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In many urban planning and visualization applications, it is crucial to have 3D window details. However, the process of acquiring and reconstructing them can be challenging. Therefore, in many 3D city models, buildings often lack 3D windows. Instead, their building façades are usually represented using 2D planar textures (i.e., LoD2 CityGML models with textures). To generate a 3D façade from 2D images, current methods often need to carefully design various grammars to achieve desired results, which can be tedious. A useful property of building, the window semantics information, is also lacking. The main contribution of this paper is proposing a semantics-aware method for addition and LoD control of 3D window details to LoD2 CityGML models with textures (namely SLOD2+WIN). A deep learning-based two-level window-pane detection is introduced, and the detection results are then processed and adjusted to generate 3D windows and add to the building models. Unlike other methods, the semantics (i.e., frames and panes) are considered for adding window details. We also propose and integrate a LoD scheme for 3D windows following the same concept as the LoD in CityGML. The tedious efforts of reconstruction or grammar creation can be reduced in our method. Only the information present in the texture itself is extracted, and the shape and pattern information of windows are obtained and adjusted from the detection results in an efficient and unsupervised manner to achieve neat window parsing. Specifically, clustering-based window/pane alignment, neatness-based window image voting, grid-based symmetry, thickness filtering, and fitting-based window-top modeling are proposed. To demonstrate the effectiveness and usefulness of SLOD2+WIN, experiments on several datasets of 3D cities are conducted to add 3D window details with the novel LoD schema, illustrative applications in architectural visualization and urban planning are also showcased. This paper extended its conference version. [ABSTRACT FROM AUTHOR]

• QTL mapping was done in bitter gourd using SSR markers. • From 630 SSRs, 35 were obtained as polymorphic by parental polymorphism screening. • Twenty eight QTLs for fourteen yield and yield attributing traits were detected. • QTL hotspot for yield per plant was detected on linkage group 1. • Higher variation was observed in the mapping population. The present study was conducted for QTL mapping for yield and other yield attributing traits in bitter gourd using Simple Sequence Repeat (SSR) markers. A total of 630 SSR markers were screened for polymorphism in two contrasting parents (DBGS-2 and Pusa Purvi), out of which only 35 were polymorphic. F 1 plants (10 individuals) in which hybridity was ascertained (using these polymorphic markers); were further employed for development of mapping population (F 2) consisting of 120 plants. Higher variation was present in the mapping population as evident from the wider range value of the characters. Continuous frequency distribution classes combined with bell-shaped, symmetrical normal distribution curve, revealed the quantitative inheritance nature of the traits studied. Higher PCV than the GCV for all the traits, along with high difference between the PCV and GCV for majority of traits indicated higher influence of environment in expression of these traits in the mapping population. Presence of transgressive segregation was also noted for majority of the traits. Amongst the various linkage groups (LG), LG 4 had the maximum number of markers, covering 171.07 cM map distance. LG4 also possessed the maximum number (nine) of QTLs while LG1 had six. QTL mapping using polymorphic SSRs resulted in detection of a total of 28 QTLs for fourteen traits viz. yield per plant (kg), earliness or flower related traits (node to first female flower, node to first male flower, days to first male flower, male to female flower ratio), fruit traits (fruit number per plant, fruit diameter (cm), fruit length/ diameter ratio, pericarp thickness (mm) and number of seed per fruit) and vegetative traits (internodal length (cm), number of primary branches, leaf width (cm), length and width ratio). The LOD score of these QTLs ranged from 3.01 to 64.47, the total phenotypic variances (PVE) ranged from 1.52 to 34.57 % and additive effects ranged from –3.69 to 17.07. Of the total, nineteen were major QTLs, having PVE >10 %. Three QTLs were detected for yield per plant while a total of seven for the traits imparting earliness viz. days to first male flower, node to first female flower and node to first male flower. Amongst all the QTLs detected, qFrtLDR-4-1 (K) had the maximum LOD (64.47) and PVE (34.57 %) value. Two hotspots were detected with multiple QTLs clustered in the LG 1. The first hotspot possessed four QTLs [qLfW-1-1, qMFR-1-1 (K), qSPF-1-1, qNFmlF-1-1 (K)] while the second had two related to yield per plant [qYldpl-1-1 (K) and qYldpl-1-1]. Many of these QTLs are also being reported for the first time in bitter gourd. The findings of the present study can be used to fasten the bitter gourd improvement by utilizing these in MAS, DNA fingerprinting, genetic mapping, genomics analysis etc. [ABSTRACT FROM AUTHOR]

In this work, a gas sensing system based on chalcogenide (ChG) glass platform in the mid-infrared (Mid-IR) region is modeled. The proposed gas sensing system composed of a linear tapers waveguide, ridge waveguide, a multimode interferometer (MMI) coupler and transducer arms. The components of the sensing system were simulated using FimmWave from Photon design. First, we determined the structural key parameters of the ridge waveguide that allow for single-mode propagation while maximizing the evanescent confinement field factor. The obtained results show that at the gas absorption wavelengths, λ CO 2 = 4.26 µm and λ CO = 4.6 µm, the evanescent confinement field factor, reached 3.12% and 3.24%, respectively. For these operating wavelengths, a maximum transmission of 99.8% was achieved with a taper length of 450 µm. The footprint of the MMI coupler is 32 × 9975 µm2. A Contrast of 16.6 dB and insertion losses of 2 dB and 2.87 dB were obtained at λ CO 2 = 4.26 µm and λ CO = 4.6 µm respectively. The sensor performance was validated at 4.26 µm and 4.6 µm, respectively, giving a detection limit of 10.73 ppm for carbon dioxide (CO2) at 4.26 µm and 138 ppm for carbon monoxide (CO) at 4.6 µm. A sensitivity of 3.02 mW.L/mol and 0.12 mW. L/mol, was achieved at the wavelenghts of interset. The obtained results of the sensor by the optimizations of its components serve to enhance a gas sensing system based on chalcogenide (ChG) glass platform. [ABSTRACT FROM AUTHOR]

Abstract Precise, fast, and reliable identification and quantification of microplastic contamination are essential for determining their environmental concentrations for risk assessments. This study investigates the use of nuclear magnetic resonance (NMR) spectroscopy to quantify microplastics by analysing dilution series of polystyrene (PS), polyisoprene-cis (PI), polybutadiene-cis (PB), polylactic acid (PLA), polyvinyl chloride (PVC) and polyurethane (PU). Each polymer type was dissolved in a suitable solvent and an internal standard was utilized for quantification. Detection and quantification limits for each polymer type were established in two ways: (1) by using an equation based on proton signals and an internal standard with known concentration and (2) by using the LOQ based on the signal-to-noise ratio. Both data sets were compared and showed that using the internal standard (method 1) results in more accurate and lower concentration limits in the range of 0.2–8 µg mL−1 for all six polymer types, while the LOQ based on the SNR (method 2) gives consistently higher concentration limits (1–10 µg mL−1). The research shows the accuracy, efficacy, and reliability of quantitative NMR spectroscopy for polymer analysis in these concentration ranges compared to established quantifying methods, such as, PyGC/MS, FTIR, or Raman spectroscopy.

Abstract Over the years, prediction techniques for the highly variable angular velocity of the Earth represented by Earth's rotation (UT1-UTC) and length-of-day (LOD) have been continuously improved. This is because many applications like navigation, astronomy, space exploration, climate studies, timekeeping, disaster monitoring, and geodynamic studies, all rely on predictions of these Earth rotation parameters. They provide early warning of changes in the Earth's rotation, allowing various industries and scientific fields to operate more precisely and efficiently. Thus, in our study, we focused on short-term prediction for UT1-UTC (dUT1) and LOD. Our prediction approach is to combine machine learning (ML) technique with efficient evolutionary computation (EC) algorithms to achieve reliable and improved predictions. Gaussian process regression (GPR) is used as the ML technique with genetic algorithm (GA) as the EC algorithm. GA is used for hyperparameter optimization of GPR model as selecting appropriate values for hyperparameter are essential to ensure that the prediction model can accurately capture the underlying patterns in the data. We conducted some experiments with our prediction approach to thoroughly test its capabilities. Moreover, two forecasting strategies were used to assess the performance in both hindcast and operational settings. In most of the experiments, the data used are the multi-technique combinations (C04) generated by International Earth Rotation and Reference Systems Service (IERS). In one of the experiments, we also investigated the performance of our prediction model on dUT1 and LOD from four different products obtained from IERS EOP 20 C04, DTRF20, JTRF20 and USNO. The prediction products are evaluated with real estimates of the EOP product with which the model is trained. The combined excitations of the atmosphere, oceans, hydrology, and sea level (AAM + OAM + HAM + SLAM) are used as predictors because they are highly correlated to the input data. The results depict the highest performance of 0.412 ms in dUT1 and 0.092 ms/day in LOD, on day 10 of predictions. It is worth noting that the later predictions were obtained by incorporating the uncertainty of the input data as weights in the prediction model, which was a novel approach tested in this study. Graphical Abstract

Xanthomonas arboricola pv. pruni (Xap) is the causal agent of bacterial spot of stone fruits and almond (Prunus spp). Detection of Xap is typically carried out using quantitative real-time PCR (qPCR) combined with culture-based isolation. However, qPCR does not differentiate between viable and dead cells, potentially leading to an overestimation of the infective population in a sample. Such overestimation could result in unnecessary phytosanitary measures. The present study aims to develop a specific protocol ideally targeting to detection of only live Xap bacterial cells. To address this challenge, the viable quantitative PCR (v-qPCR) method was evaluated using three nucleic acid-binding dyes: propidium monoazide (PMA), a combination of PMA and ethidium monoazide (EMA), and PMAxx™, an improved version of PMA. PMAxx™ proved to be the most suitable dye for the detection and quantification of living bacterial cells. This methodology was also evaluated in infected plant material over time and can be considered a rapid and reliable alternative to PCR methods for detecting only those putative infective Xap that may pose a risk for Prunus crops. Key points: • Protocol to detect biofilm and planktonic viable X. arboricola pv. pruni cells. • Host validated protocol. • Benefits, reduction of chemicals in disease control. [ABSTRACT FROM AUTHOR]

This article proposes that Resource Description Framework (RDF) technology is well suited for representing and storing inherently connected epistolary data. We justify this proposition by creating an RDF-based digital edition of the correspondence of members of the Bernoulli dynasty and Leonhard Euler and depicting the benefits this type of edition provides, which are hardly achievable otherwise. We describe the ontologies defined to fully represent letters and illustrate how we formulated letters' historical, scientific content, rich with mathematical formulae, markups, figures, and references, as RDF statements to facilitate complex queries common in the humanities field. Next, we outline the tools we developed for presenting these editions in an efficient and user-friendly form, hiding the complexity of the data structure from non-technical users while offering sophisticated analysis features to explore atoms of knowledge and their relations. Additionally, since the citability and durability of the studied digital sources play a crucial role for scholars who publish research on the editions, we explain the steps we undertook to ensure the sustainability of the RDF-based editions and to offer persistent citation possibility. [ABSTRACT FROM AUTHOR]

Over the years, prediction techniques for the highly variable angular velocity of the Earth represented by Earth's rotation (UT1-UTC) and length-of-day (LOD) have been continuously improved. This is because many applications like navigation, astronomy, space exploration, climate studies, timekeeping, disaster monitoring, and geodynamic studies, all rely on predictions of these Earth rotation parameters. They provide early warning of changes in the Earth's rotation, allowing various industries and scientific fields to operate more precisely and efficiently. Thus, in our study, we focused on short-term prediction for UT1-UTC (dUT1) and LOD. Our prediction approach is to combine machine learning (ML) technique with efficient evolutionary computation (EC) algorithms to achieve reliable and improved predictions. Gaussian process regression (GPR) is used as the ML technique with genetic algorithm (GA) as the EC algorithm. GA is used for hyperparameter optimization of GPR model as selecting appropriate values for hyperparameter are essential to ensure that the prediction model can accurately capture the underlying patterns in the data. We conducted some experiments with our prediction approach to thoroughly test its capabilities. Moreover, two forecasting strategies were used to assess the performance in both hindcast and operational settings. In most of the experiments, the data used are the multi-technique combinations (C04) generated by International Earth Rotation and Reference Systems Service (IERS). In one of the experiments, we also investigated the performance of our prediction model on dUT1 and LOD from four different products obtained from IERS EOP 20 C04, DTRF20, JTRF20 and USNO. The prediction products are evaluated with real estimates of the EOP product with which the model is trained. The combined excitations of the atmosphere, oceans, hydrology, and sea level (AAM + OAM + HAM + SLAM) are used as predictors because they are highly correlated to the input data. The results depict the highest performance of 0.412 ms in dUT1 and 0.092 ms/day in LOD, on day 10 of predictions. It is worth noting that the later predictions were obtained by incorporating the uncertainty of the input data as weights in the prediction model, which was a novel approach tested in this study. [ABSTRACT FROM AUTHOR]

This study investigates the detection of organic compounds using a surface plasmon resonance (SPR) sensor comprising Zinc oxide (ZnO), Silver (Ag), and graphene oxide (GO) layers. Graphene oxide is chosen as topmost layer due to its impressive attributes, including a large surface area, robust light absorption, thermal stability, and biocompatibility. By optimizing the thickness of the ZnO and Ag, the performance of the sensor is enhanced. The proposed sensor configuration significantly improved the sensitivity and obtained the maximal value of 215°/RIU at minimum reflectance (Rmin). At a ZnO thickness of 20 nm and Ag thickness of 35 nm, the sensor achieves maximal sensitivity of 222.79/RIU for detecting the n-octane organic compound. This improved sensor design shows efficacy in detecting analytes with refractive index (RI) variations ranging from 1.33 to 1.39. Additionally, the proposed sensor demonstrated a limit of detection (LoD) of 5.65 RIU and figure of merit (FoM) of around 50.75/RIU, highlighting its high sensitivity, and detection accuracy. Furthermore, substantial penetration depths (PDs) of 219.71 nm for water and 211.11 nm for n-octane are obtained. This analysis highlights the exceptional performance of the proposed sensor, rendering it highly suitable for sensing applications in both industrial and biomedical domains. [ABSTRACT FROM AUTHOR]

Edible Swiftlet Nest (ESN) is a swiftlet's saliva product that contains many beneficial compounds. However, improper washing leaves behind toxic nitrite content. To ensure its absence, sensitive and accurate methods are needed, such as UV-Vis spectrophotometry. However, long analysis time and complicated maintenance, limit its further use. In this research, cyclic voltammetry was developed as an alternative analysis method for nitrite content in ESN. The results show that the LOD and LOQ of this method are 0.658529 ppm and 1.995544 ppm, respectively. Compared to this value, analysis using UV-visible spectrophotometry shows lower LOD and LOQ values, respectively 0.061579 ppm and 0.186602 ppm. [ABSTRACT FROM AUTHOR]

Soybean is scientifically known as Glycine max. It belongs to the Fabaceae family. It consists of a lot of bioactive phytochemicals like saponin, phenolic acid, flavonoid, sphingolipids and phytosterols. It also owns excellent immune‐active effects in the physiological system. Soy and its phytochemicals have been found to have pharmacological properties that include anticancer, antioxidant, anti‐hypercholesterolaemic, anti‐diabetic, oestrogenic, anti‐hyperlipidaemic, anti‐inflammatory, anti‐obesity, anti‐hypertensive, anti‐mutagenic, immunomodulatory, anti‐osteoporotic, antiviral, hepatoprotective, antimicrobial, goitrogenic anti‐skin ageing, wound healing, neuroprotective and anti‐photoageing activities. Present study has been designed to set standard pharmacognostical extraction method, complexation of compounds, qualitative evaluation through phytochemical screening, identification by TLC, physicochemical properties, solubility profile, total phenolic, flavonoid content as well as analytical evaluation or characterisation like UV and FT‐IR of methanolic extract of G. max. The final observations like physicochemical properties such as total ash value, LOD and pH were recorded. Phytochemical screenings show the presence of flavonoid, alkaloid, saponin, carbohydrate, tannins, protein, gums and mucilage, fixed oils and fats. The results were found significant. Further in silico studies proved creatinine and euparin to be potent wound healing agents. [ABSTRACT FROM AUTHOR]

UV Spectrophotometric method has been developed to determine Gliclazide in bulk pure and tablet forms. It is a simple, accurate, reproducible, rapid and less time-consuming method. The maximum wavelength of the drug was found to be 232nm. Beer Lamberts' law was obeyed in the concentration range of 2-20 µg/ml. (LOD)The limit of detection and limit of qualification (LOQ) was found to be 0.16 µg/ml and 0.50 µg/ml from this method per cent recovery of the drug was found to be 99.30% which indicates no interaction of the excipients. This method was found accurate, simple, precise and rapid for determination of tablet dosage form. [ABSTRACT FROM AUTHOR]

In the Japanese official detection method for unauthorized genetically modified (GM) papayas, one of two types of real-time PCR reagents with DNA polymerase (TaqMan Gene Master Mix [Taq-Man Gene] or FastGene QPCR Probe Mastermix w/ROX [FastGene]) is primarily used for measurement. In 2022, we conducted a laboratory performance study on the unauthorized GM papaya line PRSV-YK, and the results revealed that high threshold cycle (Cq) values for the PRSV-YK detection test were obtained using TaqMan Gene with the 7500 Fast & 7500 Real-Time PCR System (ABI7500) and QuantStudio 12K Flex (QS12K), indicating the possibility of false negatives. The possibility of similar problems with all unauthorized GM papaya lines detection tests needs to be evaluated. In this study, we performed detection tests on unauthorized GM papaya lines (PRSV-YK, PRSV-SC, and PRSV-HN), the cauliflower mosaic virus 35S promotor (CaM), and a papaya positive control (Chy), and examined how the limits of detection (LOD) for each test are affected by two types of DNA polymerases (TaqMan Gene and FastGene) and three types of real-time PCR instruments (ABI7500, QS12K, and LightCycler 480 Instrument II [LC480]). In the PRSV-YK and PRSV-SC detection tests using ABI7500 and QS12K, measurement with TaqMan Gene showed a higher LOD than FastGene. In this case, an exponential amplification curve was confirmed on the amplification plot; however, the amplification curve did not cross the ARn threshold line and the correct Cq value was not obtained with a threshold line = 0.2. The other tests (PRSV-HN, CaM, and Chy with ABI7500 and QS12K, and all detection tests with LC480) showed no important differences in the LOD for each test using either DNA polymerase. Therefore, when performing PRSV-YK and PRSV-SC detection tests with the ABI7500 or QS12K, FastGene should be used to avoid false negatives for foods containing GM papaya lines PRSV-YK and PRSV-SC at low mixing levels. [ABSTRACT FROM AUTHOR]

The growing adoption of Building Information Modeling (BIM) within the architectural, engineering, and construction (AEC) sector raises questions about the quality of BIM data deliverables for project owners. Therefore, assessment and evaluation of such BIM data against relevant documents such as the BIM Execution Plan (BEP), the Level of Definition (LOD)/Level of Information (LOI) matrix, and quality control customized checklists become critical, especially in large construction projects. This study primarily aims to create an automated system for assessing the quality of 3D BIM model data, utilizing a proposed project quality control checklist. The automated system consists of four key elements: a BIM-based model, a Data Extraction and Analysis Module, a Data Storage Module, and a Data Visualization Module. The Data Extraction and Analysis Module extracts relevant information and parameters from BIM models to evaluate their quality against predefined checklists. Then, it transfers the information and stores the results in a database. The database is connected to an engineering project collaboration tool, ProjectWise, to automatically update and store the data in the cloud. The database is then connected to an interactive data visualization platform, Power BI, to enable automatic visualization of the generated quality assessment results of the BIM models' data. This system was applied to a Canadian infrastructure construction project by its BIM department during the preliminary and detailed design phases. It demonstrated an average quality score (AQS) of 87.6% for the BIM models and significantly reduced failing items by around 30%. This study concludes that the system offers a robust, practical solution for enhancing the quality control process in BIM model data management, thereby aiding engineers in timely model adjustments to meet project requirements. [ABSTRACT FROM AUTHOR]

A novel, sensible, rapid, reliable and economical analytical hyphenated LC-MS/MS method has been developed as a key for the safety surveillance in chronic leukemia patients, and as a part of therapeutic drug monitoring of imatinib mesylate in human saliva. Imatinib mesylate or imatinib methane sulfonate is a tyrosine kinase inhibitor, apoptosis inducer and also known to be an anticoronaviral agent. Imatinib mesylate is a monomesylate salt of imatinib used for the treatment of gastrointestinal tumors and chronic myelogenous leukemia, and also in other complex malignancies. The lmax of imatinib mesylate was observed at 258 nm by UV spectrometry, establishing a very good linearity along with sensitivity. The detection limit (LOD) =0.2925 µg mL-1 and quantitation limit (LOQ)= 0.8977 µg mL-1 were obtained from the linear concentrations taken in the range of 2-12 µg mL-1. The correlation coefficient (r2) found was 0.999. The method validation parameters according to ICH Q2 (R1) were performed. The developed method described here, UPLC-MS/MS, was found to be novel, sensitive and rapid with improved results when successfully tested for human saliva samples without significant differences in the steady state imatinib mesylate concentrations. Current method could overcome the safety issues during therapeutic drug monitoring and pharmacokinetic behavior of the drug when tested clinically. [ABSTRACT FROM AUTHOR]

Background: Shortcomings in current analytical methods characterized by time-consuming procedures, limited sensitivity, and high costs associated with reagents and instruments, influence the research background. Objectives: The goal of this research was to find a simple, fast, and accurate way to discern and quantify substances in bulk drugs and finished products at the utmost minimal levels of detection and quantification. Materials and Methods: The methodology involved using a C18 column then a solvent mixture comprising 0.1% orthophosphoric acid and acetonitrile in an 80:20 proportion delivered at 1 mL/min-1 and observed at 247 nm with a UV detector. Results: Following rigorous verification in line with ICH guidelines, the technique revealed several notable features. It revealed rapidity with a retention time of 2.53 min, accurate with average recoveries ranging from 99.20% to 100.43%, precision as demonstrated by a relative standard deviation below 2%, specificity, and a highly linear correlation coefficient of 0.999 between 0.0025 to 6 µg mL-1. Additionally, the method displayed remarkable sensitivity, detecting concentrations as low as 56.91 ng mL-1 and a quantification limit of 172.44 ng mL-1. Conclusion: This tested RP-HPLC method has a unique mix of speed, accuracy, and high sensitivity that makes it possible to accurately measure Vardenafil hydrochloride trihydrate, even at nanogram levels. This surpasses established techniques and offers a cost-effective solution for pharmaceutical quality control and analysis. [ABSTRACT FROM AUTHOR]

A fast method for microplastic detection is thermal extraction desorption‐gas chromatography/mass spectrometry (TED‐GC/MS), which uses polymer‐specific thermal decomposition products as marker compounds to determine polymer mass contents in environmental samples. So far, matrix impacts of different environmental matrices on TED‐GC/MS performance had not yet been assessed systematically. Therefore, three solid freshwater matrices representing different aquatic bodies with varying organic matter contents were spiked with a total of eight polymers. Additionally, for the first time, the two biodegradable polymers polybutylene adipate terephthalate (PBAT) and polylactide (PLA) were analysed using TED‐GC/MS. The methodological focus of this work was on detectability, quality of signal formation as well as realisation of quantification procedures and determination of the limit of detection (LOD) values. Overall, TED‐GC/MS allowed the unambiguous detection of the environmentally most relevant polymers analysed, even at low mass contents: 0.02 wt% for polystyrene (PS), 0.04 wt% for the tyre component styrene butadiene rubber (SBR) and 0.2 wt% for polypropylene (PP), polyethylene (PE) and PBAT. Further, all obtained LOD values were increased in all matrices compared to the neat polymer without matrix. The LOD of the standard polymers were increased similarly (PS: 0.21–0.34 µg, SBR: 0.27–0.38 µg, PP: 0.32–0.36 µg, PMMA: 0.64–1.30 µg, PET: 0.90–1.37 µg, PE: 3.80–6.99 µg) and their decompositions by radical scission processes were not significantly influenced by the matrices. In contrast, matrix‐specific LOD increases of both biodegradable polymers PBAT (LOD: 1.41–7.18 µg) and PLA (0.84–20.46 µg) were observed, probably due to their hetero‐functional character and interactions with the matrices. In conclusion, the TED‐GC/MS performance is not solely determined by the type of the polymers but also by the composition of the matrix. [ABSTRACT FROM AUTHOR]

Simple Summary: Soil-transmitted helminth parasites are associated with a neglected tropical disease affecting both humans and animals. Proper management of the infection requires an accurate diagnostic technique. Therefore, in an era of STH prevention and control, a new lab-on-a-disc (LoD)-based diagnostic technique called single-image parasite quantification (SIMPAQ) was developed with the ability to focus all STH eggs in an imaging zone, where a digital image can be captured for further processing. This report evaluates the performance of SIMPAQ in terms of prevalence, sensitivity, specificity and predictive values. In this study, a total of 518 animal faeces samples were examined using McMaster, test tube simple flotation, and the LoD technique. The highest prevalence was demonstrated by the LoD technique, which also demonstrated high sensitivity in the detection of STH eggs. Soil-transmitted helminth (STH) infections are caused by roundworms, hookworms, whipworms, and thread worms. Accurate diagnosis is essential for effective treatment, prevention, and control of these infections. This study evaluates a new diagnostic method called Single-image Parasite Quantification (SIMPAQ), which uses a lab-on-a-disc (LoD) technique to isolate STH eggs into a single imaging zone for digital analysis. The study evaluates the purification performance of the SIMPAQ technique for detecting STH eggs in animal samples. This was a cross-sectional study conducted among 237 pigs and 281 dogs in the Morogoro region in Tanzania. Faecal samples were collected and processed with the LoD technique, as well as flotation and McMaster (McM) methods for comparison purposes. The overall prevalence of STH infections was high as per the LoD technique (74%), followed by McM (65.44%) and flotation (65.04%). Moreover, the overall performance of the LoD technique, using McM as the gold standard, was 93.51% (sensitivity), 60.89% (specificity), 81.91% (PPV), and 83.21% (NPV). The LoD technique exhibited high prevalence, sensitivity, and NPV, which demonstrates its value for STH egg detection and its crucial role in the era of accurate STH diagnosis, promoting proper management of the infection. [ABSTRACT FROM AUTHOR]

The present research work discusses the development and validation of a UV spectrophotometric method for butorphanol tartrate. Simple, accurate and cost efficient spectrophotometric method has been developed for the estimation of butorphanol tartrate in tablet dosage form. The optimum conditions for the analysis of the drug were established. The maximum wavelength (λ max) was found to be 278nm. The percentage recovery of butorphanol tartrate was in the 100.016±0.68. Beers law was obeyed in the concentration range of 2-12µg/ml. Calibration curves shows a linear relationship between the absorbance and concentration. The line equation y = 0.0674x - 0.0057 with r2 of 0.9998was obtained. Validation was performed according to ICH guidelines for linearity, accuracy, precision, LOD and LOQ. The sample solution was stable up to 36 hours. The proposed method may be suitable for the analysis of butorphanol tartrate in tablet formulation for quality control purposes. [ABSTRACT FROM AUTHOR]

IntroductionThe use of illicitly manufactured synthetic opioids, specifically fentanyl and its analogs, has escalated exponentially in the United States over the last decade. Due to the targeted nature of drug detection methods in clinical laboratories and the ever-evolving list of synthetic opioids of concern, alternative analytical approaches are needed.MethodsUsing the fentanyl analog screening (FAS) kit produced by the Centers for Disease Control and Prevention (CDC), we developed a liquid chromatography-high resolution mass spectrometry (LC-HRMS) synthetic opioid spectral library and data acquisition method using information dependent acquisition of product ion spectra. Chromatographic retention times, limits of detection and matrix effects, in urine and serum, for the synthetic opioids in the FAS kit (n = 150) were established. All urine and serum specimens sent to a clinical toxicology laboratory for comprehensive drug testing in 2019 (n = 856) and 2021 (n = 878) were analyzed with the FAS LC-HRMS library to determine the prevalence of fentanyl analogs and other synthetic opioids, retrospectively (2019) and prospectively (2021).ResultsThe limit of detection (LOD) of each opioid ranged from 1 to 10 ng/mL (median, 2.5 ng/mL) in urine and 0.25-2.5 ng/mL (median, 0.5 ng/mL) in serum. Matrix effects ranged from -79 % to 86 % (median, -37 %) for urine, following dilution and direct analysis, and -80 % to 400 % (median, 0 %) for serum, following protein precipitation. The prevalence of fentanyl/fentanyl analogs in serum samples increased slightly from 2019 to 2021 while it remained the same in urine. There were only 2 samples identified that contained a fentanyl analog without the co-occurrence of fentanyl or fentanyl metabolites. Analysis of the established MS/MS spectral library revealed characteristic fragmentation patterns in most fentanyl analogs, which can be used for structure elucidation and drug identification of future analogs.ConclusionsThe LC-HRMS method was capable of detecting fentanyl analogs in routine samples sent for comprehensive drug testing. The method can be adapted to accommodate testing needs for the evolving opioid epidemic.

The healthcare industry is constantly changing because of technological breakthroughs that spur new methods of diagnosing and treating illnesses. This study investigates the development of Ion Sensitive Field Effect Transistor (ISFET) sensors for DNA-based blood cancer diagnosis. This work presents the design of a two-dimensional ion-sensitive field-effect transistor. Concentration fluctuations and transfer characteristics with different oxides are studied using blood from two electrolyte solutions. It is possible to evaluate how the modeled device can be utilized as a pH sensor or a biosensor in healthcare applications by looking at how the pH changes for different oxides. Additionally, several oxides were examined in the simulated ISFET devices' output characteristics. Blood is the electrolyte to study the device's sensitivity for different oxides. When pH 7.4 is considered, SiO2 oxide is significantly more sensitive than other oxides. The resulting 2D-ISFET exhibits remarkable blood electrolyte sensitivity and holds potential as a quick detection tool for blood cancer. The results show that the ISFET possesses drain-induced barrier lowering (DIBL), greater ON-current (ION) and switching ratio (ION/IOFF), and decreased subthreshold swing (SS). The pH sensor's sensitivity and the suggested equipment can detect up to 30 fg/mL of blood cancer biomarkers. An important development in technology-driven healthcare is the emergence of DNA-based blood cancer detection utilizing ISFET sensors. This opens up new avenues for improving cancer diagnosis and patient outcomes.

This article details a correction to: Autiero, S., Elwert, F., Moscatelli, C., & Pons, J. (2023). The Seven Steps: Building the DiGA Thesaurus. Journal of Open Humanities Data, 9. https://doi.org/10.5334/johd.111.

In order to improve the feasibility and comprehensiveness of the application of BIM lightweight technology in water conservancy projects, this paper analyzed and summarized the mainstream BIM lightweight technology. Taking Miyun reservoir reconstruction and elimination of hazards project as an example, it put forward the application route of water conservancy project BIM lightweight technology, and improved the application effects of BIM lightweight technology in different construction stages. In the design stage, the comprehensive use of model reduction optimization, rendering optimization and BIM lightweight collaborative design platform can greatly improve the efficiency of three-dimensional model design; By using the BIM lightweight engine to transmit the BIM design model to the construction stage and establishing a BIM lightweight construction management platform, the quality of construction management can be effectively improved, ensuring that the project is completed on time and with quality. For the current status of BIM lightweight technology, this paper puts forward suggestions for future development: BIM lightweight technology should be able to integrate a variety of water conservancy engineering industry characteristics of data, improve the BIM specifications and standards, so that the BIM lightweight application system is more standardized and scientific. [ABSTRACT FROM AUTHOR]

The objective of this study is to propose a knowledge organization system (KOS) for the ethnic groups of Laos by utilizing linked open data (LOD) to standardize the metadata. Data of 49 Laos ethnic groups and the techniques of Linked Open Data were used. Linked data of ethnic groups in Lao PDR from other external standardized data sources, including DBpedia and Wikidata, was found. The results indicate that there is limited an information on the ethnic groups of Laos in online databases. This study aims to link and improve data on Laos ethnic groups by utilizing ontology and reconciliation techniques to link incomplete or outdated data, as well as using OpenRefine and RDF extension to link the source database. Although the country has implemented policies to promote the national identity and the tourism economy, much of the related information remains inaccessible to the public as it is only available in official documents. The available information in the online database system would be compared to foreign languages like Vietnamese, Thai, etc., because these areas and ethnic groups were close to each other, and the languages were in the same family. [ABSTRACT FROM AUTHOR]

A class of pesticides known as neonicotinoids is commonly used in agriculture, but the pesticides are harmful to bees, other pollinators, and humans. To detect neonicotinoids in the environment, sensitive and selective methods are needed. The conventional techniques of gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography (HPLC) are effective, but expensive and time-consuming. A promising alternative to real-time detection of neonicotinoids is electrochemical analysis, since it is relatively inexpensive and can be performed instantly. Electrochemical sensors are primarily sensitive to the surface of the working electrode. Various modifiers are employed to enhance the sensitivity and selectivity of the electrochemical sensor. This review article focuses on recent advances in neonicotinoid detection technologies using metal/metal oxide nanoparticles, graphene/graphene oxide, carbon nanotubes, metal-organic frameworks, and conducting polymers. The detailed descriptions of the developed electrochemical sensors, including sensitivity, selectivity, detection limits, sample complexity, and field applicability, are presented. The article also discussed current challenges and future prospects for electrochemical methods for real-time monitoring. [ABSTRACT FROM AUTHOR]

A simple imine derivative based sensor (IDP) has been synthesized and characterized by 1 H NMR, 13 C NMR and mass spectral techniques. IDP is more capable of detecting perfluorooctanoic acid (PFOA) in a selective and sensitive manner. The PFOA as a biomarker interacts with IDP and shows "TURN-ON" response by colorimetric and fluorimetric method. Under optimized experimental observations, the selective determination of PFOA using IDP among other competitors as biomolecules has been noticed. The detection limit is 0.31 × 10− 8 mol/L. The practical applications of the IDP is effectively evaluated in human biofluids and water samples. [ABSTRACT FROM AUTHOR]

Merocyanine 540 dye (MC 540) has been demonstrated as a 'turn-off' fluorescent probe to detect hypochlorite ions (ClO−) in an aqueous medium. MC 540 was separately investigated by fluorescence and absorption spectroscopy in the presence of various analytes, including cations and anions. It was revealed that the fluorescence intensity of MC 540 was effectively quenched with only ClO− ions without being affected by the other twenty-five analytes. This was also observed with the naked eye, and the color of MC 540 changed from pink to colorless in the presence of only ClO− ions. Moreover, fluorescence interference experiments were performed for ClO−. MC 540 was found to detect ClO− independently of other analytes. The interaction ratio between MC 540 and ClO− was determined as 4:1, and the binding constant (Ka) was calculated as 28.38 M−4 for MC 540. The detection limit (LOD) of ClO− was determined to be 6.83 nM. The presented method was reliably applied to drinking, natural spring, and tap water samples. Thus, it has been proven that the MC 540 can be used as a sensitive, selective, color-changeable, and easy-to-apply 'turn-off' fluorescence sensor to detect ClO− in a specific concentration range. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal's disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia, Ruminococcus, Clostridium, and Streptococcus, to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease. [ABSTRACT FROM AUTHOR]

Due to the high correlation between Effective Angular Momentum (EAM) and Length of Day (LOD) data, and the wide application of LOD prediction, this study proposes to combine EAM data with Global Navigation Satellite System (GNSS) LOD data to obtain a more accurate LOD series and attempt to provide a reasonable formal error for the EAM dataset. Firstly, tidal corrections are applied to the LOD data. A first-order difference method is proposed to identify outliers in GNSS LODR (tidal corrected LOD) data, and the EAM data are converted into LODR data using the Liouville equation. Then, the residual term and the fitted term are obtained by least squares fitting. Finally, the fitted residual terms of GNSS LODR and EAM LODR are combined by using the Kalman combination method. In this study, EAM data from the German Research Centre for Geosciences (GFZ) (2019–2022), as well as LOD data from Wuhan University (WHU) and Jet Propulsion Laboratory (JPL), are used for the Kalman combination algorithm experiment. In the Kalman combination, we consider weighted combination based on formal error. However, none of the computing centers provide an uncertainty estimation for the EAM dataset. Therefore, we simulate the combination experiment of LOD and EAM with formal error ranging from 0 to 100 us. The experiment shows that using reasonable formal error for the EAM dataset can improve the accuracy of LOD. Finally, when the formal error of EAM is 2–5 times that of the GNSS LOD formal error, i.e., the EAM formal error is between 10 and 30 us, the accuracy of the combined LOD can be improved by 10–20%. [ABSTRACT FROM AUTHOR]

Immunoassays (IAs) with fluorescence-based detection are already well-established commercialized biosensing methods, such as enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay (LFIA). Immunoassays with surface-enhanced Raman spectroscopy (SERS) detection have received significant attention from the research community for at least two decades, but so far they still lack a wide clinical commercial application. This review, unlike any other review that we have seen, performs a three-dimensional performance comparison of SERS IAs vs. fluorescence IAs. First, we compared the limit of detection (LOD) as a key performance parameter for 30 fluorescence and 30 SERS-based immunoassays reported in the literature. We also compared the clinical performances of a smaller number of available reports for SERS vs. fluorescence immunoassays (FIAs). We found that the median and geometric average LODs are about 1.5–2 orders of magnitude lower for SERS-based immunoassays in comparison to fluorescence-based immunoassays. For instance, the median LOD for SERS IA is 4.3 × 10−13 M, whereas for FIA, it is 1.5 × 10−11 M. However, there is no significant difference in average relative standard deviation (RSD)—both are about 5–6%. The analysis of sensitivity, selectivity, and accuracy reported for a limited number of the published clinical studies with SERS IA and FIA demonstrates an advantage of SERS IA over FIA, at least in terms of the median value for all three of those parameters. We discussed common and specific challenges to the performances of both SERS IA and FIA, while proposing some solutions to mitigate those challenges for both techniques. These challenges include non-specific protein binding, non-specific interactions in the immunoassays, sometimes insufficient reproducibility, relatively long assay times, photobleaching, etc. Overall, this review may be useful for a large number of researchers who would like to use immunoassays, but particularly for those who would like to make improvements and move forward in both SERS-based IAs and fluorescence-based IAs. [ABSTRACT FROM AUTHOR]

The significance of Linked Open Data datasets for traffic information extends beyond just including open traffic data. It incorporates links to other relevant thematic datasets available on the web. This enables federated queries across different data platforms from various countries and sectors, such as transport, geospatial, environmental, weather, and more. Businesses, researchers, national operators, administrators, and citizens at large can benefit from having dynamic traffic open data connected to heterogeneous datasets across Member States. This paper focuses on the development of a semantic model that enhances the basic service to access open traffic data through a LOD-enhanced Traffic Information System in alignment with the ITS Directive (2010/40/EU). The objective is not limited to just viewing or downloading data but also to improve the extraction of meaningful information and enable other types of services that are only achievable through LOD. By structuring the information using the RDF format meant for machines and employing SPARQL for querying, LOD allows for comprehensive and unified access to all datasets. Considering that the European standard DATEX II is widely used in many priority areas and services mentioned in the ITS Directive, LOD DATEX II was developed as a complementary approach to DATEX II XML. This facilitates the accessibility and comprehensibility of European traffic data and services. As part of this development, an ontological model called dtx_srti, based on the DATEX II Ontology, was created to support these efforts. [ABSTRACT FROM AUTHOR]

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Background and Objectives: Plantago is a diverse genus of the Plantaginaceae family. Plantago lanceolata L. (P. lanceolata) and Plantago major L. (P. major) are used commercially worldwide as a traditional treatment for many diseases. A sensitive, simple, and reliable high-performance liquid chromatography (HPLC) method was developed to simultaneously quantify the three active ingredients: apigenin, catalpol, and gallic acid in P. lanceolata and P. major. Methods: HPLC analysis was carried out using C8 and C18 columns. The mobile phase comprised acetonitrile, orthophosphoric acid, or formic acid (different ratio V/V) with flow rates of 0.4, 0.8, and 1 mL/min. The eluted peaks were detected at 204, 210, 256, and 330 nm. The crude extracts were separated using the liquid-liquid extraction method. Results: HPLC analysis was performed using the C8 column with the mobile phase consisting of acetonitrile–orthophosphoric acid (1:1%) at a 1 mL/min flow rate. The detection of the eluted peaks was observed at 204 nm. Using this protocol, the detection and quantification limits for apigenin, catalpol, and gallic acid were 0.007 and 0.022 μg/mL, 0.04 and 0.14 μg/mL, 0.02 and 0.073 μg/mL, respectively. The calibration curve’s correlation coefficient indicated good linearity (r>0.9996, 0.9991, and 0.9978), with average recoveries for the three compounds between 100.02, 95.98, and 108.30%, respectively. Meanwhile, the intra-day and inter-day accuracy averages ranged from 100.07 to 99.95%, respectively. The results showed that using dichloromethane extracts of Plantago species leaves produced the highest yield of apigenin (1.08 and 0.58 μg/mg). At the same time, gallic acid was more abundant in methanolic, butanol, and aqueous extracts of P. lanceolata (3.33 μg/mg) and P. major (3.95, 4.34, and 4.72 μg/mg). The aqueous extract of P. lanceolata leaf and P. major root also showed more catalpol content (9.339 and 2.451 μg/mg). Conclusion: The developed method indicated reliable results with reproducibility, high accuracy in an analytical run, repeatability, acceptable intermediate precision, reproducibility, and stability of these working solutions. To the best of our knowledge, this study is the first report for the simple, simultaneous quantification of three compounds in Plantago spp. using HPLC.

Abstract Unmanned Aerial Vehicles (UAVs) are often preferred for modeling cultural heritage buildings due to their costs and time savings. The need for data collection, analysis, processing, and visual presentation in the context of cultural heritage buildings has become prominent, underscoring the significance of the concept of Level of Detail (LoD). The utilization of CityGML LoD standards enhances the performance of visual presentations, decreases the geometric complexity of objects, and enables users to view the model at the desired level of detail within a computerized environment. Within the scope of this study, it is aimed to determine the accuracy analysis of the 3D model for a cultural building, which is named Hekimbaşı Hunting Lodge, at different LoDs. Drawings were created at LoD 0-1-2-3 levels with 418 photographs taken by the UAV photogrammetry method. Additionally, conservative and UAV measures of facade detail at the same LoD were compared in terms of accuracy. As a result, RMSE values for X, Y, and Z axes at LoD3 standard were calculated as 1.394 cm, 0.861 cm, and 0.694 cm, respectively. It has been concluded that the high-accuracy LoD models for the cultural building could be produced using the UAV photogrammetry method at the desired accuracy.

The buildings can influence wind flow, while a better wind flow in a city will improve the air quality for the sustainable development of the urbanites. At present, Computational Fluid Dynamics (CFD) is commonly used for wind flow simulation. However, CFD simulation is able to focus only on a certain height of a building. Hence, the 3D building model Level of Details (LoD) plays a vital role in the simulation. As regards the 3D building model standard, CityGML standard provides different LoD such as LoD1.0, LoD1.1, LoD1.2, LoD1.3, LoD2.0, LoD2.1, LoD2.2, LoD2.3, LoD3.0, LoD3.1, LoD3.2 and LoD3.3. Thus, this study aimed to overcome this problem by determining the best 3D building model’s LOD for CFD wind movement simulation. This study ran CFD simulation experiments on each stated LoD using the same 3D model building. Several important points (locations) at the building were selected and analysed to obtain the best wind velocity analysis for the LoDs. Through such analysis, LoD3.1 was selected as the model that fulfils the minimum requirements to have the best CFD wind flow simulation. This research can help future planning of cities towards realizing sustainable city development by taking into account the factors affecting wind movement in the city.

The laser-induced breakdown spectroscopy assisted by laser-induced fluorescence (LIBS-LIF) in a two-step process was used to measure the concentration of platinum (Pt) and palladium (Pd) by surface analysis of a solid ore core from the Lac des Iles mine followed by analysis of the same core that was pulverized and compacted. This work focuses mainly on the measurement of Pt since the case of Pd has been extensively discussed in previous work. The excitation of Pt is performed at 235.71 nm with fluorescence emission observed near 269.84 nm. Calibration was performed with synthetic samples prepared from the same ore as the samples studied and the calibration curve shows good linearity in Pt content over several orders of magnitude. A limit of detection (LOD) of approximately 0.15 parts per million (ppm) over an average of 200 laser shots was demonstrated. In contrast, conventional LIBS provides a LOD of about 21 ppm over an average of 200 laser shots due to low signal-to-noise ratio and spectral interference from other elements and does not meet the requirements for estimating the average Pt concentration in the ore. The Pt concentrations obtained using LIBS-LIF on solid ore are generally in good agreement with those obtained in its pulverized and compacted form, as well as with laboratory measurements made by conventional chemical methods. However, the comparison of the results obtained for Pd using LIBS-LIF with the laboratory showed a less satisfactory agreement, probably due to its more inhomogeneous distribution in the ore. Graphical abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]