Morphostructural studies of pure and mixed metal oxide nanoparticles of Cu with Ni and Zn.

Nano-scale interactions between pure metal or metal-oxide components within an oxide matrix can improve functional performance over basic metal oxides. This study reports on the synthesis of monometallic (CuO), bimetallic (CuO-NiO) and trimetallic (CuO-NiO-ZnO) oxide nanoparticles (NPs) via the co-precipitation method and investigation of morphostructural properties. All of the synthesized metal oxide NPs were calcined at 550 °C temperature and annealed under vacuum. In this work, we applied Scherrer formula, modified Scherrer equation, Williamson-Hall plots, and Halder-Wagner plots to calculate the average crystallite size. The XRD data analysis showed that average crystallite sizes of the as-synthesized metal oxide phases were between 4 nm and 76 nm and average diameters calculated from SEM image were between 15 nm and 83 nm. The XRD studies also disclosed that average crystallite size and lattice microstrain of the CuO phases remain almost same (43 nm-46 nm and 2.074×10-3 to 2.665×10-3) for pure CuO and mixed CuO-NiO; but in case of mixed CuO-NiO-ZnO it is found to decrease in size to 11 nm where lattice microstrain increases to 9.653×10-3. Line broadening of diffraction peaks from microstrain contribution was between 0.02 and 0.01. Degree of crystallinity (%) of CuO phases found to decrease from 81 to 71. Dislocation density of CuO phases found to increase from 6.63×10-4nm-2 to 12.68×10-3nm-2. X-ray density of CuO phases increased from 6.48 to 6.53 g/cm3. Where this calculated small dislocation density well agreed with the high crystallinity. Crystal structure and specific surface area were determined from lattice constants and X-ray density. These synthesized nanopowders showed the existence of monoclinic, cubic, and hexagonal phases. The obtained NPs of multi-metal oxide explained more than one phases with different size, shape, and morphology at nano scale.

Multi-Stage Classification of Retinal OCT Using Multi-Scale Ensemble Deep Architecture.

Accurate noninvasive diagnosis of retinal disorders is required for appropriate treatment or precision medicine. This work proposes a multi-stage classification network built on a multi-scale (pyramidal) feature ensemble architecture for retinal image classification using optical coherence tomography (OCT) images. First, a scale-adaptive neural network is developed to produce multi-scale inputs for feature extraction and ensemble learning. The larger input sizes yield more global information, while the smaller input sizes focus on local details. Then, a feature-rich pyramidal architecture is designed to extract multi-scale features as inputs using DenseNet as the backbone. The advantage of the hierarchical structure is that it allows the system to extract multi-scale, information-rich features for the accurate classification of retinal disorders. Evaluation on two public OCT datasets containing normal and abnormal retinas (e.g., diabetic macular edema (DME), choroidal neovascularization (CNV), age-related macular degeneration (AMD), and Drusen) and comparison against recent networks demonstrates the advantages of the proposed architecture's ability to produce feature-rich classification with average accuracy of 97.78%, 96.83%, and 94.26% for the first (binary) stage, second (three-class) stage, and all-at-once (four-class) classification, respectively, using cross-validation experiments using the first dataset. In the second dataset, our system showed an overall accuracy, sensitivity, and specificity of 99.69%, 99.71%, and 99.87%, respectively. Overall, the tangible advantages of the proposed network for enhanced feature learning might be used in various medical image classification tasks where scale-invariant features are crucial for precise diagnosis.

Nutritional characterization and antioxidant properties of various edible portions of Cucurbita maxima: A potential source of nutraceuticals.

Pumpkin (Cucurbita maxima) is a widely grown vegetable in Bangladesh and is known as the sole supplier of various nutrients. Many studies evidence the nutritional value of flesh and seed while peel, flower, and leaves were reported scarcely with limited information. Therefore, the study aimed to investigate the nutritional composition and antioxidant properties of flesh, peel, seed, leaves, and flowers of Cucurbita maxima. The seed had a remarkable composition of nutrients and amino acids. Flowers and leaves possessed higher content of minerals, phenols, flavonoids, carotenes, and total antioxidant activity. The order of IC50 value (peel > seed > leaves > flesh > flower) indicates higher DPPH radicals scavenging activity of the flower. Moreover, a significant positive relationship was observed among these phytochemical constituents (TPC, TFC, TCC, TAA) and DPPH radicals scavenging activity. It could be concluded that these five parts of the pumpkin plant have an intense potency to be an exigent component of functional food or medicinal herbs.

Availability of medical abortion medicines in eight countries: a descriptive analysis of key findings and opportunities.

BACKGROUND: In recent years a growing number of manufacturers and medical abortion products have entered country markets and health systems, with varying degrees of quality and accessibility. An interplay of factors including pharmaceutical regulations, abortion laws, government policies and service delivery guidelines and provider's knowledge and practices influence the availability of medical abortion medicines. We assessed the availability of medical abortion in eight countries to increase understanding among policymakers of the need to improve availability and affordability of quality-assured medical abortion products at regional and national levels. METHODS: Using a national assessment protocol and an availability framework, we assessed the availability of medical abortion medicines in Bangladesh, Liberia, Malawi, Nepal, Nigeria, Rwanda, Sierra Leone and South Africa between September 2019 and January 2020. RESULTS: Registration of abortion medicines-misoprostol or a combination of mifepristone and misoprostol-was established in all countries assessed, except Rwanda. Mifepristone and misoprostol regimen for medical abortion was identified on the national essential medicines list/standard treatment guidelines for South Africa as well as in specific abortion care service and delivery guidelines for Bangladesh, Nepal, Nigeria, and Rwanda. In Liberia, Malawi, and Sierra Leone-countries with highly restrictive abortion laws and no abortion service delivery guidelines or training curricula-no government-supported training on medical abortion for public sector providers had occurred. Instead, training on medical abortion was either limited in scope to select private sector providers and pharmacists or prohibited. Community awareness activities on medical abortion have been limited in scope across the countries assessed and where abortion is broadly legal, most women do not know that it is an option. CONCLUSION: Understanding the factors that influence the availability of medical abortion medicines is important to support policymakers improve availability of these medicines. The landscape assessments documented that medical abortion commodities can be uniquely impacted by the laws, policies, values, and degree of restrictions placed on service delivery programs. Results of the assessments can guide actions to improve access.

Unsafe abortion is a leading cause of death and disability among women of reproductive age. Medical management of abortion with mifepristone and misoprostol pills, or just misoprostol, is a safe and effective way to end a pregnancy. Owing to an increase in the number of medical abortion products that have entered country health systems, we examined access to these medicines from supply to demand in selected countries. The overarching goal of the national landscape assessments was to produce evidence to support advocacy efforts and policymaking for improved access to quality medical abortion products that is appropriate to the needs of the country. This paper aims to describe key findings across eight country settings on the availability of medical abortion medicines and identify key opportunities to improve access to them across countries.

Effects of Antidepressants on COVID-19 Outcomes: Retrospective Study on Large-Scale Electronic Health Record Data.

BACKGROUND: Antidepressants exert an anticholinergic effect in varying degrees, and various classes of antidepressants can produce a different effect on immune function. While the early use of antidepressants has a notional effect on COVID-19 outcomes, the relationship between the risk of COVID-19 severity and the use of antidepressants has not been properly investigated previously owing to the high costs involved with clinical trials. Large-scale observational data and recent advancements in statistical analysis provide ample opportunity to virtualize a clinical trial to discover the detrimental effects of the early use of antidepressants. OBJECTIVE: We primarily aimed to investigate electronic health records for causal effect estimation and use the data for discovering the causal effects of early antidepressant use on COVID-19 outcomes. As a secondary aim, we developed methods for validating our causal effect estimation pipeline. METHODS: We used the National COVID Cohort Collaborative (N3C), a database aggregating health history for over 12 million people in the United States, including over 5 million with a positive COVID-19 test. We selected 241,952 COVID-19-positive patients (age >13 years) with at least 1 year of medical history. The study included a 18,584-dimensional covariate vector for each person and 16 different antidepressants. We used propensity score weighting based on the logistic regression method to estimate causal effects on the entire data. Then, we used the Node2Vec embedding method to encode SNOMED-CT (Systematized Nomenclature of Medicine-Clinical Terms) medical codes and applied random forest regression to estimate causal effects. We used both methods to estimate causal effects of antidepressants on COVID-19 outcomes. We also selected few negatively effective conditions for COVID-19 outcomes and estimated their effects using our proposed methods to validate their efficacy. RESULTS: The average treatment effect (ATE) of using any one of the antidepressants was -0.076 (95% CI -0.082 to -0.069; P<.001) with the propensity score weighting method. For the method using SNOMED-CT medical embedding, the ATE of using any one of the antidepressants was -0.423 (95% CI -0.382 to -0.463; P<.001). CONCLUSIONS: We applied multiple causal inference methods with novel application of health embeddings to investigate the effects of antidepressants on COVID-19 outcomes. Additionally, we proposed a novel drug effect analysis-based evaluation technique to justify the efficacy of the proposed method. This study offers causal inference methods on large-scale electronic health record data to discover the effects of common antidepressants on COVID-19 hospitalization or a worse outcome. We found that common antidepressants may increase the risk of COVID-19 complications and uncovered a pattern where certain antidepressants were associated with a lower risk of hospitalization. While discovering the detrimental effects of these drugs on outcomes could guide preventive care, identification of beneficial effects would allow us to propose drug repurposing for COVID-19 treatment.

Evaluation of advanced curve speed warning system to prevent fire truck rollover crashes.

INTRODUCTION: A disproportionately high number of deadly crash-incidents involve fire-tanker rollovers during emergency response driving. Most of these rollover incidents occur at dangerous horizontal curves ("curves") due to unsafe speed. This study examined the effects of a curve speed warning system (CSWS) on fire tanker drivers' emergency response behavior to develop system improvement suggestions. METHOD: Twenty-four firefighters participated in driving tests using a simulator. A fire tanker model, carrying a full tank of water, was used in emergency driving tests performed with and without CSWS. The CSWS was designed using the algorithm for passenger vehicles with a few initial modifications considering the unique requirements of heavy fire tanker and emergency driving. RESULTS: The results indicated that the CSWS was effective in issuing preemptive warnings when the drivers were approaching curves with unsafe speed during emergency response. Warnings occurred more frequently at curves with smaller radius. Although the CSWS improved driving performance, it did not significantly reduce the number of rollover events. A detailed analysis of the rollover events provided suggestions for improvement of CSWS algorithms. CONCLUSIONS: To further improve the CSWS algorithm, the following may be considered: including increased safety speed margin below the rollover critical speed, moving the speed warning trigger from the curve apex to the curve entry point, extending the safe speed-control zone to cover the entire curve, and employing artificial intelligence to accommodate individual driving styles. PRACTICAL APPLICATIONS: Fire tankers continue to be at increased risk of rollover during emergency response due to unsafe negotiation of dangerous curves. Development and use of advanced driver assist systems such as CSWS evaluated in this study may be an effective strategy to prevent deadly rollover crash-incidents. The knowledge generated by this study will be useful for system designers to improve the CSWS specifically designed for heavy emergency vehicles.

Socioeconomic inequalities in utilizing facility delivery in Bangladesh: A decomposition analysis using nationwide 2017-2018 demographic and health survey data.

BACKGROUND: In many low- and middle-income countries (LMICs), including Bangladesh, socioeconomic inequalities in access to maternity care remain a substantial public health concern. Due to the paucity of research, we attempted to determine the factors affecting the facility delivery, quantify wealth-related inequality, and identify potential components that could explain the inequality. METHODS: We used the latest Bangladesh Demographic and Health Survey (BDHS 2017-18) data in this study. We utilized logistic regression to investigate the associated factors of facility delivery. The concentration curves (CC), concentration index (CIX) and decomposition of CIX techniques were used to analyze the inequality in-facility delivery. RESULTS: Women living in the urban areas, age at first birth after (18-24 years ≥25 years), being overweight/obese, having secondary and higher-level education of the women and their husband, seeking four or more ANC, coming from more affluent households, and women with high enlightenment were significant determinants of facility delivery. The concentration curve was below the line of equality, and the relative concentration index (CIX) was 0.205 (p <0.001), indicating that women from wealthy groups were disproportionately more prevalent to facility delivery. The decomposition analysis reveals that wealth status of women (57.40%), age at first birth (10.24%), husband's education (8.96%), husband's occupation (7.35%), education of women (7.13%), women's enlightenment (6.15%), residence (8.64%) and ANC visit (6.84%) are the most major contributors to the inequalities in utilizing facility delivery. CONCLUSION: The study demonstrates a clear disparity in the use of facility delivery among Bangladeshi women; hence, immediate action is required to lower the inequalities, with a special emphasis on the contributing factors.

Stigma toward people with COVID-19 among Bangladeshi older adults.

The onset of the coronavirus disease (COVID-19) pandemic and its overwhelming physical and mental health burden can result in stigmatization toward the disease and those affected. This study aimed to measure the prevalence of COVID-19-related stigma and its associated factors among older people in Bangladesh. This cross-sectional study was conducted among 1,045 Bangladeshi older adults aged 60 years and above through telephone interviews in September 2021. The outcome was measured using an eight-point Stigma Scale, adapted to the Bengali language. Level of stigma was indicated by the cumulative score of the eight-items, ranging from 0 to 8, with a higher score indicating a higher level of stigma. On average, participants had stigmas on three of the eight items, and 62.6% had a high stigma score. The most prevalent stigmas were as follows: COVID-19 is a punishment from God (79.3%), patients with previous COVID-19 must be isolated (67.3%), and people infected with COVID-19 did not meet hygiene standards (63.9%). Participants who lived in rural areas (ß: 0.67, 95% CI: 0.39 to 0.95) and who perceived needing additional care during the pandemic (ß: 0.35, 95% CI: 0.09 to 0.60) had a higher average stigma score, whereas stigma scores were lower among unemployed/retired participants (ß: -0.22, 95% CI: -0.45 to 0.00). The study findings suggest implementing interventions to raise awareness through appropriate health literacy interventions and mass media campaigns.

Portable health clinic COVID-19 system for remote patient follow-up ensuring clinical safety.

Background: A developing country like Bangladesh suffers very much from the sudden appearance of the COVID-19 pandemic due to the shortage of medical facilities for testing and follow-up treatment. The Portable Health Clinic (PHC) system has developed the COVID-19 module with a triage system for the detection of COVID-19 suspects and the follow-up of the home quarantined COVID-19 patients to reduce the workload of the limited medical facilities. Methods: The PHC COVID-19 system maintains a questionnaire-based triage function using the experience of the Japanese practice of diseases management for early detection of suspected COVID-19 patients who may need a confirmation test. Then only the highly suspected patients go for testing preventing the unnecessary crowd from the confirmation PCR test centers and hospitals. Like the basic PHC system, it also has the features for patients' treatment and follow-up for the home quarantined COVID-19 positive and suspect patients using a telemedicine system. This COVID-19 system service box contains 4 self-checking medical sensors, namely, (1) thermometer, (2) pulse oximeter, (3) blood pressure machine, and (4) glucometer for patient's health monitoring including a tablet PC installed with COVID-19 system application for communication between patient and doctor for tele-consultancy. Results: This study conducted a COVID-19 triage among 300 villagers and identified 220 green, 45 light-yellow, 2 yellow, 30 orange, and 3 red patients. Besides the 3 red patients, the call center doctors also referred another 13 patients out of the 30 orange patients to health facilities for PCR tests as suspect COVID-19 positive, and to go under their follow-up. Out of these (3 + 13 =) 16 patients, only 4 went for PCR test and 3 of them had been tested positive. The remaining orange, yellow and light-yellow patients were advised home quarantine under the follow-up of the PHC health workers and got cured in 1-2 weeks. Conclusions: This system can contribute to the community healthcare system by ensuring quality service to the suspected and 80% or more tested COVID-19 positive patients who are usually in the moderate or mild state and do not need to be hospitalized. The PHC COVID-19 system provides services maintaining social distance for preventing infection and ensuring clinical safety for both the patients and the health workers.

An online cursive handwritten medical words recognition system for busy doctors in developing countries for ensuring efficient healthcare service delivery.

Doctors in developing countries are too busy to write digital prescriptions. Ninety-seven percent of Bangladeshi doctors write handwritten prescriptions, the majority of which lack legibility. Prescriptions are harder to read as they contain multiple languages. This paper proposes a machine learning approach to recognize doctors' handwriting to create digital prescriptions. A 'Handwritten Medical Term Corpus' dataset is developed containing 17,431 samples of 480 medical terms. In order to improve the recognition efficiency, this paper introduces a data augmentation technique to widen the variety and increase the sample size. A sequence of line data is extracted from the augmented images of 1,591,100 samples and fed to a Bidirectional Long Short-Term Memory (LSTM) network. Data augmentation includes pattern Rotating, Shifting, and Stretching (RSS). Eight different combinations are applied to evaluate the strength of the proposed method. The result shows 93.0% average accuracy (max: 94.5%, min: 92.1%) using Bidirectional LSTM and RSS data augmentation. This accuracy is 19.6% higher than the recognition result with no data expansion. The proposed handwritten recognition technology can be installed in a smartpen for busy doctors which will recognize the writings and digitize them in real-time. It is expected that the smartpen will contribute to reduce medical errors, save medical costs and ensure healthy living in developing countries.

Role of Surface Tension in Microrobot Penetration in Membranes.

cell-membrane fusion using microrobots can be a useful technique for delivering bioactive compounds to cellular systems. The role of membrane curvature and lipid ordering in the cell membrane penetration process is well known. However, once the fusion into the cell membrane is already initiated, the fluid dynamics of microrobot penetration based on tension difference of the microrobot solution and membrane curvature at the fusion pore has not been explored yet. Here, we demonstrate how surface tension difference among merging interfaces plays role in microrobot droplet penetration into a liquid bath, mimicking cell membrane fusion. The maximum penetration of a microrobot droplet into a liquid bath depends on the positive difference of surface tension between the droplet and liquid bath, longitudinal curvature of the bridge region, and the size of the droplet.

Cyclic force driven colloidal self-assembly near a solid surface.

HYPOTHESIS: Self-assembled colloidal mobility out of a non-equilibrium system can depend on many external and interparticle forces including hydrodynamic forces. While the driving forces guiding colloidal suspension, translation and self-assembly are different and unique, hydrodynamic forces are always present and can significantly influence particle motion. Unfortunately, these interparticle hydrodynamic interactions are typically overlooked. EXPERIMENTS: Here, we studied the collective behavior of colloidal particles (4.0 µm PMMA), located near the solid surface in a fluid medium confined in a cylindrical cell (3.0 mm diameter, 0.25 mm height) which was rotated vertically at a low rotational speed (20 rpm). The observed colloidal behavior was then validated through a Stokesian dynamics simulation where the concept of hydrodynamic contact force or lubrication interactions are avoided which is not physically intuitive and mathematically cumbersome. Rather, we adopted hard-sphere like colloidal collision or mobility model, while adopting other useful simplification and approximations. FINDINGS: Upon particles settling in a circular orbit, they hydrodynamically interact with each other and evolve in different structures depending on the pattern of gravity forces. Their agglomeration is a function of the applied rotation scheme, either forming colloidal clusters or lanes. While evolving into dynamic structures, colloids also laterally migrate away from the surface.

Was there any change in tobacco smoking among adults in Bangladesh during 2009-2017? Insights from two nationally representative cross-sectional surveys.

OBJECTIVE: This study assessed the changes in prevalence and associated factors of tobacco smoking among Bangladeshi adults over time. DESIGN: Nationally representative cross-sectional surveys. SETTING: Two most recent Global Adults Tobacco Survey (GATS) data from Bangladesh, carried out in 2009 and 2017. PARTICIPANTS: Adult population aged 15 and above (n=9629 in 2009; n=12 783 in 2017). OUTCOME MEASURES: Current use of tobacco smoke, including cigarettes, bidi, hukkah, cigars or pipes, which was dichotomised ('yes'/'no'). METHODS: We analysed data from two recent rounds of GATS (2009 and 2017). Multivariate logistic regression analysis was used. RESULTS: The overall prevalence of tobacco smoking among Bangladeshi adults was noted (23.00%, 95% CI 22.98 to 23.00 in 2009; 16.44%, 95% CI 16.43 to 16.45 in 2017). Being male (adjusted OR (AOR)=59.72, CI 40.56 to 87.93 for 2009; AOR=71.17, CI 41.08 to 123.32 for 2017), age between 25 and 64 years (all AORs >2 and p<0.05), smoking permissible at home (AOR=7.08, CI 5.88 to 8.52 for 2009; AOR=5.90, CI 5.34 to 6.95 for 2017), and watching tobacco smoking product use in movie/drama scenes (AOR=1.26, CI 1.11 to 1.44 for 2009; AOR=1.34, CI 1.17 to 1.54 for 2017) were found to be significantly associated with increased tobacco smoking among adults both in 2009 and in 2017. However, being offered free tobacco sample products (AOR=0.66, CI 0.57 to 0.77 for 2009; AOR=0.87, CI 0.76 to 0.99 for 2017) and having primary, secondary or higher education (all AORs <1 and p<0.05) as well as being a student (AOR=0.16, CI 0.09 to 0.29 for 2009; AOR=0.32, CI 0.19 to 0.53) were associated with lower odds of tobacco smoking in both surveys. CONCLUSIONS: Although the prevalence of tobacco smoking has declined over the period, it is still high among those who were relatively older, men, less educated and exposed to a movie/drama where tobacco smoking is promoted. Therefore, appropriate interventions are required to stop tobacco smoking among the Bangladeshi population.

Interocular Symmetry Analysis of Corneal Elevation Using the Fellow Eye as the Reference Surface and Machine Learning.

Unilateral corneal indices and topography maps are routinely used in practice, however, although there is consensus that fellow-eye asymmetry can be clinically significant, symmetry studies are limited to local curvature and single-point thickness or elevation measures. To improve our current practices, there is a need to devise algorithms for generating symmetry colormaps, study and categorize their patterns, and develop reference ranges for new global discriminative indices for identifying abnormal corneas. In this work, we test the feasibility of using the fellow eye as the reference surface for studying elevation symmetry throughout the entire corneal surface using 9230 raw Pentacam files from a population-based cohort of 4613 middle-aged adults. The 140 × 140 matrix of anterior elevation data in these files were handled with Python to subtract matrices, create color-coded maps, and engineer features for machine learning. The most common pattern was a monochrome circle ("flat") denoting excellent mirror symmetry. Other discernible patterns were named "tilt", "cone", and "four-leaf". Clustering was done with different combinations of features and various algorithms using Waikato Environment for Knowledge Analysis (WEKA). Our proposed approach can identify cases that may appear normal in each eye individually but need further testing. This work will be enhanced by including data of posterior elevation, thickness, and common diagnostic indices.

Membrane tension may define the deadliest virus infection.

This manuscript describes the potentially significant role of interfacial tension in viral infection. Our hypothesis is based on evidence from drop coalescence hydrodynamics. A change in membrane tension can trigger fusion between the vesicle and cell such that genetic material, like viral RNA, can subsequently be transported to the cell interior. In other cases, RNA may reside near the cell membrane inside the cell, which could make their removal energetically unfavorable because of hydrodynamic interactions between membrane and RNA. Interfacial tension of the virus membrane can be modulated by temperature, among many other factors, of the mucosa layer. We discuss our hypothesis within the scope of recent SARS-CoV-2 studies where temperature-dependent membrane surface tension could be impacted through different atmospheric conditions, air conditioning systems, and the use of masks.

Evaluation of advanced curve speed warning system for fire trucks.

A curve speed warning system (CSWS) for firetrucks was developed and tested in this study. The CSWS algorithm was developed based on guidelines in the public domain for general vehicles and modified for firetrucks for their configuration and emergency driving. Twenty-four firefighters participated in the test in a driving simulator. The results show that the CSWS was effective in issuing preemptive warnings when the drivers were approaching curves with unsafe speed during emergency responses. Drivers reduced their driving speed at curve approaching and entering phases for most challenging curves, without affecting the overall time in completing the test route. Drivers had reduced number of severe braking and decreased average in-curve distance traveled over the safety speed limits, when the CSWS was in use. Drivers also rated the CSWS as assisting, effective and useful. In summary, the CSWS can enhance firetruck safety during emergency driving without sacrificing drivers' precious response time.

In Vivo Anti-diarrheal Activity of Methanolic Extract of Streblus asper Leaves Stimulating the Na+/K+-ATPase in Swiss Albino Rats.

Streblus asper Lour., traditionally used for anti-diarrheal effects as like dysentery and diarrhea. The present study aims to prove the anti-diarrheal activities of methanolic extract of leaves of S. asper in animal models. The anti-diarrheal activity was evaluated using castor oil-induced diarrhea and magnesium sulphate-induced diarrhea models whereas anti-motility activities were investigated using gastrointestinal transit test examined in animal models. In castor oil-induced diarrhea model, methanolic extract of S. asper (MESA) at the doses of 100, 200, and 400 mg/kg produced statistically significant (P < 0.001) decreased the number of diarrheal feces of rats against castor oil-induced diarrhea as well as magnesium sulphate-induced diarrhea model also showed the same manner. In gastrointestinal transit test, delayed gastric emptying time decreased significantly (P < 0.001), the propulsion of charcoal meal in the gastrointestinal tract which also showed a dose-dependent manner in rats. The recent study indicates that MESA possesses anti-diarrheal property. The findings represent a rational explanation for its use in traditional medicine for the management of diarrhea management.

New insights into the spatial distribution of particle number concentrations by applying non-parametric land use regression modelling.

Ambient particle number concentration (PNC) varies significantly in time and space within cities, yet complexity and cost prohibit large-scale routine monitoring; as a consequence, there is not enough data for assessment of human exposure to, or risk from the particles. The quality of assessments can be augmented by modelling; however, models are generally less capable of predicting PNC spatial variation than predicting variations in other ambient pollutants. To advance modelling of PNC, we aimed to develop and compare the performance of parametric and non-parametric machine learning land-use regression (LUR) models to predict hourly average PNC. We used data from 25 short-term stationary campaigns and five long-term sites during 2009-2012 in the Brisbane Metropolitan Area, Australia. We analysed three particle size ranges of total PNC (<30 nm, <414 nm and <3000 nm) as response variables, and over 150 independent variables, including land use, roads and traffic, population, distance, elevation, meteorology and time of day as potential predictors of PNC. The LUR models were developed separately for All Days, Nuc Days (when particle nucleation occurred), and No-nuc Days (when no particle nucleation occurred). We selected two algorithms to develop LUR models for PNC: a random forest (RF) model, and a generalised additive model (GAM) based on the least angle regression (LARS). The best LARS model for <30 nm, <414 nm and <3000 nm explained 30%, 31%, and 34%, respectively, whereas the best RF models were significantly better, explaining 73%, 64%, and 88%, respectively. Using this novel approach, we provided new insights into spatial variation in PNC and also demonstrated that the non-parametric RF model is a better choice for developing a LUR model for PNCs because of its robust predictive performance in comparison with the LARS parametric regression model.

Carbon multicharged ion generation from laser-spark ion source.

Multicharged carbon ions are generated by using a laser-assisted spark-discharge ion source. A Q-switched Nd:YAG laser pulse (1064 nm, 7 ns, ≤ 4.5 × 109 W/cm2) focused onto the surface of a glassy carbon target results in its ablation. The spark-discharge (∼1.2 J energy, ∼1 µs duration) is initiated along the direction of the plume propagation between the target surface and a grounded mesh that is parallel to the target surface. Ions emitted from the laser-spark plasma are detected by their time-of-flight using a Faraday cup. The ion energy-to-charge ratio is analyzed by a three-mesh retarding field analyzer. In one set of experiments, the laser plasma is generated by target ablation using a 50 mJ laser pulse. In another set of experiments, ∼1.2 J spark-discharge energy is coupled to the expanding plasma to increase the plasma density and temperature that results in the generation of carbon multicharged ions up to C6+. A delay-generator is used to control the time delay between the laser pulse and the thyratron trigger. Ion generation from a laser pulse when a high DC voltage is applied to the target is compared to that when a spark-discharge with an equivalent pulsed voltage is applied to the target. The laser-coupled spark-discharge (7 kV peak voltage, 810 A peak current) increases the maximum detected ion charge state from C4+ to C6+, accompanied by an increase in the ion yield by a factor of ∼6 compared to applying 7.0 kV DC voltage to the target.