage intrinsically. This regulation is independent of CD74, HSP90, and RPS3A1 pathways. Full article

The literature shows that both in laboratory and in industrial conditions, the photocatalytic oxidation method copes quite well with degradation of most environmental toxins and pathogenic microorganisms. However, the effective utilization of photocatalytic processes for environmental decontamination and disinfection requires significant technological advancement in both the area of semiconductor material synthesis and its application. Here, we focused on the presence and “photocatalytic capability” of photocatalysts among soil minerals and their potential contributions to the environmental decontamination in vitro and in vivo. Reactions caused by sunlight on the soil surface are involved in its normal redox activity, taking part also in the soil decontamination. However, their importance for decontamination in vivo cannot be overstated, due to the diversity of soils on the Earth, which is caused by the environmental conditions, such as climate, parent material, relief, vegetation, etc. The sunlight-induced reactions are just a part of complicated soil chemistry processes dependent on a plethora of environmental determinates. The multiplicity of affecting factors, which we tried to sketch from the perspective of chemists and environmental scientists, makes us rather skeptical about the effectiveness of the photocatalytic decontamination in vivo. On the other hand, there is a huge potential of the soils as the alternative and probably cheaper source of useful photocatalytic materials of unique properties. In our opinion, establishing collaboration between experts from different disciplines is the most crucial opportunity, as well as a challenge, for the advancement of photocatalysis. Full article

The demand for meat alternatives in different forms is increasing due to consumers’ awareness of climate change and the health benefits of plant-based ingredients compared to animals. However, current alternatives on the market do not fulfil consumers’ acceptance for taste and texture. Hence, different physical and biological processes, such as thermal treatment and fermentation, need to be investigated. This study reveals that the thermal treatment of legume flours (soy, pea and lentil) prior to single-strain fermentation with Leuconostoc citreum TR116 has a major impact on acidification, colour, texture and sensory properties due to the pregelatinisation of starch and denaturation of proteins. The thermal treatment of soy flour resulted in liquification, and it could not be used as a fermentation substrate. However, non-heat-treated soy flour was fermented for comparison. The highest total titratable acidity (TTA) was determined in fermented pea flour (PF) and fermented lentil flour (LF) after 48 h with 24.35 ± 0.29 mL 0.1 M NaOH/10 g and 24.98 ± 0.33 mL 0.1 M NaOH/10 g, respectively. Heat treatment prior to fermentation led to a reduction in TTA by 20 mL 0.1 M NaOH/10 g for both PF and LF. The loss of colour pigments during thermal treatment led to a lighter colour of the spreadable alternatives. Moreover, a harder texture ( +13.76 N in LF; +15.13 N in PF) and a lower adhesiveness (−0.88 N in LF; −0.43 N in PF) were detected in spreadable meat alternatives that were treated with heat prior to fermentation. Cohesiveness was decreased by thermal treatment, and fermentation did not impact it. Fermentation without pre-heat treatment increased adhesiveness by 4.37 N in LF and by 2.36 N in PF—an attribute typical for spreadable meat. Descriptive sensory analysis showed that thermal treatment significantly decreased bitterness but increased crumbliness and reduced juiciness. On the other hand, fermentation without pre-heat treatment mainly influenced flavour by increasing fruitiness and decreasing beaniness, earthiness and off-flavours. In summary, thermal treatment prior to fermentation is powerful in reducing legume-typical off-flavours but is not suitable for the development of spreadable meat alternatives due to texture changes. However, this process can be very beneficial when producing sausage-like alternatives. Full article