This study was carried out to formulate and evaluate controlled release (CR) matrix tablets of Acyclovir using combination of hydrophilic and hydrophobic polymers. Acyclovir is a guanine derivative and is its half-life is short hence administered five times a day using immediate release tablets. Six formulations (F1-F6) were developed using Ethocel and Carbopol in equal combinations at drug-polymer (D:P) ratio of 10:5, 10:6, 10:7, 10:8, 10:9 and 10:10. Solubility study was performed using six different solvents. The compatibility studies were carried out using FTIR and DSC. According to USP, Quality Control and dimensional tests (hardness, friability, disintegration and thickness) were executed. In-vitro drug release studies of Acyclovir was carried out in dissolution apparatus using using 0.1 N HCl medium at constant temperature of 37 ± 0.5 ºC. In order to analyze the drug release kinetics, five different mathematical models were applied to the release data. The results showed that there was no incompatibility between drug and polymers. Physical QC tests were found within limits of USP. The release was retarded upto 24 hrs and non-fickian in-vitro drug release mechanism was found. A formulation developed using blend of polymers, showed excellent retention and desired release profiles thus providing absolute control for 24 hrs.

Introduction and Purpose: Nurses are expected to be competent in practice based on the domain of standards and interpersonal soft skills (ISS). Nurses are faced with inadequate physical assessment 28%, formulating diagnoses 56%, plans 34%, implementation 31%, evaluation 37,5%, and communication skills 41%. Aims to develop an ISS learning model based on transformative learning theory and digitalization (TLTD) to improve nurses’ competencies. Method: Used Explanatory cross-sectional involved 190 practitioner nurses. Variables of individual characters (X1), facilities (X2), Social environment support/SES (X3), TLTD (X4), ISS (X5), and nursing competencies (Y) were measured. Data was collected using a checklist questionnaire, conducted on 6 June to 10 August 2022 at Dili, Baucau, and Maliana hospitals. Used descriptive and inferential analysis with SEM-PLS. Result: Five of the 11 hypotheses of statistical p-value < 0,05 and T-Test > 1,96, including X2>X4, X3>X5, X4>X5, and X5>y, to form ISS learning model. The characteristic of respondents were 81,8% young adults, 67,9% women, 57,8% undergraduates, judging the previous training 35% was unsuccessful, and 45,8% did not meet expectations. Learning facilities that are still lacking include policies 23,7%, curriculum 23,4%, guideline 22,7%, modules 27,9%, infrastructure 20,3%, social environment support 24,2% low, organizational support, 30,0% low peer support and 26,3% low family support. The average TLTD is 25,3% to 34,2%, ISS 22,1% to 30,5%, and nurse competence 25,3% to 30,5%.Suggestion: Result of the study become base to improve nurse’s competencies. Conclusion: Learning model was formed by facilities, SES, TLTD, ISS, and nurses’ competencies.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

Knowledge of the genetic diversity of the available germplasm is an important foundation for crop conservation, management, and improvement. Successful breeding strategies rely on a sound understanding of the genetic diversity of the crop germplasm. This study was conducted to evaluate and compare the genetic diversity of 49 soybean [Glycine max (L.) Merrill] genotypes using SSR markers as well as to evaluate parental potential of these genotypes in cultivar improvement. The bulk of the genotypes were developed in the national soybean breeding program in Zimbabwe between 1940 and 2013. The genetic diversity and relatedness were estimated using 30 SSR markers and produced 5 clusters that generally matched the pedigree information of the germplasm. The SSR analysis detected a total of 135 alleles. The polymorphic information content ranged from 0.10 to 0.77 with a mean of 0.45. The SSR primer, Satt012 was the most informative. The SSR marker analysis showed a wide genetic diversity in the germplasm. To date, there are no reports regarding the genetic diversity analysis of soybean germplasm in Zimbabwe. The genotypes, EL41 and EL7; EL41 and EL1; as well as EL41 and EL42 were the most divergent thus, indicating their potential use as parental lines in the genetic improvement of soybean in the region.

Celiac disease is a chronic small intestinal immune-mediated enteropathy precipitated by exposure to dietary gluten, affecting approximately 1% of the global population and two million Americans. An increasing number of studies have identified a link between celiac disease and adverse maternal and fetal outcomes during pregnancy and after birth. Additionally, both celiac disease and pregnancy are associated with an increased risk for nutrient deficiencies, specifically vitamin B12 and folate. Deficiencies in these key nutrients are linked with several negative maternal and fetal health outcomes including preeclampsia, gestational diabetes, spontaneous abortion/miscarriage, preterm birth, NTDs, Intrauterine Growth Restriction, and low gestational age and birthweight. This review examines the current literature related to the folate trap and vitamin B12 deficiency in patients with celiac disease and pregnant women independently, and to provide rationale for future research to explore the correlation between the folate to B12 ratio in pregnant woman with celiac disease.

Diabetes mellitus, a chronic and non-transmissible disease, triggers a wide range of micro- and macrovascular complications. The differentiation of pancreatic β-like cells (PβLCs) from induced pluripotent stem cells (iPSCs) offers a promising avenue for regenerative medicine aimed at treating diabetes. Current differentiation protocols strive to emulate pancreatic embryonic development by utilizing cytokines and small molecules at specific doses to activate and inhibit distinct molecular signaling pathways, directing the differentiation of iPSCs into pancreatic β cells. Despite significant progress and improved protocols, the full spectrum of molecular signaling pathways governing pancreatic development and the physiological characteristics of the differentiated cells are not yet fully understood. Here, we report a specific combination of cofactors and small molecules that successfully differentiate iPSCs into PβLCs. Our protocol has shown to be effective, with the resulting cells exhibiting key functional properties of pancreatic β cells, including the expression of crucial molecular markers (pdx1, nkx6.1, ngn3) and the capability to secrete insulin in response to glucose. Furthermore, the addition of vitamin C and retinoic acid in the final stages of differentiation led to the overexpression of specific β cell genes.

Chenodeoxycholic acid (CA) is a naturally occurring bile acid that is produced in the liver from cholesterol. Three CA complexes using Zn(II), Mg(II), and Ca(II) ions were synthesized to examine the chelation tendencies of CA towards these metal ions. The complexation reaction of CA with the metal ions under investigation was conducted with a 1:1 molar ratio (CA to metal) at 60-70°C in natural media (pH 7-8), which consisted of a binary solvent of MeOH and H2O (1:1). The resulting CA complexes were characterized using analytical data (metal, H, C, and Cl, analysis) and spectral data (UV-visible, FT-IR, and 1H NMR) to elucidate the complexes’ structures. The results suggested that CA in anion form utilized oxygen atoms of the carboxylate group (-COO−) to capture Zn(II), Mg(II), and Ca(II) ions. This produced complexes with the general compositions of [Zn(CA)(H2O)Cl], [Mg(CA)(H2O)Cl]H2O, and [Ca(CA)(H2O)Cl]2H2O, respectively. The Kirby-Bauer disc diffusion assay was then used to explore the bioactivity of the CA complexes toward three fungal species, three Gram-positive bacteria, and two Gram-negative bacteria. The Ca(II) and Mg(II) complexes exhibited marked inhibitory effects on the cell growth of the fungal species Aspergillus niger with potency equal to 127% and 116% of the activity of the positive control, respectively. The Zn(II) and Ca(II) complexes strongly inhibited the growth of Penicillium sp., while the Zn(II) and Mg(II) complexes showed strong growth inhibition towards the Gram-negative species Pseudomonas aeruginosa.

Structure based biological and chemical properties of 4-(carboxyamino)-benzoic acid has been studied by quantum chemical methods. The revamped geometric structure and its quantum chemical parameters were obtained by DFT-B3LYP/6-311G method. Normal mode analysis is performed to assign the fundamental vibrational frequencies as per the potential energy distribution (PED) by using the VEDA program. Simulation of IR and Raman spectral patterns are observed by refinement of scale factors. TD-DFT approach is used to explore the excited states of molecule and prediction of electronic absorption spectra. NMR chemical shifts of the molecule are determined by the gauge independent atomic orbital method. The molecular docking is performed to recognize the binding energy of the ligand with the dynamic site of protein. In our docking analysis, the protein 5DT6 shows the best results than other three proteins which could be used for further analysis. Further inter and intra molecular interactions, electrophilic, nucleophilic and chemical reactivity sites are found by molecular electrostatic potential, HOMO-LUMO and Global chemical reactivity descriptors. Thermodynamic property of the title compound is also reported. The determined quantum chemical parameters show high reactivity and the dipole moment was sufficiently high enough to induce nonlinear characteristics which are required for applications in optoelectronic devices.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the largest nut crops in the world. Recently, phenolic compounds, mostly stored in almond skin, have been associated with much of the health-promoting behavior associated with their intake. The almond skin enriched fraction obtained from cold-pressed oil residues of the endemic Moroccan Beldi ecotypes is particularly rich in chlorogenic acid. In this study, both almond skin extract (AE) and chlorogenic acid (CHL) supplements, similar to traditional positive control resveratrol, significantly increased the replicative life-span of yeast compared to the untreated group. Our results showed that AE and CHL significantly reduced the production of reactive oxygen and nitrogen species (ROS/RNS), most likely due to their ability to maintain mitochondrial function during aging, as indicated by the maintenance of normal mitochondrial membrane potential in treated groups. This may be associated with the observed activation of the anti-oxidative stress response in treated yeast, which results in activation at both gene expression and enzymatic activity levels for SOD2 and SIR2, the latter being an upstream inducer of SOD2 expression. Interestingly, the differential gene expression induction of mitochondrial SOD2 gene at the expense of the cytosolic SOD1 gene confirms the key role of mitochondrial function in this regulation. Furthermore, AE and CHL have contributed to the survival of yeast under UV-C-induced oxidative stress, by reducing the development of ROS / RNS, resulting in a significant reduction in cellular oxidative damage as evidenced by decreased membrane lipid peroxidation, protein carbonyl content and 8-oxo-guanine formation in DNA. Together, these results demonstrate the interest of AE and CHL as new regulators in the replicative life-span and control of the oxidative stress response of yeast.

We performed a systematic review and meta-analysis to evaluate the role of gastric acid suppressant use on outcomes of tyrosine kinase inhibitors (TKIs) and oral chemotherapy. We identified all researches evaluating the effect of GAS use on patients receiving oral chemotherapy or TKIs for solid tumors. The pooled hazard ratios (HRs) and 95% confidence interval (95% CI) for overall survival (OS) and progression-free survival (PFS) were calculated with fixed-effects or random-effects model. The study population included n=16 retrospective studies and 372,418 patients. Series concerned gastrointestinal tract tumors (n=5 studies), renal cell carcinomas (RCC, n=3 studies), non-small cell lung cancers (NSCLC, n=5 studies), and soft tissue sarcomas or mixed histologies solid tumors in n=3 studies. The pooled HRs for OS and PFS were 1.31 (95% CI: 1.20–1.43; P<01) and 1.3 (95%CI 1.07-1.57; P<0.01) for GAS and no GAS users, respectively. Only studies of EGFR mutated NSCLC patients receiving TKIs and those with colorectal cancer receiving oral chemotherapy showed a significant correlation between GAS and poor survival. Our study supports the evidence of a possible negative impact of concomitant GAS therapy on survival outcomes of patients receiving oral anti-cancer drugs.

Marula seed cake (MSC) is a nutritionally-rich natural feed resource that can enhance the healthiness of animal-derived foods (ADFs) for human consumption. This study compared the health-related fatty acid (FA) profiles of MSC products from South Africa and Eswatini. Composite samples monthly collected from both countries were analysed for FAs. MSC products from both countries were found to be dominated by oleic acid (>70%), followed by palmitic, linoleic and stearic acids. Consequently, both products had their FA totals dominated by ƩMUFA followed by ƩSFA, ƩPUFA, Ʃn-6 PUFA and Ʃn-3 PUFA. Both oleic and stearic acids were higher (P < 0.01) whilst linoleic (P < 0.001), α-linolenic (P < 0.05), margaric (P < 0.05), palmitoleic (P < 0.05) and eicosatrienoic (P < 0.05) acids were lower in South African in comparison to Eswatini MSC. Consequently, South African MSC had higher ƩMUFA (P < 0.01) but lower ƩPUFA (P < 0.001), Ʃn-6 PUFA (P < 0.001) and Ʃn-3 PUFA (P < 0.05). Also, Eswatini MSC had higher n-6 : n-3 PUFA, PUFA : SFA (P = 0.001) and PUFA : MUFA (P < 0.05) ratios. Further, MSC products from both countries had similarly (P > 0.05) low atherogenicity and high desaturase indices. In conclusion, both country products are rich particularly in oleic acid and their incorporation into farm animal diets would increase content of the MUFA in ADFs and, consequently, improve health benefits to human consumers.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

This study delves into the intricate interplay of economic growth components, specifically focusing on Consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and cointegration techniques, we analyze the short- and long-term dynamics within the relationship of Consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables' causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight Consumption and investment's statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%.Moreover, the Granger causality study demonstrates unidirectional causal linkages between Consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private Consumption and fostering other facets of economic growth.

The growing shift toward Internet of Things (IoT)-based solutions expands the attack surface of systems by connecting an extensive network of heterogeneous devices and technologies. The heterogeneity of IoT devices and the scale of the network often make conventional security measures impractical. Therefore, recent research efforts have focused on machine learning (ML)-based device-agnostic IoT security solutions. However, most proposed solutions have focused solely on detecting malicious traffic in IoT networks. While this is important, further information about the attack is needed to provide a comprehensive defense before, during, and after the incident. To address this gap, we proposed an anomaly-based intrusion detection model that detects malicious traffic and identifies the attack category and subcategory with high accuracy, recall, precision, and F1-score. The proposed intrusion detection model is an ensemble model that integrates multiple ML models to produce more robust and reliable detections. For evaluation, we performed three sets of experiments: (1) a binary classification to detect malicious traffic; (2) a multi-class classification to detect the attack category; and (3) a multi-class classification to detect the attack subcategory. In the experiments, our model achieved an accuracy, recall, precision, and F1-score of 100% for the binary detection; a precision, recall, and F1-score of 99% and an accuracy of 100% for the multi-class category classification; and an accuracy, recall, precision, and F1-score of 88% for the multi-class subcategory classification. These results suggest that the proposed model can reliably detect anomalies in IoT devices.

Understanding the interrelationships between land use, climate change, and regional water yield is critical for effective water resource management and ecosystem protection. However, comprehensive insights into how water yield evolves under different land use scenarios and climate change remain elusive. This study employs the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models, Patch-generating Land Use Simulation (PLUS) model, and Geodetector within a unified framework to evaluate the dynamics of land use, water yield, and their relationships with various factors (meteorological, social, economic, etc.). To forecast the Land Use/Cover Change (LUCC) pattern of the Yellow River Basin by 2030, three scenarios were considered: economic development priority (Scenario1), ecological development priority(Scenario2), and cropland development priority(Scenario3). Climate change scenarios were constructed using CMIP6 data, representing low stress (SSP119), medium stress (SSP245), and high stress (SSP585) conditions. The results show the following: (1) From 2000 to 2020, cropland was predominant in the Yellow River Basin, Henan Province, with significant land conversion to impervious land (construction land) and forest land; (2) Water yield changes during this period were primarily influenced by meteorological factors, with land use changes having negligible impact; (3) By 2030, the water yield of Scenario1 is highest among different land use scenarios, marginally surpassing ecological development priority by 0.5%; (4) Climate scenarios reveal significant disparities, with SSP126 yielding 67% higher water production than SSP245, driven predominantly by precipitation; (5) Geodetector analysis identifies precipitation as the most influential single factor, with significant interactions among meteorological and socio-economic factors. These findings offer valuable insights for policymakers and researchers in formulating land use and water resource management strategies.

In order to achieve the dual carbon goal and simplify the decarbonization process, a CO2 recovery process of the fire-flooding exhaust was designed. The process adopted the two-stage membrane separation method to recover CO2 and obtain high purity CO2 rich flow, and then through the mixed refrigerant liquefaction and rectification column, food grade liquid CO2 was obtained. HYSYS process simulation shows that for the fire-flooding exhaust with a flow rate of 1000 kg/h and a given composition, the process can achieve a CO2 recovery of 69.02%, total product sales S=2086.8 yuan/h, and specific power consumption of 2.818 kW∙h/kg. On this basis, a hybrid simulation platform of HYSYS & Matlab was established. Taking the specific power consumption of the product as the objective function, sequential quadratic programming (SQP) algorithm was adopted to optimize the process, and the optimized specific power consumption was reduced by 18.8%. Finally, by adjusting N2/CO2 components, the adaptability of the optimization condition was analyzed.

Background: Despite the tremendous effort in hamstring injury prevention, injury rates in soccer remain elevated. Hypothesis: Hamstring and hip/pelvic isometric strength imbalances may increase the likelihood of hamstring strain injury (HSI) occurrence amongst soccer players.Study design: Case-control study.Methods: In 120 male soccer players (mean age: 20.0 +/- 6.96 years) pre-season maximum isometric strength of the hip adductors, abductors, flexors, and knee flexors were measured, and strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. A multivariate and Machine learning-based Logistic Regression model was employed to estimate the likelihood of players sustaining a hamstring injury.Results: 21 players sustained 32 hamstring injuries. Players with higher abduction strength in the dominant leg had an 18.5% lower risk of sustaining a hamstring injury (OR = 0.818, CI 95% = [(0.695-0.964]). No other significant contributor variables were found to be significant predictors of hamstring injury in the player group (p> 0.05).Conclusion: Isometric strength of the abductor muscles in the dominant limb had a significant association with hamstring injury.Clinical relevance: Our findings indicate the utilization of hip strength measurements as an integral component of the pre-season screening assessment, thereby affirming prior research on the correlation between lumbo-pelvic stability and incidence of hamstring injuries. Consequently, clinicians should contemplate incorporating hip strengthening exercises into regular training sessions, rehabilitation programs, and injury prevention protocols especially indicated when lower hip strength levels are observed.

The ever-increasing demand for seafood-containing diets, especially fish, primarily due to their superior nutritional value, has impacted the availability of wild stocks, necessitating the focus on other underutilised aquaculture species. In this study, the proximate and fatty acid (FA) composition of the indigenous black South African mussel (Choromytilus meridionalis) was investigated. The effects of the hot-smoking as preservation method on the proximate composition for mussels were assessed using the standard AOAC protocols; while gas chromatography-flame ionised detection (GC-FID) was used to determine the FA content. The moisture level in hot-smoked mussels significantly (P

The reaction between 5-acetylbarbituric acid and 4-dimethylthiosemicarbazide or 4-hexamethyleneiminyl thiosemicarbazide produces 5-acetylbarbituric-4-dimethylthiosemicarbazone (H2AcbDM) and 5-acetylbarbituric-4N-hexamethyleneiminyl thiosemicarbazone (H2Acbhexim). Eight new complexes with different cooper (II) salts have been prepared and characterized using elemental analysis, molar conductance, UV–vis, ESI-HRMS, FT-IR, magnetic moment, EPR and cyclic voltammetry. In addition, three-dimensional molecular structures of [Cu(HAcbDM)(H2O)2](NO3)·H2O (3a), [Cu(HAcbDM)(H2O)2]ClO4 (4), and [Cu(HAcbHexim)Cl] (6) were determined by single crystal X-ray crystallography, and was carried out an analysis of their supramolecular structure. The H-bonded assemblies were further studied energetically using DFT calculations, MEP surface and QTAIM analyses. In these complexes, the thiosemicarbazone coordinates to the metal ion in an ONS-tridentate manner, in the O-enolate/S-thione form. The electrochemical behavior of the thiosemicarbazones and their copper(II) complexes has been investigated at room temperature using the cyclic voltammetry technique in DMFA. The Cu(II)/Cu(I) redox system was found to be consistent with the quasi-reversible diffusion-controlled process.

Alcohol abuse can lead to alcoholic liver disease, becoming a major global burden. Hovenia dulcis fruit peduncle polysaccharides (HDPs) has the potential to alleviate alcoholic liver injury may play essential roles in treating for alcohol-exposed liver disease, however, the hepatoprotective effects and mechanisms remain unclear. In this study, the hepatoprotective effects of HDPs and its potential mechanisms were investigated in alcohol-exposed mice by liver metabolomics and gut microbiome. The results found that HDPs reduced medium-dose alcohol-caused dyslipidemia (significantly elevated T-CHO, TG, LDL-C), elevated liver glycogen levels and inhibited intestinal-hepatic inflammation (significantly decreased IL-4, IFN-γ and TNF-α), consequently reversing hepatic pathological changes. By applying gut microbiome analysis, HDPs showed significant decreases in Proteobacteria while significant increases in Firmicutes at the phylum level, and increased Lactobacillus abundance while decreased Enterobacteria abundance, maintaining the composition of gut microbiota. Further hepatic metabolomics analysis revealed that HDPs had a regulatory effect on hepatic fatty acid metabolism, by increasing the major metabolic pathways including arachidonic acid metabolism and glycerophospholipid metabolism and identified two important metabolites C00157 and C04230 involved in the above metabolism. Overall, HDPs reduced intestinal dysbiosis and hepatic fatty acid metabolism disorders in alcohol-exposed mice, suggesting that HDPs has a beneficial effect on alleviating alcohol-induced hepatic metabolic disorders.

APC mutation is the main driver mechanism of CRC development and leads to constitutively activated WNT signaling, overpopulation of ALDH+ stem cells (SCs), and incomplete differentiation. We previously reported that retinoic acid (RA) receptors are selectively expressed in ALDH+ SCs, which provides a way to target cancer SCs with retinoids to induce differentiation. Hypotheses: A functional link exists between WNT and RA pathways, and APC mutation generates a WNT:RA imbalance that decreases retinoid-induced differentiation and increases ALDH+ SCs. Accordingly, to restore parity in WNT:RA signaling, we induced wt-APC expression in APC-mutant CRC cells and assessed the ability of all-trans-retinoic acid (ATRA) to induce differentiation. Notably, ATRA substantially increased expression of the WNT-target gene, CYP26A1, and inducing wt-APC reduced this expression by 50%. Thus, RA and WNT pathways crosstalk to modulate CYP26A1 metabolism of retinoids. We found that inducing wt-APC augments ATRA-induced cell differentiation by: i) decreasing cell proliferation; ii) suppressing ALDH1A1 expression; iii) decreasing ALDH+ SCs; iv) increasing neuroendocrine cell differentiation. Furthermore, NanoString profiling/bioinformatics identified a novel CYP26A1-based network that links WNT and RA signaling. Moreover, CYP26A1 inhibitors sensitized CRC cells to the anti-proliferative effect of drugs that downregulate WNT signaling. Notably. in wt-APC-CRCs, decreased CYP26A1 improves patient survival. These findings have strong potential for clinical translation.

Research conducted on individuals with depression reveals that major depressive disorders (MDDs) coincide with diminished levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the brain, as well as modifications in the subunit composition of the primary receptors (GABAA receptors) responsible for mediating GABAergic inhibition. Furthermore, there is substantial evidence supporting the significant role of GABA in regulating stress within the brain, which is a pivotal vulnerability factor in mood disorders. Although there is substantial evidence indicating that GABA may be affecting GABA receptors in peripheral tissues, there is comparatively less evidence supporting its direct action within the brain. Emerging evidence highlights that GABA may exert beneficial effects on the brain and psyche through the gut-brain axis. GABA is readily available and approved as a food supplement in many countries. While GABA enjoys wide consumer acceptance in Eastern Asian markets, with many consumers reporting favorable effects on stress regulation, mood, and sleep, rigorous independent research is still largely lacking. Basic research, coupled with initial clinical findings, makes GABA an intriguing neuro-nutritional compound deserving of clinical studies in individuals with depression and other psychological problems.

Zinc, being a part of many proteins and enzymes, plays an important role in the vital processes of the body. Racemic α-lipoic acid (LA) has a wide range of biological activities: antioxidant, antidiabetic, anticancer, and it is also used in diseases such as Parkinson's and Alzheimer's. Nowadays, the synthesis and structural studies of new zinc complexes with biologically active compounds are of great importance for drug discovery. This work shows the studies carried out on the synthesis, structure, identification, also biological activity using in silico methods of a complex compound based on LA and zinc. A complex compound of zinc with LA (ZnLA) was synthesized in the presence of LA and zinc acetate in ethanol. The identification of ZnLA by (FT-IR, XRD and TGA-DTA), also DFT calculations at the B3LYP/def2-TZVPP level of theory was performed. The molecular docking investigation involved docking ZnLA with two different protein receptors such us Glycogen phosphorylase (2GPA) and Kv potassium channel beta subunit (1ZSX) using CB-Dock 2 server and Auto-Dock Vina program to determine the mechanism of action and biological activity. This study reveals potential ligand-protein interactions at the atomic level and suggests that the treatment of diabetes (non-insulin dependent) with ZnLA.

Age-related macular degeneration, a leading cause of visual loss and dysfunction in the devel-oped world, is a disease initiated by genetic polymorphisms that impairs negative regulation of complement. Proteomic investigation points to altered glycosylation and loss of SIGLEC medi-ated glyco-immune checkpoint parainflammatory homeostasis as a main determinant for the vi-sion impairing complications of macular degeneration. The effect of altered glycosylation on microglial maintained retinal para-inflammatory homeostasis and eventual recruitment and polarization of peripheral blood monocyte derived macrophages (PBMDM) into the retina can explain the phenotypic variability seen in this clinically heterogenous disease. Restoring gly-co-immune checkpoint control with a sialic acid mimetic nanoparticle targeting microgli-al/macrophage SIGLECs to regain retinal para inflammatory homeostasis is a promising thera-peutic that could halt the progression of and improve visual function in all stages of macular de-generation.

Saussurea neoserrata Nakai offers a reliable and efficient source of antioxidants that can help alleviate adverse skin reactions triggered by air pollutants. Air pollutants, such as particulate matter (PM), have the ability to infiltrate the skin and contribute to the higher occurrence of cardiovascular, cerebrovascular, and respiratory ailments. Individuals with compromised skin barriers are particularly susceptible to the impact of PM since it can be absorbed more readily through the skin. This study investigated the impact of protocatechuic acid and syringin, obtained from the n-BuOH extract of S. neoserrata Nakai, on the release of PGE₂ and PGD₂ induced by PM₁₀. Additionally, it examined the gene expression of enzymes involved in the synthesis of PGE₂ and PGD₂ in human keratinocytes. The findings of this research highlight the potential of utilizing safe and efficient plant-derived antioxidants in dermatological and cosmetic applications to mitigate the negative skin reactions caused by exposure to air pollution.

Due to its high specific surface area and rich porous structure, acacia-derived porous activated carbon is the most potentially effective material for wastewater treatment. This research study aimed to prepare activated carbon using Acacia erioloba seedpods as carbonaceous materials and phosphoric acid as an activating agent. The specific surface area of the prepared activated carbon sample was characterised by Brunauer–Emmett–Teller instrument. The specific surface area value was 387 m²/g. The activated carbon prepared was then sieved into three different particle sizes of 50, 100 and 200 micrometres and characterised using various analytical procedures, including proximate analysis to study moisture content, ash content, volatile matter content and fixed carbon content. The bulk density, SEM, power of hydrogen, iodine number and methylene blue number index were also investigated to determine the adsorption properties of the prepared activated carbon. Batch adsorption dynamics for the removal of organic compounds such as methylene blue and unsaturated character of fatty acid from aqueous solution were also carried out at room temperature to evaluate the prepared activated carbon's applicability in water treatment. The iodine number was 528, 638, and 554 mg/g for the 50, 100, and 200 μm activated carbon particles, respectively. From the results, the adsorption of methylene blue favoured the Freundlich adsorption model, showing higher correlation (R²) values than the Langmuir model. The results indicate that methylene blue particles were adsorbed on heterogeneous surfaces.

One of the most interesting groups of fatty acid derivates is the group of conjugated fatty acids, from which the most researched are conjugated linoleic acid (CLA) and conjugated linolenic acid (CLNA), which are associated with countless health benefits. Sex pheromone mixture of some insect species, including tobacco horn-worm (Manduca sexta), are typical for the production of uncommon C16 long conjugated fatty acids with two and three conjugated double bonds, as opposed to C18 long CLA and CLNA. In this study, M. sexta desaturases MsexD2 and MsexD3 were expressed in multiple strains of Y. lipolytica with different genotypes. Experiments with supplementation of fatty acid methyl esters into the medium resulted in production of novel fatty acids. Using GCxGC-MS 20 new fatty acids with two or three double bonds were identified. Fatty acids with conjugated or isolated double bonds or combination of both were produced in trace amounts. Results of this study prove that Y. lipolytica is capable of synthesizing C16 conjugated fatty acids. Further genetic optimization of the Y. lipolytica genome and optimization of the fermentation process could lead to increased production of novel fatty acid derivatives with biotechnologically interesting properties.

Arjunolic acid (AA) is a triterpenoid saponin majorly found in the Terminalia arjuna and is claimed to exert the cardiovascular protective effects as a phytomedicine. However, it is unclear how AA exerts the effects at the molecular level. Hence, this study used an in vitro model using lipopolysaccharide (LPS)-stimulated H9C2 and C2C12 myotubes to investigate the cardioprotective effects of arjunolic acid (AA) via MyD88-dependant TLR4 downstream signaling markers expression. The myotubes were developed by differentiating rat H9C2 and mouse C2C12 myoblast cells. The MTT viability assay was used to assess the cytotoxicity of AA. LPS induced in vitro cardiovascular disease model was developed in H9C2 and C2C12 myotubes. The treatment groups were designed such as control (untreated), LPS control, positive control (LPS+ pyrrolidine dithiocarbamate (PDTC)-25 µM), and treatment groups were co-treated with LPS and three doses of AA (50, 75, and 100 µM). The changes in the expression of TLR4 downstream signaling markers were evaluated through High Content Screening (HCS) and Western Blot (WB) analysis. The outcomes demonstrated that the expression of MyD88, MAPK, JNK, and NFκB markers were significantly upregulated in the LPS-treated groups compared to the untreated control. Evidently, the HCS analysis revealed that MyD88, NF-κB, p38, and JNK were significantly downregulated in the H9C2 myotube in the AA treated groups (50, 75, and 100 µM). For, the C2C12 myotube, the expression of NFκB was downregulated. TLR4 marker expression in H9C2 and C2C12 myotubes was subsequently decreased by AA treatment, suggesting possible cardioprotective effects of AA.

Modern technologies for recycling electronic waste (e-waste) impose high economic efficiency and environmental safety requirements. Among existing technologies, hydrometallurgy is considered the most promising technology for e-waste recycling. Increasing attention to the chlorination method is associated with the complex recycling of low-grade ores containing noble metals and secondary polymetallic raw materials. In this paper, we propose a new scheme for leaching metals from computer printed circuits (PCBs) pre-crushed in a disintegrator: the processes of chlorine production and hydrochlorination are implemented in one reactor under the action of alternating current (AC) of industrial frequency (50 Hz). It was found that complete leaching of gold is achieved from fine fractions of raw materials containing 0.03% and 0.01% of the gold at an experiment duration of 2 hours, a current density of 0.66 A·cm-2, and a solid/liquid ratio of 8.6 g·L-1. Under the same conditions of the electrochemical leaching process from the fraction of raw material with a gold content of 0.08%, the degree of metal leaching is 80.5%. At the same time, with an increase in the copper content in the raw material from 1.40% to 6.13%, an increase in the degree of its leaching from 84.6% to 95.2%, respectively, is observed. These results will serve as a foundation for developing a complex technology for recovering valuable metals from PCBs.

This study focused on the characterization of lactic acid bacteria (LAB) in a renowned traditional Italian cheese, Pecorino di Farindola, to select an autochthonous culture and investigate its po-tential for the improvement of safety and functional properties. Two hundred and six LAB isolated throughout production and maturation from nine cheese lots of three farms were identified by 16S rRNA gene sequencing and tested for the presence of genes encoding virulence factors, vancomycin resistance (for enterococci), biogenic amines (BAs) and bacteriocin production, for antimicrobial activity, and for the capacity to survive in the gastro-intestinal tract (GIT) based on tolerance to low pH and bile salts and adhesion to CaCo-2 cells. A Lacticaseibacillus paracasei isolate was used in cheese making and determined a decline of spiked Listeria monocytogenes and Escherichia coli O157 faster than in control cheese. The autochthonous bacterial groups were numerically unaffected, apart from lactobacilli that were recovered in higher numbers in the cheese with added L. paracasei. Based on Repetitive Extragenic Palyndrome (Rep) PCR profiles, the added strain possibly dominated until day 88 in cheese. Results encourage further trials with autochthonous cultures to efficiently inhibit hazardous bacteria and enrich a functional microbiota in Pecorino di Farindola and similar cheeses.

The experiments were designed to know the function of ascorbic acid against salinity on germination, different biochemical and micronutrients concentrations of Solanum melongena. Ascorbic acid was applied as foliar spray on leaves and given in roots through irrigation at 100 and 200 ppm to the plants growed in non saline, 60mM and 100mM salt stress conditions. Different biochemical parameters i.e. chlorophyll, carotenoids, carbohydratrates, protein and micro nutrients concentrations of Solanum melongena were observed under different salt stress concentrations from control (non-saline), 60mM NaCl and 100mM NaCl solutions. The rates of different biochemical parameters and micro nutrients concentrations exhibited decrease in saline media in comparison with their respective control while ascorbic acid used as a foliar spray and through irrigation in roots at the concentration of 100 ppm and 200 ppm resulted promotion in non saline control as compared with salt concentrations media. It was determined that chlorophyll concentration was decreased considerably under salt stress. Amongst micro nutrients ionic composition of Na, K and Na/K ratio resulted that plants treated with different NaCl concentrations at 60mM NaCl and 100mM salt concentrations showed increase in Na and K ions and ascorbic acid were used as a foliar spray and in roots showed decrease in Na and K ions. Overall from the outcomes of the study it was observed that salinity stress significantly decrease vegetative and reproductive parameters that could be improved with the using of ascorbic acid. Best concentration found were 200 ppm ascorbic acid contributed towards an increase in growth irrespective of non-saline and saline conditions. Based on these findings, ascorbic acid treatment helps in alleviating the negative effects of salinity.

The aim of this study was to investigate the effect of condensed tannin (CTs) with differing molecular weight on their capacity to modify the fatty acid profile in milk. Twenty multiparous crossbred lactating dairy goats were assigned in a randomized complete block design (RCBD), and were subjected to receive the dietary treatments as followings; T1: control (with no CTs supplementation), T2: supplemented with mangosteen peel in a concentrate as a source of low molecular weight CTs at level of 3.0 %DM of CTs equivalent, T3: supplemented with the same diet with T2 but added with polyethylene glycol (PEG, as tannin inactivator) as the control of T2, and T4: supplemented with quebracho CT extract (UNITAN ATO, Buenos Aires, Argentina; 75-77 % tannins) in a concentrate as a source of high molecular weight CTs at level of 3.0 %DM of CTs equivalent, and T5) supplemented with the same diet with T4 but added with PEG as the control of T4. No significant change was detected for feed intake and nutrient digestibility indicate that CTs at level of 3.0 %DM of diet did not showed the detrimental effect to feed intake and nutrient digestibility, however, ruminal fermentation parameters and milk yield and milk compositions did not affected by different source of CT inclusion.

This study was aimed at investigating the protective effects of glass ionomer cement (GIC) and surface pre-reacted glass ionomer (S-PRG) fillers used as dental restorative materials on demineralization of bovine enamel. GlasIonomer FX ULTRA (FXU), Fuji IX GP Extra (FIXE), CAREDYNE RESTORE (CDR) were used as GICs. PRG Barrier Coat (BC) was used as the S-PRG filler. They were incubated in a lactic acid solution (pH = 4.0) for 6 d at a temperature of 37 °C. The mineral was etched from the enamel surface, and a large number of Ca and P ions were detected in solution. The Al, F, Na, Sr, and Sr ions were released in GICs and S-RPG fillers. The Zn ion was released only in CDR and the B ion was released only in BC. The presence of apparent enamel prism peripheries was observed after 6 d of treatment for the group containing only enamel blocks. pH values for the FXU, FIXE, CDR, BC, and enamel block groups after 6 d were 6.5, 6.6, 6.7, 5.9, and 5.1, respectively. Therefore, the observed pH neutralization effect suppressed progression of caries due to the release of several ions from the restoratives.

Background and objectives: This study were designed to determine uric acid concentration and renal histopathology of M. calabura L. stem bark extract in diabetic rats and to compare the natural product of M. calabura L. stem bark extract with allopurinol. Materials and Methods: A completely randomized design was used for the experiment which consisted of 6 treatment groups, each consisting of 4 rats, as follows: 1) NR, normal rat; 2) KN, diabetic rat (negative control); 3) KP, diabetic rats given allopurinol 10 mg/kg body weight; 4) EM150, diabetic rats given the test extract 150 mg/kg body weight/day; 5) EM300, diabetic rats given the test extract 300 mg/kg body weight/day; and 6) EM450, diabetic rats given the test extract 450 mg/kg body weight/ day. Results: The results showed that M. calabura L. stem bark extract decrease (p<0.05) uric acid levels in diabetic rats and no specific damage to renal proximal tubular cells was seen. Conclusions: It was concluded that M. calabura L. stem bark extract has a potential as an antihyperuricemic in diabetic rats. The recommended does was 300 mg/kg body weight to provide a significant effect on reducing the uric acid level in diabetic rats. Our findings support the use of this plant as a treatment for gout and other inflammatory diseases.

Our study aims to implement a strategy to reduce the carbon steel corrosion rate in sulfuric acid solution, using an expired drug with adsorption affinity on the metal surface. To investigate the corrosion protection efficiency of an environmental friendly inhibitor, namely neomycin sulfate (NMS), the electrochemical measurements were applied on carbon steel immersed in 1.0 M H₂SO₄ solution with and without NMS. The protective layer formed on the steel surface was studied by atomic force microscopy (AFM). The potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) showed that the presence of the neomycin sulfate in acid solution leads to the decrease in corrosion current density (i_corr) and the increase of polarization resistance (R_p). The mixed mechanism between physical and chemical adsorption of NMS molecules on the steel surface was proposed according to the Langmuir adsorption isotherm. The Atomic Force Microscopy (AFM) indicated that the NMS molecules contributed to a protective layer formation by their adsorption on the steel surface. The AFM parameters such as: root-mean-square roughness (R_q); average roughness (R_a) and maximum peak to valley height (R_p-v) revealed that in the presence of NMS a smoother surface of carbon steel was obtained, compared to the steel surface corroded in sulfuric acid blank solution.

Background: Previously, our laboratory has provided evidence that pre-administration of the antioxidant, lipoic acid covalently bonded to various naturally occurring antioxidants, enhanced neuroprotective capacity compared to the administration of lipoic acid on its own. The naturally occurring compound scopoletin, a coumarin derivative, has been shown in various in vitro studies to have both antioxidant and anti-inflammatory mechanism of actions. To date, the effect of scopoletin on neuronal cell death in an in vivo model of ischemia or ischemia-reperfusion has not been investigated. Therefore, the present investigation was designed to determine if scopoletin on its own, or a co-drug consisting of lipoic acid and scopoletin covalent bond, named UPEI-400, would be capable of demonstrating a similar neuroprotective efficacy. Methods: Using a rodent model of stroke in male rats (anesthetized with Inactin®; 100 mg/kg, iv), the middle cerebral artery was permanently occluded for 6 hours (pMCAO), or in separate animals, occluded for 30 min followed by 5.5 hrs of reperfusion (ischemia/reperfusion; I/R). Results: Pre-administration of either scopoletin or UPEI-400 significantly decreased infarct volume in the I/R model (p<0.05), but not in the pMCAO model of stroke. However, UPEI-400 was ~1000 times more potent as compared to scopoletin on its own. The optimal dose of UPEI-400 was then injected during the occlusion and at several time points during reperfusion and significant neuroprotection was observed for up to 150 mins following the start of reperfusion (p<0.05). Conclusion: The data suggest that synthetic combination of scopoletin with lipoic acid (UPEI-400) is a more effective neuroprotectant that either compound on their own. Also, since UPEI-400 was only effective in a model of I/R, it is possible that it may act to enhance neuronal antioxidant capacity and/or upregulate anti-inflammatory pathways to prevent the neuronal cell death.

In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, the operating boundaries for both Depth of Discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.

Nowadays, unmanned vehicles are widely used in various fields. However, the safety of unmanned vehicles is directly determined by the autopilot systems, and sensor faults are a very critical factor that affects the normal operation of the autopilot systems. To efficiently and comprehensively test unmanned systems for sensor faults, this paper proposes a chip-level testing platform for unmanned vehicle autopilot systems based on FPGA hardware-in-the-loop simulation. Unlike existing testing platforms, the introduction of FPGA technology allows us to achieve nanosecond real-time simulation frequency, thus realizing chip-level simulation of sensors and black-box automated testing. Firstly, we propose a set of general platform and modeling methods, and the paper presents a detailed application of the four most common necessary sensors in autopilot systems as examples. Secondly, we propose for the first time a chip-level fault testing method for unmanned systems, and build a test platform with a quadrotor vehicle, the PX4 software platform, and the Pixhawk4 hardware platform as examples. Finally, the experimental results verify that the testing platform proposed in this paper can adapt to various autopilot systems and has high simulation test reliability.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Approximately 20% of the world's population resides in coastal areas at risk of rising sea levels due to climate change. This could lead to severe weather events and ecological impact on critical infrastructure. To combat the effects of water-based environmental forces on the land, hard engineering methods such as seawalls have been utilized. However, a more sustainable solution is emerging in nature-based engineering, which involves growing vegetation. This approach can help extend the lifespan of existing technology and provide climate change adaptation and resilience for coastal and riverine communities. The following paper will review seaweed farms as an advanced nature-based mitigation approach. The paper also outlines the findings of experiments at RWTH Aachen University's hydraulic laboratory. These tests involved using seaweed as a natural solution to dampen waves in a model system to test a hypothesis. One result involving a system with two lines of seaweed revealed 15 percent wave damping. Using seaweed as a nature-based solution, a gentle engineering approach to designing future vegetated protection systems can extend the design life of existing coastal infrastructure. This can also provide protection against climate-induced sea level rise, promote coastal risk mitigation, restore ecosystems, and foster blue bio-economic development.

This paper investigates generalized Bayesian (GB) inference in the context of a one-parameter Pareto distribution. The study focuses on the derivation of generalized Bayesian estimators (GBE) and generalized empirical Bayesian estimators (GEBE) for the parameters of the Pareto distribution using type II censored data. In addition, the study investigates a one-sample prediction approach to examine generalized Bayesian prediction (GBP) and generalized empirical Bayesian prediction (GEBP). To evaluate the performance of these estimation and prediction methods, Monte Carlo simulations were performed comparing GBE with GEBE and GBP with GEBP for different parameter values and learning rate parameters (LRP).

The optimal combination of five components to develop a concrete for high-temperature applications was studied through a response surface methodology known as mixture design of experiment. The selected components were water, an alkali-activated binder based on ferronickel slag activated with potassium silicate and potassium hydroxide, and three aggregate sizes corresponding to 0-4 mm, 4-8 mm, and 8-16 mm. Selected response parameters were slump and compressive strength before and after heat exposure. Six cubes of side 150 mm were cast for each concrete mix, three for ambient and three for residual (post-heat exposure) compressive strength. All 20 concrete mixes were exposed to a thermal load of 600 °C for two hours. The optimal concrete mix was adapted for large-scale applications, by increasing slump and replacing limestone with olivine aggregates for enhanced residual compressive strength. The adapted mix resulted in concrete with 76 MPa and 32 MPa compressive strength before and after high-temperature exposure. The CO2 emissions were found to be 77 % lower when compared to traditional OPC concrete.

The paper presents the problem of damage detection in steel girders. Static displacements at the selected point of the structure play the role of measured variables. Structural response signal decomposition is performed according to the Mallat pyramid algorithm, which is used to perform the discrete wavelet transform (DWT). This procedure allows us to quite well determine the location of structural damage. The geometry and the placement of any defective part of the structure may have a random character. It can be assumed that the random processes occurring in the broadly understood structure mechanics are Gaussian in nature. The first four probabilistic moments are estimated using three approaches independent: semi-analytical (SAM), perturbative (SPT), and Monte-Carlo simulations (MCS). The semi-analytical random approach seems to be the most optimal due to the necessary computation time. The incorporation of the mathematical stochastic apparatus into the classical (deterministic) analysis of the statics of the structure makes it possible to estimate the reliability measures of the analyzed girder.

The influenza virus has been the primary cause of the pandemic, posing a constant threat to human society. Due to its genetic evolution and continuous outbreak, antiviral research currently focuses on exploring a novel lead agent. A comprehensive antiviral screening discovered a marine bacterium whose extract exerted excellent efficacy against influenza viruses. Parerythrobacter sp. M20A3S10, a novel strain under the family Erythrobacteraceae, could produce carotenoids exhibiting antiviral and anticancer activity by enhancing the cellular immune system. Post-treatment of M20A3S10 extract showed outstanding therapeutic indexes: against influenza virus A/PR8 (H1N1) [selectivity index (SI) = 24.0], A/Wisconsin/15/2009 (H3N2) (SI = 30.1) and B/Florida/78/2015 (SI = 38.2). Comparably, the effectiveness was demonstrated against Zika virus (ZIKV) and dengue virus type 2 (DENV2) with an SI of 22.5 and 24.1, respectively, namely broad-spectrum activity. Of note, the antiviral responses resulted from the common replication mechanism between IAV, ZIKV, and DENV2. The stimulation of apoptosis-mediated cellular immunity prevented the viral release and protected the host, suggesting that switching from necroptosis to apoptosis is a novel antiviral target. Although the specific compound affecting the antiviral activity was not identified, its promising efficacy with broad activity will contribute to developing a strategy for preventing future pandemics.

Foliage-feeding fall armyworm (Spodoptera frugiperda) and root-feeding western corn rootworm (Diabrotica virgifera virgifera) are maize (Zea mays L.) pests that cause significant yield losses. Jasmonic acid (JA) play pivotal defense role against insects. 12-oxo-phytodienoic acid (12-OPDA) is converted into JA by peroxisome-localized OPDA reductases (OPR). However, little is known about the physiological functions of cytoplasmic OPRs. Here, we show that disruption of ZmOPR2 reduced wound-induced JA production and defense against FAW while accumulating more JA catabolites. Overexpression of ZmOPR2 in Arabidopsis enhanced JA production and defense against beet armyworm (Spodoptera exigua). In addition, lox10opr2 double mutants were more susceptible than either single mutant, suggesting that ZmOPR2 and ZmLOX10 uniquely and additively contributed to defense. In contrast to the defensive role of ZmOPR2 and ZmLOX10 in leaves, single mutants did not display any alteration in root herbivory defense against WCR. Feeding on lox10opr2 double mutants resulted in increased WCR mortality associated with greater herbivory-induced production of insecticidal death acids and ketols. Thus, ZmOPR2 and ZmLOX10 cooperatively inhibit synthesis of these metabolites during herbivory by WCR. We conclude that ZmOPR2 and ZmLOX10 regulate JA-mediated resistance in leaves against FAW while suppressing insecticidal oxylipin synthesis in roots during WCR infestation.

Acid stress poses a common challenge for bacteria in diverse environments by the presence of inorganic (e.g., mammals’ stomach) or organic acids (e.g., feed additives; acid-based disinfectants). Limited knowledge exists regarding acid-tolerant strains of specific serotypes, clonal lineages, or sources in human/animal pathogens, namely non-typhoidal Salmonella enterica (NTS) and Enterococcus faecium (Efm). This study evaluated acidic pH and peracetic acid (PAA) susceptibility of Efm (n=72) and NTS (n=60) from diverse epidemiological/genetic backgrounds, and with multiple antibiotic resistance profiles. Efm minimum growth/survival-pH was 4,5-5/3-4 and for NTS 4,0-4,5/3,5-4,0. Among Efm, only those of clade-non-A1 (non-hospital associated) or food chain demonstrated greater tolerance to acidic pH compared to clade-A1 (hospital-associated clones) or clinical isolates (P<0.05). MDR (multidrug-resistant) NTS survived better to acidic pH (P<0.05). The MICPAA/MBCPAA was 70-120/80-150mg/L for Efm and 50-70/60-100mg/L for NTS. Efm-clade-A1 or MDR strains exhibited higher PAA tolerance than clade-non-A1 or non-MDR ones (P<0.05). Higher tolerance was found in non-MDR and clinical NTS than in food chain isolates (P<0.05), but not between different serogroups. This unique study identifies specific NTS or Efm populations more tolerant to acidic pH or PAA, emphasizing the need for further research to tailor control measures of public health and food safety within a One Health framework.

Kummerowia striata is a traditional medicine used for the therapy of inflammation-related diseases. Herein, we investigated the anti-melanogenic and antioxidant activities of an ethanolic extract of K. striata (EKS) using a number of in vitro and cell culture model systems. The anti-melanogenic effect was assessed in B16F10 melanoma cells based on melanin synthesis and in vitro tyrosinase inhibitory activity and the anti-oxidant activity assays were performed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS); EKS exhibited strong anti-oxidant activities in both the assays. The expression of tyrosinase, tyrosinase-related protein 1, tyrosinase-related protein 2, and microphthalmia-associated transcription factor was decreased in a dose-dependent manner at mRNA and protein levels upon treatment with EKS. Notably, EKS did not affect the cell viability at all the EKS concentrations used in this study, indicating that EKS-mediated inhibition of melanin synthesis is not accompanied with cytotoxicity. Collectively, our findings demonstrate, for the first time, that EKS possesses anti-melanogenic and anti-oxidant activities, and suggest that further evaluation and development of EKS as a functional supplement or cosmetic might be useful for skin whitening and for reduction wrinkles.

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change of refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. In the experiment, a three-bladed propeller with a diameter of 39mm was selected, the water tank size was 980mm×380mm×380mm, and the laser acted at a distance of 550 mm from the propeller. The experimental results indicate that the wake dissipation time of the propeller in a strong density-stratified water environment is approximately 800s. Following the stabilization of the wake field density, the laser spot position is observed to be stable at 0.341 mm, with a corresponding refractive index change of 2.99×10-6 RIU. The wake dissipation time of the propeller in a linear density-stratified water environment is approximately 750 s. Once the wake field density has reached a stable state, the laser spot position is found to be 0.441mm, corresponding to a refractive index change of 3.87×10-6 RIU. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental device-based wake measurements with the CTD-based wake measurements reveals a consistent trend.

Cannabidiol (CBD), a non-psychotropic main component of the Cannabis plant, is approved as a drug in the European Union (EU) under the name “Epidyolex”. However, the approval process as a food ingredient under the Novel Food Regulation was paused by the European Food Safety Authority (EFSA) due to a lack of safety data. Nevertheless, there is a growing, unregulated market in which CBD is advertised with various health claims and different dosage instructions. Of particular concern is its toxic effect on the liver and possible reproductive toxicity in humans. Studies suitable for calculating a benchmark dose were identified from the available data. Animal studies yielded a Benchmark Dose Lower Confidence Limit (BMDL) of 43 mg/kg bw/day, which translates into a safe human dose of approximately 15 mg/day. Only a Lowest Observed Adverse Effect Level (LOAEL) of 4.3 mg/kg bw/day could be identified from the human data. This updated risk assessment confirmed the Health-based Guidance Value (HBGV) of 10 mg/day based on human LOAEL. Despite existing data gaps, preliminary regulation appears advisable as the current form of the gray CBD market is unacceptable from the standpoint of consumer safety and protection.

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. FE models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS PDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

Cholesterol homeostasis is pivotal for cellular function. Acyl-coenzyme A:cholesterol acyltransferase 1 (ACAT1), also abbreviated as SOAT1, is an enzyme catalyzing the storage of excess cholesterol to cholesteryl esters. ACAT1 is an emerging target to treat diverse diseases including atherosclerosis, cancer, and neurodegenerative diseases. F12511 is a high affinity ACAT1 inhibitor. Previously, we developed a stealth liposome-based nanoparticle to encapsulate F12511 to enhance its delivery to the brain and showed its efficacy in treating a mouse model for Alzheimer’s disease (AD). In this study, we introduce F26, a close derivative of F12511 metabolite in rats. F26 was encapsulated in the same DSPE-PEG2000/phosphatidylcholine (PC) liposome-based nanoparticle system. We employed various in vitro and in vivo methodologies to assess F26's efficacy and toxicity compared to F12511. Results demonstrate that F26 is more effective and durable than F12511 in inhibiting ACAT1, in both mouse embryonic fibroblasts (MEFs) and in multiple mouse tissues including the brain tissues, without exhibiting any overt systemic or neurotoxic effects. This study demonstrates the superior pharmacokinetic and safety profile of F26 in wild-type mice, and suggests its therapeutic potential against various neurodegenerative diseases including AD.

In a trip planning service, travelers first set a starting point, a destination, and a sequential list of specific points of interest types (e.g., museums, restaurants, and parks). Based on this information, the service searches the spatial database to customize the best travel itinerary for the tourist. However, in previous studies, planners only considered the time factor when designing the optimal route, and failed to fully consider the quality of each point of interest. In this study, we specifically leveraged the capabilities of large language model to parse and respond to complex travel-related user queries. To apply large language model to route planning, we fine-tuned the model to understand geotagging and user travel preferences. We have introduced a novel graph search algorithm combined with large language model output, which optimizes the route search process to provide optimal travel recommendations by taking into account various factors such as distance length, budget constraints, and popularity of tourist attractions. In addition, we have integrated real-time traffic data and historical travel data to further improve the prediction accuracy and application usefulness of the model. In the experimental validation phase, we designed a series of benchmarks to compare the performance of the system with traditional algorithms and other machine learning-based route planning methods. Experimental results show that our model has a significant improvement compared with traditional methods in improving the speed and accuracy of path selection.

Few prior works study self-driving cars by deep learning with IoT collaboration. SDC-Net, which is an end-to-end multitask self-driving car camera cocoon IoT-based system, is one of the research that tackles this direction. However, by design SDC-Net is not able to identify the accident locations, it only classifies if it is a crash scene or not. In this work, we introduce an enhanced design for the SDC-Net system by 1) replacing the classification network with a detection one, 2) adapting our benchmark dataset labels built on the CARLA simulator to include the vehicles bounding boxes while keeping the same training, validation, and testing samples, 3) modifying the shared information via IoT to include the accident location. We keep the same path planning and automatic emergency braking network, the digital automation platform, and the input representations to formulate the comparative study. SDC-Net++ system is proposed to 1) output the relevant control actions, especially in case of accidents: accelerate, decelerate, maneuver, and brake, and 2) share the most critical information to the connected vehicles via IoT, especially the accident locations. A comparative study is also conducted between SDC-Net and SDC-Net++ with the same input representations: front camera only, panorama and bird-eye views, and with single-task networks: crash avoidance only, and multitask networks. Multitask network with a BEV input representation outperforms the nearest representation in precision, recall, f1-score, and accuracy by more than 15.134%, 12.046%, 13.593%, and 5%, respectively. SDC-Net++ multitask network with BEV outperforms SDC-Net multitask with BEV in precision, recall, f1-score, accuracy, and average MSE by more than 2.201%, 2.8%, 2.505%, 2%, and 18.677% respectively.

Modern search engines encounter a significant challenge when it comes to handling duplicate and nearly identical web pages, particularly during the indexing process for vast amounts of web content. This issue can lead to slow search results and increased costs due to the accumulation of storage space necessary for storing indexes. To tackle this issue, different techniques have been proposed to find similar websites. However, it has long been a challenge in research to distinguish between web pages. In the current study, sentence-level features i.e., hashcode and thresholding are used to determine the nearly identical web pages. We employ an adaptive threshold that enables the application of our model in both large- and small-scale settings. The benchmark datasets consisting of Shakespeare’s collections, free text, job descriptions, and Reuters-21578 are used to test the proposed approach. With an accuracy of 0.99 and an F1-score of 0.97, the proposed technique outperforms existing methods.

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper better communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as a helpful tool to enhance UAV communication networks. However, due to the high mobility of UAV, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. Simulation results showed that the proposed GRU model effectively and accurately estimates the link quality of the ground users in the RIS-assisted UAV-enabled wireless communication network.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

To investigate the composition of caproic acid-producing bacterial communities in sub-high-temperature Daqu, we analyzed four different Daqu samples from Sichuan. After enriching the samples with a specialized medium, we performed high-throughput sequencing of 16S rRNA gene amplicons on the metagenomic DNA from both the Daqu samples and the enrichment cultures. Our analysis focused on identifying and characterizing the caproic acid-producing bacterial communities present in Daqu. The results revealed that enrichment increased both the diversity and abundance of potential caproic acid-producing bacteria in Daqu. The predominant caproic acid-producing bacteria, with a relative abundance greater than 1%, included Clostridium sensu stricto 18 (2.19% to 69.00%), Clostridium sensu stricto 15 (1.76% to 7.65%), as well as smaller amounts of Clostridium sensu stricto 12, Clostridium sensu stricto 1, Clostridium sensu stricto 10, Clostridium sensu stricto 7, and Caproiciproducens. Specifically, Q1 Daqu was characterized by the presence of Clostridium sensu stricto 18 and Clostridium sensu stricto 15. Q2 Daqu featured Clostridium sensu stricto 1, Caproiciproducens, and Clostridium sensu stricto 18. Q3 Daqu included Clostridium sensu stricto 18 and Caproiciproducens. Q4 Daqu contained Clostridium sensu stricto 18 and Clostridium sensu stricto 1. These findings indicate that there are variations in the composition of caproic acid-producing bacterial communities among different sub-high-temperature Daqu samples from Sichuan. This preliminary analysis provides a theoretical basis for further studies on caproic acid bacteria in Daqu and offers insights into the development of high-quality Daqu, which may enhance the quality of Nongxiangxing liquor.

In recent decades, given the important role of gamma-aminobutyric acid (GABA) in human health, scientists have paid great attention to the enrichment of this chemical compound in food using various methods, including microbial fermentation. Moreover, GABA or GABA-rich products have been successfully commercialized as food additives or functional dietary supplements. Several microorganisms can produce GABA, including bacteria, fungi, and yeasts. Among GABA-producing bacteria, lactic acid bacteria (LAB) are commonly used in the production of many fermented foods. Lactiplantibacillus plantarum (previously Lactobacillus plantarum) has a long history of natural occurrence and safe use in a variety of food products. This LAB species provides functional properties to various fermented foods by producing a variety of bioactive compounds, including GABA. The present review aims, after a preliminary excursus on the function and biosynthesis of GABA, to provide an overview on the current uses of microorganisms and in particular of L. plantarum in the production of GABA, with a detailed focus on fermented foods.

The accumulation of loss of function mutations in the uricase gene well explains the high urate levels in hominoids (apes and humans) compared to other mammals. The loss of human uricase activity may have allowed humans to survive environmental stressors, evolution bottlenecks, and life-threatening pathogens. While high urate levels may contribute to developing cardiometabolic disorders such as hypertension and insulin resistance, low urate levels may increase the risk for neurodegenerative diseases. The double-edged sword effect of uric acid has resurrected a growing interest in the antioxidant role of urate and the role of the uricase gene in modulating the risk of obesity. Characterizing both the effect of uric acid levels and the uricase gene in different animal models may provide new insights into the potential therapeutic benefits of uric acid and novel uricase-based therapy.

In the last decades, studies on the inflammatory signaling pathways in multiple pathological contexts revealed new targets for novel therapies. Among the family of G-protein-coupled Proteases Activated Receptors, PAR2 was identified as a driver of the inflammatory cascade in many pathologies, ranging from autoimmune disease to cancer metastasis. For this reason, many efforts have been focused on the development of potential antagonists of PAR2 activity. This work focuses on a small molecule, 1-Piperidine Propionic Acid (1-PPA), previously described to be active against inflammatory processes, but whose target is still unknown. Stabilization effects observed by cellular thermal shift assay coupled to in-silico investigations, including molecular docking and Molecular Dynamics simulations, suggested that 1-PPA binds PAR2 in an allosteric pocket of the receptor inactive conformation. In addition, this compound was found able to inhibit platelet aggregation, a process mediated by PAR family members, including PAR2. Since the allosteric pocket binding 1-PPA is highly conserved in all the members of the PAR family, the evidence reported here suggests that 1-PPA could represent a promising new small molecule targeting PARs with antagonistic activity.

Polyphenol ellagic acid (EA) possesses anti-oxidant, anti-inflammatory, anti-carcinogenic, anti-diabetic and cardio protection activities, remarking it an interesting multi-targeting profile. EA also controls the central nervous system (CNS) since it was proven to reduce the immobility time of mice in both the forced swimming and the tail-suspension tests, with an efficiency comparable to that of classic antidepressants. Interestingly, the anti-depressant-like effect was almost nulled by the concomitant administration of selective antagonists of the noradrenergic receptors, suggesting the involvement of these cellular targets in the central effects elicited by EA and its derivatives. By in silico and in vitro studies, we discuss how EA engages with human α2A-ARs and α2C-AR catalytic pockets, comparing EA behaviour with those ones of known agonist and antagonist. Structurally, the hydrophobic residues surrounding α2A-AR pocket confer specificity on the intermolecular interactions and hence lead to favourable binding of EA in the α2A-AR, with respect to α2C-AR. Moreover, EA seems to better accommodate within α2A-ARs into TM5 area, closely to S200 and S204 which play a crucial role for activation of aminergic GPCRs such as the α2-AR, highlighting its promising role as a partial agonist. Consistently, EA mimics clonidine in inhibiting noradrenaline exocytosis from hippocampal nerve endings in an yohimbine-sensitive fashion that confirms the engagement of naïve α2-ARs in the EA-mediated effect.

Folic acid, one of the 13 essential vitamins, plays an important role in cardiovascular development. Mutations in folic acid synthesis gene 5,10-methylenetetrahydrofolate reductase (MTHFR) is significantly associated with the occurrence of congenital heart disease. However, the mechanisms underlying the regulation of cardiac development by mthfr gene are poorly understood. Here, we exposed zebrafish embryos to excessive folate or folate metabolism inhibitors. And we established a knock-out mutant of mthfr gene in zebrafish by using CRISPR/Cas9. The zebrafish embryos of insufficient or excessive folic acid, and mthfr-/- mutant all gave rise to early pericardial edema and cardiac defect at 3 days after fertilization(dpf). Furthermore, the folic acid treated embryos showed abnormal movement at 5dpf. The expression levels of cardiac marker genes hand2, gata4 and nppa changed in the abnormality of folate metabolism embryos and mthfr-/- mutant, and there is evidence that they are related to the change of methylation level caused by the change of folate metabolism. In conclusion, our study provides a novel model for the in-depth study of MTHFR gene and folate metabolism. And our results reveal that folic acid has a dose-dependent biphasic effect on early cardiac development.

We evaluated the change in water dispersibility of lactic acid bacteria (LAB, Enterococcus faecalis KH2) upon powderization and its influence on their efficacy. When cultured LAB are washed, heat-killed, and powdered, adhesion between LAB occurs and they form aggregation (non-treated LAB, n-LAB). However, a dispersed LAB (d-LAB) powder with less aggregates can be prepared by treating them with a high-pressure homogenizer and adding an excipient during powdering. n-LAB or d-LAB was administered to mice and the Peyer's patches in the small intestine were observed. n-LAB administration showed a high amount of aggregated LAB drifting in the intestinal mucosa, whereas d-LAB reached the Peyer's patches and was taken up into the Peyer's patches. Evaluation in a mouse influenza virus infection model showed that d-LAB was more effective than n-LAB in influenza yield of bronchoalveolar lavage fluids (BALFs) on day 3 post-infection, neutralizing antibody titers of sera and influenza virus-specific IgA in the feces on day 14 post-infection. Thus, the physical properties of LAB affect their efficacy; controlling their water dispersibility can improve their effectiveness.

The search for economical and sustainable sources of PUFAs within the framework of the circular economy is encouraged by their proven beneficial effects on health. The extraction of monkfish liver oil (MLO) for the synthesis of omega-3 ethyl esters was performed evaluating two blending systems and four green solvents. Moreover, the potential solubility of the MLO in green solvents was studied using the predictive simulation software COSMO-RS. The production of the ethyl esters was performed by one or two step reactions. Novozym 435, two resting cells (Aspergillus flavus and Rhizopus oryzae) obtained in our laboratory and mix of them were used as biocatalysts in a solvent-free system. The yields for Novozym 435, R. oryzae and A. flavus in the one-step esterification were 63%, 61% and 46%, respectively. The hydrolysis step in the two-step reaction led to 83%, 88% and 93% of free fatty acids (FFA) for Novozym 435, R. oryzae and A. flavus respectively. However, Novozym 435 showed the highest yield in the esterification step (85%) followed by R. oryzae (65%) and A. flavus (41%). Moreover, selectivity in front of polyunsaturated fatty acids of R. oryzae lipase was evidenced, since it did slightly esterified docosahexaenoic acid (DHA) in all the esterification reactions tested.

Perfluorooctanoic acid (PFOA), C7F15COOH, has been widely employed over the past fifty years, causing an environmental problem due to its dispersion and low biodegradability. Furthermore, the high stability of this molecule, conferred by the high strength of the C-F bond makes it very difficult to remove. In this work, electrochemical techniques are applied for PFOA degradation in view to study the influence of the cathode on defluorination. For this purpose, boron doped diamond (BDD), Pt, Zr and stainless steel have been tested as cathodes working with BDD anode at low electrolyte concentration (3.5 mM) to degrade PFOA at 100 mg/L. Among these cathodic materials, Pt improves the defluorination reaction. The electro-degradation of a PFOA molecule starts by a direct exchange of one electron at the anode and then follows a complex mechanism involving reaction with hydroxyl radicals and adsorbed hydrogen on the cathode. It is assumed that Pt acts as an electrocatalyst, enhancing PFOA defluorination by the reduction reaction of perfluorinated carbonyl intermediates on the cathode. The defluorinated intermediates are then more easily oxidized by HO• radicals. Hence, high mineralization (xTOC: 76.1%) and defluorination degrees (xF-: 58.6%) were reached with Pt working at current density j = 7.9 mA/cm2. This BDD-Pt system reaches a higher efficiency in terms of defluorination for a given electrical charge than previous works reported in literature. Influence of the electrolyte composition and initial pH are also explored.

Introduction: Increased oxidative stress, including elevated homocysteine (Hcy) plasma levels, and lowered levels of antioxidants participate in the pathophysiology and progression of chronic kidney disease (CKD). Paraoxonase (PON)1 activity and folic acid are antioxidants which play a role in Hcy metabolism. However, there are no data whether, in CKD, treatment with folic acid improves glomerular filtration rate (GFR) through effects on PON1 activity and Hcy concentrations. Methods: In the current study, we determined PON1 genotypes and activity, Hcy and estimated GFR (eGFR) both before and after treatment with folic acid (5 mg/d) versus no treatment during three consecutive months in 113 outpatients with CKD classified into stages 4, 3b and 3a. Results: PON1 CMPAase and AREase activities were significantly lower in patients allocated to CKD stage 4 as compared with stages 3b and 3a. Treatment with folic acid significantly improved eGFR and increased levels of CMPAase and AREase in patients allocated to classes 4 and 3b, but not 3a. The improvement of eGFR was associated with increased CMPAase and AREase activities, while the latter were associated with increased levels of folic acid. Treatment with folic acid significantly reduced plasma Hcy levels and the Hcy/PON1 activity ratio. The effects of folic acid increasing PON1 activities were not mediated by changes in Hcy. Discussion: Treatment of CKD patients in early/intermediate stages of CKD patients improves oxidative stress by rebalancing the prooxidant (Hcy) / antioxidant (PON1 activities) ratio. Treatment with folic acid significantly improves eGFR and these effects are mediated via increased PON1 activities. Treatment with folic acid in phase G3b and G4 may reduce renal disease progression by enhancing antioxidant defenses.

Tough and antimicrobial dual-crosslinked poly((trimethylamino)ethyl methacrylate chloride)-phytic acid hydrogel (pTMAEMA-PA) has been synthesized by adding chemical crosslinker and docking physical crosslinker of multivalent phytic acid into a cationic polyelectrolyte network. By increasing the loading concentration of PA, the tough hydrogel exhibits compressive stress of >1 MPa, along with high elasticity and fatigue-resistant properties. The enhanced mechanical properties of pTMAEMA-PA were stem from multivalent ion effect of PA via the formation of ion bridges within polyelectrolytes. In addition, a comparative study for a series of pTMAEMA-counterion complexes was conducted to elaborate the relationship between swelling ratio and mechanical strength. The study also revealed secondary factors, such as ion valency, ion specificity and hydrogen bond formation, holding crucial roles in tuning mechanical properties of the polyelectrolyte hydrogel. Furthermore, in bacteria attachment and disk diffusion tests, pTMAEMA-PA exhibits superior fouling resistance and antibacterial capability. The results reflect the fact that PA enables chelating strongly with divalent metal ions, hence, disrupting the outer membrane of bacteria, as well as dysfunction of organelles, DNA and protein. Overall, the work demonstrated a novel strategy for preparation of tough polyelectrolyte with antibacterial capability via docking PA to open up the potential use of PA in medical application.

For the effective utilization of rice husk, organosolv fractionation was investigated to separate three main components (glucan, xylose, and lignin) with low acid concentration. Reaction temperatures of 170–190 °C, ethanol concentrations of 50–70% (v/v), and sulfuric acid concentrations of 0–0.7% (w/v) were investigated, with the reaction time and liquid-to-solid ratio kept constant at 60 min and 10, respectively. The fractionation conditions for the efficient separation into the three components of rice husk were determined to be 180 °C, 60% (v/v) of ethanol, and 0.25% (w/v) of sulfuric acid. Under these fractionation conditions, 86.8% of the xylan and 77.5% of the lignin were removed from the rice husk, and xylose and lignin were obtained from the liquid in 67.6% and 49.8% yields, respectively. The glucan digestibility of the fractionated rice husk was 85.2% with an enzyme loading of 15 FPU (filter paper unit) of cellulase per g-glucan.

An exploratory Life Cycle Assessment was carried out to provide insight into the environmental impacts of using the green seaweed Ulva spp. as a feedstock for production of bioplastic. The study focused on the production of lactic acid as a precursor of polylactic acid. The studied production process consists of (1) the cultivation of Ulva spp. in Integrated Multitrophic Aquaculture, (2) the processing of the biomass for solubilisation of sugars, (3) the fermentation of the sugars to lactic acid and (4) isolation of lactic acid from the fermentation broth. The study identifies environmental hotspots and compares the experimental seaweed production chain with conventional feedstock. The main hotspot identified is electricity consumption during seaweed cultivation. This impact of electricity consumption can be lowered by reducing energy use and sourcing renewable energy, and by improving the material efficiency in the product chain. To improve understanding of the environmental impacts of the production process, future studies can broaden the system boundaries and broaden the scope of sustainability issues included in the environmental assessment.

This study focuses on enhancing controllable fibrin-based hydrogels for tissue engineering, addressing existing weaknesses. By integrating a novel copolymer, we improve the foundation for cell-based angiogenesis with adaptable structural features. Tissue engineering often faces challenges like waste disposal and nutrient supply beyond the 200 µm diffusion limit. Angiogenesis breaks through this limitation, allowing the construction of larger constructs. Our innovative scaffold combination significantly boosts angiogenesis, resulting in longer branches and more capillary network junctions. The copolymer attached to fibrin fibers enables precise adjustment of hydrogel mechanical-dynamic properties for specific applications. Our material proves effective for angiogenesis, even under suppression factors like suramin. In our study, we prepared fibrin-based hydrogels with and without the copolymer PVP12400-co-GMA10mol%. Using a co-culture system of human umbilical vein endothelial cells (HUVEC) and mesenchymal stem cells (MSC), we analyzed angiogenetic behavior on and within the modified hydrogels. Capillary-like structures were reproducibly formed on different surfaces, demonstrating the general feasibility of three-dimensional endothelial cell networks in fibrin-based hydrogels. This highlights the biomaterial's suitability for in vitro pre-vascularization of biohybrid implants.

The domain of construction engineering and management is evolving rapidly. Optimizing resource positioning is crucial for meeting the challenges of efficiency and productivity. This research presents a novel methodology that incorporates Agent-Based Modeling (ABM), Building Information Modeling (BIM), and Bluetooth Low Energy (BLE) technologies, augmented with a Client Early Warning System (CEWS) and a Decision Support System (DSS). What makes this study unique is that it provides a real-time methodology for resource allocation and project management, tailored to address the complexities of modern construction projects. The application of this integrated technological framework marks a significant leap in construction management, empowering data-driven decision-making and significantly improving project efficiency. Empirically validated through a case study at Helwan University's College of Engineering and substantiated by expert surveys, this research showcases a transformative model for resource management. The findings not only underscore the practical applicability of this approach but also open new horizons for its adoption in global construction practices, offering insights for future research endeavors focused on expanding these methodologies to a wider range of resources.

Optical artificial neural networks (ONNs) — analog computing hardware tailored for machine learning [1,2] — have significant potential for ultra-high computing speed and energy efficiency [3]. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources [4] that is programmable, highly scalable and capable of reaching ultra-high speeds. We experimentally demonstrate the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths of a micro-comb to achieve a high single-unit throughput of 11.9 Giga-FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps. We test the perceptron on simple standard benchmark datasets — handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record small wavelength spacing (49GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, we propose an approach to scaling the perceptron to a deep learning network using the same single micro-comb device and standard off-the-shelf telecommunications technology, for high-throughput operation involving full matrix multiplication for applications such as real-time massive data processing for unmanned vehicle and aircraft tracking.

Infill drilling is one of the most effective methods to improve the performance of poly-mer flooding. The difficulties related to infill drilling are determining the optimal numbers and placements of infill wells. In this study, an improved archimedes optimization algorithm with Halton sequence (HS-AOA) was proposed to overcome the aforementioned difficulties. First, to optimize the infill well placement for polymer flooding, an objective function that considered the economic influence of infill drilling was developed. Then, the novel optimization algorithm (HS-AOA) for infill well placement was developed by combining the AOA with the Halton se-quence. The codes were developed in MATLAB and connected to a commercial reservoir simula-tor CMG STARS to carry out the infill well placement optimization. Finally, the HS-AOA was compared to the basic AOA to confirm its reliability and then used to optimize the infill well placements for polymer flooding in a typical offshore oil reservoir. The results showed that the introduction of the Halton sequence into AOA effectively increased the diversity of the initial ob-jects in the AOA and avoided the HS-AOA trapping into the local optimal solutions. The HS–AOA outperformed the AOA. It was an effective approach to optimize the infill well placement for polymer flooding processes. In addition, infill drilling could effectively and economically im-prove the polymer flooding performance in offshore oil reservoirs. The NPV of the polymer flooding case with infill wells determined by HS-AOA reached 3.5 × 108 $, which was an increase of 7% over that of the polymer flooding case. This study presents an effective method for opti-mizing infill well placement for polymer flooding processes. It also can serve as a valuable refer-ence for other optimization problems in the petroleum industry, such as joint optimization of well control and placement.

The layer-by-layer (LBL) fabrication method allows for controlled microstructure morphology and vertical component distribution, and also offers a reproducible and efficient technique for fabricating large-scale organic solar cells (OSCs). In this study, polymer D18 and PYIT-OD are employed to fabricate all-polymer solar cells (all-PSCs) using the LBL method. Morphological studies reveal that the use of additives optimizes the microstructure of the active layer, enhancing the crystallinity and charge transport capability. The optimized device with 2% CN additive significantly reduces bimolecular recombination and trap-assisted recombination. All-PSCs fabricated by the LBL method based on D18/PYIT-OD deliver a power conversion efficiency (PCE) of 15.07%. Our study demonstrates the great potential of additive engineering via LBL fabrication method in regulating microstructure of active layers, suppressing charge recombination, and enhancing the photovoltaic performance of devices.

This study aims at better understanding the damage and fracture kinetics in flax fibres elements at both the unitary and bundle scales using an experimental setup allowing optical observation at high recording rate in the course of tensile loading. Defects issues from flax unitary fibre extraction are quantitated using polarized light microscopy. Tensile loading is conducted according to a particular setup adapted to fibres of 10 to 20 µm in diameter and 10 mm in length. Optical recording using high speed camera is performed during loading up to the failure at acquisition speed ranging from 108,000 to 270,000 frames per second. Crack initiation in polymer layers of fibre elements, propagation as well as damage mechanisms are captured. The results show different failure scenarios depending on the fibre element nature. In particular, fractured fibres underline either a fully transverse failure propagation or a combination of transverse and longitudinal cracking with different balances. Image recordings with high time resolution down to 3.7 μs suggest unstable system and transverse crack speed higher than 4 m/s and a slower propagation for longitudinal crack deviation.

Efficient oxygen evolution reaction (OER) electrocatalysts are highly desired in the field of water electrolysis and rechargeable metal-air batteries. In this study, a chelate polymer, composed of copper (II) and dithiooxamide, was used to derive an efficient catalytic system for OER. Upon potential sweep in 1M KOH, copper (II) centers of the chelate polymer were transformed to CuO and Cu(OH)2. The carbon-dispersed CuO nanostructures formed a nanocomposite which exhibits an enhanced catalytic activity for OER in alkaline media. The nanocomposite catalyst has overpotential of 280 mV (at 1 mA/cm2) and a Tafel slope of 81 mV/dec in 1M KOH solution. It has a seven-fold higher current than IrO2/C electrode, per metal loading. A catalytic cycle is proposed, in which, CuO undergoes electrooxidation to Cu2O3 that further decomposes to CuO with releasing oxygen. This work reveals a new method to produce an active nanocomposite catalyst for OER in alkaline media using a non-noble metal chelate polymer and a porous carbon. This method can be applied to the synthesis of transition metal oxide nanoparticles used in the preparation of composite electrodes for water electrolyzers and can be used to derive cathode materials for aqueous-type metal-air batteries.

Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by improved glucose tolerance and higher blood insulin levels. 7S,14R-diHDHA-treated MSCs increased insulin+ β-cell ratio and decreased glucogan+ α-cell ratio in islets, as well as reduced macrophages in pancreas. 7S,14R-diHDHA induced MSC functions in promoting MIN6 β-cell viability and insulin secretion. 7S,14R-diHDHA induced MSC paracrine functions by increasing the generation of hepatocyte growth factor and vascular endothelial growth factor. Furthermore, 7S,14R-diHDHA enhanced MSC functions to ameliorate diabetes-caused pericyte loss in diabetic retinopathy by increasing their density in retina in db/db mice. Our findings provide a novel strategy for improving therapy for diabetes and diabetic retinopathy using 7S,14R-diHDHA-primed MSCs.

Use of antibiotics and other chemicals to combat disease outbreaks have been a bottleneck for the sustainable growth of shrimp industry. Among various replacement proposed, organic acid (OA) and their salts (OS) are commonly used by farmers and feed millers. However, in free forms, their requirement is very high (2-3 kg/MT) as they tend to disassociate before reaching the hindgut. The dosage can be reduced by microencapsulation of the ingredients. In this study, a 63-day trial was conducted to assess the effects of OA and OS (COMP) microencapsulated (ENCAP) with fat (HF), fat + alginate (HA), wax esters – (WE), and HA and WE (HAWE) on performance, digestive enzyme, immune, and resistance to Vibrio parahaemolyticus. A positive control (PC, 200 g/kg fishmeal - FM) and a negative control (NC, 130 g/kg FM) diet were formulated. Eight other diets were formulated supplementing NC diet with microencapsulated OA (OAHF, OAHA, OAWE, OAHAWE) and OS (OSHF, OSHA, OSWE, OSHAWE). Among the ENCAPs, significant difference was observed in serum malondialdehyde (P = 0.026) where HF showed the lowest level (6.4 ±0.3 mmol/L). Significant interactions between COMP and ENCAP were observed in lipid deposition (P = 0.047), serum alkaline phosphatase and acid phosphatase (P < 0.0001), and hepatopancreatic and serum phenol oxidase (P < 0.0001). Despite no differences, 96-h mortality during pathogenic Vibrio parahaemolyticus challenge in all treatment diets (45% - 56%) was lower compared to the NC diets (63%). In conclusion, use of HF microencapsulated OA diets could provide improved performance and disease resistance that could contribute to the reduction of antibiotic use by the shrimp industry.

The phenylpropanoid pathway is a major secondary metabolite pathway that helps plants overcome biotic and abiotic stress and produces various by-products that promote human health. Its byproduct, chloroquinic acid (CQA), is a soluble phenolic compound present in many angiosperms. Hy-droxycinnamate-CoA shikimate/quinate transferase(BAHDs superfamily enzyme) is a significant en-zyme that plays a role in accumulating CQA biosynthesis. This study analyzed transcriptome-wide identification of the phenylpropanoid to chloroquinic acid biosynthesis candidate genes in A. spathulifolius flowers and leaves. Transcriptomic analyses of the flowers and leaves showed a differential expression of the PPP and CQA biosynthesis regulated unigenes. An analysis of PPP captive unigenes revealed the following: the major duplication of the key enzyme, PAL, 120 unigenes in leaves and 76 in flowers; the gene encoding C3’H, 169 unigenes in leaves and 140 unigenes in flowers; duplicated unigenes of 4CL, 41 in leaves and 27 in flowers. In addition, C4H unigenes had 12 unigenes in the leaves of A. spathulifolius and four in the flowers. The characterization of the BAHDs superfamily members identified 82 in leaves and 72 in flowers. Among them, phylogenetic analysis showed that five unigenes encoded HQT and three en-coded HCT in A. spathulifolius. The three HQT are common to both leaves and flowers, whereas the two HQT were specialized for leaves. The pattern of HQT synthesis was upregulated in flowers, whereas HCT was expressed strongly in the leaves of A. spathulifolius. Overall, 4CL, C4H, and HQT are expressed strongly in flowers, and caffeic acid and HCT show more expression in leaves. Therefore, CQA biosynthesis occurs in the flowers of A. spathulifolius rather than leaves.

The enhancement of health-beneficial omega-3 long chain polyunsaturated fatty acid (n-3 LC-PUFA) contents in the muscle, liver, heart and kidney of Australian prime lambs through pasture grazing and supplementation with oil infused pellets was investigated. Forty-eight first-cross prime lambs were randomly assigned into a split-plot design with pasture type as the main plot effect and pellet supplementation as a sub-plot effect in a feeding trial that lasted for nine weeks. The n-3 LC-PUFA content in Longissimus dorsi muscle of all lambs was well above the 30 mg threshold for “omega-3 source” nutrition claim under the Australian Food Standards and Guidelines. Pasture type impacted the fatty acid contents in muscle, heart and kidney of prime lambs. Lambs grazing cocksfoot only had the highest 18:3n-3 (ALA) and n-3 LC-PUFA contents (67.1 mg/100g and 55.2 mg/100 g, respectively). Supplementation of pellets with or without oil infusion to grazing lambs decreased the ALA and n-3 LC-PUFA contents and increased n-6/n-3 ratio in Longissimus dorsi muscle. The fatty acid content in internal organs of grazing lambs was also affected by pellet supplementation. The liver and kidney of grazing lambs were both “good sources” (60 mg/100 g) of omega-3. The cocksfoot grass showed considerable potential for producing healthy, premium quality meat with high contents of n-3 and n-3 LC-PUFA which may consequently enhance the omega-3 intake of Australian lamb consumers.

Iron (Fe) and zinc (Zn) deficiency in cereal grains has deleterious effects on the health of millions of people, especially in developing countries. As wheat, as a staple crop, is consumed in large quantities, its micronutrient content is important. Crops in Africa are often grown under low nitrogen (N) and low phosphorous (P) conditions. The aim of this study was to determine the effect of low N and low P stress on Fe and Zn and phytic acid concentration, in two commercial spring wheat cultivars with excellent baking quality. The two cultivars did not differ significantly for the measured characteristics. Across all treatments the average values for Fe varied between 19.60-28.61 mg kg^-1, Zn between 17.68-33.79 mg kg^-1 and phytic acid between 5.03-6.92 mg g^-1. Low P stress lead to the highest values of Fe and Zn, and the lowest value for phytic acid. Phytic acid:Fe and phytic acid:Zn ratios were also highly significantly reduced under low P stress conditions. Low N conditions caused significantly increased Zn levels. Despite this, the phytic acid:Fe and phytic acid:Zn ratios were relatively high under all conditions, indicating a low bioavailability of both Fe and Zn in these wheat cultivars.

Aseptic implant loosening after total joint replacement is partially influenced by material-specific factors when cobalt-chromium alloys are used, including osteolysis induced by wear- and corrosion products, and stress shielding. Here, we aim to characterize a hybrid material consisting of alumina-toughened zirconia ceramics (ATZ) and additively manufactured Ti-35Nb-6Ta (TiNbTa), joined by a glass solder. The structure of the joint, static and fatigue shear strength, the influence of accelerated aging, and the cytotoxicity using an elution assay with human osteoblasts is characterized. Furthermore, the biomechanical properties of functional demonstrators of a femoral component for total knee replacements are evaluated. TiNbTa-ATZ specimens showed a homogenous joint with statistical distributed micro-pores and a slight accumulation of Al-rich compounds at the glass solder-TiNbTa interface. The static shear strength was 26.4 ± 4.2 MPa (Ti-ATZ reference: 38.2 ± 14.4 MPa, p = 0.117), all specimens survived 107 cycles of shear loading to 10 MPa, and aging did not reduce the strength. TiNbTa-ATZ did not impair the proliferation and metabolic activity of human osteoblasts. Functional demonstrators of TiNbTa-ATZ provided a maximum bearable extension-flexion moment of 40.7 ± 2.2 Nm. Biomechanical and biological properties of TiNbTa-ATZ demonstrate potential application for endoprosthetic implants.

Despite the lack of evidence that suggests hemodiafiltration (HDF) offers a better survival outcome than standard hemodialysis (HD), the number of patients initiating HDF in Japan continues to rise. This study examined the temporal change in the number of HDF incidents, evaluated factors associated with all-cause mortality, and compared the mortality risk and survival time of patient on HDF with patients receiving standard HD in three sets of 2-year cohorts. The primary analyses included the insurance claims data of 460 HDF patients and propensity score-matched 903 standard HD patients who initiated dialysis therapy between April 1, 2012 and March 31, 2018. Patient follow-up was censored at the time of death or the end of the 2-year study period. The influence of comorbidities on all-cause mortality was investigated, and the survival outcomes between HDF and standard HD patient groups throughout cohorts were compared. The number of HDF patients was increasing throughout cohorts, but the proportions of mortality cases across cohorts slowly decreased. Dementia status increases the mortality risk of patients regardless of dialysis modality. The mortality risk among HDF patients with dementia was more significant than HD patients. Adjusting for all covariates, we observed that HDF patients had a reduced mortality risk and longer survival time than patients on standard HD. This study supports the notion that HDF reduces all-cause mortality compared with standard HD in an incident dialysis population in Fukuoka Prefecture, Japan.

The objective of this study is to investigate the correlation between the advancement of flood research and the utilization of Geographic Information Systems (GIS) and multi-criteria evaluation techniques, both from a theoretical and practical standpoint. Additionally, this research seeks to identify potential ways to address the aforementioned relationship. The present study employs a thorough literature review methodology. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, a total of 28 papers were identified and included in the analysis, as they fulfilled the predetermined criteria. The findings of the study indicate that current research pertaining to the utilization of Geographic Information Systems (GIS) and multicriteria evaluation in flood control mostly centers around five key areas, namely natural factors, technical considerations, institutional factors, socio-economic factors, and financial factors. However, the aforementioned studies have identified specific areas of focus, including natural factors pertaining to climate, technical factors related to infrastructure, institutional factors concerning flood management strategies, socio-economic factors associated with demographics, and financial factors pertaining to financial obligations. However, there is a limited amount of existing research that specifically addresses flood management in developing nations. Therefore, it is anticipated that this study can serve as a valuable resource for future research endeavors, particularly in informing decision-making processes pertaining to the establishment of priorities in flood control plans. The primary subject of this study pertains to flood management occurrences within developing nations.

Environmental estrogen pollution and estrogen effects on the female reproduction system are well-recognized scientifically. Among the estrogens, 17 β-estradiol is a priority in environmental estrogen pollution, and it is also a major contributor to estrogen which regulates the female reproduction system. 17 β-estradiol is carcinogen and has a tumor promotion effect relating to breast cancer, lung cancer and others. It also affects the psychological well-being such as depression, fatigue and others. Thus, a simple method of detection of 17 β-estradiol will be important for both environmental estrogen pollution and women’s health care. This study demonstrates a simple-use, cost effective 17 β-estradiol biosensor system which can be used for both environment and women’s health care applications. The bio-recognition mechanism is based on the influence of the redox couple, K₃Fe (CN) ₆/K₄Fe (CN) ₆ by the interaction between 17 β-estradiol antigen and its α-receptor (ER- α; α-estrogen antibody). The transduction mechanism is an electrochemical analytical technique, differential pulse voltammetry (DPV). The levels of 17 β-estradiol antigen studied was between 2.25 pg/mL to 2,250 pg/mL, Phosphate buffered saline (PBS), tap water from the Cleveland regional water district, and simulate urine were used as the test media covering the potential application areas for 17 β-estradiol detection. An interference study by testosterone which has a similar chemical structure and molecular weight as those of 17 β-estradiol was carried out, and this 17 β-estradiol biosensor showed excellent specificity without any interference by similar chemicals.

A typical orchard's mechanical operation consists of three or four stages: lining, digging for plantation, moving the seedling from nurseries to the farm, moving the seedling to the planting hole, and planting the seedling in the hole. However, the digging the planting hole is the most time-consuming operation. In fruit orchards, robots' usage is increasingly becoming more prevalent to increase operational efficiency. They offer practical and effective services to both industry and people, whether they are assigned to plant trees, reduce the use of chemical fertilizers, or carry heavy loads to relieve staff. Robots can operate for extended periods of time and can highly adept at repetitive tasks like planting many trees. The present study aims to identify the locations for planting trees in orchards using geographic information systems (GIS), to develop an autonomous drilling machine and use the developed robot to open planting holes. There isn't a comparable study on autonomous hole planting in the literature in this regard. The agricultural mobile robot is a four wheeled nonholonomic robot with differential steering and forwarding capability to stable target positions. The designed mobile robot can be used in fully autonomous, partially autonomous, or fully manual modes. The drilling system, which is a y-axis shifter driven by a DC motor with reducer includes an auger with a 2.1 HP gasoline engine. SOLIDWORKS software was used for designing and drawing of the mobile robot and drilling system. The Microsoft Visual Basic.NET programming language was used to create the robot navigation system and drilling mechanism software. The cross-track error (XTE), which determines the distances between the actual and desired holes positions, was utilized to analyze the steering accuracy of the mobile robot to the drilling spots. Consequently, the average of the arithmetic means was determined to be 4.35 cm, and the standard deviation was 1.73 cm. This figure indicates that the suggested system is effective for drilling plant holes in orchards.

Asymptotic theories for fractional cointegrations have been extensively studied in the context of time series data, with numerous empirical studies and tests developed. However, most of the previously developed testing procedures for fractional cointegration were primarily designed for time series data. This paper proposes a generalized residual-based test for fractionally cointegrated panels with fixed effects. The test development is based on bivariate panel series with the regressor assumed to be fixed across cross-sectional units. The proposed test procedure accommodates any integration order between [0,1], and it is asymptotically normal under the null hypothesis. Monte Carlo experiments demonstrate that the test exhibits better size and power compared to a similar residual-based test across varying sample sizes.

Public transportation scheduling aims to optimize the allocation of transportation resources, enhance transportation efficiency, and increase passenger satisfaction, which is crucial for building a sustainable urban transportation system. As a complement to public transportation, shared bikes provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, such as peak usage periods in the morning and evening and significant fluctuations in demand across different areas, the optimization of shared bike dispatch can better meet user needs, thereby reducing vehicle vacancy rates and increasing operating revenue. Addressing this issue, this paper designs a comprehensive decision-making approach for spatio-temporal demand prediction and bike dispatch optimization. For demand prediction, we designed a T-GCN based bike demand prediction model. In terms of dispatch optimization, we considered factors such as dispatch capacity, distance restrictions, and dispatch costs, and designed an optimization solution based on genetic algorithms. Finally, this paper validates the approach using shared bike operating data, shows that T-GCN can effectively predict short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper, which combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.

In the last decades bioresorbable and biodegradable polymers have gained a very good reputation both in research and in industry thanks to their unique characteristics. They are, indeed, able to ensure high performances and biocompatibility, at the same time avoiding post-healing surgical interventions for devices removal. In the medical device industrial use of such biopolymers, it is widely known that product formulation and manufacturing need to follow specific procedures in order to ensure both proper mechanical properties and desired degradation profile. Moreover, also the sterilization method is crucial and its impact on physical properties is generally underestimated. In this work we focused our attention on the effect of different terminal sterilization methods on two commercially available poly(L-lactide-co-ε-caprolactone) with equivalent chemical composition (70% PLA and 30% PCL) and relatively similar initial molecular weight, but different chains arrangement and crystallinity. Results obtained show that crystallinity plays a key role, helping in preserving the narrow distribution of chains and, as a consequence, defined physical properties. These statements can be used as guidelines for a better choice of the most adequate biodegradable polymers in the production of resorbable medical devices.

Deep learning-based handwriting personality prediction uses neural networks (CNNs) to consider and predict personality characters from handwritten text to improve applications such as adaptive technology and automated data access. This method requires high computational resources and widely classified data, and its accuracy may suffer from signature variation and overfitting. This study introduces a novel optimizeddeep learning for Hand Written Personality Prediction. First the input data is collected from givendataset and an enhanced Gaussian filter is used in pre-processing to improve image quality by reducing noise and increasing contrast.After pre-processing, features are extracted by PCA-based normalized GIST, which standardizes the features to improve image representation.These extracted features are generated using an adaptive horse herd optimization algorithm to select the most important features. Based on selected features Improved Generative Adversarial Networks with artificial hummingbird optimization (IGAN_AHb) enables fast and efficient convergence of GANs. This reduce the mode collapse and ensures training with consistently fine-tuned parameters.The selected features are considered by characters such as openness, conscientiousness, extroversion, agreeableness and neuroticism, and finally classified using the IGAN_AHb classifier. In the result section, the proposed model is compared with various models with the matrix precision, recall, F1-score. The proposed model attained the value of 97.3% of precision and a recall rate of 96%, respectively. By comparing with other models, the proposed model attained highest values.

The progress in markerless technologies is bringing clinicians tools to rapidly evaluate tests such as Timed Up and Go (TUG) without compromising the time of the assessment, yet it raises questions about the potential trade-off in accuracy compared to traditional marker-based systems, suggesting that the precision of these evaluations is not yet conclusively established. The OpenCap system is an easy tool to process 3D kinematics with two iPhone cameras placed in front of the subject. Previous research has primarily focused on walking and movement towards the cameras with the subject facing the cameras (WF) and thus has been unable to disentangle the differences in the movement directions. We have compared the OpenCap system with a standard marker-based system for both walking directions. In OpenCap, we found significantly worse results capturing walking facing away from the cameras (RW). Compared to the marker-based system, our findings indicate troubles measuring kinematic parameters but provide good accuracy in measuring spatial-temporal parameters. These insights pave the way for refining markerless assessment technologies, potentially enhancing their utility in clinical settings.

Heat-stressed lactating dairy cattle exhibit unique metabolic symptoms; many of which are undoubtedly involved in heat-induced subfertility. Because of its known systemic effects, we hypothesized that γ-aminobutyric acid (GABA) participates in the regulation of insulin and progesterone during heat stress. Multiparous lactating Holstein cows (n=6) were studied during four experimental periods: 1) thermoneutral (TN; d 1-5), 2) TN + hyperinsulinemic-hypoglycemic clamp (d 6-10), 3) heat stress (HS; d 16-20), and 4) HS + euglycemic clamp (d 21-25). Blood samples were collected once daily via coccygeal venipuncture into heparinized evacuated tubes. Analysis of GABA concentrations from all four treatment periods yielded no differences. In direct comparison to TN concentrations, plasma GABA tended to be decreased during HS (16.57±2.64 vs 13.87±2.28 ng/ml, respectively, P = 0.06). Both milk production and plasma insulin were moderately correlated with plasma GABA (r=0.35, P<0.01; r = -0.32, P<0.01). Plasma progesterone was correlated with plasma GABA concentrations during TN but not HS. These results are the first to indicate that peripheral GABA could be involved in regulating aspects of production and reproduction during heat stress. More research is needed to determine its precise role(s).

The growth of two pairs of co-cultures (Escherichia coli/Geotrichum candidum, and Staphylococcus aureus/Geotrichum candidum) with a starter culture of lactic acid bacteria was studied in milk at temperatures related to artisanal cheesemaking ripening. For an inoculum of approximately 106 CFU/mL, LAB not only induced an early stationary phase of E. coli (two strains BR and PS2) and S. aureus (strains 2064 and 14733) but affected their death phase. G. candidum was found to be the subject of interactions with LAB within a given temperature range only partially. To develop a tertiary model for the growth curves of the populations, a one-step approach was used, combining two types of primary models (Huang and Gimenez and Dalgaard) with secondary square root models for growth rate and lag time. Furthermore, the reparametrized Gompertz-inspired function with the Bigelow secondary model was used to describe the death phase of the E. coli and S. aureus strains. The prediction ability of the growth of the H-GD tertiary model for co-cultures was cross-validated within the strains and data sets in milk and milk medium with 1 % NaCl.

Petit vert (scientific name: Brassica oleracea var. gemmifera DC. × Brassica oleracea var. acephala DC.) is a new variety of vegetable created by crossbreeding kale and brussels sprouts (Brassica oleracea species). The present study aimed to identify biologically active compounds in extracts of the outer leaves of Petit vert by purification and to examine their biological activities. Dried and powdered outer leaves of Petit vert were extracted, fractionated, and purified to isolate active compounds. Nuclear magnetic resonance and mass spectrometries were performed to elucidate the structures of five compounds (1‒5). The compounds isolated from Petit vert leaves were glycosides that contained kaempferol, quercetin (flavonol), or sinapinic acid (phenylpropanoid).　Glucose uptake in cultured C2C12 murine myoblasts in the absence of insulin was significantly increased by these compounds, kaempferol, sinapic acid, and ferulic acid, while that in the presence of insulin was also significantly increased by compounds 3 and 4, kaempferol, and sinapic acid. The present study reports for the first time the isolation of five compounds containing sinapic acid from the outer leaves of Petit vert and their stimulation of glucose uptake in cultured C2C12 murine myoblasts. The results obtained herein suggest the potential of these compounds to effectively attenuate hyperglycemia and maintain muscle strength by promoting glucose metabolism in muscle cells.

RM (red mud) was acidified with sulphuric acid and the acidified ARM (acidified red mud) was utilized as an innovative adsorption material for treating antibiotic-contained wastewater. The adsorption conditions, kinetics, isotherms, thermodynamics, and mechanism of ARM for CIP (ciprofloxacin) were investigated. Characterization of the ARM involved techniques such as scanning electron microscopy(SEM), transmission electron microscope(TEM), brunauer- emmett-teller (BET), X-ray diffraction (XRD), X-ray fluorescence (XRF), thermogravimetric analysis (TGA) and NH3-TPD analysis. Adsorption studies were conducted employing response surface methodology (RSM) for experimental design. The results showed that ARM can absorb CIP effectively. The RSM optimal experiment indicated that the most significant model terms influencing adsorption capacity were solution pH, CIP initial concentration and ARM dosage, under which the predicted maximum adsorption capacity achieved 7.30 mg/g. The adsorption kinetics adhered to a pseudo-second-order model, while equilibrium data fitted the Langmuir-Freundlich isotherm, yielding maximum capacity values of 7.35 mg/g. The adsorption process occurred non-spontaneously and absorbed heat, evidenced by ΔG0 values between 2.06 and 0.87 kJ/mol, ΔS0 at 39.41 J/mol/K, and ΔH0 at 13.8 kJ/mol. Analysis using attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) indicated there existed complex reaction between Al-O in ARM and the ester group –COO in CIP. The C=O bond in CIP was likely to undergo a slight electrostatic interaction or be bound to the internal spherical surface of ARM. The findings indicate that ARM is a promising and efficient adsorbent for CIP removal from wastewater.

Monometallic (Ni, Co, Cu) and bimetallic (Ni-Co, Ni-Cu) 10-20 wt. % metal containing catalysts supported on fly ash zeolite were prepared by post-synthesis impregnation method. The catalysts were characterized by X-ray powder diffraction, N2 physisorption, XPS and H2-TPR methods. Finely dispersed metal oxides and mixed oxides were detected after the decomposition of impregnating salt on the relevant zeolite support. By reduction intermetallic, NiCo and NiCu phases were identified in the bimetallic catalysts. Hydrogeoxygenation of lignocellulosic biomass-derived levulinic acid to γ-valerolactone (GVL) was studied. Bimetallic, 10 wt. % Ni, 10 wt. % Cu or Co containing fly ash zeolite catalyst showed higher catalytic activity than monometallic ones. Their selectivity to GVL reached 70-85 % at 100 % conversion. The reaction proceeds through formation of 4-hydroxy pentanoic acid, as the only intermediate compound.

Biomass as a whole offers a more diverse potential for valorisation than any other renew-able energy source. As one of the stages in the separation of bio-oil involves the liquid mixture of acetol and acetic acid, and as both components are particularly well suited for valorisation, a hybrid method has been developed for their separation with a high purity level through an approach combining liquid-liquid extraction and rectification. In order to design and simulate the flowsheet, the ChemCAD 7.0 simulation software has been used. Sensitive analyses have been carried out to investigate the influence of the different pa-rameters in the rectification columns such as the reflux ratio, the feed stage location, and the vapour/bottom molar flow ratio. The effect of different extractants and of their excess on the separation process as well as the possibility of regenerating the extractant has also been studied. Tri-n-octylamine has accordingly been selected as a separating agent which has been fully recycled. The end result for separating an initial 48/52 wt% ace-tol/acetic-acid liquid mixture has been acetol with a purity of 99.4 wt% and acetic acid with a purity of 100 wt%.

Plastic materials have revolutionized modern life, particularly in the domain of food packaging, owing to their versatility, lightweight nature, and ease of processing. However, the environmental ramifications of non-degradable plastics have raised concerns. Polylactic acid (PLA), derived from renewable sources, presents a sustainable alternative due to its biodegradability and exceptional barrier, mechanical, and safety properties. Nevertheless, the high UV transmittance of PLA limits its use for photosensitive food and pharmaceutical packaging, where UV radiation can lead to nutritional loss and spoilage. Various methods have been explored to enhance the UV-blocking capabilities of PLA, including the integration of inorganic nanoparticles and surface coatings. Despite advancements, these approaches often compromise the inherent transparency of PLA. Incorporating large conjugated groups can maintain transparency but introduces additional challenges. This paper reviews modification methods to enhance PLA's UV-barrier properties and anticipates its expanded utility in food and drug packaging, promoting UV resistance and diversifying PLA's applications.

Lysophosphatidic acid (LPA) is a promising biomarker candidate to screen for ovarian cancer (OC) and potentially stratify and treat patients according to disease stage. LPA is known to target actin-binding protein gelsolin that is a key regulator of actin filament assembly. Previous studies have shown that the phosphate headgroup of LPA alone is inadequate to bind to the short chain of amino acids in gelsolin known as the PIP2-binding domain. Thus, the molecular-level detail of the mechanism of LPA binding is poorly understood. Here, we model LPA binding to the PIP2-binding domain of gelsolin in the gelsolin-actin complex through extensive ten microsecond atomistic molecular dynamics (MD) simulations. We predict that LPA binding causes a local conformational rearrangement due to LPA interactions with both gelsolin and actin residues. These conformational changes are a result of the amphipathic nature of LPA, where the anionic phosphate, polar glycerol and ester groups, and lipophilic aliphatic tail mediate LPA binding via charged electrostatic, hydrogen bonding, and van der Waals interactions. The negatively-charged LPA headgroup binds to the PIP2-binding domain of gelsolin-actin while its hydrophobic tail is inserted into actin, creating a strong LPA-insertion pocket that weakens the gelsolin–actin interface. The computed structure, dynamics, and energetics of the ternary gelsolin–LPA–actin complex confirms that a quantitative OC assay is possible based on LPA-triggered actin release from the gelsolin-actin complex.