The tambaqui Colossoma macropomum is the main species of edible fish originating from fish farming in the Amazon region. This study aimed to determine and compare the hematological and biochemical parameters of tambaqui from fish farms in municipalities in the Metropolitan Region of Manaus, Amazonas, Brazil. Two fish farms were sampled in a semi-excavated pond-type breeding system in each of the five towns investigated (Presidente Figueiredo, Manaus, Iranduba, Manacapuru and Novo Airão), totaling ten breeders. On each farm, ten specimens were captured, totaling 100 animals. Blood was collected by caudal puncture, and hematological and biochemical parameters were determined using the methodology described for teleosts fish. For the erythrogram in the variables of hematocrit, hemoglobin concentration and erythrocytes, significant differences were observed in Iranduba and Novo Airão, demonstrating indications of anemic processes and dehydration. For plasma biochemistry, low levels were observed in fish from Iranduba and Novo Airão. High values in lipid compounds were found in tambaqui from Manacapuru. High intraspecific variation was found in the leukogram and thrombogram, which determined similarities between tambaqui from different farms and municipalities. On the other hand, fish from Manacapuru have an inappropriate diet, indicated by the high levels of cholesterol and triglycerides found in the blood.

We demonstrate how a rigorous mathematical approach can be used to extract a current CMB temperature of 2.7276 ±0.0723 K from the 580 type Ia supernova data points in the Union2 database. Using redshift formula: z = Sqrt(Rh/R_t) − 1, incorporated into our new CMB redshift prediction redshift formula, we find that the above current CMB temperature value is a remarkably good match for this particular data set. In addition, we can alternatively start out with the measured current CMB temperature and extract the Hubble constant from all 580 supernovae. We then get an estimated Hubble constant of H0 = 66.8711+0.0019 km/s/Mpc when using the CMB temperature from the recent Dhal et al study [1] in combination with redshifts from all 580 supernovae. Furthermore, we get an estimated Hubble constant value of H_0 = 66.8943+0.0287 km/s/Mpc when using the CMB temperature measured by Fixsen [2]. In summary, our simple model essentially perfectly matches all 580 type Ia supernova redshifts while extracting H_0 or T_0 values. The Hubble constant we extract by this method fits very well with the Hubble constant extracted from the CMB by other studies. We believe that our new approach likely solves the Hubble tension problem, at least inside R_h = ct cosmology.

Hepatocellular carcinoma (HCC) development is associated with altered modifications in DNA methylation, changing transcriptional regulation. Emerging evidence indicates that DNA methyltransferase 1 (DNMT1) plays a key role in carcinogenesis process. This study aimed to investigate how pirfenidone (PFD) modifies this pathway and the effect generated by the association between c-Myc expression and DNMT1 activation. Rats F344 were used for HCC development using 50 mg/kg of diethylnitrosamine (DEN) and 25 mg/kg of 2-aminofluorene (2-AAF). HCC/PFD group received simultaneous doses of 300 mg/kg of PFD. All treatments lasted 12 weeks. On the other hand, HepG2 cells were used to evaluate the effects of PFD in restoring DNA methylation in the presence of the inhibitor 5-Aza. Histopathological, biochemical, immunohistochemical, and western blot analysis were carried out and our findings showed that PFD treatment reduced the amount and size of tumors along with decreased Glipican-3, β-catenin, and c-Myc expression in nuclear fractions. Also, this treatment improved lipid metabolism by modulating PPARγ and SREBP1 signaling. Interestingly, PFD augmented DNMT1 and DNMT3a protein expression, which restores global methylation, both in our in vivo and in vitro models. In conclusion, our results suggest that PFD could slow down HCC development by controlling DNA methylation.

Infant mortality remains a major global concern. Sudden unexpected death in infancy (SUDI) is reported globally and in the Western Cape of South Africa it accounted for 40% of all infant deaths between 2012 and 2016. Research highlighting molecular typing of respiratory viruses in SUDI cases is lacking. A total of 116 PCR-positive human rhinovirus (HRV) and respiratory syncytial virus (RSV) swab samples collected from the lungs and trachea of SUDI cases admitted to Tygerberg Medico-legal Mortuary in Cape Town between 2015 and 2019 were included and underwent sequencing and phylogenetic analysis. Three distinct HRV species were identified; HRV-A (n=28), HRV-C (n=11), and HRV-B (n=4), including eight HRV-A, seven HRV-C and one HRV-B genotypes. For RSV, both RSV-A (n=5) and -B (n=5) were detected, but no RSV-A. After amino acid alignment indicating 20 amino acid duplication and nine substitutions, two BA9 genotypes were confirmed. This study describes the first molecular and phylogenetic characterisation of respiratory viruses in SUDI cases in South Africa. The rapid decline in viral viability in post-mortem samples and the retrospective study design employed for the current study did not allow for any correlations between viral genotypes and cause of death and future prospective studies should investigate temporality and specific viral strains associated with clinical disease severity.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Micro satellites must survive severe mechanical conditions during their launch phase. Therefore, structural design requirements are imposed on the micro satellites. These requirements are the strength requirement and the stiffness requirement. Usually, the structural design of a micro satellite is performed using the internal stress analysis and the natural frequency analysis, which are based on a Finite Element Method (FEM). The validity of this structural design is evaluated through vibration tests. In an early stage of development, which has a FEM model of a satellite in the process of creation, presumption of the natural frequency of a satellite may be difficult. In this study, a simple method for determining the longitudinal and lateral minimum natural frequencies of the micro satellites during the ascent phase was clarified. The structure of the micro satellites used in this research is made of aluminum alloy, and they have a monocoque structure. The Young's modulus and moment of inertia of area used to calculate the minimum natural frequencies were determined using the area ratio of the monocoque structure to the entire satellite. When this method is used, the estimated minimum natural frequencies of the longitudinal direction and the lateral direction are in agreement with the measured values acquired by the vibration tests. In order to shorten the process of micro satellites development, this paper describes a practical estimation method of the minimum natural frequency for micro satellites.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

Telerehabilitation is an appealing service delivery option for optimising recovering. Internationally, the equity of telerehabilitation services for people from culturally and linguistically diverse (CALD) backgrounds has been questioned. Using a 31-item survey, our study explored the access, readiness, and willingness of 260 patients to use allied health telerehabilitation services for adults receiving interventions from a large tertiary health service located in Sydney, Australia. Overall, 72% patients reported having access to technology, 38% met our readiness criteria, and 53% reported willingness to engage in telerehabilitation. There were no difference in access, readiness and willingness to engage in telerehabilitation between patients from CALD and non-CALD backgrounds. Age was the only factor that influenced access, readiness and willingness to engage in telerehabilitation. Past experience of telerehabilitation was related to willingness, but not access or readiness. Findings highlight the importance of ensuring positive patient experiences to promote ongoing willingness to use telerehabilitation. Efforts are needed to improve patients’ digital health literacy, especially patients from older age groups, to ensure equitable access to telerehabilitation services.

Childhood obesity has become a global epidemic, with significant increases in prevalence over recent decades. While excessive calorie consumption and physical inactivity are known factors, emerging research highlights the role of Endocrine-Disrupting Chemicals (EDCs), particularly obesogens, in obesity's pathogenesis. This review explores the historical context of the environmental obesogens hypothesis, their sources, mechanism of action, impact on prenatal and postnatal development and epigenetics. Additionally, it discusses the long-term consequences of childhood obesity and proposes prevention strategies that will mitigate the negative health effects. Obesogens were found to disrupt hormonal balance and metabolic processes through various mechanisms such as altering gene expression, hormonal interference, and inflammation. Especially significant, was exposure during critical windows of development which correlates with increased risk of obesity in childhood or adolescence. Long-term effects of childhood obesity include chronic health conditions and psychosocial issues. A comprehensive approach is necessary to address childhood obesity, encompassing genetic, environmental, and lifestyle factors. Prevention strategies should focus on reducing obesogens exposure, promoting healthy lifestyles, and implementing regulatory policies. Future research should investigate obesogens-diet interactions, microbiome impacts, and combined obesogens effects. Long-term human studies are also crucial for validating findings from animal models and allow for inform decision-making to combat the obesity pandemic.

In the last years, advances in materials engineering based on adaptive electronics have found a new paradigm to optimize drawbacks in signal processing. A two-layer MnO/ZnO:Zn heterostructure envisioned for frequency adaptive electronic signal processing is synthesized by sputtering where the use of internal states allows reconfigurability to obtain new operating modes at different frequency input signals. An X-Ray Diffraction (XRD) is performed on each layer, MnO:Mn had a cubic and ZnO:Zn a hexagonal structure with preferential growth in [111] and [002] directions respectively. It is determined that the coupling in this heterojunction is compatible with a mismatch less 1 % due texture in each layer which implies a low number of defects. An electrical characterisation with an oscilloscope and signal generator was carried out to obtain the time-response signals and current-voltage (I-V) curves where no degradation is detected when changing from a range of frequencies (100 Hz – 1 MHz). An equivalent circuit is proposed to explain the effects in the interface. Finally, the MnO/ZnO:Zn heterojunction delivers states that are stable, repeatable, and reproducible and it demonstrates how the interaction of the materials can be used in adaptive device applications applying frequencies and internal states as to create new and innovative design schematics, reducing the numbers of components/connections in a system for future sustainable electronics.

Mutual exclusion algorithms are at the heart of concurrent, distributed/parallel, real-time and operating systems. It is well-known that such algorithms are very difficult to analyze and in the literature different conjectures about starvation-freedom and the number of by-passes (also said the overtaking factor), which in turn affects the (hopefully) bounded waiting time that a process competing for entering the critical section has to suffer before accessing the shared resource, have been formulated for specific algorithms. This paper proposes a novel modelling approach based on Timed Automata and the Uppaal toolset, which proves effective for studying all the properties of a mutual exclusion algorithm for N≥2 processes, by exhaustive model checking. Although the approach, as already confirmed by similar experiments reported in the literature, is not scalable due to state explosion problems, and can be practically applied until N≤5, it is of great value for revealing true properties of analyzed algorithms. For dimensions N>5 the statistical model checker of Uppaal can be used which, although based on simulations, can confirm properties by estimations and probabilities. The paper describes the proposed modelling and verification method and applies it to several mutual exclusion algorithms, thus retrieving known properties but also showing new results about properties often studied only by peer-review and intuitive reasoning.

The recent advancement of Artificial Intelligence (AI) and Machine Learning (ML) tools has had a pervasive effect on every sphere of human existence. Libraries and information centres are not immune to these technological advances. These disruptive technologies have transformed the traditional face of libraries and their operations. There are many available AI tools, for example, chatbots, literature review tools, plagiarism detection tools, and several other developments in the field that have perhaps made the functioning of libraries easier. However, there is growing concern and uncertainty among both traditional library and modern professionals regarding the possible job loss and security issues related to these new technologies, which the professionals must deal with. Librarians and information professionals must be ready to handle the unforeseen situation. However, it is to be observed how libraries cope with these uncertainties, and threats to the integrity, availability of data, and normal library housekeeping functions.

The article presents a methodology for modeling the impact of factors of both on-farm activity and environmental factors on the resulting indicators of an international company. The dataset includes the company's profit, revenue, valuation, share price, and market share from 2012 through 2022. This empirical period is optimal for such a type of modeling. Modeling the impact of carbon emissions factors on the resulting indicators is considered based on complex systems theory. Endogenous model variables include indicators of the development of the international company. Predefined model variables reflect the influence of both the external environment and internal factors on the development indicators of an international company. An approach of picture fuzzy rough sets based on time series of endogenous and exogenous variables can provide an opportunity to analyze and consider the consequences of feedback changes in the systems of which they are a part. Based on the results of the analysis of the model construction, it is concluded that picture fuzzy rough sets can be an excellent way to model interdependent social processes.

One of the main factors that influence the fertility of cattle in grazing systems in hot tropical climates is heat stress. The objective of this study was to evaluate the effect of season, breed, hormonal and physiological condition on the quantity and quality of cumulus-oocyte complexes (COCs) and embryos produced in vitro, from Romosinuano (RM) and Tropical Milking (TM) donors. Three ovum pick-up and in vitro fertilization (OPU-IVF) were performed, one per season; hot dry (HD; 10, 10), hot humid (HH; 9, 9) and fresh dry (FD; 7, 10) in RM and LT donors. Serum levels of cortisol, insulin and glucose were measured, in addition to heart rate (HR), respiratory rate (RR) and rectal temperature (RT). Effect of season x genotype interaction (p≤0.05) was observed in all COCs variables and only in cleavage embryos (CLI) (p≤0.05). Body weight (BW) affected all COCs variables (p≤0.01), except unviable (UNV) although affected degenerated embryos (DEG) (p≤0.01) and total blastocysts (BLAST) (p≤0.01). Cow age only affected viable COCs (VIAB) (p ≤ 0.05), code one blastocysts (BC1) and BLAST (p≤0.01). Cortisol affected total COCs (COCsT), VIAB and total matured in vitro (TMIV) (p≤0.01), as well as CLI, BC1 (p≤0.01) and BLAST (p≤0.05). Insulin affected COCsT (p≤0.01), UNV (p≤0.05), denuded oocytes (DE) (p≤0.01), BC1 and code two blastocysts (BC2) (p≤0.01). Glucose affected all COCs variables (p≤0.01), except UNV and all embryo variables except BC2. HR affected COCsT, DE, TMIV (p≤0.01), CLI, BLAST and DEG (p≤0.05). RR affected COCsT, UNV, VIAB, CLI (p≤0.05), BC1, BLAST and DEG (p≤0.01). RT only affected DE, VIAB (p≤0.01) and BLAST (p≤0.05). The seasonal climatic year variation of Veracruz and changes in physiological and hormonal variables have diverse effects on the cumulus-oocyte complexes and embryos produced by RM and TM donors.

Abstract: Melatonin influences arterial biomechanics, and its absence could cause remodeling of the arterial wall, leading to increased stiffness. Direct effects of fentanyl on the aortic wall have also been observed previously. This study aimed to evaluate in vitro the effects of fentanyl on aortic viscoelasticity in a rat model of melatonin deficiency. It also aimed to test the hypothesis that melatonin deficiency leads to increased arterial wall stiffness. The viscoelasticity of the aortic wall was estimated in strip preparations from pinealectomised and sham-operated adult rats using the forced oscillations method. We found that melatonin deficiency in the untreated aortic wall did not significantly alter viscoelasticity. However, combined with 10^-9 M fentanyl, melatonin deficiency increased the natural frequency and arterial stiffness compared to the sham-operated. Independently, fentanyl treatment decreased the natural frequency and arterial stiffness compared separately to untreated normal and melatonin-deficient preparations. The observed effects of fentanyl were neither dose-dependent nor affected by naloxone, suggesting a non-opioid mechanism. Furthermore, an independent effect of naloxone was also detected in the normal rat aortic wall, resulting in reduced arterial stiffness. Further studies are needed to clarify the underlying mechanisms, which may improve the clinical decisions for pain management and anesthesia.

Verifying the accuracy of a 3D-printed object involves using an image processing system. This system compares images of the CAD model of the object to be printed with its 3D-printed counterparts to identify any discrepancies. It is important to note that the integrity of the accuracy measurement is heavily dependent on the image processing settings chosen. This study focuses on this issue by developing a customized image processing system. The system generates binary images of a given CAD model and its 3D-printed counterparts and then compares them pixel-by-pixel to determine the accuracy. Users can experiment with various image processing settings, such as grayscale to binary image conversion threshold, noise reduction parameters, masking parameters, and pixel-fineness adjustment parameters, to see how they affect accuracy. The study concludes that the grayscale to binary image conversion threshold has the most significant impact on accuracy and that the optimal threshold varies depending on the color of the 3D-printed object. The system can also effectively eliminate noise (filament marks) during image processing, ensuring accurate measurements. Additionally, the system can measure the accuracy of highly complex porous structures where the pores size, depth, and distribution are random. The insights gained from this study can be used to develop intelligent systems for the metrology of additive manufacturing.

Background: Both hypertension and carotid atherosclerosis are independent risk factors for cardiovascular disease. Understanding their combined impact could enhance risk assessment and management strategies. Hypothesis: We hypothesized that the synergistic effects of hypertension and carotid plaques would increase the risk of both cardiovascular events and all-cause mortality. Methods: A follow-up study was conducted at the Preventive Cardiology department of Vilnius University Hospital Santaros klinikos between 2012 and 2021. The study recruited participants aged 40-60 who did not have overt CVD and were part of the Lithuanian High Cardiovascular Risk primary preventive program. The study collected demographic and clinical data, including an ultrasound assessment of carotid plaque. The participants were monitored for 4-10 years for CVD events and all-cause mortality. Results: Among 6,138 participants, 954 (16%) experienced cardiovascular disease (CVD) events. The presence of carotid plaque on both sides was significantly associated with CVD events, myocardial infarction, and all-cause mortality. However, the combination of hypertension and carotid plaque did not significantly increase the risk for CVD events, stroke, or all-cause mortality. Conclusion: The combination of hypertension and carotid plaque did not significantly increase the risk of CVD events or all-cause mortality. CV events depend on the spread of the atherosclerosis process in the carotid vessels.

In our investigation of the time evolution of energy states Einstein’s interpretation from more than a century ago is found to have greater internal consistency than that of non-relativistic quantum mechanics. We choose to align more closely with his methods by abandoning the non-relativistic Hamiltonian method, which has been the standard for nearly a century, in favor of a relativistically correct Lagrangian method. Integral equations of motion for the absorption and emission of radiation are derived that underlie and anticipate the differentially motivated Schrödinger equation. This new interpretation applies to a large volume of experimental evidence of both classical and quantum mechanical origin. Among the examples discussed in support are Planck’s law describing black body radiation, matrix mechanics, the function of the simplest quantum mechanical system an electron cyclotron, chaos theory, and evolutionary biology.

Children are inherently curious about everything they encounter, making the early years a perfect time for STEAM (science, technology, engineering, arts, and math) investigations. An outdoor learning environment can influence STEAM concept formation of preschoolers with intentional design that offer STEAM learning affordances. Despite the rising interest in early STEAM education, there is still limited literature on how the outdoor environment may influence STEAM learning behaviors of preschoolers (3-5 years old). This scoping review intends to evaluate the existing knowledge regarding the physical factors that contribute to STEAM learning affordances in an outdoor environment for children aged 3 to 5. The review included studies from the last twenty years. This scoping review was conducted in accordance with the criteria outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). For this scoping review, 843 citations were discovered across four databases (JSTOR, Scopus, EBSCOhost, and Web of Science), ProQuest, and Google Scholar, and 31 articles were considered eligible for inclusion. Through the synthesis of information from those 31 studies, a list of STEAM learning behaviors of children and STEAM activity-supportive settings were identified that may positively influence preschoolers' STEAM concept development.

This study provides a comprehensive comparison of the Peter Chew Sum method and Newton's Sum in Quadratic Root Function Computations. Both methods offer significant advancements by alleviating the need for memorization of multiple formulas. However, when confronted with higher-order quadratic root functions such as the calculation of power 33. Newton's Sum method proves cumbersome due to its requirement of all previous answers for final computation, leading to increased steps and error risks. In contrast, the Peter Chew Sum method simplifies the computational process by requiring only a few previous answers, resulting in a more straightforward series of operations. We contextualize our analysis within the historical progression of mathematical techniques, highlighting the transformative leap represented by the Peter Chew Sum method in quadratic root function computations. Peter Chew Sum addressing the limitations of Newton's Sum , especially concerning higher-order functions such as the calculation of power 256. Furthermore, study demonstrates that the innovative approach of the Peter Chew Sum method not only simplifies complex computations but also fosters enhanced conceptual understanding among students. In conclusion, study findings underscore the profound impact of the Peter Chew Sum method on quadratic root function computations.

Background and Objectives: The purpose of this study was to investigate whether early surfactant administration affects the status of ductus arteriosus (DA) in preterm infants ≤32 weeks of gestational age (GA) within 24 hours of birth. Materials and Methods: It is a prospective study conducted from March 15, 2022, to November 15, 2023, in a tertiary academic center. In-born infants ≤ 32 weeks of gestation (n = 88) were enrolled. The study group was further divided into surfactant (n=44) and non-surfactant (n=44) subgroups. Results: 76% of the preterm infants who received surfactant therapy (RRR = 0.839) recorded an increase in Kindler Score at 24 hours of life (1-RR = 1-0.24 = 76%). Surfactant administration was significantly associated with decreased pre-ductal diastolic pressure (29.9 mmHg vs. 34.8 mmHg, p=0.0231), post-ductal diastolic pressure (28.7 mmHg vs. 32.2 mmHg, p=0.0178) pre-ductal MAP (41.6 mmHg vs. 46.5 mmHg, p=0.0210) post-ductal MAP (41.0 mmHg vs. 45.3 mmHg, p=0.0336). There were no significant changes in ductus arteriosus parameters at 24 hours of life. Conclusions: Early surfactant administration does not affect the status of ductus arteriosus in preterm infants ≤32 weeks of gestational age at 24 hours of life.

In an attempt to reuse fibrous textile waste and, at the same time, to address dye pollution in textile wastewater, waste cotton-based yarn was utilized as both a cheap and sustainable adsorbent and a precursor for carbon adsorbent production. Cotton and cotton/polyester yarn samples underwent thermal modification through carbonization followed by chemical activation with KOH. Various techniques including nitrogen adsorption-desorption isotherms, scanning electron microscopy, Fourier transform infrared spectroscopy, and surface charge determination were employed to analyze the morphological and surface properties of the cotton-based adsorbents. Adsorption properties were evaluated by testing the removal of selected cationic and anionic dyes from water. The impact of temperature, contact time, initial concentration, and pH of the adsorbate solution on adsorption was investigated, with experimental data analyzed using theoretical models. While carbonization alone did not significantly enhance adsorption properties, activated samples exhibited high efficacy in removing both cationic and anionic dyes from water. Despite the negative influence of the polyester component in the carbon precursor on the efficiency of activated samples in removing methyl orange, results indicated that activated cotton and cotton/polyester yarn could be used to prepare highly efficient adsorbents for the rapid removal of methylene blue from real wastewater samples.

Surface–subsurface soil-rock modeling is crucial for infrastructure design and groundwater yield optimization, especially in the complex crystalline basement terrains of Penang Island, Malaysia. This study conducted large-scale characterization of soil-rock profiles using ERT, SRT, rock quality designation, and soil penetration test (SPT N-values) data, optimized through regression modeling. The approach effectively identified soil-rock structures and their suitability to prevent structural failures and enhance groundwater productivity. Correlations between borehole lithologic logs and velocity–resistivity models revealed distinct soil compositions across the study area. The results highlighted thick, saturated, and loose silty to sandy bodies in the eastern to northern sections, contrasting with sandy compositions and penetrative fractures in the southern part. The study also found good correlations between rock mass quality and N-values for different soil types. Depths of intra-bedrock weathered/fractured units varied between 12 and >35 m. This has significant implications for determining optimal foundation depths in the study area. Groundwater productivity was associated with intra-bedrock planes of weakness at depths exceeding 40 m. Overall, this study developed empirical relations between geophysical and geotechnical parameters for wet tropical granitic terrains, filling critical gaps in understanding subsurface characteristics.

Abstract Background Fatigue Syndrome (FS) is described as extreme exhaustion following ordinary activities. Sleep deprivation, the use of antidepressants, autoimmune illnesses, and anemia are also risk factors for FS. Symptoms of FS include headache, dizziness, and dyspnea, among others. Objective: This study focused on assessing the prevalence of fatigue syndrome (FS) and its association with depression and anxiety, among the medical students in Saudi Arabia. Methodology In this cross-sectional investigation conducted in 2023, 740 medical students participated. Data were gathered using an online survey, which encompassed four key sections: Sociodemographic details, the 11-item Chalder Fatigue Questionnaire (CFQ), the 9-item Primary Health Questionnaire (PHQ) assessing depression, and the Generalized Anxiety Disorder 7-item (GAD-7) scale. Analyses were performed by the use of SPSS version 25. Results A total of 740 students were surveyed, 417 (56.4%) satisfied the diagnostic requirements for fatigue syndrome (FS), with most of them being females. Furthermore, 234 (31.2%) and 296 (40.8%) of the participants reported having significant anxiety symptoms and depressive symptoms, respectively. FS was positively correlated with symptoms of anxiety and depression (P

We demonstrate a new quantitative method to the sieve of Eratosthenes, which is an alternative to the sieve of Legendre. In this method, every element of a given set is sifted out once only, and therefore, this method is free of the Mobius function and of the parity barrier. Using this method, we prove that every sufficiently large even number is the sum of two primes, and that every even number is the difference of two primes in infinitely many ways.

In this paper, we consider an economy, in which consumers exhibit unrealistic optimism, and show that such an economy is more likely to undergo early recessions and underinvestment rather than experiencing bubbles or overinvestment. In this model, each consumer incorrectly believes that a negative aggregate preference shock will hit all other consumers, but not herself. When consumers have such an unrealistic optimism, the output price must fall prematurely before the aggregate shock occurs. The reason is that if the price does not plummet today, all consumers would postpone making purchases by falsely expecting that an arbitrage opportunity will arise in the future when the aggregate shock hits the economy, in which case, the output market cannot clear. We also show that the government has the potential to improve welfare of the economy by providing subsidies, if the government judiciously selects the right timing for intervention.

Underwater image often exhibit detail blurring and color distortion due to light scattering, impurities, and other influences, obscuring essential textures and details. This presents a challenge for existing super-resolution techniques in identifying and extracting effective features, making high-quality reconstruction difficult. This research aims to innovate underwater image super-resolution technology to tackle this challenge. Initially, an underwater image degradation model was created by integrating random subsampling, Gaussian blur, mixed noise, and suspended particle simulation to generate a highly realistic synthetic dataset, thereby training the network to adapt to various degradation factors. Subsequently, to enhance the network's capability to extract key features, improvements were made based on the symmetrically structured Blind Super-Resolution Generative Adversarial Network (BSRGAN) model architecture. An attention mechanism based on energy functions was introduced within the generator to assess the importance of each pixel, and a weighted fusion strategy of adversarial loss, reconstruction loss, and perceptual loss was utilized to improve the quality of image reconstruction. Experimental results demonstrate that the proposed method achieved significant improvements in Peak Signal-to-Noise Ratio (PSNR) and Underwater Image Quality Measure (UIQM) by 0.85 dB and 0.19, respectively, significantly enhancing the visual perception quality and indicating its feasibility in super-resolution applications.

Polyphenols are ubiquitous plant metabolites that demonstrate biological activities essential to the plant-environment interactions. They are of interest to plant food consumers, as well as to the food, pharmaceutical and cosmetic industry. The class of the plant metabolites comprises both widespread (chlorogenic acids, luteolin, quercetin) and unique compounds of diverse chemical structures but of the common biosynthetic origin. Polyphenols, next to sesquiterpenoids are regarded as the major class of the Inuleae-Inulinae metabolites responsible for the pharmacological activity of medicinal plants from the subtribe (Blumea spp., Dittrichia spp., Inula spp., Pulicaria spp. and others). Recent decades have brought a rapid development of molecular and analytical techniques which resulted in better understanding of the taxonomic relationships within the Inuleae tribe and in a plethora of data concerning the chemical constituents of the Inuleae-Inulinae. The current taxonomical classification has introduced changes in the well-established botanical names and rearranged the genera based on molecular plant genetic studies. The newly created chemical data together with the earlier phytochemical studies may provide some complementary information on biochemical relationships within the subtribe. Moreover, they may at least partly explain pharmacological activities of the plant preparations traditionally used in therapy. The current review aimed to systematize the knowledge on the polyphenols of the Inulae-Inulinae.

Leishmaniasis in wild canids is a vector-borne disease caused in Europe by the protozoan parasite Leishmania infantum. To date, there is limited information on clinical signs and laboratory abnormalities in wolves due to leishmaniasis. The current clinical case report described a female Iberian wolf (Canis lupus signatus) housed in semi-captivity conditions at the Centro del Lobo Ibérico “Félix Rodríguez de la Fuente”, in Robledo de Sanabria, Zamora (Spain) with an interdigital ulcerous wound at the right forepaw, hyper-gammaglobulinemia, and abnormal liver blood parameters. Definitive serodiagnosis of leishmaniasis was established using antileishmanial serum antibodies and PCR analysis of different biological samples. A gold standard anti-L. infantum treatment protocol consisting in intramuscular meglumine antimoniate and oral allopurinol combination was installed. However, the presence of pain at the site of injection due to meglumine antimoniate administration forced its substitution by oral miltefosine. A progressive reduction of the levels of anti-L. infantum serum antibodies and the concentrations of gamma-globulin fraction was detected after antileishmanial treatment as well as a decline of liver GPT. To our knowledge, this is the first case of leishmaniasis diagnosed in a wolf housed in semi-captivity conditions treated and successfully cured.

The application of space robotic manipulators and heightened autonomy for ios represents a paramount pursuit for leading space agencies, given the substantial threat posed by space debris to operational satellites and forthcoming space endeavors. This work presents a guidance algorithm based on drl to solve for the space manipulator path-planning during the motion synchronization phase with the mission target. The goal is the trajectory generation and control of a spacecraft equipped with a 7-dof robotic manipulator, such that its end effector remains stationary with respect to the target point of capture. The ppo drl algorithm is used to optimize the manipulator’s guidance law, and the autonomous agent generates the desired joints rates of the robotic arm, which are then integrated and passed to a model-based feedback linearization controller. The agent is first trained to optimize its guidance policy and then tested extensively to validate the results against a simulated environment representing the motion synchronization scenario of an ios mission.

Gliomas are the most common primary brain tumors in adults. Despite multidisciplinary treatment approaches, the survival rates for patients with malignant glioma have only improved marginally, and few prognostic biomarkers have been identified. Peroxisome proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α) is a crucial regulator of cancer metabolism, playing a vital role in cancer cell adaptation to fluctuating energy demands. In this study, the clinicopathological roles of PGC-1α in gliomas were evaluated. Employing immunohistochemistry, cell culture, siRNA transfection, cell viability assays, western blot analyses, and in vitro and in vivo invasion and migration assays, we explored the functions of PGC-1α in glioma progression. High PGC-1α expression was significantly associated with an advanced pathological stage in patients with glioma and with poorer overall survival. The downregulation of PGC-1α inhibited glioma cell proliferation, invasion, and migration and altered the expression of oncogenic markers. These results conclusively demonstrated that PGC-1α plays a critical role in maintaining the malignant phenotype of glioma cells and indicated that targeting PGC-1α could be an effective strategy to curb glioma progression and improve patient survival outcomes.

In the decarbonization of the steel, cement, and chemical industry in Germany, green hydrogen is expected to play a crucial role. The utilization of green hydrogen in the production processes of said industries requires organizations to modify their business model, requiring sustainable business model innovation (SBMI). Numerous tools and frameworks that support organizations in the process of SBMI have been proposed in the literature in recent years. However, the applicability of these tools and frameworks for steel, cement, and chemical companies that intend to utilize green hydrogen to produce their goods remains unexplored. By conducting a systematic literature review on tools and frameworks for SBMI, a literature and practice review to identify and analyze existing green hydrogen projects of steel, cement, and chemical companies, and an evaluation of the identified tools and frameworks in an evaluation matrix, this paper aims to assess the suitability of SBMI tools and frameworks for steel, cement, and chemical companies that plan to use green hydrogen to produce their goods. Based on the evaluation, the Cambridge Business Model Innovation Process (CBMIP) was identified as the most suitable SBMI framework.

(1) Background: Asthma and Chronic Obstructive Pulmonary Disease (COPD ) are major global health issues, impacting morbidity, mortality, and healthcare costs. Despite the proven benefits of pharmacist involvement in managing these conditions, their potential in hospitals remains underused. This study aimed to identify patients at high risk of rehospitalisation post-exacerbation of asthma or COPD, to target pharmaceutical interventions. (2) Methods: Data from the University Hospital for January-December 2019 on adult admissions for asthma/COPD were analyzed, focusing on demographics, hospitalization, and clinical outcomes. (3) Results: Among the 140 patients enrolled, a significant majority (91%) underwent adjustments in their treatment regimens during their hospital stay, and nearly 59% faced readmission within six months. A survival analysis highlighted a notable disparity in the rates of rehospitalisation-free survival between patients with asthma and those with COPD, identifying COPD patients as having a higher susceptibility to rehospitalisation. (4) Conclusion: The study found COPD pa-tients at greater risk but didn't specify a priority profile, suggesting the necessity for broad, cus-tomized interventions to improve outcomes and reduce healthcare strain.

This paper comprehensively reviews sensors and sensing devices developed or/and proposed so far utilizing two smart materials: electrorheological fluids (ERFs) and magnetorheological materials (MRMs) whose rheological characteristics such as stiffness and damping can be controlled by external stimuli, an electrical voltage for ERFs and a magnetic field for MRMs, respectively. In this review article, the MRMs are classified into magnetorheological fluid (MRF), magnetorheological elastomer (MRE) and magnetorheological plastomer (MRP). To easily understand the history of sensing research using the two smart materials, the order of this review article is organized in a chronological manner of ERF sensors, MRF sensors, MRE sensors and MRP sensors. Among many sensors fabricated from each smart material, one or two sensors or sensing devices are adopted to discuss on the sensing configuration, working principle and specifications such as accuracy and sensitivity. Some sensors adopted in this article include force sensor, tactile device, strain sensor, wearable bending sensor, magnetometer, display device and flux measurement sensor. After briefly describing what have been reviewed in a conclusion, several challenging future works, which should be done for practical applications as sensors or sensing devices, are remarked in terms of new technologies such as artificial intelligence neural network in which several parameters affecting the sensor signals can be precisely tuned or controlled. It is sure that this review article is very helpful to make creative sensors using not only the proposed smart materials but also several different types of smart materials including shape memory alloys and active polymers.

In this study, the friction factor of turbulent pipe flow for dried rice malt extract solutions is reduced experimentally to that of a Newtonian fluid. The friction factor is measured for four types of solutions at different culture times and concentrations. The results indicate that the experimental data points of the test solutions diverge from the maximum drag reduction asymptote at and above Re√f ≅ 200 and align parallel to those of Newtonian fluids. This drag reduction phenomenon differs from that of artificial high molecular polymer solutions. It is classified as a Type B drag reduction phenomenon of biopolymer solutions and fine solid particle suspensions. The order of drag reduction corresponds approximately to that of 5–50 ppm xanthan-gum solutions reported previously. Furthermore, the velocity profile in a turbulent pipe flow was predicted using a semi-theoretical equation, in which the friction factors were determined using the difference between the experimental results of the tested solutions and Newtonian fluids. The results indicate a more considerable thickening of the viscous sublayer in the turbulent pipe flow of the test solutions than that of Newtonian fluids.

Polymerase I (Pol I) is at the epicenter of ribosomal RNA (rRNA) synthesis. Pol I is a target for treatment of cancer. Given the many cellular commonalities between cancer and neurodegeneration (i.e., different faces of the same coin) it seems rational to consider targeting of Pol I or, more generally, rRNA synthesis for treatment of disorders associated with the death of terminally differentiated neurons. Principally, ribosomes synthesize proteins and, accordingly, Pol I can be considered the starting point for protein synthesis. Given that cellular accumulation of abnormal proteins such as α-synuclein and tau is an essential feature of neurodegenerative disorders such as Parkinson disease and fronto-temporal dementia, reduction of protein production is now considered as a viable target for treatment of these and closely related neurodegenerative disorders. Abnormalities in polymerase I activity and rRNA production may also be associated with nuclear and nucleolar stress, DNA damage, and childhood onset neuronal death as is the case for the UBTF E210K neuroregression syndrome. Moreover, restraining the activity of Pol I may be a viable strategy to slow aging. Before starting down the road of Pol I inhibition for treating non-cancerous disorders of the nervous system, many questions must be answered. First, how much Pol I inhibition can neurons tolerate and for how long? Should inhibition of Pol I be continuous or pulsed? Will cells compensate for Pol I inhibition by upregulating the number of active rDNAs? At present, we have no effective and safe disease modulatory treatments for Alzheimer disease, α-synucleinopathies, or tauopathies, and novel therapeutic targets and approaches must be explored.

The identification of fetal cells in the blood and tissues of healthy mothers raised questions about the potential alloreactive origins of various diseases, such as autoimmunity, diabetes, arteriosclerosis, and cancer. However, the extent to which alloreactivity contributes to these diseases remains unverified. This study presents a basic mathematical disease model based on the genes’ origin and immunological interactions. This model, grounded in set theory, classifies these immunological interactions based on their intrinsic, extrinsic, and allogeneic nature. Therefore, this model offers an unexpected common theoretical foundation for understanding alloreactivity, genetic diseases, and infections. Furthermore, this model provides a valuable framework for scrutinizing the role of alloreactivity in health and disease.

The aim of this paper is to establish a valid procedure for better understanding all the phenomena associated with the high-speed machining of Glass Fibre Reinforced Plastic (GFRP) composites. Both rectangular and circular specimens were machined at high speeds (up to 50 m/min) in order to understand what occurred for all values of fiber orientation angles during machining operations. An innovative testing methodology was proposed and studied to investigate the phenomenon of burr formation and thus understand how to avoid it during machining operations. To this end, the forces arising during the machining process and the roughness of the resulting surface, were carefully studied and correlated with the cutting angle. Additionally, the cutting surface and chip morphology formed during cutting tests were examined using a high-speed camera. Close correlations are found between the variations of the cutting forces' signals and the trends of the roughness and the morphology of the machined surface.

The sound and heat insulation are among the most important concerns in modern life and nonwoven composite structures are highly effective in noise reduction and heat insulation. In this study, three layered nonwoven composite structures composed of recycled polyester (r-Pet) based thermo bonded nonwoven outer layer and meltblown nonwovens from PP and PBT as inner layers were formed to provide heat and sound insulation. Fiber fineness and cross section of thermo bonded outer layer, fiber type (PP/PBT), areal weight (100/200g/m2) and process conditions (calendared/non-calendared) of meltblown inner layer have changed systematically and the influence of these parameters on thickness, bulk density, air permeability, sound absorption coefficient and thermal resistance of composite structures were analyzed statistically. Also; the results were compared with composite structures including electrospun nano fiber web inner layer and with structures without inner layer. It was determined that sound absorption coefficients ranging between 0.77-0.98 for moderate sound frequencies and 0.99-1 for higher sound frequencies were acquired with developed nonwoven composite structures. Besides, higher sound absorption coefficients were obtained as 0.71 and 0.74 for low sound frequencies such as 800 and 1000Hz, respectively. As a result of this study it can be concluded that developed nonwoven composite structures that provides better sound absorption coefficients and similar thermal conductivity values compared to previous studies and materials in the market can be used as insulation material in required areas.

Osteoporosis is a bone condition where bones become weaker, leading to fractures, especially in older adults and postmenopausal women. Bioceramics for bone regeneration have indeed emerged as a promising solution for conditions like osteoporosis. Choosing the right bioceramic depends on how quickly it dissolves, how strong it is, and whether the body will react to it. Studies show that bioceramics can help bones grow back by activating (bone morphogenetic protein) BMP, (mitogen-activated protein kinase) MAPK, and Wingless/integrated (Wnt)/β-catenin pathways in the body when combined with stem cells, drugs, and supports. However, bioceramics have some problems like not being flexible enough and being prone to breaking, as well as difficulties in growing stem cells and finding the right supports for different bone types. While there has been progress in improving bioceramics for bone healing, we need to keep looking for new ideas from other areas of medicine to keep improving them. This review aims to add to the expanding field of scientific research by offering a detailed look at how bioceramics and growth factors contribute to bone regeneration. Ultimately, this knowledge will help in creating new types of bioceramics that can improve bone regrowth, providing new treatment options for people with bone diseases.

The number of diabetic patients worldwide is increasing rapidly. Prevention of diabetic reti-nopathy (DR), a leading cause of blindness, is a serious issue. We examined the effects of prophy-lactic pattern scanning laser retinal photocoagulation on DR development in 16 Spontaneously Diabetic Torii (SDT) fatty rats. Photocoagulation was applied to the right eyes of 8-week SDT fatty rats, and the left eyes served as the untreated controls. Electroretinography at 9 and 39 weeks of age and pathological examination of the retinal thickness and number of retinal folds, and immunohistochemistry of vascular endothelial growth factor and glial fibrillary acidic pro-tein at 24 and 40 weeks of age were performed bilaterally. No significant differences were seen between the left and right eyes in the apex latency and the amplitude of the oscillatory potential wave in the SDT fatty rats at 9 and 39 weeks of age and in the pathology and immunohistochem-istry in the SDT fatty rats at 24 and 40 weeks of age. Prophylactic pattern scanning retinal laser photocoagulation did not affect the development of DR in SDT fatty rats.

The article aims to present an alternative perspective on the relativistic expression of energy. This perspective is based on the virtual use of a Dempster mass spectrometer. In this spectrometer, it is possible to simulate Alfred Bucherer's experiment and conclude, using Lienard's relativistic equation, that the classical expression of energy predicted by Special Relativity is a more complete expression than the one presented by high school and college physics textbooks.

In this paper, a 100CMM regenerative thermal oxidizer (RTO) system based on a high heating device for low-emission combustion is implemented at a volatile organic compound (VOCs) gas generation workplace. Existing RTO has a structure that repeats the inflow and discharge of VOCs gas into a cylindrical drum-type rotating disk and has excellent energy efficiency with a heat recovery rate of 95% or more. However, when used for a long time, there is a problem that rotation stops or explodes due to the discharge of pollutants due to dust and thermal expansion due to high temperature of 800℃. To overcome this, a RTO based on a high heating device was developed to reduce low-emission combustion emissions and energy use. Through 177 hours of demonstration time, the oxidation efficiency of VOCs was 98.87%; the waste heat recovery rate was reduced by 95.78%, the fuel consumption was reduced by 21.95%, and the nitrogen oxide concentration was 3.9 ppm

Walking of humanoid robots is dependent on precise tracking of the center of gravity and foot trajectories. Trajectory tracking is achieved by mobilizing the robot joints to produce the correct trajectory. Errors are being occurred because of assumptions on tracking the center of gravity and the foot trajectories. In this study, a numerical algorithm has been developed that produces an exact and single kinematic solution in which the center of gravity and foot trajectories can be tracked with the desired precision. The effectiveness of the algorithm was examined with a dynamic simulation and compared with the method given in the literature The main highlight of this study, using the presented algorithm, the robot can walk even if the position of its center of gravity is lower than its hips, resulting tracking error was smaller than reported in the literature.

Environmental pollution is one of today's main ecological and social concerns. Among these pollutants are the heavy metals present in the burning of fossil fuels, mining, smelting of metallic minerals, fertilizers and pesticides. Billions of tons of heavy metals are emitted every year from industrial chimneys and sewers, contaminating the hydrosphere and polluting rivers, lakes and seas. In this context, freshwater fish are the most affected due to their proximity to the source of contamination and are therefore used as bioindicators in assessing environmental impact following exposure to metals. However, our understanding of the effects of heavy metals on detoxification organs - such as the liver and gills - in freshwater fish in situ is still limited. Therefore, we conducted a systematic review to determine the main changes and mechanisms involved in morphological modifications in the liver and gills of cichlid fish following exposure to heavy metals in situ. Based on a structured search, 36 original articles were selected from the PubMed and SCOPUS databases. The selection of studies and the identification of duplicates were identified by Rayyan, and the study selection process was presented in the PRISMA statement diagram. Bias analysis was carried out using the Software Review Mananger (RevMan) 5.3, from the Cochrane Collaboration. Thirty-six studies were selected which showed negative effects attributed to environmental contamination by heavy metals, ranging from bioaccumulation to morphophysiological alterations. Almost all the heavy metals analyzed were found in the liver and gill tissues, especially cadmium, copper, lead, zinc, iron and manganese. In view of the continuous morphophysiological changes identified in the liver and gill studies, it is possible to state that bioaccumulation analyses, combined with these configurations, are emerging as crucial tools for assessing and guiding environmental monitoring. This approach aims not only to preserve but also to strengthen the integrity of the aquatic ecosystem and the ichthyofauna.

One of the industries with the fastest rate of growth is healthcare, and this industry's enormous data requires extensive cloud storage. The cloud may offer some protection, but there is no assurance that data owners can rely on it for refuge and privacy amenities. Therefore, it is essential to offer security and privacy protection. Increased customer satisfaction with security and privacy preservation is crucial since healthcare big data and its sources are stored in the cloud and contain increasingly private and sensitive information. However, maintaining privacy and security in an untrusted green cloud environment is difficult, thus the data owner should have complete data control. A new work SecPri-BGMPOP(security and privacy of Boost graph Convolutional Network -Pinpointing-Optimization Performance) is suggested that can offer a solution that involves several different steps in order to handle the numerous problems relating to security and protecting privacy. Initially Boost Graph Convolutional Network Clustering (BGCNC) algorithm, which reduces computational complexity in terms of time and memory measurements, is first applied to the input dataset to begin the clustering process. Second, enlarge by employing a piece of the magnifying bit string to generate a safe key, pinpointing based encryption avoids amplify leakage even if a rival or attacker decrypts the key or asymmetric encryption. Finally, to determine the accuracy of the method, an optimal key was created using a meta-heuristic algorithmic framework called Hybrid fragment horde bland lobo Optimization (HFHBLO). Our proposed method currently kept in a cloud environment, allowing analytics users to utilize it without risking their privacy or security.

All types of sports are potential application scenarios for automatic and real-time visual object and event detection. In rink hockey, the popular roller quad skate variant of hockey team sports, it is of great interest to automatically track player’s movements and positions, player’s sticks and, also, making other judgments, such as being able to locate the ball. In this work, we introduce a real-time pipeline composed by an object detection model, created specifically for rink hockey games, followed by a knowledge-based event detection module. Even in the presence of occlusions and quick motions, our deep learning object detection model effectively identifies and tracks, in real-time, important visual elements such as: ball; players; sticks; referees; crowd; goalkeeper; and goal. Using a curated dataset composed by a collection of videos of rink hockey, comprising 2525 annotated frames, we trained and evaluated the algorithm performance and compare it to state of the art object detection techniques. Our object detection model, based on YOLOv7, presents a global accuracy of 80%, and presents a good performance in terms of accuracy and speed, according to our results, making it a good choice for rink hockey applications. In our initial tests, the event detection module successfully detected one important event type in rink hockey games, the occurrence of penalties.

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed in January 17 and 26-27, 2013 under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms, but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations of foF2 from median values observed during the night/morning periods on 13-15 and 20-23 January which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in foF2, h’F and daily averaged foF2 values with quasi-period of 5-8 days and peak-to-peak amplitude from about 1MHz to 2 MHz (from 20% to 40%) and ~40 km are observed during the 9-28 January, after registration the occurrence of the major SSW event on 6-7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionosheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F-region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms.

Cellulose nanofibrils (CNFs) are materials with high aspect ratio. Typically, TEMPO-oxidised, or cationic CNFs consist of long fibrils (up to 2 μm) with very low thickness (less than 10 nm). Derived from their high aspect ratio, CNFs form strong hydrogels with high elasticity at low concentrations. Thus, CNF suspensions appear as an interesting rheology modifier to be applied in cosmetics, paints, foods, as a mineral suspending agent, among other applications. The high viscosity results from the strong 3D fibril network, which is related to good fibrillation of the material, allowing the nanofibrils to overlap. The overlap concentration (c*) was found to vary from ca. 0.13 to ca. 0.60 wt.% depending on the type and intensity of the pre-treatment ap-plied during the preparation of the CNFs. The results confirm the higher tendency for the fibres treated with CHPTAC (cationic) and TEMPO to form a 3D network, resulting in the lowest c*. For the TEMPO-oxidised CNF suspensions, it was also found that aggregation is improved at acidic pH conditions due to lower charge repulsion among fibrils, leading to an increase in the suspension viscosity, as well as higher apparent yield stresses. TEMPO CNF suspensions with low content of carboxylic groups tend to precipitate at moderate acidic pH values.

Background and objective: Symptoms of most neurodegenerative diseases, including Parkinson’s disease (PD), usually do not occur until substantial neuronal loss occurs. This makes the process of early diagnosis very challenging. Hence, this research used variant call format (VCF) analysis to detect variants and novel genes that could be used as prognostic indicators in the early diagnosis of prodromal PD. Materials and Methods: Data were obtained from the Parkinson’s Progression Markers Initiative (PPMI), and we analyzed prodromal patients with gVCF data collected in the 2021 cohort. A total of 304 participants were included, including 100 healthy controls, 146 prodromal genetic individuals, 21 prodromal hyposmia individuals, and 37 prodromal RBDs. A pipeline was developed to process the samples from gVCF to reach variant annotation and pathway and disease association analysis. Results: Novel variant percentages were detected in the analyzed prodromal subgroups. The prodromal subgroup analysis revealed novel variations of 1.0%, 1.2%, 0.6%, 0.3%, 0.5%, and 0.4% for the genetic male, genetic female, hyposmia male, hyposmia female, RBD male, and RBD female, respectively. Interestingly, 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) that were recently detected in PD patients were detected in the prodromal stage of PD. Conclusion: Genetic biomarkers are crucial for the early detection of Parkinson’s disease and its prodromal stage. The novel PD genes detected in prodromal patients could aid in the use of gene biomarkers for early diagnosis of the prodromal stage without relying only on phenotypic traits.

Dietary intake and alcohol consumption might be influenced by genetic variations in taste receptor genes. The objectives of this study were to examine the relationship between polymorphisms in bitter taste receptor genes TAS2R13 (rs1015443) and TAS2R38 (rs1726866, rs10246939, and rs713598) as well as alcohol consumption and body fat percentage in college students. Four hundred and two students with a mean age of 20.2 years participated in this study. An NIH Diet History Questionnaire (DHQ II) was used to collect data on their dietary intake, while AUDIT survey was used to determine their level of alcohol consumption. Bitter taste receptor gene polymorphisms were assessed by TaqMan allelic discrimination assays. Despite significant associations between TAS2R13 (rs101544) and certain aspects of alcohol consumption, including the frequency of alcohol intake, no indeed significant associations were found between TAS2R13 (rs1015443) and alcohol consumption after accounting for confounding variables in the regression model. Neither association was found regarding percent of body fat. In contrast, ethnicity and gender significantly influenced percent of body fat (p < 0.001), while no significant association was observed between TAS2R13 (rs1015443) and percent of body fat. Likewise, TAS2R38 (rs1726866, rs10246939 and rs713598) demonstrated no significant association with alcohol consumption and percent of body fat. These results were controlled for confounding factors, such as ethnicity and gender. Body fat percentage and alcohol consumption may be influenced by ethnicity, gender and age rather than SNPs of TAS2R13 and TAS2R38 genes. Assessing the taste genes’ interactions with diet and body composition might be useful in identifying human disease risk.

Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study is to evaluate changes in soil moisture in the state of Pernambuco during the period 1961-2021, using the System of Hydrological Response Units for Pernambuco. In this study, two river basins in the state of Pernambuco that represent the different climatic conditions of the state will be chosen. The results show that in the coastal region, there is a tendency towards more saturated soils, and in the semi-arid region, there is a tendency towards drier soils. With these results, it is possible to conclude that public policy decisions for the economy, environment, and society must consider this vital water balance variable.

The incessant evolution of online platforms has ushered in a multitude of shopping modalities. Within the food industry, however, assessing the delectability of meals can only be tentatively determined based on consumer feedback encompassing aspects such as taste, pricing, packaging, service quality, delivery timeliness, hygiene standards, and environmental considerations. Traditional text data mining techniques primarily focus on consumers' emotional traits, disregarding pertinent information pertaining to the online products themselves. In light of these aforementioned issues in current research methodologies, this paper introduces the Bert BiGRU Softmax model combined with multimodal features to enhance the efficacy of sentiment classification in data analysis. Comparative experiments conducted using existing data demonstrate that the accuracy rate of the model employed in this study reaches 90.9%. In comparison to single models or combinations of three models with the highest accuracy rate of 7.7%, the proposed model exhibits superior accuracy and proves highly applicable to online reviews.

This paper presents the results of investigations into the pyrolysis of waste polypropylene in a laboratory fixed-bed batch reactor. The experiments were designed and verified in such a way as to allow the application of the Response Surface Methodology (RSM) in the development of an empirical mathematical model that quantifies the impacts mentioned above. The influence of the mass of the raw material (50, 100 and 150 g), together with the reactor temperature (450, 475 and 500 °C) and the reaction time (45, 50 and 75 min) was examined. It has been shown that the mass of the raw material, i.e. the filling volume of the reactor, has a significant influence on the pyrolysis oil yield. This influence exceeds the influence of reactor temperature and reaction time. This was explained by observing the temperature change inside the reactor at three different spots at the bottom, middle and top of the reactor. Recorded temperature diagrams show that with greater masses of feedstock, local overheating occurs in the middle part of the reactor, which leads to overcracking of vapor products, and from there to an increased formation of non-condensable gases, i.e. reduced yield of pyrolytic oil.

Background: Renal cancers are among the top ten causes of cancer-specific mortality, of which the ccRCC subtype is responsible for most cases. The grading of ccRCC is important in determining tumour aggressiveness and clinical management. Objectives: The objectives of this research were to predict the WHO/ISUP grade of ccRCC pre-operatively and characterise the heterogeneity of tumour sub-regions using radiomics and ML models, including comparison with pre-operative biopsy-determined grading in a sub-group. Methods: Data were obtained from multiple institutions across two countries, including 391 patients with pathologically proven ccRCC. For analysis, the data were separated into four cohorts. Cohorts 1 and 2 included data from the respective institutions from the two countries, cohort 3 was the combined data from both cohort 1 and 2, and cohort 4 was a subset of cohort 1, for which both the biopsy and subsequent histology from resection (partial or total nephrectomy) were available. 3D image segmentation was carried out to derive a voxel of interest (VOI) mask. Radiomics features were then extracted from the contrast-enhanced images, and the data were normalised. The Pearson correlation coefficient and the XGBoost model were used to reduce the dimensionality of the features. Thereafter, 11 ML algorithms were implemented for the purpose of predicting the ccRCC grade and characterising the heterogeneity of sub-regions in the tumours. Results: For cohort 1, the 50% tumour core and 25% tumour periphery exhibited the best performance, with an average AUC of 77.9% and 78.6%, respectively. The 50% tumour core presented the highest performance in cohorts 2 and 3, with average AUC values of 87.6% and 76.9%, respectively. With the 25% periphery, cohort 4 showed AUC values of 95.0% and 80.0% for grade prediction when using internal and external validation, respectively, while biopsy histology had an AUC of 31.0% for the classification with the final grade of resection histology as a reference standard. The CatBoost classifier was the best for each of the four cohorts with an average AUC of 80.0%, 86.5%, 77.0% and 90.3% for cohorts 1, 2, 3 and 4 respectively. Conclusion: Radiomics signatures combined with ML have the potential to predict the WHO/ISUP grade of ccRCC with superior performance, when compared to pre-operative biopsy. Moreover, tumour sub-regions contain useful information that should be analysed independently when determining the tumour grade. Therefore, it is possible to distinguish the grade of ccRCC pre-operatively to improve patient care and management.

Gastric inflammation-related disorders are commonly observed digestive system illnesses char-acterized by the activation of proinflammatory cytokines, particularly tumor necrosis factor-α (TNF-α). This results in the induction of cyclooxygenase-2 (COX-2)/prostaglandin E2 (PEG2) and matrix metallopeptidase-9 (MMP-9). These factors contribute to the pathogenesis of gastric in-flammation disorders. We examined the preventive effects of Lonicera japonica Thunb. ethanol ex-tract (Lj-EtOH) on gastric inflammation induced by TNF-α in normal GES-1 cells. The GES-1 cell line was used to establish a model that simulated the overexpression of COX-2/PGE2 and MMP-9 proteins induced by TNF-α, to examine the anti-inflammatory properties of Lj extracts. The re-sults indicated that Lj-EtOH exhibits significant inhibitory effects on COX-2/PEG2 and MMP-9 ac-tivity, attenuates cell migration, and provides protection against TNF-α-induced gastric inflam-mation. The protective effects of Lj-EtOH are associated with the modulation of COX-2/PEG2 and MMP-9 through activation of TNFR–ERK 1/2 signaling pathways as well as the involvement of c-Fos and nuclear factor kappa B (NF-κB) signaling pathways. Based on our findings, Lj-EtOH ex-hibits a preventive effect on human gastric epithelial cells. Consequently, it may represent a novel treatment for the management of gastric inflammation.

The development of reliable predictive algorithm for house price as the housing market is a stand-out among the most involved regarding valuing the price and continues to fluctuate, is constantly a need for socio-economic advancement and welfare of citizen. In this paper, we develop machine learning algorithms for forecasting UK housing Price, and find an optimal algorithm that forecasts housing price accurately on the premises of the presence of many features or covariates. After applying correlation analysis to remove correlated variables in order to avoid multicollinearity, thereby increasing the statistical power, a novel method of using regression analysis to first of all understand and select statistically significant features for the various regions in England based on North South divide is adopted. These features are then used in the machine learning algorithm to further increase the statistical power of the algorithm, increase the level of accuracy for each of them and ultimately increase the predictive values for the algorithms. The model construction involves 3 stages: 1- correlation analysis to identify and remove correlated variables thereby avoiding multicollinearity and increasing the statistical power of the linear regression, 2 - using linear regression to determine variables that are statistically significant and 3 - building the machine learning algorithms based on the variables that are statistically significant from the linear regression. A comprehensive dataset of UK Paid housing Price from 2010 to 2019 was linked to a number of other datasets to generate a total 21 variables or features used for the models. Catboost, Gradient Boosting, Bagging, Random Forest, Extra Tree all achieved the excellent models performance result in all the regions considered. The comparison of the seven models showed that Extra Tree algorithm consistently achieved the best performance in term of level of accuracy in all the regions. K-Nearest Neighbours (KNN) is the only algorithm with less than 50% level of accuracy. Noticeably, the regions considered had varying or differing insignificant variables, implying that although many variables are common (statistically significant) to all the regions, there are regional differences and impact when modelling or predicting housing prices. This study validates the practicability of developing a machine learning methodology for the prediction of housing price. This research offers a reference for future house price prediction based on machine learning.

To get more data concerning the influence of fertilizers (organic and mineral) on different forage plants existing in North-eastern Romanian grassland, the mass fractions of 14 essential, enzymatic, or considerd toxic elements was determined by Instrumental Neutron Activation Analysis together with the amount of crude proteins, ash, fibres as well as ether fact extract. Final results showed a significant variance of the content of analysed elements on organic as well as on mineral fertilized experimental plots, i.e. the content increased in 24% of plots, decreased in 23%, and remained unchanged in 45% while in 8% of plots their content was below the detection limits, as the case of Se. At the same time, an increase content of crude protein and ether extract was evidenced in fertilized grasses for all applied fertilizers while other global indicators such as neutral and acid fibre of sufuric lignin content decreased, suggesting significant higher nutritional values of fertilized forage plant.

This article describes an approach for optimising sensor-controlled systems through minimal intervention, utilising Fuzzy Linear Systems of Equations (FLSE). Staring with a generalised model of the system behaviour, incorporating an array of control units, environmental sensors, and an expert knowledge base. The described problems of detecting the level of intervention needed to change the system state to another is handled with the help of developed methods for solving the inverse problem for FLSE. By achieving minimal intervention, we ensure that system adjustments effective, economically optimal and non-intrusive. A MATLAB-based implementation is presented.

We show how the Poincar\'e--Riemann--Hilbert boundary-value problem enables us to construct effective estimates of the potential in the Schr\"odinger equation. The apparatus of the three-dimensional inverse problem of quantum scattering theory is developed for this. It is shown that the unitary scattering operator can be studied as a solution of the Poincar\'e--Riemann--Hilbert boundary-value problem. This allows us to go on to study the potential in the Schr\"odinger equation

Dielectric elastomers, such as thermoplastic polyurethanes (TPU), are widely used as dielectric layer, emulation layer and substrate of flexible and stretchable devices. To construct capacitors and actuators that work stably upon deformation, it has become an urgent need to investigate the evolution of dielectricity under stress and strain. However, the lack of effective methods for estimating the dielectric constant of elastomers under strain poses a big challenge. This article reports a device for in-situ measuring the dielectric constant of TPU under strain. It is found that upon stretching TPU to a strain of 400%, its dielectric constant decreases from 8.47 to 2.94. In addition, combined Fourier-transform infrared spectroscopy, X-ray scattering technique, and atomic force microscopy have been utilized to characterize the evolution of microstructure under strain. The investigation under tensile strain reveals that a decreased density and average size of polarized hard domains, along with a tendency of the molecular chains to align in parallel with the tensile stress. The evolution of the microstructures results in a reduction of the dielectric constant parallel to the electric field in TPU. Our work provides valuable experimental reference for improving the stability of flexible sensors and actuators based on dielectric elastomers.

This research addresses a gap in the literature by conducting a comprehensive analysis of patients’ level of satisfaction with dental care. Methods: By combining quantitative and qualitative survey methods with the PSQ questionnaire this study aims to augment ongoing initiatives to enhance dental patients’ experiences by painting a more comprehensive depiction of patients' level of satisfaction; Results: When asked about their overall level of satisfaction 77,1% of the patients said they received excellent services from the office personnel and 72,2% said they trust their doctors; Conclusions: Assessing patient satisfaction in the realm of dental services quality is crucial for enhancing service quality and accuracy, benefiting both patients and dentists, and ultimately improving public health.

Multivariate Time Series Classification (MTSC) is one of most important tasks in time series analysis, aiding in activities such as human motion recognition and medical diagnostics. Existing methods for MTSC do not explicitly model temporal differences and generalize the idea of temporal difference into a efficient temporal module. Additionally, existing methods are not yet able to capture cross-variable relationships well during network training. As a result, they are unable to achieve convincing feature representation, leading to suboptimal classification accuracy. In this paper, we propose a novel MTSC model called Temporal Difference and Cross-variate Fusion Network (TDCFN), which integrates a two-stream differential LSTM network and a cross-variate feature extraction network to enhance feature representation. TDCFN achieves superior classification accuracy by capturing dynamic temporal evolution and inter-variable relationships. The experimental results show that TDCFN can achieve competitive performance with state-of-the-art multivariate time series classification approaches.

Food and Agricultural Organisation estimates from 2014 suggest 64% of the high seas migratory stocks are either overfished or undergoing overfishing. Illegal fishing exacerbates the damage to marine ecosystems, human rights, and food security, and is yet to be included in the recent United Nations (UN) draft agreement to protect high seas biodiversity. We used catch data from the Sea Around Us Project to determine trends in fishing gear use and the catches of countries fishing in the high seas. Using Two-way ANOVA, Principal Coordinates Analysis, and SIMPER Test, we found that Spain, Taiwan, Japan, Indonesia, and Ecuador had the highest catches in 2004-2014. Each decade, only 1 in 10 countries (10.8%) caught over 500,000 tonnes, leaving the remaining 90% of countries catching less than 500,000 tonnes. Further analysis showed the mean high seas catch per fishery decreased 55% between the 2000s and the 2010s. Purse seine and longline were increasingly used towards the 2010s. Catch from purse seine and longline accounted for 70.5% and 78.4% of total high seas catch in 1950-2014 and 2004-2014, respectively. Discards were unreported throughout 1950-2014, and the reporting levels of landings varied greatly between countries and gears. We call for immediate action and recommend (1) including international, overarching high seas governance to end illegal and unsustainable fishing in the high seas in the UN draft agreement, and (2) using large mobile marine protected areas in high seas fisheries management through the UN draft agreement.

This study evaluated the stability of the Poly-(sorbitol-co-citrate adipate) with potential applica-tion in the biomedical area. Thus, the physical, chemical and microbiological stability of this was investigated. First, the chemical stability in alkaline phosphate buffer (pH 7.4) was evaluated for 5 days. In aqueous solution, the copolymer acidified the medium indicating the presence of residual citric acid. In the moisture absorption test the results obtained followed the pH, reinforcing the presence of citric acid. In the evaluation of the antimicrobial activity the results indicate that the copolymer did not allow the growth of the yeast Saccharomyces cerevisiae, as the only source of carbon. However, in the cell lysis phase and due to the restriction of access to nutrients in the culture medium, the copolymer showed a loss of mass due to its use by the microorganism. Thus, it presented biodegradability property under extreme conditions of cell culture.

Objective: The aim of our study was to perform a retrospective analysis of the volume of cervical screening tests, the number of patients treated with an excision method, and the incidence of invasive and non-invasive cervical during a pandemic and pre-pandemic period of 24 months. Results: There was a statistically significant age difference between the two study periods, both by the average age of patients and by age group. The mean difference was 32 years before the pan-demic and 35 years during the pandemic (p-value >0.05). The majority of patients presenting for investigations before and during the pandemic were in the 30-39-year-old age group (31.95%, respectively; 34.2% (p-value = 0.003). The biggest patient loss ratio identified by age group was in the 50–59 years: 14,53% in the pre-pandemic period and 9,1% in the pandemic period. In the pan-demic period, patients from rural areas presented in the clinical trial with a lower rate of 39.52% (83 patients) vs. 60.47% (127 patients) in urban areas. A higher percentage of patients experiencing cervicorrhagia as a clinical manifestation in the pandemic period vs. the prepandemic period, with an increase in more severe lesions in the pandemic period, has a statistical significance of 8% more newly diagnosed compared to the pre-pandemic period. Conclusion: The addressability of the patients during the COVID period was not affected in a drastic way in our study. We encountered a decrease in appointments in the age group 50–59 years and a decrease in patients with rural residence. In our study, we found an increase in cervicorrhagia as a reason for consultation in the pandemic period with a higher lesion degree, both on a pap smear and on a cervical biopsy.

Research on retinoid-based cancer prevention, spurred by the effects of vitamin A deficiency on gastric cancer and subsequent clinical studies on digestive tract cancer, unveils novel avenues for chemoprevention. Acyclic retinoids like 4,5-didehydrogeranylgeranoic acid (4,5-didehydroGGA) emerged as potent agents against hepatocellular carcinoma (HCC), distinct from natural retinoids such as all-trans retinoic acid (ATRA). Mechanistic studies reveal GGA's unique induction of pyroptosis, a rapid cell death pathway, in HCC cells. GGA triggers mitochondrial superoxide hyperproduction and ER stress responses through Toll-like receptor 4 (TLR4) signaling and modulates autophagy, ultimately activating pyroptotic cell death in HCC cells. Unlike ATRA-induced apoptosis, GGA and palmitic acid (PA) induce pyroptosis, underscoring their distinct mechanisms. While all three fatty acids evoke mitochondrial dysfunction and ER stress responses, GGA and PA inhibit autophagy, leading to incomplete autophagic responses and pyroptosis, whereas ATRA promotes autophagic flux. In vivo experiments demonstrate GGA's potential as an anti-oncometabolite, inducing cell death selectively in tumor cells and thus suppressing liver cancer development. This review provides a comprehensive overview of the molecular mechanisms underlying GGA's anti-HCC effects and underscores its promising role in cancer prevention, highlighting its importance in HCC prevention.

The article presents a model for optimizing biomass supply chains using the linear programming framework integrated with a Geographic Information System. Based on the distance from a given type of biomass resource, its calorific value, price, and transportation costs, the model identifies the optimal source of biomass, allowing it to cover the demand for the required total energy value with the lowest possible costs. The case study includes the Połaniec power plant in southeastern Poland and potential sources of forest biomass and agricultural straw within 100 km of the plant. Unit costs of biomass varied depending on biomass availability and energy demands. For energy demand on the level of 1 PJ yearly, the lowest unit costs of biomass (4.08 €/MJ) were when all kinds of biomass were available, and the highest (5.47 €/MJ) was when only stacked wood was available. As energy demand increased, unit costs increased, and the ability to meet this demand with just one type of biomass decreased. The energy biomass sector can utilize the model to benefit both biomass producers and their final buyers.

Neurodegenerative diseases that include Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD), and multiple sclerosis (MS), arise due to numerous causes like protein accumulation and autoimmunity, characterized by neurologic depletion which lead to incapacity in normal physiological function such as thinking and movement in these patients. Glial cells perform a critical role in protective neuronal function; in the case of neuroinflammation, glial cell dysfunction can promote the development of neurodegenerative diseases. MiRNA participates in gene regulation and plays a vital role in many biological processes in the body; in the central nervous system (CNS), it can play an essential part in neural maturation and differentiation. In neurodegenerative diseases, miRNA dysregulation occurs, enhancing the development of these diseases. In this review, we discuss neurodegenerative diseases (Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS)) and how miRNA is preserved as a diagnostic biomarker or therapeutic agent in these disorders. Finally, we highlighted miRNA as therapy.

(1) Background: Neurologic and musculoskeletal diseases represent a considerable portion of the underlying etiologies responsible for the widely prevalent symptoms of pain, weakens, numbness, and paresthesia. Because of the subjective and often nonspecific nature of these symptoms, different diagnostic modalities have been explored and utilized.; (2) Methods: Literature review; (3) Results: Nerve and muscle biopsy remains the gold standard for diagnosing many of the responsible neurological and musculoskeletal conditions. However, the need for invasive tissue sampling is diminishing as more investigations explore alternative diagnostic modalities. Because of this, it is important to explore the current role of neurosurgical intervention for nerve and muscle biopsies and its current relevance in the diagnostic landscape of neurological and musculoskeletal disorders. With consideration of the role of nerve and muscle biopsy, it is also important to explore innovations and emerging techniques for conducting these procedures. This review explores the indications and emerging techniques for neurological intervention for nerve and muscle biopsies; (4) Conclusions: The role of neurosurgical intervention for nerve and muscle biopsy remains relevant in diagnosing many neurological and musculoskeletal disorders. Biopsy is especially relevant as a supportive point of evidence for diagnosis in atypical cases. Additionally, emerging techniques have been explored to guide diagnostics and biopsy, conduct less invasive biopsies, and reduce risks of worsening neurologic function and other symptoms secondary to biopsy.

Across decades of contemporary discussion on sustainable development, a core debate has concerned the relationship between the economic, social, and environmental dimensions of sustainability. In recent years, a debate on economic growth versus degrowth has been going on discussing whether economic growth can be sustainable in environmental terms and whether economic degrowth can be sustainable in social terms. This conceptual and theoretical article has used the Sustainability Window, or ‘SuWi’ method, to theoretically determine the sustainable window of economies, as upper and lower bounds of future change in GDP, that could be deemed in line with environmental and social sustainability. All theoretically possible scenario paths of development are considered by combining the economic, environmental, and social dimensions, with the environmental and social productivities of GDP. In moving to sustainability analysis through SuWi it is noted that only four of the logically possible scenario paths could be considered theoretically 'sustainable’, and only if adhering to strict conditions. Two of the hypothesised scenarios involve economic growth and two of economic degrowth. The approach, including calculation formulas, has many potential uses in providing analysis and support to 21st century sustainability policymaking, including the United Nations Sustainable Development Goals.

We present a study of the radio variability of bright, $S_{1.4}\geq100$ mJy, high-redshift quasars at $z\geq3$ on timescales up to 30--40 years. The study involved simultaneous RATAN-600 measurements at frequencies of 2.3, 4.7, 8.2, 11.2, and 22.3 GHz in 2017--2020. In addition, data from the literature were used. We have found that the variability index $V_S$ of the quasars ranges from 0.02 to 0.96, with about half of the objects in the sample showing a variability index in the range of 0.25--0.50, which is comparable to that of the blazars at lower redshifts. The distribution of $V_S$ at 22.3 GHz is significantly different from that at 2.3--11.2 GHz, which may be attributed to the fact that a compact AGN core dominates at the source's rest frame frequencies greater than 45 GHz, leading to higher variability indices obtained at 22.3 GHz (the $V_S$ distribution peaks around 0.4) compared to the lower frequencies (the $V_S$ distribution peaks around 0.1--0.2). Several source groups with distinctive variability characteristics were found using cluster analysis of quasars. We propose 7 new candidates for gigahertz peaked-spectrum (GPS) sources and 5 new megahertz peaked-spectrum (MPS) sources based on their spectrum shape and variability features. Only 6 out of 23 sources previously reported as GPS demonstrate a low variability level typical of classical GPS sources ($V_{S} < 0.25$) at 4.7--22.3~GHz. When excluding the highly variable peaked-spectrum blazars, we expect no more than 20\% of the sources in the sample to be GPS candidates and no more than 10\% to be MPS candidates.

The genetic causes of the differentiated, highly treatable and mostly non-fatal papillary thyroid cancer (PTC) are not yet fully known. The widely accepted PTC etiology blames altered sequence or/and expression level of certain biomarker genes. However, our previous studies found that the PTC biomarkers played significantly lower roles than the personalized PTC Gene Master Regulators. Our publicly accessible gene expression data from the cancer nodule and the surrounding normal tissue of surgically removed PTC tumor were re-analyzed to determine the transcriptomic effects on the genomic fabrics responsible for the DNA replication, repair and transcription. Tumor results were compared to the gene expression profiles of the papillary (BCPAP) and the anaplastic (8505C) human thyroid cancer cell lines. The analyses were carried out from the Genomic Fabric Paradigm (GFP) perspective that provides the most theoretically possible comprehensive characterization of the transcriptome and its alterations in disease. The study indicated that, in addition to regulating numerous genes, changes in the homeostatic control of transcript abundances and remodeling of the gene networks had major contributions to the PTC occurrence, resilience and proliferation. Therefore, the molecular mechanisms responsible for gene expression control and inter-coordination should also be considered when designing personalized anti-cancer gene therapies.

Abstract: Alzheimer's Disease (AD) is a progressive uncurable neurodegenerative disease affect-ing millions worldwide. Various methods, including drug therapies and light emission diode (LED) irradiation, are promising alternatives for preventing and reducing the rapid progression of neurodegenerative diseases, also stimulating the reconstructing of neural tissue structures. In this study, we evaluated the neuroprotective and restorative effects of taurine combined with LED on human neuroblastoma cells (SH-SY5Y), under oxidative stress condition, a considerable modulator in AD. We evaluated LED at the wavelength of 660 nm and taurine under different concentrations before and after exposing SH-SY5Y cells to different concentrations of hydrogen peroxide (H2O2), assessing mitochondrial activity by the MTT colorimetric test and labeling live cell mitochondria by fluorescence using MitoTracker Orange. Cell viability was also evaluated by the trypan blue exclusion assay, and we verified cellular morphological structures by scan-ning electron microscopy (SEM). It was observed that neuroprotective effects are achieved by both LED and taurine when cells are exposed to them and later are stressed with H2O2. Compar-ing both agents, LED irradiation is sufficient to stimulate cell proliferation, representing an af-fordable candidate to contribute against neurodegeneration.

Polystyrene (PS) is an extremely stable polymer with relatively high molecular weight and a strong hydrophobic character that makes it highly resistant to biodegradation. In this study, PS was subjected to biodegradation tests by Tenebrio Molitor (T. Molitor) and Zophobas Morio (Z. Morio) larvae. Specifically, six different experimental diets were compared: (i) T. Molitor fed with bran; (ii) T. Molitor fed only PS; (iii) T. Molitor fed only PS treated with H2O2; (iv) Z. Morio fed with bran; (v) Z. Morio fed only PS and (vi) Z. Morio fed only PS treated with H2O2. Therefore, the mass change of the larvae and the survival rate were measured periodically, while the frass collected after 15 and 30 days were analyzed by different analyses, such as spectroscopy (FTIR), spectrometry (molecular weight and polydispersity), and microscopy (scanning electron microscopy observations). The obtained results suggest that in the case of T. Molitor larvae, larvae feeding on bran showed the highest survival rate of ~94 % at 30 days, while in the case of the Z. Morio larvae, the highest survival rate was exhibited by larvae eating PS-H2O2. Although not strongly pronounced, the Mw and Mn of PS frass of both T. Molitor and Z. Morio larvae decreased over 30 days, suggesting the Ps biodegradation. Finally, the morphological analysis shows that PS samples isolated from the frass of T. Molitor and Z. Morio larvae showed completely different, rough and irregularly carved surface structures, in comparison to PS before biodegradation.

Variable and sometimes contrasting effects of using artificial rhizobium inocula to increase grain legume performance have been reported. The objectives of this systematic review and meta-analysis were therefore to (i) estimate the overall effect of rhizobium inocula on grain yield and protein content and (ii) identify potential confounding factors that explain the observed variation. A web of Science database literature search was carried out in 2016. Data from all field experiments, greenhouse and pot experiments that compared grain yields and protein contents in Rhizobium/Bradyrhizobium-inoculated with non-inoculated control crops were extracted and analyzed using previously described unweighted and weighted meta-analysis protocols. GRADE assessments of the strength of evidence of results from the weighted meta-analyses were carried which included an assessment of the risk of publication bias. Results: For unweighted meta-analyses we identified eligible data in 236 and 36 studies for grain yield and protein content respectively. For weighted meta-analyses we identified eligible data in 92 and 8 studies for grain yield and protein content respectively. Rhizobium inoculation was found to (i) significantly increase grain yield in both the unweighted (mean percent difference: 41%, 95%CI 36,46, p&lt;0.0001) and weighted meta-analysis (Standardized mean difference: 1.56, 95%CI 1.26,1.87, p&lt;0.0001) and (ii) significantly increase protein content in the unweighted meta-analysis (mean percent difference: 11%, 95%CI 5,18, p&lt;0.0001), but not the weighed meta-analyses which only detected a trend (0.1&gt;p&gt;0.05) towards higher protein content in inoculated grain legume crops. Multi-level model-based weighted meta-analyses suggest that the (i) type of experiment, (ii) type of fertilizer used in experiments, (iii) grain legume type/species and (iv) the country in which experiments were carried out, were confounding factors. The main limitation of the evidence is that a large number of publications did not report measures of variation and could therefore not be included in the more scientifically sound weighted meta-analyses. However based on the large evidence-base available for grain yield it can be concluded that overall Bradyrhizobium/Rhizobium seed inoculation results can increase grain yield by ~40% compared with non-inoculated grain legume crops.

Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

This review delves into using natural antimicrobials in the dairy industry and examines various sources of these compounds, including microbial, plant, and animal sources. It highlights dairy products' most commonly used natural antimicrobials, such as nisin, lysozyme, lactoferrin, chitosan, and essential oils. It discusses the mechanisms by which they inhibit microbial growth and improve the shelf life of dairy products. Moreover, the review explores encapsulation technology as a promising approach for increasing the viability of natural antimicrobials. It discusses how encapsulation technology can protect these compounds from environmental factors that can reduce their effectiveness, such as pH, temperature, and oxygen exposure. The review also highlights the different materials that can be used for encapsulation, such as alginate, chitosan, and starch, and discusses their properties and suitability for encapsulating different natural antimicrobials. Finally, the review examines the benefits and challenges of using natural antimicrobials in dairy products. While natural antimicrobials offer several advantages, including improved safety, quality, and sensory properties of dairy products, it's crucial to be aware of the challenges associated with their use, such as potential allergenicity, regulatory requirements, and consumer perception. The review concludes by emphasizing the need for further research to identify and develop effective and safe natural antimicrobials for the dairy industry to ensure the quality and safety of dairy products for consumers.

Succinic semialdehyde dehydrogenase (SSADH) is a mitochondrial enzyme involved in the catabolism of the neurotransmitter γ-amino butyric acid. Pathogenic variants in the gene encoding this enzyme cause SSADH deficiency, a developmental disease manifesting as hypotonia, autism and epilepsy. SSADH deficiency patients usually have family-specific gene variants. Here, we describe a family exhibiting four different SSADH variants, Val90Ala, Cys93Phe, and His180Tyr/Asn255Asp (a double variant). We provide a structural and functional characterization of these variants and show that Cys93Phe and Asn255Asp are pathogenic variants that affect the stability of the SSADH protein. Due to impairment of the cofactor NAD+ binding, these variants show a highly reduced enzyme activity. However, Val90Ala and His180Tyr exhibit normal activity and expression. The His180Tyr/Asn255Asp variant exhibits a highly reduced activity as a recombinant species, is inactive and shows a very low expression in eukaryotic cells. A treatment with substances that support protein folding by either increasing chaperone protein expression or by chemical means was not capable of increasing the expression of the pathogenic variants of the SSADH deficiency patient. However, stabilization of the folding of pathogenic SSADH variants by other substances may provide a treatment option for this disease.

The interface of a structural system in the soil is usually unsaturated. A decrease in the shear strength of the soil-structure interface can degrade the structure, especially under humid conditions. Studying the shear characteristics of the silt-concrete interface using a shear apparatus. Suction-controlled ring shear tests were carried out on the silt-concrete interface for three interface roughness values. The influence of the matric suction (s) and interface roughness (R) on the shear strength index of the silt-concrete interface was analyzed. The test results showed that high values of s and R improved the shear strength of the interface, but the result was affected by the net normal stress (NNS). High values of NNS and R improved the strain-hardening characteristics. NNS, s, and R significantly affected the interface shear shrinkage. The internal friction angle of the saturated interface was smaller than that of saturated silt, whereas the opposite occurred in the unsaturated state. The cohesion and internal friction angle of the interface rose with an increase in R, and they were larger than that of silt. A shear strength model of the silt and interface was established.

Multiple sclerosis is an autoinflammatory condition that results in damage of myelinated neurons in affected patients. While disease-modifying treatments have been successful in slowing the progression of relapsing remittent disease, most patients still progress to secondary progressive disease that is largely unresponsive to disease-modifying treatments. Similarly, there is currently no effective treatment for patients with primary progressive MS. Innate and adaptive immune cells in the CNS play a critical role in initiating an autoimmune attack and in maintaining the chronic inflammation that drives disease progression. In this review, we will focus on recent insights into the role of T cells with regulatory function in suppressing the progression of MS, and, more importantly, in promoting the remyelination and repair of MS lesions in the CNS. We will discuss the exciting opportunity to genetically reprogram regulatory T cells to achieve immune suppression and enhance repair locally at sites of tissue damage, while retaining a fully competent immune system outside the CNS. In the future, reprogramed regulatory T cells with defined specificity and function may provide life medicines that can persist in patients and achieve lasting disease suppression after one cycle of treatment.

Despite their relatively low incidence globally, CNS tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes..

The state-of-the-art smart city has been calling for an economic but efficient energy management over large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze and control electric loads of all users in system. In this paper, we employ the popular computer vision techniques of AI to design a non-intrusive load monitoring method for smart electric energy management. First of all, we utilize both signal transforms (including wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods to map one-dimensional current signals onto two-dimensional color feature images. Second, we propose to recognize all electric loads from color feature images using a deep neural network with multi-scale feature extraction and attention mechanism. Third, we design our method as a cloud-based, non-intrusive monitoring of all users, thereby saving energy cost during electric power system control. Experimental results on both public and our private datasets have demonstrated our method achieves superior performances than its peers, and thus supports efficient energy management over large-scale Internet of Things.

To assess if SARS-CoV-2 infection induces changes in the urinary volatilomic fingerprint able to be used in the non-invasive COVID-19 diagnosis and management, urine samples of SARS-CoV-2 infected patients (62), recovered COVID-19 patients (30), and non-infected individuals (41) were analysed using solid-phase microextraction technique in headspace mode, combined with gas chromatography hyphenated with mass spectrometry (HS-SPME/GC-MS). In total, 101 volatile organic metabolites (VOMs) from 13 chemical families were identified, being terpenes, phenolic compounds, norisoprenoids, and ketones the most represented groups. Overall, a decrease in the levels of terpenes and phenolic compounds was observed in the control group, whereas norisoprenoids and ketones showed a significant increase. In turn, a remarkable increase was noticed in norisoprenoids and ketones and a milder increase in alcohols, furanic, and sulfur compounds in the recovery group than in the COVID-19 group. Multivariate statistical analysis identified sets of VOMs with the potential to constitute volatile signatures for COVID-19 development and progression. These signatures are composed of D-carvone, 3-methoxy-5-(trifluoromethyl)aniline (MTA), 1,1,6-trimethyl-dihydronaphthalene (TDN), 2-heptanone, and 2,5,5,8a-tetramethyl-1,2,3,5,6,7,8,8-octahydro-1-naphthalenyl ester acetate (TONEA) for COVID-19 infection and nonanoic acid, α-terpinene, β-damascenone, α-isophorone, and trans-furan linalool for patients recovering from the disease. This study provides evidence that changes in the urinary volatilomic profile triggered by SARS-CoV-2 infection constitute a promising and valuable screening and/or diagnostic and management tool for COVID-19 in clinical environment.

The fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing kThe fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing knowledge for the information- theoretic fractal dimensions. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.

The SBA-15 loaded with methylene blue was successfully prepared by sample adsorption of methylene blue in SBA-15 and is characterized by an XRD, SEM, FTIR, and BET. The photocatalytic activity for methyl orange (MO) degradation was investigated under visible light irradiation under LEDs. Experimental results demonstrate that the SBA-15-MB exhibited higher photocatalytic activity than SBA-15 under visible light irradiation. The degradation efficiency of MO (50 ppm) by SBA-15-MB could reach 80% within 180 min under 25W LED visible light. The photocatalytic activity of SBA-15 could be attributed to the excitation of methylene blue by visible light, the transfer of electrons from methylene blue to SBA-15, and the production of radicals at the surface of SBA-15.

In an era where dietary habits significantly impact health, technological interventions can offer personalized and accessible food choices. This paper introduces Chef Dalle, a recipe recommen-dation system that leverages multimodal human-computer interaction (HCI) techniques to pro-vide personalized cooking guidance. The application integrates voice-to-text conversion via Whisper, ingredient image recognition through GPT-Vision, and employs TF-IDF vectorization alongside cosine similarity for personalized recipe recommendations. These methods enable users to interact with the system using voice, text, or images, accommodating various dietary re-strictions and preferences. Furthermore, the utilization of DALL-E 3 for generating recipe images enhances user engagement. User feedback mechanisms allow for the refinement of future rec-ommendations, demonstrating the system's adaptability. Chef Dalle showcases potential appli-cations ranging from home kitchens to grocery stores and restaurant menu customization, ad-dresses accessibility, promoting healthier eating habits. This paper underscores the significance of multimodal HCI in enhancing culinary experiences, setting a precedent for future developments in the field.

Most neurodegenerative diseases, including Alzheimer's disease, ischemic stroke, subarachnoid hemorrhage, and intracerebral hemorrhage are associated with inflammation. Tumor necrosis factor (TNF) is a pleiotropic pro-inflammatory cytokine that regulates cerebral infarction in stroke pathology, and its action is influenced by the bioavailability of its membrane-bound receptors, TNFR1 and TNFR2, and microglial activation. During the initial onset of these diseases, the soluble variant of the cytokine presents with prolonged and excessive activation of TNFR1, resulting in cell death and long-term neurological impairments. Therapeutic interventions for neurodegenerative diseases have targeted TNF to limit the onset of neuroinflammation. First-generation therapeutics have been demonstrated to inhibit membrane-bound TNF to TNFR2 receptor binding, resulting in severe side effects such as infections and cancer. As such, second-generation drugs, including XPro1595, have been developed to selectively inhibit soluble TNF and impede the effects of TNFR1 while still allowing for TNFR2 activation. Early results in murine TBI models demonstrate reduced glial reactivity by 50%, reduced dendritic degeneration by 30%, increased plasticity by 15%, and improved functional outcomes by 20% post-TBI. This scoping review of TNF receptors in various neurodegenerative diseases seeks to evaluate current and future therapeutic strategies as well as highlight potential strategies to eliminate confounding variables present in the current literature.

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. The model dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

An entomopathogenic nematode, Oscheius tipulae, was isolated from a soil sample. The identification of this species was supported by morphological and molecular markers. The nematode isolate exhibited pathogenicity against different target insects including lepidopteran, coleopteran, and dipteran insects. The virulence of this nematode was similar to that of a well-known entomopathogenic nematode, Steinernema carpocapsae, against the same insect targets. A comparative metagenomics analysis of these two nematode species predicted the existence of a combined total of 272 bacterial species in their intestines, of which 51 bacterial species were shared between the two nematode species. In particular, the common gut bacteria included several entomopathogenic bacteria including Xenorhabdus nematophila, which is known as a symbiotic bacterium to S. carpocapsae. The nematode virulence of O. tipulae to insects was enhanced by an addition of dexamethasone but suppressed by an addition of arachidonic acid, suggesting that the immune defenses of the target insects against the nematode infection is mediated by eicosanoids, which would be manipulated by the symbiotic bacteria of the nematode. Unlike S. carpocapsae, O. tipulae showed high virulence against dipteran insects including fruit flies, onion flies, and mosquitoes. O. tipulae showed particularly high control efficacies against the onion maggot, Delia platura, infesting the Welsh onion in the rhizosphere in both pot and field assays.

The presence of anti SARS-CoV2-RBD antibody (Anti-RBD) prevents severe COVID-19. We aimed to determine the accuracy of a point-of-care Anti-RBD test implemented in person living with HIV (PLWH), systemic lupus erythematosus (SLE), and chronic kidney disease (CKD). We enrolled 182 non-comorbid subjects and 335 persons with comorbid (PLWH, SLE, CKD) to test anti-RBD assay compared to surrogate viral neutralization (SVNT) as the reference test. We performed linear correlation analysis between anti-RBD vs SVNT and a ROC analyses to ascertain anti-RBD cut-off at 30%, 60%, and 90% inhibition of SVNT to calculate accuracy. Correlations of anti-RBD to SVNT among all groups were excellent with R= 0.7903, R=0.7843, R=0.8153 among non-comorbid, SLE and CKD groups, respectively, with significantly higher correlation among the PLWH group (R=0.8877; p-value=0.0072) compared to non-comorbid group. The accuracy of the anti-RBD test among PLWH and CKD group was similar with the non-comorbid but showed lower sensitivity in the SLE group (p=0.000014). The specificity of the test remained high in all groups. In conclusion, the Anti-RBD test had excellent correlation to SVNT. The persistently high specificity in all groups suggests that this test can be reliably utilized to detect presence of low neutralization capacity, prompting additional vaccination.

Background: Both of cognitive decline and unhealthy lifestyle have been associated with an increased risk of mortality in older people. We aimed to investigate whether lifestyle behaviors might modify the association between cognitive function and the risk of all-cause mortality in Chinese older populations. Methods: The study included 5,124 individuals free of dementia in the Chinese Longitudinal Healthy Longevity Survey from 2011 to 2018. Cognitive function was measured using the Mini-Mental State Examination in 2011. A lifestyle score was calculated on the basis of five lifestyle factors including smoking, alcohol consumption, physical activity, diet and body mass index. Cox proportional hazards models were performed to examine the association between baseline cognitive function and all-cause mortality, with an interaction term of cognitive function and lifestyle score being added to the models Results: During a median follow-up of 6.4 years, we documented 1,461 deaths. Both higher cognitive function (HR: 0.96; 95% CI: 0.96–0.97) and healthier lifestyle (HR: 0.92; 95% CI: 0.87–0.97) were significantly associated with a lower risk of mortality. We found that lifestyle significantly modified the association of cognitive function with mortality (P for interaction = 0.004). The inverse association between high cognitive function and mortality was more prominent among participants with healthier lifestyle. Of note, among the lifestyle scores component, diet showed a significant interaction with mortality (P for interaction = 0.003), with the protective HR of the all-cause mortality associated with higher MMSE scores was stronger among participants with healthy diets compared with unhealthy diets. Conclusion: Our study indicates that cognitive decline is associated with an increased risk of mortality, and such relations are modified by overall lifestyle, with healthy diet being the major contributor.

Using a detailed atmospheric radiative transfer model, we derive macroscopic relationships of downwelling and outgoing longwave radiation, useful for hydrological practice. We validate them using empirical formulae based on downwelling radiation data, which are in common use in hydrology, as well as satellite data for the outgoing radiation. We use the macroscopic relationships to infer the relative importance of carbon dioxide and water vapour in the greenhouse effect. The results show that the contribution of the former is 4% – 5%, while water and clouds dominate with a contribution of 87% – 95%. The minor effect of carbon dioxide is also confirmed by the small, non-discernible effect of the recent escalation of atmospheric CO2 concentration from 300 to 420 ppm, which is quantified at 0.5% for both downwelling and outgoing radiation. Water and clouds also perform other important functions in climate, such as regulating the heat storage and the albedo, as well as cooling the Earth’s surface though latent heat transfer, with a contribution of 50%. By confirming the major role of water on climate, these results suggest that hydrology should have a more prominent and more active role in climate research.

The Drinking Water Directive (EU) 2020/2184 includes the parameter microcystin-LR, a cyanotoxin, which drinking water producers need to analyze if the water source has potential for cyanobacterial blooms. In light of the increasing occurrences of cyanobacterial blooms worldwide and given that more than 50 percent of the drinking water in Sweden is produced from surface water, both fresh and brackish, the need for improved knowledge about cyanotoxin occurrence and cyanobacterial diversity has increased. In this study a total of 98 cyanobacterial blooms were sampled in 2016-2017 and identified regarding their toxin production and taxonomical compositions. The surface water samples from freshwater lakes throughout Sweden including brackish water from 8 east coast locations along the Baltic Sea were analyzed for their toxin content with LC-MS/MS and taxonomic composition with 16S rRNA amplicon sequencing. Both the extracellular and the total toxin content was analyzed. Microcystin´s prevalence was highest with presence in 82% of blooms, of which as free toxins in 39% of blooms. Saxitoxins were found in 36% of blooms in which the congener decarbamoylsaxitoxin (dcSTX) was detected for the first time in Swedish surface waters at four sampling sites. Anatoxins were most rarely detected, followed by cylindrospermopsin, which were found in 6% and 10% of samples, respectively. As expected, nodularin was detected in samples collected from the Baltic Sea only. The cyanobacterial operational taxonomic unit (OTU) with the highest abundance and prevalence could be annotated to Aphanizomenon NIES-81 and the second most profuse cyanobacterial taxon to Microcystis PCC-7914. In addition, two correlations were found, one between Aphanizomenon NIES-81 and saxitoxins and another between Microcystis PCC-7914 and microcystins. This study is of value to drinking water management and scientists involved in recognizing and controlling toxic cyanobacteria blooms.

Human activities (e.g., exploitation, utilization, and conservation) exert substantial impact on forest ecological functions (FEF). The human influence on FEF significantly varies across developmental stages, which are attributed to the temporal and spatial in nature. This study evaluates some notable FEF indices (FEFI) in the 448 counties within the Yellow River basin (YRB) using panel data from the Seventh to Ninth National Forest Inventory. Data analysis involves employing the residual trends, geographical and temporal weighted regression. Results indicate that, firstly, the overall forest ecological function in the YRB is moderate to inferior, with superior FEF in counties endowed with more natural forest resources. Afforestation demonstrates a short-term improvement, but its effectiveness diminishes over time. Secondly, the positive spatial correlation is stronger among counties, characterized by both high-high and low-low agglomeration effects. Scattered planting, simple stand structure, and concentrated harvesting of forests at the identical stand ages hinder the formation of complex and large-scale FEF agglomerations. Thirdly, significant spatial-temporal differences exist in the impact of human activities on FEF. In the upper reaches of the basin, increased vegetation coverage through agricultural and forestry production benefited FEF, however, some over-exploitation of forests and grasslands is observed there. In the middle reaches, the economic development, expanding population and the greening activities help to improve FEF effectively, but excessive water using in agricultural production brought more difficulties to FEF improvement. In the lower reaches of the basin, improved wastelands and forest protection positively influence FEF. This study recommends that county governments should prioritize forest management with multi-species and multi-layered complex forests. Each county should define its position in regional development and ecological protection, considering the potential impacts on neighboring regions. This holistic approach promotes more effective integrated regional management.

(i) Investigations of stellar systems known as wide binaries suggest that Newton’s law of gravitation breaks down at low accelerations. This can be explained by proposing a fifth force with $U(1)$ gauge symmetry, whose corresponding gauge boson is the sought for dark matter candidate. (ii) Relativistic causality (i.e. no faster than light signalling) permits nonlocal correlations stronger than those permitted by quantum mechanics. This can be explained if our universe possesses a second 4D spacetime with a signature opposite to ours. (iii) Such a fifth force, and a second spacetime, arise naturally in a recently proposed theory of unification based on an $E_8\times E_8$ symmetry. Our spacetime arises from breaking of an $SU(2)_R\times U(1)_{YDEM}$ symmetry, and the second spacetime arises from broken electroweak symmetry.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Earth’s climate cannot be ignored any longer. Policies are vital in order to mitigate the negative effects of climate change. The energy crisis created by the Russo-Ukrainian war and pandemic affected the EU and its member states. The focus is more than ever on its energy policies and independence. The EU revised the energy strategy in response to Russia’s blackmail, and it sped up all the processes for energetic independence from Russia. This benefited the climate change policies the most, as all the measures involved reducing energy consumption and increasing renewables, thus contributing to reducing greenhouse gas emissions. As a member state of the EU, Romania is committed to complying with EU regulations. With a high degree of energy independence compared with the other EU members, Romania plans to become a regional energy provider and modernize the energy infrastructure internally as a response to Russia’s unprovoked aggression. The measures that the EU and Romania implemented after the war started in 2022 have come to fruition, and the effects are becoming visible a year later. This study aims to study the energy strategy of Romania in correlation with the EU strategy in the turbulent period of pandemics and war between 2019 and 2023, with the latest available data.