Accurately estimating shrub biomass in arid and semi-arid regions is critical for understanding ecosystem productivity and carbon stocks at both local and global scales. However, capturing the shrub biomass accurately by satellite observations is challenging due to the short and sparse features of shrubs. In this study, we presented a framework to estimate shrub biomass at a 10m spatial resolution by integrating ground in-situ data, unmanned aerial vehicle (UAV), Sentinel-2, and Sentinel-1 observations. The pilot study was conducted in the Helan mountains of Ningxia province, China. First, the spatial distribution map of shrubland and other land cover types was generated in 2023. Then, a prediction model of shrub biomass was developed in a Random Forest Regression (RFR) approach driven by different predicted variable datasets based on in-situ measurements, UAV, and satellite images. Finally, the developed model was used to produce the biomass map of shrubland in 2023. The uncertainty was characterized by creating a standard deviation (SD) map using the Leave-One-Out Cross-Validation (LOOCV) method in the shrub biomass estimates. The resultant shrubland distribution map in 2023 has an F1 score of 0.92. The shrub biomass model driven by spectral bands and vegetation indices (R2= 0.62) demonstrated superior performance than that only driven by spectral bands (R2=0.33) or vegetation indices (R2=0.55). The uncertainty of the estimated biomass was lower than 4%, with the lowest values (<2%) happening in the high shrub coverage (>30%) and biomass production (>30kg/m2) regions. Furthermore, the findings show that the magnitude of shrub biomass was affected by the aridity and precipitation significantly in the study region. This study provides a workflow to accurately monitor the biomass of shrublands in a complicated environment based on remote sensing images from multi-platform observations.

Background: Ankle fractures, comprising about 10% of musculoskeletal injuries, pose a significant healthcare burden with an increasing incidence, particularly among an aging population. This study focuses on isolated Danis-Weber type B fractures. Recent trends lean towards surgical intervention for anatomical restoration, quicker recovery, albeit with associated complications. This report aims to assess the safety and efficacy of NewClip narrow locking plate system with early weight bearing in treating isolated fibular fractures. Methods: The study includes patients with Danis-Weber type B fractures surgically treated with NewClip narrow locking plate system. Exclusions involved nondisplaced fractures, open fractures, or those requiring additional fixation.Results: Fifteen patients were enrolled in this study. Minor complications, including wound swelling, were observed in two cases. The Visual Analogue Scale (VAS) for pain exhibited a steady decline postoperatively, with almost complete resolution by the third month. At three months, the FAOS demonstrated excellent results, and final follow-up at twelve months revealed complete osseous healing without complications.Conclusions: The use of this type of plates in treating isolated fibular fractures with early weight bearing shows promising results in terms of fracture healing, pain resolution, and functional outcomes warranting further investigation with larger cohorts.

In light of the critical and emerging global challenge posed by the increasing frequency and severity of heatwaves in recent decades, this study demonstrates a practical and robust workflow that bridges the gap in understanding how the effective integration of remote sensing data with ground-based observations can facilitate a comprehensive assessment of spatiotemporal heatwave patterns and trends in the central region of Thailand. This research transcends traditional methods, utilizing air temperature (Tair) and satellite-derived land surface temperature (LST) data from 1981 to 2019. Results exhibit that an analysis of Tair indicates increasing daytime heatwaves in peri-urban areas, with significant trends in heatwave number (HWN), heatwave frequency (HWF), and heatwave duration (HWD), heatwave amplitude (HWA) rises in urban settings while nighttime heatwaves significantly intensify in rural locales. Notably, LST trends reveal varied patterns, with peri-urban areas showing marked daytime increases in heatwave magnitude (HWM), HWA, and HWF. Correlation analysis (p=0.05) highlights strong daytime associations between Tair and LST in rural (HWN, HWF, HWD, r&gt;0.90) and peri-urban (HWM, HWA, r&gt;0.65) regions. Overall, this study advances approaches to the adaptable measurement and spatial-temporal pattern of heatwave-related risk areas, providing insights for decision-makers to develop sustainable practices and strategies for climate change adaptation.

Precise individual tree or sample-based inventories derived from 3D point cloud data of mobile laser scanning can improve our comprehensive understanding of the structure, function, resilience, biodiversity, and ecosystem services of urban forests. This study assessed the performance of a hand-held laser scanning system for the extraction of tree position, diameter at breast height (DBH) and tree height (H) in an urban area. A total of 2083 trees of 13 species from 34 plots were analyzed. The results showed that the registration of tree positions using ground control points (GCPs) demonstrated high accuracy, with errors consistently below 0.4 m, except for a few instances. The extraction accuracy of DBH for all trees and individual species remained consistently high, with a total root mean square error (RMSE) of 2.06 cm (6.89%) and a bias of 0.62 cm (2.07%). Notably, broad-leaved trees outperformed coniferous trees, with RMSE and bias values of 1.86 cm (6%) and 0.76 cm (2.46%) compared to 2.54 cm (9.46%) and 0.23 cm (0.84%). Tree height extraction accuracy varied significantly among different species, with R2 values ranging from 0.65 to 0.92. Generally, both DBH and height were underestimated. Linear mixed effects models (LME) were applied to evaluate factors affecting the performance of HLS with the plot as a random factor. LME analysis revealed that plant type and terrain significantly influenced the accuracy of DBH and H derived from HLS data. Other fixed factors of plot area, tree density and trajectory length didn’t have significance. With a large sample size, we concluded that the HLS demonstrated sufficient accuracy in extracting individual tree parameters in urban forests.

In March 2013, a novel avian influenza A H7N9 virus was emerged in China, which cause rapidly progressive pneumonia and with a high fatality rate. Serologic studies to evaluate neutralizing antibodies of infected patients and birds are invaluable tools for immunogenicity research of H7N9 and epidemiological investigation. Conventional neutralization assays are laborious and time-consuming which also hampered by biosafety requirement. In this study, We construct and produce pseudovirus bearing the full-length hemagglutinin (HA) of H7N9 virus in the Env-defective, luciferase-expressing HIV-1 backbone. The production of lentiviral pseudovirus was analysed by HA gene specific real-time reverse-transcription PCR, transmission electron microscopy (TEM), and Western Blot assay to prove the nucleic acid replication, the morphology of virus, and the expression of HA protein in pseudovirus. After that pseudovirus based inhibition assay was established to detect neutralizing antibodies of a panel of serum samples. Our results demonstrated that H7N9 pseudovirus which had single-cycle infection was generated. By comparing the neutralization antibody titers, pseudovirus based neutralization test could be recognized as an alternative of conventional microneutralization (MN). Hence, we conclude that it is possible to use pseudovirus inhibition assay to screen sera samples, as well as evaluate vaccine-induced neutralizing antibodies against H7N9 virus.

Chronic pancreatitis is a progressive fibroinflammatory disorder with no currently satisfactory treatment. Emerging evidence suggests an association between gut microbial dysbiosis and chronic pancreatitis. Although direct causative evidence is lacking, it is hypothesized that the gut microbiota may play a pivotal role in modulating pancreatic function via the gut-pancreas axis. Thus, modulating the gut microbiota through the administration of probiotics or prebiotics may alleviate pancreatic disorders. In this review, we first propose the potential mechanisms by which specific probiotics or prebiotics may ameliorate chronic pancreatitis, including the alleviation of small intestinal bacterial overgrowth (SIBO), facilitation of short-chain fatty acids (SCFAs) production, activation of the glucagon-like peptide 1 receptors (GLP-1Rs) in the pancreas. Since there are currently no probiotics or prebiotics used for the treatment of chronic pancreatitis, we have discussed research in other disease models that use probiotics or prebiotics to modulate pancreatic endocrine and exocrine functions and prevent pancreatic fibrosis. This provides indirect evidence for their potential application in the treatment of chronic pancreatitis. We anticipate that this research will stimulate further investigation into the gut-pancreas axis and the potential therapeutic value of probiotics and prebiotics in chronic pancreatitis.

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

Bigeye grunt Brachydeuterus auritus is an important economic species in the waters off Sierra Leone in West Africa, with great ecological value. Based on the survey data of bottom trawl nets from 6 voyages from 2019 to 2021, the body weight-length relationship (WLR), as well as their relative fatness, were studied in depth using the method of body length and its corresponding mean body weight. This study fitted the WLR of bigeye grunt by gender, calculated its fullness, and analyzed the influence of environmental factors. The results showed that month and gender had a significant impact on body length and weight distribution (P&lt;0.01). There was a highly significant negative correlation (P&lt;0.01) between the condition factor (a) and the allometric factor (b) in the WLR, and salinity significantly affects b (P&lt;0.05). The (lga)/b ratio was less affected by environmental factors which may be related to the body size and density of the fish. The difference in b between male and female populations was extremely significant (P&lt;0.01). The relative fatness had significant seasonal variation characteristics, with highly significant effects of sex and body length (P&lt;0.01). With increasing body length, the relative fatness showed two types of changes, continuously increasing and first increasing then decreasing, with salinity and b significantly affecting the type of change (P&lt;0.05) and depth having a highly significant effect (P&lt;0.01). The bigeye grunt off the coast Sierra Leone exhibited significant seasonal growth characteristics, with significant differences in growth characteristics between male and female individuals. This study suggested that salinity may be the main factor affecting its growth and development. In addition, this study hypothesised that the peak breeding season may occur during the dry season, beginning in December and ending before April of the following year. The study provides updated and more comprehensive insights into the biology and ecology of the bigeye grunt offshore Sierra Leone, West Africa, which can provide scientific basis for its resource assessment, development and utilization, and resource management.

We have carried out a systematic review of the scientific literature published on PM and, more specifically, on its presence in fish and seafood of interest to the population from Mediterranean area. Given its preference and wide acceptability in the scientific community, we followed the PRISMA. The potential functional and clinical toxicity in humans due to MP in fish must be considered by the chemical composition of the microplastics the presence of PM and its additives, associated contaminants and pathogens in fish and shellfish, as well as the possible effects on human health, requires improving legislation on evaluation and providing a basis for consumer protection.

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

In this study, we investigated the features of co-infection with SARS-CoV-2 and nonpathogenic strain LEV8 of coxsackievirus A7 or enterovirus A71 for Vero E6 cells and Syrian hamsters. The investigation of co-infection with SARS-СoV-2 and LEV-8 or EV-A71 in the cell model was shown that a competitive inhibitory effect for these viruses were especially significant against SARS-CoV-2. Pre-infection with enteroviruses in animals caused more than a 100-fold decrease in the levels of SARS-CoV-2 virus replication in the respiratory tracts and more rapid clearance of the lower respiratory tract from infectious SARS-CoV-2. Co-infection with SARS-CoV-2 and LEV-8 or EV-A71 also reduced the severity of clinical manifestations of the SARS-CoV-2 infection for animals. Additionally, the histological data illustrated that co-infection with nonpathogenic coxsackievirus decreased the level of pathological changes by SARS-CoV-2 in the lungs. Research into the chemokine/cytokine profile demonstrated that the studied enteroviruses efficiently triggered this part of antiviral immune response, which can be associated with significant inhibition of SARS-CoV-2 infection. These results demonstrate that there exists a strong viral interference between the studied nonpathogenic strain of coxsackievirus A7 or enteroviruses A71 and SARS-CoV-2 pathogenic for humans in vitro and in vivo.

A method based on ultra performance liquid chromatography with diode array detector (UPLC-DAD) was developed for quantitative analysis of five active compounds and chemical fingerprint analysis of Rosa rugosa. Ten batches of Rosa rugosa collected from different plantations in the Xinjiang region of China were used to establish the fingerprint. The feasibility and advantages of the used UPLC fingerprint were verified for its similarity evaluation by systematically comparing chromatograms with professional analytical software recommended by State Food and Drug Administration (SFDA) of China. In quantitative analysis, the five compounds showed good regression (R²=0.999 5) within the test ranges and the recovery of the method was in the range of 94.2–103.8%. The similarities of the fingerprints of 10 batches of the samples were more than 0.981. The developed UPLC fingerprint method is simple, reliable and validated for the quality control and identification of Rosa rugosa. Additionally, simultaneous quantification of five major bioactive ingredients in the Rosa rugosa samples was conducted to interpret the consistency of the quality test. The results indicated that the UPLC fingerprint as a characteristic distinguishing method combining similarity evaluation and quantification analysis, can be successfully used to assess the quality and to identify the authenticity of Rosa rugosa.

The River Habitat Survey (RHS) is a method for assessing the conditions of a river channel and valley, taking into account hydromorphological factors, and assessing the degree of naturalness or the degree of anthropogenic alteration within the channel and valley based on physical and landscape data. The hypothesis tested in this study was that the quality of river habitats demonstrated using the RHS should translate into the composition of their fauna. We investigated aquatic bugs (Heteroptera Aquatica), which are a group with considerable dispersal abilities and, at the same time, composed of stenotopic species associated with a particular environment as well as of eurytopic elements inhabiting a wide range of environments (REF). The research was carried out in a small lowland river, the River Krąpiel (north-western Poland) at 6 sites with 43 sub-sites included. Our analyses suggest the RHS method can predict the composition and quality of the aquatic bug fauna inhabiting a given river. Indicators of river habitat quality (HQA and RHQ) will be associated with different habitat types depending on the geographic location and type of river, once indicating habitats associated with the mainstream river and mineral substrate (mountain and small lowland rivers) and at other times habitats covered by vegetation with relatively slow water flow (large and medium lowland rivers). Therefore, RHS may be a good method for estimating the water bug fauna, linking it to the size and character of the river.

Gestational diabetes mellitus (GDM) pathophysiology comprises clinical and genetic factors. In fact, GDM has been associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT), 255 (16.1%) with GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed by IPLEX Mass ARRAY PCR selecting 110 SNPs based on literature references. The SNPs showing the strongest likelihood of GDM development were the rs10830963, rs7651090 and rs1371614 in CAU and rs1387153 and the rs9368222 in LAT. Clinical variables including age, pre-pregnancy body mass index and fasting plasma glucose (FPG) at 12 gestational weeks predicted the risk of GDM (AUC 0.648, 95%CI 0.601-0.695 in CAU; AUC 0.688, 95%CI 0.628-9.748 in LAT) and adding the SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95%CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women. An RCT is underway to demonstrate its usefulness

Background: Historically, in the United States and globally, women have supported other women before, during, and after childbirth. Birth doulas are considered an important component to eliminating racial disparities in maternal morbidity and mortality. To address disparities in birth outcomes, Healthy Women Healthy Futures (HWHF) provides free birth and postpartum doula services to low-income women and communities of color in New York City. Methods: Secondary analysis of program data (n=364) collected between 2020 and 2021 was conducted. Univariate and multivariable analyses focused on: method of delivery, preterm birth, low-birthweight birth, breastfeeding, maternal-infant skin contact. The key exposure variable was total doula hours. Results: Clients who received prenatal doula support had low rates of preterm birth (8.8%) and low birthweight (7.1%), and high rates of vaginal delivery (69.1%), breastfeeding in the hospital (90.9%), and maternal-infant skin contact (78.2%). Multivariable analysis did not identify an association between number of doula hours and any of the five outcomes examined. Conclusion: While descriptive results point to positive birth outcomes, these effects did not persist in multivariable analyses. Data quality concerns from this intervention likely hindered the ability to detect a program impact, emphasizing the importance of funding to support data collection and management activities.

This study investigates the performance and environmental impact of n-butanol blended with Jet-A fuel in turbo-engines, aiming to assess its viability as a sustainable aviation fuel (SAF). The research involves experimental testing of various blends, ranging from low to high concentrations of methanol, to determine their effects on engine performance and emissions. The experimental setup includes comprehensive measurements of engine parameters such as thrust, fuel consumption rates, and exhaust gas temperatures. Emissions of nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and unburned hydrocarbons (HC) are also analysed to evaluate environmental impacts. Key findings indicate that n-butanol/Jet-A blends can significantly enhance combustion efficiency and reduce emissions compared to conventional Jet-A fuel. Higher n-butanol concentrations lead to improved thermal efficiency and lower NOx and CO emissions. However, PM emissions slightly increase with higher methanol content. The study underscores the potential of n-butanol as a SAF for turbo-engines, highlighting its ability to mitigate environmental impacts while maintaining or improving engine performance. This research supports the feasibility of integrating n-butanol into Jet-A blends for turbo-engine applications, emphasizing its role in achieving more environmentally friendly aviation operations.

Rice yield underperformance coupled with production instability in Odisha state of India is primarily due to low irrigation potential, the spatiotemporal disparity in rainfall pattern and relentless confrontation with biotic and abiotic stresses. System of Rice Intensification (SRI) was introduced in the state with the promises of higher production horizon. However, the present scenario of patchy adoption pattern has necessitated comprehensive study on dynamics and determinants of adoption of SRI. We found that, 57 percent farmers continued SRI, 28 percent discontinued and rest were practicing conventional rice farming. The focused group discussion among the farmers helped us to triangulate the determinants of SRI adoption.The increased SRI area allocation was observed at the expense of reduced number of adopting farmers. Economic scarcity of skilled labour, difficulties in transplantation and mechanical weeding, low irrigation potential and poor on-farm water management were major constraints in SRI practice. Farmers’ compliance in following different resilient SRI components that also varied spatiotemporally has resulted in realized incremental yield. SRI was proved to be resilient to severe drought during 2015-16 and yielded 27 percentage higher than conventional one with considerable decline in hazardous chemicals usage. Farmers’ decision on SRI adoption/discontinuation was analysed using probit regression analysis. The results indicated that, active social involvements of NGOs, on-farm training and demonstrations, and realized incremental rice income influenced SRI adoption. On the other hand, SRI area expansion hindered mainly because of infeasible land topography, area saturation and lack of farmers’ interest. The sustainability index was developed to analyse SRI’s performance to other conventional methods at farm level. Comparatively, SRI adopters benefitted in terms of incremental net return by enhancing ecological balance and sustained productivity of soil, use of eco-friendly and own farm inputs. Nonetheless, higher women labour displacement observed under SRI can be curtailed by providing training to young farm women.

The mechanistic Target of Rapamycin Complex 1 (mTORC1) regulates ribosome biogenesis and the transcription of ribosomal genes. Its inactivation impacts protein synthesis necessary for transport of cell adhesion molecule. In Dictyostelium discoideum, the activity of mechanistic Target of Rapamycin Complex 2 (mTORC2) is crucial for cAMP synthesis and relay, processes that depend on heterotrimeric G-proteins and Ras GTPases. Mutants lacking rip3 or lst-8 genes exhibit impaired adenyl cyclase activation and cAMP signaling, resulting in deficient expression of the cell adhesion protein CsaA. Despite this, rip3^- cells, which have impaired mTORC2, upregulate Cad-1 expression, a cell adhesion protein regulated by Ras-GTPases, to compensate for the loss of CsaA. lst-8^- cells, which have both mTORC1 and mTORC2 inactivated, show reduced nutrient sensing, premature CsaA expression and solitary cell behavior. These cells also show defective transport of adhesion proteins to the cell surface, impeding aggregation. Similar defects are observed with caffeine treatment, suggesting both mTORC1 and mTORC2 inhibition. This study highlights the interplay between mTORC1 and mTORC2 in regulating cell adhesion and aggregation through cAMP signaling and protein synthesis pathways in Dictyostelium.

It is meaningful to monitor and identify the concrete cracks as they will seriously reduce the fatigue life of pavement. In this paper a new method based on distributed long-gauge optic fiber sensing is proposed to implement the crack identification. Firstly, the damage indicator, namely strain curve envelope area ratio (SCEAR), is proposed and calculated with the measured strain in time series when the plane goes across the pavement where the sensors are installed. Then the indicators with different sensors are normalization by the value of the indicator from one referenced sensor where damage normally will not happen. If the crack happens within the sensing gauge of the sensor, the value of damage indicator SCEAR from the sensor will increase. Therefore, the crack will be identified with the change of the damage indicator. The effect of the proposed method is first verified by some simulations of prefabricated pavement as the cracks can be accurately identified by the proposed method. Moreover, the influence from the aircraft, such as taxiing position, aircraft load and aircraft type, is not obvious enough to mislead the identification results. Lastly the static loading tests were implemented with one small-scale model of prefabricated concrete pavement in the lab. From the experimental results the prefabricated cracks inside the pavement slab can be identified accurately with the proposes method as the parameter SCEAR is increased by about 100% at the crack position, while it is only changed by about 3% at the undamaged position.

This study presents the design and comprehensive 3D multiphysics simulation of a novel microfluidic immunosensor for real-time, non-invasive monitoring of pro-inflammatory biomarkers in human sweat. The patch-like device, designed using COMSOL Multiphysics, integrates magnetofluidic manipulation with direct-field capacitive sensing. The sensor comprises two distinct units: an immunocomplex enhancement unit, employing a series of microcoils to optimize the binding efficiency, reaction kinetics, and homogeneity of biomarker-magnetic nanoparticle (MNP) interactions, thereby enhancing the sensor's specificity; and a layered capacitive sensing unit, designed to concentrate and detect biomarker-tagged MNPs, thus amplifying sensitivity. Simulations of the capacitive sensing unit revealed a substantial sensitivity increase of up to 42.48\% at an 85\% MNP concentration within the detection zone. These findings highlight the potential of the proposed immunosensor for efficient and precise real-time biomarker monitoring, which may facilitate early disease diagnosis and enable personalized healthcare interventions.

Vibration problems have become one of the most important factors affecting robot performance. To this end, a terminal residual vibration suppression method based on joint trajectory optimization is proposed to improve the accuracy and stability of robot motion. Firstly, based on the characteristics of the friction nonlinearity due to joint coupling and physical feasibility of dynamic parameters, a semidefinite programming method is used to identify dynamic parameters with actual physical meaning, thereby obtaining an accurate dynamic model. Then, based on the result of the residual vibration time domain analysis, a joint trajectory optimization model with the goal of minimizing joint tracking error is established. The Chebyshev collocation method is used to discretize the optimization model. The dynamic model is used as the optimization constraint, and barycentric interpolation is used to obtain the optimized joint motion trajectory. Finally, industrial robot experiments prove that the vibration suppression method proposed in this article can reduce the maximum acceleration amplitude of residual vibration by 62% and the vibration duration by 71%. Compared with the input shaping method, the method proposed in this paper can reduce the terminal residual vibration more effectively and ensure the consistency of running time and trajectory.

ABSTRACTCaffeine is known to impair both growth and development in the model social amoeba Dictyostelium discoideum. However, little is known about the transcriptional regulation in response to caffeine treatment in Dictyostelium. In yeast cells, caffeine mimics the effect of rapamycin in inhibiting mTORC1 activity. Here, we investigated whether changes in growth and development of Dictyostelium in the presence of caffeine or rapamycin are mediated by mTORC1 and/or mTORC2. Results: Treatment of wild type cells with caffeine or rapamycin resulted in severely impaired growth and in the formation of small aggregates in comparison to untreated cells. rip3‾ cells (lacking a mTORC2 component) and lst8‾cells (lacking a component of both mTOR complexes) showed higher and slower growth rates, respectively, in comparison to parental AX3 cells. Parental AX3 and rip3‾ cells displayed similar sensitivity to rapamycin and caffeine, while lst8‾ cells were more sensitive to these compounds. When developed in the presence of caffeine or rapamycin, AX3 cells formed aggregates after a long delay. Caffeine did not alter the morphology of small rip3‾ mounds and lst8‾ cells continued to remain solitary. However, in the presence of 1µM rapamycin rip3‾cells failed to form mounds while AX3 cells streamed and formed aggregates. Complementation of lst8‾ cells with the wild type lst8 gene rescued the aggregation phenotype. cDNA microarray analysis to uncover the spectrum of differentially regulated genes in response to caffeine treatment revealed 104 and 193 differentially expressed genes at 3-and 6-hours of development, respectively, in comparison to control cells. After 6 hours of starvation in the presence of caffeine, 25 genes encoding ribosomal proteins and 4 encoding elongation factors were up regulated. Furthermore, we identified that upon caffeine treatment at the 3- and 6-hours’ time points, 12 (10 up and 2 down) and 21 (13 up and 8 down) genes, respectively, encoding proteins involved in early development. Conclusion: We conclude that caffeine and rapamycin have similar effects in decreasing the growth rate and in reducing the aggregate size of D. discoideum. Studies with lst8‾ and rip3‾ cells suggest that these compounds affect cell growth and aggregation by acting on both mTOR complexes, mTORC1 and mTORC2. Analysis of the differentially expressed genes after caffeine treatment suggests a key role of these genes in growth and aggregation.

Although heart failure with preserved ejection fraction (HFpEF) has become the predominant heart failure subtype, it remains clinically under-recognized. This, has been attributed to the complex pathophysiological mechanisms that accompany individuals with several co-morbidities and symptoms and signs of HFpEF. Natriuretic peptides have been recognized to have important role in the diagnosis and monitoring of patients with heart failure with reduced ejection fraction (HFrEF), but their role in HFpEF remains controversial. Its seems that the role of NtproBNP in the diagnosis of HFpEF, is mainly driven by the pathophysiological characteristics of the patients.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

The control of the fine particle emission from the coal-fired power plants has been a big challenge in china. Either the conventional electrostatic precipitator or the fabric filter has some shortages. The electrostatic precipitator is hard to keep high efficiency for the submicron particles. The fabric filter could keep high efficiency but with very high pressure drop. One solution is to combine them together. Several types of hybrid particle collectors (HPC) combining the electrostatic precipitator and the fabric filter together have been developed and applied in a number of projects in China. In recent years, numerical simulation technology has been widely used in the design of the collectors. In this paper, an unsteady numerical model is used to investigate the particle deposition characteristics in a scale hybrid collector. The fluid field is modeled by using incompressible Navier-Stokes equations with the RNG turbulence equations. The corona discharge is solved by using a finite volume method. The particle charging is modeled by using a filed-diffusing combined model. And an unsteady cake formation model is used to simulate the filtration process.

Strong-aroma Baijiu is a traditional Chinese spirit distilled from grains that undergo solid-state fermentation. At the end of each fermentation cycle, a significant quantity of Huangshui accumulates at the bottom of the fermentation pit, constituting one of the primary by-products in the brewing process of strong-flavor liquor. In this report, the chemical component analysis of Huangshui obtained from a strong-flavor liquor factory revealed a diverse array of organic acids, alcohols, esters, starch, reducing sugars, amino acids, and other compounds present in Huangshui. Additionally, two specialized solid-state fermentation models were developed to investigate the formation process of Huangshui. Our findings demonstrate a positive correlation between the yield of Huangshui and the initial moisture content of fermented grains. It is concluded that Huangshui is the percolate produced during the solid-state brewing process of strong-flavor liquor, with its water content originating from the initial moisture of fermented grains.

Multimedia resources, such as instructional videos, are currently enjoying a certain popularity in training programmes for medical and dental students. The major challenge is to create such resources that have quality content and are acceptable to students. We investigated the opinions of a sample of 551 students from 4 medical universities in Romania in order to identify the characteristics of the instructional videos that students prefer and we comparatively analysed these characteristics according to gender, age group, but also according to their general preferences for using Internet services. We used univariate (hypothesis testing) and multivariate (Two-Step Clustering) data analysis techniques and revealed three clusters of students, primarily determined by perceptions of the visual appearance of instructional videos. The structure of the clusters by gender and age group is relatively similar, but we recorded differences between them associated with students' expressed preferences for certain Internet services compared to others. Students who prefer instructional videos to contain images used only for aesthetic purposes, to fill in breaks, use Internet services mainly for communication, while students who prefer in videos the use of already drawn explanatory diagrams are slightly younger than the others and use Internet services mainly for information and communication.

Based on the dynamic strength variation mechanism of concrete under complex loading conditions, two approaches were devised: numerical testing and CT scanning, guided by the principle of minimizing energy dissipation. A methodology for calculating concrete's failure area and measuring its strength was developed. The analysis delves into the mechanisms behind failure patterns and variations in concrete specimen strength, focusing on crack initiation, development, and the resultant failure surface formed by crack propagation, along with the stress distribution in concrete specimens subjected to diverse loading conditions. Through evaluating the strength and computed failure area of concrete specimens, it is evident that the loading method influences both the strength and failure area of concrete specimens. In general, a larger failure area correlates with a higher measured strength.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

Taeniid infections pose a significant threat to both animal and public health, as certain tapeworms within this group can also infect humans, potentially leading to severe health conditions. Therefore, this calls for preventive and control measures, such as regular deworming of dogs. While the efficacy of deworming has been established in developed countries, there is a paucity of reported deworming practices in rural areas of developing countries, such as Tanzania. This study aims to understand determinants for helminth treatment-seeking behavior towards control of cestodial taeniid infections in rural settings in northern Tanzania. A cross-sectional study was undertaken in agropastoral and pastoral areas of northern Tanzania. Comprehensive data from household surveys in selected sub-villages were collected to ascertain dog ownership, dog deworming practices, and the availability of dewormers. Analytical methods were employed to discern how various determinants influenced deworming practices among dog owners in these communities. Awareness of dewormers specifically formulated for dogs emerged as a pivotal factor affecting dog deworming practices. Dog owners who were informed about appropriate dog dewormers were nearly two times more likely to engage in deworming compared to those with limited knowledge (OR = 1.78, 95% CI 1.77 - 4.18, p < 0.001). A majority 32(51.6%, 95% CI: 38.7-64.3) acknowledged accessing dewormers for livestock within their wards. Praziquantel a potent dewormer on cestodes was least known to most dog owners 2(13%, 95% CI: 2.3-41.6). Praziquantel, a potent and common dewormer effective against cestodial taeniid infections, remains relatively unknown in rural areas of northern Tanzania. Therefore, more awareness on appropriate deworming agents against taeniids in dogs should be raised in rural dog-keeping communities.

The building envelope has the most significant contribution in the reduction of the building energy consumption. Application of new, alternative and improved materials and systems has an important impact on the buildings performances. This paper is focused on the thermal transmittance, as an indicator of the thermal conductance of the construction element. It includes comparisons of the U-values, calculated by software, with those measured in situ on three representative façade walls. The walls have been constructed with the new wall system Fragmat NZ-1, a new product in Macedonian buildings. This research provides basic information on the thermal transmittance of the system. The results of the analysis show that the in situ measuring is a useful tool in validation of the precision of analytically calculated values, since it was difficult to obtain precise results from the analytical calculations only, especially when the layers are with non-uniform thickness.

The heat transfer and fluid mechanics analysis in agitated vessels is usually performed using the Dittus-Boelter correlation. In this study, we propose the analysis of an agitated vessel with a draft tube through the analysis of dimensionless numbers correlations. The heat transfer and fluid mechanics simulation was conducted using ANSYS Fluent software. The simulation used the Sliding Mesh approach and the SST k-ω turbulent model to capture the vessel's fluid flow and heat transfer phenomena. A grid independence study was conducted by varying the number of time steps to obtain an appropriate time step size for the simulation. The convective heat transfer coefficient, as indicated by the mean values of the Nusselt number, was calculated. The local values along the radial coordinate of the heat transfer surface were also determined. These results provide insights into the distribution of heat transfer rates within the vessel, which can help optimize process efficiency and equipment design. The simulation results were analyzed by varying the c and m coefficients in the Nusselt correlation presented as Nu= c Rem Pr1/3. Furthermore, correlations describing the mean Nusselt number at the bottom and wall of the vessel are presented and compared with existing literature, contributing to advancing knowledge in this field.

In reinforced concrete (RC) structures, splicing is required owing to the length limitations of rebars, insufficient lengths, and transportation issues. In particular, splices connect the rebar of RC structures such as walls, columns, beams, slabs, and joints. Lap splices are the most commonly used method worldwide because they do not require specific equipment or skilled workers. However, lap splices incur high construction costs because of the long splice lengths required for large-diameter rebars in megastructures, as well as issues pertaining to material supply, labor costs, constructability, and project duration. Additionally, approximately 15% more rebar is required because of the overlap. Energy saving for a sustainable built environment is possible if the disadvantage of lap splices, which generate high CO2 emissions due to the excessive use of rebar, are resolved. Hence, mechanical rebar couplers (MRCs) have been developed. However, despite their advantages, they have not been widely applied in construction sites owing to concerns regarding safety, quality, and constructability. Although various MRCs have been developed, most studies focus only on their structural performance. Therefore, a data-driven approach for selecting MRCs based on the reinforcing bar shape and structural characteristics is proposed in this study. Using a data-driven MRC selection algorithm, using the T-threaded coupler for one rebar over two floors resulted in 56% more efficient labor productivity, 15% shorter assembly time, 17% lower costs, and 26% lower CO2 emission. Using a developed algorithm, the appropriate MRC can easily and rapidly be selected for frequent design changes.

Objectives: The purpose of the study was to evaluate the effectiveness of dental caries segmentation on the panoramic radiographs taken from children in primary dentition, mixed dentition, and permanent dentition with an Artificial Intelligence (AI) models developed using the deep learning method. Methods: This study used 6075 panoramic radiographs taken from children aged between 4 and 14 to develop the AI model. The radiographs included in the study were divided into three groups as primary dentition (n: 1857), mixed dentition (n: 1406), and permanent dentition (n: 2812). U-Net model implemented with PyTorch library was used for segmentation of caries lesions. Confusion matrix was used to evaluation of model performance. Results: In the primary dentition group, the sensitivity, precision and F1 scores calculated using the confusion matrix were found to be 0.8525, 0.9128, and 0.8816, respectively. In the mixed dentition group, the sensitivity, precision, and F1 scores calculated using the confusion matrix were found as 0.7377, 0.9192, and 0.8185, respectively. In the permanent dentition group, the sensitivity, precision, and F1 scores calculated using the confusion matrix were found as 0.8271, 0.9125, and 0.8677, respectively. In the total group including primary, mixed, and permanent dentition, the sensitivity, precision and F1 score calculated using the confusion matrix were 0.8269, 0.9123 and 0.8675, respectively. Conclusion: Deep learning-based AI models are promising tools for the detection and diagnosis of caries in panoramic radiographs taken from children in different dentitions.

Despite widespread vaccination, early treatments, and improved understanding of the disease, the effects of SARS-CoV-2 infection remain significant worldwide. Many patients still suffer from severe COVID-19, necessitating admission to intensive care units. Remdesivir is a primary treatment option among viral RNA polymerase inhibitors for hospitalized SARS-CoV-2 patients. However, there is a lack of studies examining factors influencing its effectiveness in this context. We conducted a retrospective study throughout 2022, analyzing clinical, laboratory, and sociodemographic data from 252 hospitalized COVID-19 patients treated with remdesivir. Six machine learning algorithms were compared and validated to predict factors associated with the loss of clinical benefit from remdesivir in terms of mortality and hospital stay. Data were extracted from electronic health records. The eXtreme Gradient Boost (XGB) method achieved the highest balanced accuracy for both mortality (95.45%) and hospital stay (94.24%). Factors associated with worse outcomes of remdesivir use in terms of mortality included limitation of life support treatment, need for ventilatory support (especially invasive mechanical ventilation) on day 14 after the first dose of remdesivir, lymphopenia, low levels of albumin and hemoglobin, presence of flu and/or coinfection, and cough. Factors associated with worse outcomes of remdesivir use in terms of hospital stay included the number of doses of the COVID-19 vaccine, patchy lung density, bilateral pulmonary radiological status, number of comorbidities, oxygen therapy, troponin and lactate dehydrogenase levels, and asthenia. These findings highlight the effectiveness of XGB as a strong candidate for accurately categorizing COVID-19 patients undergoing remdesivir treatment.

Matter grows and self-assembles to produce complex structures such as virus capsids, carbon fullerenes, proteins, glasses, etc. Due to its complexity, performing pen-and-paper calculations to explain and describe such assemblies is cumbersome. Many years ago, Richard Kerner presented a pen-and-paper path integral approach to understand self-organized matter. Although successfully addressed many important problems including the yield of fullerene formation, the glass transition temperature of doped chalcogenide glasses, the fraction of boroxol rings in B2O3 glasses, the first theoretical explanation for the empirical recipe of window and Pyrex glass and the understanding of virus capsid self-assembly, still is not the primary choice when tackling similar problems. The reason lies in the fact that it diverges from mainstream approaches based on the energy landscape paradigm and non-equilibrium thermodynamics. In this context, a critical review is presented, demonstrating that the Richard Kerner method is, in fact, a clever way to identify relevant configurations. Its equations are simplified, common physical sense versions to those found in the energy landscape kinetic equations. Subsequently, the utilization of equilibrium Boltzmann factors in the transition Markov chain probabilities is analyzed within the context of local two-level energy landscape models kinetics. This analysis demonstrates that their use remains valid when the local energy barrier between reaction coordinate states is small compared to the thermal energy. This finding places the Richard Kerner model on par with other more sophisticated methods and, hopefully, will promote its adoption as an initial and useful choice for describing the self-agglomeration of matter.

For achieving climate targets, public engagement is key. Climate communication can play an important role here. Telling regional stories of successful climate action seems a promising form of climate communication: It may convey a feeling of ‘So this is what climate action looks like – and it is people like you and me who are starting to take action.’ This transformative research project (1) formulates hypotheses on what could make such local climate stories effective, (2) then identifies, produces and disseminates stories in the region of Konstanz, Germany, following a rapid prototyping approach, and (3) analyzes the effect of the stories by using focus groups. So far, two prototyping series of filmic story production have been completed in 2022/2023 and some initial insights were derived: Potential protagonists seem willing to tell their stories, and the stories have a potential to inspire people. Technical film quality is relevant. The stories must be selected and told carefully (who is portrayed, which actions are interpreted as success, through which channels are the stories shared), in order to create resonance with different target groups. Next steps are continuation of film production prototyping, a broader sharing of stories, and thorough impact research by focus groups.

Fluorophores with a tetraphenylethylene (TPE) core are attracting increasing interest because of their aggregation-induced emission (AIE) behaviour, which makes them particularly suitable when dispersed in thin-layer films. We propose the synthesis and use of a novel TPE fluorophore (hereafter called TPE-BPAN) decorated with two dimethylamino push groups and a 4-biphenylacetonitrile pull moiety. In tetrahydrofuran solutions, TPE-BPAN showed a broad absorption spectrum, and an intense emission is observed when a non-solvent as water is added in amounts of 70% and above. We selected and synthetized five different polymer matrices for TPE-BPAN with decreasing polarity: a) poly(methylmetacrylate) homopolymer (PMMA); b), c), and d) three copolymers of methyl methacrylate and cyclohexyl methacrylate at different compositions (P(MMA-co-CHMA) 75:25, 50:50, 25:75 mol%); e) poly(cyclohexyl methacrylate) homopolymer (PCHMA). The presence of a less polar comonomer as cyclohexyl methacrylate appeared to enhance the emission behaviour of TPE-BPAN, which displayed the highest quantum yield (QY) in P(MMA-co-CHMA) 75:25 in all the range of concentration studied from 0.4 wt.% to 2.0 wt.%. Further reduction in polarity lowered QY to the values of PMMA films; also, lower adhesion to the glass and a marked fragility of the films were observed. Referring to the P(MMA-co-CHMA) 75:25 films, QY values decreased from over 40% at 0.4 wt.% to about 30% at 2.0 wt.%, which is still helpful for energy harvesting applications such as luminescent solar concentrators (LSC). LSC performances were not significantly affected by the matrix's lower polarity and resulted in around one-third of the state-of-the-art due to the lower QY of TPE-BPAN. The theoretical investigation on density functional theory (DFT) clarified the origin of the observed AIE and the role played by the environment in modulating the photophysical behaviour.

Abstract Peripartum depression (PPD) is a major complication of pregnancy and many risk factors have been associated with its development, including dysfunctional coping strategies and insecure attachment styles, both during pregnancy and postpartum. The aim of our study was to investigate the role of coping strategies in mediating the relationship between women’s attachment style and PPD in pregnancy, and one week after childbirth, in a large cohort of women. We hypothesized that the relationship between anxious and avoidant attachment and PPD would be mediated by use of maladaptive coping strategies. The assessment instruments were Edinburgh Postnatal Depression Scale (EPDS), Brief Coping Orientation for Problem Experiences (COPE), Experiences in Close Relationship Scale (ECR). The results indicated that the effect of insecure attachment styles (anxious and avoidant attachment) on antepartum depressive symptomatology was partially mediated by dysfunctional coping styles. Anxious attachment has also an indirect significant effect on postpartum depression through emotional coping; however, avoidant attachment does not seem to be significantly related to postpartum depression. Our findings revealed that not only it is important to consider attachment in understanding PPD but also that coping plays an important role in these relationships. These findings would help a preventive coping-based intervention strategy to enhance the capacity of women with insecure attachment styles to use more adaptive coping during and after pregnancy.

Condition monitoring is a primary principle for predictive maintenance. In this regard, several techniques have been employed, each of which has its strengths and weaknesses. In this work, the relationships between the electrical (ε', ε", tan δ) and chemical (Fe, Pb, Cu, Cr, Al, Si, Zn) properties of engine lubricants were investigated using soft computing models. The models' performance was evaluated considering some criteria, including RMSE and MAPE. The RBF model was determined as the best one to predict chemical properties (Fe, Pb, Cu, Cr, Al, Si, Zn) through electrical indexes (ε', ε", tan δ). The RBF’s parameters (e.g., hidden size and training algorithm) were then optimized for optimum performance. For instance, in the RBF model implemented to predict Al, the best hidden size and training algorithmic were 15 and 'trainlm', respectively. Finally, by sensitivity analysis it was observed that eliminating any of the inputs does not improve the performance of the RBF model performance. In general, the results of the current research showed that the electrical properties (e.g., ε', ε", tan δ) have the capability of estimating the contaminants in the lubricants which can improve the existing monitoring methods.

This article is a followup to an earlier review which outlined some of the interesting features of the soliton/wave-action potential (AP) model, and noted the need to test its key aspects; including the need to test if its presumed lipid phase transition is actually happening during AP firings in excitable cells. The intent here is to point out the sort of tests, and evidence from them, that might be needed if the soliton/wave-AP model is to be accepted broadly by biologists. Here, after an overview of the modern electrophysiological-AP model and of the soliton/wave-AP model, there are three areas considered. First, possible compositional influences on membrane properties relative to the soliton/wave-AP model are presented. Including questions with regard to the soliton/wave-AP model’s assumption that changes in surface potentials influence the transmembrane potential. Second, some recent work from the good folks who advocate for the soliton/wave-AP model concerning the occurrence of lipid phase transitions in neurons or in extracts from nervous tissues are examined. Here it is noted that there is a need to consider whether these lipid phase transitions happen within normal physiological conditions or not. Third, and finally, the advocates for the soliton/wave-AP model have adopted a thermodynamic/theory-based philosophical approach in their studies. It is argued that this philosophical approach is a radical departure from the philosophical approach used under the scientific method. The features of this new approach, and implications its use, are examined.

Airborne microplastic (MP) is an emerging pollutant, still under-characterised and insufficiently understood. Detailed description of MP air pollution is crucial as it has been identified in human lungs and remote locations, highlighting atmosphere as medium of MP dispersion and transportation. The lack of standardization of methods for measuring and further monitoring of the MP pollution is an obstacle towards the assessment of health risks. Since the first recognition of MP presence in the atmosphere of Krakow in 2019, this research was conducted to further characterise and develop the methods for qualitative and quantitative analysis of airborne MP (ATR-FTIR, Pyr-GC-MS, SEM-EDS) and pre-treatment of samples.The data was gathered in seven cycles, from June 2019 to February 2020. Methods used in the study allowed the identification and analysis of the changing ratio of the different types of synthetic polymers identified in the atmospheric fallout (LDPE, Nyl-66, PE, PET, PP, PUR). Observations of interactions between MP particles and environment were made with analyses of surface changes due to the degradation. Mineral phases attached to the MPs’ surfaces, with some of the inorganic contaminants transported on these surfaces, determined to also be of anthropogenic origin.Methodology proposed in this study, allows further characterisation of MP from multiple locations to provide highly comparable data, leading to the identification of the sources of this phenomenon, as well as seasonal changes.

Abstract: Diabetes mellitus (DM) is associated with severe COVID-19 infection and complications. This study assessed COVID-19 vaccine acceptance and hesitancy in diabetes and explored reasons for nonvaccinating. This was a web-based cross-sectional survey using a mixed-method approach conducted between March-May 2021 corresponding to most SSA countries' early vaccine rollout period. Participants were those aged ≥18 years with self-reported DM in 11 Sub-Saharan African (SSA) countries. Responses to comments on reasons for vaccine hesitancy and facilitators for vaccine uptake were analyzed. Of the 73 participants with DM, 65.8% were males older than 35 years (86.3%), had post-secondary education (90%), and a significant proportion was from South Africa (39.7%), Nigeria (28.8%) and Ghana (13.7%). 64.4% had COVID-19 symptoms, 46.6% were tested for COVID-19, of which 19.2% tested positive. Few participants (6.8%) had taken the COVID-19 vaccination, 65.8% were willing to take the vaccine, while 26.0% either refused or hesitated to take the vaccine. The main reasons identified for not taking the vaccine were: advice from religious leaders, concerns about the vaccine safety, its effects, and efficacy, mistrust of the pharmaceutical companies, the conspiracy theories around the vaccines, the process of production, and the personal belief of the participants. However, participants stated they would take the vaccine if given more education about it, receive positive feedback from those vaccinated, are rewarded for taking the vaccine or if vaccination becomes a condition for travel and employment. The findings of this study showed that uptake of the COVID-19 vaccine was very low in this high-risk group. It is imperative that efforts to increase the uptake of vaccines, such as the provision of education and relevant information, are made.

Interferometry Synthetic Aperture Radar (InSAR) is an advanced remote sensing technique for studying the earth's surface topography and deformations. It is used to generate high-quality Digital Elevation Models (DEMs). DEMs are a crucial and primary input to various topographical quantification and modelling applications. The quality of input DEMs can be further improved using fusion methods, which combine multi-sensor or multi-temporal datasets intelligently to retrieve the best information amongst the input data. This research study is based on developing a Neural Network based fusion approach for improving InSAR based DEMs in plain and hilly terrains. The study areas comprise of relatively plain terrain from Ghaziabad and hilly terrain of Dehradun and their surrounding regions. The training dataset consists of DEM elevations and derived topographic attributes like slope, aspect, topographic position index (TPI), terrain ruggedness index (TRI), and vector roughness measure (VRM) in different land use land cover classes of the study areas. The spaceborne altimetry ICESat-2 ATL08 photon data is used as a reference elevation. A Feed Forward Neural Network with backpropagation algorithm is trained based on the prepared training samples. The trained model produces fused DEMs by learning the relationship between the input and target samples. This is used to predict elevations in the test areas. The accuracy of results from the models are assessed with TanDEM-X 90 m DEM. The fused DEMs show significant improvement in terms of RMSE over the input DEMs with improvement factor of 94.65 % in plain area and 82.62 % in hilly area. The study concludes that the ANN with its universal approximation property is able to significantly improve the fused DEM.

Cancer stem cells play a crucial role in tumor initiation, metastasis and therapy resistance. Cellular heterogeneity and plasticity challenge the isolation of cancer stem cells. The impact of intratumoral cellular heterogeneity in the context of treatment resistance using a label-free approach remains understudied. Here, we use the sedimentation field-flow fractionation technique to separate, without labeling, cell subpopulations of colorectal cancer cell lines and primary cultures according to their biophysical properties. One of the three cell subpopulations sorted by SdFFF exhibits cancer stem cell traits, including high tumorigenicity in vivo, and a higher frequency of tumor-initiating cells compared to the other subpopulations. In vitro two- and three-dimensional chemosensitivity assays emphasize the therapeutic relevance of this cancer stem cell-like subpopulation due to its chemoresistance. Therefore, our findings highlight a label-free cell sorting approach to reveal intratumoral cellular heterogeneity and its implication in therapy resistance. This approach enables the study of the individualized response of each sorted cell subpopulation by breaking down the tumor, thus offering new perspectives for personalized therapy.

The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that affected the lifestyle and economy. Various studies have been focused on the identification of COVID-19 impact to mental health of children and adolescents via traditional statistical approaches. However, a machine learning methodology must be developed to explain the main factors that contribute to the change of mood state of children and adolescents during the first lockdown. Therefore, to this study an explainable machine learning pipeline is presented focusing on children and adolescents in Greece, where a strict lockdown was imposed. The target group consists of children and adolescents, recruited from children and adolescent mental health services, who present mental health problems diagnosed before the pandemic. The proposed methodology imposes: (i) data collection via questionnaires; (ii) a clustering process to identify the groups of subjects with amelioration, deterioration and stability to their mood state; (iii) a feature selection process to identify the most informative features that contribute to mood state prediction; (iv) a decision-making process based on an experimental evaluation among classifiers; (v) calibration of the best performing model and (v) a post-hoc interpretation of the features’ impact on the best performing model. The results showed that a blend of heterogeneous features from almost all feature categories is necessary to increase our understanding regarding the effect of COVID-19 pandemic on the mood state of children and adolescents.

The search for sustainable resources remains a subject of global interest and the conversion of the abundantly available bivalve shell wastes to advanced materials is an intriguing method. By grinding, each shell of bivalves (cockle, mussel, and oyster) was transformed to the same crystal type of calcite phase of CaCO3, revealed by FTIR and XRD results. Each individual shell powder was reacted with H3PO4 and H2O to prepare Ca(H2PO4)2•H2O giving an anorthic crystal structure. The mixture of each shell powder and its produced Ca(H2PO4)2•H2O was heated at 900 °C for 3 h, giving rhombohedral crystal -Ca3(PO4)2 powder. FTIR and XRD results of the CaCO3, Ca(H2PO4)2•H2O, and Ca3(PO4)2 prepared from each shell powder are quite similar showing no impurities. Thermal behaviors of CaCO3 and Ca(H2PO4)2•H2O produced from each shell are slightly different. Particle sizes and morphologies of all products are significantly different, affected by the kind of shells used. Overall, the bivalve shell wastes were successfully converted to CaCO3, Ca(H2PO4)2•H2O, and Ca3(PO4)2 by a simple, rapid, environmentally benign, and cost-effective approach, which can be a huge potential in many industries providing both economic and ecological benefits according to the Bio-Circular-Green Economy (BCG) model.

This paper presents a practical case illustrating how the Sustainable Development Goals (SDGs) of the 2030 Agenda have been designed and articulated in the context of the University of the Basque Country (UPV/EHU). Even though there is a widespread formal adherence of universities to the SDGs, there is a lack of solid commitment to go beyond the compartmentalization of their implementation and to contribute to a holistic approach. The EHUagenda 2030 is a roadmap to move towards an integrated, verifiable and pragmatic contribution to this international agenda. It describes the UPV/EHU's contribution to 12 of the 17 SDGs, with the addition of its own commitment to linguistic and cultural diversity (SDG 17 + 1), along with the three sectoral plans: the Equality Campus, the Inclusion Campus and the Planet Campus. It also describes the refocus of its education model IKD i3; i3 is ikaskuntza x ikerketa x iraunkortasuna, Basque for learning x research x sustainability. Additionally, it includes the UPV/EHU’s Panel of Sustainable Development Indicators, which addresses the technical aspects of monitoring the implementation of the SDGs. The systematic methodology used in this process (mapping; mainstreaming; diagnosis and definition and, finally, estimation) and presented in this paper could be replicated in other universities yet to embark on this integration. The steps and findings presented here can also be applied to other organizations and help the integration process.

Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma (ccRCC) samples were re-analyzed from the Genomic Fabric Perspective that considers the transcriptome a multi-dimensional mathematical object, constrained by a dynamic set of expression correlations among genes. Every gene in the chest wall metastasis (MET), two primary tumors (PTA, PTB) and the surrounding normal tissue (NOR) of the right kidney was characterized by three independent measures: average expression level (AVE), relative expression variation (REV) and expression correlation (COR) with each other gene. AVE was used to determine the regulation of the genomic fabrics of ccRCC, apoptosis, chemokine and VEGF signaling pathways. REV quantified the alteration of the transcripts’ abundances control, while COR determined the remodeling of the transcriptomic networks of chemokine signaling and oxidative phosphorylation genes. The gene hierarchy was established in based on Gene Commanding Height and the Gene Master Regulators (GMR) TASOR (PTA), FAM27C (PTB) and ALG13 (MET) and DAPK3 (NOR) were identified in each profiled region. We predict that TASOR overexpression would block transcription in PTA but not in PTB, while slightly stimulating it in NOR. Silencing of ALG3 would slow-down the cell-cycle in all three cancer regions with practically no effect in NOR.

Low levels of physical activity (PA) and sedentarism are associated with the onset of different pathologies and health problems. Regular physical activity has been linked with being beneficial to the health of the general population. Within this framework of analysis, the aim of the present study is to analyse the existing association between the time spent doing physical activity and the expressed motives for doing so, from which the first innovative aspect of the paper emerges: the use of the time spent doing PA as a study variable of the phenomenon. The data analysed come from the latest special Eurobarometer survey about the sport and physical activity done in Europe. Using an exploratory factorial analysis and a structural equations model, we were able to find a six-dimensional factorial model that explains the reasons for doing PA, demonstrating that there is no relationship between the reasons for and time spent doing PA. Therefore, motivation is not a variable that explains the time spent doing PA and another type of variable must be used to explain the phenomenon if PA is to be incentivised.

Both intestinal schistosomiasis and giardiasis are co-endemic throughout many areas of sub-Saharan Africa, significantly impacting the health of millions of children within endemic areas. While giardiasis is not considered a neglected tropical disease, intestinal schistosomiasis is formally grouped within the NTD umbrella and, as such, receives significant advocacy and financial support for large-scale control, annually. Given the many epidemiological similarities between intestinal schistosomiasis and giardiasis, in this review, we critically discuss why disease surveillance and control activities for giardiasis are largely absent within low- and middle-income countries. With advances in new methods of parasite diagnostics and provision of existing anti-parasitic medications, better management of intestinal schistosomiasis and giardiasis co-infection could, not only be better understood but also, more effectively controlled. In this light, we appraise the suitability of a One Health approach for intestinal schistosomiasis, for if adopted more broadly, could also pave a way forward for more inclusive public health actions against giardiasis.

Putting value to ecosystem services is something that society still refuses or simply ignores because it is not aware of the benefits that ecosystems provide us. In fact, people should be aware that a good understanding of ecosystem services can lead to win-win situations. Being aware of the importance of preserving the ecosystem and attaching value to its services will enable the development of self-sustaining strategies and appropriate policies for better ecological governance. Decades of over exploitation of natural resources, introduction and spread of alien species and, also, climate change, forest fires among other threats, have fostered biodiversity loss. The European Union Biodiversity Strategy has as one of its main goals to stop biodiversity loss and the degradation of ecosystem services; if possible, to recover the most threatened and degraded ecosystems, based on 20 Actions divided into 6 Targets. The present work falls within the scope of Action 5 of Target 2 – Improve knowledge of ecosystems and their services in the EU. The specific focus of this study is the Site of Community importance “Dunas de Mira, Gândara and Gafanhas” (Portugal) and the assessment of its ecosystem services, in accordance with the methodology proposed by the MAES (Mapping and Assessment of Ecosystems and their Services) Working Group. The work currently under way, a small segment of which is presented here, aims to identify, map and, when possible, assign value to the ecosystem services. For this purpose, modern GIS technologies will be used. This approach was implemented using a combination of data and tasks, including the photo-interpretation of Sentinel 2 (COPERNICUS Program) satellite imagery. The data geoprocessing tasks and image segmentation were developed using QGIS software and IMPACT Toolbox software (developed by the Joint Research Center – JRC, of the European Union), respectively. The analysis of Land Use and Burned Areas maps for the SCI "Dunas de Mira, Gândara and Gafanhas" led us to conclude that Forests ecosystems, the most affected by the fire of October 2017, continue to have the greatest expression in the area under study even though they have lost more than 50% of the area, and their services were also the ones most affected by the fire.

Confidence in intermodal transport has not yet been defined. There are many different approaches to the concept of trust. However, the authors embedded them in the light of the challenges of sustainability, linking with the shift paradigm. The objective of the article is to indicate the directions and criteria for the implementation of the shift paradigm, inscribed in the idea of sustainable transport. The auxiliary objective is to predict which countries in a given year will have the TRUST status, i.e. implement the shift paradigm, and which will not implement it (DISTRESS). The article uses taxonometric techniques and built a model using General Discriminant Analysis. On their basis, the utility function was approximated, including the directions of implementation of the shift paradigm depending on the scale of the environmental load of transport. In the course of the research, an original and innovative econometric model was constructed, pointing to three variables, which had the greatest impact on trust. Thanks to the cognitive value of the model, it is possible to identify individuals who deserve the trust, i.e. it will implement the shift paradigm, with 93% probability. In the future, it is worth expanding the research by models for each country.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for 15-5PH Stainless steel by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as concentration of cutting fluid , temperature of cutting fluid , feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error and material removal rate, the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, concentration of cutting fluid, radial depth of cut and temperature of cutting fluid. Finally, confirmation tests were carried out to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Ca2+ can boost protein-protein interactions and, if present at an appropriate level, can potentially improve the physicochemical properties of protein gels and films. This study aimed to determine the effect of CaCl2 (0, 0.01 0.025 0.05% w/w) on the optical, water affinity, and mechanical char-acteristics of glycerol (Gly)- and sorbitol (Sor)-plasticized pea protein isolate (PPI) films. The CaCl2 caused darkening and a color shift of the films from yellow to yellow-green. Additionally, de-creased light transmission, particularly in the UV range, and reduced moisture content were observed. The CaCl2 decreased the water vapor permeability (WVP) of the Gly-plasticized film by an average of 20%, with no effect on the Sor-plasticized film. All films were completely soluble in water. The CaCl2 negatively impacted the mechanical integrity of the films, reducing the tensile strength of the Gly- and Sor-plasticized films by ~16% and 14-37%, respectively. Further increases in CaCl2 content (0.1% and 0.2% w/w) led to concentration-dependent cracks, suggesting protein over-crosslinking. In summary, the incorporation of CaCl2 into PPI films did not provide signif-icant benefits and actually worsened key properties such as transparency and mechanical strength. The type of plasticizer influenced how CaCl2 affected some properties of the PPI film.

Seedling emergence is crucial for the establishment and growth of crops and is influenced by topsoil temperature and moisture. Mulching has been widely used to promote seedling emergence in areas with a cold spring. This study was conducted to determine and simulate the effects of transparent plastic film mulch on surface soil moisture, temperature, and seedling emergence of spring maize in Northwest China. Four treatments were used: no mulching (CK), full plastic film mulch (PMF), and partial plastic film mulch, 60 cm in width (PM60, 40 cm uncovered between rows of mulch) or 30 cm in width (PM30, 20 cm uncovered between rows of mulch). The effects of soil water conservation and temperature enhancement gradually decreased as the plastic film width decreased, but there was little difference between PMF and PM60 treatments. Soil-water-modified growing degree days (WGDD) described the beneficial effects of soil moisture and temperature with respect to seedling emergence under mulching conditions. Plastic film mulching markedly accelerated seedling emergence and increased final seedling emergence rate because mulching can shorten the autotrophy duration and maintain surface soil moisture, which leads to increased germination. The effects of seedling emergence improvement decreased as the plastic film width decreased. The relationship between WGDD and cumulative relative seedling emergence (CRE) was adequately described by a Gompertz function.

This paper introduces a novel framework for zero-shot learning (ZSL), i.e., to recognize new categories that are unseen during training, by distilling knowledge from foundation models. Specifically, we first employ ChatGPT and DALL-E to synthesize reference images of unseen categories from text prompts. Then, the test image is aligned with text and reference images using CLIP and DINO. Finally, the predicted logits are aggregated according to their confidence to produce the final prediction.Experiments are conducted on multiple datasets, including CIFAR-10, CIFAR-100, and TinyImageNet. The results demonstrate that our model can significantly improve classification accuracy compared to previous approaches, achieving AUROC scores above 96\% across all test datasets. Our code is available at https://github.com/1134112149/MICW-ZIC.

المستخلص تصنيع لقاح مكون من الحمض النووي الريبوزي الرسول الخاص بالبروتينات المسئولة عن انتاج البروتينات نيورامنيديز والهيم اجليوتونين لفيروسي الانفلونزا الخنازير والطيورمحاط بجزيئات دهنية بحجم النانوميتر عدوى انفلونزا الخنازير وانفلونزا الطيور مشكلة خطيرة تؤرق العالم كله هذه الايام خصوصا انها مميتة لكثير من اطفال العالم . بعد فترة التعافي من الاصابة تتكون المناعة المكتسبة ضدها لمدة عام تقريبا. هذه الانفلونزا تسبب تسمم فيروسي في الدم بالاضافة للالتهاب الرئوي وهذامن بين اكبرالاسباب للوفاة بين الاطفال قبل سن عامين عالميا بشكل مباشر. الهدف من الدراسة هو انتاج لقاح الحمض النووي الريبوزي الرسول من نوع الام بالنانوتكنولوجي لبروتينات الهيم اجليوتونين والنيورامنيديز الموجودة على سطح هذه الفيروسات التي تساعدتها في الاتصاق بالعائل الذي ستتكاثر داخل خلاياه بالجهاز التنفسي. هذه الدراسة دراسة استكشافية ومن خلالها استطاعنا تصميم هذا اللقاح باستعمال نظام توصيل للقاح بالنانوتكنولوجي حجم جزيئاته 70نانوميمتر. اللقاح الجديد اظهر فاعلية بنسبة 60% واظهر فاعلية حيوية مقاربة واثار جانبية اقل بالمقارنة باللقاحات المتوفرة حاليا بالسوق الدوائي ضد هذا النوع من الفيروسات الوبائية. ABSTRACT Background: Worldwide, Swine and Avian influenza, or the H1N1 and H5N1 serotypes of the Influenza A virus, is a highly contagious illness. In recent years, the global incidence of mortality rate has surpassed 284,000 fatalities. Aim of the study: The production of mRNA vaccine lipid nanoparticles (LNP) to combat the deadly strains of Avian and Swine influenza (H1N1 and H5N1 of the influenza A serotype). Methodology: Polymerase chain reaction (PCR) was used to clone genes of interest encoding Haemagglutinin (HA) and Neuraminidase (NA) of Influenza A virus strains (H5N1 and H1N1) known as Avian flu and Swine flu, respectively. The genes were then inserted using the EcoR1, BAM Hind II restriction endonuclease type II, and Ligase enzyme into the pET-21(+) transcription vector plasmid. On the other hand, the hybrid transcription vectors were mixed with T7 RNA polymerase and ribonucleotides within a test tube after being linearized using EcoR II. Following their purification via reversed-phase high-performance liquid chromatography (RP-HPLC), the mRNAs of the HA and NA were encased in 70 nm LNPs and subjected to reverse-phase high-performance liquid chromatography (RP-HPLC). Lastly, immunogenicity studies were performed in stages 1/2 of randomized human and preclinical clinical trials. Results: The bivalent vaccination had around 63% efficacy in preclinical studies and approximately 60% efficacy in randomized human clinical trials. As shown by the ELISA test, strong neutralizing antibodies against HA were prevalent. Conclusion: The current study is a promising effort because of the development of the novel LNP-mRNA vaccine, which could lower the incidence of Avian and Swine flu infectious disorders.

ABSTRACT Purpose: Tongue image analysis for disease diagnosis is an ancient traditional non-invasive diagnosis technique widely used by traditional medicine practitioners. Deep Learning based multi-label disease detection models offer tremendous potential to clinical decision support systems, by facilitating preliminary diagnosis. Methods: In this work, we propose a multi-label disease detection pipeline, where in observation and analysis of tongue images captured and received via smartphones assist in predicting the health status of an individual. All images are voluntarily given by subjects consulting collaborating physicians. Images thus acquired are first and foremost classified either into a diseased or a normal category by a 5-fold cross-validation algorithm using a convolution neural network (MobileNetV2) model for binary classification. Once the diseased label is predicted, the image is used to diagnose multiple diseases using the prediction algorithm based on DenseNet121. Results: Average accuracy of 93 % was achieved in classifying diseased from normal healthy tongue by detection model with MobileNetV2 architecture. Multilabel disease classification produced more than 90% accurate results for the seven class labels considered. Conclusion: AI based image analysis shows promising results and an extensive dataset could provide further improvements to this approach. Rather than employing high-cost sophisticated image capturing setup, experimenting with smartphone images opens opportunity to provide preliminary health status to individuals on smartphone prior to further line of treatment and diagnosis.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

In the present work report, the MgAl₂O₄and the Ag/MgAl₂O₄ samples were successfully synthesized by the modified hydrothermal and the isovolumetric impregnation methods, respectively. The structural properties of the prepared samples were systematically characterized by XRD, SEM, TEM, DRS, XPS and et al techniques. The photocatalytic degradation of methylene blue by the Ag/MgAl₂O₄ and MgAl₂O₄ samples was comparatively studied under UV lamp irradiation. The results revealed that the prepared Ag/MgAl₂O₄ (pH=6) samples were the most active among the samples in photocatalytic of methylene blue. Under UV lamp irradiation, the Ag/MgAl₂O₄ (pH=6) photodegradation of methylene blue reached to 89.6% within 120 min. And the Ag/MgAl₂O₄ (pH=6) complex photocatalysts displayed a high photochemical stability under repeated irradiation. Repeated irradiate the Ag/MgAl₂O₄ (pH=6) compound, which indicated it had a high photochemical stability.

This article provides a literature review on tubal carcinoma to offer an updated insight into its preventative strategies, diagnosis, treatment, and oncological surveillance. In addition to the search string utilized, the authors' focus extended to key scientific studies, consensus statements, guidelines, and relevant case reports essential for the proper clinical management of the disease, providing a methodologically well-structured literature review combined with the practical expertise in the oncological field. The article also includes two emblematic clinical cases that emphasize the importance of understanding the physiopathology and the current state of the art in the anatomopathological advancements of tubal/ovarian/peritoneal carcinoma, often assimilated into a single clinical entity.

This study aims to investigate the interfacial tension, emulsion stability, and the impact on oil displacement effectiveness of mixed systems containing nonionic surfactants and amphoteric surfactants at different ratios. To achieve this, three different emulsion stability formulations were prepared by mixing betaine and nonionic surfactants in ratios of 1:1, 3:2, and 3:1 respectively. By adjusting the proportions of betaine and nonionic surfactants, variations in interfacial tension and emulsion formation among the three mixed systems were studied to analyze the mechanism of interaction between betaine and nonionic surfactants and evaluate their effects on crude oil displacement and enhanced oil recovery in reservoirs. Subsequently, microscopic and macroscopic oil displacement experiments were conducted on the three mixed systems, along with experiments on emulsion flow resistance. The aim was to verify the oil displacement effectiveness of different mixed systems and further understand their potential applications in reservoirs. By comprehensively analyzing the experimental results, optimal ratios and conditions for the mixed systems were determined. The experimental results indicate that the emulsification system formed by mixing betaine and nonionic surfactants at a ratio of 3:1 achieves molecular synergies through electrostatic interactions and mixed adsorption with betaine, resulting in a compact arrangement of interface membranes and demonstrating a synergistic effect in reducing interfacial tension to an ultra-low value of 10 -4 mN/m. Additionally, as the proportion of betaine surfactant increases, the viscosity of the aqueous phase liquid film increases, the rate of thinning of the liquid film slows down, the rate of water release slows down, and the stability of the emulsion increases. Microscopic oil displacement experiments verified that the three mixed systems increase oil washing efficiency through low interfacial tension and emulsification stripping action, thereby increasing the oil displacement mechanism's coefficient. Emulsion flow resistance experiments demonstrated that as the proportion of betaine surfactant increases, the system exhibits better plugging ability. However, macroscopic oil displacement experiments revealed differences in compatibility between different emulsion stability solutions and rocks with different permeabilities. The mixed system of betaine and nonionic surfactants at a ratio of 3:1 exhibits the best emulsification plugging ability in rocks with a permeability of 109mD, while the 1:1 mixed system performs best in rocks with a permeability of 12mD. This holds significant theoretical and practical significance for reservoir development and enhanced production.

This article explores the cutting-edge advancement of gypsum and cement building boards infused with shape-stabilized n-octadecane, an organic phase change material (PCM). The primary focus is on improving energy efficiency and providing electromagnetic interference (EMI) shielding capabilities for contemporary buildings. The research investigates the integration of these materials into construction materials, using red-mud Carbon Foam as a stabilizer for n-octadecane (OD@CCF). Various analyses, including microstructural examination, porosity assessment, and additive dispersion, were conducted using X-ray microtomography and density measurements. Thermal conductivity measurements demonstrated the enhancement of composite boards as the OD@CCF content increased, while mechanical tests indicated an optimal additive content of up to 20%. The thermal-regulated capabilities of these advanced panels were evaluated in a custom-designed room model equipped with a homemade environmental chamber, illustrating a consistent temperature environment during heating and cooling cycles. The incorporation of OD@CCF into cement boards exhibited improved thermal energy storage properties. Moreover, the examined composite boards displayed efficient electromagnetic shielding performance within the frequency range of 3.2–7.0 GHz, achieving EMI values of approximately 18 and 19.5 dB for gypsum and cement boards, respectively, meeting the entry-level value required for commercial applications.

Frequent and excessive consumption of alcohol, be it episodic or sustained misuse, ranks among the top causes of mortality globally. This comprehensive analysis seeks to elucidate how alcohol misuse precipitates death, with a particular focus on associated cardiac anomalies. Notably, the phenomenon of "Holiday Heart Syndrome," linked to binge drinking, is recognized for inducing potentially fatal cardiac arrhythmias. Moreover, persistent alcohol consumption is implicated in the development of alcoholic cardiomyopathy, a condition that underlies heart failure and arrhythmic disturbances of the heart. Additionally, individuals undergoing withdrawal from alcohol frequently exhibit disruptions in normal heart rhythm, posing a risk of death. This review further delves into additional alcohol-related mortality factors, including the heightened likelihood of hypertension, cerebrovascular accidents (strokes), and the connection between excessive alcohol use and Takotsubo syndrome.

Nowadays, the identification and characterization of grapevine cultivars resilient to climate and water stress while preserving quality traits is crucial for the wine industry. Therefore, the objective of this work was to characterize according to their aromatic potential 9 white and 6 red minority cultivars recently recovered from Castilla-La Mancha region (Spain), subjected at two different water deficit regimes: rainfed, with subsistence irrigation, and irrigated. For this, the varietal aromatic potential index (IPAv) and the detailed aromatic composition were analyzed by HS-SBSE-GC/MS, in extracts of two different ph. For IPAv values, red varieties did not show a clear trend with respect to irrigation. However, in white minority varieties, higher values were obtained under irrigation conditions. Thus, a clear differentiation of the minority varieties in comparison to the references was observed, primarily attributed to the content of esters and acids, in both white and red varieties. A notable contrast was observed at different pH, indicating a greater extractability of certain compounds like linalool, under more acidic conditions. This suggests that some recovered minority cultivars could be promising for cultivation in semi-arid regions with limited water, contributing to the wine sector sustainability in the future.

PURPOSE: Breast cancer tumors frequently have intratumor heterogeneity. Tumors with high intratumor heterogeneity have caused therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to poor prognosis for HER2-targeted adjuvant therapies resistance in primary breast cancers. METHODS: This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with HER2 gene copy number within a tumor sample. Those heterogeneity classified each tumor into the biphasic grade graph (high heterogeneity [HH]) group and the monophasic grade graph (low heterogeneity [LH]) group. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up. RESULTS: Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: P < 0.001 (HH:63% vs LH:91% at 10 years), and OS: P = 0.012 (HH:78% vs LH:95% at 10 years). CONCLUSION: High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach of heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy.

The human eye is a vital source of collecting information worldwide via daily observation. The computer science area recognizes it in research as a human-computer interaction. Human blink is an integral part of this observation as a research topic. Several studies have been conducted on eye blinking and left-right eye movements. Previous studies conducted on the eye blink consider the availability of hardware devices high in the budget, high Precision, and low light expo-sure, unlike our study, which uses low-budget devices as simple as a webcam and more versatile usable techniques, incredibly both dim and high light to name a few. This study offers the observational approach via ResNet101v2, VGG-19, and Convolution Neural Network (CNN) architectures. Outperforming both VGG-19 and CNN in this study, ResNet101v2 achieves an impressive accuracy of 98.2%. In contemporary times, deep learning in AI is taking an advanced form. This study attempts to provide a new insight into the real-world implementation of the eye blink.

The COVID-19 pandemic has triggered seismic shifts in how we work, and organizations behave. It has caused many organizations to transition from an office-centric culture to more flexible ways of working. This shift is necessitated by health conditions and the need for controls. It is also driven by the assumption that remote work or working from home offer a certain assurance of safety for employees against the threat of infection in highly vulnerable office conditions. The shift to remote work has so far been mainly experimental as most businesses continue to learn about what works and what doesn’t. There is also the assumption that all that matters for the efficient operability of a remote work regime is the availability and effectiveness of computing technologies and internet connectivity. Thus, once those supplies are in place remote work is expected to be fully functional and without problems. As learning continues about what works and what doesn’t, it has also become increasingly clear that beyond the threat of covid-19 and the relative safety that individual homes may offer, there are other vulnerabilities which are ignored or underestimated in the process. In most instances, the home environment of the employee, the conditions under which employees operate from home and the health and safety such environments provide (or not) are either ignored or underestimated in discussions around remote work practices. This paper highlights remote work as an emergent practice while exploring associated, but ignored, health and safety issues in employee homes.

This paper assesses the association of ESG scores with stock returns and highlights the moderating role of the COVID-19 pandemic and the country's governance. The study uses panel data regressions to analyze how ESG performance influences plain, absolute, and risk-adjusted returns in a sample of European and selected non-European countries. These suggest that higher overall ESG scores are related positively to financial performance, and this relation is enhanced during the COVID-19 pandemic. Specifically, the two dimensions of ESG that matter most are environmental and governance. Country-level governance is important because firms in well-governed countries amplify the benefits of high ESG scores. The opposite is true for the higher Controversies scores, whose bad financial outcome is magnified during the pandemic. These results present an argument for the resilience of firm financial performance, dependent on strong ESG practices and governance frameworks. This holds great interest for investors and policymakers in associating good ESG considerations with the effective management of financial risks, leading to sustainable returns during periods of widespread economic uncertainty.

In this study, a novel oral formulation of berberine hydrochloride (BBH) hydrogel was successfully synthesized through physical cross-linking using chitosan (CS) and carboxymethyl-β-cyclodextrin (CMCD). The characterization results confirmed the successful synthesis of CS/CMCD hydrogel and the subsequent loading of BBH into this composite (CS/CMCD/BBH) was effectively accomplished. BBH was used as a model drug and the resulting hydrogel demonstrated a sustained drug release profile. In addition to its improved solubility and sustained release characteristics, the hydrogel exhibited excellent antibacterial activity against common pathogens such as Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans). Additionally, in vitro studies indicated that the hydrogel was not cytotoxic to NIH3T3 and HaCaT cells, suggesting its safety for biomedical applications. This lack of cytotoxic effects, combined with the mechanical strength, solubility improvements, and antibacterial properties of the hydrogel, positions the CS/CMCD/BBH hydrogel as a promising candidate for effective oral delivery of BBH. By addressing the solubility and delivery challenges of BBH, this hydrogel offers a viable solution for the oral administration of berberine hydrochloride, with potential applications in various biomedical fields.

The importance of contact with nature for human health was confirmed by numerous research. One of the sometimes neglected fields is the landscape design of hospital premises. This study focuses on the perception and preferences of prospective patients regarding the hospital site design. The methodology included anonymous survey with images and lists of adjectives. The online questionnaire was distributed using e-mails and social media from 4th May to 8th July 2024. The objective was to include all age groups. The results confirm previous studies and demonstrate the importance of landscape architecture design of hospital premises for the well-being of patients. The findings may inform the design of hospital sites.

A low cost, scalable and robust process has been proposed as innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminium nitrides, previously obtained on the laboratory scale. This work presents the scaling-up of fabrication process from laboratory to prototypal scale and pre-liminary results of outdoor self-cleaning solar mirror prototypes testing in the demonstrative CSP plant ENEASHIP located in Casaccia (Rome) ENEA research centre. Prototypes 50x40cm have shown stability in external conditions: no degradation occurs during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows the utilization of a reduced quantity of water for cleaning operations with respect to uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as glass envelopes of heat collecting elements, PV panels and everywhere are required self-cleaning performance combined to optical ones.

Researches on the runoff and sediment reduction effects of soil and water conservation measures are being on the rise, which is of great significance for carrying out strategic on soil and water conservation in the Yellow River Basin. Through the analysis of various soil and water conserva-tion measures, runoff, sediment, and rainfall datas in the Sanchuan River Basin from 1960 to 2019, we use the lagrange multiplier method to determining the threshold year of soil and water con-servation measures on runoff and sediment processes. The preliminary conclusion is as follows: The trend of flood season rainfall and annual rainfall in the Sanchuan River Basin is consistent. The 10-year average rainfall in each periods indicates that before 2000, it gradually decreased and then significantly increased. The 10-year average runoff showed a gradual decrease before 2010, followed by a sudden increase, while the 10-year average sediment has shown a decreasing trend years by years, especially after the centralized treatment period. Terrace and dam measures show a trend of first decreasing, then increasing, and then approaching stability during different treat-ment periods, while the trend of forest and grass measures is slightly decreasing and then in-creasing rapidly. The runoff and sediment reduction effects of various soil and water conservation measures during different treatment periods indicate that the runoff reduction effect reached its peak in 2005, while the sediment reduction benefit reached its best in 2015. Based on the compre-hensive benefits of runoff and sediment regulation, 2015 are considered as the threshold year for various soil and water conservation measures, with each measure areas being 4.86 × 104, 17.91 × 104, 1.20 × 104, and 0.83 × 104hm2, respectively. The research results will have certain reference significance for the high-quality development of soil and water conservation in the Yellow River Basin.

Although a lot of research has been carried out on hand sanitizer as an effort to prevent Covid-19, there is still limited research on non-alcoholic hand sanitizer lotion from the brown algae Scytosiphon lomentaria (S. lomentaria) as a raw material that provides antibacterial effects and maintains healthy skin. Therefore, this study aimed to analyze microbial inhibitory ability, physical and chemical characteristics of hand sanitizer lotion made from S. lomentaria algae. S. lomentaria powder was tested for phytochemicals, total phenolic content, free radical scavenging activity (IC50), and antibacterial tests. S. lomentaria slurry was prepared by adding distilled water (1:1) for lotion preparations in four treatment groups, such as normal control (lotion base without adding algae), lotion with the addition of algae 20%, 30%, and 40%. The lotion preparations for each treatment group were tested for antibacterial activity of Staphylococcus aureus and Escherichia coli, phytochemicals, pH, adhesion, spreadability, homogeneity, emulsion type, and hedonic. S. lomentaria powder contains bioactive polyphenolic compounds with a total phenolic content of 117.70±1.40 mg GAE/g dry weight and an IC50 value of 455±3.4 ppm, while lotion with the addition of S. lomentaria contains polyphenols and saponins The best treatment was shown by 40% S. lomentaria hand sanitizer lotion with inhibition of 6.30 ± 0.64 mm E. coli, 6.85 ± 1.12 mm S. aureus, hedonic test for color, texture and absorption with likes to likes very much level, neutral pH, greenish-white color, O/W emulsion type, high adhesion, homogeneous, and easily absorbed by the skin. This research can be an alternative reference in making non-alcoholic hand sanitizer lotion that is safe for the skin.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

While the role of safe riding behavior as a safety contributor for cyclists has been increasingly studied in recent years, there have been few studies analysing cycling behavior in relation to crash-related outcomes in Baltic countries. Indeed, to the best of our knowledge, this is the first time this issue has been addressed in the case of Latvia. Aim: The objective of this study was to assess the relationships among self-repotted cyclists’ behavior, traffic safety literacy, and their cycling crash involvement rates. Method: A total of 299 cyclists aged M=32.8 from across Latvia (42% females) participated in an online survey, which comprised questions regarding respondents’ demographics, frequency of riding, and the number of crashes in the past five years. The Cycling Behavior Questionnaire (CBQ) and the Cyclist Risk Perception and Regulation Scale (RPRS) were applied to assess cyclists' behavior patterns and traffic safety literacy. Results: According to the findings, it can be inferred that cyclists frequently engage in riding errors and traffic violations while cycling. Those who exhibit more antisocial behavior patterns are also more likely to be involved in road crashes. Conversely, cyclists with greater positive behavior rates more often also tend to possess better knowledge of traffic rules and exhibit a heightened risk perception, indicating a greater awareness of road traffic safety. Conclusion: All in sum, this study underscores key age differences, with older individuals significantly less involved in riding crashes, exhibiting fewer driving errors and a higher level of risk perception, which serves as a crucial factor in road safety. At the practical level, these results stress the need to address both traffic safety literacy and protective cycling factors of cyclists, in a manner to improve overall road safety and promote active transport modes in Latvia.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P&lt;0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

Students have historically fared poorly on the West African Examinations Council’s (WAEC) mathematics exam. This study investigated senior high school students’ difficulties with studying Geometry in the Cape Coast Metropolis, Central Region, Ghana. Using the descriptive survey design, data were collected from 300 Senior High School Two (SHS 2) students using simple random sampling. Students responded to the questionnaire and a 30-item multiple-choice achievement test on geometry. Four geometry concepts students perceived difficult to study are Circle theorems, Perpendicularity of Tangent and radius of a circle, Angle between Tangent and a chord and Tangents from an external point. The reasons for the difficulty in studying geometry topics are the unavailability of instructional materials, the geometry topics being complex, and teachers not teaching geometry concepts to the students’ understanding. Students’ gender did not influence the learning of concepts in geometry at a 0.05 level of significance. There was an insignificantly weak positive correlation between the students’ performance and their perceived difficult geometry concepts. It was concluded that the Ministry of Education does not provide relevant instructional materials to the various schools to teach geometry concepts. Schools do not organise workshops and seminars for teachers on effectively teaching geometry concepts in mathematics.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

With the development of organizational biology and forced from the EU Cosmetic Regulation (EU/1223/2009) with the complete ban of animal testing for cosmetic purposes, 3D skin models have been widely developed due to their similar physiological structure and metabolic function to native human tissue. 3D skin models for in vitro cosmetic evaluation are still promising alternative methods for evaluating phototoxicity, corrosivity and irritation. These models have been used for early screening and later validation of toxicity and efficacy evaluation by many well-known cosmetic companies. 3D skin models have become an important tool in cosmetic evaluation research. This article reviews the development of 3D skin models and their application in cosmetic evaluation. An outlook on the current application and future technological development directions in the cosmetic field is also presented.

As the most active plateau on the Earth, the Qinghai-Tibet Plateau has a complex crust-mantle structure. Knowledge of the distribution of such a structure provides information for understanding the underlying geodynamic processes. We obtains a three-dimensional density model of crustal and upper mantle beneath Qinghai-Tibet plateau and its surrounding areas from the residual geoid anomalies using the Earth Gravitational Model (EGM) 2008. We estimate a refined density model by iterations, using an initial density contrast model. We confirm that the EGM2008 mission products can be used to constrain the crust-mantle density structures. Our major findings are: (1). At 300-400 km depth, high-D anomalies terminate around Jinsha River Suture (JRS) in the central TP, suggesting that the Indian plate has been reached over the Bangong Nujiang Suture (BNS) and almost reach to the JRS. (2). On the eastern TP, low-D anomalies at the depth of 0-300 km together with high-D anomalies at 400-670 km further verified the current eastward subduction of Indian plate. The ongoing subduction provides forces to the occurrences of frequent earthquakes and volcano. (3). At 600 km depth, low-D anomalies inside the TP illustrate the existence of hot weak material beneath there, contributing to the external material inward-thrusting.

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

Credit card payment platforms are increasingly used for e-commerce activities. Credit cards are payment cards issued to individuals so they can purchase products and services based on their accumulated debt. Since credit cards are becoming very popular and widely used, the number of related fraud cases is likewise increasing. Whereas, there are large numbers of credit card transactions daily; thus, it becomes complex to differentiate between fraudulent and non-fraudulent transactions. Accordingly, different machine learning (ML) tools have been deployed in the literature to filter credit card transactions to prevent cardholders and financial institutions from losing money. In this article, the ensemble hidden Markov model (EHMM) approach is deployed to predict credit card fraud. EHMM is a popular and flexible ML tool that can easily model randomly changing datasets. Yet, the performance of the EHMM solely depends on the adopted feature extraction technique. The more reliable the feature extraction technique, the better the performance of the EHMM. In this vein, this article analyses two feature extraction techniques that can be combined with the EHMM for the prediction of credit card fraud. First, the principal component analysis (PCA) feature extraction techniques are combined with the EHMM to effectively predict credit card fraud. Yet, the PCA increases the computational time complexity of the EHMM. Therefore, this article adapts some statistical features to reduce the computational time complexity imposed on the EHMM. These robust but simple statistical features termed MRE; Mean, Relative Amplitude, and Entropy, are merged to form a feature vector that can be combined with the EHMM to effectively predict credit card frauds. The performance of the PCA-EHMM and MRE-EHMM are evaluated using the credit card transactions dataset of European cardholders gathered within two days in September 2013. The results were documented using different performance metrics such as recall/sensitivity, specificity, precision, and F1-score. The findings of this article will offer solutions to the loss experienced by cardholders and financial institutions as a result of online banking which requires credit card details.

This paper proposes the GD (Geometric Distribution) algorithm, a novel approach to enhance the default Adaptive Data Rate (ADR) mechanism in the Long Range Wide Area Network (LoRaWAN). By leveraging the Probability Mass Function (PMF) of the GD model, the GD algorithm effectively addresses massive device distribution challenges in real-life scenarios. To evaluate the algorithm's performance, the LoRaWAN simulations were conducted using the fixed node pattern derived from actual locations of dairy farms in Ratchaburi province, Thailand. The research established scenarios for assessing the network's performance namely, DER (Data Extraction Rate) and SF (Spreading Factor) assignment. Comparative analyses were performed against the uniform random node pattern and established algorithms, including the default ADR scheme, EXPLoRa, Quantile Classification of Variance from the Mean (QCVM), and Standard Deviation (SD). The GD algorithm demonstrated significant improvements over existing methodologies for both fixed and uniform random patterns. The fixed pattern exhibited an enhancement of 14.3%, while the uniform random pattern showed 4.8% enhancement over the default ADR scheme. Further assessments covered the coverage area, payload size, and energy consumption. The GD algorithm consistently achieved the optimal DER values with a coverage area and payload size, albeit often at the expense of increased energy consumption.

The link between the world of communication and the world of racing is provided by telemetry systems in electric racing cars. These systems send real-time data about the vehicle’s behavior and systems to enable informed decisions during the race. The aim of this research was to integrate telemetry into the battery bank of a racing electric vehicle to find the optimal values of current and voltage that optimize the charging process, thus improving the vehicle’s performance in competition using Response Surface Analysis. Particularly, the telemetry system consisted of an Arduino Mega, a digital wattmeter, and temperature sensors, all installed in the vehicle. Once the telemetry data was obtained, a response surface design was adapted with current, voltage, and temperature as factors, varying from low to high values, with the objective function being to minimize the battery’s charging time. Applying the response surface methodology and the steepest descent algorithm, it was found that all factors significantly affect the charging time, with the minimum charge time being 6961 seconds, obtained with a current of 2.4 amps and voltages of 50.5 volts and 43.6 volts.

The increasing growth in knowledge about functioning of the nervous system of mammals and humans, as well as the significant neuromorphic technologies development in recent decades, have led to the emergence of a large number of brain-computer interfaces and neuroprosthetics for the regenerative medicine tasks. Neurotechnologies have traditionally been developed for therapeutic purposes to help or replace motor, sensory or cognitive abilities damaged by injury or disease. They also have significant potential for memory enhancement. However, there are still no fully developed neurotechnologies and neural interfaces capable of restoring or expanding cognitive functions, in particular memory, in mammals or humans. In this regard, the search for new technologies in the field of restoration of cognitive functions is an urgent task of modern neurophysiology, neurotechnology and artificial intelligence. Hippocampus is an important brain structure connected to memory and information processing in the brain. The aim of this paper is to propose an approach based on deep neural networks for prediction of hippocampal signals in CA1 region based on received biological input in CA3 region. We compare results of prediction for two widely used deep architectures: reservoir computing (RC) and long short-term memory (LSTM) networks. Proposed study can be viewed as a first step in the complex task of the development of a neurohybrid chip, which allows one to restore memory functions in the damaged rodent hippocampus.

(1) Background: Learning and training in variable conditions favors adapting to unstable or changing environments. The aim of the study was to test the effect of variable practice on the accuracy of the forehand net approach shot in tennis.; (2) Methods: Thirty (n=30) first-class national players (12.9 ± 1.1 years old) participated, divided into three groups: i) induced variability training (n=10) (varying court surfaces and balls), ii) specific training (n=10) and iii) usual training -control group- (n=10). All groups trained for a month: 12 sessions of 20 minutes -3 per week-. The accuracy of the shots were analyzed through a 2D capture and digitization process of the ball bounce on the court; (3) Results: The variability group presented better accuracy values after the period without practice than the stable training group (p = 0.041; ES= 0.51).; (4) Conclusions: the application of variability in the game conditions during tennis training seems to have a favorable effect on the retention of accuracy in the forehand down the line approach to the net.

Urban air pollution is a significant threat to both the environment and public health. Primarily originating from traffic emissions, particulate matter is identified as the most prevalent and toxic pollutant in cities. In recent years, street vegetation has emerged as a nature-based solution to improve urban air quality. However, to achieve this goal, proper placement of vegetation is crucial. This study critically investigates how different street tree placement strategies affect the local air quality, based on a model calibrated using existing air quality measurements from one of the most polluted streets in Glasgow. We then test the local air quality effects of tree orientation, spacing, shape, porosity, size, species, and wind directions. The findings suggest that trees effectively enhance air quality, particularly when implemented on the leeward side of the street. To achieve optimal effectiveness, the spacing of trees require careful alignment with the aspect ratio, as haphazard planting could lead to unfavorable results. The insights on improving air quality in Glasgow's street canyons, complements the objectives of the ‘Glasgow Avenues Programme’ and can be included in its Low Emission Zones to co-benefit the environment and the wellbeing of the local community.

The unprecedented production and sharing of data, opinions, and comments among people on social media and the Internet in general has highlighted sentiment analysis as a key machine learning approach in scientific and market research. Sentiment analysis can extract sentiments and opinions from user-generated text, providing useful evidence for new product decision-making and effective customer relationship management. However, there are concerns about existing standard sentiment analysis tools regarding the generation of inaccurate sentiment classification results. The objective of this paper is to determine the efficiency of off-the-shelf sentiment analysis APIs in recognizing low-resource languages, such as Greek. Specifically, we examined whether sentiment analysis performed on 300 online ordering customer reviews using the Meaning Cloud web-based tool produced meaningful results with high accuracy. According to the results of the study, we found low agreement between the web-based and the actual raters in the food delivery services related data. However, the low accuracy of the results highlights the need for specialized sentiment analysis tools capable of recognizing only one low-resource language. Finally, there is a significant need for the creation of industry-specific lexical resources that provide decision-makers with valuable insights.

For concrete structures exposed to offshore areas, chloride ion erosion is one of the main factors affecting the durability. It is crucial to evaluate chloride ion permeability resistance of concrete structures. In this article, a finite element simulation of the chloride ion diffusion process in concrete is conducted. A mass diffusion finite element model based on random aggregate approach is established to investigate the influence of aggregate, interface transition zone, and micro-cracks on chloride ion diffusion coefficients in concrete. The results show that the mass diffusion finite element analysis based on the exponential function model and power function model can effectively simulate the chloride ion diffusion process in concrete. In addition, the data reveal that coarse aggregate is the most important factor affecting chloride ion diffusivity in concrete. However, the interface transition zone significantly accelerates chloride ion diffusion in concrete. Moreover, this acceleration effect exceeds the barrier effect of aggregate.

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

Through the use of Smart Sensor Networks (SSN), Marine Observatories (MO) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of SSN devices’ hardware and software when combined with the Internet. Hence, SSN are regarded as complex distributed systems. As such, SSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed SSN. To this end, we describe in this article how we extended our previously proposed ArchiMO meta-model and design tool by extending an Enterprise Architecture Framework based on the ArchiMate Modeling Language. This extension proposes the incorporation of new Underwater Environmental Constraints (UEC) for SSN in ArchiMO which is coupled with the fusion of sensors with Artificial Intelligence. This serves as the basis for generating a new version of our ArchiMO design tool, which incorporates the new added constraints and invokes the AI created Database. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to handle and control the uncertainties and variances of the provided quality of service that may occur during the performance of the SSN, hence reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of SSN.

(1) Background: This paper details the development process of two assistive technology products (ATs) implemented in the PAID project, aiming to promote the social, educational, and labor inclusion of people with disabilities across 10 municipalities of Antioquia, Colombia. (2) Methods: Applying Design Thinking (DT) methodology, including stages of empathizing, defining, ideating, prototyping, and testing, alongside a demographic study where specific needs of people with disabilities (PwDs) were identified. (3) Results: As a result, the construction process of two specific cases of assistive technology products (ATs) is detailed, including finite element simulation, mechanical testing, and delivery to end-users. Additionally, workshops for assistive product fabrication conducted in select municipalities of the project are highlighted. (4) Conclusions: the information gathered guided the development of the ATs, focusing on their features on accessibility and ease of replication. The primary objective is to facilitate the participation of PwDs in educational environments, thus promoting inclusion and accessibility. This article describes the results of two of these ATs; however, it is worth noting that this process was performed for 112 ATs delivered through the duration of the project.

The current research examines the many characteristics of the $\ell_{p}(\widetilde{F}(\widetilde{r},\widetilde{s}))$ $(1\leq p<\infty)$ and $\ell_{\infty}(\widetilde{F}(\widetilde{r},\widetilde{s}))$ spaces which are the generalized forms of those by Candan in 2024 using Fibonacci numbers and two non-zero real numbers in accordance with a predetermined rule, we have made an effort to go through all the characteristics and features which the author of earlier versions thought are the most valuable. This manuscript contains all the information required to describe the matrix class $(\ell_{1},\ell_{p}(\widetilde{F}(\widetilde{r},\widetilde{s})))$ $(1\leq p<\infty)$ which are going to be given in detail in the following sections of the manuscript. We are going to offer estimates for the norms of the bounded linear operators $L_{A}$ formed by those matrix transformations utilizing the Hausdorff measure of non-compactness and identify prerequisites to derive the relevant subclasses of compact matrix operators. When the findings of the current study are compared to those found in the literature, it can be said that the newly found ones are more inclusive and comprehensive.

Salmonella causes various type of disease worldwide with a remarkable pace. Salmonella enteric serotype typhi (S. typhi), a gram-negative bacterium (only cause disease in man) is the mainly causative agent of Typhoid fever. Typhoid fever is most common in poor and unprivileged developing countries of Asia and Africa. One of the major components of virulence factors produced during salmonella infection is Lipid A, which acts as a potent human immuno-modulator bacterial endotoxin. Regulation of Lipid A biosynthetic pathway occurs at second step, catalyzed by LpxC, a Zn2+ dependent metalloamidase. Systematic Screening of a pool of drug datasets like natural products library from Zinc database, Asinex database, Thiophene analogues fruitfully provided us 3 potent lead molecules s1_dl_mseq2, s1_ll_mseq2, and s2_ll_mseq8 which actively binds with LpxC enzyme and could be developed into sound inhibitors of LpxC enzyme after the application of drug development and processing strategies. Wet lab experimentation is required to validate these results for further use.

We present an innovative method harnessing multistability within a diode-pumped erbium-doped fiber laser to construct logic gates. Our approach involves manipulating the intensity of external noise to regulate the probability of transitioning among four concurrent attractors. In this manner, we facilitate the realization of OR, AND, NOT, and NOR logic operations, aligning with the coexisting period-1, period-3, period-4, and period-5 orbits. Employing detrended fluctuation analysis, we establish equilibrium in the probability distributions of these states. The obtained results denote a substantial advancement in the field of optical logic gate development, representing a pivotal stride toward the seamless integration of an all-optical logic gate within laser oscillator-based systems.

Background: Cognitive for patients with neurocognitive disorders are mostly measured by Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left skewed and the results of association analysis might not be robust. This study aims to study the distribution of the cognitive outcomes and to discuss potential solutions. Materials and Methods: The inverse transformed cognitive outcomes are modelled using different statistical distributions. Robustness of the proposed models are checked under different scenarios: with intercept only, models with covariate, with and without bootstrapping. Results: Main results were based on VCAT score, and validated via MoCA score. Findings suggested that the inverse transformation method improves modelling the cognitive scores compared to the conventional methods using the original cognitive scores. Association of baseline characteristics (age, gender and years of education) and the cognitive outcomes were reported as estimates and 95% confidence intervals. Bootstrap methods improved the estimate precision and the bootstrapped standard errors of the estimates are more robust. Cognitive outcomes are widely analyzed using linear regression models with default normal distribution as a conventional method. We compared the results of our suggested models with the normal distribution under various scenarios. Goodness-of-fit measurements were compared between proposed models and conventional methods. Conclusions: The findings support the use of the inverse transformation method to model the cognitive outcomes instead of the original cognitive scores for early stage neurocognitive disorders where the cognitive outcomes are left skewed.

Non-alcoholic fatty liver disease (NAFLD) has emerged as a significant liver ailment attributed to factors like obesity and diabetes. While ongoing research explores treatments for NAFLD, further investigation is imperative to address this escalating health concern. NAFLD manifests as hepatic steatosis, precipitating insulin resistance and metabolic syndrome. This study aims to validate the regenerative potential of chimeric fibroblast growth factor 21 (FGF21)-Hepatocyte Growth Factor Receptor (HGFR) in NAFLD-afflicted liver cells. AML12, a murine hepatocyte cell line, was utilized to gauge the regenerative effects of chimeric FGF21/HGFR expression. Polysaccharide accumulation was affirmed through periodic acid-Schiff (PAS) staining, while LDL uptake was microscopically observed with labeled LDL. mRNA analysis via RT-PCR revealed reduced expression of key NAFLD markers, including acetyl-CoA carboxylase 1 (ACC1) and sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP), alongside elevated levels of hepatocyte growth factor (HGF), hepatocyte nuclear factor 4 alpha (HNF4A), and albumin (ALB). These findings affirm the hepatoregenerative properties of chimeric FGF21/HGFR within AML12 cells, opening novel avenues for NAFLD therapeutic exploration.