A reliable estimate of evapotranspiration (ET) in river basins is important for the purpose of water resources planning and management. ET represents a significant portion of rainfall in the water ...budget; therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water resources. While remote sensing techniques are available to estimate ET, such methods are expensive and necessary data may not be readily available. Classical methods of estimating ET require detailed land use/cover information that are not readily available in rural river basins. Complementary methods provide simple and reliable approaches to estimate ET using meteorological data only. However, these methods have not been investigated in detail to assess the overall applicability and the needs for revisions if any. In this work, an improved approach to use the complementary methods using readily available meteorological data is presented. The methodology is validated using 34 global FLUXNET sites with heterogeneous land use/cover, climatic, and physical conditions. The method was compared with classical methods using Ghana as a study area where original pioneering studies of ET have been performed. The work was extended to develop global maps of ET and water surplus (precipitation - ET) for the 20 th century followed by climate change-induced 21st century estimates for 2040-2069 and 2070-2099 periods. The emission scenario used was the moderate A1B with the global climate models CGCM3.1 and HADGEM1. The results were assessed at different scales from global to regional such as for potential outcomes of climate change on ET and water surplus.
AIM To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy.METHODS A cohort of 332 patients infected ...with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensinconverting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance(HOMA-IR).RESULTS Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis(F0-F) = 179, moderate fibrosis(F2) = 64, and advanced fibrosis(F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage(P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤-0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis.CONCLUSION Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy.
Current SARS-CoV-2 containment measures rely on controlling viral transmission. Effective prioritization can be determined by understanding SARS-CoV-2 transmission dynamics. We conducted a systematic ...review and meta-analyses of the secondary attack rate (SAR) in household and healthcare settings. We also examined whether household transmission differed by symptom status of index case, adult and children, and relationship to index case.
We searched PubMed, medRxiv, and bioRxiv databases between January 1 and July 25, 2020. High-quality studies presenting original data for calculating point estimates and 95% confidence intervals (CI) were included. Random effects models were constructed to pool SAR in household and healthcare settings. Publication bias was assessed by funnel plots and Egger's meta-regression test.
43 studies met the inclusion criteria for household SAR, 18 for healthcare SAR, and 17 for other settings. The pooled household SAR was 18.1% (95% CI: 15.7%, 20.6%), with significant heterogeneity across studies ranging from 3.9% to 54.9%. SAR of symptomatic index cases was higher than asymptomatic cases (RR: 3.23; 95% CI: 1.46, 7.14). Adults showed higher susceptibility to infection than children (RR: 1.71; 95% CI: 1.35, 2.17). Spouses of index cases were more likely to be infected compared to other household contacts (RR: 2.39; 95% CI: 1.79, 3.19). In healthcare settings, SAR was estimated at 0.7% (95% CI: 0.4%, 1.0%).
While aggressive contact tracing strategies may be appropriate early in an outbreak, as it progresses, measures should transition to account for setting-specific transmission risk. Quarantine may need to cover entire communities while tracing shifts to identifying transmission hotspots and vulnerable populations. Where possible, confirmed cases should be isolated away from the household.
Smart health surveillance technology has attracted wide attention between patients and professionals or specialists to provide early detection of critical abnormal situations without the need to be ...in direct contact with the patient. This paper presents a secure smart monitoring portable multivital signal system based on Internet-of-Things (IoT) technology. The implemented system is designed to measure the key health parameters: heart rate (HR), blood oxygen saturation (SpO2), and body temperature, simultaneously. The captured physiological signals are processed and encrypted using the Advanced Encryption Standard (AES) algorithm before sending them to the cloud. An ESP8266 integrated unit is used for processing, encryption, and providing connectivity to the cloud over Wi-Fi. On the other side, trusted medical organization servers receive and decrypt the measurements and display the values on the monitoring dashboard for the authorized specialists. The proposed system measurements are compared with a number of commercial medical devices. Results demonstrate that the measurements of the proposed system are within the 95% confidence interval. Moreover, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Error (MRE) for the proposed system are calculated as 1.44, 1.12, and 0.012, respectively, for HR, 1.13, 0.92, and 0.009, respectively, for SpO2, and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system.
Seizures are a common neurological disorder that affects people of all ages. These sudden, uncontrolled electrical disturbances in the brain can cause a variety of symptoms, including convulsions, ...loss of consciousness, and abnormal sensations. While seizures have long been recognized as a potential cause of hormonal imbalances, recent research has shed new light on the link between seizures and prolactin. The study involved 30 adult female Wistar rats, which were divided into a control group (treated with normal saline) and four treatment groups: chronic group (treated with 30 mg/kg pentylenetetrazol intraperitoneally three days a week for 10 weeks), chronic + Levetiracetam (50 mg/kg, gavage), chronic + Cabergoline (0.05 mg/kg, gavage), and chronic + Levetiracetam (25 mg/kg) + cabergoline (0.025). The drugs were administered three days a week for 10 weeks. Field action potentials were recorded from the CA1 area of the hippocampus using eLab after anesthetizing the animals with a ketamine-xylazine combination (70 +7 mg/kg). The prolactin levels were measured using the ELISA method after serum preparation. The findings indicate that the use of levetiracetam as an anticonvulsant drug resulted in a significant decrease in the amount of prolactin and spike number of convulsive activities compared to the chronic group. However, the amplitudes of convulsive activities did not show a significant difference between the control and other treatment groups. In conclusion, investigating the possibility of subclinical seizures and utilizing anticonvulsant medications in hyperprolactinemia that is resistant to treatment are crucial in treating infertility.
•How chronic seizures affect serum prolactin levels and the intricate relationship between seizures and hormonal regulation.•Levetiracetam effectively reduces prolactin levels in rats with chronic seizures.•Levetiracetam's effectiveness in suppressing neuronal hyperexcitability shows promise for treating chronic seizures.
This paper evaluates the performance and suitability of four different metaheuristic algorithms for optimal sizing of standalone microgrids in remote area. The studied metaheuristic algorithms are ...particle swarm optimization, differential evolution, water cycle algorithm and grey wolf optimization. These algorithms are applied to optimize the capacity of diesel generator, fuel tank, solar photovoltaic, wind turbine, and battery energy storage in four different AC-coupled standalone microgrids for a remote area community in South Australia. The objective function is selected as the net present value of electricity over a 20-year lifetime. The optimisation study is conducted based on the real data of annual load consumption, ambient temperature, solar insolation, and wind speed of the site. Capital, replacement, and maintenance costs of components in Australian market are incorporated for the economic analysis. An operating power reserve is maintained based on the static and dynamic reserve concepts. Uncertainty analysis based on 10-year real data of renewable energies and load consumption is conducted. Sensitivity analysis is provided for variations of the battery price and capacity. The performance of the applied algorithms is evaluated by comparing the economic and operational results, as well as the computational time and optimization convergence. It is found that differential evolution algorithm is unreliable for optimal sizing problem of the studied standalone microgrids..
Biometric identification depends on the statistical analysis of the unique physical and behavioral characteristics of individuals. However, a unimodal biometric system is susceptible to different ...attacks such as spoof attacks. To overcome these limitations, we propose a multimodal biometric authentication system based on deep fusion of electrocardiogram (ECG) and finger vein. The proposed system has
three
main components, which are biometric pre-processing, deep feature extraction, and authentication. During the pre-processing, normalization and filtering techniques are adapted for each biometric. In the feature extraction process, the features are extracted using a proposed deep Convolutional Neural Network (CNN) model. Then, the authentication process is performed on the extracted features using
five
well-known machine learning classifiers: Support Vector Machine (SVM), K-Nearest Neighbors (KNNs), Random Forest (RF), Naive Bayes (NB), and Artificial Neural Network (ANN). In addition, to represent the deep features in a low-dimensional feature space and speed up the authentication task, we adopt Multi-Canonical Correlation Analysis (MCCA). We combine the two biometric systems based on ECG and finger vein into a single multimodal biometric system using feature and score fusion. The performance of the proposed system is tested on
two
finger vein (TW finger vein and VeinPolyU finger vein) databases and
two
ECG (MWM-HIT and ECG-ID) databases. Experimental results reveal improvement in terms of authentication performance with Equal Error Rates (EERs) of 0.12% and 1.40% using feature fusion and score fusion, respectively. Furthermore, the authentication with the proposed multimodal system using MCCA feature fusion with a KNN classifier shows an increase of accuracy by an average of 10% compared with those of other machine learning algorithms. Therefore, the proposed biometric system is effective in performing secure authentication and assisting the stakeholders in making accurate authentication of users.
•Fabrication of an 18-cell SEES for the ECL detection of HER2.•Gold nanoprism-enhanced ECL of luminol/H2O2.•A wide linear range of 1 pg mL−1 to 1 μg mL−1.
Breast cancer, constituting 30% of newly ...diagnosed cancer cases in women globally, remains a critical health issue. Timely identification of cancer biomarkers, such as human epidermal growth factor receptor 2 (HER2), is crucial for prediction, diagnosis, and monitoring. Addressing this challenge, a groundbreaking single-electrode electrochemical system has been developed for electrochemiluminescence (ECL) detection of HER2 antigen. This innovative immunosensor utilizes a sandwich immunoassay technique, incorporating gold nanoprisms to enhance the ECL signal produced by luminol. Noteworthy is the single electrode electrochemical system (SEES), featuring 18 individual electrochemical cells for concurrent analysis of 18 samples.
The research introduces a fully integrated and compact ECL immunosensor capable of simultaneously evaluating 18 samples. To boost electrode performance, Ti3C2 MXene modification is applied, enhancing electrical conductivity and facilitating antibody attachment through OH functional groups. Au nanoprisms play a crucial role in intensifying the ECL signal, particularly in the presence of H2O2, enhancing analyte detection. ImageJ software is employed for data analysis, establishing a robust linear correlation between the B value and the logarithm of analyte concentration in artificial sample analysis.
In real sample examination, the linear range remains consistent, with an impressive Limit of Detection (LOD) of 5 pg mL−1, highlighting the system's reliability. Its adaptability to diverse antibodies positions it as a versatile tool for detecting a broad spectrum of analytes, enhancing practicality, and facilitating exploration of various substances of interest. The device, maintaining the same framework while adjusting antibodies, emerges as a potent instrument for identifying and quantifying diverse analytes, providing a resilient platform for ongoing research and innovation.
Using a rehabilitation program for the survivors of acute respiratory distress syndrome (ARDS) could be one of the important and fundamental steps to improve the pulmonary function and health-related ...quality of life (HRQoL) of patients. This study was carried out to evaluate the effect of two rehabilitation techniques (Family-Based Empowerment Model (FECM)/Continuing Care Model (CCM), or both of them) on pulmonary function, and HRQoL in ARDS survivors. From December 2009 to June 2016, ARDS survivors from mixed medical-surgical ICUs at four academic teaching hospitals in Tehran, Iran, were randomly assigned to one of three intervention groups (A, B, or C) or a control group (D). Pre- and post-interventions, pulmonary functions and HRQoL status of patients in all groups were collected 48 times via clinical measurements and various questionnaires during 5 years of follow-up. Significantly improvement was seen in the intervention groups compared to the control group, and the greatest benefit was observed in patients who received mixed of FCEM and CCM rehabilitation techniques. Co-administration of FCEM and CCM can improve pulmonary function as well as the life satisfaction of ARDS survivors. As a result, the execution of the empowerment model by nurses is recommended for ARDS survivors and the participation of their families at the same time.Trial registration: NCT02787720 (ClinicalTrial.gov, 24/05/2016).
PDF
