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Automatic License Plate Recognition (ALPR) systems are essential for Intelligent Transport Systems (ITS), effective transportation management, security, law enforcement, etc. However, the performance of ALPR systems can be significantly affected by environmental conditions such as heavy rain, fog, and pollution. This paper introduces a weather-adaptive Convolutional Neural Network (CNN) framework that leverages the YOLOv10 model that is designed to enhance license plate detection in adverse weather conditions. By incorporating weather-specific data augmentation techniques, our framework improves the robustness of ALPR systems under diverse environmental scenarios. We evaluate the effectiveness of this approach using metrics such as precision, recall, F1, mAP50, and mAP50-95 score across various model configurations and augmentation strategies. The results demonstrate a significant improvement in overall detection performance, particularly in challenging weather conditions. This study provides a promising solution for deploying resilient ALPR systems in regions with similar environmental complexities.

Two experiments assessed the effects of providing a vitamin and mineral supplement to gestating beef heifers on concentrations of immunoglobulins (Ig) in colostrum and calf serum 24 h after feeding maternal colostrum (Exp. 1) or a colostrum-replacement product (Exp. 2). Angus-based heifers ( n = 31, Exp. 1; n = 14, Exp. 2) were fed a basal diet (CON) or were fed a basal diet plus a vitamin and mineral supplement (VTM) from breeding (Exp. 1) or 60 d pre-breeding (Exp. 2) through calving. Colostrum was collected at calving, and serum was collected from calves 24 h after colostrum consumption to evaluate passive transfer. Serum was collected from calves in Exp. 1 to determine serum titers in response to vaccination at birth, pasture turn out, weaning, and 14 d after vaccination. Concentrations of IgG, IgM, or IgA in colostrum or in calf serum at 24 h were not impacted by dam treatment ( p ≥ 0.21); however, concentrations of Ig in calf serum at 24 h were greater ( p ≤ 0.01) in calves receiving maternal colostrum than those receiving a colostrum replacer. Calves born to VTM heifers had greater antibody titers at birth, pasture turn out, and weaning for infectious bovine rhinotracheitis (IBR), bovine viral diarrhea virus type 2 (BVD-2), and bovine respiratory syncytial virus (BRSV), respectively. Our results suggest that the programming of immune function in calves via prenatal nutrition appears to extend postnatally in CON and VTM offspring.

Since its discovery in 1992, the receptor for advanced glycation end products (RAGE) has emerged as a key receptor in many pathological conditions, especially in inflammatory conditions. RAGE is expressed by most, if not all, immune cells and can be activated by many ligands. One characteristic of RAGE is that its ligands are structurally very diverse and belong to different classes of molecules, making RAGE a promiscuous receptor. Many of RAGE ligands are damaged associated molecular patterns (DAMPs) that are released by cells under inflammatory conditions. Although RAGE has been at the center of a lot of research in the past three decades, a clear understanding of the mechanisms of RAGE activation by its ligands is still missing. In this review, we summarize the current knowledge of the role of RAGE and its ligands in inflammation.

Post-harvest storage loss in sugar beets due to root rot and respiration can cause >20% sugar loss. Breeding strategies focused on factors contributing to improved post-harvest storage quality are of great importance to prevent losses. Using 16S rRNA and ITS sequencing and sugar beet mutational breeding lines with high disease resistance (R), along with a susceptible (S) commercial cultivar, the role of root microbiome and metabolome in storage performance was investigated. The R lines in general showed higher abundances of bacterial phyla, Patescibacteria at the M time point, and Cyanobacteria and Desulfobacterota at the L time point. Amongst fungal phyla, Basidiomycota (including Athelia ) and Ascomycota were predominant in diseased samples. Linear discriminant analysis Effect Size (LEfSe) identified bacterial taxa such as Micrococcales , Micrococcaceae , Bacilli , Glutamicibacter, Nesterenkonia , and Paenarthrobacter as putative biomarkers associated with resistance in the R lines. Further functional enrichment analysis showed a higher abundance of bacteria, such as those related to the super pathway of pyrimidine deoxyribonucleoside degradation, L-tryptophan biosynthesis at M and L, and fungi, such as those associated with the biosynthesis of L-iditol 2-dehydrogenase at L in the R lines. Metabolome analysis of the roots revealed higher enrichment of pathways associated with arginine, proline, alanine, aspartate, and glutamate metabolism at M, in addition to beta-alanine and butanoate metabolism at L in the R lines. Correlation analysis between the microbiome and metabolites indicated that the root's biochemical composition, such as the presence of nitrogen-containing secondary metabolites, may regulate relative abundances of key microbial candidates contributing to better post-harvest storage.

Many non-natural amino acids can be incorporated by biological systems into coded functional peptides and proteins. For such incorporations to be effective, they must not only be compatible with the desired function but also evade various biochemical error-checking mechanisms. The underlying molecular mechanisms are complex, and this problem has been approached previously largely by expert perception of isomer compatibility, followed by empirical study. However, the number of amino acids that might be incorporable by the biological coding machinery may be too large to survey efficiently using such an intuitive approach. We introduce here a workflow for searching real and computed non-natural amino acid libraries for biosimilar amino acids which may be incorporable into coded proteins with minimal unintended disturbance of function. This workflow was also applied to molecules which have been previously benchmarked for their compatibility with the biological translation apparatus, as well as commercial catalogs. We report the results of scoring their contents based on fingerprint similarity via Tanimoto coefficients. These similarity scoring methods reveal candidate amino acids which could be substitutable into modern proteins. Our analysis discovers some already-implemented substitutions, but also suggests many novel ones.

Monensic acid is a natural polyether ionophore and is a therapeutic of first choice in veterinary medicine for the control of coccidiosis. Although known as a sodium-binding ligand, it can also form a variety of coordination species depending on experimental conditions applied. In this study, we present the crystal structures and properties of Co(II) and Mn(II) complexes of sodium monensinate (MonNa) derived from the reaction of MonNa with cobalt or manganese dinitrates. The newly obtained coordination compounds have the same composition [M(MonNa) 2 (NO 3 ) 2 ] but the transition metal ions are placed in a different environment. The two nitrate ligands behave mono- or bidentately bound in the Co(II)- and Mn(II)-containing species, respectively, while the monensinate ligands act in a similar manner through their monodentate carboxylate functions. The formed CoO 4 and MnO 6 units determine the geometry of the corresponding inner coordination cores of the complexes as a tetrahedron in the case of Co(II), and as a strongly distorted octahedral structure in Mn(II) species. The effect of inorganic anions on the antibacterial performance of sodium monensinate appears to be negligible, while the presence of Co(II) or Mn(II) cations preserves or enhances the activity of unmodified MonNa, which differentially affects the growth of Bacillus subtilis , Bacillus cereus , Kocuria rhizophila , Staphilococcus aureus , and Staphilococcus saprophyticus strains.

Poly(vinyl alcohol) (PVA)-based films have drawn significant attention owing to their potential applications in various industries. The application of wax to PVA films enhanced their resistance to dissolution and water infiltration. Nevertheless, waxed PVA films often exhibit inadequate mechanical properties owing to crack formation. In this study, we evaluated the impact of glycerol as a plasticizer in varying concentrations of Carnauba wax (CW). The addition of glycerol to the PVA/CW blend led to enhanced mechanical properties compared to the blend without glycerol. The functional group and morphology of the blends confirm glycerol compatibility with PVA/CW films. Glycerol was fully dispersed to form a consistent polymer matrix and equally improved the film's contact angle. Furthermore, the thermal property from differential scanning calorimetry and thermogravimetric analysis highlights the plasticizing effect of glycerol in PVA/CW films, potentially broadening their use in food packaging and wrapping applications.

Reinforcing thermoset polymers with continuous carbon fiber (CF) tow has emerged as a promising avenue to overcome the thermal and mechanical performance limitations of 3D printed polymeric structures for load-bearing applications. Unlike traditional methods, manufacturing continuous fiber-reinforced composites by 3D printing has the unique capability of locally varying the mechanical properties of the composites. In this study, continuous CF thermoset composite specimens were printed with varying line spacing, resin flow rate, and nozzle sizes. The resin flow rates for different line spacings and nozzle sizes were optimized by topographic analysis. Printed composite mechanical properties were evaluated, and their trends were correlated with the trend of print parameter changes. Results showed that tensile strength and modulus could be altered and improved by ~50% by adjusting the printing process parameters. Higher composite strength and modulus were obtained by shortening the line spacing and nozzle diameter.

The stubby root nematode, Paratrichodorus allius, is one of the most important plant-parasitic nematodes. Besides root feeding, P. allius also transmits the Tobacco rattle virus in potatoes, which causes corky ringspot disease. Rapid detection of P. allius is key for efficient management. This study was conducted to develop a real-time recombinase polymerase amplification (RPA) assay that is capable of detecting P. allius directly in DNA extracts from soil using a simple portable device in real time. A fluorophore-attached probe was designed to target the internal transcribed spacer (ITS)-rDNA of P. allius and was used along with primers designed previously. The real-time RPA assay had the ability to detect P. allius DNA extracted directly from infested soil with a sensitivity of one-sixteenth portion of a single nematode. This RPA assay was specific, as it did not produce positive signals from non-target nematodes tested. The real-time RPA was found to be rapid as it could even detect P. allius in as little as 7 min. Testing with 15 field soil samples validated the RPA assay developed in this study. This is the first report of P. allius detection directly from soil DNA using real-time RPA and is the fastest method for P. allius detection in soil to date.

This work is devoted to the investigation of dielectric permittivity which is influenced by electronic, ionic, and dipolar polarization mechanisms, contributing to the material's capacity to store electrical energy. In this study, an extended dataset of 86 polymers was analyzed, and two quantitative structure-property relationship (QSPR) models were developed to predict dielectric permittivity. From an initial set of 1273 descriptors, the most relevant ones were selected using a genetic algorithm, and machine learning models were built using the Gradient Boosting Regressor (GBR). In contrast to Multiple Linear Regression (MLR)- and Partial Least Squares (PLS)-based models, the gradient boosting models excel in handling nonlinear relationships and multicollinearity, iteratively optimizing decision trees to improve accuracy without overfitting. The developed GBR models showed high R 2 coefficients of 0.938 and 0.822, for the training and test sets, respectively. An Accumulated Local Effect (ALE) technique was applied to assess the relationship between the selected descriptors-eight for the GB_A model and six for the GB_B model, and their impact on target property. ALE analysis revealed that descriptors such as TDB09m had a strong positive effect on permittivity, while MLOGP2 showed a negative effect. These results highlight the effectiveness of the GBR approach in predicting the dielectric properties of polymers, offering improved accuracy and interpretability.

Xanthan gum (XG) is an exopolysaccharide synthesized by the aerobic fermentation of simple sugars using Xanthomonas bacteria. It comprises a cellulosic backbone with a trisaccharide side chain connected to alternative glucose residues in the main backbone through α (1→3) linkage. XG dissolves readily in cold and hot water to produce a viscous solution that behaves like a pseudoplastic fluid. It shows excellent resistance to enzymatic degradation and great stability throughout a broad temperature, pH, or salt concentration range. Additionally, XG is nontoxic, biocompatible, and biodegradable, making it a suitable carrier for drug delivery. Furthermore, the carboxylic functions of pyruvate and glucuronic acid offer a considerable opportunity for chemical modification to meet the desired criteria for a specific application. Therefore, XG or its derivatives in conjunction with other polymers have frequently been studied as matrices for tablets, nanoparticles, microparticles, and hydrogels. This review primarily focuses on the applications of XG in various oral delivery systems over the past decade, including sustained-release formulations, gastroretentive dosage forms, and colon-targeted drug delivery. Source, production methods, and physicochemical properties relevant to drug delivery applications of XG have also been discussed.

Carbon dots (CDs) have garnered extensive interest in basic physical chemistry as well as in biomedical applications due to their low cost, good biocompatibility, and great aqueous solubility. However, the synthesis of multi-functional carbon dots has always been a challenge for researchers. Here, we synthesized novel CDs with a high quantum yield of 28.2% through the straightforward hydrothermal method using Diaminomaleonitrile and Boc-D-2, 3-diaminopropionic acid. The size, chemical functional group, and photophysical properties of the CDs were characterized by TEM, FTIR, XPS, UV, and fluorescence. It was demonstrated in this study that the prepared CDs have a high quantum yield, excellent photostability, and low cytotoxicity. Regarding the highly water-soluble property of CDs, they were proven to possess selective and sensitive behavior against Cu 2+ ions (linear range = 0-9 μM and limit of detection = 1.34 μM). Moreover, the CDs were utilized in fluorescent ink in anti-counterfeiting measures. Because of their low cytotoxicity and good biocompatibility, the CDs were also successfully utilized in cell imaging. Therefore, the as-prepared CDs have great potential in fluorescence sensing, anti-counterfeiting, and bioimaging.

Cell surface signaling (CSS) is a means of rapidly adjusting transcription in response to extracellular stimuli in Gram-negative bacteria. The pseudobactin BN7/8 uptake (Pup) system not only imports iron but also upregulates its own transcription through CSS in Pseudomonas capeferrum . In the absence of ferric pseudobactin BN7/8, the signaling components are maintained in a resting state via the formation of a periplasmic complex between the N-terminal signaling domain (NTSD) of the outer membrane iron-transporter, PupB, and the C-terminal CSS domain (CCSSD) of the sigma regulator, PupR. The previously determined 1.6 Å crystal structure of this periplasmic complex has allowed us to probe the structural and thermodynamic consequences of mutating key interfacial residues. In this report, we describe the solution structure of the PupB NTSD and use Nuclear Magnetic Resonance spectroscopy, Isothermal Titration Calorimetry, and Circular Dichroism spectroscopy together with thermal denaturation to investigate whether three PupB point mutations, Q69K, H72D, and L74A, influence the interaction merely due to the chemical nature of the amino acid substitution or also cause changes in overall protein structure. Our results demonstrate that binding to the PupR CCSSD does not alter the structure of PupB NTSD and that the individual mutations have only minor effects on structure. The mutations generally lower thermodynamic stability of the NTSD and weaken binding to the CCSSD. These findings validate the X-ray crystal structure interface, emphasizing the importance of amino acid chemical nature at the interface.

Poor maternal nutrition during gestation negatively affects offspring growth and metabolism. To evaluate the impact of maternal nutrient restriction and realimentation on metabolism in the fetal liver, skeletal muscle, and circulation, on day 50 of gestation, ewes ( n = 48) pregnant with singletons were fed 100% (CON) or 60% (RES) of requirements until day 90 of gestation, when a subset of ewes ( n = 7/treatment) were euthanized, and fetal samples were collected. The remaining ewes were maintained on a current diet (CON-CON, n = 6; RES-RES, n = 7) or switched to an alternative diet (CON-RES, RES-CON; n = 7/treatment). On day 130 of gestation, the remaining ewes were euthanized, and fetal samples were collected. Fetal liver, longissimus dorsi (LD), and blood metabolites were analyzed using LC-MS/MS, and pathway enrichment analysis was conducted using MetaboAnalyst. Then, 600, 518, and 524 metabolites were identified in the liver, LD, and blood, respectively, including 345 metabolites that were present in all three. Nutrient restriction was associated with changes in amino acid, carbohydrate, lipid, and transulfuration/methionine metabolic pathways, some of which were alleviated by realimentation. Fetal age also affected metabolite abundance. The differential abundance of metabolites involved in amino acid, methionine, betaine, and bile acid metabolism could impact fetal epigenetic regulation, protein synthesis, lipid metabolism, and signaling associated with glucose and lipid metabolism.

The incidence of early-onset colorectal cancer (EO-CRC) in individuals under 50 years old is rapidly increasing in the United States. This study aims to evaluate EO-CRC incidence rates using data from the Global Burden of Disease Study (GBD) 2021, providing insights into trends from 1990 to 2021. We employed an age-period-cohort (APC) model analysis to estimate the effects of age, time period, and birth cohort on EO-CRC incidence. Our findings indicate that the number of EO-CRC cases rose from 6256 (95% UI: 6059-6456) in 1990 to 9311 (95% UI: 8859-9744) in 2021, a 49% increase from 1990 to 2021. The age-standardized incidence rate per 100,000 population increased by 34% during this period. The net drift in females (0.22%, 95% CI: 0.20-0.24) was slightly higher than in males (0.21%, 95% CI: 0.19-0.23) ( p = 0.45). The APC analysis revealed that being over 25 years old, the period from 2005-2021, and being born after 1983 negatively impacted EO-CRC incidence rates, with a sharp rise after 2000 and a reduction among females from 2017 to 2021. Our study highlights the need for targeted prevention strategies and further research to understand these trends.

Oil serves as the essential fuel and economic foundation of contemporary industry. However, the use of traditional light crude oil has exceeded its supply, making it challenging to meet the energy needs of humanity. Consequently, the extraction of heavy oil has become crucial in addressing this demand. This research focuses on the synthesis of several water-soluble catalysts that can work along with reservoir minerals to catalyze the hydrothermal cracking process of heavy oil. The goal is to effectively reduce the viscosity of heavy oil and lower the cost of its extraction. Based on the experimental findings, it was observed that when oil sample 1 underwent hydrothermal cracking at a temperature of 180 °C for a duration of 4 h, the amount of water added and catalyst used were 30% and 0.2% of the oil sample dosage, respectively. It was further discovered that the synthesized Mn(II)C was able to reduce the viscosity of oil sample 1 by 50.38%. The investigation revealed that the combination of Mn(II)C + K exhibited a significant synergistic catalytic impact on reducing viscosity. Initially, the viscosity reduction rate was 50.38%, which climbed to 61.02%. Subsequently, when catalyzed by the hydrogen supply agent isopropanol, the rate of viscosity reduction rose further to 91.22%. Several methods, such as freezing point analysis, thermogravimetric analysis, DSC analysis, component analysis, gas chromatography, wax crystal morphology analysis, and GC-MS analysis, were conducted on aqueous organic matter derived from heavy oil after undergoing different reaction systems. These analyses confirmed that the viscosity of the heavy oil was decreased. By studying the reaction mechanism of the model compound and analyzing the aqueous phase, the reaction largely involves depolymerization between macromolecules, breakdown of heteroatom chains, hydrogenation, ring opening, and other related consequences. These actions diminish the strength of the van der Waals force and hydrogen bond in the recombinant interval, impede the creation of a grid-like structure in heavy oil, and efficiently decrease its viscosity.

Fused filament fabrication (FFF) is a key extrusion-based additive manufacturing (AM) process for fabricating components from polymers and their composites. Functionally gradient materials (FGMs) exhibit spatially varying properties by modulating chemical compositions, microstructures, and design attributes, offering enhanced performance over homogeneous materials and conventional composites. These materials are pivotal in aerospace, automotive, and medical applications, where the optimization of weight, cost, and functional properties is critical. Conventional FGM manufacturing techniques are hindered by complexity, high costs, and limited precision. AM, particularly FFF, presents a promising alternative for FGM production, though its application is predominantly confined to research settings. This paper conducts an in-depth review of current FFF techniques for FGMs, evaluates the limitations of traditional methods, and discusses the challenges, opportunities, and future research trajectories in this emerging field.

Semiconducting conjugated polymers (CPs) are pivotal in advancing organic electronics, offering tunable properties for solar cells and field-effect transistors. Here, we carry out first-principle calculations to study individual cis-polyacetylene (cis-PA) oligomers and their ensembles. The ground electronic structures are obtained using density functional theory (DFT), and excited state dynamics are explored by computing nonadiabatic couplings (NACs) between electronic and nuclear degrees of freedom. We compute the nonradiative relaxation of charge carriers and photoluminescence (PL) using the Redfield theory. Our findings show that electrons relax faster than holes. The ensemble of oligomers shows faster relaxation compared to the single oligomer. The calculated PL spectra show features from both interband and intraband transitions. The ensemble shows broader line widths, redshift of transition energies, and lower intensities compared to the single oligomer. This comparative study suggests that the dispersion forces and orbital hybridizations between chains are the leading contributors to the variation in PL. It provides insights into the fundamental behaviors of CPs and the molecular-level understanding for the design of more efficient optoelectronic devices.

The commercial veterinary antibiotic sodium monensinate (MonNa) binds mercury(II) or zinc(II) cations as thiocyanate [Hg(MonNa) 2 (SCN) 2 ] ( 1 ) or isothiocyanate [Zn(MonNa) 2 (NCS) 2 ] ( 2 ) neutral coordination compounds. The structure and physicochemical properties of 1 and 2 were evaluated by the methods of single crystal and/or powder X-ray diffraction, infrared, nuclear magnetic resonance, X-ray photoelectron spectroscopies, and electrospray-mass spectrometry. The primary cores of the two complexes comprise HgS 2 O 2 ( 1 ) and ZnN 2 O 2 ( 2 ) coordination motifs, respectively, due to the ambidentate binding modes of the SCN-ligands. The directly bound oxygen atoms originate from the carboxylate function of the parent antibiotic. Sodium cations remain in the hydrophilic cavity of monensin and cannot be replaced by the competing divalent metal ions. Zinc(II) binding does not influence the monensin efficacy in the case of Bacillus cereus and Staphylococcus aureus whereas the antimicrobial assay reveals the potential of complex 2 as a therapeutic candidate for the treatment of infections caused by Bacillus subtilis , Kocuria rhizophila , and Staphylococcus saprophyticus .

Continuous carbon fiber-reinforced (CCFR) thermoset composites have received significant attention due to their excellent mechanical and thermal properties. The implementation of 3D printing introduces cost-effectiveness and design flexibility into their manufacturing processes. The light-assisted 3D printing process shows promise for manufacturing CCFR composites using low-viscosity thermoset resin, which would otherwise be unprintable. Because of the lack of shape-retaining capability, 3D printing of various shapes is challenging with low-viscosity thermoset resin. This study demonstrated an overshoot-associated algorithm for 3D printing various shapes using low-viscosity thermoset resin and continuous carbon fiber. Additionally, 3D-printed unidirectional composites were mechanically characterized. The printed specimen exhibited tensile strength of 390 ± 22 MPa and an interlaminar strength of 38 ± 1.7 MPa, with a fiber volume fraction of 15.7 ± 0.43%. Void analysis revealed that the printed specimen contained 5.5% overall voids. Moreover, the analysis showed the presence of numerous irregular cylindrical-shaped intra-tow voids, which governed the tensile properties. However, the inter-tow voids were small and spherical-shaped, governing the interlaminar shear strength. Therefore, the printed specimens showed exceptional interlaminar shear strength, and the tensile strength had the potential to increase further by improving the impregnation of polymer resin within the fiber.

The increasing usage of interconnected devices within the Internet of Things (IoT) and Industrial IoT (IIoT) has significantly enhanced efficiency and utility in both personal and industrial settings but also heightened cybersecurity vulnerabilities, particularly through IoT malware. This paper explores the use of one-class classification, a method of unsupervised learning, which is especially suitable for unlabeled data, dynamic environments, and malware detection, which is a form of anomaly detection. We introduce the TF-IDF method for transforming nominal features into numerical formats that avoid information loss and manage dimensionality effectively, which is crucial for enhancing pattern recognition when combined with n-grams. Furthermore, we compare the performance of multi-class vs. one-class classification models, including Isolation Forest and deep autoencoder, that are trained with both benign and malicious NetFlow samples vs. trained exclusively on benign NetFlow samples. We achieve 100% recall with precision rates above 80% and 90% across various test datasets using one-class classification. These models show the adaptability of unsupervised learning, especially one-class classification, to the evolving malware threats in the IoT domain, offering insights into enhancing IoT security frameworks and suggesting directions for future research in this critical area.

Global Positioning Systems (GPSs) can collect tracking data to remotely monitor livestock well-being and pasture use. Supervised machine learning requires behavioral observations of monitored animals to identify changes in behavior, which is labor-intensive. Our goal was to identify animal behaviors automatically without using human observations. We designed a novel framework using unsupervised learning techniques. The framework contains two steps. The first step segments cattle tracking data using state-of-the-art time series segmentation algorithms, and the second step groups segments into clusters and then labels the clusters. To evaluate the applicability of our proposed framework, we utilized GPS tracking data collected from five cows in a 1096 ha rangeland pasture. Cow movement pathways were grouped into six behavior clusters based on velocity (m/min) and distance from water. Again, using velocity, these six clusters were classified into walking, grazing, and resting behaviors. The mean velocity for predicted walking and grazing and resting behavior was 44, 13 and 2 min/min, respectively, which is similar to other research. Predicted diurnal behavior patterns showed two primary grazing bouts during early morning and evening, like in other studies. Our study demonstrates that the proposed two-step framework can use unlabeled GPS tracking data to predict cattle behavior without human observations.

Background: Most people believe that student-athletes experience fewer difficulties related to mental health than non-sport participants. However, several studies have shown high depression levels or emotional difficulties in adolescent athletes. Most secondary school students have access to athletic trainers in their schools. Secondary school athletic trainers (SSATs) are medical professionals who can provide health care for student-athletes, and they could be appropriate supporters in providing mental health management in secondary schools. However, there are no studies that have addressed their preparedness and confidence level to manage potential risk factors and mental health disorders. This study aims to ascertain preparedness and confidence levels from SSATs' perspectives in handling mental health disorders using a survey based on the mental health management guidelines and consensus statement., Methods: This is a cross-sectional study design. The research team created an online survey questionnaire based on the National Athletic Trainers' Association (NATA) Mental Health Guidelines for Secondary School and Interassociation Recommendation: A Consensus Statement. Utilizing the NATA Research Survey Service, the online survey was emailed to SSATs who self-categorized as secondary school athletic trainers in the NATA membership system. ( n = 171, 65% completion rate). SPSS was used to analyze the survey data., Result: This study found that 29.2% of SSATs reported they have policies or guidelines regarding mental health disorders management for minors. The most frequent policy was mandatory reporting in cases in which an individual is being abused or neglected (80.5%). The highest confidence area was aligned with the most frequent policy. The least frequent policy was considering unique stressors and triggers with student-athletes to recognize the potential mechanisms that may cause a mental illness or exacerbate an existing mental illness (58.5%). Even though the least frequent policy was not aligned with the least confidence area, it was the second lowest confidence level. This study identified significant differences between two different employment structures: school-based employment and hospital-based employment structures. Policies were more common in school-based employment than in hospital-based employment structures., Conclusion: This study demonstrated the gap between organizational and individual preparation. The majority of SSATs respondents expressed moderate to high confidence in their ability to manage mental health disorders, despite the lack of mental health policies or procedures in their secondary schools. This study recommends that SSATs create guidelines or procedures in the areas where they are least confident and prepared to offer mental health management for minor student-athletes. They can use the interassociation recommendations and the NATA guidelines for mental health care to close the gap.

In order to study the synergistic effects of exogenous catalysts and in situ minerals in the reservoir during heavy oil aquathermolysis, in this paper, a series of simple supported transition metal complexes were prepared using sodium citrate, chloride salts and bentonite, and their catalytic viscosity reduction performances for heavy oil were investigated. Bentonite complex catalyst marked as B@Zn(II)L appears to be the most effective complex. B@Zn(II)L was characterized by scanning electron microscopy (SEM), Fourier-Transform Infrared (FTIR) spectroscopy, thermo-gravimetric analysis (TGA) and N2 adsorption-desorption isotherms. Under optimized conditions, the viscosity of the heavy oil was decreased by 88.3%. The reaction temperature was reduced by about 70 °C compared with the traditional reaction. The results of the group composition analysis and the elemental content of the heavy oil indicate that the resin and asphaltene content decreases, and the saturated and aromatic HC content increases. The results of TGA and DSC of the heavy oil show that the macromolecular substances in the heavy oil were cracked into small molecules with low boiling points by the reaction. GC-MS examination of water-soluble polar compounds post-reaction indicates that B@Zn(II)L can diminish the quantity of polar substances in heavy oil and lower the aromatic nature of these compounds. Thiophene and quinoline were utilized as model compounds to investigate the reaction mechanism. GC-MS analysis revealed that C-C, C-N and C-S bonds were cleaved during the reaction, leading to a decrease in the viscosity of heavy oil.

Neurodegenerative disorders (NDs) have become increasingly common during the past three decades. Approximately 15% of the total population of the world is affected by some form of NDs, resulting in physical and cognitive disability. The most common NDs include Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. Although NDs are caused by a complex interaction of genetic, environmental, and lifestyle variables, neuroinflammation is known to be associated with all NDs, often leading to permanent damage to neurons of the central nervous system. Furthermore, numerous emerging pieces of evidence have demonstrated that inflammation not only supports the progression of NDs but can also serve as an initiator. Hence, various medicines capable of preventing or reducing neuroinflammation have been investigated as ND treatments. While anti-inflammatory medicine has shown promising benefits in several preclinical models, clinical outcomes are often questionable. In this review, we discuss various NDs with their current treatment strategies, the role of neuroinflammation in the pathophysiology of NDs, and the use of anti-inflammatory agents as a potential therapeutic option.

To investigate the effects of nutrient restriction and one-carbon metabolite (OCM) supplementation (folate, vitamin B 12 , methionine, and choline) on fetal small intestine weight, vascularity, and cell proliferation, 29 ( n = 7 ± 1 per treatment) crossbred Angus beef heifers (436 ± 42 kg) were estrous synchronized and conceived by artificial insemination with female sexed semen from a single sire. Then, they were allotted randomly to one of four treatments in a 2 × 2 factorial arrangement with the main factors of nutritional plane [control (CON) vs. restricted feed intake (RES)] and OCM supplementation [without OCM (-OCM) or with OCM (+OCM)]. Heifers receiving the CON level of intake were fed to target an average daily gain of 0.45 kg/day, which would allow them to reach 80% of mature BW by calving. Heifers receiving the RES level of intake were fed to lose 0.23 kg/heifer daily, which mimics observed production responses in heifers that experience a diet and environment change during early gestation. Targeted heifer gain and OCM treatments were administered from d 0 to 63 of gestation, and then all heifers were fed a common diet targeting 0.45 kg/d gain until d 161 of gestation, when heifers were slaughtered, and fetal jejunum was collected. Gain had no effect ( p = 0.17) on the fetal small intestinal weight. However, OCM treatments ( p = 0.02) displayed less weight compared to the -OCM groups. Capillary area density was increased in fetal jejunal villi of RES - OCM ( p = 0.02). Vascular endothelial growth factor receptor 2 (VEGFR2) positivity ratio tended to be greater ( p = 0.08) in villi and was less in the crypts ( p = 0.02) of the RES + OCM group. Cell proliferation decreased ( p = 0.02) in villi and crypts of fetal jejunal tissue from heifers fed the RES + OCM treatment compared with all groups and CON - OCM, respectively. Spatial cell density increased in RES - OCM compared with CON + OCM ( p = 0.05). Combined, these data show OCM supplementation can increase expression of VEGFR2 in jejunal villi, which will promote maintenance of the microvascular beds, while at the same time decreasing small intestine weight and crypt cell proliferation.

Circulating tumor cells (CTCs) are cells released from the primary and metastatic tumor and intravasate into the blood or lymphatic vessels, where they are transported to distant sites and act as seeds that initiate cancer metastases or the development of further lesions. Recent advances in CTC research have shown their relevance as prognostic markers for early and metastatic disease detection, predictive biomarkers for relapse, and response to medical intervention or therapy. The rapidly evolving landscape of CTC biology has opened new avenues for understanding cancer progression, metastasis, and treatment response. Additionally, translating these findings into clinical applications holds promise for improving cancer diagnostics, prognosis, and personalized therapeutic strategies. This review discusses the significance of CTCs in cancer research and their associated challenges. We explore recent developments in the detection and characterization of CTCs and their implications in cancer research and clinical practice.

This research investigated the factors associated with the quantitative detection of Paratrichodorus allius in soil using droplet digital PCR (ddPCR). Small-sized nematodes exhibited significantly lower DNA quantities compared to their medium and large counterparts. Soil pre-treatments (room temperature drying and 37 °C oven-drying) demonstrated no substantial impact on ddPCR detection, and soil storage (0-3 months at 4 °C) exhibited negligible alterations in DNA quantities. A commercial DNA purification kit improved the resulting quality of ddPCR, albeit at the cost of a notable reduction in DNA quantity. Upon assessing the impact of inhibitors from soil extracts, a higher inhibitor concentration (5%) influenced ddPCR amplification efficiency. Incorporating bovine serum albumin (BSA) (0.2 μg/μL or 0.4 μg/μL) into the ddPCR setup mitigated the issue. In brief, while ddPCR exhibits minimal sensitivity to soil pre-treatments and storage, higher concentrations of PCR inhibitors and the DNA purification process can influence the results. Despite ddPCR's capability to detect nematodes of all sizes, quantification may not precisely reflect soil population. Incorporating BSA into the ddPCR setup enhances both detection and quantification capacities. This study represents the first comprehensive investigation of its kind for plant-parasitic nematodes, providing crucial insights for application of ddPCR in nematode diagnosis directly from the soil DNA.

The effect of vitamins and minerals supplementation (VTM) and/or two rates of body weight gain (GAIN) on bovine placental vascular development and angiogenic factors gene expression were evaluated in two experiments: In Exp. 1, crossbred Angus heifers ( n = 34) were assigned to VTM/NoVTM treatments at least 71 days before breeding to allow changes in the mineral status. At breeding, through artificial insemination (AI), heifers were assigned to low-gain (LG) 0.28 kg/d or moderate-gain (MG) 0.79 kg/d treatments, resulting in NoVTM-LG (Control; n = 8), NoVTM-MG ( n = 8), VTM-LG ( n = 9), and VTM-MG ( n = 9) until day 83 of gestation; In Exp. 2, crossbred angus heifers ( n = 28), were assigned to control (CON; n = 12), receiving a basal total mixed ration (TMR) or TMR + VTM (VTM; n = 16) from breeding until parturition. Placentomes from Exp. 1 and cotyledons (COT) from Exp. 2 were evaluated by immunohistochemistry for COT vascular density area. COTs from Exp. 1 were evaluated for angiogenic factor ( ANGPT -1, ANGPT -2, eNOS 2, eNOS 3, FLT 1, KDR , TEK , VEGFA ) gene expression. In Exp. 1, COT vascularity was not affected by the interaction of VTM and GAIN ( p = 0.67) or the main effects of VTM ( p = 0.50) and GAIN ( p = 0.55). Likewise, angiogenic factors were not differentially expressed between treatments ( p < 0.05). In Exp. 2, COT vascularity was greater in VTM vs. CON ( p = 0.07). In conclusion, there is a suggested later-stage influence of vitamin and mineral supplementation on placental vascularity, emphasizing the importance of supplementation beyond early pregnancy.

The aberrant glycosylation is a hallmark of cancer progression and chemoresistance. It is also an immune therapeutic target for various cancers. Tunicamycin (TM) is one of the potent nucleoside antibiotics and an inhibitor of aberrant glycosylation in various cancer cells, including breast cancer, gastric cancer, and pancreatic cancer, parallel with the inhibition of cancer cell growth and progression of tumors. Like chemotherapies such as doxorubicin (DOX), 5'fluorouracil, etoposide, and cisplatin, TM induces the unfolded protein response (UPR) by blocking aberrant glycosylation. Consequently, stress is induced in the endoplasmic reticulum (ER) that promotes apoptosis. TM can thus be considered a potent antitumor drug in various cancers and may promote chemosensitivity. However, its lack of cell-type-specific cytotoxicity impedes its anticancer efficacy. In this review, we focus on recent advances in our understanding of the benefits and pitfalls of TM therapies in various cancers, including breast, colon, and pancreatic cancers, and discuss the mechanisms identified by which TM functions. Finally, we discuss the potential use of nano-based drug delivery systems to overcome non-specific toxicity and enhance the therapeutic efficacy of TM as a targeted therapy.

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are commonly used diabetes and obesity medications but have been associated with gastrointestinal (GI) adverse events. However, real-world evidence on comparative GI adverse reaction profiles is limited., Objectives: This study aimed to evaluate GI adverse events among GLP-1 RA users and compare semaglutide, dulaglutide, liraglutide, and exenatide safety regarding the GI adverse reaction profile., Methods: This retrospective cross-sectional analysis utilized real-world data on 10,328 adults with diabetes/obesity in the National Institutes of Health All of Us cohort. New GLP-1 RA users were identified, and GI adverse events were examined. Logistic regression determined factors associated with GI adverse events., Results: The mean age of the study population was 61.4 ± 12.6 years, 65.7% were female, 51.3% were White, and they had a high comorbidity burden. Abdominal pain (57.6%) was the most common GI adverse event, followed by constipation (30.4%), diarrhea (32.7%), nausea and vomiting (23.4%), GI bleeding (15.9%), gastroparesis (5.1%), and pancreatitis (3.4%). Dulaglutide and liraglutide had higher rates of abdominal pain, constipation, diarrhea, and nausea and vomiting than semaglutide and exenatide. Liraglutide and exenatide had the highest pancreatitis (4.0% and 3.8%, respectively). Compared to semaglutide, dulaglutide and liraglutide had higher odds of abdominal pain, and nausea and vomiting. They also had higher odds of gastroparesis than semaglutide. No significant differences existed in GI bleeding or pancreatitis risks between the GLP-1 RAs., Conclusions: In this real-world cohort, GI adverse events were common with GLP-1 RAs. Differences in GI safety profiles existed between agents, with exenatide appearing safer than other GLP-1 RAs, except for gastroparesis. These findings can inform GLP-1 RA selection considering GI risk factors. Further studies are needed to evaluate the causal relationship and GLP-1 RA safety with concomitant medication use.

The widely used high-density polyethylene (HDPE) polymer has inadequate mechanical and thermal properties for structural applications. To overcome this challenge, nano zinc oxide (ZnO) and nano boron oxide (B 2 O 3 ) doped lignin-containing cellulose nanocrystals (L-CNC) were blended in the polymer matrix. The working hypothesis is that lignin will prevent CNC aggregation, and metal oxides will reduce the flammability of polymers by modifying their degradation pathways. This research prepared and incorporated safe, effective, and eco-friendly hybrid systems of nano ZnO/L-CNC and nano B 2 O 3 /L-CNC into the HDPE matrix to improve their physio-mechanical and fire-retardant properties. The composites were characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray analysis, thermo-gravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, horizontal burning test, and microcalorimetry test. The results demonstrated a substantial increase in mechanical properties and a reduction in flammability. The scanning electron microscope (SEM) images showed some agglomeration and irregular distribution of the inorganic oxides.

Background: Population-level surveillance of the prevalence and trends of basic self-care limitations will help to identify the magnitude of physical disablement in the rapidly growing older American demographic. We sought to evaluate the prevalence and trends of activities of daily living (ADL) limitations in the United States., Methods: The analytic sample included 30,418 Americans aged ≥50 years from the 2006-2018 waves of the Health and Retirement Study. ADLs were self-reported. Weighted prevalence estimates were presented, and trends analyses were performed., Results: Although overall ADL disability prevalence was 16.5% (95% confidence interval: 15.8-17.2) in 2018, there were no changes in limitations during the study period ( p = 0.52). Older adults had a greater ADL disability prevalence than middle-aged adults ( p < 0.001). While older persons experienced a declining trend of ADL limitations ( p < 0.001), middle-aged persons had an increasing trend ( p < 0.001). Males had a lower ADL limitation prevalence than females ( p < 0.001). Hispanic and non-Hispanic Black had a higher ADL disability prevalence than non-Hispanic White ( p < 0.001)., Conclusions: This investigation revealed that while the estimated prevalence of ADL limitations in the United States was substantial, changes in such limitations were not observed. Our findings can help guide ADL screening, target sub-populations with an elevated ADL limitation prevalence, and inform interventions.

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects.

iron-based coatings have exhibited good mechanical properties, such as high hardness and good wear resistance, which are desirable properties in applications such as automobile brake rotors. iron-based coatings are also good replacements for Co- and Ni-based coatings, which are costly and could have health and environmental concerns due to their toxicity. In this research, three different iron-based coatings were deposited using the Detonation Gun Spraying (DGS) technology onto aluminum substrates, including the steel powders alone (unreinforced), and steel powders mixed with Fe 3 C and SiC particles, respectively. The microstructural characteristics of these coatings and mechanical properties, such as hardness and wear resistance, were examined. The morphology and structure of the feedstock powders were affected by the exposure to high temperature during the spraying process and rapid solidification of steel powders that resulted in the formation of an amorphous structure. While it was expected that steel particles reinforced with hard ceramic particles would result in increased hardness, instead, the unreinforced steel coating had the highest hardness, possibly due to a higher degree of amorphization in the coating than the other two. The microstructural observation confirmed the formation of dense coatings with good adhesion between layers. All samples were subjected to ball-on-disk wear tests at room temperature (23 °C) and at 200 °C. Similar wear resistances of the three samples were obtained at room temperature. At 200 °C, however, both ceramic reinforced composite samples exhibited higher wear rates in line with the reduction in their hardness values. This work explains, from the microstructural point of view, why adding hard particles to steel powers may not always lead to coatings with higher hardness and better wear resistance.

The research presented in this paper is about the mechanical properties of fiber-reinforced alkali-activated slag cementitious sandwich panels with different types and amounts of admixtures. The mechanical properties, drying shrinkage properties, and micro-morphology were used to determine the optimal ratio of the admixtures. The results show that the alkali-activated slag sandwich panels have the characteristics of light weight, high strength and excellent thermal insulation, and the factors such as magnesium oxide, expansion agent and solution temperature have significant influence on their mechanical properties and dry shrinkage. This paper provides a theoretical basis and experimental data for the preparation process and application of alkali-activated slag sandwich panels.

American Aberdeen (AD) cattle in the USA descend from an Aberdeen Angus herd originally brought to the Trangie Agricultural Research Centre, New South Wales, AUS. Although put under specific selection pressure for yearling growth rate, AD remain genomically uncharacterized. The objective was to characterize the genetic diversity and structure of purebred and crossbred AD cattle relative to seven common USA beef breeds using available whole-genome SNP data. A total of 1140 animals consisting of 404 purebred ( n = 8 types) and 736 admixed individuals ( n = 10 types) was used. Genetic diversity metrics, an analysis of molecular variance, and a discriminant analysis of principal components were employed. When linkage disequilibrium was not accounted for, markers influenced basic diversity parameter estimates, especially for AD cattle. Even so, intrapopulation and interpopulation estimates separate AD cattle from other purebred types (e.g., Latter's pairwise F ST ranged from 0.1129 to 0.2209), where AD cattle were less heterozygous and had lower allelic richness than other purebred types. The admixed AD-influenced cattle were intermediate to other admixed types for similar parameters. The diversity metrics separation and differences support strong artificial selection pressures during and after AD breed development, shaping the evolution of the breed and making them genomically distinct from similar breeds.

Oil is the "blood" and economic lifeblood of modern industry, but traditional light crude oil has been over-consumed, and it has been difficult to meet human demand for energy, so the exploitation of heavy oil is particularly important. In this paper, an oil-soluble catalyst was synthesized to catalyze the pyrolysis reaction of heavy oil in collaboration with reservoir minerals, so as to achieve efficient viscosity reduction of heavy oil and reduce production costs. The experimental results showed that Zn(II)O + K had the best synergistic viscosity reduction effect after the aquathermolysis of No. 1 oil sample under the reaction conditions of 180 °C, 4 h, 30% of water, and 0.2% of catalyst, respectively, and the viscosity reduction rate was 61.74%. Under the catalysis of the isopropanol system, the viscosity reduction rate was increased to 91.22%. A series of characterizations such as freezing point, thermogravimetric analysis, DSC analysis, component analysis, gas chromatography, wax crystal morphology analysis, and GC-MS analysis of aqueous organic matter were carried out on heavy oil after reaction by different reaction systems, and it could be verified that the viscosity of heavy oil was reduced. Finally, through the study of the reaction mechanism of the model compound, combined with the aqueous phase analysis, it can be clearly found that the depolymerization between macromolecules, the breaking of heteroatom chains, hydrogenation, ring opening, and other effects mainly occur during the reaction, thereby weakening the van der Waals force and hydrogen bond of the recombinant interval, inhibiting the formation of grid structure in heavy oil and effectively reducing the viscosity of heavy oil.

Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding affinity of 169 FDs to 10 human proteins (1D6U, 1E3K, 1GOS, 1GS4, 1H82, 1OG5, 1UOM, 2F9Q, 2J0D, 3ERT) obtained from the Protein Data Bank (PDB) and showing high similarity to proteins from aquatic species. Then, the binding activity of 169 FDs to the enzyme acetylcholinesterase (AChE)-as a known target of toxins in fathead minnows and Daphnia magna , causing the inhibition of AChE-was analyzed. Finally, the structural aquatic toxicity alerts obtained from ToxAlert were used to confirm the possible mechanism of action. Machine learning and cheminformatics tools were used to analyze the data. Counter-propagation artificial neural network (CPANN) models were used to determine key binding properties of FDs to proteins associated with aquatic toxicity. Predicting the binding affinity of unknown FDs using quantitative structure-activity relationship (QSAR) models eliminates the need for complex and time-consuming calculations. The results of the study show which structural features of FDs have the greatest impact on aquatic organisms and help prioritize FDs and make manufacturing decisions.

Natural frequency is an important parameter in the structural health monitoring (SHM) system. Any changes in this parameter indicate structural alteration due to damage. This study provides a neural network (NN) solution as an alternative to the finite element (FE) method to measure the natural frequencies of a cantilever beam with random multiple damage. It is based on a statistical dataset of a free vibration test obtained from the APDL (Ansys parametric design language) simulation using a MATLAB (matrix laboratory) script. The script can generate an unlimited number of possible damage combinations for any given parameters with the help of the Monte Carlo (MC) technique. MC helps to generate a random number of damages in random locations at each simulation. Damage conditions are controlled by three parameters including damage severity and damage size (in terms of the mean and standard deviation of damage). Moreover, the method proposes a curve-fitting equation to validate the predicted natural frequency for the first three modes obtained from the neural network model. Both methods are in good agreement with each other, having minimal errors in the range of 0.2-3% for each mode. The frequency result shows that the beam frequency is 8.6486 Hz if the area reduction is 10%, whereas it comes down to 7.2338 Hz if there is a 30% area reduction. A two-level factorial test shows that damage severity is the most impactful factor compared to the damage sizes on the frequency shift event. This indicates that damage alters the composition of the beam and has an impact on its frequency change with the assumed damage parameters. Therefore, the proposed NN model can estimate the frequency shift for various damage scenarios. It can be utilized in the vibration-based damage identification process to predict the frequency changes of the damaged beam without any computational burden.

Internal corrosion is a major concern in ensuring the safety of transmission and gathering pipelines in Structural Health Monitoring (SHM). It usually requires numerous sensors deployed inside the piping system to comprehensively cover the locations with high corrosion rates. This study presents a hybrid modeling strategy using Computational Fluid Dynamics (CFD) and Genetic Algorithm (GA) to improve the sensor placement scheme for corrosion detection and monitoring. The essence of the proposed strategy harnesses the well-validated physical modeling capability of the CFD to simulate the oil-water two-phase flow and the stochastic searching ability of the GA to explore better solutions on a global level. The CFD-based corrosion rate prediction was validated through experimental results and further used to form the initial population for GA optimization. Importantly, fitness was defined by considering both sensing effectiveness and cost of sensor coverage. The hybrid modeling strategy was implemented through case studies, where three typical pipe fittings were used to demonstrate the applicability of the sensor layout design for corrosion detection in pipelines. The GA optimization results show high accuracy for sensor placement inside the pipelines. The best fitness of the U-shaped, upward-inclined, and downward-inclined pipes were 0.9415, 0.9064, and 0.9183, respectively. Upon this, the hybrid modeling strategy can provide a promising tool for the pipeline industry to design the practical placement.

Background: There have been multiple reported pharmacy initiatives to reduce opioid misuse and accidental overdose to address our nation's public health crisis. To date, there has not been a description in the literature of a community pharmacy follow-up initiative for dispensed opioids., Methods: A follow-up program was designed and implemented in community pharmacies as part of a previously developed opioid overdose and misuse prevention program (ONE Program). Five to twelve days after the dispensing of an opioid, pharmacy technicians called the patient to follow up on opioid safety topics. Pharmacy technicians used a questionnaire to inquire about medication disposal plans, if the patient was taking the medication more than prescribed, medication side effects, and if the patient needed a pharmacist consultation. The results from that questionnaire were documented., Results: During the first 18 months of the follow-up program, 1789 phone calls were completed. Of those contacted, 40% were still using their opioid medication, and over 10% were experiencing side effects which triggered a pharmacist consult. Patients were reminded of proper medication disposal methods, and most patients (78%) desired to dispose of unused medication at the pharmacy medication disposal box., Conclusions: Follow-up phone calls post-opioid medication dispensing were shown to add value to a previously established opioid misuse and accidental overdose prevention program and allowed for the fulfillment of the Pharmacist Patient Care Process.

Chitosan-based polymeric micelles are promising non-viral nanocarriers for safe and targeted gene delivery. Multi-functionalized chitosan polymeric micelles were prepared by grafting fatty acid, cell-penetrating peptide, and mannose on the chitosan backbone. The polymeric micelles were subjected to surface morphology and surface topography using scanning electron microscopy and atomic force microscopy, respectively. The hemotoxic profile of the prepared polymeric micelles was established against erythrocytes and was found to be <5% hemotoxic up to the concentration of 600 µg/mL. In vitro ApoE2 expression in primary astrocytes and neurons was analyzed. Multi-functionalized polymeric micelles produced greater ( p < 0.05) transfection in astrocytes and neurons in comparison to mono-functionalized micelles. Intranasal administration of polymeric micelles/ pApoE2 polyplex led to significantly higher ( p < 0.05) in vivo pApoE2 expression than chitosan and unfunctionalized polymeric micelles-treated mice groups. The outcomes of this study predict that the developed multi-functionalized polymeric micelles could be an effective and safe gene delivery platform to the brain through the intranasal route.

Fructan 1-exohydrolase (1-FEH) is one of the major enzymes in water-soluble carbohydrate (WSC) remobilisation for grains in wheat. We investigated the functional role of 1-FEH w1 , w2 , and w3 isoforms in WSC remobilisation under post-anthesis water deficit using mutation lines derived from the Australian wheat variety Chara. F1 seeds, developed by backcrossing the 1-FEH w1 , w2 , and w3 mutation lines with Chara, were genotyped using the Infinium 90K SNP iSelect platform to characterise the mutated region. Putative deletions were identified in FEH mutation lines encompassing the FEH genomic regions. Mapping analysis demonstrated that mutations affected significantly longer regions than the target FEH gene regions. Functional roles of the non-target genes were carried out utilising bioinformatics and confirmed that the non-target genes were unlikely to confound the effects considered to be due to the influence of 1-FEH gene functions. Glasshouse experiments revealed that the 1-FEH w3 mutation line had a slower degradation and remobilisation of fructans than the 1-FEH w2 and w1 mutation lines and Chara, which reduced grain filling and grain yield. Thus, 1-FEH w3 plays a vital role in reducing yield loss under drought. This insight into the distinct role of the 1-FEH isoforms provides new gene targets for water-deficit-tolerant wheat breeding.

The ultrasonic guided lamb wave approach is an effective non-destructive testing (NDT) method used for detecting localized mechanical damage, corrosion, and welding defects in metallic pipelines. The signal processing of guided waves is often challenging due to the complexity of the operational conditions and environment in the pipelines. Machine learning approaches in recent years, including convolutional neural networks (CNN) and long short-term memory (LSTM), have exhibited their advantages to overcome these challenges for the signal processing and data classification of complex systems, thus showing great potential for damage detection in critical oil/gas pipeline structures. In this study, a CNN-LSTM hybrid model was utilized for decoding ultrasonic guided waves for damage detection in metallic pipelines, and twenty-nine features were extracted as input to classify different types of defects in metallic pipes. The prediction capacity of the CNN-LSTM model was assessed by comparing it to those of CNN and LSTM. The results demonstrated that the CNN-LSTM hybrid model exhibited much higher accuracy, reaching 94.8%, as compared to CNN and LSTM. Interestingly, the results also revealed that predetermined features, including the time, frequency, and time-frequency domains, could significantly improve the robustness of deep learning approaches, even though deep learning approaches are often believed to include automated feature extraction, without hand-crafted steps as in shallow learning. Furthermore, the CNN-LSTM model displayed higher performance when the noise level was relatively low (e.g., SNR = 9 or higher), as compared to the other two models, but its prediction dropped gradually with the increase of the noise.

As the use of construction robots continues to increase, ensuring safety and productivity while working alongside human workers becomes crucial. To prevent collisions, robots must recognize human behavior in close proximity. However, single, or RGB-depth cameras have limitations, such as detection failure, sensor malfunction, occlusions, unconstrained lighting, and motion blur. Therefore, this study proposes a multiple-camera approach for human activity recognition during human-robot collaborative activities in construction. The proposed approach employs a particle filter, to estimate the 3D human pose by fusing 2D joint locations extracted from multiple cameras and applies long short-term memory network (LSTM) to recognize ten activities associated with human and robot collaboration tasks in construction. The study compared the performance of human activity recognition models using one, two, three, and four cameras. Results showed that using multiple cameras enhances recognition performance, providing a more accurate and reliable means of identifying and differentiating between various activities. The results of this study are expected to contribute to the advancement of human activity recognition and utilization in human-robot collaboration in construction.

Pancreatic cancer remains a disease that is very difficult to treat. S100 proteins are small calcium binding proteins with diverse intra- and extracellular functions that modulate different aspects of tumorigenesis, including tumor growth and metastasis. High mobility group box 1 (HMGB1) protein is a multifaceted protein that also actively influences the development and progression of tumors. In this study, we investigate the possible correlations, at the transcript level, between S100s and HMGB1 in pancreatic cancer. For this purpose, we calculated Pearson's correlations between the transcript levels of 13 cancer-related S100 genes and HMGB1 in a cDNA array containing 19 pancreatic cancer tumor samples, and in 8 human pancreatic cancer cell lines. Statistically significant positive correlations were found in 5.5% (5 out of 91) and 37.4% (34 of 91) of the possible S100/S100 or S100/HMGB1 pairs in cells and tumors, respectively. Our data suggest that many S100 proteins crosstalk in pancreatic tumors either with other members of the S100 family, or with HMGB1. These newly observed interdependencies may be used to further the characterization of pancreatic tumors based on S100 and HMGB1 transcription profiles.