Standard Deviation Values Research Articles

Perilaku Organizational Citizenship Behavior pada Karyawan

Every company is required to be able to improve company performance maximally and effectively, especially to improve individual performance. The low quality of human resources will certainly have a negative impact on the company, while successful companies need employees who are willing to do more than just their formal duties and are willing to provide performance that exceeds expectations. The purpose of this research is to determine organizational citizenship behavior in employees. This research was conducted on 72 permanent employee subjects. The research uses a quantitative approach with saturated sampling techniques. The data collection technique uses a questionnaire with measurements based on organizational citizenship behavior variables. The data analysis technique uses descriptive analysis and determines the calculated average for each aspect. The results of data processing show that the minimum value for the organizational citizenship behavior variable is 82.00 with a maximum value of 134.00 and a mean value of 108.36. The standard deviation value is 10.57809. As for aspects of organizational citizenship behavior, the average obtained was the altruism aspect of 3.15. The average courtesy aspect is 3.31. The average sportsmanship aspect is 3.18. The average conscientiousness aspect is 3.21. The Civic Virtue aspect averages 3.09.

HPTLC quantification of garcinol in three endemic Garcinia species of Assam, estimation of secondary metabolites and evaluation of in vitro antioxidant activity

AbstractGarcinol, the main polyisoprenylated benzophenone present in Garcinia species. A simple, rapid, reliable high-performance thin-layer chromatography (HPTLC) technique has been developed for simultaneous detection and quantification of garcinol in three endemic Garcinia sp. of Assam, India. While G. mangostana and G. indica have garnered extensive recognition, these lesser-known species have not received proportionate level of scientific exploration, therefore has served as the subject of investigation. Chromatographic separation was achieved using pre-coated silica gel 60 F254 plates. The optimized mobile phase (Toluene-Ethyl acetate-Formic acid, 5:4:1V/V) at 276 nm produced well-defined and sharp peaks of garcinol, maintaining a constant RF value of 0.75. The regression equation demonstrated a linear relationship with a correlation coefficient of 0.9955. The method was validated in accordance with International Conference of Harmonization guidelines (ICH), encompassing assessments for precision, accuracy, repeatability and robustness, all of which yielded low percentage of relative standard deviation values, attesting to its excellent performance. The content of garcinol found in the extracts were in the range of 0.58–0.98% w/w. In secondary metabolite analysis, significant amount of phenols (26.06 ± 1.65–57.51 ± 2.62 gallic acid equivalent mg g−1), flavonoids (11.27 ± 1.06–21.09 ± 1.34 quercetin equivalent mg g−1) and ascorbic acid (3.56 ± 0.12–3.65 ± 0.11 mg/10 g) contents were detected in the extracts. Further, the extracts exhibited good anti-radical activity, which may be attributed to the presence of important secondary metabolites. Therefore, this research establishes the three endemic Garcinia sp. as promising source of garcinol. Additionally, the developed method can be applied for routine quality control analysis of herbal formulations containing garcinol.

Wind-induced vibration response of supertall sightseeing tower evaluation during construction through wind tunnel test of aeroelastic models

Four construction phases of an ultra-high sightseeing tower with a cable-barrel composite structure and their wind-induced vibration response were studied. The first-order natural vibration characteristic of the structure in four different construction phases was calculated through finite element models, and associated aeroelastic models were also designed. Meanwhile, rough strips are applied uniformly on the surface of the model to compensate the Reynolds number of the wind tunnel test. The performance of this method was investigated utilizing the pressure test of rigid segment models. The wind-induced vibration response under four construction conditions, and the effects of wind direction angle, wind speed and structural damping ratio were investigated through the wind tunnel test of aeroelastic models. The results show that sticking rough strips on the surface can effectively improve the Reynolds number of wind tunnel tests. As the wind speed during construction increases, the structural wind-induced vibration response intensifies. A large vortex-induced resonance occurs in the construction phase of a cable-barrel composite structure with the Strouhal number around 0.12 under turbulent conditions in this study. Furthermore, the crosswind-induced vibration response of the structure at a wind deflection angle of 0° is greater than 45° and 90°. Specifically, the mean value of downwind displacement and the maximum value of standard deviation (STD) of downwind and crosswind displacements on the prototype tower top at 0° during construction phases are 1.21 m, 0.35 m, and 0.25 m respectively. Thus, the risk of large wind-induced vibration should be fully considered during construction. Implementing corresponding damping measures to improve the damping ratio of the structure proves effective in restraining its vibration.

Non-Enzymatic Detection of Glucose and Ketones in Urine using Paper-Based Analytical Devices

Diabetes, driven by unbalanced diets and unhealthy lifestyles, is highly prevalent. In Indonesia, its prevalence is projected to reach 28.6 million by 2045. Microfluidic paper-based analytical devices (μPADs) are paper-based analytical tools that use hydrophilic paper for measurement and hydrophobic barriers to control fluid flow. This research aims to develop a non-enzymatic method for detecting glucose and ketones in artificial urine using S2Z-μPADs. The fabrication of S2Z-μPADs involves printing the design on Whatman No. 1 paper using wax printing and applying silver nanoparticles for glucose detection and the Schiff base reaction for ketone detection. The results show that the optimum condition for glucose detection is achieved with an AgNO3 concentration of 500 mM. A NaOH concentration of 10 M. Acetoacetate detection is optimized with a glycine concentration of 1 M, sodium nitroprusside concentration of 15%, NaOH concentration of 1 M, a drying time of 8 minutes, and a reaction time of 10 minutes. Validation results demonstrate good linearity for glucose (R² = 0.9821) and ketones (R² = 0.995). High precision was achieved with relative standard deviation (RSD) values of 3.792% for glucose and 1.482% for ketones. The obtained limits of detection (LOD) and limits of quantification (LOQ) indicate that the developed S2Z-μPADs can differentiate between each category of diabetes. The accuracy of glucose and ketone detection ranges from 87.463% to 97.374%. The high accuracy of the μPADs highlights their potential for reliable diabetes management and effective disease monitoring.

Identifying Nursing Students' Views of Studying Mental Health and Diseases Nursing Course via Distance Education during the Pandemic

Objective: This research was conducted to determine students' opinions about taking the mental health and disease nursing course through distance education. Methods: The research, designed as a descriptive quantitative study, and conducted with students (n=243) taking the Mental Health and Disease Nursing course at the Nursing Department of a state university in Ankara. "Participant Information Form", " Assessment Form for Mental Health and Diseases Nursing Course Distance Education," created by the researchers, and the "Opinions About Distance Education Scale" were used to collect the data. In data analysis, content analysis was performed for open-ended questions, and the data were presented under themes, sub-themes, and categories. Number, percentage, mean, standard deviation, median, minimum, and maximum values were given for the scale scores. Results: The views of students on distance education were conceptualized under four themes: "Views on distance education", "Effectiveness of teaching methods used", ''Effectiveness of methods used in the practice skill courses, ''Preparedness for provide nursing care to patients followed up with a psychiatric diagnosis.' The total mean score of the participants for the opinions about the distance education scale was determined as 2.91±0.48. Conclusion: The students evaluated the education provided through distance education as moderately sufficient. The teaching methods used in the mental health and diseases nursing course taken through distance education and ensuring permanence through repeated access to courses were stated as positive aspects in theoretical terms, significant deficiencies were expressed in terms of contacting patients in the clinical environment and gaining professional roles.

Development of HPTLC method for simultaneous determination of quercetin and kaempferol in leaf extract of Hibiscus mutabilis

The aim of this study was to develop and validate a densitometric High-Performance Thin-Layer Chromatography (HPTLC) method for the simultaneous quantification of quercetin (Q) and kaempferol (K) in Hibiscus mutabilis leaf extracts. The analyses were performed on silica gel 60 F254 plates using a mobile phase composed of toluene, formic acid, and ethyl acetate (6:0.4:4, v/v/v). Detection was carried out at a wavelength of 272 nm using a deuterium and tungsten light source. The method exhibited excellent linearity over the concentration range of 100–600 ng/spot for quercetin and 500–3000 ng/spot for kaempferol, with determination coefficients (r2) of 0.9989 and 0.9973, respectively. The method showed no interferences from the plant matrix. The relative standard deviation (RSD) values for intra- and inter-day precision were less than 2% for both flavonoids. Recovery rates ranged from 97.69% to 99.20% for quercetin and from 89.91% to 95.87% for kaempferol. The limits of detection (LOD) were 190.23 ng/spot for quercetin and 187.23 ng/spot for kaempferol, while the limits of quantification (LOQ) were 570.10 ng/spot for quercetin and 566.12 ng/spot for kaempferol. This validated HPTLC method is reliable, precise, and accurate, making it suitable for the quality control of Hibiscus mutabilis leaf extracts. The study’s findings can be broadly applied to the quality control of herbal products, pharmacological research, and the development of nutraceuticals. The method’s ability to provide rapid and accurate quantification makes it an invaluable tool for researchers across various disciplines.

Engineering the Hot-Spots in Au-Ag Alloy Nanoparticles through Meniscus-Confined 3D Printing for Microplastic Detection.

The escalating concern surrounding microplastic (MP) pollution necessitates urgent attention and the development of rapid techniques for quantifying extremely low concentrations. Surface-enhanced Raman spectroscopy (SERS) has emerged as a promising method due to its simplicity, high sensitivity, and rapid quantification capabilities. Herein, the efficacy of gold-silver alloy nanoparticles (3DPAu-Ag) substrates for detecting poly(methyl methacrylate) (PMMA) and polystyrene (PS) MPs is investigated. The 3DPAu-Ag SERS substrates are fabricated using the meniscus-confined electrochemical 3D printing (MC-E3DP) process, employing a nozzle of 0.8 mm size with 2.5 V potential at a printing speed of 0.4 mm s-1. The proposed SERS substrates exhibit exceptional sensitivity and are capable of detecting PMMA concentrations as low as 0.2 μg mL-1 and PS concentrations of 1.2 μg mL-1 within the ranges of 1-103 μg mL-1 and 10-104 μg mL-1, respectively. Remarkable enhancement factors (EFs) of up to 3.2 × 104 for PMMA and 9.3 × 103 for PS are achieved, underscoring the substrates' effectiveness. Furthermore, the investigation demonstrates outstanding uniformity and reproducibility of the 3DPAu-Ag substrates, with relative standard deviation (RSD) values of only 4.1 and 6.4%, respectively, across 31 and 5 measurements. Additionally, a minimal 17% decrease in the initial SERS signal value after 5 weeks highlights the substrates' high stability. This not only highlights the superior quality of the substrates but also positions them ahead of previously reported works in the literature. Moreover, this study also comes up with a plausible mechanism for MPs SERS detection facilitated by the 3DPAu-Ag substrates, offering insights into the underlying processes. Overall, 3DPAu-Ag substrates show promise for sensitive, stable MP detection, which is crucial for environmental monitoring.

Rapid and specific differentiation of Salmonella enterica serotypes typhi and Paratyphi by multicolor melting curve analysis

Rapid and accurate identification of Salmonella enterica serotypes Typhi and Paratyphi (A, B and C), the causal agents of enteric fever, is critical for timely treatment, case management and evaluation of health policies in low and middle-income countries where the disease still remains a serious public health problem. The present study describes the development of a multiplex assay (EFMAtyping) for simultaneous identification of pathogens causing typhoid and paratyphoid fever in a single reaction by the MeltArray approach, which could be finished within 2.5 h. Seven specific genes were chosen for differentiation of typhoidal and nontyphoidal Salmonella. All gene targets were able to be detected by the EFMAtyping assay, with expected Tm values and without cross-reactivity to other relevant Salmonella serovars. The limit of detection (LOD) for all gene targets was 50 copies per reaction. The LOD reached 102–103 CFU/ml for each pathogen in simulated clinical samples. The largest standard deviation value for mean Tm was below 0.5 °C. This newly developed EFMAtyping assay was further evaluated by testing 551 clinical Salmonella isolates, corroborated in parallel by the traditional Salmonella identification workflow, and serotype prediction was enabled by whole-genome sequencing. Compared to the traditional method, our results exhibited 100% of specificity and greater than 96% of sensitivity with a kappa correlation ranging from 0.96 to 1.00. Thus, the EFMAtyping assay provides a rapid, high throughput, and promising tool for public health laboratories to monitor typhoid and paratyphoid fever.

Establishing Healthy Breath Baselines With Tin Oxide Sensors: Fundamental Building Blocks for Noninvasive Health Monitoring.

Volatile organic compounds (VOCs) in breath serve as a source of biomarkers for medical conditions relevant to warfighter health including Corona Virus Disease and other potential biological threats. Electronic noses are integrated arrays of gas sensors that are cost-effective and miniaturized devices that rapidly respond to VOCs in exhaled breath. The current study seeks to qualify healthy breath baselines of exhaled VOC profiles through analysis using a commercialized array of metal oxide (MOX) sensors. Subjects were recruited/consented through word of mouth and using posters. For each sample, breath was analyzed using an array of MOX sensors with parameters that were previously established. Data were also collected using a lifestyle questionnaire and from a blood test to assess markers of general health. Sensor data were processed using a feature extraction algorithm, which were analyzed through statistical approaches to identify correlations with confounding factors. Reproducibility was also assessed through relative standard deviation values of sensor features within a single subject and between different volunteers. A total of 164 breath samples were collected from different individuals, and 10 of these volunteers provided an additional 9 samples over 6 months for the longitudinal study. First, data from different subjects were analyzed, and the trends of the 17 extracted features were elucidated. This revealed not only a high degree of correlation between sensors within the array but also between some of the features extracted within a single sensor. This helped guide the removal of multicollinear features for multivariate statistical analyses. No correlations were identified between sensor features and confounding factors of interest (age, body mass index, smoking, and sex) after P-value adjustment, indicating that these variables have an insignificant impact on the observed sensor signal. Finally, the longitudinal replicates were analyzed, and reproducibility assessment showed that the variability between subjects was significantly higher than within replicates of a single volunteer (P-value = .002). Multivariate analyses within the longitudinal data displayed that subjects could not be distinguished from one another, indicating that there may be a universal healthy breath baseline that is not specific to particular individuals. The current study sought to qualify healthy baselines of VOCs in exhaled breath using a MOX sensor array that can be leveraged in the future to detect medical conditions relevant to warfighter health. For example, the results of the study will be useful, as the healthy breath VOC data from the sensor array can be cross-referenced in future studies aiming to use the device to distinguish disease states. Ultimately, the sensors may be integrated into a portable breathalyzer or current military gear to increase warfighter readiness through rapid and noninvasive health monitoring.

Fast uncertainty assessment of in-service thrust control for turbofan engines: An equivalent model using Taylor expansion

An equivalent model using Taylor expansion (TEEM) is proposed for a fleet of engines regulated by the industrial baseline controller, aiming at the fast assessment of in-service thrust control under gas path and measurement uncertainties in advance. TEEM is fulfilled initially by the equivalent transformation of measurement uncertainties into engine set-point distribution, followed by a first-order Taylor expansion on the steady-state aero-thermal engine model along the average degradation curve of engine fleets. Simulations are conducted at take-off states on a validated aero-thermal turbofan engine model with publicly available uncertainty statistics on a desktop computer. Results show that the equivalent transformation is successful for both new and degraded engine fleets. Moreover, TEEM can estimate the mean and standard deviation values of key engine control parameters including thrust with the maximum errors of 0.04 % and 3.85 % for new engine fleets, 0.04 % and 6.25 % for degraded engine fleets, respectively, compared to the classic sample-based Monte-Carlo simulations (MCS). Computational time for TEEM and MCS for the tested life cycle are 3,018,564s and 137.52s accordingly, which means 99.995 % simulation time reduction is achieved by TEEM. Hence, the accuracy and efficiency of the proposed model for uncertainty assessment of thrust control of turbofan engines are confirmed.

A new approach based on 2D wavelet transform in the analysis of wettability behavior and evaporation rate for the surface of PTFE dielectric material used in high voltage applications

In this study, a new approach based on 2D wavelet transform is proposed for the analysis of wettability behavior and evaporation rate. Droplet images were taken from the PTFE dielectric sample surface at 30th, 270th, 510th, 750th, 990th, 1230th, 1470th, and 1710th seconds. The droplet images were decomposed into sub-bands using functions from six different wavelet families. The energy, entropy, mean, standard deviation, skewness, and kurtosis measures were calculated using wavelet coefficients for each sub-band image. Linear, exponential, and polynomial fitting methods were used to estimate the contact angle of the droplet images. The energy and standard deviation values, which are the selected optimal measures, were used as input in the fitting methods, and the regression coefficient (R2) and Root Mean Square Error (RMSE) values of the fitting methods were calculated. Thus, a high-performing contact angle prediction model with 2nd level sub-band image wavelet coefficients has been obtained.

EFL STUDENTS’ PERCEPTION ON THE IMPLEMENTATION OF CANVA AS LEARNING MEDIA

The development of times goes alongside the improvement of technology. Appropriate learning media is needed that a teacher can apply to students in class. In this case, Canva was chosen as classroom learning media. This research aimed to know the perceptions of 11th grade student of one of the public high schools in Bekasi students concerning the usage of Canva app as a teaching and learning media in English class. This research is a Quantitative method research. Quantitative data was obtained by using a questionnaire. The research sample was 75 students (N = 75) out of 370 students. After the data is obtained, the data is calculated with statistical calculations by finding the mean, median, mode and standard deviation values through the SPSS application. After that, the data was analyzed by descriptive analysis method. It was discovered that every statement derived from the student questionnaire responses fell into the "very good" category. Canva is an useful dan easy to use as an application to be a learning media in English classroom and students felt satisfy with the canva as a learning media in English class which it is related to satisfaction with the ease and ease of use of the canva application.

Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes

The Arctic and boreal regions are experiencing a rapid increase in temperature, resulting in a changing cryosphere, increasing human activity, and potentially increasing high-latitude methane emissions. Satellite observations from Sentinel-5P TROPOMI provide an unprecedented coverage of a column-averaged dry-air mole fraction of methane (XCH4) in the Arctic, compared to previous missions or in situ measurements. The purpose of this study is to support and enhance the data used for high-latitude research through presenting a systematic evaluation of TROPOMI methane products derived from two different processing algorithms: the operational product (OPER) and the scientific product (WFMD), including the comparison of recent version changes of the products (OPER, OPER rpro, WFMD v1.2, and WFMD v1.8). One finding is that OPER rpro yields lower XCH4 than WFMD v1.8, the difference increasing towards the highest latitudes. TROPOMI product differences were evaluated with respect to ground-based high-latitude references, including four Fourier Transform Spectrometer in the Total Carbon Column Observing Network (TCCON) and five EM27/SUN instruments in the Collaborative Carbon Column Observing Network (COCCON). The mean TROPOMI–TCCON GGG2020 daily median XCH4 difference was site-dependent and varied for OPER rpro from −0.47 ppb to 22.4 ppb, and for WFMD v1.8 from 1.2 ppb to 19.4 ppb with standard deviations between 13.0 and 20.4 ppb and 12.5–15.0 ppb, respectively. The TROPOMI–COCCON daily median XCH4 difference varied from −26.5 ppb to 5.6 ppb for OPER rpro, with a standard deviation of 14.0–28.7 ppb, and from −5.0 ppb to 17.2 ppb for WFMD v1.8, with a standard deviation of 11.5–13.0 ppb. Although the accuracy and precision of both TROPOMI products are, on average, good compared to the TCCON and COCCON, a persistent seasonal bias in TROPOMI XCH4 (high values in spring; low values in autumn) is found for OPER rpro and is reflected in the higher standard deviation values. A systematic decrease of about 7 ppb was found between TCCON GGG2014 and GGG2020 product update highlighting the importance of also ensuring the reliability of ground-based retrievals. Comparisons to atmospheric profile measurements with AirCore carried out in Sodankylä, Northern Finland, resulted in XCH4 differences comparable to or smaller than those from ground-based remote sensing.

Iodine concentration, HU accuracy, and metal artifacts evaluation on second-generation dual-layer spectral detector CT images with metal implants: a phantom study.

Metal implants may affect the image quality, iodine concentration (IC), and CT Hounsfield unit (HU) quantification accuracy. To investigate the quantitative accuracy of IC and HU from dual-layer spectral detector (DLCT) in the presence of metal artifacts. An experimental cylindrical phantom containing eight iodine inserts and two metal inserts was designed. The phantom underwent scanning at three radiation dose levels and two tube voltage settings. A set of conventional images (CIs), virtual monoenergetic images (VMIs), and iodine concentration maps (ICMs) were generated and measured for all the eight iodine inserts. Quantitative indicators of mean absolute percentage error (MAPE), artifact index (AI), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and standard deviation (SD) on CIs and VMIs were calculated for IC and HU. Subjective score evaluation was also conducted. The MAPEiodine values of all regions of interest across different scanning configurations were all <5%. Almost all APEiodine values were <5%, indicating that metal artifacts had little impact on IC measurements. When the tube voltage was fixed, the SD value of attenuation decreased with the increase of the tube current; this is also true when the tube current was fixed. The middle energy reconstructions seemed to give a good balance between reducing artifacts and improving contrast. VMIs from DLCT can reduce metal artifacts, the accuracy of IC quantification is not sensitive to imaging parameters. In summary, metal implants exhibit minimal impact on image quality and IC quantification accuracy in reconstructed images from DLCT.

The Framework of Quantifying Biomarkers of OCT and OCTA Images in Retinal Diseases.

Despite the significant advancements facilitated by previous research in introducing a plethora of retinal biomarkers, there is a lack of research addressing the clinical need for quantifying different biomarkers and prioritizing their importance for guiding clinical decision making in the context of retinal diseases. To address this issue, our study introduces a novel framework for quantifying biomarkers derived from optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images in retinal diseases. We extract 452 feature parameters from five feature types, including local binary patterns (LBP) features of OCT and OCTA, capillary and large vessel features, and the foveal avascular zone (FAZ) feature. Leveraging this extensive feature set, we construct a classification model using a statistically relevant p value for feature selection to predict retinal diseases. We obtain a high accuracy of 0.912 and F1-score of 0.906 in the task of disease classification using this framework. We find that OCT and OCTA's LBP features provide a significant contribution of 77.12% to the significance of biomarkers in predicting retinal diseases, suggesting their potential as latent indicators for clinical diagnosis. This study employs a quantitative analysis framework to identify potential biomarkers for retinal diseases in OCT and OCTA images. Our findings suggest that LBP parameters, skewness and kurtosis values of capillary, the maximum, mean, median, and standard deviation of large vessel, as well as the eccentricity, compactness, flatness, and anisotropy index of FAZ, may serve as significant indicators of retinal conditions.

Carbon Nano-Dots based potentiometric sensor for the assay of the antiviral agent; Valacyclovir: In-Depth DFT Calculations, application to the pharmaceutical formulation and greenness assessment

Valacyclovir (VAL), as a prodrug to acyclovir antiviral agent, has recently held a lot of interest for its efficacy boosting owing to the significant improvement in bioavailability. This makes it a successful candidate in the management of herpes simplex strains as well as CORONA viruses. In this work a carbon nano dot-modified glassy carbon electrode (GCE) has been optimized as potentiometric sensor for the assay of VAL through a systematic approach. A mixture components of polyvinyl chloride (PVC) membrane have been selected and fine-tuned for optimum sensitivity and selectivity. The best results have been obtained by drop casting a blend in % w/w of PVC; 30.85, tricrasyl phosphate (TCP) as plasticizer; 64.32, phosphotungstic acid (PT) as cation exchanger; 1.61 and phosphorus – nitrogen-doped carbon nano-dots (PNCDs); 3.22 over the GCE. The density function theory (DFT) calculations have been applied to the optimized structures of VAL and the CDs and have proven high binding affinity of 46 kcal/mol dominated by π-π stacking and hydrogen bonding. The developed sensor has exhibited a swift response time of six seconds at a 5.00 pH value. The ICH guidelines have been applied to validate the optimized parameters. A good linearity range has been obtained from 1.18 × 10-3 down to 1.07 × 10-6 M for a correlation coefficient 0.9996 with a Nernstian slope of 33.16 mV/decade. The greenness has been assessed using the AGREE approach, giving a score of 0.8, which has indicated the environmental friendliness. An average % recovery of almost 99.00 % was obtained by application to the tablet formulations and furtherly it has been monitored by the standard addition method, giving recoveries varied from 98.00 and up to 102.00 % for relative standard deviation values (%RSD) less than 1.50 %, evidencing efficiency for application in the quality control laboratories.

A multiband terahertz metamaterial sensor evaluated using a multiresponse variable fusion framework for the precise detection of trace fluoroquinolone antibiotics

A specific structural multiband terahertz (THz) metamaterial sensor (TMS) was designed herein to improve the sensitivity of detecting multiple trace fluoroquinolone (FQ) antibiotics in water, and a multiple resonance response competition and selection fusion (MRR-CSF) framework was proposed for accurate FQ analysis. The TMS based on three-concentric C4-symmetrical split-ring (TC4) structures generated five bands at 0.797, 0.900, 1.097, 1.198, and 1.777 THz. The multiband resonance signals for three types of FQs, including enrofloxacin (ENR), pefloxacin (PEF), and nadifloxacin (NAD), were detected by the TMS, which increased as the antibiotic concentrations increased (5–140 ng/L). The proposed method can solve the problems of low accuracy and poor robustness of conventional single-response regression by combining selected and fused TMS-effective resonance response variables with three multivariate regression strategies. The calculated comprehensive metrics also provide an objective evaluation of multiband TMS performance. The designed TMS combined with the proposed MRR-CSF framework showed 21 %–27 %, 13 %–17 %, and 12 %–13 % improvements in the detection accuracy for ENR, PEF, and NAD, respectively, according to the univariate regression results. The limit of detection for the ENR, PEF, and NAD antibiotic solutions was achieved at 5 ng/L, and the reliable range of recoveries (100 % ± 25 %), average recoveries (>90 %), and relative standard deviation values (<5 %) were obtained for the concentration prediction of newly prepared FQs. This study demonstrates the promising prospect of applying the multiband TMS combined with the MRR-CSF framework for accurate biochemical sensing and detection.

An impedimetric approach for determination of ammonium using silver/poly-1-aminoanthraquinone/carbon paste electrode

Here, we present the electrochemical determination of ammonium in water samples, emphasizing the importance of accurate and precise assessment of its concentration. The modified electrode used in this study was fabricated through the anodic polymerization of 1-aminoanthraquinone (1-AAQ) and deposition of silver particles into a carbon paste electrode. The fabrication process involved cyclic voltammetry in a 0.1 M HCl solution, followed by the application of a potential of 0.2 V for 75 s. The resulting Ag/poly-1-AAQ/CPE exhibited remarkable electrochemical properties, as confirmed by scanning electron spectroscopy (SEM), energy-dispersive X-ray analysis (EDX), and elemental mapping. The successful deposition of silver at percentages of 12.07% on Ag/CPE and 0.75% on Ag/poly-1-AAQ/CPE was observed. The Ag/poly-1-AAQ/CPE was employed for impedimetric determination of ammonium in a solution of 0.1 M Na2SO4. The charge transfer resistance) output from the fitting of the experimental impedimetric data of ammonium determination exhibited good linearity over a concentration range of 5 µM to 200 µM NH4+, with a detection limit of 3.3 µM NH4+. The precision of the modified electrode over ten replicate measurements were conducted at three concentration levels (a low of 5 µM NH4+, a medium of 50 µM NH4+, and a high of 200 µM NH4+). The obtained relative standard deviation (RSD) values of 18%, 12% and 7%, respectively, indicating good precision.

Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using Deep Learning.

Endobronchial ultrasound (EBUS) is used in the minimally invasive sampling of thoracic lymph nodes. In lung cancer staging, the accurate assessment of mediastinal structures is essential but challenged by variations in anatomy, image quality, and operator-dependent image interpretation. This study aimed to automatically detect and segment mediastinal lymph nodes and blood vessels employing a novel U-Net architecture-based approach in EBUS images. A total of 1161 EBUS images from 40 patients were annotated. For training and validation, 882 images from 30 patients and 145 images from 5 patients were utilized. A separate set of 134 images was reserved for testing. For lymph node and blood vessel segmentation, the mean ± standard deviation (SD) values of the Dice similarity coefficient were 0.71 ± 0.35 and 0.76 ± 0.38, those of the precision were 0.69 ± 0.36 and 0.82 ± 0.22, those of the sensitivity were 0.71 ± 0.38 and 0.80 ± 0.25, those of the specificity were 0.98 ± 0.02 and 0.99 ± 0.01, and those of the F1 score were 0.85 ± 0.16 and 0.81 ± 0.21, respectively. The average processing and segmentation run-time per image was 55 ± 1 ms (mean ± SD). The new U-Net architecture-based approach (EBUS-AI) could automatically detect and segment mediastinal lymph nodes and blood vessels in EBUS images. The method performed well and was feasible and fast, enabling real-time automatic labeling.

A validated spectrophotometric analysis for simultaneous estimation of vincristine sulfate and bovine serum albumin in pure preparations using Vierordt’s method

The novel Vierordt’s approach, or simultaneous equation method, was created and validated for the concurrent determination of vincristine sulfate (VCS) and bovine serum albumin (BSA) in pure solutions utilizing UV spectrophotometry. It is simple, precise, economical, rapid, reliable, and accurate. This method depends on measuring absorbance at two wavelengths, 296 nm and 278 nm, which correspond to the λmax of VCS and BSA in deionized water, respectively. The calibration curves of VCS and BSA are linear at concentration ranges of 10–60 μg/mL and 200–1600 μg/mL, with correlation coefficient values (R2) of 1 and 0.999, respectively. The limits of detection (LOD) and quantification (LOQ) were 0.465 μg/mL and 1.410 μg/mL for VCS and 41.096 μg/mL and 124.533 μg/mL for BSA. The precision investigation indicated that the relative standard deviation (RSD) value was within limitations (RSD &amp;lt; 2%). The percentage recovery varied between 99.40 and 103.20% for VCS and 97.90 and 102.54% for BSA at various concentration levels, demonstrating that the simultaneous equation technique is accurate. The suggested approach can be successfully applied to estimate VCS and BSA simultaneously in pure and pharmaceutical-marketed products comprising these two components.