Lung cancer (LC) stands as the foremost cause of cancer-related fatality rates worldwide. Early diagnosis significantly enhances patient survival rate. Nowadays, low dose computed tomography (LDCT) is widely employed on chest as a tool for large-scale lung cancer screening. Nonetheless, a large amount of chest radiographs causes an onerous burden on radiologists. Some computer-aided diagnostic (CAD) tools can provide insights to medical images for diagnosis and augmenting diagnostic speed. However, due to variation in parameter settings across different patients, substantial discrepancies in image voxels persist. We find different voxel-size causing a compromise between model generalization and diagnostic efficacy. This study investigates the performance disparities of diagnostic models trained on original images and LDCT images reconstructed to different voxel-sizes but isotropic. The application is to differentiate a nodule to be benign or malignant. Using 11 features, a support vector machine (SVM) is trained on LDCT images with an isotropic voxel having side-length of 1.5 mm for 225 patients in house. The result yields a favorable model performance with an accuracy of 0.9596 and an area under the receiver operating characteristic curve (ROC/AUC) of 0.9855. In addition to furnish CAD tools for clinical applications, future research is encouraged to include LDCT images from multi-centers.

Grape pomace is a byproduct of wineries and sustainable source of bioactive phenolic compounds. Encapsulation of phenolics with a well-chosen coating may be a promising means of delivering them to the intestine, where they can then be absorbed and exert their health-promoting properties. Ionic gelation of grape pomace extract with natural coatings (sodium alginate and its combination with maltodextrins, gelatin, chitosan, tragacanth gum, and gum arabic) was performed, and the resulting hydrogel microbeads were then air-, vacuum-, or freeze-dried to prevent their spoilage. The physicochemical characterization (size, shape, texture, and morphology) of the microbeads and the in vitro release of phenols from microbeads were studied and a good relationship between them was established. Freeze-dried microbeads showed the highest cumulative release of phenols as in the intestinal phase (23.31 – 43.27 mgGAE/gMB), followed by vacuum-dried (23.31 - 35.41 mgGAE/gMB) and air-dried (22.74 – 31.38 mgGAE/gMB), while the most suitable release dynamics in the intestinal phase were observed for alginate-based microbeads combined with gelatin (58.4 %), gum arabic (34 %) and 1.5 % w/v chitosan (15.3 %). The results highlight the importance of developing encapsulated formulations containing a natural source of bioactive compounds that can be used in various functional foods and pharmaceutical products.

Here we mathematically model black holes following dynamics similar to RC electrical model, focusing on their similarities at the singularity. We use this mathematically modelling to hypothesize the origin and growth of a black Hole. Or model consists of several steps defined by: (1) the formation of a black hole following general relativity equations; (2) growth of the black hole modelled as a resistance-capacitance-like electrical circuit. Based on the mathematical modeling of a black hole following dynamics similar to an RC circuit, for a circular motion with constant acceleration, in which the condition is fulfilled, Vt = ω r, we are going to calculate the amount of dark matter in the Milky Way galaxies and the Andromeda galaxy and subsequently the rotation curve of both galaxies to compare them with observed or measured values.

This paper evaluates norms and assesses the level of knowledge in air conditioning project management within the construction industry. A total of 25 questions were distributed to multiple candidates, who were filtered based on pre-established inclusion and exclusion criteria. Thirty-nine candidates were ultimately approved to participate in the survey. The questions were designed to address five hypotheses, with each set of five questions corresponding to one hypothesis. The results were obtained after pre-processing the data using Matlab software. The data was pre-processed using Matlab software, and the results were analyzed using the Delphi method. The analysis revealed that only two hypotheses were approved: No matter whether there are nationalized safety rules or not, the impact of data sciences and smart technologies, including air conditioning management systems, is critical for human life in the building business.

Background: One of the main diseases of worldwide concern is non–insulin dependent Diabetes mellitus. 90-95% of patients with diabetes suffers from Type II diabetes, a metabolic diabetes whose prevalence is increasing in the world.Given the current prevalence of diabetes type II in society, research of natural compounds able to regulate glycaemia and insulin–resistance is nowadays covering importance, as alternative or co–adjuvant treatment to existing hypoglycaemic medicines. In pre–clinical steps of research, C. elegans is considered a promising in vivo model for the study of the molecular mechanism of glucose as part of anti–diabetic bioactivity.Most of the studies of insulin resistance with this in vivo model are carried out by using mutant strains such as daf-2 and the effects of the compounds are attributed a posteriori, after a physiological response of the worms rather than directly measuring preservation of activity inside the worm. Methods: The in vitro α-glucosidase inhibition of two oral formulations with Origanum vulgare extract before and after a simulated process of gastrointestinal digestion was evaluated. After confirming the in vitro activity, the α-glucosidase inhibition was tested in vivo through the new method proposed. Results: The crude extract showed an IC50 value similar to acarbose (positive control), before and after the gastrointestinal digestion. The encapsulated extract (111.86±1.25 µg/mL) did not present statistical differences with the positive control (110.10±1.15 µg/mL) after digestion. However, the powder formulation showed the highest hypoglycaemic activity (59.55±0.85 µg/mL).In vivo, the IC50 values showed similar profile than in vitro. Conclusion: A new simple and reliable method has been developed to determine pharmacological activities inside in vivo model C. elegans.The method has been evaluated with a hydroalcoholic extract of O. vulgare. The method is accurate and valid for the quantification of the inhibition of in vivo, allowing the direct attribution of this in vivo hypoglycaemic activity to the treatment. In addition, it opens the door to further research into in vitro pharmacological activities that require an in vivo counterpart.

To handle the problem of solving the results of aircraft’s visual navigation with scene matching, this paper take the measure of the spherical EPnP positioning posture solving by measuring the central angle threshold value and approaches for constructing a measuring model. The detailed steps are as follows: firstly, this approach needs to construct a positioning coordinate model for the earth surface, makes sure the expression for the 3-dimensional coordinate of the earth surface and solves the positioning of constructing data model with EPnP positioning posture solving algo-rithm. Secondly, by contrasting and analyzing the positioning posture value of approximate plane coordinates, the critical value is acquired, which can be recognized as plane calculation. Lastly, this method should construct a theoretical model of measurement for the visual height and central angle with the decided central angle threshold value. The simulation experiment shows that the average positioning precision of taking the spherical coordinates as input is 16.42 percent way higher than taking the plane coordinates as input. When the central angle is less than 0.05 degrees and the surface district is less than 5585 square meters, the positioning precision of the plane co-ordinates is pretty much equal to the spherical coordinates. At this moment, the sphere can be seen as flat. The conclusion of this essay can theoretically guide the further study of positioning posture solving of the scene matching, which is also of vital significance for theory research and engineering application.

In this paper, we introduce as a pedagogical strategy an internal division-free, straightforward, and symmetrically progressing algorithm in manually computing matrix inverse and solving systems of linear equations by revisiting the application of elementary row operations in the Gauss-Jordan reduction method and connecting it to the determinant method. The proposed cross-multiplication-flip (CMF) algorithm employs cross-multiplication similar to the butterfly movement in computing determinants as a strategic application of elementary row operations to efficiently reduce the rows and then applies flipping of rows and entries to put an upper triangular matrix into lower triangular form to continue the reduction process.

In this work, a novel silane coupled cationic precursor (SAGS) was synthesized by 3-glycidyloxypropyltrimethoxysilane and sodium 2-((2-aminorthyl)amino) ethanesulfonate. A series of cation exchange membranes were prepared with poly(vinyl alcohol) (PVA) and SAGS by sol-gel process. The structure of the prepared membranes were characterized by fourier transform infrared spectrum (FTIR) and scanning electron microscopy (SEM), and its properties were studied by water uptake (WR), cation exchange capacity (CEC), linear expansion ratio (LER), alkali stability, thermogravimetric analysis (TGA), mechanical properties and diffusion dialysis performance. FTIR and X-ray photoelectron spectroscopy (XPS）confirmed the successful preparation of SAGS membranes, and SEM images showed that the prepared membranes were dense and uniform. The WR values of the SAGS membranes were in the range of 91.49-122.39 %, and the LER values were 17.65-28.21 %. In addition, the SAGS membranes had suitable CEC value, good alkali resistance and thermal stability which ensured the application of membranes in the field of diffusion dialysis (DD) for alkali recovery. In DD test, the dialysis coefficients of NaOH (UOH) ranged from 0.012 mm/h to 0.023 mm/h, and the separation factors (S) was in the range of 30.77-16.43. In summary, the prepared membrane had good performance and simple preparation process, which had great application potential in textile industrial wastewater recovery.

Background: Corrosive injuries (CI) became medical problems related complications include esophageal, pyloric stricture, squamous cell carcinoma [1], physical and quality of life [2]. Endoscopic dilatation (ED) is primary therapy [3]. The ultrathin endoscope assisted method is potentially safe and useful in avoiding technical failure [4]. Methods: Retrospective study of esophageal and/or pyloric stricture after CI who underwent di-latation at Soetomo General Hospital (July 2018 – July 2022). One-biweekly ED using Ultrathin Endoscope Assisted Method then continued by Through The Scope (TTS) balloon or Bougie dila-tor. Target diameter is 14mm. Clinical outcome included successful, refractory, recurrent rate and complications related procedures Results: Fifteen patients with stricture related CI. Eleven patients underwent ED with total 73 procedures. Mean age 31,45 years, Male 6(54,6%), suicide attempt 7(63,6%), acid agent 9(81,8%) located at esophagus 3(27,3%), pylorus 3(27,3 %), or both 5(45,4%). Number of esophageal dilata-tion to achieve target 14mm was 1-2 and 2-15 procedures for simple and complex stricture with overall successful, recurrent and refractory rate were 75%, 12.5% and 12.5% respectively. Pyloric dilatation outcome were 62.5%, 25% and 12.5% for successful, recurrent and refractory rate re-spectively. Conclusions: Stricture-related corrosive injury has predominantly complex anatomical structure, more sessions are required and lower clinical outcome

Antimicrobial peptides (AMPs) are a promising alternative to antibiotics to combat drug resistance in pathogenic bacteria. However, the development of AMPs with high potency and specificity remains a challenge, and new tools to evaluate antimicrobial activity are needed to accelerate the discovery process. As a step toward direct prediction of the experimental minimum inhibitory concentration (MIC) of AMPs, we proposed MBC-Attention, a combination of a multi-branch CNN architecture and attention mechanism. Using a curated dataset of 3929 AMP against Escherichia coli, the optimal MBC-Attention model achieved an average Pearson correlation coefficient of 0.775 and an RMSE of 0.533 (log μM) in three independent tests of 393 sequences each. This results in a 5–12% improvement in PCC and 7–13% improvement in RMSE compared with RF and SVM models. Ablation studies confirmed that both attention mechanisms contributed to performance improvement.

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

The three-dimensional structure of Gulf of Mexico’s warm-core rings, detaching from the Loop Current, is investigated using satellite altimetry and a large set of ARGO float profiles. Reconstruction of the Loop Current rings (LCRs) vertical structure from sea surface height observations is made possible by the use of the gravest empirical modes method (GEM). The GEMs are transfer functions that associate a value of temperature and salinity for each variable pair {dynamic height;pressure}, and are computed by estimating an empirical relationship between dynamic height and the vertical thermohaline structure of the ocean. Between 1993 and 2021, 40 LCRs were detected in the altimetry and their three-dimensional thermohaline structure was reconstructed, as well as a number of dynamically relevant variables (geostrophic and cyclogeostrophic velocity, relative vorticity, potential vorticity, available potential energy and kinetic energy density etc.). The structure of a typical LCR was computed by fitting an analytical stream function to the LCRs dynamic height signature and reconstructing its vertical structure with the GEM. The total heat and salt contents and energy of each LCR were computed and their cumulative effect on the Gulf of Mexico’s heat, salt and energy balance is discussed. We show that LCRs have a dramatic impact on these balances and estimate that residual surface heat fluxes of -13 Wm−2 are necessary to compensate their heat input, while the fresh water outflow of the Mississippi river approximately compensates for their salt excess input. An average energy dissipation of O[10−10−10−9] Wkg−1 would be necessary to balance their energy input.

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

Objectives: Few studies in literature evaluate the "mean measure" of root divergence. Most of them are linear measurements, they hardly describe the dental furcation conformation. It is left to the subjectivity of the operator deciding whether a furcation is convergent or divergent. The goal of this study is to create a visual evaluation method to overcome these problems giving a conformation of the entire interradicular space. Material and methods: A user-friendly software (Paint®, Windows10®) was used to measure endo-oral radiographs of upper and lower molars. Three kinds of measurements were taken. Three operators used the software to measure 20 radiographs, then the technique was repeated on 250 radiographic images to identify an average measurement. The ratio of these three measurements allowed to develop a new visual evaluation method of the interradicular space. Results: Intra and inter-operator reproducibility was statistically assessed on a sample of 20 anonymous endo-oral radiographs measured by 3 blind operators. Then, a sample of 250 anonymous endo-oral radiographs were measured by a blind operator and were statistically evaluated to identify an average value to define a main conformation of the interradicular space. Measurements made by the 3 operators on the 20 radiographic images showed that the technique is reproducible, and a mean value of the interradicular space was obtained. Conclusions: A new anatomical evaluation of the interradicular space in its entirety, which could help the clinicians in the therapy of furcated molars, can be obtained.

Nowadays, wearable devices for human health monitoring are increasingly become popular and widely used. Typically, the wearable device is small size and operates with batteries. Therefore, the wearable device acquires bio-signals and transfers to smartphones or personal computers (PC) via WiFi/ Bluetooth for processing data. To reduce power consumption is one of the most important challenges of designing wearable devices. To solve this problem, the proposed signal quality valuation (SQV) method can be select the high-quality signal and reduce the transfer time to other devices. In this paper, the proposed SQV and data compression method rely on real-time PPG signals analysis to retain important information of PPG signal, improve performance and power consumption of PPG devices. Besides, we also proposed Heuristic rules for heart rate (HR) estimation with compression data. The experimental results show that the highest compression ratio (CR) is 387.8 with BIDMC Physionet database (sampling frequencies of 125 Hz) and HR error as 1.43 bpm for averaging absolute error (avAE), the standard deviation absolute error (sdAE as 0.4) and relative error mean (avRE as 0.019). The proposed real-time PPG measurement system (sampling frequency as 100/ 200/ 400 Hz) reduce power consumption and open the new structure for healthcare application systems

This article discuss the estimation of electrical stresses input that is required to determine lifetime degradation of the HV cables installed within overhead transmission lines (OHTL’s). Abort from lightning effects, these electrical stresses are mainly generated due to repetitive switching operation of the transmission line that produces transient overvoltage (TOV) stress and high frequency stress. The transient overvoltage (TOV) due to switching-off the transmission line at the interface points between the cable and OHTL is estimated using artificial neural network (ANN). PSCAD software is used to build the transmission line model for 749 different case in order to build the required database for ANN training. Two different algorithm input to train ANN with one hidden layer and one output layer using different number of nodes are modeled in MATLAB. The results performance is continuously compared and evaluated till acceptable Regression is achieved to insure the error is less than +/-1.5%. The high frequency due to switching-on the transmission line is also recorded and analyzed. The results show that this new method is efficient, accurate and useful as there is no cable monitoring system is available for each HV cable installed within the transmission line.

In dry season paddy farming, the alternate wetting and drying (AWD) irrigation improves water productivity, paddy production, and has the potential to decrease greenhouse gas (GHG) such as methane (CH4) and nitrous oxide (N2O) emissions when compared to continuous flooding (CF). However, there is a lack of research in Bangladesh on the effects of water management on CH4 and N2O emissions. During November 2017–April 2018, participatory on-farm trials were conducted at Feni and Chattogram districts of Bangladesh. Total 105 farmers comprising 20-hectare of land (62 farmers at Feni and 43 farmers at Chattogram district, each location having 10 hectare of land). We compared irrigation water and cost reductions, paddy yield, and CH4 and N2O emissions from paddy fields irrigated using AWD and CF irrigation methods. The CH4 and N2O emissions were determined using the Cool Farm Beta-3 methodology, and the global warming potential (GWP) was estimated using the Intergovernmental Panel on Climate Change-2014 standard approach. The mean results of randomly selected 30 farmers from two locations (15 of each) showed that AWD remarkably decreased irrigation water consumption by about 24% and increased water productivity by 224%. We estimated 23% savings for irrigation costs in AWD. By this time, AWD improved paddy production by 3% over CF. The AWD irrigation resulted in a 47% reduction in cumulative CH4 emissions having a lower CH4 emission factor (0.74 kg ha-1 day-1) than CF (1.39 kg ha-1 day-1). There was no obvious difference in N2O emission between AWD and CF. When compared to CF, AWD decreased the overall GWP by 27% and lowered the GHG intensity by 42%. The CH4 and N2O emissions did not differ substantially between Feni and Chattogram.

African swine fever (ASF) is one of the major threats to pig production, and real-time PCR (qPCR) protocols are integral part of ASF laboratory diagnosis. With the pandemic spread of ASF, commercial kits have risen on the market. In Germany, the kits have to go through an approval process and thus, general validation can be assumed. However, they were never compared to each other. In this study, 12 commercial PCR kits were compared to an OIE recommended method. Samples representing different matrices, genome loads, and genotypes were included in a panel that was tested under diagnostic conditions. The comparison included user-friendliness, internal controls, and the time required. All qPCRs were able to detect ASFV genome in different matrices across all genotypes and disease courses. With one exception, there were no significant differences when comparing the overall mean. The overall specificity was 100 % [95 % CI 87.66 - 100], and the sensitivity was between 95 % and 100 % [95 % CI 91.11 - 100]. As can be expected, variability concerned samples with low genome load. Concluding, all tests were fit for purpose. The test system can therefore be chosen based on compatibility and prioritization of the internal control system.

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

The instability of traveling pulses in nonlinear diffusion problems is inspected on the example of Gunn domains in semiconductors. Mathematically the problem is reduced to the calculation of the "energy" of the ground state in Schrödinger equation with a complicated potential. A general method to obtain the bottom-part spectrum of such equations based on the approximation of the potential by square wells is proposed and applied. Possible generalization of the approach to other types of nonlinear diffusion equations is discussed.

Rail transit tunnels span long distances, are large-scale structures and pass through complicated geological conditions; thus, the risk of uneven settlement cannot be ignored. To address this issue, a method for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed in this study. First, distributed optical fiber sensing technology is implemented to obtain a massive amount of strain data from densely distributed measurement points along regional railway tunnels, and a method for determining the intervals of strain measurement points with strong spatial correlations is proposed based on a support vector machine. Second, combined with the statistical analysis of the influence range of the uneven settlement of a tunnel, an algorithm for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed; this approach realizes the accurate identification of the uneven settlement area of long-distance urban railway tunnels. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual tunnel data.

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, the different quality of language use across sources, present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research, aimed at the Southern Balkans and Coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “Expert-Apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a Machine Learning (ML) algorithm, utilizing a combination of Active Learning (AL) and Reinforcement Learning (RL), and the Expert is the human researcher. ML-powered research improved 3.1 times the effectiveness and 5.14 times the efficiency of the domain expert, fetching a total number of 420 relevant ethnopharmacological documents in only 7 hours versus an estimated 36-hour human-expert effort. Therefore, utilizing Artificial Intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

To better understand the genes with altered expression caused by infection with the novel coronavirus strain SARS-CoV-2 causing COVID-19 infectious disease, a tensor decomposition (TD)-based unsupervised feature extraction (FE) approach was applied to a gene expression profile dataset of the mouse liver and spleen with experimental infection of mouse hepatitis virus, which is regarded as a suitable model of human coronavirus infection. TD-based unsupervised FE selected 134 altered genes, which were enriched in protein-protein interactions with orf1ab, polyprotein, and 3C-like protease that are well known to play critical roles in coronavirus infection, suggesting that these 134 genes can represent the coronavirus infectious process. We then selected compounds targeting the expression of the 134 selected genes based on a public domain database. The identified drug compounds were mainly related to known antiviral drugs, several of which were also included in those previously screened with an in silico method to identify candidate drugs for treating COVID-19.

A novel, rapid and sensitive liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed and validated for the evaluation of OTS167 pharmacokinetics in mouse serum. SN-38 was optimized to be selected as the internal standard. Chromatographic separation was performed on a BDS Hypersil C18 column (100 x 2.1 mm, 5 µm) using gradient elution with mobile phase solvent A as water containing 0.1% formic acid and solvent B as acetonitrile containing 0.1% formic acid. The analysis was carried out using multiple reaction monitoring (MRM) with a triple-quadrupole mass spectrometer operated in the positive electrospray ionization mode. Mass transitions of 487.2 > 348.0 and 393.2 > 349.2 were monitored for OTS167 and SN-38 respectively. The standard calibration curve demonstrated high linearity at a range of 5-1000 ng/mL, with a coefficient of determination (r2) ≥ 0.996. The accuracy for OTS167 ranged from 92.3% to 102.2% and the precision was ≤ 12.7%. Recovery was consistent at about 83% to 89%. No significant matrix effect was observed. This method was successfully applied to monitor the pharmacokinetic profiles in mice over 24 h after ingestion of 5 mg/kg of OTS167. Maximum serum concentrations (3197 ng/mL) of OTS167 was observed at 1.67 hour after OTS167 ingestion via garage at 5 mg/kg and area under the curve (AUC) was 28579 h*ng/mL, suggesting that OTS167 can be quickly absorbed after oral administration.

A sensitive and robust liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed and validated for the determination of nimbolide in mouse serum. Exemestane was used as the internal standard (IS). Here, we employed acetonitrile-based protein precipitation (PPT) for serum sample preparation, and performed chromatographic separation using an ODS Hypersil C18 column (100×2.1 mm, 5µm) with gradient elution (0.1% formic acid in water vs 100% acetonitrile). The run time was 6 min. Instrumental analysis was performed by electrospray ionization tandem mass spectrometry (ESI-MS/MS) in the multiple-reaction monitoring (MRM) under positive mode. A good linear calibration was achieved in the 5–1000 ng/ml range. The intra- and inter-day precisions for nimbolide were ≤ 12.6% and ≤ 13.9 % respectively. Intra-day accuracy ranged from 96.9% – 109.3% while inter-day accuracy ranged from 94.3% – 110.2%. The matrix effect of nimbolide, detected but consistent at low and high concentrations, do not affect linearity of standard curve. In conclusion, we have developed and validated a sensitive analytical method for determination of a novel natural compound nimbolide in mouse serum and it has been successfully applied to our preclinical study in investigating the pharmacokinetic properties of nimbolide, which could greatly facilitate the preclinical development of the promising lead compound for anticancer therapy.

Wind turbine upgrades have been spreading in the recent years in the wind energy industry, with the aim of optimizing the efficiency of wind kinetic energy conversion. This kind of interventions has material and labor costs and it is therefore fundamental to estimate realistically the production improvement. Further, the retrofitting of wind turbines sited in harsh environments might exacerbate the stressing conditions to which wind turbines are subjected and consequently might affect the residue lifetime. This work deals with a case of retrofitting: the testing ground is a multi-megawatt wind turbine from a wind farm sited in a very complex terrain. The blades have been optimized by installing vortex generators and passive flow control devices. The complexity of this test case, dictated by the environment and by the features of the data set at disposal, inspires the formulation of a general method for estimating production upgrades, based on multivariate linear modeling of the power output of the upgraded wind turbine. The method is a distinctive part of the outcome of this work because it is generalizable to the study of whatever wind turbine upgrade and it is adaptable to the features of the data sets at disposal. In particular, applying this model to the test case of interest, it arises that the upgrade increases the annual energy production of the wind turbine of an amount of the order of the 2%. This quantity is of the same order of magnitude, albeit non-negligibly lower, than the estimate based on the assumption of ideal wind conditions. Therefore, it arises that complex wind conditions might affect the efficiency of wind turbine upgrades and it is therefore important to estimate their impact using data from wind turbines operating in the real environment of interest.

Nowadays, the study of preparing silica/rubber composites, which can be used in “green tire”, in energy saving method is fast-growing. In our work, silica modified by using alcohol polyoxyethylene ether (AEO) and 3-Mercaptopropyltriethoxysilane (K-MEPTS) together were investigated. Thermal gravimetric analyzer (TGA) result indicated that both AEO and K-MEPTS could be grafted on the silica surface. Raman spectroscopy confirmed that the AEO could generate a certain steric hindrance for the mercaptopropyl group on K-MEPTS. Silica modified by using AEO and K-MEPTS together can be completely co-coagulated with the rubber in preparing silica/natural rubber (NR) composites by latex compounding method. AEO can form a physical interface between silica and rubber; meanwhile, K-MEPTS can form a chemical interface between silica and rubber. The effects of chemical and physical interface between silica and rubber on dynamic and mechanical performances of silica/NR composites were also given in this research. A proper combination of physical and chemical interface between silica and NR can improve performances of silica/NR composites.

Thin films (100-400 nm) of Ba_xSr_1-xTiO₃ (0≤x≤1) deposited in RF-magnetron co-sputtering equipment are presented in this research work. The change of deposition rate, gap energy, and resistivity as a function of temperature- applied power change in the growth parameters was studied through the ISO colour-code lines constructed with MATLAB: By analysing the trend information and take into account the influence of the calculated "x" parameter with the Boltzmann profile fitting is proposed a method to allow a controlled set up of the RF-magnetron co-sputtering system and predict the E_g and resistivity values in the Ba_xSr_1-xTiO₃ solid solution with 0≤x≤1 for amorphous and crystalline phases. Also, a versatile tool to optimise the deposition process and material properties.

That how to improve the sensitivity and the detection ability of the Large-caliber sensor is critical to satisfy the requirement of heavy vehicle wear condition monitoring. In this paper, we introduced the LC resonance principle to the design of sensor with large flow channel (7mm). The resonant exciting coil increases the impedance change of the exciting circuit caused by wear particles which magnify the current difference between the two exciting coils and improve the sensitivity of the sensor. The resonant induction coil greatly suppresses the interference signals and magnifies the weak induced electromotive force which is beneficial to enhance the detection ability. In order to boost the detectability for different materials particles, a phase controlled variable-frequency exciting system (PCVFES) was adopted to automatically switch the exciting frequency between 284kHz for ferromagnetic particles and 420KHz for non-ferromagnetic particles. For the weak signal detection, based on the essential characteristic of the signal, we apply a simpler method that modified lock-in amplifier (MLIA) rather than the conventional algorithms (Wavelet transform, EMD). Results show that using these methods the sensitivity and the detection ability of the sensor are significantly improved and the 75μm iron particles and 220μm copper particles were successfully detected which realizes the initial abnormal wear monitoring for the large flow project.

Dynamic virtual testing by Hardware in the Loop (HIL) real time simulation systems is common to minimize physical tests to validate and verify control algorithms, logics and software, under normal and emergency conditions. The accurate but costly HIL models setup activities could have an extended use to simulate faulty conditions that are seldom observable in the real system, yet they must be detected in advance and recognized. Data driven diagnostic methods have reached a mature development, in various sectors, proving effective in early detecting slowly varying deviations from nominal patterns of signals, even without a priori knowledge of their nature and behavior. These methods rely on vast amount of data logged from real systems that are ever and ever richer of monitoring telemetries that are worth being exploited. However, due to the usually reliable and safe systems being managed, it is often difficult to collect enough data on anomalous situations to validate fault detection and isolation and limit false positives. HIL model-based simulations allow generating and observing operational domains or transients rarely observed in real operations. This allows identifying the signals that are most correlated to faults and that could be selected to setup data-based diagnostic models of parts or subsystems, which are more suitable than the whole HIL model for online diagnostics, as well as to identify the features and trends that are most symptomatic of anomalous conditions.

The injury causes resistance in human gastric cancer (GC). This Adverse Outcome Pathway (AOP) entitled “Increases in cellular reactive oxygen species (ROS) and chronic ROS leading to human treatment-resistant gastric cancer (GC)” consists of molecular initiating event (MIE) as “Increases in cellular ROS” and “Chronic ROS”, followed by series of key events (KEs); “porcupine-induced Wnt secretion and Wnt signaling activation”, “beta-catenin activation”, “epithelial-mesenchymal transition (EMT), and adverse outcome (AO) as “human treatment-resistant GC” in the sequence. ROS has multiple roles in disease such as development and progression of cancer, or apoptotic induction causing anti-tumor effects. In this AOP, we focus on the role of sustained levels of chronic ROS to induce the therapy-resistance in human GC. EMT, which is cellular phenotypic change from epithelial to mesenchymal-like features, demonstrates cancer stem cell (CSC)-like characteristics in human GC. EMT is induced by Wnt/beta-catenin signaling, providing the rationale to have Wnt secretion and beta-catenin activation as KEs in the AOP.

The limited supply of drinking water has aroused people's curiosity in recent decades. Adsorption is a popular method for removing hazardous substances from wastewater, especially heavy metals, as it is cheap, highly efficient and easy to use. In this work, a new sludge-based activated carbon adsorbent (SBAC1 / SBAC2) was developed to remove hazardous metals such as cadmium (Cd+2) and lead (Pb+2) from an aqueous solution. The chemical structure and surface morphology of the produced SBAC1 and SBAC2 were investigated using a range of analytical tools such as CHNS, BET, FT-IR, XRD, XRF, SEM, TEM, N2 adsorption/desorption isothermal and zeta potential. BET surface areas were examined and SBAC2 was found to have a larger BET surface area (498.386 m2/g) than SBAC1 (336.339 m2/g). SBAC2 had a lower VBJH (1.5026 cm3 g-1) than SBAC1 (1.59873 cm3 g-1), but a higher VT (0.3748 cm3 g-1) than SBAC1 (0.2688 cm3 g-1), while the average pore size was 10-100 nm for SBAC1 and 45-50 nm for SBAC2. The ideal conditions investigated for the removal of Pb+2 and Cd+2 were 10 mg SBAC1 / SBAC2, Pb+2 / Cd+2 at an starting concentration of 30 mg/L, a temperature of 40 and 50 °C, pH = 6, 8 and contact times of 10 and 15 minutes for Pb+2 and Cd+2, respectively. SBAC1 and SBAC2 eliminated approximately 99.99% of Cd+2 and Pb+2 out the water under all conditions tested. The results of the adsorption of Cd+2 and Pb+2 were in good agreement with the pseudo-second-order equation (R2 = 1.00). Under the experimental conditions, the Cd+2 and Pb+2 adsorption equilibrium data were effectively linked to the Langmuir and Freundlich equations for SBAC1 and SBAC2, respectively. Langmuir model calculated the adsorption capacities of SBAC1 and SBAC2 for Cd+2 (309.24 and 329.62 mg/g) and for Pb+2 (318.46 and 339.61 mg/g), respectively. The regeneration showed high recyclability for the fabricated SBAC1 and SBAC2 during five consecutive reuse cycles. As a result, the produced SBAC1 and SBAC2 are attractive adsorbent for the elimination of heavy metals from various environmental and industrial wastewater samples.

Earthquake forecasting is arguably one of the most challenging tasks in Earth sciences owing to the high complexity of the earthquake process. Over the past 40 years, there has been a plethora of work on finding credible, consistent and accurate earthquake precursors. This paper is a cumulative survey on earthquake precursor research, arranged into two broad categories: electromagnetic precursors and radon precursors. In the first category, methods related to measuring electromagnetic radiation in a wide frequency range, i.e. from a few hz to several MHz, are presented. Precursors based on optical and radar imaging acquired by space borne sensors are also considered, in the broad sense, as electromagnetic. In the second category, concentration measurements of radon gas found in soil and air, or even in ground water after being dissolved, form the basis of radon activity precursors. Well-established mathematical techniques for analysing data derived from electromagnetic radiation and radon concentration measurements are also described with an emphasis on fractal methods. Finally, physical models of earthquake generation and propagation aiming at interpreting the foundation of the aforementioned seismic precursors, are investigated

In Southeast Asia, the incidence of Leukemia, a malignant blood cancer originating from hema-topoietic progenitor cells, is on the rise, marked by a concerning 54% mortality rate. This study focuses on enhancing early-stage prediction to improve patient recovery prospects significantly. Leveraging Machine Learning and Data Science, we employ protein sequential data from frequently mutated genes such as BCL2, HSP90, PARP, and RB to predict Chronic Myeloid Leukemia (CML). Our approach relies on robust feature extraction techniques, namely Di-peptide Composition (DPC), Amino Acid Composition (AAC), and Pseudo amino acid composition (Pse-AAC), with prior attention to addressing outliers and validating feature selection through the Pearson Corre-lation Coefficient. Data augmentation ensures a well-rounded dataset for analysis. Employing a range of Machine Learning models, including Support Vector Machine (SVM), XGBoost, Random Forest (RF), K Nearest Neighbor (KNN), Decision Tree (DT), and Logistic Regression (LR), we achieve accuracy rates spanning from 66% to 94%. These classifiers undergo comprehensive as-sessment using performance metrics such as accuracy, sensitivity, specificity, F1-score, and the confusion matrix. Our proposed solution, encompassing a user-friendly web application dashboard, presents an invaluable tool for early CML diagnosis with profound implications for practitioners, offering a deploy-able asset within healthcare institutions and hospitals.

This study aimed to explore the sociocultural determinants of family planning (FP) utilization among women in pastoralist areas of Ethiopia. A community based cross-sectional survey was conducted involving 682 re-productive aged women selected from three regions in pastoralist districts. Hierarchical logistic regression was used to identify factors associated with women who did not use FP. This study revealed that 47% of women did not use FP. Women who did not use FP were more likely to shorter spaces between births, lack of partners’ support, when only a husband or someone else decides on large household purchases, and low use of household expenditure were some of the factors associated with not using FP. Overall, the prevalence of not using FP is significantly high in pastoralist communities of Ethiopia. The authors recommend that investment in women’s health and FP be targeted at educational campaigns to raise awareness about FP and its importance. Engaging men and community leaders, promoting their support for FP and contraceptive use, and providing financial assistance to address financial barriers such as transportation costs and healthcare fees, are important aspects that can increase the utilization of FP methods.

Hydrogels are three-dimensional crosslinked materials known for their ability to absorb water, exhibit high flexibility, biodegradability, biocompatibility, and mimic properties of different tissues in the body. However, their application is limited by inherent deficiencies in mechanical properties. To address this issue, reduced graphene oxide (rGO) and tannins (TA) were incorporated into alginate hydrogels (Alg) to evaluate the impact of the concentration of these nanomaterials on mechanical and adhesive, as well as cytotoxicity and wound healing properties. Tensile mechanical tests demonstrated improvements in tensile strength, elastic modulus, and toughness upon the incorporation of rGO and TA. Additionally, the inclusion of these materials allowed a greater energy dissipation during continuous charge-discharge cycles. However, the samples did not exhibit self-recovery under environmental conditions. Adhesion was evaluated on pig skin, revealing that higher concentrations of rGO led to enhanced adhesion, while the concentration of TA did not significantly affect this property. Moreover, adhesion remained consistent after 10 adhesion cycles, and contact time before the separation between the material and the surface did not affect this property. The materials were not cytotoxic and promoted healing in human fibroblast model cells. Thus, an Alg/rGO/TA hydrogel with enhanced mechanical, adhesive, and wound healing properties was successfully developed.

Change Detection (CD) of aerial images refers to identifying and analyzing changes between two or more aerial images of the same location taken at different times. The CD is a highly challenging task due to the need to distinguish relevant changes, such as urban expansion, deforestation, or post-disaster damage assessment, from irrelevant ones, such as light conditions, shadows, and seasonal variations. Many CD papers have recently been published, where most of the papers that proposed a new model contained a comparison between their proposed and state-of-the-art (SOTA) models. While many recent studies propose new deep learning (DL) models for improving CD performance, their comparative analyses are often restricted, lacking comprehensive insights into the proposed models' real-world generalizability, robustness, and performance trade-offs across diverse change characteristics. This paper presents a novel generic framework to systematically benchmark and assess DL-based CD models through three parallel pipelines: 1) cross-testing models on diverse benchmark datasets to evaluate generalization, 2) robustness analysis against different image corruptions, and 3) multi-faceted contour-level analytics evaluating detection sensitivity to change size/complexity. The framework is applied to comparatively evaluate five state-of-the-art DL-based CD models - Changeformer, BIT, Tiny, SNUNet, and CSA-CDGAN. Extensive experiments unveil each model's strengths, limitations and biases, highlighting their relative proficiencies in generalizing across data distributions, resilience to noise corruption, and discriminative capabilities for changes of varying characteristics. The proposed benchmarking framework demonstrates significant potential for guiding the selection of suitable CD models tailored to specific application requirements by comprehensively evaluating their generalizability, robustness, and detection capabilities across diverse real-world scenarios. This systematic evaluation approach can drive future research into developing more robust and versatile CD solutions aligned with practical needs.

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing constellation of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9, Sentinel-2, and planned future missions like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA) Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from Reference systems to Client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

This study introduces a novel nanocomposite coating composed of PANI/CeO2 nanocomposite films, aimed at addressing corrosion protection needs. Analysis through FTIR spectra and XRD patterns confirms the successful formation of the nanocomposite films. Notably, the PANI/CeO2 nanocomposite films exhibit a hydrophilic nature. The bandgap energy of the PANI composite film measures at 3.74 eV, while the introduction of CeO2 NPs into the PANI matrix reduces the bandgap energy to 3.67 eV. Furthermore, the electrical conductivity of the PANI composite film is observed to be 0.40 S.cm-1, with the incorporation of CeO2 NPs leading to an increase in electrical conductivity to 1.07 S.cm-1. To evaluate its efficacy, electrochemical measurements were conducted to assess the corrosion protection performance. Results indicate a high protection efficiency of 92.25% for the PANI/CeO2 nanocomposite film.

Green spaces take part a vital role in reducing the harmful effects occurred through the process of rapid urbanization. This study focuses on evaluating the change of green space and per capita green space in Colombo District, Sri Lanka in between 2008 and 2015 using Landsat images. The NDVI differencing method and classification method were used to detect the change of land cover. According to the results, a gradual decline of green space from 629.1km2 to 591.16km2 with a rate of 6.03% can be depicted. The change is considerable in Kaduwela, Moratuwa and Maharagama DSDs and quite better in the areas such as Avissawella, Homagama and Padukka. The per capita green space has been decreased from 272.361 m2 to 248.811 m2. Though these rates are very well higher than the UN, EU and WHO standards for the district, Colombo DSD do not comply with UN and EU standards. The case would turn into worst in 2025, as the predictions with current rates. Therefore, the study recommends taking immediate actions to make a greener city. Further, a tax system is proposed to get the attraction of the general public.

Background: Stroke is the third leading cause of disability, primarily due to motor, sensory, and cognitive impairments. Virtual reality (VR) has shown promising results in post-stroke rehabilita-tion, particularly for upper limb recovery. The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), aligned with the International Classification of Functioning, Disa-bility, and Health (ICF) principles, is a valid tool for measuring disability regardless of its cause. This study aimed to investigate the feasibility of VR TRAVEE system in upper limb rehabilitation for stroke patients. Methods: 14 stroke patients with residual hemiparesis were enrolled in the study. They underwent a 10-day program combining conventional therapy (CnvT) with VR rehabilitation. At baseline (T0), upper limb was assessed using the Modified Ashworth Scale (MAS), Active Range of Motion (AROM), and the Numeric Rating Scale (NRS) for pain. These assessments were repeated after the 10-day rehabilitation program (T1). Additionally, disability was measured using WHODAS 2.0 at T0 and again 30 days after completing the program. Results: Significant im-provements were observed in AROM, MAS scores for the shoulder, elbow, wrist, and metacar-pophalangeal joints as well as in the reduction of shoulder pain (p˂0.001). WHODAS scores de-creased across all six domains, with a statistically significant improvement in the cognition domain (p=0.011). Conclusions: Combining CnvT with VR as a rehabilitation approach enhances motor function in the upper limb. This method has the potential to reduce disability scores and promote neuroplasticity.

A rapid and simple high-performance liquid chromatography (HPLC) method using extraction with zinc sulfate has been developed for the determination of Casiopeina III-ia (Cas III-ia) and validated over the linear range 10-120 g/mL in 200 L of rabbit blood. Previously we have reported a HPLC method to quantify CasIII-ia in plasma, but in distribution studies in total blood [20], the Cas III-ia concentrations were higher in total blood that in plasma [19]. The analysis was performed on a Symmetry C (18) (5 microm) column. The mobile phase was Methanol-sodium phosphate buffer (pH 6.5; 0.01 M) (40:60 v/v) was kept at a flow-rate of 0.8 ml/min. The analyses were performed at room temperature. The column effluent was monitored at 262 nm. Acetaminophen was used as internal standard. The results showed that the assay is sensitive at 10 g/mL. Maximum intra-day coefficient of variation was 5.10%. The average recovery obtained in blood was 94.51%. The applicability of this method for distribution in vitro and pharmacokinetic studies in rabbits was demonstrated. Conclusions: the present assay is rapid, simple, precise, and accurate. The pharmacokinetic study was carried out in rabbits and the following pharmacokinetic parameters were obtained: (kel) = 0.0150 min-1, half-life time (T1/2) = 53.92 min, apparent volume of distribution (Vd) = 202.81 mL, clearance (Cl) = 2.08 mL /mi and area under the curve (AUC)=23163.85 µg/mL.min. Contributing to the preclinical characterization of the Cas III-ia.

To date, the development of unmanned technologies using autonomous underwater vehicles (AUV) has become an urgent demand for solving the problem of inspection of industrial sub-sea structures. A key issue here is precise localization of AUVs relative to underwater objects. However, the well-known challenges of recognizing and coordinating underwater objects (impossibility to use GPS, undercurrents, etc.) do not allow high-precision navigation if based solely on a standard suite of AUV navigation tools (sonars, etc.). An alternative is a technology of processing of optical images that, at short distances, can provide higher accuracy of AUV navigation compared to a technology of acoustic measurement processing. In this study, in the context of the problem of subsea production system inspection, we propose a method to recognize underwater objects and provide coordinate reference of AUV to them, based on stereo-image processing. Its distinctive features are the use of a non-standard technique for generating a geometric model of an object from its views (foreshortening) taken from positions of a pre-made overview trajectory, the use of various characteristic geometric elements when recognizing objects, and the original algorithms for comparing visual data of the inspection trajectory with an a priori model of the object.

Gas-water relative permeability curve is the foundation of gas reservoir dynamic analysis and numerical simulation. It is generally obtained through gas displacing water experiment. Referring to the existing national standards, gas-water relative permeability test is carried out for low-permeability and tight sandstone. The flow is discontinuous and the curve smoothness is poor, which affects the application of gas-water relative permeability curve. Based on the comparative analysis of a large number of mercury injection and NMR experimental results of low-permeability and tight sandstone, a method to characterize the throat radius distribution of low-permeability tight sandstone based on NMR T2 spectrum is explored. Combined with high-speed centrifugal experiment, the calculation formulas of core water saturation, phase relative permeability of gas-water under different centrifugal force are established. A new method of "nuclear magnetic resonance + high-speed centrifugation" for gas-water relative permeability curve test of low-permeability and tight sandstone is formed, and the test is carried out on Sulige low-permeability tight sandstone core. The results show that: (1) The shape of cumulative distribution curve of throat radius by mercury injection method is basically consistent with that of T2 relaxation time by NMR, and there is a good corresponding relationship between them. (2) The centrifugation process is similar to the gas displacing water process. With the decrease of water saturation, water centrifugation in rock core becomes more and more difficult until it become irreducible. (3) The test process of the new method is unified and standard and up to 6 cores can be tested at the same time. The calculation results of water saturation and relative permeability curve are reliable and the integral curve is smooth, which greatly improves the test efficiency of gas-water relative permeability curve in low-permeability and tight sandstone. The new method can be widely used to study the gas-water two-phase seepage law in low-permeability and tight sandstone gas reservoir.

Understanding and measuring rock characteristics is crucial for scientific and practical applications. This study investigates stone quarries in Morelia, Michoacán, Mexico, evaluating ten quarries (both volcanic and crushed) using diverse analytical methods. Physical properties such as density were measured alongside mechanical tests like uniaxial compressive strength and ultrasonic pulse velocity. Results demonstrate that crushed materials exhibit superior physical and mechanical properties compared to volcanic stones. Advanced techniques including high-magnification scanning electron microscopy and X-ray fluorescence provided insights into surface morphology and elemental composition. Additionally, a novel finite element model was constructed, leveraging dynamic modulus of elasticity (Ed) derived from ultrasonic pulse velocity and maximum load data from uniaxial compressive strength tests. This model facilitated the classification of quarries based on their engineering characteristics. The findings underscore the model’s potential applicability to quarry assessments globally, offering valuable insights into optimizing stone resource utilization and enhancing structural integrity in construction projects.

Quantum thermal engines are receiving much attention in recent years, due to their potential applications.~For a candidate group, harmonically trapped gases under Bose-Einstein condensation (BEC), we see little investigation on the energy transference around that transition.~Therefore, we present an empirical study with rubidium-87 gas samples in a magnetic harmonic trap.~We developed an empirical Equation of State model to fit to our experimental dataset, expressing the pressure parameter ($\mathcal{P}$) in terms of temperature ($T$) and six technical coeffcients ($\{a_i\}_{0,\dots,4}$, $T_\mathrm{th}$), functions of volume parameter ($\mathcal{V}$) and number of atoms ($N$).~For weakly interacting gases, the internal energy is $U\cong3\mathcal{P}\mathcal{V}$, thus we determine the entropy with $U = TS - \mathcal{P}\mathcal{V}$ for fixed $N$.~As expected, we show that the entropy at the BEC transition ($S_c$) is constant for varying $\mathcal{V}$.~Being isentropic makes BEC transition an energy source for non-mechanical work.~Hence, we observed that the enthalpy at the BEC transition $H_c = E_c + \mathcal{P}_c\mathcal{V} = T_cS_c$, at fixed values of $\mathcal{V}$ and varying $N$, grows fairly linearly with $N$.~We fitted $H_c=\eta{N}-H_c^0$ to that data, being $\eta$ the specific enthalpy of BEC transformation and $H_c^0$ an intrinsic enthalpic loss.~We deem this study to be a step closer to practical quantum-based engines.

Urban rivers and waterfronts play a vital role in the ecological, social, and economic fabric of cities, providing not only aesthetic value but also serving as important ecosystems that contribute to the overall well-being of urban environments. However, many urban rivers, including the Beirut River in Lebanon, face challenges such as pollution, neglect, and the loss of recreational and ecological value due to urbanization and industrialization. According to the Lebanese MOE (Ministry of Environment), almost 70% of Lebanese rivers are polluted due to untreated waste management systems and which leads to undrinkable water and possible flooding disasters if not treated. This study addresses the problem of abandoned and degraded spaces along the Beirut River riverside through the application of urban acupuncture, a strategic approach that targets specific points in the urban environment to stimulate positive change and regeneration. The aim of the study is to assess the effectiveness of implementing small-scale ‘sensitive urban points’ known as urban acupuncture as the method for regenerating the Beirut River riverside, with the hypothesis that targeted interventions through Blue Urban Acupuncture or Aqua-puncture- can lead to significant improvements in the ecological, social, and economic aspects of the area that re-connect the people of Beirut with its river. The methodology involves a multidisciplinary approach that integrates urban design, and community engagement, and analysing similar examples of different approaches through creating a comparative table. Data collection includes environmental assessments of water quality, biodiversity, and ecosystem health, as well as social surveys to understand community needs and perceptions. By applying urban acupuncture principles to the Beirut River riverside, this study seeks to demonstrate how strategic interventions can lead to the regeneration of abandoned spaces, improve the overall quality of the urban environment, and create sustainable and inclusive riverside landscapes that benefit both the environment and the community.

The subject of the research are materials formed as a result of hydrothermal treatment, in this case cellular concretes, both traditional and modified with plastics (HIPS). There are two types of materials resulting from hydrothermal treatment: autoclaved sand-lime bricks and autoclaved concrete. Both in the case of ABK and silicates, the basic stubstrates used during their production are: lime, sand and water (cement is also added to cellular concrete). The article presents the methodology of testing the porous structure of autoclaved materials with the use of computed tomography. Aerated concrete (light autoclaved concrete) has a compressive strength of 2-6 MPa. The tests included aerated concrete modified with high-impact polystyrene, commonly known as HIPS. HIPS high-impact polystyrene is a thermoplastic polymer that is obtained by block-suspension polymerization of styrene with the addition of synthetic rubber. As a result of polymerization, small particles of polybutadiene remain in the polystyrene male, changing its physical and mechanical properties. The results from the content of air voids in the autoclaved concrete sample with HIPS were on average: 52.53%.

A new approach for predicting the geometrical characteristics of the mixing behavior of an inclined dense jet for angles ranging from 15° to 85° is proposed in this study. This approach is called group method of data handling (GMDH) which is based on the artificial neural network (ANN) technique. The proposed model was trained and tested using existing experimental data reported in literature. The model was then evaluated using statistical indices as well as compared with analytical models from previous studies. The results of the coefficient of determination (R2) indicate a high accuracy of the proposed model with values of 0.9719 and 0.9513 for training and testing for the dimensionless of the distance from the nozzle to the return point xr/D, and 0.9454 and 0.9565 for training and testing for the dimensionless of the terminal rise height yt/D . Moreover, four previous analytical models were used to evaluate the GMDH model. The results showed the superiority of the proposed model in predicting the geometrical characteristics of the inclined dense jet for all tested angles. Finally, the standard error of estimate (SEE) was applied to demonstrate which model performed the best in terms of getting closer to the actual data. The results illustrate that all fitting lines of the GMDH model performed very well for all geometrical parameter predictions and was the best model with approximately 10% error, which was the lowest value of error among the models. Therefore, this study confirms that the GMDH model can be used to predict the geometrical properties of the inclined negatively buoyant jet with high performance and accuracy.

We used a mixed-method single-case experimental research design to examine the effect of modelling (peer versus non-peer) on exercise self-efficacy in stroke survivors who participated in a community-based exercise program. Quantitative data were obtained using a ABCA design: (A1) no model/baseline 1 (3 weeks); (B) peer model (6 weeks); (C) non-peer model (6 weeks); and (A2) no model/baseline 2 (3 weeks). Four participants completed self-efficacy questionnaires after each weekly session. Qualitative data were obtained using researcher diaries and two semi-structured interviews: after B and A2. Based on quantitative and qualitative results, participants reported higher exercise self-efficacy in the model conditions, with ratings appearing highest for the non-peer model. This finding could be due to a lack of full integration of the peer model and low feelings of similarity. Modelling in general could help people recovering from a stroke increase their exercise self-efficacy, but non-peer models may not be most advantageous.

The Internet of Things (IoT) aims to connect all objects and facilitate data interchange, with data accuracy being paramount. While IoT has seen extensive adoption in conventional sectors, its application in the petroleum industry, especially with downhole equipment, poses challenges due to the extreme high-temperature and high-pressure conditions, making accurate measurements elusive. This Paper we aim to enhance the accuracy of downhole pressure measurements in slim-hole drilling parameter monitoring, mitigate the temperature influences on strain gauges, and surmount the intrinsic limitations of the traditional BP neural network, such as sluggish convergence speeds, high sensitivity to initial weights and biases, unstable learning rates, and a tendency to fall into local minima. This study introduces a temperature compensation model using a chaotic-initiated adaptive whale optimization algorithm (C-I-WOA) to optimize a BP neural network, which is henceforth referred to as the C-I-WOA-BP model. Initially, we harnessed chaotic mapping techniques to refine the initialization process of the whale optimization algorithm (WOA) population, thereby bolstering the heterogeneity of the algorithm. Subsequently, we integrated an adaptive weight recalibration mechanism, refined the encompassing methodology of the WOA, and bolstered its capabilities for expansive global scouting and meticulous local refinement in the solution arena. Subsequently, the WOA was used to optimize the weight coefficients of the BP neural network. Finally, we conducted a detailed comparative analysis by juxtaposing the performance metrics of the BP, C-WOA-BP, I-WOA-BP, and C-I-WOA-BP networks. The experimental results indicate that the C-I-WOA-BP model demonstrates faster convergence speed, superior global search capabilities, and enhanced local exploitation potential compared to the other models. Additionally, it provides a more stable and accurate reduction in temperature-induced errors in drilling pressure parameter measurements.

The objective of the study was to apply the principles of analytical quality by design (AQbD) to the analytical method for the determination of the radiochemical purity (PQR) of the radiopharmaceutical sodium iodide 131I oral solution, by means of thin layer chromatography (TLC) with a Radio-TLC scanner, the same one that allows to evaluate the quality of the product. For the AQbD, the analytical objective profile (ATP), critical quality attributes (CQA), risk management, the method operable design region (MODR) were defined through the response surface methodology for method optimization using the MINITAB ® software, Control Strategy and the validation of the method where the parameters of selectivity, linearity, precision, robustness, detection limit, quantification limit, range and stability of the sample solution were evaluated. Under the experimental conditions, the conditions of the method were demonstrated by TLC-Scanner and optimization was carried out for an injection volume of 3 µL, radioactive concentration of 10 mCi/mL and carrier volume of 40 µL. It was statistically demonstrated that the method is selective for the 131I iodide band Rf of 0,8 and for the radiochemical impurity IO₃⁻ Rf of 0.6, linearity from 6,0 to 22.0 mCi/mL, intermediate precision with Global RSD of 0,624%, robustness with global RSD 0,101%, detection limit of 0,09 mCi/mL, quantification limit of 0.53 Ci/mL, conforming range, and stability of the sample solution evaluated over time 0, 2 and 20 hours with a global RSD of 0,362%, obtaining consistent results. The development of the method based on AQbD allowed the generation of a design space and an operational space with knowledge of all the characteristics and limitations of the method, likewise in all the operations the conformity of the tests to the acceptance criteria was verified. The validity of our method is concluded under the established conditions, suitable for use in the manufacturing process of sodium iodide 131I and application in nuclear medicine services.

Context: Despite the effort put into developing standards for structuring construction cost, and the strong interest into the field. Most construction companies still perform the process of data gathering and processing manually. That provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly on big projects. Additionally, the lack of standardization makes very difficult the cost estimation and comparison tasks. Objective: To create a method to extract and organize construction cost and quantity data into a consistent format and structure, to enable rapid and reliable digital comparison of the content. Method: The approach consists of a two-step method: Firstly, the system implements data mining to review the input document and determine how it is structured based on the position, format, sequence, and content of descriptive and quantitative data. Secondly, the extracted data is processed and classified with a combination of data science and experts’ knowledge to fit a common format. Results: A big variety of information coming from real historical projects has been successfully extracted and processed into a common format with 97.5% of accuracy, using a subset of 5770 assets located on 18 different files, building a solid base for analysis and comparison. Conclusion: A robust and accurate method was developed for extracting hierarchical project cost data to a common machine-readable format to enable rapid and reliable comparison and benchmarking.

Background: The aim of this study was to design and analyze the content validity of an instrument to assess the risk of behaviors associated with the Chemsex phenomenon since there is currently no instrument with this objective. Method: Firstly, a bank of items identified from the literature was elaborated. Secondly, 50 experts with knowledge of the Chemsex phenomenon at the national level were contacted. A Delphi group was formed with them to carry out two rounds of item evaluation (comprehension and appropriateness) using a Likert scale of 1 to 5. To assess linguistic validity, the mean score of the item comprehension scores was used. The content validity index (CVI) and Aiken's V (VdA) were calculated for each item. A minimum value of CVI and VdA of 0.6 was established to include the items in the questionnaire. Results: In the first round of evaluation, 36 experts evaluated 114 items, of which 61 were selected. In a second round, 30 experts evaluated the 61 items selected, leaving the scale finally made up of 52 items. Conclusion: A questionnaire has been designed to assess the risk of behaviors associated with the Chemsex phenomenon. The items that make up the questionnaire have shown adequate content and linguistic validity, so this instrument can be considered valid. The Delphi method proved to be a useful technique for the proposed objective.

The purpose of this study is to apply the convergence-confinement method (CCM) based on the assumption of hydrostatic stress to the surrounding rock excavated in a circular tunnel whose rock mass characteristics meet the requirements of the non-linear Hoek-Brown failure criterion. Based on a consistent and rigorous method of theoretical analysis, a closed-form analytical solution for the stress/displacement of the ground reaction induced by the advancing excavation of the tunnel, especially in the elastic and plastic regions, is derived and investigated under the condition of an isotropic stress state. By taking the value of a confinement loss as an explicit analysis process in an incremental manner, not only is the computationally executable analytical solution achieved, but it can also be performed using a simple spreadsheet. The validity of the analytical solution implemented by the incremental procedure was examined with published data to study the effect of nonlinear failure criteria on the ground reaction curve; in particular the mechanical behavior at the intrados of the tunnel, and the distribution of stress/displacement on the cross-section of the tunnel. A comparison between the published results and the solution proposed in this study, which interprets the closed-form by the incremental procedure, shows consistent and favorable trends.

This study aims to focus on using the Volterra series and machine learning for forecasting random and chaotic wind speed regimes, since the calm weather is mostly noticed at the local site, making the dataset selection difficult. A novel method is proposed to predict Volterra kernels up to the third order, using a forward-back propagation neural network with 12-month measurements at Fujairah site (UAE). Both daily and monthly wind speed data sets are investigated for forecasting. The three dominant hourly and daily kernels are extracted for each day and each month. Predicted future Volterra kernels are estimated from past values using both statistical analysis and individual neuro networks for each of the Volterra kernel coefficients. Due to the random nature of wind speed at the local site, a two-layer with 4 neurons per layer neuro network is used to locate the most variable and intense speed during 8-hours in the day. Forecasted wind speed is determined with errors arising from different sources such as the utilization of only 3rd-order Volterra kernels and the difficulty of machine training of the employed shallow network. Nevertheless, this work depicts a useful algorithm to forecast chaotic and random wind speed regimes. Computational time is a trade of the complexity of Volterra mathematical analysis.

To determine promethazine (PMZ) and its metabolites promethazine sulfoxide (PMZSO) and monodesmethyl-promethazine (Nor1PMZ) in swine muscle, fat, kidney, and liver, a sample preparation and high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis method were established and validated. The sample was extracted with 0.1% formic acid-acetonitrile, and the extract was purified with acetonitrile-saturated n-hexane. After concentration by rotary evaporation, the extract was re-dissolved in 0.1% formic acid-water and acetonitrile (80:20, v/v). The HPLC-MS/MS column used was a Waters Symmetry C18 (100 mm × 2.1 mm i.d., 3.5 μm), with 0.1% formic acid-water and acetonitrile as the mobile phase, and the target compounds were determined by positive ion scan and multiple reaction monitoring. PMZ and Nor1PMZ were quantified with deuterated promethazine (PMZ-d6) as the internal standard, while PMZSO was quantified by external standard method. The limits of detection (LOD) and limits of quantification (LOQ) of PMZ and PMZSO in muscle, liver, and kidney spiked samples were 0.05 μg/kg and 0.1 μg/kg, respectively, while those of Nor1PMZ were 0.1 μg/kg and 0.5 μg/kg, respectively. The LOD and LOQ of analytes in fat spiked sample were 0.05 μg/kg and 0.1 μg/kg, respectively. The sensitivity of this method reaches or exceeds its presented in previous reports. The analytes PMZ and PMZSO showed good linearity within the range of 0.1 μg/kg to 50 μg/kg, while Nor1PMZ showed good linearity within the range of 0.5 μg/kg to 50 μg/kg, with correlation coefficients (r) greater than 0.99. The recoveries of the target compounds in the sam-ples were between 81.73% and 107.17%, and the precision ranged from 1.78% to 10.47%. This study developed for the first time an HPLC-MS/MS method for the determination of PMZ and its metabolites PMZSO and Nor1PMZ in four swine edible tissues, comprehensively covered target tissues of monitoring object, which is applicable for monitoring veterinary drug residues in ani-mal-derived foods and ensuring food safety.

C-C chemokine receptor 9 (CCR9) is a receptor for C-C-chemokine ligand 25 (CCL25). CCR9 is crucial in the chemotaxis of immune cells and inflammatory responses. Moreover, CCR9 is highly expressed in tumors including several solid tumors and T-cell acute lymphoblastic leukemia. Several preclinical studies have shown that anti-CCR9 monoclonal antibodies (mAbs) exert antitumor activity. Therefore, CCR9 is an attractive target for tumor therapy. In this study, we conducted the epitope mapping of an anti-mouse CCR9 (mCCR9) mAb, C9Mab-24 (rat IgG2a, kappa), using a 1 × alanine (1 × Ala) and 2 × alanine (2 × Ala)-substitution method via enzyme-linked immunosorbent assay. We first performed the 1 × Ala-substitution method using one alanine-substituted peptides of the mCCR9 N-terminus (amino acids 1-19). C9Mab-24 did not recognize two peptides (F14A and F17A), indicating that Phe14 and Phe17 are critical for C9Mab-24-binding to mCCR9. Furthermore, we conducted the 2 × Ala-substitution method using two consecutive alanine-substituted peptides of the mCCR9 N-terminus, and showed that C9Mab-24 did not react with four peptides (M13A–F14A, F14A–D15A, D16A–F17A, and F17A–S18A), indicating that 13-MFDDFS-18 is involved in C9Mab-24-binding to mCCR9. Overall, combining, the 1 × Ala or 2 × Ala scanning methods could be useful for understanding for target-antibody interaction.

Modularity in the construction of industrial robots is becoming increasingly popular, as the modules can be assembled in different ways so as to obtain various architectures of industrial robots determined by the requirements of specific applications. Such a robot with modular structure is considered in this paper. The tracked mobile robot, with translation – rotation – translation – translation – rotation (TRTTR) modular serial structure, is the subject of national invention patent number RO132301 B1/2021, granted by the State Office for Inventions and Trademarks of Bucharest, to “Nicolae Bălcescu” Land Forces Academy of Sibiu, Romania [1]. The tracked mobile robot has been designed to perform the task of humanitarian demining operations and the mechanical structure, respectively the kinematic analysis were described in detail in papers [1,2]. A first general objective of this paper is to highlight a dynamic-organological method to achieve an architectural structure of mobile robot on tracks, able to replace the human element in areas with high risk for health and life, for detection and demining anti-personnel and anti-armor minefields in countries where military conflicts have taken place. For this scope it was performed the dynamic modeling using the Lagrange’s formalism and to achieve the constructive optimization of the TRTTR mechanical structure, in order to obtain a minimum energy consumption through an optimal arrangement of the modules in its structure. A second objective is to improve the action flexibility of the technological product in humanitarian detection and demining operations, as well as for educational purposes, by training highly educated and specialized human resources in the field of advanced military technologies. The differential equations of motion of the robot has obtained and respectively the mechanical design equations, which lead to the optimal choice of the drive motors of the modules in the robot structure. Also, it is presented the mathematical model for obtaining the driving motor of base translation modulus (MTB SIL) of the modular serial tracked robot and the constructive solution of the MTB SIL module.

Next-generation sequencing (NGS) has actualized human papillomavirus (HPV) virome profiling for in-depth investigation of viral evolution and pathogenesis. However, viral computational analysis remains a bottleneck due to semantic discrepancies between computational tools and curated reference genomes. To address this, we developed and tested automated workflows for HPV taxonomic profiling and visualization using a customized Papillomavirus database in CLC Microbial Genomics Module. HPV genomes from Papilloma Virus Episteme were customized and incorporated into CLC “ready-to-use” workflows for stepwise data processing to include: 1) Taxonomic Analysis, 2) Estimate Alpha/Beta Diversities, and 3) Map Reads to Reference. Low-grade (n = 95) and high-grade (n = 60) Pap smears were tested with ensuing collective runtimes: Taxonomic Analysis (36 min); Alpha/Beta Diversities (5 sec); Map Reads (45 min). Tabular output conversion to visualizations entailed 1-2 keystrokes. Biodiversity analysis between low- (LSIL) and high-grade squamous intraepithelial lesions (HSIL) revealed loss of species richness and gain of dominance by HPV-16 in HSIL. Integrating clinically relevant, taxonomized HPV reference genomes within automated workflows proved to be an ultra-fast method of virome profiling. The entire process named “HPV DeepSeq” provides a simple, accurate and practical means of NGS data analysis for a broad range of applications in viral research.

With the continuous development of Artificial Intelligence technology and Internet of Things engineering, more and more driver-less vehicles have been developed and put into the industrial production. The birth of driver-less vehicles undoubtedly brings new vitality to a large amount of industries, particularly in transportation. For the mining industry, transportation is undoubtedly an extremely important link in the whole production process. If the driver-less vehicles can be applied to the underground mines, it can not only improve the production and transportation capacity of the whole mine, but also can reduce the occurrence of many mine safety accidents. ZigBee WSN technology can play a greater role in the narrow environment like underground mines according to the relevant literature, this concept paper just like a engineering project plan mainly tries to integrate the ZigBee WSN technology and the communication-based train control (CBTC) system to explore the possibility of the driver-less vehicles to be used in the underground mines, which aims to solve practical engineering problems for the engineering projects. As the mining engineers, we put forward the concept of this integrated system in this concept paper, but we need to continue to work hard for the future of the underground mines. This concept paper serves just as a guide to the Tossing out a brick to get a jade gem, has a few implications for the development of underground mine transportation.

Lipophilicity can be measured with different methods, such as Shake-Flask or liquid chromatography. HPLC presents the advantage of overcoming solubility issues and therefore extending the range of lipophilicity to high values. A specific HPLC method, called ELogD, had been developed 20 years ago on a C₁₆-amide stationary phase, enhancing hydrophobic and hydrogen bond interactions to mimic octanol-water partition. The emergence of novel stationary phases added to the need for a less complex mobile phase has led to the development of a new HPLC assay called alphaLogD, applicable to neutral and basic compounds at pH 7.4, that combines superficially porous particles, a high number of equilibriums between solutes and stationary phase, and results in a lower number of isocratic methods to determine the logk’_w at a higher throughput. Statistical studies have been run to successfully evaluate the alphaLogD method compared to the Shake-Flask method and to allow this lipophilicity measurement into the so-called Beyond-Rule-of-5-molecules space.

This study addressed a Fluid-Structure Interaction of an open Water test for vp1304 propeller to predict pressure and stress distributions with a low cost and high precision method. The most striking aspect of such a method(one-way coupling) is to use one hydrodynamic solution for the number of different structural sets involved in other materials or different layup methods and combinations of layers. An open-access software(OpenFOAM) with an open-source code solver is used to simulate the fluid domain. Abaqus is used To evaluate and predict the deformation and strength of the blade with the Finite Element Method(FEM). The coupling approach is based on dry condition, which means the added mass effects due to propeller blades vibration is neglected. The pressures imposed on the blades are extracted from the fluid solver for each time step. Then, These pressures role as a load condition for the structure solver. This approach was verified in the last paper(wedge impact); a key factor for the present solution is the rotational rate interrelated between two solution domains, which is explained in this paper. Finally, the blades' stress and strain are calculated and compared in each advance coefficient.

Toward the standardization of O. biennis sprout extract (OBS-E), we aimed to obtain indicator compounds, using a validated method. HPLC-UVD allowed simultaneous quantification of indicator compounds quercetin 3-glucuronide and ellagic acid. The method was validated in terms of specificity, linearity, precision, accuracy, and limit of detection/limit of quantification (LOD/LOQ). High specificity and linearity was demonstrated, with correlation coefficients of 1.0000 for quercetin 3-glucuronide and 0.9998 for ellagic acid. The LOD/LOQ values were 0.486/1.472 μg/mL for quercetin 3-glucuronide and 1.003/3.039 μg/mL for ellagic acid. Intra-day and inter-day variability tests produced relative standard deviation for each compound of <2%, a generally accepted precision criterion. High recovery rate were also obtained, indicating accuracy validation. The OBS-E prepared using various concentrations of ethanol were then analyzed. The 50% ethanol extract had highest content of quercetin 3-glucuronide, whereas the 70% ethanol extract possessed the lowest. However, the ellagic acid content was highest in the 70% ethanol extract and lowest in the 90% ethanol extract. Thus, quercetin 3-glucuronide and ellagic acid can be used industrially as indicator compounds for O. biennis sprout products, and our validated method can be used to establish indicator compounds for other natural products.

The Convective Rainfall Rate from Cloud Physical Properties (CRPh) for Meteosat Second Generation Satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT’ Satellite Application Facility in support to Nowcasting and Very Short Range Forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for the next few hours. This paper critically discusses the theoretical basis of the algorithm with special emphasis in the empirical values and assumptions in the microphysics of precipitation and compares the performances of the CRPh with its antecessor, the Convective Rainfall Rate algorithm (CRR), using an object-based method. The analyses show that AEMET’s CRPh is physically consistent and that outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges to evolve the product to an all-day algorithm are also presented.

The state of charge estimation is an important part of the battery management system, the estimation accuracy of which seriously affects the working performance of the lithium ion battery pack. The unscented Kalman filter algorithm has been developed and applied to the iterative calculation process. When it is used to estimate the SOC value, there is a rounding error in the numerical calculation. When the sigma point is sampled in the next round, an imaginary number appears, resulting in the estimation failure. In order to improve the estimation accuracy, an improved adaptive square root - unscented Kalman filter method is introduced which combines the QR decomposition in the calculation process. Meanwhile, an adaptive noise covariance matching method is implied. Experiments show that the proposed method can guarantee the semi-positive and numerical stability of the state covariance, and the estimation accuracy can reach the third-order precision. The error remains about 1.60% under the condition of drastic voltage and current changes. The conclusion of this experiment can provide a theoretical basis of the state of charge estimation in the battery management of the lithium ion battery pack.

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.

The advent of Sixth Generation (6G) wireless technologies introduces challenges and opportunities for Mobile Ad Hoc Networks (MANETs) and Vehicular Ad Hoc Networks (VANETs), necessitating a reevaluation of traditional routing protocols. This paper introduces the Multi-Metric Scoring Dynamic Source Routing (MMS-DSR), a novel enhancement of the Dynamic Source Routing (DSR) protocol, designed to meet the demands of 6G-enabled MANETs and the dynamic environments of VANETs. MMS-DSR integrates advanced technologies and methodologies to enhance routing performance in dynamic scenarios. Key among these is the use of a CNN-LSTM based beamforming algorithm, which optimizes beamforming vectors dynamically, exploiting spatial-temporal variations characteristic of 6G channels. This enables MMS-DSR to adapt beam directions in real-time based on evolving network conditions, improving link reliability and throughput. Furthermore, MMS-DSR incorporates a multi-metric scoring mechanism that evaluates routes based on multiple QoS parameters, including latency, bandwidth, and reliability, enhanced by the capabilities of Massive MIMO and the IEEE 802.11ax standard. This ensures route selection is context-aware and adaptive to changing dynamics, making it effective in urban settings where vehicular and mobile nodes coexist. Additionally, the protocol uses machine learning techniques to predict future route performance, enabling proactive adjustments in routing decisions. The integration of dynamic beamforming and machine learning allows MMS-DSR to effectively handle the high mobility and variability of 6G networks, offering a robust solution for future wireless communications, particularly in smart cities.

The research investigates the factors affecting the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia and their impact on the country’s economic growth. The research methods of the studies involve data collection through surveys or interviews, followed by statistical analysis. The study found that entrepreneurial qualities such as motivation, entrepreneurial orientation, and risk behavior positively influence the financial performance of MSMEs. MSMEs that manage working capital optimally tend to increase profitability and growth, despite operational difficulties like worker shortages. MSMEs engaged in foreign trade usually achieve higher profitability. Bank loans can enhance profitability and sales, but the collateral requirement may hinder growth. The owner’s involvement doesn’t affect growth but can enhance profitability. Factors like the Human Capital Index, interest rates, the Indonesian Rupiah exchange rate, and inflation do not significantly impact MSME investment. However, business units, labor, investment, and exports of MSMEs significantly influence Indonesia’s economic growth. MSMEs play a crucial role in job creation, rural development, economic diversification, and GDP contribution in Indonesia. Despite challenges, they have the potential for sustainable growth. The research also explores strategies for overcoming challenges faced by MSMEs and investigates the role of universities in supporting the MSME sector. The University of Indonesia (UI) supports the MSME sector through strategic initiatives, including education, training, mentoring, and internship programs. The research provides valuable insights into the operation of MSMEs in Indonesia and their contribution to the economy, highlighting areas for further exploration and potential strategies for supporting the growth and sustainability of these enterprises.

We study epidemic spreading in complex networks by a multiple random walker approach. Each walker performs an independent simple Markovian random walk on a complex undirected (ergodic) random graph where we focus on Barabási-Albert (BA), Erdös-Rényi (ER) and Watts-Strogatz (WS) types. Both, walkers and nodes can be either susceptible (S) or infected and infectious (I) representing their states of health. Susceptible nodes may be infected by visits of infected walkers, and susceptible walkers may be infected by visiting infected nodes. No direct transmission of the disease among walkers (or among nodes) is possible. This model mimics a large class of diseases such as Dengue and Malaria with transmission of the disease via vectors (mosquitos). Infected walkers may die during the time span of their infection introducing an additional compartment D of dead walkers. Infected nodes never die and always recover from their infection after a random finite time. This assumption is based on the observation that infectious vectors (mosquitos) are not ill and do not die from the infection. The infectious time spans of nodes and walkers, and the survival times of infected walkers, are represented by independent random variables. We derive stochastic evolution equations for the mean-field compartmental populations with mortality of walkers and delayed transitions among the compartments. From linear stability analysis, we derive the basic reproduction numbers R M , R 0 with and without mortality, respectively, and prove that R M < R 0 . For R M , R 0 > 1 the healthy state is unstable whereas for zero mortality a stable endemic equilibrium exists (independent of the initial conditions) which we obtained explicitly. We observe that the solutions of the random walk simulations in the considered networks agree well with the mean-field solutions for strongly connected graph topologies, whereas less well for weakly connected structures and for diseases with high mortality. Our model has applications beyond epidemic dynamics, for instance in the kinetics of chemical reactions, the propagation of contaminants, wood fires, among many others.

The design and operation of quantum networks are both decisive in the current push towards a global quantum internet. Although space-enabled quantum connectivity has already been identified as a beneficial candidate for long-range quantum channels for over two decades, the architecture of a hybrid space-ground network is still a work in progress. Here, we propose an analysis of such a network based on a best-path approach, where either fiber- or satellite-based elementary links can be concatenated to form a repeater chain. The network consisting of quantum information processing nodes, equipped with both ground and space connections, is mapped into a graph structure, where edge weights represent the achievable secret key rates, chosen as the figure of merit for the network analysis. A weight minimization algorithm allows identifying the best path dynamically, i.e., as the weather conditions, stray light radiance, and satellite orbital position changes. From the results we conclude that satellite links will play a significant role on the future large-scale quantum internet, and both a constellation of satellites and significant advances in filtering technology are required to fulfill continuous coverage.

Background: Although previous studies have implicated a role for the stool microbiome in cancer cachexia, the fecal microbiome has not been previously characterized for patients with pancreatic ductal adenocarcinoma (PDAC) and cachexia treated with nutritional interventions such as enteral feeding. Methods: The PANCAX-1 (NCT02400398) prospective trial enrolled 31 cachectic advanced PDAC patients to receive jejunal tube peptide-based diet for 12 weeks who were planned for palliative chemotherapy. Out of 16 evaluable patients, 62.5% receiving enteral feeding met the primary endpoint of weight stability at 12 weeks. As part of an exploratory analysis of the PANCAX-1 trial, serial stool and blood samples were collected at 0 (C1D1), 6 (C2D1), and 12 (C3D1) weeks over the 12-week period of enteral feeding. Stool samples were analyzed using 16S v4 sequencing of the microbiome. Up to 219 plasma metabolites were analyzed by mass spectrometry and high-performance liquid chromatography. Results: A total of 29 stool samples were prospectively collected from 16 subjects with PDAC enrolled in PANCAX-1 who were evaluable for weight stability. Over 12 weeks of enteral feeding, statistically significant increases in the abundance of bacterial genera such as Veillonella (p=0.0150) and Actinomyces (p=0.0390) were observed, while there was a lower abundance of Bacteroides (p=0.0150) and Butyricicoccus (p=0.0390). Greater abundance of Veillonella and reduced Bifidobacterium at baseline were linked to greater weight stability. Plasma metabolomics in 10 subjects showed that weight unstable patients had significantly decreased levels of essential (L-histidine, L-phenylalanine) and non-essential amino acids (L-citrulline, L-tyrosine, all p<0.05) at the end of 12 weeks of enteral feeding. High stool Veillonella abundance was significantly associated with increases in the nucleotide 2-deoxycytidine 5-diphosphate and essential amino acid L-isoleucine but decreased TCA cycle metabolite alpha-ketoglutarate (all p<0.05). Conclusions: We are the first to demonstrate the feasibility of stool microbiome profiling and plasma metabolomics in paired stool and plasma samples from a prospective cohort of advanced PDAC patients on enteral feeding as their primary source of nutrition. Our findings are hypothesis-generating in that metabolites unique to weight stability and abundance of stool bacterial genera may inform future studies of anti-cachexia therapies involving enteral feeding or microbial modulation.

Monomeric Ubiquitin (Ub) is a 76-amino acid highly conserved protein found in eukaryotes. The first described biological activity of Ub in the 1970s was extracellular, but it quickly gained relevance due to its intracellular role, i.e., post-translational modification of intracellular proteins (ubiquitination) that regulate numerous eukaryotic cellular processes. In the following years, the extracellular role of Ub was relegated to the background, until a correlation between higher survival rate and increased serum Ub concentrations in patients with sepsis and burns was observed. Although the mechanism of action (MoA) of extracellular ubiquitin (eUb) is not yet well understood, further studies have shown that it may ameliorate the inflammatory response in tissue injury and multiple sclerosis diseases. These observations compounded with the high stability and low immunogenicity of eUb due to its high conservation in eukaryotes have made this small protein a relevant candidate for biotherapeutic development. Here, we review the in vitro and in vivo effects of eUb on immunologic, cardiovascular, and nervous systems, and discuss the potential MoAs of eUb as an anti-inflammatory, antimicrobial, cardio- and brain-protective agent.

The VEMoS AXL system is a new optical biometer based on spectral domain optical coherence tomography (SD-OCT) that has been tested in terms of intrasession repeatability and compared with a swept-source optical coherence tomography biometer (SS-OCT), which is considered the gold standard, for an agreement analysis. A biometric analysis was performed three consecutive times in 120 healthy eyes of 120 patients aged between 18 and 40 years with the SD-OCT system and afterwards a single measurement was obtained with the SS-OCT system. Within-subject standard deviations were 0.004 mm, 4.394 µm and 0.017 mm for axial length (AL), central corneal thickness (CCT), and anterior chamber depth (ACD) measures obtained with the SD-OCT biometer, re-spectively. The agreement between devices was good for AL (Limits of agreement, LoA: -0.04 to 0.03 mm) and CCT (LoA: -4.36 to 14.38 µm), whereas differences between devices were clinically relevant for ACD (LoA: 0.03 to 0.21 mm). In conclusion, the VEMoS AXL system provides consistent measures of anatomical parameters, being most of them interchangeable with those provided by the SS-OCT-based gold standard.

Base excision repair (BER) is the predominant pathway to remove most forms of hydrolytic, oxidative and alkylative DNA damage. The precise functioning of BER is achieving by the regulation of each step by regulatory/accessory proteins, with the most important of which being poly(ADP-ribose) polymerase 1 (PARP1). The PARP1 regulatory functions extend to many cellular processes including regulation of mRNA stability and decay. PARP1 can therefore affect BER both at the level of the BER proteins and at the level of their mRNAs. Systematic data on how the PARP1 content affects the activities of key BER proteins and the levels of their mRNAs in human cells are extremely limited. In this study the CRISPR/Cas9 based technique has been used to knocked out the PARP1 gene in the human HEK 293FT line. The obtained cell clones with putative PARP1 deletion were characterized by several approaches including: PCR analysis of deletions in genomic DNA, Sanger sequencing of genomic DNA, qPCR analysis of PARP1 mRNA, western-blot analysis of whole-cell-extract proteins with anti-PARP1 antibodies, and the PAR synthesis in the whole-cell-extracts. qPCR analysis of mRNAs coding the BER related proteins: PARP2, uracil DNA glycosylase 2, AP endonuclease 1, DNA polymerase β, DNA ligase III and XRCC1 did not reveal crucial influence of PARP1 knockout. The corresponding catalytic activities in the whole-cell extracts (WCEs) evaluated in parallel did not differ significantly between mutant and parental cell lines. No considerable influence of poly(ADP-ribose) synthesis on the activity of the above WCE enzymes was revealed.

The fungal order Entomophthorales in the Zoopagomycotina includes many fungal pathogens of arthropods. This review explores five genera in the Erynioideae subfamily, namely Erynia, Furia, Pandora, Strongwellsea, and Zoophthora. This is the largest subfamily in the Entomophthorales including 125 described species. The species diversity, global distribution, and host range of this subfamily are summarized, revealing that relatively few taxa are geographically widespread, and few have broad host ranges, contrasting with a large number of species with single reports, from one location and one host species. The insect orders infected by the greatest numbers of species are the Diptera and Hemiptera. Across the subfamily relatively few species have been cultivated in vitro and those that have require more specialized media than any fungi. Given their potential to attack arthropods and in the fungal evolutionary tree, which species might be adopted for biological control purposes or biotechnological innovations are highlighted. Current challenges in the implementation of these species in biotechnology include the limited ability or difficulty in culturing many in vitro, a correlated paucity in genomic resources, and considerations regarding the host ranges of different species.

Tyrosyl-DNA phosphodiesterase 1 (Tdp1) is an important DNA repair enzyme and one of the causes of tumor resistance to topoisomerase 1 inhibitors such as topotecan. Inhibitors of this Tdp1 in combination with topotecan may improve the effectiveness of therapy. In this work, we synthesized usnic acid derivatives, which are hybrids of its known derivatives - tumor sensitizers to topotecan. New compounds inhibit Tdp1 in the micromolar and submicromolar concentration range; some of them enhance the effect of topotecan on the metabolic activity of cells of various lines according to the MTT test. One of the new compounds (compound 7) not only sensitizes Krebs-2 and Lewis carcinomas of mice to the action of topotecan, but also normalizes the state of the peripheral blood of mice, which is disturbed in the presence of a tumor. Thus, the synthesized substances may be the prototype of a new class of additional therapy for cancer.

In the last two decades, the development of high-throughput diagnostic methods and availabil-ity of effective treatments has increased interest in newborn screening for lysosomal storage disorders. However, long-term follow-up experience is needed to clearly identify risks, benefits and challenges. We report our 8-year experience of screening and follow up on about 250,000 neonates screened for four lysosomal storage diseases (Pompe disease, mucopolysaccharidosis type I, Fabry dis-ease, Gaucher disease), using enzyme activity assay by tandem mass spectrometry, and bi-omarker quantification as second tier test. Among the 126 positive newborns (0.051%), 51 infants were confirmed as affected (positive pre-dictive value 40%), with an overall incidence of 1:4,874. Of these, 3 infantile-onset Pompe dis-ease, 2 neonatal-onset Gaucher disease and 4 mucopolysaccharidosis type I patients were imme-diately treated. Furthermore, another four Gaucher disease patients needed treatment in the first years of life. Our study demonstrated the feasibility and effectiveness of newborn screening for lysosomal storage diseases. Early diagnosis and treatment allow the achievement of better patient out-comes. Challenges such as false positive rates, the diagnosis of variants of uncertain significance or late-onset forms, and the lack of treatment for neuronopathic forms, should be addressed.

Background In many African countries, clinical samples are not routinely tested for carbapenem-resistant bacteria, the resistance data remaining limited. Material and methods In March 2020 –June 2022, we collected extended spectrum β-lactamase (ESBL) -producing Enterobacterales (ESBL-PE) isolates from five hospitals in Burkina Faso. The species were identified using API20E and ESBL production confirmed by double-disc synergy test. Production of carbapenemases and AmpC-β-lactamases and phenotypic co-resistance were determined. Results Among the 473 ESBL-PE, 356 were ESBL- E. coli (ESBL-Ec) and 117 Klebsiella spp. (ESBL-K). Of the isolates, 5.3% were carbapenemase and 5.3% AmpC-β-lactamase positive Three types of carbapenemases were identified: 19 NDM, 3 OXA-48 like and 1 VIM. Two isolates produced both NDM and OXA48-like carbapenemases. Carbapenemase rates were highest among isolates in tertiary hospitals. Co-resistance rates were up to 85% for aminoglycosides, 90% for sulfonamides, 95% for fluoroquinolones and 25% for chloramphenicol, Fosfomycin resistance was 6% for ESBL-Ec and 49% for ESBL-K (49%). Conclusion Many ESBL-Ec and ESBL-K co-produced carbapenemases and/or AmpC-β-lactamases, at all healthcare levels and in various samples, with high co-resistance rates to non-betalactams. Carbapenem resistance is no longer rare, calling for testing in routine diagnostics, vigorous resistance surveillance system, and infection control within healthcare.

(1) Background: Some evidence suggests that cannabidiol (CBD) has potential to help alleviate HIV symptoms due to its antioxidant and anti-inflammatory properties. Here we examined acute CBD effects on various behaviors and the endocannabinoid system in HIV Tat transgenic mice. (2) Methods: Tat transgenic mice (female/male) were injected with CBD (3,10,30 mg/kg) and assessed for antinociception, activity, coordination, anxiety, and recognition memory. Brains were taken to quantify endocannabinoids and related lipids. Additionally, CBD and metabolite 7-hydroxy-CBD were quantified in the plasma and cortex. (3) Results: Tat decreased striatal-related nociception and locomotion, with some sex-dependent effects on coordination. CBD had no effect on nociception and coordination, but increased locomotor activity. For anxiety, differential CBD effects were noted for sex, with decreasing anxiety-like behavior in males only. In the striatum and spinal cord, male sex was associated with lower 2-arachidonoylglycerol and with elevated concentrations of its proinflammatory metabolite arachidonic acid. CBD metabolism was altered by sex and Tat. (4) Conclusion: Findings indicate that acute CBD effects are not altered by HIV Tat, and CBD has minimal effects on behavior and the endocannabinoid system. Interestingly, sex-dependent alterations were noted for endocannabinoids and related lipids, which may be of relevance in view of potential CBD-based treatment options for people living with HIV.

The direct measurements of the magnetocaloric effect were performed in Heusler Ni44.4Mn36.2Sn14.9Cu4.5 alloy at cryogenic temperatures in magnetic fields up to 10 T. The maximum value of the inverse magnetocaloric effect in a field of 10 T was observed ∆Tad = –2.7 K in the vicinity of the 1st order magnetostructural phase transition at T0 = 117 K. The ab initio and Monte Carlo calculations were performed to discuss the effect Cu doping into Ni-Mn-Sn compound on the ground state structural and magnetic properties. It is shown that with increasing Cu content the martensitic transition temperature decreases and the Curie temperature of austenite slightly increases. In general, calculated transition temperatures, magnetization values are correlated well with the experimental ones.

Total-body PET/CT scanners provide increased sensitivity, enabling the adjustment of imaging parameters by reducing injected activity or shortening acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectabil-ity, and quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min. scan time) were included in this analysis. PET raw data was rebinned for shorter frame durations to simulate 5 min. scans with lower activities in high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n=82) were assessed using a 5-point Likert scale. The co-efficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Sub-jective image ratings were generally superior in UHS compared to HS mode. At 0.5 MBq/kg, le-sion detectability decreased to 95% (HS) and 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7±0.6) and 0.5 MBq/kg in UHS (5.5±0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a total-body PET/CT provides diagnostic image quality without statistical-ly significant changes in uptake parameters. UHS mode improves image quality, noise, and le-sion detectability compared to HS mode.

Tdp1 and Tdp2 are DNA repair enzymes that repair DNA damages caused by various agents, including anticancer drugs. Thus, these enzymes resist anticancer therapy and could be the reasons of resistance to such widely used drugs as topotecan and etoposide. In the present work, we found compounds capable of inhibiting both enzymes among derivatives of (-)-usnic acid. Both (+)- and (-)-enantiomers of compounds act equally effectively against Tdp1, and only (-)-enantiomers inhibited Tdp2. Surprisingly, the compounds protect HEK293FT wild type cells from the cytotoxic effect of etoposide but potentiate it against Tdp2 knockout cells. We assume that the sensitizing effect of the compounds in the absence of Tdp2 is associated with effective inhibition of Tdp1, which could take over the functions of Tdp2.

Abstract: Accurately predicting a fetus's gestational age (GA) is of utmost importance in prenatal care. This study aimed to develop an artificial intelligence (AI) model that can automatically predict GA using biometric measurements derived from fetal brain mag-netic resonance imaging (MRI). Additionally, we aimed to assess the significance of con-sidering different references when interpreting GA predictions. To achieve this, we obtained measurements such as Biparietal Diameter (BPD), Fron-to-occipital Diameter (FOD), and Head Circumference (HC) from a dataset comprising 52 normal fetal MRI cases with T2 Haste sequences from Rush University. Both manual and AI-based methods were utilized to acquire these measurements. We also employed three reference papers (Garel, Freq, and Bio) for comparison purposes. The results demonstrated a strong correlation between manual and AI measure-ments, indicating consistency between the two methods. The AI-based measurement of HC exhibited a higher correlation with actual values compared to BPD, FOD, and correct-ed BPD (BPDC). When comparing these measurements with GA in the Picture Archiving and Communication System (PACS), the differences varied depending on the reference used. Specifically, the differences ranged from 0.47 to 2.17 weeks for BPD, 0.46 to 2.26 weeks for FOD, and 0.75 to 1.74 weeks for HC. Furthermore, the Pearson correlation coeffi-cient analysis revealed that all correlation coefficients between PACS records and GA pre-dictions using different references were greater than 0.97. In conclusion, the AI model based on fetal brain MRI accurately predicts GA by uti-lizing BPD, FOD, and HC measurements. The AI approach, which involves combining line segments to calculate fetal head circumference, offers improved accuracy and con-venience compared to manual estimation. This study underscores the potential of AI models in accurately estimating gestational age and highlights their utility in prenatal care. By integrating AI as a valuable tool in prenatal care, we can enhance the accuracy, ef-ficiency, and decision-making involved in assessing fetal development and monitoring pregnancies using MRI measurements.

(1) Background: Inflammatory breast cancer (IBC) is a rare and aggressive form of breast cancer that poses unique management challenges. This review aims to synthesize the current literature on IBC, focusing on diagnosis, treatment, and prognosis, while highlighting recent advances and ongoing issues in patient management.; (2) Methods: We outline the typical clinical presentation and diagnostic criteria of IBC. Additionally, we detail the main therapeutic strategies, including neoadjuvant chemotherapy, surgery, radiation therapy, targeted therapies, hormonal therapies, and emerging treatments such as immunotherapy. The review is based on a comprehensive analysis of the existing literature.; (3) Results: Despite advancements in systemic therapy and a better understanding of IBC biology, the prognosis for patients with IBC remains poor. The overall survival rate has shown only marginal improvement over the past few decades. Future research directions, including the identification of novel biomarkers for early detection and personalized medicine strategies, are identified. The need for more high-quality clinical trials to address the challenges in IBC management is emphasized.; (4) Conclusions: Managing IBC is a complex task that necessitates multidisciplinary care and patient-centered communication. This review provides clinicians and researchers with a comprehensive overview of the current challenges and future directions in IBC management. The goal is to guide treatment decisions and inform further research, ultimately improving patient outcomes and prognosis.

Botanical biopesticides have emerged as sustainable and eco-friendly alternatives to synthetic pesticides, whose indiscriminate use leads to several drawbacks to human and environment health. The present study reports on the evaluation of the roots extract from Magonia pubescens, species from the Cerrado (Brazilian savannah), on the phytopathogenic fungi, Alternaria alternata, Botrytis cinerea, and Fusarium oxysporum. In addition, its insect antifeedant effect was assayed against Chrysodeixis chalcites. Thus, an in vitro test-assay was used to determine the fungicide potential (percentage growth inhibition, % GI) of the ethanolic extract of this plant species, whereas a leaf-disk bioassay on the 5^th instar larvae of C. chalcites was performed to evaluate the insecticide potential. The ethanolic extract was further fractionated by liquid-liquid extraction, using organic solvents of increasing polarity. The hexane/dichloromethane fraction exhibited a moderated potency, and similar to the ethanolic extract on the three assayed fungi (around % GI 30 at 1 mg/mL), whereas the n-butanol fraction showed a slight improvement of the fungicide effect against B. cinerea (% GI 39.18 at 1 mg/mL). Moreover, the etanolic extract exhibited a strong antifeedant activity, with a refusal rate (FR) higher than 90% in both choice and non-choice assays against C. chalcites, while the ethyl acetate and n-butanol fractions behaved as appetite suppressors. These results highlight M. pubescens as a promising source of biopesticides and deserve further investigations to optimize extraction procedures.

Two different silica conformations (Xerogels and Nanoparticles) both formed by the mediation of dendritic poly (ethylene imine) were tested at low pHs on the problematic uranyl cation sorption. The effect of crucial factors i.e., temperature, electrostatic forces, adsorbent composition, accessibility of the pollutant to the dendritic cavities and MW of the organic matrix was investigated to conclude the optimum formulation for water purification under these conditions. This was attained with the aid of UV-Visible and FTIR spectroscopy, dynamic light scattering (DLS), ζ-potential; Brunauer–Emmett–Teller (BET) porosimetry, Thermo Gravimetric Analysis (TG) and Scanning Electron Microscopy (SEM) Results highlighted that both adsorbents have extraordinary sorp-tion capacity. Xerogels are cost-effective since they approximate the performance of na-noparticles with much lesser organic content. Furthermore, they are more practicable materials since they may penetrate the pores of a metal or ceramic solid substrate in the form of a precursor, gel-forming solution.

Al-6%Mg-Sc-Zr alloys with the total ratio of Sc + Zr = 0.32 wt.% make up the target of this research. The content of scandium and zirconium varied with an increment of 0.02%. The alloys were produced by induction casting. Their ultrafine-grained (UFG) microstructure was formed with Equal Channel Angular Pressing (ECAP). Such cast alloys have a homogeneous macrostructure formed by small equiaxed grains in the central part of the ingot and columnar crystals along the edges of the cross section. After ECAP, the average grain size in the alloy specimens is 0.5–1 µm. The average grain size does not depend on the ratio of Sc and Zr in these alloys. Superplasticity tests were performed at temperatures ranging from 300 to 500 °C and at a strain rate varying between 3.3·10-3 and 3.3·10-1 s-1. UFG Al-6%Mg-0.20%Sc-0.12%Zr and Al-6%Mg-0.18%Sc-0.14%Zr alloys exhibit the highest superplasticity. It was suggested that changes in Sc:Zr ratio affect spatial distribution and composition of the following precipitating particles: Al3Sc, Al3Zr, Al3(ScxZr1-x). An increase in Zr concentration is shown to reduce the susceptibility of UFG alloys to cavitation fracture.

With the ongoing fifth-generation cellular network (5G) deployment, electromagnetic field exposure has become a critical concern. However, measurements are scarce, and accurate electromagnetic field reconstruction in a geographic region remains challenging. This work proposes a conditional Generative Adversarial Network to address this issue. The main objective is to reconstruct the electromagnetic field exposure map accurately according to the environment’s topology from a few sensors located in an outdoor urban environment. The model is trained to learn and estimate the propagation characteristics of the electromagnetic field according to the topology of a given environment. In addition, the conditional Generative Adversarial Network based electromagnetic field mapping is compared with simple kriging. Results show that the proposed method produces accurate estimates and is a promising solution for exposure map reconstruction.

One of the most frequent brain diseases, Alzheimer's is defined by poor cognitive function brought on by the build-up of Beta Amyloid plaques and the gradual death of neurons. Glucose metabolism and the development of amyloid plaques are being studied together. Under physiologically normal circumstances, glucose is the primary substrate for the adult human brain. The prodromal phases of AD are significantly influenced by glucose hypometabolism. Hypometabolism of glucose in the brain is a clear sign of mitochondrial dysfunction and bioenergetic system impairment. By regulating energy synthesis and cell death, mitochondria play a crucial role in the functioning of cells. Increased formation of reactive oxygen species (ROS) and oxidative stress are a result of mitochondrial dysfunction, which also accelerates the development of Alzheimer's disease. For the maintenance of balance, autophagy is crucial because it selectively destroys damaged mitochondria. AD affects this route for mitochondrial breakdown. Targeting specific mitochondrial ligands by interventions along this pathway might be a useful therapeutic approach. Due to a number of biological obstacles, this method has significant limitations. As a result, many nanocarriers have been created to improve drug delivery effectiveness. All potential nanotechnology-based treatments for AD have been examined in this study, with a particular emphasis on medication delivery to the mitochondria

Background: Affective states play a role in dietary behaviors. Yet, little research has studied within-subjects associations between affect and diet during pregnancy. We examined the acute bidirectional relationships between affect and food intake and moderation by pre-pregnancy body mass index (BMI) in low-income, Hispanic pregnant women using ecological momentary assessment (EMA). Methods: Women (N=57) completed four days of EMA during their first trimester. Women responded to five random prompts per day about their current affect and past two-hour food intake. Results: Higher positive affect (PA) or lower negative affect (NA) predicted greater likelihood of fruit/vegetable consumption in the next two hours in women with lower pre-pregnancy BMI and lower likelihood in women with higher pre-pregnancy BMI. Higher PA predicted less likelihood of fast food consumption in the next two hours in women with lower pre-pregnancy BMI and slightly higher likelihood in women with higher pre-pregnancy BMI. Women with lower pre-pregnancy BMI had higher PA when they reported consuming chips/fries in the past two hours, and women with higher pre-pregnancy BMI had lower PA when they reported consumption of chips/fries in the past two hours. Conclusions: Results showed differential relationships between affect and food intake as a function of pre-pregnancy BMI.

This work presents the first evidence that dissolved globular proteins change the arrangement of hydrogen bonds in water, with different proteins showing quantitatively different effects. Using ATR-FTIR (Attenuated Total Reflection – Fourier Transform Infrared) spectroscopic analysis of OH-stretch bands, we obtain quantitative estimates of the relative amounts of the previously reported four subpopulations of water structures coexisting in a variety of aqueous solutions. Where solvatochromic dyes can measure the properties of solutions of non-ionic polymers, the results correlate well with ATR-FTIR measurements. In protein solutions to which solvatochromic dye probes cannot be applied, NMR (Nuclear Magnetic Resonance) spectroscopy was used for the first time to estimate the hydrogen bond donor acidity of water. We found strong correlations between the solvent acidity and arrangement of hydrogen bonds in aqueous solutions for several globular proteins. Even quite similar proteins are found to change water properties in dramatically different ways.

Generating long-lived mucosal and systemic antibodies through respiratory immunization with protective antigens encapsulated in nanoscale biodegradable particles could potentially decrease or eliminate the incidence of many infectious diseases but requires incorporation of a suitable mucosal immunostimulant. We previously found that respiratory immunization with a model protein antigen (LPS-free OVA) encapsulated in PLGA 50:50 nanoparticles (~380 nm diameter) surface modified with complement peptide-derived immunostimulant 02 (CPDI-02; formerly EP67) through 2kDa PEG linkers increases mucosal and systemic OVA-specific memory T-cells with long-lived surface phenotypes in young, naïve female C57BL/6 mice. Here, we determined if respiratory immunization with LPS-free OVA encapsulated in similar PLGA 50:50 microparticles (~1 μm diameter) surface modified with CPDI-02 (CPDI-02-MP) increases long-term OVA-specific mucosal and systemic antibodies. We found that, compared to MP surface modified with inactive, scrambled scCPDI-02 (scCPDI-02-MP), intranasal administration of CPDI-02-MP in 50 μL sterile PBS greatly increased titers of short-term (14 days post-immunization) and long-term (90 days post-immunization) antibodies against encapsulated LPS-free OVA in nasal lavage fluids, bronchoalveolar lavage fluids, and sera of young, naïve female C57BL/6 mice. Thus, surface modification of biodegradable microparticles with CPDI-02 is likely to increase long-term mucosal and systemic antibodies against encapsulated protein antigen after respiratory and possibly other routes of mucosal immunization.

Alcohol use disorder (AUD) is a chronically relapsing disease characterized by loss of control in seeking and consuming alcohol (ethanol) driven by recruitment of brain stress systems. However, AUD differs among the sexes: men are more likely to develop AUD, but women progress from casual to binge drinking and heavy alcohol use more quickly. The central amygdala (CeA) is a hub of stress and anxiety, with corticotropin releasing factor (CRF)-CRF1 receptor and GABAergic signaling dysregulation occurring in alcohol dependent male rodents. However, we recently showed that GABAergic synapses in female rats are less sensitive to the acute effects of ethanol. Here, we used patch clamp electrophysiology to examine the effects of alcohol dependence on the CRF-modulation of rat CeA GABAergic transmission of both sexes. We found that GABAergic synapses of naïve female rats were unresponsive to CRF application compared males, although alcohol dependence induced a similar CRF responsivity in both sexes. In situ hybridization revealed that females had less CeA neurons containing mRNA for the CRF1 receptor (Crhr1) than males, but in dependence, the percentage of Crhr1-expressing neurons in females increased, unlike males. Overall, our data provide evidence for sexually dimorphic CeA CRF system effects on GABAergic synapses in dependence.

The COVID-19 pandemic has put a lot of pressure on health systems worldwide. Mass vaccination against SARS-CoV-2 has reduced morbidity and mortality worldwide. Despite their safety profiles, vaccines like any other medical product can cause adverse events. Yet, in countries with poor epidemiological surveillance and monitoring systems, reporting vaccine-related adverse events is scarce. The objective of this study was to describe self-reported vaccine adverse events after receiving one of the available COVID-19 vaccine schemes in Ecuador. A cross-sectional analysis based on an online self-reporting 32-questionnaire was conducted in Ecuador from April 1st to July 15th, 2021. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 6,654 participants were included in this study. A 38.2% of the participants reported having at least one comorbidity. Patients received AstraZeneca, Pfizer, and Sinovac vaccines, and these were distributed 38.4%, 31.1%, and 30.5%, respectively. Pain, inflammation at the injection site (20,01%), and headache (16,91%) were the most reported adverse events. Women addressed ESAVIs (64%), more often than men (36%). After receiving the first dose of any available COVID-19 vaccine, a total of 19,481 self-reported ESAVIs were informed (86.9% were mild, 11.6% moderate and 1.5% severe). In terms of vaccine type and brand, the most reactogenic vaccine was AstraZeneca with 57.8%, followed by Pfizer (24.9%) and Sinovac (17, 3 %). After the second dose, 6,757 self-reported ESAVIs were reported (87.0% mild, 10.9% moderate, and 2.1% severe). AstraZeneca vaccine users reported a higher proportion of ESAVIs (72.2%) in comparison to Pfizer/BioNTech (15.9%) and Sinovac Vaccine (11.9%). Swelling at the injection site, headache, muscle pain, and fatigue were the most common ESAVIs for the first as well as second dose. In conclusion, most ESAVIs were mild. AstraZeneca users were more likely to report adverse events. Participants without a history of COVID-19 infection, as well as those who receive the first dose, were more prone to report ESAVIs.

Abstract: The genus Acaryochloris is unique among phototrophic organisms due to the dominance of chlorophyll d in its photosynthetic reaction centres and light-harvesting proteins. This allows Acaryochloris to capture light energy for photosynthesis over an extended spectrum of up to ~760 nm in the near infra-red (NIR) spectrum. Acaryochloris sp. has been reported in a variety of ecological niches, ranging from polar to tropical shallow aquatic sites. Here, we report a new Acarychloris strain isolated from an NIR-enriched stratified microbial layer 4-6 mm under the surface of stromatolite mats located in the Hamelin Pool of Shark Bay, Western Australia. Pigment analysis, by traditional spectrometry/fluorometry, flow cytometry and spectral confocal microscopy identify unique patterns in pigment distribution that likely reflect niche adaption. For example, unlike the original A. marina species (type strain MBIC11017), this new strain, Acarychloris LARK001, shows little change in the chlorophyll d/a ratio in response to changes in light wavelength, displays a different Fv/Fm response and lacks detectable levels of phycocyanin. Indeed, 16S rRNA analysis supports the identity of the A. marina LARK001 strain as distinct from the A. marina HICR111A strain first isolated from Heron Island, previously found on the Great Barrier Reef, under coral rubble on the reef flat. Taken together, A. marina LARK001 is a new cyanobacterial strain adapted to the stromatolite matts in Shark Bay.

In horses, there is an increasing interest in developing long-lasting drug formulations, with bi-opolymers as viable carrier alternatives in addition to their use as scaffolds, suture threads, screws, pins, and plates for orthopedic surgeries. This communication focuses on the prolonged biocompatibility and biodegradation of PLA, prepared by hot pressing at 180 ºC. Six samples were implanted subcutaneously on the lateral surface of the neck of one horse. The polymers remained implanted for 24 to 57 weeks. Physical examination, plasma fibrinogen, and the mechanical noci-ceptive threshold (MNT) were performed. After 24, 28, 34, 38, and 57 weeks, the materials were removed for histochemical analysis using hematoxylin-eosin and scanning electron microscopy (SEM). There were no essential clinical changes. MNT decreased after the implantation procedure, returning to normal after 48h. A foreign body response was observed by histopathologic evalua-tion up to 38 weeks. At 57 weeks, no polymer or fibrotic capsules were identified. SEM showed surface roughness suggesting a biodegradation process, with an increase in the average pore di-ameter. As in the histopathological evaluation, it was not possible to detect the polymer 57 weeks after implantation. PLA showed biocompatible degradation and these findings may contribute to future research in the biomedical area.

Assuming that climate warming in the WSL will lead to a northward shift of the forest and permafrost boundaries, a “substituting space for time” approach predicts an increase in concentration of DIC and labile major and trace elements and a decrease of the transport of DOC and low soluble trace metals in the form of colloids in the main stem of the Ob River. However, an unknown factor is the change in hydrochemistry of the largest southern tributary, the Irtysh River, which is impacted by permafrost-free steppe and forest-steppe zone. Overall, seasonally-resolved transect studies of large riverine systems of western Siberia are needed to assess the hydrochemical response of this environmentally-important territory to on-going climate change.

(1) Background: Although resistance to pathogens and pests has been researched in many potato cultivars and breeding lines with DNA markers, there is scarce evidence as to the efficiency of the marker-assisted selection (MAS) for these traits when applied at the early stages of breeding. A goal of this study was to estimate the potential of affordable DNA markers to track Rpi disease resistance genes, that are effective against the pathogen Phytophthora infestans, as a practical breeding tool on a progeny of 68 clones derived from a cross between the cultivar Sudarynya and 13/11-09. (2) Methods: this population was studied for four years to elucidate the distribution of LB resistance and other agronomical desirable or simple to phenotype traits such as tuber and flower pigmentation, capacity and structure of yield. LB resistance was phenotypically determined through natural and artificial infection and the presence/absence of nine Rpi genes was assessed via 11 sequence-characterized amplified region (SCAR) markers. To aid this analysis, the profile of Rpi genes in the 13/11-09 parent was established using diagnostic resistance gene enrichment sequencing (dRenSeq) as a gold standard. (3) Results: at the early stages of a breeding program, MAS can halve the workload when screening the segregation of F1 offspring and selected SCAR markers for Rpi-genes provide useful tools.

For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is the afterglow from an ultra-relativistic jet. Where this afterglow is observed, it will likely be viewed off-axis, such as the afterglow following GW170817/GRB 170817A. The temporal behaviour of an off-axis observed GRB afterglow can be used to reveal the lateral jet structure, and statistical model fits can put constraints on the various model free-parameters. Amongst these parameters is the inclination of the system to the line of sight. Along with the GW detection, the afterglow modelling provides the best constraint on the inclination to the line-of-sight and can improve the estimates of cosmological parameters e.g. the Hubble constant, from GW-EM events. However, modelling of the afterglow depends on the assumed jet structure and, often overlooked, the effects of lateral spreading. Here we show how the inclusion of lateral spreading in the afterglow models can affect the estimated inclination of GW-EM events.