High Standard Deviation Research Articles

Geofence‐Based Boundary Violation Detection Algorithms in Unmanned Aerial Vehicles

ABSTRACTGeofence is a virtual boundary that helps in location‐based services. Unmanned aerial vehicles (UAVs) fly without a pilot, and geofence helps in regulating these vehicles and constraints a UAV to enter the boundary of other UAV. However, these have to go through many safety and security features like avoiding collision, complying within the restricted area, and organizing airspaces with high traffic. The UAVs need to be within the boundaries to avoid various damages to property and loss of lives. Geofences help to detect boundary violation of UAVs to a great extent. This study uses various mathematical algorithms to create geofences and detect boundary violation of UAVs. The existing methods, Delaunay triangulation and triangle weight characterization with adjacency, are implemented. The existing methods have high execution time as well as high standard deviation and low accuracy. Further, a novel method for boundary violation detection is proposed using a convex hull to create geofences. The results show that the proposed method improves the execution time by 59.23% and accuracy by 1.35%.

Prediksi Risiko Emisi Karbon Dioksida Melalui Pemodelan GSTAR Kriging di Wilayah Asia

This study analyzes the variability of carbon dioxide emissions across Asia, revealing that China, India, and Indonesia are the primary contributors with extremely high average emissions and standard deviations. The GSTAR(3;1,1,1) model has been shown to be optimal for forecasting future emissions, based on lower RMSE and MAPE values. Ordinary Kriging analysis using the isotropic spherical semivariogram model provides the most accurate predictions for unobserved areas, with contour maps indicating that the northeastern region of Asia will continue to face high emission concentrations until 2027. While countries such as Brunei and Armenia have managed to keep emission levels low, the instability of emission trends across Asia underscores the need for emission reduction strategies tailored to the specific context of each country.

Community Awareness and Participation for Land and Forest Fire Prevention and Implementation of Lancang Kuning Nusantara System Application in Toba District, North Sumatra Province

This study employs a sociometric analysis of Community Concern and Participation in Implementing the Lancang Kuning Nusantara Application for Forest and Land Fire Prevention in Toba Regency, Indonesia. With a sample of 401 respondents, the study aims to comprehensively understand social interactions and community engagement in this context. Results indicate that the perception score (X(i.1)) and participation score (X(i.2)) are high or significant, reflecting positive community awareness and active involvement in fire prevention activities. However, the acceptability score (X(i.3)) is low or insignificant, suggesting potential dissatisfaction or skepticism regarding the effectiveness or implementation of current programs. Furthermore, standard deviation analysis reveals that variability in respondent ratings is generally within control, with only 2 out of 15 testing points showing high standard deviation, while 13 are within acceptable limits. Nevertheless, the proportion of respondents who rate low (PRMR) exceeds the desired threshold of 10% across all variables, indicating that many respondents have low evaluations. These findings suggest a need for improved communication, education, and potential adjustments to enhance the acceptability and effectiveness of the fire prevention initiatives and the Lancang Kuning Nusantara System application.

Simultaneous estimation of nebivolol hydrochloride and amlodipine besylate in human plasma employing an innovative HPLC chromatographic method

Abstract Background This study developed and validated a simple, robust, and cost-effective RP-HPLC bioanalytical method for the determination of nebivolol hydrochloride (NBH) and amlodipine besylate (AMB) in human plasma. Briefly, NBH and AMB were extracted from plasma through protein precipitation using 5% formic acid and acetonitrile. Chromatographic separation was achieved using an Inertsil ODS-3 V column (150 mm × 4.6 mm, 5 μm) with a mobile phase composed of acetonitrile and buffer (40:60, v/v). The analysis was conducted using UV detection at 215 nm. Results The bioanalytical method demonstrated linearity for NBH (4.50–180.12 μg/mL) and AMB (3.50–140.06 μg/mL). It exhibited good selectivity and sensitivity, with LLOQ responses within ≤ 20% of the analyte signal. Accuracy and precision were within acceptable limits. The extraction recovery from human plasma showed a CV (%) of 1.15% for NBH and 1.35% for AMB, indicating consistent recovery rates. Stability studies on drug-spiked human plasma at LQC and HQC levels confirmed the stability of the drugs under various conditions. Conclusion The present bioanalytical method successfully quantified NBH and AMB simultaneously in plasma samples. It demonstrated suitability, supported by high recovery rates and low relative standard deviations. With its proven linearity, accuracy, and precision, this technique is well suited for drug identification in plasma samples.

Quality of Life in Patients with Birdshot Chorioretinitis Aged 80 and Older

ABSTRACT Purpose Birdshot chorioretinitis (BSCR) is an ocular HLA-related disease with variable clinical progression. We examine the quality of life (QOL) of BSCR individuals aged ≥80 years, providing insights into the long-term disease impact. Methods We utilized data from the CO-BIRD cohort (ClinicalTrials.gov Identifier: NCT05153057) conducted at Hôpital Cochin in Paris, France, focusing on BSCR patients aged ≥80. The main outcome was vision-related QOL using the National Eye Institute Visual Function Questionnaire-25 (NEI VFQ-25). We used Spearman correlation to explore the impact of better BCVA and MD on the composite score, and the Wilcoxon test to evaluate specific visual symptoms’ effects. Results The study included 35 patients with a mean age of 83.9 ± 3.7 years, 74.3% of whom received systemic immunosuppression. The mean composite score was 58 ± 30, with a median of 75 (23–79). The lowest subscores were driving capacity (38 ± 38), mental health (49 ± 33), and role difficulties (50 ± 35), while the highest were for ocular pain (70 ± 25) and social function (70 ± 38). Decimal BCVA below 0.5 and MD below −6 dB were associated with lower subscores. BCVA and MD were strongly correlated with the composite score (R = 0.67). Symptoms of poor color and blurry vision were significantly associated with lower composite score (p < 0.005). Conclusion Most BSCR patients over 80 in our cohort maintained sufficient vision for daily activities. The high standard deviation and wide range of VFQ-25 results reflect the heterogeneity of visual outcomes among elderly BSCR patients.

Investigation of changes in the cumulative number of magnetic anomalies before and after earthquakes using satellite data

Iran is always at risk of destructive earthquakes due to its location on the Alpine-Himalayan seismic belt. Many significant earthquakes have occurred there so far, which have caused a lot of financial and human losses. The plateau consists of a composite system of collision-oblique transpressive fold-and-thrust mountain belts with active reverse and strike-slip faulting, range-and-basin terrains, active subduction zones, recent volcanic activity, variable crust thicknesses and rigidity, and relatively stable aseismic blocks of different dimensions with low.topographic relief and nearly flat areas., as a result, attention to earthquakes and research in its various fields is necessary and inevitable in Iran. This study investigated Iran’s earthquakes from 2014 to 2021 with a magnitude above 5.5. A total of 30 earthquakes were investigated, of which 21 cases were considered due to solar activities and the simultaneous occurrence of some earthquakes. For this purpose, Swarm Alpha and Swarm Charlie satellite data belonging to the European Space Agency have been used vector magnetic field of all the paths that passed near the place of the earthquake was used between two months before the occurrence and one month after it. First, by performing the first stage of processing for the paths that are close to the earthquake in terms of time, the vivid anomalies caused by the event are identified in the y component of the magnetic field. Then, using these anomalies, a threshold value for the standard deviation is defined for each event so that the anomalies with a higher standard deviation than this threshold value are examined and analyzed. Finally, the occurrence of the studied earthquakes was predicted by fitting the sigmoid function to the cumulative number of anomalies. Because the sigmoid function is not a dynamic function, at the same time, a cubic function has been used to estimate the critical time of the system so that when the sigmoid function cannot fit the data, the cubic function can do this. A first-order curve has also been used to show the proper fit of the data with the sigmoid and cubic functions. And also, C-factor has been used to show the strong compatibility of sigmoid and cubic functions with the cumulative number of anomalies. In the last stage, an analysis has been done under the title of “Confutation analysis” in such a way that the said algorithm is applied to the areas where the earthquake did not occur, and it is expected that the cumulative number of anomalies drawn, will be closer to the linear state than when the earthquake occurred. Using the existing database, 90% of the occurrence of earthquakes studied in this study, pre-indication abnormalities are observed a few hours to a month before the incidence of earthquakes.Also, a Confutation analysis was performed on three cases of earthquakes to show that the obtained results were not random and the change in the cumulative number of magnetic anomalies could be caused by the earthquake.

Omicron and periodontal health; a clinical exploration of gingivitis and periodontitis

Introduction: The COVID-19 pandemic has profoundly affected global health, with variants such as Omicron posing new challenges due to their increased transmissibility and potential to evade immunity. Periodontal diseases, which are highly prevalent worldwide, have been linked to various systemic conditions, including respiratory infections. Objectives: To determine how periodontal problems affect Omicron infection susceptibility, symptom severity, and outcome in individuals infected with this variety and discover oral microbiota biomarkers that indicate severe Omicron patients. Materials and Methods: To gather data, a quantitative descriptive study was instituted, utilizing a well-structured questionnaire comprising multiple-choice and Likert scale questions. The sample population, dentists in Erbil, was reached through email, followed by statistical analyses involving mean scores, standard deviations, and practices degree to interpret the data. Results: Results displayed a varied range of perceptions, with significant discrepancies highlighted through high standard deviations in specific responses, pointing to the necessity for homogenized guidelines or educational outreach. The overall mean score categorized the sentiment as ‘Medium,’ indicating a moderate level of consensus on the relationship between the Omicron variant and periodontal issues. Conclusion: This exploration unveils not only a nuanced understanding among the dentist community but also showcases domains where unanimity is deficient, calling for intensified research and educational efforts to harmonize perspectives in this pressing matter, especially amid the prevalence of the Omicron variant. The findings signify an imperative to foster aligned understandings through enhanced educational interventions in the dental community in Erbil, Kurdistan, Iraq, potentially steering towards a more cohesive approach in handling cases with pre-existing periodontal conditions amid the Omicron surge.

The signal quality improvement of laser-induced breakdown spectroscopy due to the microwave plasma torch modulation

BackgroundLaser-induced breakdown spectroscopy (LIBS) is a versatile analytical technique for element determination in solids, liquids, and gases. However, LIBS suffers from low detection sensitivity and high relative standard deviation (RSD), restricting its large-scale applications. the process of a physical sampling can, in some cases, compromise the mechanical strength of the component under examination. It should be considered that too large laser energy is bound to cause damage to samples which cannot be tolerated in the process of safe production in the nuclear industry. It is necessary to find a method to obtain high elemental signal intensity in low energy laser. ResultsHere, we present a novel approach by integrating microwave plasma torch (MPT) with LIBS, referred to as MPT-LIBS, which effectively addresses the limitations associated with traditional LIBS. The MPT-LIBS technique is evaluated using Cu samples with a low laser pulse energy of 0.55 mJ. A remarkable enhancement factor of over 70 for Cu I 521.82 nm line is demonstrated, while that of Cu I 324.75 nm and 327.40 nm lines exceeding two orders of magnitude. Furthermore, the RSDs of all Cu spectral lines are reduced, especially for Cu I 521.82 nm, which is decreased from 11.48 % to 1.36 %. This indicates a significant improvement in signal stability. Characterization of the tested samples using con-focal microscopy reveals that the ablation area of MPT-LIBS is only 1.36 times of that of LIBS. The limit of detection of Cu I 324.75 nm line is reduced from 52.8 ppk to 319 ppm. Significance and noveltyThis study not only offers valuable guidance for improving signal stability and the limit of detection in LIBS, but also demonstrates minimal sample damage due to its low ablation amount. Consequently, the proposed methodology has the potential to significantly advance LIBS technology, expanding its applicability in industrial applications.

PVC membrane bulk optode incorporating 4-nitrobenzo-15-crown-5 and sodium tetrakis(1-imidazolyl) borate for the pico-molar determination of silver ion in pharmaceutical formulation

Silver ion (Ag+) is of harmful effects to both environment and human health. Ag+ soluble compounds and salts is used in treating mental illness, epilepsy, nicotine addiction, gastroenteritis, and infectious diseases, including syphilis and gonorrhea, and as anti-infective dermatological agent for controlling nose bleeding. However, high Ag+ doses cause several harmful effects to human health such as irreversible pigmentation of skin and eye, and problems to liver and kidney. A bulk membrane Optode is proposed in this work to measure the Ag+ concentration in the pharmaceutical formulations. The membrane optode is prepared from the ionophore 4-nitobenzo-15-crown-5, the ion-exchanger sodium tetrakis (imidazolyl) borate, the plasticizer o-nitrophenyl octyl ether, and the chromoionophore ETH 5294; these components are dissolved in the PVC/THF slurry to form the membrane. The optode is studied by atomic force microscope and UV–visible spectrophotometer, and its spectrum exhibits two maximum wavelengths of 550 and 665 nm, and response for Ag+ at these maximum wavelengths is reproducible in the concentration range of 10–11 to 10–8 M using acetate buffer of pH 5.0, with very low detection limit of 8.8 × 10–12 M. The most important feature in this work is the selectivity improvement for Ag+ over all interfering ions; the selectivity coefficient logarithm logKAg+,cationopt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${logK}_{Ag+, cation}^{opt}$$\\end{document} is found to be − 4.3 for Cu2+, − 5.6 for Ni2+ and − 5.0 for Cd2+. The response mechanism is studied by FTIR, and it depends on ion-exchange of Ag+ and sodium imidazolyl borate, followed by the host–guest complexation between Ag+ and the crown ionophore, which is accompanied by concomitant deprotonation of the chromoionphore. The optode has a response time of 2–3 min within lifetime of 10 days with the same response. The optode can be applied successfully for Ag+ determination in the pharmaceutical formulation, PinkEye Relief® eye drop, which is used for treating inflammation, redness and water discharge of the eye; the high recovery and low standard deviation of the results using calibration curve method confirm the accuracy and precision of the proposed optode for its application in real samples.

Fabrication of a highly sensitive conductive copolymer layer modified immunosensing tool for cytokeratin-19 fragment detection

Design of a new and highly selective impedimetric biosensor based on the immobilization of a fragment of cytokeratin subunit 19 (CYFRA 21-1)-specific antibodies onto a conductive copolymer layer (poly(epoxy-substituted thiophene)-co-poly(3,4-ethylenedioxythiophene), CCL)-coated indium tin oxide (ITO) for the determination of CYFRA 21-1 in serum samples was reported. CCL was applied as a working electrode-modifying reagent to prepare the surface of the working ITO electrode, and CYFRA 21-1-specific antibodies bound to epoxy ends present in the copolymer layer matrix. The impedimetric response of the immunosensor to CYFRA 21-1 was recorded, and the signaling mechanism of the suggested immunosensor was based on an increase in the charge transfer resistance in the presence of target CYFRA 21-1. The developed biosensor exhibited excellent selectivity for CYFRA 21-1, and it could detect CYFRA 21-1 in a linear dynamic range from 0.0125 to 35 pg/mL with a limit of quantification (LOQ) of 12.25 fg/mL. The designed biosensor showed good storage stability, high sensitivity, suitable repeatability and reproducibility, and acceptable long-term stability. The clinical analysis of the manufactured immunosensor was explored for the analysis of serum samples, and high recoveries and good relative standard deviations (RSDs) were obtained in the range of 97.01 and 103.17 %, respectively. This copolymer-based biosensor could be a feasible tool for clinical diagnosis in complex serum samples.

Data-driven integration of synthetic representative volume elements and machine learning for improved microstructure-property linkage and material performance in ceramics

Ceramic materials, characterized by their heat resistance, dielectric properties, and mechanical performance, are often compromised by brittleness due to microstructural inclusions. These inclusions, such as defects, secondary phases, and pores, are critically analyzed for their impact on material strength and fracture properties. In this study, the linkage between microstructure and properties in ceramic materials is explored through a methodological approach that combines experimental observations with physics-based and machine learning models. A data-driven approach has been employed, utilizing synthetic Representative Volume Elements (RVEs) derived from X-ray computed tomography scans of ceramics. The methodology involves an automated finite element (FE) simulation process for progressive failure analysis under uniaxial compression and tension. The analysis is conducted using statistical, data-driven, and machine learning techniques, including principal component analysis and k-means clustering, to assess the microstructural features' impact on material performance. The study focuses on the use of RVEs for accurately capturing essential microstructural characteristics and addresses the challenges in developing synthetic models and the limitations of simulation capabilities. The study's findings reveal that less uniform inclusion distribution and a higher standard deviation in inclusion size correlate to lower mechanical performance. By applying data-driven methods, this research contributes to the optimization of material performance and the establishment of structure-property relationships, with a particular emphasis on the influence of inclusions and defects on the mechanical behavior of ceramic materials.

COMPARATIVE STUDY BETWEEN GOOGLE TRANSLATE AND PRINTED DICTIONARY TO INCREASE STUDENTS’ VOCABULARY

This study compares the effectiveness of Google Translate and printed dictionaries in enhancing students' vocabulary acquisition. A quantitative, quasi-experimental design was employed. Participants were twenty eighth-grade students from SMPN 4 Tolitoli (2023/2024), Central Sulawesi, Indonesia, divided into a control group (using printed dictionaries) and a treatment group (using Google Translate). Pre-tests and post-tests, consisting of multiple-choice, matching, and fill-in-the-blank tasks, assessed vocabulary knowledge. Data collection involved pre-tests, a four-week treatment, and post-tests. Descriptive statistics and t-tests analyzed the data. Both groups showed improved vocabulary acquisition post-treatment, with no significant differences in learning outcomes. Despite similar average scores, substantial variability was observed within each group, reflected by high standard deviations and wide score ranges. These results suggest both tools have unique strengths: Google Translate offers convenience and accessibility, while printed dictionaries provide comprehensive definitions and contextual understanding. A blended approach incorporating both tools is recommended for educators and curriculum designers. Future research should explore long-term vocabulary retention and the integration of digital tools into traditional learning frameworks, considering personalized strategies to address diverse student needs.

Dynamic Formation of a Posterior-to-Anterior Peak-Alpha-Frequency Gradient Driven by Two Distinct Processes.

Peak-alpha frequency varies across individuals and mental states, but it also forms a negative gradient from posterior to anterior regions in association with increases in cortical thickness and connectivity, reflecting a cortical hierarchy in temporal integration. Tracking the spatial standard deviation of peak-alpha frequency in scalp EEG, we observed that a posterior-to-anterior gradient dynamically formed and dissolved. Periods of high spatial standard deviation yielded robustly negative posterior-to-anterior gradients-the "gradient state"-while periods of low spatial standard deviation yielded globally converged peak-alpha frequency-the "uniform state." The state variations were characterized by a combination of slow (0.3-0.5 Hz) oscillations and random-walk-like fluctuations. They were relatively independently correlated with peak-alpha frequency variations in anterior regions and peak-alpha power variations in central regions driven by posterior regions (together accounting for ∼50% of the state variations), suggesting that two distinct mechanisms modulate the state variations: an anterior mechanism that directly adjusts peak-alpha frequencies and a posterior-central mechanism that indirectly adjusts them by influencing synchronization. The state variations likely reflect general operations as their spatiotemporal characteristics remained unchanged while participants engaged in a variety of tasks (breath focus, vigilance, working memory, mental arithmetic, and generative thinking) with their eyes closed or watched a silent nature video. The ongoing state variations may dynamically balance two global processing modes, one that facilitates greater temporal integration (and potentially also information influx) toward anterior regions in the gradient state and the other that facilitates flexible global communication (via phase locking) in the uniform state.

Highly sensitive and selective detection of amoxicillin using molecularly imprinted ratiometric fluorescent nanosensor based on quantum dots.

A dual-emission ratiometric fluorescence sensor (CDs@CdTe@MIP) with a self-calibration function was successfully constructed for AMO detection. In the CDs@CdTe@MIP system, non-imprinted polymer-coated CDs and molecule-imprinted polymer-coated CdTe quantum dots were used as the reference signal and response elements, respectively. The added AMO quenched the fluorescence of the CdTe quantum dots, whereas the fluorescence intensity of the CDs remained almost unchanged. The AMO concentration was monitored using the fluorescence intensity ratio (log(I647/I465)0/(I647/I465)) to reduce interference from the testing environment. The sensor with a low detection limit of 0.15μg/L enableddetection ofthe AMO concentration within 6min. The ratiometric fluorescence sensor was used to detect AMO in spiked pork samples; it exhibited a high recovery efficiency and relative standard deviation (RSD) of 97.94-103.70% and 3.77-4.37%, respectively. The proposed highly sensitive and selective platform opens avenues for sensitive, reliable, and rapid determination of pharmaceuticals in the environment and food safety monitoring using ratiometric sensors.

Integration of concentration gradient generator with competitive PCR in a droplet for rapid nucleic acid quantification

Competitive PCR is an efficient way for the measurement of nucleic acids without requiring a standard curve. It uses a competitor template mimicking the target sequence for direct comparison and quantification during amplification. However, manually preparing various concentrations for competitive PCR is labor-intensive. Additionally, target and competitor DNA bands are often inadequately separated on gels due to their similar sizes. This leads to inaccurate distinction and imprecise measurement of bandwidths and intensities, resulting in high standard deviations in quantification. Thus, this study presents an alternative way to combine droplet competitive PCR with the concentration gradient generator in a microfluidic device that simplifies competitive PCR preparation and provides precise control over reaction conditions and sample handling. Generating a wide range of competitor-to-target ratios in a single experiment enhances statistical reliability and isolating individual reactions in droplets reduces background noise and increases sensitivity. Additionally, it eliminates gel electrophoresis, improves consistency and reproducibility, requires smaller sample and reagent volumes, and allows direct sample quantification through a calibration curve for fast, simple quantification. We envision that our platform can offer a promising alternative to digital PCR, addressing its challenges and driving progress in molecular biology and diagnostics.

Digit ratios and hospitalization for COVID-19: A test of the low-androgen-driven and high-androgen-driven theories of COVID-19 severity.

Sex hormones are likely to be important determinants of COVID-19 severity, and two opposing explanations regarding severity, the low-androgen-driven and high-androgen-driven theories, seek to explain this pattern. Digit ratios are sex dependent (males<females) and are claimed to be markers for both prenatal and postnatal testosterone. Here, we use a measure of COVID-19severity (hospitalization), compare digit ratios in patients and controls and consider whether vaccination status changed these associations. Four digits were measured (2D, 3D, 4D, 5D). There were 194 participants (94 hospitalized patients [45 men] and 100 controls [53 men]) in Sample I and 162 participants (100 hospitalized [42 men], including 40 vaccinated and 62 controls [32 men]) in Sample II. Six ratios were calculated (2D:3D; 2D:4D; 2D:5D; 3D:4D; 3D:5D, 4D:5D) and compared between COVID-19 hospitalized and non-hospitalized patients and vaccinated and non-vaccinated. In comparison to controls, we found higher ("feminized") means in patient ratios that included 5D (2D:5D; 3D:5D; 4D:5D) in both samples. The differences were independent of sex and age. Hospitalized patients with COVID-19 have higher (feminized) means and higher standard deviations (SDs) for 5D digit ratios. Digit ratios are sex dependent (males<females) and are considered as markers for both prenatal and postnatal testosterone. If verified in future studies, the results will be helpful in regard to targeting mortality-reducing therapies for COVID-19 in certain groups of patients. We conclude that the association between high (feminized) 5D ratios and hospitalization supports the low-androgen-driven theory of COVID-19 severity.

Predictive uncertainty analysis for a highly parameterized karst aquifer using null-space Monte Carlo

Inverse problems in hydrogeology pose a great challenge for modelers as they are ill-posed, resulting in a non-unique solution. High computational resources are needed for the calibration process, especially in the case of highly parameterized aquifers like karst limestone, characterized by significant heterogeneity. The null-space Monte Carlo (NSMC) is a parameter-constrained Monte Carlo approach that can be used to quantify uncertainty, as it produces a set of solutions that calibrate the model. This method is used to assess uncertainty in the calibration of a karst aquifer in Qatar, which has high heterogeneity. Pilot points were used to reflect the geostatistics of the calibrated field, and the calibration results at these points were interpolated over the aquifer area using kriging. The NSMC was then used to produce 200 realizations of the null-space parameter field using the constrained random variable of hydraulic conductivity. The null-space realizations were then incorporated into the parameter space derived from the calibrated model. Statistical analysis of the calibrated hydraulic conductivity revealed a variation ranging from 0.1 to 350 m/d, indicating a considerable variability in the aquifer’s hydraulic parameters. The areas with high hydraulic conductivity were concentrated in the central and eastern parts of the aquifer, and these same areas exhibited a high standard deviation. Based on the findings of this study, while the NSMC method is effective for uncertainty analysis in solving inverse problems, it is important to note that a considerable number of runs are necessary to reach the threshold of calibration error. This is because of the significant non-linearity inherent in the karst aquifer.

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Mechanical Properties of Silicon Carbide Composites Reinforced with Reduced Graphene Oxide.

This article presents research on the influence of reduced graphene oxide on the mechanical properties of silicon carbide matrix composites sintered with the use of the Spark Plasma Sintering method. The produced sinters were subjected to a three-point bending test. An increase in flexural strength was observed, which reaches a maximum value of 503.8 MPa for SiC-2 wt.% rGO composite in comparison to 323 MPa for the reference SiC sample. The hardness of composites decreases with the increase in rGO content down to 1475 HV10, which is correlated with density results. Measured fracture toughness values are burdened with a high standard deviation due to the presence of rGO agglomerates. The KIC reaches values in the range of 3.22-3.82 MPa*m1/2. Three main mechanisms responsible for the increase in the fracture toughness of composites were identified: bridging, deflecting, and branching of cracks. Obtained results show that reduced graphene oxide can be used as a reinforcing phase to the SiC matrix, with an especially visible impact on flexural strength.

Association of systolic blood pressure variability with remote ischemic conditioning in acute ischemic stroke

Systolic blood pressure variability (SBPV) is associated with outcome in acute ischemic stroke. Remote ischemic conditioning (RIC) has been demonstrated to be effective in stroke and may affect blood pressure. Relationship between SBPV and RIC treatment after stroke warrants investigation. A total of 1707 patients from per-protocol analysis set of RICAMIS study were included. The SBPV was calculated based on blood pressure measured at admission, Day 7, and Day 12. (I) To investigate the effect of SBPV on efficacy of RIC in stroke, patients were divided into High and Low categories in each SBPV parameter. Primary outcome was excellent functional outcome at 90 days. Compared with Control, efficacy of RIC in each category and interaction between categories were investigated. (II) To investigate the effect of RIC treatment on SBPV, SBPV parameters were compared between RIC and Control groups. Compared with Control, a higher likelihood of primary outcome in RIC was found in high category (max–min: adjusted risk difference [RD] = 7.2, 95% CI 1.2–13.1, P = 0.02; standard deviation: adjusted RD = 11.5, 95% CI 1.6–21.4, P = 0.02; coefficient of variation: adjusted RD = 11.2, 95% CI 1.4–21.0, P = 0.03). Significant interaction of RIC on outcomes were found between High and Low standard deviations (adjusted P < 0.05). No significant difference in SBPV parameters were found between treatment groups. This is the first report that Chinese patients with acute moderate ischemic stroke and presenting with higher SBPV, who were non-cardioemoblic stroke and not candidates for intravenous thrombolysis or endovascular therapy, would benefit more from RIC with respect to functional outcomes at 90 days, but 2-week RIC treatment has no effect on SBPV during hospital.