Significant Difference In Accuracy Research Articles

Prediction of Heart Disease using Forest Algorithm over Linear Regression Algorithm using Machine Learning With Improved Accuracy

Aim: To perform Predicting heart disease using the Forest algorithm and comparing its feature extraction precision with the Linear Regression Algorithm for improving the accuracy of the prediction. Methods and Materials: In the proposed work, Predicting heart disease was carried out using machine learning algorithms such as Linear Regression (n=10)and Forest algorithm(n=10). Here the pretest power analysis was carried out with 80% and the sample size for the two groups are 20. Results: From The implemented experiment, the Forest algorithm accuracy is 90.32% and the Linear Regression Algorithm 77.21%. There is a statistical 2-tailed significant difference in accuracy for two algorithms is 0.001 (p<0.05) Conclusion: This study concludes that the Forest algorithm on patients healthcare analysis is significantly better than the Linear Regression Algorithm.

Single Lead EMG signal to Control an Upper Limb Exoskeleton Using Embedded Machine Learning on Raspberry Pi

Post-stroke can cause partial or complete paralysis of the human limb. Delayed rehabilitation steps in post-stroke patients can cause muscle atrophy and limb stiffness. Post-stroke patients require an upper limb exoskeleton device for the rehabilitation process. Several previous studies used more than one electrode lead to control the exoskeleton. The use of many electrode leads can lead to an increase in complexity in terms of hardware and software. Therefore, this research aims to develop single lead EMG pattern recognition to control an upper limb exoskeleton. The main contribution of this research is that the robotic upper limb exoskeleton device can be controlled using a single lead EMG. EMG signals were tapped at the biceps point with a sampling frequency of 2000 Hz. A Raspberry Pi 3B+ was used to embed the data acquisition, feature extraction, classification and motor control by using multithread algorithm. The exoskeleton arm frame is made using 3D printing technology using a high torque servo motor drive. The control process is carried out by extracting EMG signals using EMG features (mean absolute value, root mean square, variance) further extraction results will be trained on machine learning (decision tree (DT), linear regression (LR), polynomial regression (PR), and random forest (RF)). The results show that machine learning decision tree and random forest produce the highest accuracy compared to other classifiers. The accuracy of DT and RF are of 96.36±0.54% and 95.67±0.76%, respectively. Combining the EMG features, shows that there is no significant difference in accuracy (p-value 0.05). A single lead EMG electrode can control the upper limb exoskeleton robot device well.

Age-related differences in food-specific inhibitory control: Electrophysiological and behavioral evidence in healthy aging

The number of older adults in the United States is estimated to nearly double from 52 million to 95 million by 2060. Approximately 80–85% of older adults are diagnosed with a chronic health condition. Many of these chronic health conditions are influenced by diet and physical activity, suggesting improved diet and eating behaviors could improve health-related outcomes. One factor that might improve dietary habits in older adults is food-related inhibitory control. We tested whether food-related inhibitory control, as measured via behavioral data (response time, accuracy) and scalp-recorded event-related potentials (ERP; N2 and P3 components), differed between younger and older adults over age 55. Fifty-nine older adults (31 females [52.5%], Mage = 64, SDage = 7.5) and 114 younger adults (82 females [71.9%], Mage = 20.8) completed two go/no-go tasks, one inhibiting to high-calorie stimuli and one inhibiting to low-calorie stimuli, while electroencephalogram (EEG) data were recorded. Older adults had slower overall response times than younger adults, but this was not specific to either food task. There was not a significant difference in accuracy between younger and older adults, but both groups’ accuracy and response times were significantly better during the high-calorie task than the low-calorie task. For both the N2 and P3 ERP components, younger adults had larger no-go ERP amplitudes than older adults, but this effect was not food-specific, reflecting overall generalized lower inhibitory control processing in older adults. P3 amplitude for the younger adults demonstrated a specific food-related effect (greater P3 amplitude for high-calorie no-go than low-calorie no-go) that was not present for older adults. Findings support previous research demonstrating age-related differences in inhibitory control though those differences may not be specific to inhibiting towards food.

Predictive accuracy of Static-99R across different racial/ethnic groups: A meta-analysis.

The overrepresentation of numerous racial/ethnic groups in the criminal legal system warrants examination of the cross-cultural applicability of risk assessment tools. Static-99R is a tool used in diverse countries to assess sexual recidivism risk. We conducted a meta-analysis on the predictive accuracy of Static-99R across different racial/ethnic groups. No hypotheses were made regarding discrimination, given that past research could support hypotheses of differential or equivalent accuracy. We hypothesized that Indigenous individuals would score higher on Static-99R than non-Indigenous or White individuals. Our search identified 18 eligible documents (from 17 distinct studies) with 41 nonoverlapping effect sizes. These 17 studies examined the predictive accuracy of Static-99R with racially/ethnically diverse men charged with or convicted of sexually motivated offenses. We report analyses using both fixed-effect and random-effects meta-analysis. Indigenous and Black individuals scored significantly higher on Static-99R than their non-Indigenous or White counterparts, with small effect sizes. For discrimination, area under the curve (AUC) values were generally moderate-to-large and statistically significant for all groups in both fixed-effect and random-effects analyses. Within-study subgroup analyses indicated significantly lower accuracy for Indigenous and Hispanic individuals compared with White/non-Indigenous samples (though for Hispanic individuals, this finding was significant only in the fixed-effect analyses). No statistically significant differences in accuracy were found between White and Black individuals. Static-99R significantly predicted recidivism with large effect sizes across two samples of Asian individuals. Two studies supported calibration across Black, White, and Hispanic individuals. Two studies examining calibration of Static-99R for Indigenous individuals had mixed findings. Given a small number of studies and limitations with both the fixed- and random-effects analyses, readers should interpret findings regarding Hispanic individuals with caution. The analyses clearly found significant but lower accuracy for Static-99R with Indigenous individuals. Potential reasons for this differential accuracy are discussed, along with limitations of the meta-analysis and suggestions for research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Analisis Keakuratan Capital Asset Pricing Model Dan Arbitrage Pricing Theory Dalam Memprediksi Return Saham (Studi Pada Perusahaan LQ 45 Di Bursa Efek Indonesia Periode 2016-2020)

This study is based on the rapid development of the investment world. Hence, most investors have limited abilities and strategies in investing, therefore it takes important methods and concepts to assess the level of profit from an investment with various existing risk factors. This study focuses on the comparison of the accuracy between the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) methods in predicting stock returns of LQ 45 index companies for the 2016-2020 period. This study aimed to determine which method was more appropriate in predicting the company's stock returns. The accuracy of the CAPM and APT methods was measured by using the Mean Absolute Deviation (MAD). The Independent Sample T-test was used to determine whether there was a difference in accuracy between the CAPM and APT methods in predicting stock returns. The results of this study show that by using the calculation of the Mean Absolute Deviation, the APT method is more accurate than the CAPM method in predicting stock returns. The MAD APT value (0.000246) is smaller than the MAD CAPM value (0.003739) and based on data processing from the Independent Sample T-test shows that H0 is rejected, which means that there is a significant difference in accuracy between the CAPM and APT models particularly in predicting the company's stock return.

Improved Accuracy and Lowered Learning Curve of Ventricular Targeting Using Augmented Reality-Phantom and Cadaveric Model Testing.

Augmented reality (AR) has demonstrated significant potential in neurosurgical cranial, spine, and teaching applications. External ventricular drain (EVD) placement remains a common procedure, but with error rates in targeting between 10% and 40%. To evaluate Novarad VisAR guidance system for the placement of EVDs in phantom and cadaveric models. Two synthetic ventricular phantom models and a third cadaver model underwent computerized tomography imaging and registration with the VisAR system (Novarad). Root mean square (RMS), angular error (γ), and Euclidian distance were measured by multiple methods for various standard EVD placements. Computerized tomography measurements on a phantom model (0.5-mm targets showed a mean Euclidean distance error of 1.20 ± 0.98 mm and γ of 1.25° ± 1.02°. Eight participants placed EVDs in lateral and occipital burr holes using VisAR in a second phantom anatomic ventricular model (mean RMS: 3.9 ± 1.8 mm, γ: 3.95° ± 1.78°). There were no statistically significant differences in accuracy for postgraduate year level, prior AR experience, prior EVD experience, or experience with video games ( P > .05). In comparing EVDs placed with anatomic landmarks vs VisAR navigation in a cadaver, VisAR demonstrated significantly better RMS and γ, 7.47 ± 0.94 mm and 7.12° ± 0.97°, respectively ( P ≤ .05). The novel VisAR AR system resulted in accurate placement of EVDs with a rapid learning curve, which may improve clinical treatment and patient safety. Future applications of VisAR can be expanded to other cranial procedures.

Trueness and Precision of Eight Intraoral Scanners with Different Finishing Line Designs: A Comparative In Vitro Study.

This study aimed to evaluate the accuracy in terms of trueness and precision of eight intraoral scanners (IOS) and the effect of different finishing line designs on the IOS's accuracy. Three printed models of the maxillary arch with maxillary right first molar virtually prepared with chamfer, shoulder, and vertical preparation designs were used as master models in this study. Each model was scanned 30 times with each IOS: Medit i700, Planscan Emerald S, CEREC Primescan, TRIOS 3, CS3600, MEDIT i500, Heron 3Disc, and Cerec Omnicam. The trueness was measured by superimposition of the scanned dataset made with IOS and the scanned dataset made with a lab scanner (In Lab Medit T710) that was used as a reference and the deviation was measured and expressed as a color-coded map by the metrology program (Medit compare, version 2.3.5.892), while precision was measured by the superimposition of the scans of each IOS on each other.The data were analyzed statistically using repeated measure analysis of variance (ANOVA) test, one-way ANOVA test, and Bonferroni test at significance level of 0.05. The tested IOS showed significant differences in trueness and precision. Medit i700 and CEREC Primescan recorded the highest precision with no significant difference between them, while Medit i700 recorded the highest trueness as compared to other IOS. Each IOS showed significant differences in trueness and precision with the three finishing line designs except CEREC Primescan and Heron 3 disc that showed no significant difference in trueness with the three finishing line designs and CS3600 that showed no significant difference in precision with the three finishing line designs. A significant difference in accuracy was found among the tested IOS and the type of finishing line design had a significant effect on IOS's accuracy.

Does Adjunctive Under-flap CXL Reduce Regression for Hyperopic LASIK?

To investigate whether adding accelerated under-flap corneal cross-linking to hyperopic laser in situ keratomileusis (LASIK-ufCXL) affects postoperative stability and regression, visual and refractive outcomes, and subjective quality of vision. This prospective comparative contralateral eye study included 51 patients with hyperopia (102 eyes) who received LASIK-ufCXL in the eye with highest defocus equivalent (DEQ) or randomized when DEQ equal, with the contralateral control eye receiving LASIK alone. After excimer ablation, 0.25% riboflavin was instilled on the stromal bed for 3 minutes. The flap was repositioned, followed by a total irradiation dose of 3.24 J ultraviolet A (UV-A) light administered to the corneal surface, using 18 mW/cm2 UV-A for 3 minutes. Postoperative hyperopic regression (stability) was the primary outcome measure, defined by the difference in spherical equivalent (SEQ) at 1 week and 24 months postoperatively. Secondary measures reported uncorrected distance visual acuity, corrected distance visual acuity, cylinder vector analysis, subjective quality of vision, subjective night vision disturbances, and corneal haze. At 24 months, the SEQ stability (P = .4273) and the magnitude of hyperopic regression (P = .5613) did not significantly differ between groups, with a small trend showing hyper-opic regression of 0.50 diopters or greater being less frequent in LASIK-ufCXL eyes. There were no significant differences in accuracy, efficacy, and safety (P > .05), with a small trend of more residual refractive astigmatism in the LASIK-ufCXL group (P = .3216, Cohen's d: -0.29). Subjective quality of vision trended inferior in LASIK-ufCXL eyes (P = .2237, Cohen's d: -0.25), with a greater haze grading (P = .0466, Cohen's d: 0.41). Postoperative regression and stability were statistically equivalent between hyperopic LASIK vs LASIK-ufCXL, with identical safety. There were small clinical trends of lower efficacy, accuracy, and subjective quality of vision in LASIK-ufCXL eyes. [J Refract Surg. 2022;38(12):770-779.].

A new method for the rapid detection of the antibacterial and bacteriostatic activity of disinfectants based on Propidium Monoazide combined with real-time PCR.

Rapid detection of antibacterial and bacteriostatic properties is an important part of the quality and safety supervision of disinfectants. In this study, propidium monoazide (PMA) was used in combination with real-time PCR (PMA-qPCR) to detect the antibacterial and bacteriostatic activity of disinfectants against three commonly used indicator bacteria, Escherichia coli, Staphylococcus aureus, and Candida albicans, utilizing specifically designed primers. The method for preparing membrane-damaged bacteria was optimized to improve the ability of the PMA dye to distinguish between live and dead indicator bacteria. Finally, this method could simultaneously detect viable numbers of the indicator bacteria after the disinfectants were used. The R 2 values of the PMA-qPCR standard curves were 0.9986, 0.9980, and 0.9962 for E. coli, S. aureus, and C. albicans, respectively, and the detection range was 103 ~ 106 CFU/ml, showing no significant difference in accuracy compared to that of the plate counting method (p > 0.05). The method established here is the first application of PMA-qPCR to detect the antibacterial and bacteriostatic activity of disinfectants. This technique markedly simplifies the detection steps of antibacterial and bacteriostatic activity, reduces the detection time (3 h compared to 48 ~ 72 h for the plate counting method), improves the quality supervision efficiency of disinfectants, and guarantees healthy and safe lives.

DIFFERENCES IN ACCURACY OF PASSING THE BALL IN YOUNG BASKETBALL PLAYERS OF DIFFERENT LEVELS OF COMPETITION

This research determined the differences in accuracy between junior basketball players at the federal and regional competition level. In this research, the following four tests were used to assess precision: Elevation precision of passing with one hand; Elevation precision of passing with two hands; Shooting a ball that bounces after falling from a height of 3.05 meters directly into the target; Shooting a ball that bounces after falling from a height of 3.05 meters with a mandatory bounce from the ground. No statistically significant differences in accuracy were found between basketball players of the federal and regional level of competition, so hypothesis X1 cannot be accepted.The conclusions reached based on the discussion of the results indicate that the accuracy of passing the ball is not one of the factors that contributes to the difference in quality between basketball players in the junior age who compete in different ranks of the competition. Also, good systematic work in the clubs and good orientation and selection of basketball players in the tested clubs contribute to the quality development of motor skills in general, which do not contribute to differences in basketball players of different levels of competition in younger selections. In further work, it is necessary to further investigate precision as one of the least researched fields of motor skills.

Central composite design as an analytical optimization tool for the development of eco-friendly HPLC-PDA methods for two antihypertensive mixtures containing the angiotensin receptor blocker Valsartan: Greenness assessment by four evaluation tools

Using green chemistry principles in chromatography has grown tremendously in recent years. Two green HPLC techniques for determining two antihypertensive binary mixtures, (Nebivolol hydrochloride/Valsartan mixture) and (Sacubitril/Valsartan mixture), were developed and validated. Green Analytical Chemistry (GAC) principles were used, with the employed solvents and analysis run time having a significant impact on the method's greenness. In the mobile phase, the organic modifier was “non-toxic” ethanol. The two-factor three-level response surface methodology was used to optimize analyte separation in both mixtures in a short time span. For the first mixture, phosphate buffer (pH 3): ethanol (21:79 v/v) was used as the mobile phase, where the separation time was 2.5 min. On the other hand, the second mixture was separated using phosphate buffer (pH 3): ethanol (35:65 v/v) in 6 min. It is worth mentioning that using green solvents did not affect the resolution, which was 10.1 and 3.1 for the first and second mixtures, respectively. Four well-known GAC evaluation techniques were used to assess the greenness of the proposed methods on a qualitative and quantitative level: The National Environmental Methods Index (NEMI), analytical eco-scale, Green Analytical Procedure Index (GAPI), and the Analytical GREEnness metric (AGREE). The proposed methods were statistically compared to other published chromatographic methods, and no significant differences in accuracy were discovered. Meanwhile, there is a major variation in the approaches' greenness. The suggested procedures proved to be an excellent, environmentally friendly alternative to the previously mentioned approaches.

Optimization of variational-quantum-eigensolver measurement by partitioning Pauli operators using multiqubit Clifford gates on noisy intermediate-scale quantum hardware

Measuring the expectation value of Pauli operators on prepared quantum states is a fundamental task in a multitude of quantum algorithms. Simultaneously measuring sets of Pauli operators allows for fewer measurements and an overall speedup of the measurement process. Using results from coloring random graphs, we give evidence for an upper bound on the expected minimum number of simultaneously measurable parts necessary to partition a set of Pauli operators. By expanding our gate set to allow multiqubit Clifford gates before measurement, we were able to cut down the number of measurements considerably compared to previous approaches. We conjecture that this improvement is, in general, linear with respect to the lengths of the Pauli operators. We conclude by demonstrating the feasibility of this approach by implementing the variational quantum eigensolver on the Aspen-4-4Q-A quantum processor unit. In doing so, we calculate the ground-state energies of ${\mathrm{H}}_{2}$ using fewer measurements than is possible with single-qubit gates with no statistically significant difference in accuracy.

Comparison Accuracy in Determining the Degree of Lumbar Spinal Stenosis between Lumbar Spine MRI with Axial Loading and Routine Conventional MRI with Clinical Correlation

Objective: To evaluate the accuracy in determining the degree of lumbar spinal stenosis in patients utilizing lumbar spine magnetic resonance imaging (MRI) with axial loading as compared to conventional lumbar spine MRI with clinical correlation. To assess the difference in the dural cross sectional area (DCSA) between lumbar spine MRI with axial loading and conventional lumbar spine MRI. Materials and Methods: Thirteen patients with clinically diagnosed lumbar spinal stenosis, which comprised of three males and ten females, aged 20 to 80 years, and that had the severity of their stenosis clinically and radiologically graded by history taking, physical examination, and by performing both conventional and axial loaded MRI were included in this study. Results: The present study found a statistically significant difference (p<0.05) after applying load at all lumbar levels. The L4-L5 level showed the greatest reduction at 12.8%, followed by L3-L4 and L2-L3, in which the DCSA was reduced by 11.2% and 9.0%, respectively. Comparing the clinical severity and degree of each lumbar spinotic level and the maximum severity per person, the results showed that the most accuracy was at the L3-L4 level followed by L5-S1 and L2-L3 levels. No accuracy between clinical severity and the degree of lumbar spinal stenosis at L1-L2 and L4-L5 levels were shown, suggesting that more than the DCSA change influence the clinical severity. To gain further insights, following up patients and a study with more patients are needed. The maximum severity by DCSA measurement, both pre- and post-loading, of individual patients compared with clinical severity showed concordance for three patients. No significant difference in accuracy was found between pre- and post-loading. Conclusion: Changes in the DCSA of lumbar spinal stenosis after loading MRI was statistically significant especially at the moderate and severe stenotic levels particularly at the L3-4 level and L5-S1 level. Keywords: Lumbar spine MRI; Axial loading; Lumbar spinal stenosis

AI-based chest CT semantic segmentation algorithm enables semi-automated lung cancer surgery planning by recognizing anatomical variants of pulmonary vessels.

The recognition of anatomical variants is essential in preoperative planning for lung cancer surgery. Although three-dimensional (3-D) reconstruction provided an intuitive demonstration of the anatomical structure, the recognition process remains fully manual. To render a semiautomated approach for surgery planning, we developed an artificial intelligence (AI)-based chest CT semantic segmentation algorithm that recognizes pulmonary vessels on lobular or segmental levels. Hereby, we present a retrospective validation of the algorithm comparing surgeons' performance. The semantic segmentation algorithm to be validated was trained on non-contrast CT scans from a single center. A retrospective pilot study was performed. An independent validation dataset was constituted by an arbitrary selection from patients who underwent lobectomy or segmentectomy in three institutions during Apr. 2020 to Jun. 2021. The golden standard of anatomical variants of each enrolled case was obtained via expert surgeons' judgments based on chest CT, 3-D reconstruction, and surgical observation. The performance of the algorithm is compared against the performance of two junior thoracic surgery attendings based on chest CT. A total of 27 cases were included in this study. The overall case-wise accuracy of the AI model was 82.8% in pulmonary vessels compared to 78.8% and 77.0% for the two surgeons, respectively. Segmental artery accuracy was 79.7%, 73.6%, and 72.7%; lobular vein accuracy was 96.3%, 96.3%, and 92.6% by the AI model and two surgeons, respectively. No statistical significance was found. In subgroup analysis, the anatomic structure-wise analysis of the AI algorithm showed a significant difference in accuracies between different lobes (p = 0.012). Higher AI accuracy in the right-upper lobe (RUL) and left-lower lobe (LLL) arteries was shown. A trend of better performance in non-contrast CT was also detected. Most recognition errors by the algorithm were the misclassification of LA1+2 and LA3. Radiological parameters did not exhibit a significant impact on the performance of both AI and surgeons. The semantic segmentation algorithm achieves the recognition of the segmental pulmonary artery and the lobular pulmonary vein. The performance of the model approximates that of junior thoracic surgery attendings. Our work provides a novel semiautomated surgery planning approach that is potentially beneficial to lung cancer patients.

Investigating the effect of electroadhesion tactile feedback on accuracy and efficiency of Steering tasks

Tactile interaction technology has brought much convenience to user’s study and life. The interaction accuracy and efficiency of mobile terminals are widely investigated in intelligent human–computer interaction (HCI). The introduction of tactile feedback is of great importance for improving the usability and commerciality of interactive interfaces. This study investigates the effect of tactile feedback on mobile terminal interaction performance on the basis of electroadhesion tactile feedback widely used in touch screen interaction with bare finger. There are two different positions called intra-tunnel electroadhesion and extra-tunnel electroadhesion. There are five different perceived intensities (0, 5, 10, 15, 20 PI). A total of ten combinations of different positions and perceived intensities are used to study the effect of electroadhesion tactile feedback on accuracy and efficiency of steering tasks. The results show that electroadhesion tactile feedback can improve the efficiency, especially inside the tunnel. But there is no significant difference in accuracy. Meanwhile, intra-tunnel electroadhesion can improve the efficiency while bringing a better interaction experience according to the subjective evaluation. Our findings suggest that electroadhesion should be applied inside the tunnel as a guiding signal and offer insights on future touch screen interactions.

Eco-friendly resolution of spectrally overlapping signals of a combined triple-action over-the-counter pharmaceutical formulation for symptomatic management of COVID-19 pandemic: application to content uniformity testing

Currently, all researchers are concentrating their efforts on countering the COVID-19 pandemic. The majority of patients are managed at home, according to recent statistics. An OTC triple action combination comprising paracetamol (PAR), aspirin (ASP), and diphenhydramine (DIPH) is commonly given for pain relief, fever control, and as a night-time sleep aid. This combination is currently recommended for COVID-19 patients as part of symptomatic treatment and management. In this work, three smart, simple, accurate, eco-friendly, and cost-effective spectrophotometric methods are developed for simultaneous determination of PAR, ASP, and DIPH in their combined over-the-counter caplet dosage form without any prior separation steps. The first method is the first derivative spectrophotometry (D1) which determined PAR at 259.7 nm. The second one is the dual-wavelength in ratio spectra (DWRS) for determination of ASP at 214.1 and 220.1 nm after using 10.0 μg/mL of PAR as a divisor, where PAR was a constant, and the wavelengths difference equal to zero for DIPH. The third method is the double divisor-ratio difference spectrophotometric one (DD-RD) which was based on using the sum of 15.0 µg/mL of each of PAR and ASP as a double divisor, and the difference in amplitudes was measured at two wavelengths ∆P(214.5–226.0) for determination of DIPH. The developed methods have been validated as per ICH guidelines. Furthermore, the three suggested methods were employed successfully to assay marketed pharmaceutical formulation and to investigate the content uniformity of the dosage units in accordance with the United States Pharmacopeia's guidelines. Finally, the greenness profile of the proposed methods was assessed and compared with the reported method using the analytical eco-scale system, national environmental method index (NEMI), green analytical procedure index (GAPI), and analytical greenness (AGREE) metric. The results from the proposed methods statistically agreed with those obtained by the reported one, with no significant differences in accuracy and precision.Graphical

Establishment of low-cost laboratory automation processes using AutoIt and 4-axis robots.

In most small laboratories, many processes are not yet automated because existing laboratory automation solutions are usually expensive and inflexible to use. Examples of this are autosamplers that are only compatible with one specific laboratory instrument or larger liquid handling stations that are expensive and usually self-contained. A flexible and inexpensive way to automate laboratory processes would be to automate existing laboratory equipment with the help of suitable robotic arms. In this study, we investigate the feasibility of such a strategy based on a low-cost 4-axis robot and freely available software. We used the scripting language AutoIt that automates any Windows-based instrument control software. Using these tools, we automated three fundamentally different laboratory processes: a pipetting process, a use as an autosampler for an atomic absorption spectroscopy instrument, and a more complex process involving the inoculation of bacterial cultures. We also integrated a conventional webcam for 2D barcode recognition. Compared to a trained professional who performed all experiments manually, all setups showed no significant differences in accuracy and precision. In summary, the tested system consisting of a 4-axis robot and freely available software is suitable for flexible automation and has potential for even more complex laboratory processes. Limitations such as a lack of collaboration and speed will be addressed in follow-up studies. The system thus represents a well-suited flexible laboratory automation system for both research and teaching purposes.

Performance, Usability, and User Experience of Rayyan for Systematic Reviews

ABSTRACTThis study investigated performance, usability, and user experience with Rayyan, a systematic review (SR) tool. A remote usability inspection was conducted via the institutional Zoom platform. Each participant was randomly assigned to two groups and completed two citation screening sessions independently. Data were collected through pre‐ and post‐test questionnaires, screening sessions, and Systems Usability Scale (SUS) surveys. Thirteen participants completed the study. We found significant accuracy difference between Web Rayyan and its mobile app (t[12] = 1.877 p = .042), but no statistically sequential effect on screening performance. The average SUS scores of both Rayyan versions were below 68. More participants (77%) preferred Web Rayyan to the mobile app. The mobile Rayyan has potential if its user interface design can prevent errors or allow easy action reversal. As the first controlled experiment investigating both Web and mobile Rayyan, this study provides empirical evidence to guide the design, development, and selection of SR tools.

Qualitative and quantitative analysis of curcumin in dried ginger by the resonance Rayleigh scattering technique and absorption spectroscopy

On the basis of our qualitative analysis, two new methods of the resonance Rayleigh scattering (RRS) and multiwavelength visible absorption spectroscopy (VIS) for the determination of curcumin in dried ginger are established. At pH 6.70 Tris-HCl, curcumin reacts with brilliant green to form binary ionic association complexes. Curcumin was determined by the RRS method at 347 nm, and the detection limit and quantitative limit were 0.0018 mg · L−1 and 0.047 mg · kg−1, respectively. In addition, curcumin was also determined by single-wavelength, dual-wavelength, and three-wavelength VIS at 429 nm, 570 nm, and 656 nm, respectively. The detection limit, quantitative limit, and apparent molar absorption coefficient are, respectively, 0.025 mg · L−1, 0.65 mg · kg−1, and 1.03 × 105 L · mol−1 · cm−1 (429 nm or 656 nm); 0.028 mg · L−1, 0.73 mg · kg−1, and 7.89 × 104 L · mol−1 · cm−1 (570 nm); 0.013 mg · L−1, 0.33 mg · kg−1, and 2.06 × 105 L · mol−1 · cm−1 (429 nm + 656 nm); 0.009 mg · L−1, 0.23 mg · kg−1, and 2.85 × 105 L · mol−1 · cm−1 (429 nm + 570 nm + 656 nm). Taking the RRS method and dual-wavelength VIS (DWO–VIS) with moderate sensitivity as examples, the detection results of curcumin in dried ginger samples are compared, and there are no significant differences in accuracy and precision between the two new methods. The two methods are accurate, reliable, and highly sensitive for the determination of curcumin in commercially available dried gingers, and the results are satisfactory.

Real-time gastric juice analysis with EndoFaster for H. pylori diagnosis: a large, multicentre study.

Helicobacter pylori infection is the main cause of the most frequent gastroduodenal diseases. Because its prevalence is decreasing in developed countries, gastric biopsies are negative in several patients. By measuring ammonium in the gastric juice, EndoFaster allows to exclude H. pylori infection during endoscopy. This study aimed to assess the accuracy of device versions working with either 6 ml or 3 ml of gastric juice. This prospective study involved 12 endoscopic units. During endoscopy, EndoFaster testing was performed and standard five gastric biopsies were taken. The accuracy was calculated by considering histological assessment as the gold standard for H. pylori diagnosis. Gastric juice analysis was attempted in 1279 patients, but it failed in 131 (15.5%) and in 10 (2.3%), with the 6 ml and the 3 ml device, respectively (P < 0.001). Overall, EndoFaster detected H. pylori infection with an 86.3% sensitivity, 83.3% specificity, 52.7% positive predictive value, 96.6% negative predictive value and 83.8% accuracy. The performance was not affected either by ongoing proton pump inhibitor therapy or a previous H. pylori eradication. No significant difference in accuracy emerged between the two versions of the device. The novel version of the EndoFaster device operating with 3 ml gastric juice may be performed in virtually all patients, and it allows excluding H. pylori infection with a very high accuracy. Gastric biopsies can be avoided in a definite portion of cases without endoscopic lesions or other clinical indications.