The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

Analysis of immediate effects of the COVID-19 pandemic on SMEs in Rwanda aims to assess and quantify the economic and financial impacts of the pandemic during the lockdown and presents options adopted by SMEs to reopen their business opera-tions. It also seeks to recommend options for sustainable and resilient economic recovery from the scars of COVID-19. This analysis used data collected from nearly 220 SMEs located across the country and applied an Exploratory Data Analysis (EDA) and multivariate linear regression models to measure the pandemic effects. The study revealed that firms downsized employment by 36.4 per cent, but data depict significant deviation within SMEs by their size. The COVID-19 pandemic has had a greater magni-tude of negative effects on sales levels among small businesses. Tax amounts were reduced amidst the crisis however, data do not show any significant variations among SMEs. Additionally, SMEs owners applied various coping mechanisms during re-opening. The study used firm-level data, providing detailed and reliable effects of the shocks on business performance. This analysis recommends establishing the medium-term financing and technical support for SMEs to ensure steady and sustainable recovery from pandemic effects as well as strengthening their resilience to any other socio-economics shocks.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

Drug-target binding is a crucial parameter in drug discovery and design, ensuring drug efficacy and specificity. Semaglutide, a potent GLP-1 receptor agonist, is widely used to treat type 2 diabetes mellitus by regulating blood glucose levels and promoting weight loss. This study introduces a novel approach utilizing the concept of a general intermolecular binding affinity calculator (GIBAC) for designing semaglutide analogues with enhanced binding affinity to GLP-1R. For the first time, a Val27-Arg28 exchange was manually introduced to strengthen the semaglutide-GLP-1R binding affinity. A comprehensive structural and biophysical analysis was conducted to explore the semaglutide-GLP-1R sequence space, leading to the identification of promising analogues. Among these, one semaglutide analogue demonstrated a binding affinity to GLP-1R that is more than two orders of magnitude (113.3 times) higher than native semaglutide, achieving a Kd of 3.0 x 10^-8 M compared to the Kd of 3.4 x 10^-6 M for native semaglutide. This article proposes a promising structural biophysical approach for developing GLP-1 receptor agonists with improved efficacy. The prototype GIBAC, termed semaGIBAC, represents a paradigm shift in precise drug discovery and design, advocating for the construction of a full-scale GIBAC to be prioritized within the drug discovery and design community.

Drug-target binding is an essential parameter in drug discovery and design to ensure drug efficacy and specificity. In 2022, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined: $Kd = f(molecules, envPara)$. Technically, GIBAC represents a set of in silico approaches for structural and biophysical data generation towards a paradigm shift in precise drug discovery and design, providing a comprehensive framework for intermolecular binding affinity calculation with adequate accuracy, precision and efficiency. For the first time, this study reports a prototype of GIBAC (semaGIBAC), i.e., a one-dimensional semaglutide-GLP-1R-based mini static GIBAC, based on an experimental complex structure of semaglutide and GLP-1R. Semaglutide is a potent GLP-1 receptor agonist used to treat type 2 diabetes mellitus by regulating blood glucose levels and promoting weight loss. In 2021, a structural modification involving a Val27-Arg28 exchange was manually introduced to enhance semaglutide-GLP-1R binding affinity. This study employs a comprehensive structural and biophysical analysis aimed at thoroughly exploring the sequence space of semaglutide-GLP-1R to design analogues with improved binding affinity, leading to the identification of a promising semaglutide analogue, which binds to GLP-1R with an affinity that is more than two orders of magnitude (113.3 times) higher than native semaglutide. To sum up, this article puts forward a promising structural biophysical approach for developing GLP-1 receptor agonists with enhanced efficacy, and with a GIBAC prototype (semaGIBAC), this article argues again that the time is now ripe for the construction of a real GIBAC to be listed on the agenda of the drug discovery and design community.

Phosphodiesterase type 5 (PDE5) inhibitors are widely used in the treatment of various conditions, including erectile dysfunction and pulmonary hypertension. Despite their clinical efficacy, these drugs quite often cause visual disturbances due to off-target effects on Phosphodiesterase type 5 (PDE6) in the retina. This review explores the application of a general intermolecular binding affinity calculator (GIBAC)-based binding selectivity strategy in the design of PDE5 inhibitors, aiming to enhance binding selectivity and minimize visual side effects. This GIBAC strategy integrates computational structural biological approaches to iteratively refine drug-target binding affinities, thereby improving target specificity and the structural biophysical limit for the efficacy-safety balance of PDE5 inhibitors. Through detailed analysis of PDE5’s and PDE6’s biological role and the molecular mechanisms underlying visual disturbances, this article underscores the necessity of target binding selectivity in PDE5 inhibitor design in future. Additionally, this article discusses the practical applications of GIBAC in computational drug discovery and design, along with the future directions and the potential for GIBAC to transform PDE5 inhibitor development, ultimately enhancing therapeutic outcomes and patient safety. Finally, this article calls for a GIBAC-based paradigm shift in computational drug discovery and design towards the continued development of the pharmaceutical industry.

Semaglutide is a potent GLP-1 receptor agonist used in the treatment of type 2 diabetes mellitus due to its ability to regulate blood glucose levels and promote weight loss. On July 26, 2021, with a manually defined set of computational structural and biophysical analysis, a simple Val27-Arg28 exchange was for the first time introduced in the backbone of semaglutide to strengthen the semaglutide-GLP-1R binding affinity. In this article, a comprehensive structural and biophysical analysis approach is for the first time proposed towards an exhaustive exploration of the semaglutide-GLP-1R sequence space for the design of semaglutide analogues with elevated binding affinity to GLP-1R, thereby potentially enhancing therapeutic efficacy of structurally conceivable semaglutide analogues. Through structure biophysics-based rational design and computational modeling, this article puts forward a set of semaglutide analogues and calculated their binding affinities to GLP-1R, with one particular semaglutide analogue-GLP-1R structural model reaching a K_d of 3.0 × 10^-8 M, while the K_d is 3.4 × 10^-6 M for the binding of native semaglutide to GLP-1. Overall, the computationally designed semaglutide analogues here constitute a hopeful approach for developing GLP-1 receptor agonists with improved efficacy for the treatment of diabetes and weight management in future.

Insulin therapy is a cornerstone in the management of diabetes, yet the pursuit of optimizing its pharmacokinetic profile remains a focal point in diabetes research. For instance, insulin icodec of Novo Nordisk is a novel long-acting insulin analogue that exhibits an extended duration of action, providing a promising once-weekly treatment option for diabetic patients. However, designing insulin analogues with lower receptor affinity than that of insulin icodec could still produce a further extended duration of action than that of insulin icodec through the suppression of receptor-mediated internalization of insulin analogues. In this study, therefore, I present the design of a novel series of insulin analogues engineered towards lower binding affinity to the insulin receptor compared to that of insulin icodec. Through computational structural biophysics-based rational design strategies, this article aims to further extend the duration of action while maintaining therapeutic efficacy of insulin analogues. Utilizing homology molecular modeling and structural biophysics-based binding affinity calculations, this article puts forward a set of insulin analogues with lower binding affinity to insulin receptor than that of insulin icodec from a structural and biophysical point of view. Overall, this article calls for subsequent in vitro and in vivo evaluations of the efficacy and prolonged action of the engineered insulin analogues to pharmacokinetically test whether these analogues acutally surpass that of insulin icodec as hopeful candidates for next-generation insulin analogue therapies with improved duration of action and enhanced control of blood glucose levels for diabetic patients in future.

From a structural point of view, understanding interfacial electrostatic features of ligand-receptor complexes is crucial for biophysics-based design of therapeutics with improved efficacy and safety. Here, with a high-throughput structural feature extraction approach, this article reports a set of electrostatic structural features from glucagon-like peptide-1 (GLP-1) and GLP-1 receptor (GLP-1R) complex structures determined using experimental tools. Leveraging a set of computational structural biophysical analyses, this article systematically characterized the electrostatic interactions within the GLP-1-GLP-1R complexes with two sets of criteria to identify interfacial salt bridges and hydrogen bonds. Overall, the results here reveal intricate details of electrostatic interactions critical for GLP-1 binding to its receptor GLP-1R, providing biophysical insights into the stabilization of the GLP-1-GLP-1R complex structure and the molecular basis of GLP-1/GLP-1R signaling. Furthermore, the electrostatic structural features extracted from GLP-1 and GLP-1R complex structures are useful in the development of a machine learning-based ligand-receptor binding affinity calculating model, i.e., a GLP-1-GLP-1R-specific general intermolecular binding affinity calculator (GIBAC), paving the way for accelerated discovery and structure-based design of drug candidates targeting the GLP-1/GLP-1R system with improved efficacy and safety.

The importance of conflict analysis and safety considerations during work zone intervals at signalized intersections cannot be overstated, as these periods pose unique challenges and safety risks for both motorists and pedestrians. Work zones introduce temporary changes to traffic patterns, lane configurations, and signal timings, which can disrupt the flow of traffic and increase the likelihood of conflicts between vehicles and pedestrians. By conducting comprehensive conflict analysis, it is possible to identify potential conflict points, such as merging areas, pedestrian crossings, and lane transitions, and implement targeted safety measures to mitigate risks. Additionally, considering safety considerations during work zone intervals is paramount to safeguarding the well-being of road users and minimizing the occurrence of conflicts or collisions. Measures such as enhanced signage, temporary traffic control devices, and increased enforcement efforts can help promote compliance with traffic regulations and ensure the safe passage of vehicles and pedestrians through work zones. This study investigates the dynamics of traffic behavior and safety implications within work zones at signalized intersections, aiming to address key challenges and enhance intersection management strategies. Through comprehensive analysis, varying frequencies of Vehicle-to-Vehicle (V2V) conflicts were observed across different movement directions, with significant occurrences identified in specific phases of the traffic signal cycle. Specifically, 69 V2V conflicts in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8 were recorded. Furthermore, the examination of Vehicle-to-Pedestrian (V2P) conflicts underscored the importance of prioritizing pedestrian safety, with notable occurrences observed in phases associated with pedestrian crossing movements. Meanwhile, despite the closure of left-turn movements, instances of red light running persisted, with 69 red light running events in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8.To mitigate these safety concerns during work zone intervals, proactive measures are essential. Strategies include improving communication through clear signage and advanced warning systems, enhancing enforcement efforts with red light cameras and increased police presence, and investing in infrastructure improvements such as temporary pedestrian facilities. Integration of real-time data from sensors, particularly LiDAR technology, offers significant advantages in detecting conflicts and red light runners during work zone intervals. LiDAR's precise, real-time data on vehicle and pedestrian movements, combined with its 360-degree coverage and high spatial resolution, facilitates accurate detection and tracking of potential conflict scenarios, contributing to enhanced intersection safety and traffic management efficiency. This study endeavored to conduct a traffic safety analysis during work zone intervals at a signalized intersection in Baltimore City, known for its high rate of traffic crashes, utilizing LiDAR sensor technology.

Immortal-time bias (ITB) is known to be common in cohort studies and distorts the association estimates between treated and untreated groups. We used data from the last of two large studies in an Italian province on COVID-19 vaccines safety and effectiveness incurred this bias, and aligned the entire population on a single index date, to correct the ITB. We considered the "all-cause deaths" outcome to compare the survival curves between the unvaccinated group and the various vaccination statuses. The all-cause deaths Hazard Ratios in univariate analysis for unvaccinated (reference) versus vaccinated with 1, 2, 3/4 doses were 0.88 (CI95: 0.78 –1.00; p-value 0.044), 1.23 (1.16–1.32; p-value ≤0.001) and 1.21 (1.14–1.29; p-value ≤0.001), respectively. The multivariate values were 2.40 (2.00–2.88; p-value <0.0001), 1.98 (1.75–2.24; p-value <0.0001), 0.99 (0.90–1.09; ns). The possible explanations of the trend of the Hazard Ratios as vaccinations increase could be a harvesting effect; a calendar-time bias, accounting for seasonality and pandemic waves; a case-counting windows bias; a healthy-vaccinee bias; or some their combination. With two and even with 3/4 doses the calculated Restricted Mean Survival Time and Restricted Mean Time Lost have shown a small but significant downside for the vaccinated populations.

Compared to the general population, patients with inflammatory bowel disease (IBD) are less likely to be vaccinated, putting them at an increased risk of vaccine-preventable illnesses. This risk is further compounded by the immunosuppressive therapies commonly used in IBD management. Therefore, developing new treatments for IBD that maintain immune function is crucial, as successful management can lead to better vaccination outcomes and overall health for these patients. Here, we investigate the potential of recombinant banana lectin (rBanLec) as a supporting therapeutic measure to improve IBD control and possibly increase vaccination rates among IBD patients. By examining the therapeutic efficacy of rBanLec in a murine model of experimental colitis, we aim to lay the foundation for its application in improving vaccination outcomes. After inducing experimental colitis in C57BL/6 and BALB/c mice with 2,4,6-trinitrobenzene sulfonic acid, we treated animals orally with varying doses of rBanLec 0.1-10 µg/ml (0.01 – 1 µg/dose) during the course of the disease. We assessed the severity of colitis and rBanLec’s modulation of the immune response compared to control groups. rBanLec administration resulted in a dose-dependent reduction in colitis severity (less pronounced weight loss, less shortening of the colon) and an improved recovery profile, highlighting its therapeutic potential. Notably, rBanLec-treated mice exhibited significant modulation of the immune response, favoring anti-inflammatory pathways (primarily reduction in a local [TNFα]/[IL-10]) crucial for effective vaccination. Our findings suggest that rBanLec could mitigate the adverse effects of immunosuppressive therapy on vaccine responsiveness in IBD patients. By improving the underlying immune response, rBanLec may increase the efficacy of vaccinations, offering a dual benefit of disease management and prevention of vaccine-preventable illnesses. Further studies are required to translate these findings into clinical practice.

This study assessed vaccination coverage and associated factors among children aged 12-23 months in the pastoralist Ethiopia. It was conducted in three woredas of the Afar region using a community-based cross-sectional mixed methods design with quantitative and qualitative methods. A total of 413 mothers with children aged 12-23 months participated in the quantitative study via a simple random sampling technique. Logistic regression was used to identify factors associated with vaccination, and thematic analysis techniques were used for qualitative data. The percentage of patients who received full vaccination was 25%. Based on vaccination card observations, the dropout rate from Pentavalent-1 to Pentavalent-3 was found to be 2.9%. Logistic regression analysis revealed significant associations between mothers and caretakers with formal education, those who owned mobile phones, had antenatal care (ANC) visits and birthed at a health faciltiy with full vacination. The overall proportion of full immunization is lower than the target set by the World Health Organization (WHO). The findings suggest that programs and policy makers should prioritize improving access and enrolment of women and caretakers, promoting mobile phone ownership, and encouraging ANC visits, and promotion of health facility deliveries, as these are are associated with higher rates of immunization

Micropollutants belongs to various groups of chemicals. One of the most diverse and large group of them are pharmaceuticals. The presence of pharmaceutical residues in wastewater poses a significant challenge to water quality and environmental health. This paper provides an overview of recent advancements in the removal of pharmaceuticals from water, focusing on various treatment processes and their effectiveness in eliminating micropollutants. Through a review of literature, including studies on ozonation, UV irradiation, sulphate radical-based tech-nologies, and photocatalytic processes, insights into degradation mechanisms and optimal con-ditions for their removal are synthesized. Additionally, with new legislation mandating the monitoring of selected micropollutants and the implementation of quaternary treatment in wastewater treatment plants, the paper discusses prospects for future research and recommen-dations for effective pharmaceuticals removal. Key actions include conducting comprehensive laboratory and pilot trials, implementing quaternary treatment of wastewaters, continuously monitoring of water quality, investing in research and development, and promoting collabora-tion and knowledge sharing among stakeholders. By embracing these strategies, we can work towards safeguarding water resources and protecting public health from the adverse effects of pharmaceutical contamination.

Piezoelectric c-axis oriented zinc oxide (ZnO) thin films, from 1.8 up to 6.6 µm thick, have been grown by radio frequency magnetron sputtering technique onto fused silica substrates. A delay line consisting in two interdigital transducers (IDTs) with wavelength λ = 80 µm was photolith-ographically implemented onto the surface of the ZnO layers. Due to the IDTs split finger con-figuration and metallization ratio (0.5), the propagation of both the fundamental, third and nineth harmonic Rayleigh waves is excited; also, three leaky surface acoustic waves (SAWs) were detected travelling at velocity close to that of the longitudinal bulk wave in SiO2. The acoustic waves propagation in ZnO/fused silica was simulated by using 2D finite-element method (FEM) tech-nique to identify the nature of the experimentally detected waves. It turned out that, in addition to the fundamental and harmonic Rayleigh waves, also high-frequency leaky surface waves are ex-cited by the harmonic wavelengths; such modes are identified as leaky-Sezawa (LS) waves under cut-off. The velocity of all the modes was found in good agreement with the theoretically calcu-lated values. The existence of a low-loss region for the Sezawa wave below the cut off was theo-retically predicted and experimentally assessed.

The individual and combined effects of extracellular products (ECP) from Arthrobotrys oligospora (Ao) and A. musiformis (Am) growth in liquid media against Haemonchus contortus L3 (HcL3) were assessed. The following methodological steps were established: isolation, morphological (MI) and molecular identification (Mol-I), assessment of nematocidal activity (NA) of fungal liq-uid culture filtrates (LCF) produced in two liquid media alone and in combination and finally, the myco-compound profile identification (MCP). The MI of both isolates suggested that the fungi corresponded to the species Ao and Am. This result was confirmed by PCR analysis followed by sequencing, alignment and obtaining coverage and similarity with respect to isolates reported in the NCBI database. Likewise, the highest Hc mortalities were 91.4% with individual LCF of Am and 86.2% with those of Ao at the highest concentration (100 mg/mL) in Czapek-Dox Broth. The combination of both LCF resulted in a similarly high larval mortality with no statistical differ-ences in relation to individual activity (P>0.05). The MCP showed the presence of alkaloids in both fungi. Coumarins, triterpenes and saponins were found only in Ao. Both fungi produced ECP with a high NA that could be identified and assessed in future studies as potential natural an-thelmintic compounds.

Despite the known benefits of precision agriculture, the adoption is challenging due to the cost of investment and the farm sizes. Therefore, profitability is an important aspect to consider. This study aimed to evaluate the net returns, profitability, and investment efficiencies of PA by different economic farm sizes. The study was based on data retrieved from FADN and Eurostat. The study examined four countries (Poland, Germany, France, and Romania) under field crop farming using an investment cost of €35 941 - €71 883, and a 20% and 15% reduction in the cost of crop protection and fertilizer usage respectively without compromising productivity. There is a positive relationship between the adoption of PA and farm returns for larger-scale farms. The result of the profitability and analysis of investment efficiency using NPV showed a positive value for economic farm sizes of €100 000 and above. Hence, it is not economically advisable that all farmers use PA technologies with the hope that they will be profitable but with public support (subsidies) more farms will be able to use PA and be profitable. Also, an opportunity to meet the goal of the European Union Green Deal of minimizing emissions that cause climate change.

This paper is the second part of a two-part report studying the responses of a typical point-contact elastohydrodynamic lubrication (EHL) problem to multiscale roughness that is mimicked by artificially generated waviness with different amplitudes, frequencies, and directions. The previous Part I paper (doi:10.3390/lubricants10120368) focuses on the full film regime, while the current paper focuses on the partial film regime. The amplitudes and frequencies are related to the feature geometry of smooth EHL problems. Generated waviness is input to a transient thermal EHL model. The simulation is conducted 1,600 times for different waviness parameters, loads, and speeds. Eight performance parameters are extracted: the asperity contact ratio, minimum film thickness, maximum pressure, central point film thickness, central point pressure, mean film thickness, coefficient of friction (COF), and the maximum temperature rise. The ratios of the first seven parameters with and without waviness and the asperity contact ratio values are plotted on the frequency–amplitude coordinate plane as contour maps. The influences of the amplitude, frequency, wave direction, load, and speed on the eight performance parameters are analyzed and summarized. The simulated data and plotted contour maps are provided to the readers in the Supplementary Material.

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.

In Germany, the phloem sucking planthopper Pentastiridius leporinus (Hemiptera: Cixiidae) currently represents the epidemiological driver for the spread of the syndrome “Basses Richesses” in sugar beet, which results in a reduced sugar content and an economic loss for the farmers. This disease is associated with the γ-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ and the Stolbur phytoplasma ‘Candidatus Phytoplasma solani’. Recently, P. leporinus was found in potato fields in Germany associated with Stolbur-like symptoms in this crop. In this study, we confirmed that the vector completes its lifecycle on sugar beet as well as on potato when reared under controlled conditions. Transmission experiments with adults of this vector combined with molecular analyses showed for the first time that both pathogens are transmitted by this vector to potato. For an accurate assessment of the Ca. P. solani and Ca. A. phytopathogenicus titers in the vector and host plants, gBlocks derived from the hsp20- and 16S rRNA gene were employed, respectively. For Ca. P. solani the limit of detection was determined in potato and sugar beet material. The results of this study will further research on the epidemiology of the syndrome “Basses Richesses” and “Stolbur” diseases and the response of host plants and vector insects to both pathogens.

Background: The accurate diagnosis of regional lymph node metastasis is critical for guiding treatment decisions in head and neck cancer patients. Despite advances in imaging techniques, detecting nodal metastasis remains challenging, leading to potential undertreatment or overtreatment. This systematic review aims to identify molecular markers associated with occult metastasis in Head and Neck Squamous Cell Carcinoma (HNSCC) patients. Methods: The present research was conducted following PRISMA guidelines. Prospero registration nr. CRD42024522985. Results: Through a comprehensive literature search and review process, 634 articles were considered, 103 of them were finally included. Conclusions: Several promising markers were identified, including miR-205, DSG3, pan-CK AE1/AE3, HPV-16, Activin-A, Cyclin D1, and NPL that demonstrated effectiveness across multiple studies. Future research should focus on exploring combination scoring systems to improve diagnostic precision and optimize treatment selection in HNSCC patients.

The goal of farmers operating in a market economy is to maximise profit. In the face of the changing political situation, the main social interest, besides food security, should be energy security. This article aims to indicate the direction of agricultural policy development so that it guarantees both the economic security of producers—farmers—and Europe’s energy security. The work uses data obtained from the agri benchmark Cash Crop database. DEA method and stepwise multiple regression were used. The research showed that plants are already grown in Europe which will ensure high energy efficiency of production without compromising farm financial results (including oats, peas and winter rye) and that improving the involvement of certain inputs results in improved production efficiency (among others, by expenditure on agricultural advisory services). The significance of the presented research results from the fact that the recent COVID pandemic and escalation of the military conflict in Ukraine have led to a renewed interest in the concept of EU energy security, i.e. generation of generating the greatest possible amount of energy within the EU, to be used both for food and non-food purposes.

This article provides a detailed analysis of non-invasive techniques for prediction and diagnosis of faults in internal combustion engines, focusing on the application of the Proknow-C and Methodi Ordinatio systematic review methods. Initially, the relevance of these techniques in promoting energy sustainability and mitigating greenhouse gas emissions is discussed, aligning with the Sustainable Development Goals (SDGs) of Agenda 2030 and the Paris Agreement. The systematic review conducted in the subsequent sections offers a comprehensive mapping of the state-of-the-art, highlighting the effectiveness of combining these methods in categorizing and systematizing relevant scientific literature. The results reveal significant advancements in the use of artificial intelligence (AI) and digital signal processors (DSP) to enhance fault diagnosis, as well as underscore the crucial role of non-invasive techniques in minimizing interference in monitored systems. Finally, concluding remarks point towards future research directions, emphasizing the need to develop digital twins for internal combustion engines and identify gaps for further improvements in fault diagnosis and prediction techniques.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder. A wealth of evidence indicates that the amyloid β (Aβ) aggregates result from dyshomeostasis between Aβ production and clearance, which plays a pivotal role in the pathogenesis of AD. Consequently, therapies targeting Aβ reduction represent a promising strategy of AD intervention. Tetramethylpyrazine nitrone (TBN) is a novel tetramethylpyrazine derivative with the potential for the treatment of AD. Previously, we demonstrated that TBN markedly improved cognitive functions and reduced Aβ, APP, BACE 1 and hyperphosphorylated tau levels in 3 × Tg-AD mice. However, the mechanism by which TBN inhibits Aβ deposition still unclear. In this study, we employed the APP/PS1 mice treated with TBN (60 mg/kg, ig, bid) for six months and N2a/APP695swe cells treated with TBN (300 μM) to explore the mechanism of TBN on the Aβ reduction. Our results indicated that TBN significantly alleviated cognitive impairment and reduced Aβ depositions in APP/PS1 mice. Further investigation of the underlying mechanisms revealed that TBN decreased the expression of APP and BACE1, activated the AMPK/mTOR/ULK1 autophagy pathway and inhibited the PI3K/AKT/mTOR/ULK1 autophagy pathway, as well as decreased the phosphorylation levels of JNK and ERK in APP/PS1 mice. Moreover, TBN was found to significantly reduce the mRNA levels of APP and BACE1, as well as those of SP1, CTCF, TGF-β, and NF-κB, transcription factors involved in regulating gene expression. Additionally, TBN was observed to decrease the level of miR-346 and increase the levels of miR-147 and miR-106a in the N2a/APP695swe cells. These findings indicate that TBN may reduce Aβ levels likely via reducing APP expression by regulating APP gene transcriptional factors and miRNAs, reducing BACE1 expression, and promoting autophagy activities.

This work focuses on identifying the most effective machine learning techniques and supervised learning models to precisely estimate power output from Photovoltaic (PV) plants. The performance of various regression models is analyzed by harnessing experimental data, including Random Forest, Support Vector Regression (SVR), Multi-layer Perceptron (MLP), Linear Regressor (LR), Gradient Boosting, and k-Nearest Neighbors (KNN). The methodology applied starts with meticulous data preprocessing steps aimed at ensuring dataset integrity. Following the preprocessing phase, which entails eliminating missing values and outliers using Isolation Feature selection based on a correlation threshold, is performed to identify relevant parameters for accurate prediction in PV systems. Subsequently, Isolation Forest is employed for outlier detection, followed by model training and evaluation using key performance metrics such as Root Mean Squared Error (RMSE), Normalized Root Mean Squared Error (NRMSE), Mean Absolute Error (MAE), and R-squared (R2). Among the array of models evaluated, Random Forest emerges as the top performer, highlighting promising results with an RMSE of 19.413, NRMSE of 0.048% and an R2 score of 0.968. Furthermore, the best-performing model is integrated into a MATLAB application for real-time predictions, thereby enhancing usability and accessibility for a wide range of applications in renewable energy.

Background: Here, we investigated the inflammaging and physical performance in older adults before and after the COVID-19 pandemic. Methods: Women(n=18) and men(n=7) older were evaluated before the COVID-19 pandemic(PRE), 12 months after the lockdown(POST), and 10 months after resuming exercise training(POS-TR). Physical tests [gait speed(GS) and timed-up-and-go(TUG)]; muscle strength (handgrip-HG), and serum cytokine levels were assessed. Results: The older women showed higher GS and TUG at POST than PRE and POST-TR, besides lower HG at POST-TR than PRE, whereas older men exhibited lower HG at POST and POST-TR than PRE. Both groups presented (1)lower IL-10 and IL-12p70 values in contrast to higher IL-6/IL-10 and IL-8/IL-10 ratios at POST than PRE; (2)higher IL-10 values and lower IL-8/IL-10 ratio at POST-TR than POST; (3)higher IL-12p70/IL-10 ratio at POST-TR than PRE and POST. Particularly older women showed: (4)lower IL-6 values at POST and POST-TR than PRE; (5)lower IL-8 and IL-10 values at POST-TR than POST; (6)and higher TNF-α/IL-10 and IFN-γ/IL-10 ratios at POST than PRE and POST-TR. Significant correlations between the variables were found in both groups. Conclusion: During the COVID-19 pandemic, detraining and resumption of exercise training promoted distinct alterations in physical capacity and inflammaging among older women and older men population.

This study aims to provide empirical evidence on whether using renewable and non-renewable energy, CO₂ emissions and the resulting changes in temperature and precipitation can alter cereal yields in European Union countries. To this end, a panel data set covering 1992-2021 has been used to analyse the impact of climate change and economic factors on cereal production in European Union countries. The study employed various analytical techniques to understand better the relationship between climate change, energy consumption, and economic growth. These included using annual average temperature and rainfall to measure climate change and energy consumption and economic growth to analyse the economic aspects. To achieve the objective, feasible generalised least squares (FGLS) models with robust standard errors and bootstrap and a quantile regression (QR) model with marginal analysis were employed. The Westerlund cointegration test confirmed the presence of cointegration between cereal production and climate variables, economic growth, and energy consumption. The results indicate that increases in temperature and precipitation may contribute to increased cereal production in European Union countries. In contrast, energy consumption, including renewable energy and CO₂ emissions, may have a nonlinear effect on cereal production. Quantile regression analysis suggests climate change may impact crop yields most in countries with low and moderate cereal production per hectare. Increased CO₂ emissions may increase yields in the initial period, but excessive CO₂ may negatively impact cereal production in the long term. It would be advisable for countries with low and moderate crop productivity to consider implementing technological advances and combating global warming by modernising cultivation methods and making greater use of renewable energy sources.

According to previous studies the median raphe region (MRR) is known to contribute significantly to social behavior. Beside serotonin, there are reports of a small population of dopaminergic neu-rons in this region. Dopamine is linked to reward and locomotion, but very little has been known about its role in the MRR. To address that, we first confirmed the presence of dopaminergic cells in the MRR of mice (immunohistochemistry, RT-PCR) and humans (RT-PCR). Next, we used chemogenetic technology in mice containing Cre enzyme under the promoter of the dopamine transporter (DAT). With the help of an adeno-associated virus, artificial receptors were expressed in the dopaminergic cells of the MRR (DAT-MRR). Four weeks later, extensive behavioral charac-terization started 30 minutes after the injection of the artificial ligand (Clozapine-N-Oxide). Stimu-lation of DAT-MRR decreased social interest without influencing aggression and with an increase in social discrimination. Additionally, inhibition of the same cells increased the friendly social be-havior during social interaction test. No behavioral changes were detected in anxiety, memory and locomotion. All in all, dopaminergic cells were present both in the mice and human MRR, and manipulation of dopaminergic neurons of the MRR elicited a specific social response.

Particulate matter (PM) contains heavy metals that affect various cellular functions and gene expression associated with an array of acute and chronic diseases, in humans. However, their specific effects on the stem cells remain unclear. Here, we report the effects of PM collected from Jeddah city on bone marrow mesenchymal stem cells (BM-MSCs) on proliferation, cell death, related gene expression and systems biological analysis aiming to understand the underlying mechanisms. Two different sizes (PM_2.5-₁₀) were tested in vitro at various concentrations (15 to 300 µg/ml) and durations (24 to 72 h). PMs induced cellular stress including membrane damage, shrinkage and death. Lower concentrations of PM_2.5 increased BM-MSCs proliferation, while higher concentrations decreased it. PM₁₀ decreased BM-MSCs proliferation in a concentration-dependant manner. The X-Ray Fluorescence spectrometric analysis showed that PM contains high levels of heavy metals. Ingenuity Pathway Analysis (IPA) and hierarchical clustering analyses showed that heavy metals were associated with signalling pathways involving cell stress/death, cancer and chronic diseases. qRT-PCR results showed differential regulation of the apoptosis genes (BCL2, BAX); upregulation of inflammation associated genes (TNF-a and IL-6) and downregulation of cell cycle regulation gene (P53). We conclude that PM could affect different cellular functions and predispose to debilitating diseases.

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs, discovered in the Neogene (Lower Pontian) subsurface sandstones in the northern Croatia (Pannonian Basin System). They represent small and large data samples. Also a standard statistical analysis of the data was made, followed by the qualitative-quantitative analysis of the maps, based on the selection of different values of the power distance exponent (p-value) for the K and L reservoirs maps. According to the qualitative analysis, for a small data set, p-value could be set on 1 or 2 giving the most optimal result, while for a large data set, a p value of 3 and 4 could be applied. By quantitative analysis, for the case of small data p=2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. Oppositely, a p-value of 3 and 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

Introduction: Gastric cancer (GC) is one of the most common cancers in the world. It is a very aggressive and heterogeneous tumor. GC does not cause symptoms, so it is often diagnosed in an advanced stage and associated with poor prognosis. Despite new treatment options, it still remains a therapeutic problem. An important element determining the method of treatment of locally advanced gastric cancer (LAGC) is the assessment of lymph node metastases in preoperative and postoperative imaging and/or histopathological examination.Aim: The assessment of lymphovascular invasion (LVI) in histopathological examination in patients with LAGC after gastrectomy. The groups of patients were divided into patients who received preoperative chemotherapy, patients without preoperative chemotherapy, and all patients. Additionally, we assessed the correlation between the presence of LVI and the number of lymph nodes collected during gastrectomy.Material and method: We collected patients with histologically confirmed GC after gastrectomy. The collected samples were divided into three subgroups: patients with neoadjuvant chemotherapy (NAC), patients without NAC, and all patients. Histopathological examination assessed the presence of LVI infiltration. We then assessed the correlation between the presence of LVI and the presence of lymph node metastasis in GC. Additionally, we assessed the correlation between LVI and the number of lymph nodes evaluated in patients in each group. The statistical analyses were performed using Statistica v13.3 and Microsoft Excel 2021. The significance limit was set at p<0.05.Results:The presence of LVI strongly correlated with node involvement, and the result was statistically significant in all patients and the group of patients treated with NAC. The difference was not statistically significant in the group not treated by NAC. Additionally, we did not observe a correlation between the presence of LVI and the number of metastatic lymph nodes in GC.Summary and Conclusions: The presence of LVI in a patient with GC indicates a high probability of lymph node metastasis, which should translate into therapeutic procedures. Assessment of LVI may help identify potential patients with lymph node metastases, particularly in patients undergoing endoscopic resection without planned lymphadenectomy. It is advisable to expand research on a larger scale in order to establish clear standards in this area.

Helical (frontier) molecular orbitals [Chem. Sci. 2013, 4, 4278] have been reported almost a decade ago. Yet, helical molecular spin densities [Mol. Phys. 2022, e2157774] have been observed by us only very recently. In this work, we have observed that some chiral boron clusters (B–16, B–20, B–24, and B–28) can simultaneously have helical molecular orbitals and helical spin densities. To our best knowledge, it is the first time we have discovered that inorganic boron clusters assume such an unprecedented property. We have unambiguously unraveled that it is chiral Jahn-Teller distortion of quasi-planar boron clusters that drives the formation of helical molecular spin densities. More interestingly, we have shown that elongation/enhancement of helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity properties of these boron clusters are also discussed. Implication of this work is straightforward that boron clusters may find potential applications in spintronics, such as molecular magnets.

The current study aimed to examine the relationship between sociodemographic variables (i.e., sex, age, marital status, educational level, socioeconomic status, and working mode) and physical activity levels declared by Chilean adults. The sample comprised 483 Chilean adults, 159 men (32.9%), and 324 women (67.1%) aged from 18 to 69 years old (36.5±12.0). The participants completed an ad-hoc sociodemographic online survey that included questions about characteristics of participants such as sex, age, educational level, household income, marital status, and working mode. Vigorous, moderate, and walking activities were measured using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), a self-administered questionnaire. Results: Men declared significantly higher vigorous and moderated physical activity than women. People aged 18 to 25, single or unmarried, and with the lowest household income, showed significantly higher scores in vigorous physical activity than those aged 26 to 45, cohabiting with a partner or married, and middle household income, respectively. Regarding working mode, people working on their job site said walking more than people not working, working on hybrid, and online mode. Our findings suggest that promoting strategies that increase physical activity during the pandemic is necessary to avoid health problems.

Spodoptera frugiperda (J.E. Smith) is a global agricultural pest that poses a threat to crop production, characterized by its refractory polyphagous nature that makes it difficult to control and may lead to damage to woody plants. However, research on its adaptability to woody plants remains limited. This study compares the feeding adaptations (survival rate, pupation time, pupation rate, weight, length, and feeding volume), protective enzyme activities, and feeding preferences of S. frugiperda on leaves of six economically significant tree species (Areca catechu, Aquilaria sinensis, Cocos nucifera, Camellia oleifera, Dalbergia odorifera and Hevea brasiliensis) and maize as a control treatment. The results indicate that A. sinensis as the most vulnerable trees in high risk, H. brasiliensis and C. nucifera presented varying degrees of susceptibility, A. catechu, C. oleifera, and D. odorifera were unsuitability for S. frugiperda. In conclusion, this report extensively explores the feeding effects of S. frugiperda on six economically important tree species, and provides insights into the feeding preferences on these plants, thereby informing the potential threat posed by S. frugiperda to economically vital trees.

Traditional population-based metaheuristic algorithms are effective in solving complex real-world problems but require careful strategy selection and parameter tuning. Parameter-less population-based optimization algorithms have gained importance due to their simplicity and efficiency. However, research on their applicability for solving large systems of nonlinear equations is still incipient. In this paper, a systematic review and detailed description of metaphor-less optimization algorithms is made, including the Jaya algorithm, the main Jaya variants for continuous optimization problems, with a focus on the Enhanced Jaya (EJAYA) algorithm, the three Rao algorithms, the best-worst-play (BWP) algorithm, and the very recent max-min-greedy-interaction (MaGI) algorithm. This paper also discusses a few previous parallelizations of the Jaya optimization algorithm, as well as recent GPU-based massively parallel implementations of the Jaya, Enhanced Jaya (EJAYA), Rao, and BWP algorithms developed by the authors. In addition, a novel GPU-accelerated version of the MaGI algorithm is proposed. The GPU-accelerated versions of the metaphor-less algorithms developed by the authors were implemented using the Julia programming language and tested primarily on GeForce RTX 3090 and NVIDIA A100 GPUs, as well as on Tesla V100S and Tesla T4 GPUs, using a set of difficult, large-scale nonlinear equation system problems. The computational experiments carried out produced quite significant speedups, which highlights the efficiency of the GPU-based versions of the metaphor-less algorithms developed for solving large-scale systems of nonlinear equations.

The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedure for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods - whenever available - is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented.

Inflammation is the body’s response to infection, injury, or other stimuli. Acute inflammation is a crucial component of the immune system’s defense, aimed at eliminating infected or damaged cells and halting disease progression. A subtle interaction between pro- and anti-inflammatory processes determines its progression to inflammation resolution or to chronic inflammation. In this study, we propose a generic model of inflammation through a system of reaction-diffusion equations involving various inflammatory and anti-inflammatory cells and cytokines. We investigate the formation of patterns, determined by the emergence of Turing structures, through linear stability analysis and numerical simulations. These theoretical findings are further supported by observations of similar patterns in skin diseases.

Heat pumps are increasingly becoming a key solution in the quest for decarbonization, offering a significant advantage over traditional boilers due to their superior energy efficiency. Not only can heat pumps provide both heating and cooling, but they also achieve thermal efficiencies exceeding 500%, which can seem to defy conventional expectations. The outdoor unit of a heat pump consists of about twenty main components, one of which is a complex network of copper pipes and sheets welded to valves, connectors, and other fittings. This set involves over thirty welded joints, highlighting a significant opportunity for reducing manufacturing time through process optimization. Copper is a critical material extensively used in various applications due to its excellent thermal and electrical conductivity. However, these very properties make welding copper particularly challenging, especially when aiming to automate and streamline industrial processes. Traditionally, connecting copper pipes and fittings is done through brazing, yet, alternative methods such as LASER welding, electron beam welding, resistance welding, friction welding, and ultrasonic welding also exist. This study focuses on the ultrasonic welding of copper, aiming to identify the optimal parameters that maximize the mechanical strength of overlapping joints and ensure effective tube sealing. Experimental results showed that for copper sheets, the best outcomes were achieved with a welding time of 3 s and a pressure of 6 bar. For tube sealing, the optimal conditions were a welding time of 3 s and a pressure of 4 bar. For both scenarios, the same variables were used, retention time of 0.62 s, initial pressure of 2 bar, retention pressure of 2 bar and sonotrode rising pressure of 3 bar. The analysis reveals that ultrasonic welding of copper can achieve both robust mechanical strength and reliable sealing, making it a promising technique for industrial applications.

The consumption of insects in the Democratic Republic of Congo is an ancient practice. The taxonomic identification and characterization of “entomophagy” seem urgent in Kinshasa following the related anthropogenic pressures (demographic pressure, uncontrolled urbanization) leading to a food crisis. This study aims to assess the diversity of edible insects and their consumption by the population of Kinshasa. A total of 360 people were surveyed to identify the insect species consumed in Kinshasa, the ecosystems that provide them, and the preference for species in relation to ethnolinguistic groups, churches (faith) and household size. Three species of insects most consumed in Kinshasa are: Gonimbrasia jamesonii, Cirina forda and Brachytrupes membranaceus. 41.9% of these insects are consumed by the Kongo ethno-linguistic group, 23.6% by the Luba, 20.6% by the Ngala and 13.9% by the Swahili. Inhabitants of the communes of Kassa Vubu (57%), Maluku (54%), Masina (54%) and Mont-Ngafula (39%) mainly consume C. forda and G. jamesonii. Luba and Kongo ethnolinguistic groups mainly consume C. forda while the Swahili and Ngala consume G. jamesonii. Catholic, Revivalist Church, Kimbagu, Islam, Protestant and Johovah's Witness believers mainly consume C. forda and G. jamesonii. This study made it possible to understand the socio-cultural influence on the degradation (pressure) of biodiversity and; contributes to SDGs 2 and 12 by 2023..

Many clinical research datasets have a large percentage of missing values that directly impacts their usefulness in yielding high accuracy classifiers when used for training in supervised machine learning. While missing value imputation methods have been shown to work well with smaller percentages of missing values, their ability to impute sparse clinical research data can be problem specific. We previously attempted to learn quantitative guidelines for ordering cardiac magnetic resonance imaging during the evaluation for pediatric cardiomyopathy, but missing data significantly reduced our usable sample size. In this work, we sought to determine if increasing the usable sample size through imputation would allow us to learn better guidelines. We first review several machine learning methods for estimating missing data. Then, we apply four popular methods (mean imputation, decision tree, k-nearest neighbors, and self-organizing maps) to a clinical research dataset of pediatric patients undergoing evaluation for cardiomyopathy. Using Bayesian Rule Learning (BRL) to learn ruleset models, we compared the performance of imputation-augmented models versus unaugmented models. We found that all four imputation-augmented models performed similarly to unaugmented models. While imputation did not improve performance, it did provide evidence for the robustness of our learned models.

The COVID-19 pandemics has had an unprecedented global impact, and the COVID-19 mass vaccination campaign has been commonly regarded as crucial to overcome the pandemics. Since all-cause mortality is the best way to measure the consequences of a health intervention, the present study was devised to analyze the all-cause mortality data of the United Kingdom (UK), which are made publicly available broken down by vaccination status. Data from April 2021 to May 2023 were retrospectively collected and analyzed according to age groups and vaccination status and the Standardized Mortality Ratio (SMR) for all-cause mortality and for non-COVID-19 were calculated in comparison to the corresponding unvaccinated groups. Results show that, since an age group dependent date, the all-cause mortality SMRs were increasing in any of the age groups considered. Initially, the all-causes death SMRs were less than 1 for all age groups, but due to their growth, for the age groups 18-39, 80-89 and 90+ years by a certain date they exceeded the reference value. For the other age groups, as long as the trend is maintained, it is possible to predict the date in which the SMR would reach the value 1. Non-COVID-19 SMR values show a very similar trend. Their initial values much lower than 1 suggest the presence of significant biases in the ONS dataset which lead to an underestimation of the risks for those vaccinated, as it is not plausible that the vaccine protects from causes other than COVID-19. The finding that all-cause mortality SMRs in vaccinated in comparison to unvaccinated people increases over time requires careful examination to understand the underlying factors. Meanwhile, the other major countries should undertake a systematic collection of all-causes mortality broken down by vaccination status, and should be implemented a moratorium of the promotion of mass vaccination campaigns.

Background: The two-stage technique combining the Endoscopic Retrograde CholangioPancreatography (ERCP) with common bile duct (CBD) clearance carried out before the laparoscopic cholecystectomy represents the most common approach for CBD stones. Over time, different techniques have been proposed to manage cholecysto- choledocholithiasis (CCL) advantageously in one stage. Among these, the laparoendoscopic rendez-vous (LERV) addresses the CCL issue with a laparoscopic cholecystectomy with insertion of a guide wire performed at initial stage of the procedure, followed by the clearance of the bile duct carried out by the endoscopists. The goal of this study was to evaluate the efficacy and safeness of LERV procedure recording results and complications, also making a comparison between our results and current literature. Methods: We reviewed our experience of all consecutive patients with cholecysto-choledocholithiasis managed with LERV between January 2018 and December 2023. LERV success rate, operative time, length of hospital stay, stone recurrence, incidence of endoscopic and surgical complications were analysed. Results: A total of 120 patients underwent LERV in our facilities. We reported a 97% LERV success rate, 1.6% conversion-to-open rate, a median intraoperative time of 122 (range 95-220) min. The median hospital stay was 4 (range 2-38) days. An overall morbidity of 15% was reported (18/120): 15 Clavien-Dindo type 1/2, 2 type 3a and one type 3b. In two cases a re-operation during the hospital stay was necessary. At a median follow-up of 14 months (3-59) five patients experienced stone recurrence requiring redo-ERCP in two cases. Conclusion: LERV offers the significant advantage of a single stage procedure and hospitalisation along with a lower risk of post-ERCP pancreatitis, failed CBD cannulation and complications. Our experience confirms safety and effectiveness of the technique for CCL management.

The objective of this study was to detail the monomer composition of resin-based dental materials sold in the market in 2023 and to evaluate the proportion of BPA derivatives in relation with their applications. A search on manufacturers’ websites was performed to reference resin-based dental materials currently on the market. Their monomer composition was determined from material safety data sheets and completed with a search on PubMed database. Among the 543 material compositions exploitable, 382 (70.3%) contained BPA derivatives. Among them, 56.2% contained BisGMA, 28% BisEMA, the most frequently reported. A total of 59 monomers of which 6 BPA-derivatives were found. 309 materials (56.9%) contained UDMA and 292 (53.8%) TEGDMA. Less than one third of materials identified contained no BPA derivatives. These proportions vary a lot depending on their applications with materials dedicated to dental care of young populations containing the highest proportions of BPA-derivatives monomers. The long-term effects on human health of the different monomers identified including BPA-derivatives monomers is a source of concern. For children and pregnant or lactating women arises the question to take a precautionary principle and avoid the use of resin-based dental materials likely to release BPA by opting for alternative materials.

Sarcopenia is associated with clinical complications, which increase mortality. Effective sarcopenia risk screening in the elderly should be grounded in a comprehensive assessment, encompassing both nutritional status and medication use. Current screening tools, while emphasizing muscular per-formance, exhibit limited sensitivity in identifying elderly individuals at risk of sarcopenia. This cross-sectional study aimed to develop a sarcopenia risk screening tool, named Sarc-Global, with enhanced sensitivity, incorporating factors pertinent to the overall health of the elderly. Utilizing the criteria established by EWGSOP2 for diagnosing sarcopenia, we evaluated 395 communi-ty-dwelling elderly individuals. This evaluation served as a reference for assessing the efficacy of two validated questionnaires, Sarc-F and Sarc-CalF, and our newly developed Sarc-Global. Con-structed through multiple logistic regression, Sarc-Global integrates variables such as sex, age, medication use, body mass index, arm circumference, and handgrip strength – all significantly associated with sarcopenia (p

Ethical considerations regarding our treatment of animals have gained strength, leading to legislation and a societal focus across various disciplines. This is a subject of study within curricula related to agri-food sciences. The aim was to determine the perceptions of agronomy university students concerning animal welfare in livestock production systems. A survey was conducted to encompass various aspects, from participants' sociodemographic attributes to their attitudes and behaviors regarding animal welfare and the consumption of animal products. Statistical analysis, performed using R software, delved into the associations between participants' characteristics and their perspectives on the ethical, bioethical, and legal dimensions of animal welfare. Associations between demographic factors and ethical viewpoints among students were identified. Gender differences emerged in animal treatment perceptions, while rural and urban environments impacted perspectives on various animals. Bioethical considerations revealed distinctive disparities based on gender and education in concerns for animal welfare, value perceptions, evaluations of animal behaviors, and opinions on animal research. It is crucial to distinguish between animal welfare and ethical considerations arising from coexisting with sentient beings capable of experiencing suffering. Ethical theories provide a lens through which we perceive our obligations toward animals. The responsibility to ensure animal welfare is firmly rooted in recognizing that animals, like humans, experience pain and physical suffering. Consequently, actions causing unjustified suffering or mistreatment, particularly for entertainment purposes, are considered morally unacceptable.

In this paper, we introduce a computational procedure that enables autonomous LEO laser trackers endowed with INSs to increase the current accuracy when shooting at middle distant medium-size LEO debris targets. The code is designed for the trackers to throw the targets into the Atmosphere by means of ablations. In case that the targets are eclipsed to the trackers by the Earth, the motions of the trackers and targets are modeled by equations that contain post-Newtonian terms accounting for the curvature of space. Otherwise, when the approaching targets become visible for the trackers, we additionally use more accurate equations, which allow to account for the local bending of the laser beams aimed at the targets. We observe that under certain circumstances the correct shooting configurations that allow to safely and efficiently shoot down the targets, differ from the current estimations by distances that may be larger than the size of many targets. In short, this procedure enables to estimate the optimal shooting instants for any middle distant medium-size LEO debris target.

The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, while providing useful information about the current state of a structure, are limited in the monitoring of defects over time and in linking them to predictive simulation. This paper presents a new approach to the predictive modeling of geometric defects. A combination of segmented from point clouds are parametrized using the convex hull algorithm to extract features from detected defects, and a stochastic dynamic model is then adapted to these features to model the evolution of the hull over time. Describing a defect in terms of its parameterized hull enables consistent temporal tracking for predictive purposes, while implicitly reducing data dimensionality and complexity as well. In this study, 2D point clouds analogous to information derived from point clouds were first generated over simulated life-cycles. The evolutions of point cloud hull parameterizations were modeled as stochastic dynamical processes via autoregressive integrated moving average (ARIMA) and vectorized autoregression (VAR) and compared against ground truth. The results indicate that this convex hull approach provides consistent and accurate representations of defect evolution across a range of defect topologies and is reasonably robust to noisy measurements, however assumptions regarding the underlying dynamical process play a significant the role in predictive accuracy. The results were then validated on experimental data from fatigue testing with high accuracy. Longer term, the results of this work will support finite element model updating for predictive analysis of structural capacity.

This study aimed to compare the levels of physical activity and quality of life reported by Chileans with and without osteoarthritis (OA). Educational level and monthly income data were collected from eighty-two participants (62 women and 20 men), of whom 41 had OA. Concerning the medical information of the persons suffering from OA, diseases, and date of diagnosis were indicated. The International Physical Activity Questionnaire-Short Form (IPAQ-SF) and its Elderly version (IPAQ-E) estimated physical activity levels. The Short Form 36 Questionnaire (SF-36) assessed health-related quality of life. The findings indicate that non-OA subjects scored higher on all dimensions of the SF-36, including physical function, physical role, bodily pain, general health, vitality, social function, emotional role, and mental health. Individuals with OA reported better physical function and role, general health, vitality, social function, and mental health when they walked more. However, no associations were found between any physical activity levels and the degree of pain in people with OA. Our findings underscore the critical role of investigating physical activity in OA patients to enhance their quality of life, particularly in light of the increased sedentary behavior observed post-pandemic.

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness consistency recovery method is pro-posed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from the images. After image-level processing, a combined underwater acousto-optic feature association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for the visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for performance against the OKVIS framework. The system achieves better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.

Background: To compare photodynamic therapy 41 and the use of probiotics in reducing halitosis assessed through gas chromatography and microbiome analysis. Methods: Participants aged from 18 to 25 years, showing sulfide (SH2) ≥ 112 ppb on gas chromatography, were selected. They were divided into 4 treatment groups: Group 1 - Tongue Scraping; Group 2- Antimicrobial Photodynamic Therapy (aPDT); Group 3- Probiotics; Group 4- Antimicrobial Photodynamic Therapy (aPDT) and Probiotics. The halimetry process was performed before, immediately after the treatments, 7 days, 14 days and 30 days after the initial collection. The collections for later microbiological analysis were made along with the halimetry, for the microbiome analysis. Results: Treatment with aPDT or probiotics under these experimental conditions was not able to change the bacteria present in the biofilm of the tongue. Conclusions: More research is needed to know the behavior of the oral microbiome in the presence of halitosis and the effectiveness of new treatments.

As critical biocontrol agents, Trichoderma and Metarhizium have demonstrated vast potential in disease prevention and pest control respectively. Current applications, however, are predominantly confined to singular use or simplistic combinations of the two fungi. This study innovatively utilizes Metarhizium and Trichoderma as experimental subjects, employing non-targeted metabolomics to compare the differences in metabolites between co-culture and separate fermentation. The metabolite distinctions in co-culture are meticulously analyzed using sample correlation, least squares discriminant analysis, cluster analysis, and KEGG enrichment analysis. Metabolome sequencing analysis is then applied to compare the co-culture fermentation filtrate with Trichoderma atroviride and Metarhizium anisopliae. Differential metabolite analysis found that co-culture had significantly up-regulated or down-regulated metabolites compared to singular cultures.However,significant metabolite discrepancies are discovered in singular cultures, notably the up-regulated metabolites such as osthole and spirocyclic amine, which have documented antibacterial functions that may prove effective against Fusarium graminearum. Ultimately, the findings from this research contribute to the exploration of synergistic applications of biocontrol fungi and serve as a valuable reference for future development of bio-pesticides for disease and pest control.

Background and Objectives: Age-related macular degeneration (AMD) is one of the major causes of central vision loss in the older age group and its dry form accounts for the majority of cases. Although several causes and mechanisms for the development and progression of AMD have previously been identified, the pathogenesis of this complex disease is still not entirely understood. As the inflammation and involvement of the immune system are strongly suggested to have a central role to promote the degenerative process and to stimulate the onset of complications, we aimed to analyze the prevalence of serum anti-retinal (ARA) and anti-endothelial cell antibodies (AECA) in patients with dry AMD and to determine their relationship with the clinical features of the disease, notably area of geographic atrophy (GA). Materials and Methods: We enrolled 41 patients with dry AMD and 50 sex- and age-matched healthy controls without AMD. The presence of ARA was determined by indirect immunofluorescence using monkey retina as an antigen substrate, while the presence of AECA was determined using cultivated human umbilical vein endothelial cells and primate skeletal muscle. Results: ARA were detected 36 (87.8%) AMD patients (titers range from 1:20 to 1:320) and in 16 (39.0%) (titers range from 1:10 to 1:40) of controls (p=0.0000). Twenty of the 41 patients (48.8%) were positive for AECA, while in a control group AECA were present only in 5 sera (10.0%). The titers of AECA in AMD patients ranged from 1:100 to 1:1000 and in the control group the AECA titers were 1:100 (p=0.0001). There were no significant correlations between the presence of AECA and disease activity. Conclusions: This study provides evidence for the possible involvement of an autoimmune process against retina and retinal vessel antigens in the pathogenesis of geographic atrophy associated with dry AMD.

Abstract Background: Temporomandibular disorders (TMD) are a range of clinical problems related to the temporomandibular joint (TMJ), chewing muscles, and surrounding facial structures. Functional magnetic resonance studies suggest that these disorders affect over 5% of the population. The relationship between dental occlusion and TMD has been a topic of debate in dentistry; some researchers suggest using lateral cephalograms and cephalometric data to identify which morphological profiles and types of malocclusion are most likely to cause TMD. The aim of this study is to identify the morphological profiles and associated skeletal malocclusions that have the greatest influence on the development of TMD. This will be accomplished through the analysis of cephalometric data obtained from cephalograms and condylar section images of patients from the Orthognathodontics Department of Chieti, who underwent low-dose cbct during their initial visit. Matherial and methods: This study, conducted at the Orthognathodontics Department of Gabriele D’Annunzio University in Chieti, examined a group of 67 patients (both males and females) presenting with signs of temporomandibular joint disorders (TMD). The inclusion criteria for the study were first-time TMD diagnosis, age 18 and above, and accessible medical records, wide field of view cone beam low dosage, and photographs. Patients with a history of tumor, trauma, surgical interventions in the jaw and facial area, fractures, and other craniofacial anomalies were excluded from the study. The aim of the study is to further understand the morphological profiles and associated skeletal malocclusions that contribute to TMD. Results: male patients: sagittal profile: 56% exhibited a skeletal Class II profile due to mandibular retrognathia. Vertical Profile: 73% were brachyfacial with a hypodivergent pattern. Dental Relationships: Increased overjet and a tendency towards deep bite were observed. 23% exhibited deep bite, 20% were normodivergent, and 8% were dolichofacial. The soft tissue profile tended towards flatness. Condyle Position: in Class II hypodivergent males, the condyle was non-concentric and positioned more posteriorly. In mesiodivergent males, the condyle was concentric, while in hyperdivergent males, it was slightly anterior. Female Patients: Sagittal Profile: 79% had a skeletal Class II profile with mandibular retrognathia. Vertical Profile: 47% were hypodivergent with reduced anterior facial height (105°). Dental Relationships: 17% exhibited deep bite, and 48% of those with a Class II profile had increased overjet. 43% were mesofacial, and 10% were dolichofacial. Condyle Position: In Class II hypodivergent and normodivergent females, the condyle was non-concentric and positioned more posteriorly. In hyperdivergent females, the condyle was positioned more anteriorly and higher in the fossa. Conclusion: The study highlighted significant differences in cephalometric parameters and condyle positions between male and female patients with TMD. A posteriorly positioned condyle was associated with a flattened condylar head, particularly in Class II hypodivergent profiles. These findings underscore the importance of individualized diagnostic and treatment approaches based on detailed cephalometric and condylar assessments. Further research is needed to explore the implications of these variations for TMD management and outcomes.

The intestinal microbial community of aquatic animals is closely related to the environment and thus affects the health of aquatic animals. Here we investigated annual variation of intestinal bacteria community structures of Ruditapes philippinarum cultured using two different methods, bottom sown and raft hanging. Bacterial diversity of seawater and sediment in different seasons was examined as well. Correlation between R. philippinarum intestinal bacteria community structures and environmental factors was analyzed. The results showed that in the two aquculture areas where R. philippinarum was differentially cultured, bacteria community structure of seawater and sediment both altered with seasons. However, neither seasonal changes nor difference in culture methods could significantly affect the intestinal bacteria community structures of R. philippinarum. Additionally, in terms of the alpha diversity of intestinal bacteria communities, there was no significant difference in R. philippinarum cultured using the two methods. For benthic cultured clams, alpha diversity of the intestinal bacterial communities was often higher than that of the environmental bacterial communities. For raft hanging cultured calms, Alpha diversity of the intestinal bacterial communities was normally comparable with that of the environmental counterparts. Beta diversity analysis showed that the intestinal bacterial community structure of R. philippinarum was mainly determined by both deterministic and stochastic processes. Correlation analysis showed that the intestinal bacterial community structures of R. philippinarum were determined by a variety of environmental factors. For clams collected from the benthic culture area, the intestinal bacterial structure was more correlated with the physicochemical properties of sediment in comparing with those of seawater. For clams collected from the raft-culture area, the intestinal bacterial structure was mainly determined by the phsicochemical characteristics of seawater. This study helps us to better understand the bacterial community structure in complex aquaculture ecosystems, providing a reference for healthy shellfish aquaculture and ecosystem protection in aquaculture area.

The study aimed to evaluate for the first time the degree of contamination of soil and crops with major and trace elements (Cd, Co, Cr, Cu, Ni, Pb, Zn, F, Na, Mg, Si, P, Cl, Fe, Al) in agricultural lands situated in the Lower Danube Basin, Galati and Braila counties (SE Romania), impacted by the steel industry. Soil samples from two depths (0–5 cm and 5–30 cm), as well as leaves and seeds of wheat, corn, and sunflower, were collected from 11 different sites. Along with elemental and mineralogical analysis, performed by HR-CS AAS, PIGE, SEM-EDX and ATR-FTIR, the soil pH, texture, organic matter, electric conductivity and CaCO3 content were investigated. The results showed that the levels of Cr (83.270–383.100 mg kg-1), Cu (17.110–68.151 mg kg-1), Ni (30.157–55.656 mg kg-1), and F (319–544 mg kg-1) in soil exceeded the Romanian regulations for sensitive use of the land. The pollution indices (Igeo, EF, PI, PERI) indicate that the soil is moderate to highly contaminated with Cr, Ni and Cu, while CSI and mERMQ indices suggested a relatively low risk for metal contamination. The concentrations of elements in plant tissues and bioaccumulation factors (BFs) show the soil-plant relation and health risk, but also the elemental selectivity of vegetal compartments. Thus, the results showed that wheat plants tend to exclude the bioaccumulation of certain elements in their tissues, while for Zn and Cu, the bioaccumulation pattern is different. In the case of corn, most BFs were below 1, indicating limited phytoaccumulation capacity. However, exceptions were observed for Cd, Zn, and Cu. Sunflower BFs indicate higher bioconcentration of Cu, Cd, and Zn in both the leaves and seeds compared to other elements. Chromium (Cr) contributes to non-carcinogenic dermal contact and ingestion hazards, with children being more susceptible to the adverse effects of this contaminant.

Danyore Valley area is a new prospect of copper-gold mineralization in the Gilgit-Baltistan province, Kohistan terrane, northern Pakistan. The mineralization is Cu-Au vein-type, localized within quartz veins and controlled by a fracture system mainly trending NW and NE. The host units belong to the Ladakh-Kohistan arc terrane, which covers northern Pakistan and north-western India and mainly comprises Precambrian basement units, Paleozoic to Cenozoic magmatic rocks, and sedimentary strata. The mineralized wall rocks consist of Mesozoic gabbro and diorite, which have undergone an intensive hydrothermal alteration. The study area, Danyore Valley, has yet to be explored. The geological background and mineralization type in literature are scarce. Moreover, the tectonic setting, petrogenesis, age, and magmatic evolution of the gabbro-diorite hosting unit still need to be better understood. Furthermore, the sources of metals and mineralized fluids and the types of mineralization and alteration are also unexplored. This research's contribution presents the field investigation, microscopic observations, whole rock geochemistry (major, trace, and REE), mineral analysis (EPMA), in situ LA–ICP–MS zircon U–Pb age dating, and zircon trace elements data for Danyore Valley Cu-Au prospect of Kohistan Batholith. The current research work's objectives are to (a) constrain the emplacement ages of the Danyore Valley host rocks, (b) determine the petrogenesis and tectonic environment of the gabbro-diorite wall rocks, and (c) identify the mineralization style and alteration patterns of Cu-Au occurrences. The U-Pb isotopic data of studied zircons from Danyore Valley diorite specimens yielded concordia ages from 111.60 ± 0.90 Ma to 112.18 ± 0.74 Ma. Correspondingly, the gabbro rock sample displayed a concordia age of 110.21 ± 0.99 Ma, indicating the crystallization time of the host bodies is mainly the early cretaceous period (∼110 Ma). The findings of this study reveal that the calc-alkaline affinity and arc-like geochemical characteristics of the gabbro and diorite rocks have been characterized by a significant enrichment in large-ion lithophile elements and an apparent depletion in high-field strength elements. The parent magma probably originated from a partial melting process of mantle depletion, and geochemical traits are characteristic of magmas associated with subduction zones. The Danyore Valley area of Kohistan terrane is defined by the existence of several mineralized quartz veins, which are mainly sulfide assemblages. The sulfide ore is mainly comprised of chalcopyrite, pyrite, and bornite, with a smaller amount of covellite and sphalerite and significant traces of gold, which are distributed mainly in sulfides. Copper and gold mineralization of Danyore Valley is associated with phyllic, propylitic, and carbonatization alteration assemblages. Metal-rich quartz veins exhibit a spatial correlation with diorite and gabbro rocks. The discovery of several surface Cu-Au vein-type mineralized areas accompanying outcrops of copper supergene enrichment at the Danyore Valley prospect is significant evidence (predictor patterns) of porphyry-style deposits in the Gilgit district, Kohistan terrane, northern Pakistan. This work also advocates the importance of the Danyore Valley prospect and Kohistan Batholith region for further detailed geological studies.

Telecoupling, interactions between social-ecological systems across large, often global, distances, drives negative impacts from the forest-based carbon market. Yet, these negative impacts have been underreported; and therefore, likely vastly underestimated. We identify how these unintended negative impacts may occur and provide recommendations for the forest-based carbon market to better account for externalities by prioritising positive social impact, expanding comprehensive ecological outcomes and improving transparency of investments. We call for a carbon market that is designed to account for its global interconnectedness.

Three-dimensional structure of six closely related hydrogenases from purple bacteria has been modeled by combining template-based and ab initio modeling approach. The results lead to conclusion that there should be 4Fe3S-cluster in the structure of these enzymes. Thus, these hydrogenases could drive attention for exploring their oxygen tolerance and practical applicability in hydrogen fuel cells. Analysis of 4Fe3S-cluster's microenvironment showed intragroup heterogeneity. Possible function of the C-terminal part of the small subunit in membrane binding has been discussed. Comparison of the built models with existing hydrogenases of the same subgroup (membrane-bound oxygen-tolerant hydrogenases) has been carried out. Analysis of intramolecular interactions in the large subunits showed statistically reliable differences in number of hydrophobic interactions and number of ionic interactions. Molecular tunnels were mapped in the models and compared with structures from PDB. Protein-protein docking showed that these enzymes could exchange electrons in oligomeric state, which is important for oxygen-tolerant hydrogenases. Molecular docking with model electrode compounds showed mostly the same results as with hydrogenases from E.coli, H. marinus, R. eutropha, S. enterica; some interesting results were shown in case of HupSL from Rba. sphaeroides and Rvx. gelatinosus.

Despite the diaphragm's direct connection with the heart through the phreno-pericardial ligament, little is still known about the role of this primary breathing muscle in the cardiovascular system. The purpose of the present study was to determine the relationship of diaphragm muscle thickness, thickening, and strength with selected cardiovascular parameters. Thirty participants who qualified for a three-week post-COVID physiotherapy program were examined. Diaphragm muscle thickness on the left and right sides was assessed using ultrasound. Blood pressure and heart rate were evaluated by an automatic oscillometric device, while the rest of the cardiovascular parameters were calculated using standardized formulas from the literature. We found a relationship between the left diaphragm dome thickening ratio and systolic blood pressure, pulse pressure, stroke volume, cardiac index, ejection fraction, and saturation level measured after the 6-minute walk test (6-MWT). Patients with better left diaphragm dome strength were characterized by a lower difference in systolic blood pressure, pulse pressure, stroke volume, cardiac output, cardiac power output, ejection fraction, cardiac index, and pressure-heart rate product between pre- and post-6-MWT measurements. There was no correlation between right diaphragm dome function and cardiovascular parameters. There was no association of left and right hemidiaphragm function with resting cardiovascular parameters. In conclusion, the strength of the left hemidiaphragm plays an important role in the regulation and modulation of cardiovascular parameters during physical exertion.

This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation-Impervious-Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1,263 million in 1991 to 1,409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.

The accompanying mechanical behavior during the flow of ore-rock dispersion is an important factor leading to the instability and failure of the orepass in the ore storage section. It is of great significance to accurately understand the instability characteristics of the well wall in the ore section, during the ore drawing process by understanding the flow characteristics and internal mechanical transfer mechanism of ore-rock dispersion. Using the discrete element method to analyze the flow characteristics, contact compactness, stress distribution characteristics and contact force probability distribution of the ore-rock dispersion, it realizes the quantitative characterization of the damage degree of ore-rock flow, and reveals the damage mechanism of mine storage wall. The results show that: (1) The friction between ore-rock particles, between ore-rock and well wall is an important reason for the change of the macroscopic flow form of ore-rock from “one” to “V” type. (2) The compactness and stress concentration of ores are increasing with the increase of storage depth, which is shown that with the increase of storage depth, the greater the probability of well wall instability. (3) The probability distribution of contact force strength between particles decreases exponentially in the whole process of ore drawing, in which the strong chain plays a major role in the stability of the dispersion system. (4) The number of overpressure and the overpressure coefficient can be used to quantitatively characterize the wall damage degree under the action of ore-rock flow. The dynamic side pressure decreases periodically in the form of exponential fluctuations, and the dynamic load formed by the ore-rock flow mainly played a role in the lower area of the ore storage section.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Recently, the concept of participatory democracy developed in the early 1970s has come back into fashion to revitalize the public involvement in political decision-making processes. Public par-ticipation in forest policy has been fully conceptualized by the scientific community in the late 1990s and early 2000s, but in many contexts the practical application remains unfulfilled. The aim of this study is to identify and analyze the participatory techniques used in literature to increase knowledge and facilitate its transferability into forest policies and strategies. A literature review was carried out to offer an overview of the participatory techniques adopted in the deci-sion-making process. At the end of literature review, 25 participatory techniques were identified based on over 2,000 publications. Afterwards, the participatory techniques were assessed using seven indicators (degree of participation, type and number of participants, time scale, cost, po-tential influence on policy). The results showed that the type of actors involved in the participa-tory technique is a key variable for the complexity and usefulness of the process, while the number of participants influences how information is disseminated. The Principal Component Analysis highlighted that the participatory techniques can be divided in three groups: the first group includes those techniques with a high degree of participation and a contextual high po-tential influence on policies, the second one includes techniques with a costs in terms of re-sources, while the third one consists of those with a large number of participants and reduced time requirements.

Treating central giant cell granuloma (CGCG) is challenging due to high recurrence rates and variable therapy responses. This study examines the efficacy of various treatments in reducing CGCG recurrence. A literature review explored outcomes of surgical excision, curettage, intralesional corticosteroid injection, and adjuvant therapy, considering factors like lesion location, size, and histological features. Aggressive surgical techniques such as en bloc resection were found to potentially lower recurrence rates compared to conservative approaches. However, treatment should be tailored to individual patient needs. Further research is needed to confirm these findings and improve treatment strategies. A concise literature review was conducted using PubMed, MEDLINE, and Google Scholar, focusing on papers published from 1986 to 2024. Search terms included "central giant cell granuloma," "recurrence," "treatment modalities," and "surgical excision". Studies reporting recurrence rates and treatment outcomes for CGCG were analyzed. Twenty-nine studies were reviewed, including six studies on surgical excision and curettage, eight studies on intralesional corticosteroid injections, six studies on calcitonin therapy, five studies on interferon alpha therapy and four studies on the therapy with denosumab. Analysis indicated that aggressive surgical treatments like en bloc resection were associated with lower recurrence rates compared to conservative methods. Predictors of recurrence included lesion size (&gt;3 cm), location (mandible), and aggressive histopathological features. Aggressive surgical excision combined with nonsurgical methods may lower recurrence rates, while conservative techniques remain viable in some cases. Further prospective research is needed to validate these findings and enhance CGCG treatment options.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

Titanium dioxide nanoparticles (TiO2NPs) are used in products that are applied to the human body, such as cosmetics and food, but their biocompatibility remains controversial. Pycnogenol (PYC), a natural extract of pine bark, exerts anti-inflammatory and antioxidant effects. In this study, we investigated whether PYC effectively alleviates pulmonary toxicity induced by airway exposure to TiO2NPs, and the beneficial effects of PYC were explained through the analysis of changes to the mechanism of cytotoxicity. TiO2NPs induced pulmonary inflammation and mucus production, increased the levels of malondialdehyde, and upregulated thioredoxin-interacting protein (TXNIP) and cleaved-caspase 3 (Cas3) in the lungs of mice. However, PYC treatment reduced the levels of all toxicity markers of TiO2NPs and restored glutathione levels. These antioxidant and anti-inflammatory effects of PYC were also demonstrated in TiO2NP-exposed human airway epithelial cells by increasing the mRNA levels of antioxidant enzymes and decreasing the expression of TXNIP, cleaved-Cas3, and inflammatory mediators. Taken together, our results showed that PYC attenuated TiO2NP-induced lung injury via TXNIP downregulation. Therefore, our results suggest the potential of PYC as an effective anti-inflammatory and antioxidant agent against TiO2NP-induced pulmonary toxicity.

A series of waterborne polyurethane (WBPU)/modified lignin amine (MLA) adhesives was prepared using modified lignin amine (MLA) as a chain extender by a prepolymer mixing process. A successful Mannich reaction was achieved during the synthesis of MLA by reacting lignin with bis(3-aminopropyl)amine. Higher tensile strength, Young’s modulus and thermal stability were recorded for WBPU/MLA adhesives with higher MLA contents. The WBPU/MLA adhesive materials were used to coat PVC substrates. The adhesive strength increased with increasing MLA content. More importantly, the MLA also enhanced the WBPU/MLA coating in terms of adhesive strength at moderately high temperatures as well as under natural weather exposed conditions. The adhesive strength was essentially unaffected with 6.48 mole% MLA in the WBPU/MLA coating after exposure to natural weather conditions for 180 days.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

In the pursuit of functional foods that promote health, nanoliposomal carriers have been used to enhance the stability and functionality of dairy products such as yogurt, promising therapeutic benefits. This study aimed to evaluate the impact of fucoxanthin-loaded nanoliposomes in yogurt on its antioxidant, physico-chemical, and rheological properties under cold storage (21 days). Fucoxanthin-loaded nanoliposomes were prepared using the ultrasonic film dispersion technique and added at concentrations of 0%, 5% and 10% at the yogurt (Y-C, Y-FXN-5, Y-FXN-10). Homogeneous and uniform nanoliposomes (98.28 nm) were ob-tained, preserving their integrity and functionality, and ensuring prolonged release and bioavailability of fucoxanthin. Y-FXN-10 maintained the highest antioxidant activity according to the DPPH (52.96%), ABTS (97.97%), and FRAP (3.16 mmol ET/g) methods. This formulation exhibited enhanced erythroprotective potential, inhibiting hemolysis, photohemolysis, and heat-induced hemolysis, thereby preventing lipid pe-roxidation. However, viscosity and firmness decreased, affecting the texture and appearance. Sensory properties such as color, flavor, aftertaste, texture, and overall acceptance improved with the 10% fuco-xanthin-enriched yogurt formulation. These results suggest that nanoliposomal are suitable for carries fuco-xanthin, their incorporation into food matrices is key to developing functional foods. Regulatory approvals and consumer perceptions regarding nanotechnology-based products must be addressed, emphasizing their safety and health benefits.

Objective: Lower extremity ischemia-reperfusion injury (IRI) may occur with trauma-related vascular injury and various vascular diseases, during the use of a tourniquet, temporary clamping of the aorta in aortic surgery, and acute or bilateral acute femoral artery occlusion. Mitochondrial dysfunction and increased basal oxidative stress in diabetes may cause an increase in the effects of increased reactive oxygen species (ROS) and mitochondrial dysfunction due to IRI. It is of great importance to examine therapeutic approaches that can minimize the effects of IRI, especially for patient groups under chronic oxidative stress. Cerium oxide (CeO2) nanoparticles mimic the antioxidant enzymes and act as a catalyst that scavenges ROS. In this study, it was aimed to investigate whether CeO2 has protective effects on skeletal muscles in lower extremity IRI in mice with streptozocin-induced diabetes. Methods: A total of 38 Swiss albino mice were divided into six groups as follows: control group (group C, n=6), diabetes group (group D, n=8), diabetes-CeO2 (group DCO, n=8), diabetes-ischemia/reperfusion (group DIR, n=8), and diabetes-ischemia/reperfusion-CeO2 (group DIRCO, n=8). DCO and DIRCO groups were given doses of CeO2 0.5mg/kg intraperitoneally 30 minutes before the IR procedure. A 120-minute ischemia-120-minute reperfusion period with 100% O2 was performed. At the end of the reperfusion period, muscle tissues were removed for histopathological and biochemical examinations. Results: Total antioxidant status (TAS) levels were found to be significantly lower in group DIR compared with group D (p=0.047 and p=0.022, respectively). In group DIRCO and total oxidant status (TOS) levels were found to be significantly higher than in group DIR (p

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

For the first time, mathematical models were obtained for evaluating biomedical images using fuzzy set methods on the basis of expert knowledge bases, which made it possible to carry out complex qualitative diagnostics and increase the reliability and efficiency of diagnosis, to form a methodology for analyzing biomedical images based on the fuzzy set apparatus, which allowed to more fully assess the level of the disease for glaucoma. Aspects of practical implementation of the optical-electronic system of biomedical information processing are considered. An algorithm and an optical-electronic system of biomedical image analysis are proposed, which are used to increase the informativeness and reliability of diagnosing eye pathologies, in particular, glaucoma.

The blood count is crucial for assessing bone marrow's cell production and differentiation during infections, gauging disease severity, and monitoring therapeutic responses. The profile of blood count in chronic form of paracoccidioidomycosis (PCM) has been insufficiently explored. To better understand the changes in hematological cells in different stages of the PCM chronic form, we evaluated the blood count, including immature blood cells in automated equipment, before and during the treatment follow-up of 62 chronic PCM patients. Predominantly male (96.8%) with an average age of 54.3 (SD 6.9) years, participants exhibited pre-treatment conditions such as anemia (45.2%), monocytosis (38.7%), and leukocytosis (17.7%) which became less frequent after clinical cure. Anemia was more prevalent in severe cases. Notably, hemoglobin and reticulocyte hemoglobin content increased, while leukocytes, monocytes, neutrophils, immature granulocytes, and platelets decreased. Chronic PCM induced manageable hematological abnormalities, mainly in the red blood series. Monocytosis, indicating monocytes' role in PCM's immune response, was frequent. Post-treatment, especially after achieving clinical cure, significant improvements were observed in various hematological indices, including immature granulocytes and reticulocyte hemoglobin content, underscoring the impact of infection on these parameters.

Considering the worldwide impact of heart failure, it is crucial to develop approaches that can help us comprehend its root cause and make accurate predictions about its outcome. This is essential for lowering the suffering and death rates connected with this widespread illness. Cardiomyopathies frequently result from genetic factors, and the study of heart failure genetics is advancing quickly. Dilated cardiomyopathy (DCM) is the most prevalent kind of cardiomyopathy, encompassing both hereditary and nongenetic abnormalities. It is distinguished by the enlargement of the left ventricle or both ventricles, accompanied by reduced contractility. The discovery of the molecular origins and subsequent awareness of the molecular mechanism is broadening our knowledge of DCM development. Additionally, it emphasizes the complicated nature of DCM and the necessity to formulate several different strategies to address the diverse underlying factors contributing to this disease. Genetic variations that can be transmitted from one generation to another can be a significant contributor to causing family or isolated DCM. Genetic variation also plays a significant role in determining susceptibility for acquired triggers for DCM. The genetic causes of DCM can have a diverse range of phenotypic expressions. It is crucial to select the most probable patients to have advantages from genetic testing. The purpose of this research is to emphasize the significance of identifying genetic DCM, the crucial relationships between genotype and phenotype, and the usefulness of genetic testing in the therapeutic care of both those affected and their relatives. This approach is expected to gain importance once treatment is guided by genotype-specific advice and disease-modifying medications.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

This article delves into the complex landscape of Bitcoin halving events, analyzing the historical context and implications of these pivotal occurrences within the cryptocurrency ecosystem and on its sustainability within the landscape of financial technologies. Through an examination of past halving events in 2012, 2016, and 2020, this study meticulously scrutinizes the conditions and prices of Bitcoin before and after each halving. By synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, reached peaks and price troughs. Furthermore, this research presents a comparative analysis of past halving events, drawing parallels and distinctions to elucidate the evolving nature of Bitcoin's price movements and market sentiment surrounding these milestone events. Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. By unraveling the intricate relationship between Bitcoin halving events and market behavior, this article seeks to provide a comprehensive understanding of the broader implications for Bitcoin's trajectory and the evolving landscape of the cryptocurrency market and its sustainability.

During the COVID-19 pandemic, the term “behavioural fatigue” became the centre of policy debates in Great Britain. These debates involved deciding when to go into lockdown and whether behavioural interventions could be effective. Behavioural interventions can only succeed where people’s capabilities, opportunities, and motivations to perform target behaviours are supported. Our retrospective data analyses examine the relationships between people’s capabilities, opportunities, motivations, and behaviours, i.e., adherence to lockdown guidelines. Our cross-sectional analyses include 17,962 unique participants in Great Britain who completed a survey over the initial 30 days of the first lockdown (April 2020). We examine trends in responses to each scale and then the relationships between the scales using Granger’s causality test with tests for stationarity and cointegration. A mixture of increasing and decreasing trends were identified for capabilities and opportunities. Decreasing trends were identified for motivation and behaviour. Granger’s causality tests found that capability forecasts opportunity and behaviour and that motivation forecasts opportunity. The discussion reiterates that to realize and maintain behaviour changes, policies surrounding people's capabilities, opportunities, and motivations must continue to support target behaviours.

This paper delves into the challenge of controlling the multiple synchronizations in mechatronic vibration machines featuring a duo of unbalanced rotors. Its primary aim is to not only attain specific rotation speeds but also to ensure the desired phase shift between these rotors. To tackle this issue, the paper employs a control law integrating cross-couplings. It conducts an analysis of the dynamics of a simplified linearized system, showcasing the robustness of the control system across varying plant parameters. Additionally, the paper outlines experimental findings from a multi-resonance vibrational laboratory setup. These findings effectively demonstrate the effectiveness of the proposed approach and highlight its potential applications. Crucially, the paper provides experimental evidence illustrating the capability to control vibration fields on the operational platform, a vital aspect pertinent to vibration transportation and bulk material mixing processes.

The electric vehicle (EV) industry is experiencing rapid growth, accompanied by continuous advancements in charging infrastructure to satisfy the rising need for fast and reliable charging. Particularly, the focus has shifted towards EV fast charging (EVFC) and its impact on the power grid. This paper presents a comprehensive analysis and survey of scholarly literature and projects conducted in this field over the past decade. The findings highlight the rising demand for EVFC and the need to address its potential adverse effects on the power grid. However, there is a noticeable lack of clear research guidance regarding charging time. To tackle these challenges and pave the way for future solutions, extensive research on DC fast charging, ultra-fast charging, and the integration of vehicle-to-grid (V2G) systems is required. This review paper thoroughly investigates the development of fast charging technology for electric vehicles (EVs), including its advantages and comparative analyses from various perspectives. Furthermore, it delves into the advancements in DC fast charging infrastructure, emphasizing charging standards and control modes. The study also investigates different categories of battery chargers for both on-board and off-board charging. Additionally, it explores the classification of DC-DC converters in the context of DC fast charging stations, discusses control strategies for EV systems, identifies existing challenges, and outlines future trends in EV fast charging.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

The species Lactococcus lactis is the bacterium extensively used in dairy industry. This bacterium is generally recognized as safe which was added to the European Food Safety Authority Qualified Presumption of Safety list. The major functions of this species in dairy fermentation are production of lactic acid from lactose, citric acid fermentation and hydrolysis of casein. But the representatives of this species producing bacteriocin substances can exert an inhibitory effect against spoilage bacteria. The aim of this study was to test three lactococcal strains isolated from raw goat milk for their postbiotic activity and to test their stability in goat milk yogurts in encapsulated form for further application. To reach the aims, validated methods were used. Three postbiotic active Lactococcus lactis subsp. lactis strains (identified by Blastn 16S rRNA analysis) from raw goat milk produced bacteriocin substances which in their concentrated form inhibited the growth of indicator enterococci and staphylococci up to 97.8 % with inhibitory activity up to 800 AU/mL. The encapsulated (freeze dried) lactococci fortified goat milk yogurts showed sufficient stability and survival in yogurts. The highest amount was reached using the strain MK2/8 (8.1 ± 0.0 cfu/g log 10) not influencing yogurt pH.

In recent years, long periods of drought and heat waves have become increasingly frequent, causing forest dieback phenomena that make stands more sensitive to biotic stressors. How trees may respond to extreme climatic events and which metabolites are involved under stress conditions is still not clear. In this study, we analysed by SPME how dieback (D) and non-dieback (ND) Hungarian oak trees from the San Paolo Albanese site respond to these climatic dynamics, in terms of volatile organic compounds (VOCs). For each group of trees, three wood samples were taken, each divided into four sub-samples with 5 growth rings, subjected to SPME and increase in basal area (BAI) analysis of the last 20 years. Dieback trees had a lower amount of leaves, and this condition may translate into less photosynthesis, less organic matter production and lower reserves of carbohydrates available for growth. Indeed, D trees showed lower radial increases and a lower content of aldehydes, terpenes, and fatty acids than ND trees, indicating a better health of ND trees compared to D trees. While D trees showed a reduction in terpenes, such as α-pinene, γ-eudesmol, and cyperene (with significant insecticidal activity), a reduction in aromatic aldehydes, such as furfural and 5-methylfurfural, and an increase in silanols (with antimicrobial function). Considering the different compounds’ contents between D and ND trees, our study could be useful for detecting bio-indicators to identify an early warning signal of dieback phenomena.

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on barium fluoride substrate close to the sample. Preliminary results of imaging thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and increase in background noise.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

Pragmatic trials aim to assess intervention efficacy in usual patient care settings, contrasting with explanatory trials conducted under controlled conditions. In aging research, pragmatic trials are important designs for obtaining real-world evidence in elderly populations, which are often underrepresented in trials. In this review, we discuss statistical considerations from a frequentist approach for the design and analysis of pragmatic trials. When choosing the dependent variable, it is essential to use an outcome that is highly relevant to usual medical care while also providing sufficient statistical power. Besides traditionally used binary outcomes, ordinal outcomes can provide pragmatic answers with gains in statistical power. Cluster randomization requires careful consideration of sample size calculation and analysis methods, especially regarding missing data and outcome variables. Mixed effects models and generalized estimating equations (GEEs) are recommended for analysis to account for center effects, with tools available for sample size estimation. Multi-arm studies pose challenges in sample size calculation, requiring adjustment for design effects and consideration of multiple comparison correction methods. Secondary analyses are common but require caution due to the risk of reduced statistical power and false-discovery rates. Safety data collection methods should balance pragmatism and data quality. Overall, understanding statistical considerations is crucial for designing rigorous pragmatic trials that evaluate interventions in elderly populations under real-world conditions. In conclusion, this review focuses on various statistical topics of interest to those designing a pragmatic clinical trial, with consideration of aspects of relevance in the aging research field.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

Glioblastoma is a highly aggressive brain tumor characterized by rapid growth, extensive infiltration, and poor prognosis. Understanding the complex interplay of biological processes driving glioblastoma progression is crucial for developing effective therapeutic strategies. In this study, we present a comprehensive mathematical model that incorporates key aspects of glioblastoma growth and dissemination, including tumor cell diffusion, angiogenesis, nutrient availability, molecular signaling pathways, and blood-brain barrier (BBB) interactions. The model is based on a system of coupled partial differential equations (PDEs) and ordinary differential equations (ODEs) that capture the spatiotemporal dynamics of tumor cell density, nutrient concentration, signaling molecule concentrations, and BBB integrity. We employ numerical simulation techniques, such as the finite difference method and the Runge-Kutta method, to solve the model equations and visualize the evolution of tumor growth and its associated biological processes. The model parameters are estimated using experimental data from the literature, and the model is validated against clinical observations. Furthermore, we perform a comprehensive sensitivity analysis to identify the key parameters that significantly influence tumor growth, diffusion, and dissemination. The sensitivity analysis reveals the relative importance of each parameter in driving glioblastoma progression and highlights potential targets for therapeutic interventions. Our computational framework provides a powerful tool for understanding the complex dynamics of glioblastoma growth and offers valuable insights into the underlying biological mechanisms. The model can be used to test hypotheses, predict tumor response to various treatment strategies, and guide the design of targeted therapies. The findings from this study contribute to the ongoing efforts in developing personalized treatment approaches for glioblastoma patients and improving their clinical outcomes.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Sporotrichosis’ clinical manifestations, lesions in the cutaneous or subcutaneous tissues, it is caused by dimorphic fungi of the Sporothrix complex, is a cosmopolitan mycosis that affects humans and animals. This study aimed to identify prevalent species in Minas Gerais, Brazil, and characterize virulence profiles and antifungal susceptibility associated with Sporothrix isolates. Isolates were identified using macro and micro-morphological traits as well molecular biology techniques. Antifungal susceptibility was determined using the Minimal Inhibitory Concentration test, while, virulence factors such as growth at different temperatures, biofilm formation, melanin production, and urease activity were assessed. Our findings revealed S. brasiliensis as a predominant species isolated. Urease activity was a crucial factor associated with growth at 50°C in S. brasiliensis isolates, highlighting their high thermotolerance. Furthermore, strains isolated from humans produced a more robust biofilm compare to those from felines. Strains of S. brasiliensis isolated from Felis catus exhibited faster melanin production, decreased susceptible to antifungal agents tested, and superior growth capacity at 50°C to strains isolated from humans. Therefore, our study highlights the prevalence of S. brasiliensis causing sporotrichosis in both human and felines. However, it underscores the circulation of different strains, with varying levels of virulence and susceptibility to antifungal agents.

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

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

Human milk (HM) feedings are associated with reduced risks of neurodevelopmental and neurocognitive delays and systemic inflammatory diseases in infants born prematurely and/or at a low birth weight. Utilizing a neonatal piglet model, HM feedings were compared to bovine milk-derived infant formula (IF)-feedings with the aim of understanding the underlying mechanisms involved in reducing these risks. Six male piglets at postnatal-day (PD)2 were randomized into two feeding groups: HM-fed (n = 3) or IF-fed (n = 3) for 28 days. At 3- and 4-weeks-old, piglet memory and learning performance were assessed using novel object recognition (NOR). At PD30 piglets were euthanized, and whole brains were excised, weighed, and preserved for further analyses, and brain microglial morphology, and systemic inflammatory cytokines were quantified. During NOR, HM-fed piglets had significantly more non-novel revisits at both 3- and 4-weeks-old compared to IF-fed piglets. Microglia of HM-fed piglets had longer processes, more branch points, more endpoints, and a larger territorial volume compared to IF-fed piglets at PD30. In a neonatal piglet model, HM-feedings may improve cognition and reduce brain inflammatory response compared to IF-feedings.

(1) Background: Cardiac resynchronization therapy (CRT) is essential for patients with heart failure and ventricular conduction abnormalities. Cardiomyopathy often includes left bundle branch block (LBBB) marked by delayed activation of the LV lateral wall and a widened QRS complex. Following CRT, patients with heart failure and LBBB have better outcomes and quality of life improvements. Various electrocardiographic and clinical parameters are thought to predict this improvement. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a reliable tool for measuring the quality of life in these patients. (2) Methods: We performed an observational prospective study over 69 individuals diagnosed with cardiac failure and dilatative cardiomyopathy with low FE and major LBBB and analyzed the correlations between patient outcomes after the procedure and the demographic, clinical, and electrocardiographic parameters, which include systolic blood pressure, ECG morphology elements, QRS duration, QRS area and associated comorbidities. (3) Results: Following our analysis a correlation between QRS area, intraprocedural systolic blood pressure, QRS duration and CRT outcomes assessed by the KCCQ score was observed which reflected that CRT has a hemodynamic impact and also affects the severity of ventricular asynchrony.; (4) Conclusions: The significant correlations observed with the KCCQ score show how CRT therapy impacts patients' quality of life, symptom burden, and functional status.