► We reviewed the published correlations for estimating higher heating value of biomass. ► A new approach of linear correlations is proposed. ► A linear and a non-linear correlation are developed and ...validated.
Heating value of biomass is necessary to analyze and design any bio-energy systems. The experimental methods to estimate the heating value are time consuming as well as expensive and have higher possibilities of experimental errors. Many correlations have been published for estimating higher heating values of biomass, coal, and other solid fuels based on proximate analysis. In this paper, a new approach of linear correlations is proposed, developed, and analyzed for its forecasting errors. Two hundred and fifty published data with the higher heating values ranging from 5.63 to 23.46MJ/kg are used to develop the correlations. The best correlation, which has least errors, is selected and subjected to develop non-linear correlations to decrease its estimation errors. The selected linear and non-linear correlations are validated by using experimentally determined higher heating values of biomass. The correlations are also compared with other published correlations.
Depression is a psychiatric problem which affects the growth of a person, like how a person thinks, feels and behaves. The major reason behind wrong diagnosis of depression is absence of any ...laboratory test for detection as well as severity scaling of depression. Any degradation in the working of the brain can be identified through change in the electroencephalogram (EEG) signal. Thus detection as well as severity scaling of depression is done in this study using EEG signal. In this study, features are extracted from the temporal region of the brain using six (FT7, FT8, T7, T8, TP7, TP8) channels. The linear features used are delta, theta, alpha, beta, gamma1 and gamma2 band power and their corresponding asymmetry as well as paired asymmetry. The non-linear features used are Sample Entropy (SampEn) and Detrended Fluctuation Analysis (DFA). The classifiers used are: Bagging along with three different kernel functions (Polynomial, Gaussian and Sigmoidal) of Support Vector Machine (SVM). Feature selection technique used is ReliefF. Highest classification accuracy of 96.02% and 79.19% was achieved for detection and severity scaling of depression using SVM (Gaussian Kernel Function) and ReliefF as feature selection. From the analysis, it was found that depression affects the temporal region of the brain (temporo-parietal region).It was also found that depression affects the higher frequency band features more and it affects each hemisphere differently. It can also be analysed that out of all the kernel of SVM, Gaussian kernel is more efficient to other kernels. Of all the features, combination of all paired asymmetry and asymmetry showed high classification accuracy (accuracy of 90.26% for detection of depression and accuracy of 75.31% for severity scaling).
Considering the Navier Stokes equations paired with the heat equation for ferrohydrodynamic flow of magnetic nanofluid amidst two rotating porous disks, nothing is known on the significance of ...geothermal viscosity for the magnetic fluid flow between co-rotating porous surfaces. The current analysis considers the effects of changing viscosity and thermal radiation. Additionally, the stretching and angular velocities of the two disks differ. The flow model's estimated basic equations are transformed into nondimensional ordinary differential equations (ODEs) with the proper transformation before being numerically solved using Maple's built-in BVP Midrich approach. For velocity and temperature fields, the effects of active flow parameters such as the depth-dependent viscosity variation parameter, ferro-hydrodynamics interaction parameter, Reynolds number, Prandtl number, Darcy number, Eckert number, and radiation parameter are discussed. It is worth noticing that the temperature field tends to decline as the Darcy parameter is higher estimated. It is worth concluding that there exists a high fluctuating viscosity around the lower disk, the magnitude of horizontal velocity decreased, but vertical velocity increased everywhere else. Furthermore, skin friction becomes more valuable at higher Reynolds numbers and porosity estimates.
Torrefaction, a mild roasting process in inert atmosphere, is an emerging thermo-chemical pretreatment process that can eliminate many of the shortcomings of raw biomass, but the supply of an inert ...gas like nitrogen in large industrial units may not be cost-effective. This paper examines the use of air as a potential substitute for the expensive nitrogen gas through a simple innovative means. It proposes to use a mildly pressurized batch reactor instead of an open continuous reactor continuously fed by nitrogen. Torrefaction of poplar wood was conducted in a 25.4 mm diameter × 304.8 mm long batch reactor under different operating parameters (Gauge Pressures, 0, 200, 400, and 600 kPa, temperatures, 220, 260, and 300 °C, and residence times, 15, 25, and 35 min) in air and nitrogen. Results show that torrefaction in pressurized air has higher energy density, higher fuel ratio, and similar energy yield but reduced mass yield compared to those in pressurized nitrogen. While reactor pressure was increased from 200 to 600 kPa, fuel ratio, energy density enhancement factor, fixed carbon increased but mass yield decreased in both air and nitrogen medium. Data obtained further showed that torrefaction temperature is the most important operating parameter influencing the process. Using Response Surface Methodology, this work also developed correlations to predict mass loss for given values of temperature, pressure, and time in air and nitrogen media. Correlations to estimate torrefied product properties like energy density enhancement and fuel ratio for known mass loss during torrefaction were then established. This also offers a quantitative characterization of different modes of torrefaction that could be used for design selection.
Many correlations are available in the literature to predict the higher heating value (HHV) of raw biomass using the proximate and ultimate analyses. Studies on biomass torrefaction are growing ...tremendously, which suggest that the fuel characteristics, such as HHV, proximate analysis and ultimate analysis, have changed significantly after torrefaction. Such changes may cause high estimation errors if the existing HHV correlations were to be used in predicting the HHV of torrefied biomass. No study has been carried out so far to verify this. Therefore, this study seeks answers to the question: "Can the existing correlations be used to determine the HHV of the torrefied biomass"? To answer this, the existing HHV predicting correlations were tested using torrefied biomass data points. Estimation errors were found to be significantly high for the existing HHV correlations, and thus, they are not suitable for predicting the HHV of the torrefied biomass. New correlations were then developed using data points of torrefied biomass. The ranges of reported data for HHV, volatile matter (VM), fixed carbon (FC), ash (ASH), carbon (C), hydrogen (H) and oxygen (O) contents were 14.90 MJ/kg-33.30 MJ/kg, 13.30%-88.57%, 11.25%-82.74%, 0.08%-47.62%, 35.08%-86.28%, 0.53%-7.46% and 4.31%-44.70%, respectively. Correlations with the minimum mean absolute errors and having all components of proximate and ultimate analyses were selected for future use. The selected new correlations have a good accuracy of prediction when they are validated using another set of data (26 samples). Thus, these new and more accurate correlations can be useful in modeling different thermochemical processes, including combustion, pyrolysis and gasification processes of torrefied biomass.
Background:
Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was ...implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015–2016.
Aim:
To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India.
Methods:
NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees.
Results:
The weighted lifetime prevalence of ‘any mental morbidity’ was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10–F19; 22.44%), mood disorders (F30–F39; 5.61%) and neurotic and stress-related disorders (F40–F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%.
Conclusion:
NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.
Background:
The social, economic, and physical environments are widely recognized as important determinants of health and affect the outcome of service delivery. The differences in the patient ...outcomes can be inferred upon by looking into the process and content of service delivery.
Methods:
This study is a mixed-methods, prospective cohort study to be conducted at two community extension clinics run by the Central Institute of Psychiatry, Ranchi, Jharkhand. Service users diagnosed with a common mental disorder (CMDs) will be recruited during the study period of three years. The main objective is to ascertain the unmet needs of patients with CMDs. The secondary goals involve measuring the clinical outcome through the lens of process-oriented recovery, service satisfaction, and accessibility, and analyzing the barriers to access healthcare services along with the impact on the carers. Focus group discussions with participants will help understand the reasons behind their unmet needs and factors essential in service delivery.
Discussion:
Healthcare, as well as social care, aims to deliver services according to need. In a country with 15 million people with CMDs, evaluation of needs could create a platform for the rational distribution of services.
Background: Obsessive compulsive disorder (OCD) is a clinically heterogeneous psychiatric disorder in terms of symptom content and insight. Aim: To study the various factors associated with insight ...in OCD. Materials and Methods: A cross-sectional hospital-based study was conducted among 40 patients with OCD who were evaluated on Yale-Brown Obsessive-Compulsive Scale, Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, Brown Assessment of Beliefs Scale, Meta-Cognitions Questionnaire, WHOQOL-BREF, and Sheehan Disability Scale. Statistical analysis was done using SPSS version 22. Results: Metacognition, severity of OCD, and associated disability were the significant predictors for insight in patients with OCD. Conclusion: Factors associated with insight in OCD can enhance our understanding in the management of OCD.
Globally, there is a growing concern over pesticides use, which has been linked to self-harm and suicide. However, there is paucity of research on the epidemiology of pesticides poisoning in Nepal. ...This study is aimed at assessing epidemiological features of pesticides poisoning among hospital-admitted cases in selected hospitals of Chitwan District of Nepal.
A hospital-based quantitative study was carried out in four major hospitals of Chitwan District. Information on all pesticides poisoning cases between April 1 and December 31, 2015, was recorded by using a Pesticides Exposure Record (PER) form.
A total of 439 acute pesticides poisoning cases from 12 districts including Chitwan and adjoining districts attended the hospitals during the 9-month-long study period. A majority of the poisoned subjects deliberately used pesticides (89.5%) for attempted suicide. The total incidence rate was 62.67/100000 population per year. Higher annual incidence rates were found among young adults (111.66/100000 population), women (77.53/100000 population) and individuals from Dalit ethnic groups (98.22/100000 population). Pesticides responsible for poisoning were mostly insecticides (58.0%) and rodenticides (20.8%). The most used chemicals were organophosphates (37.3%) and pyrethroids (36.7%). Of the total cases, 98.6% were hospitalized, with intensive care required for 41.3%. The case fatality rate among admitted cases was 3.8%.
This study has indicated that young adults, females and socially disadvantaged ethnic groups are at a higher risk of pesticides poisoning. Pesticides are mostly misused intentionally as an easy means for committing suicide. It is recommended that the supply of pesticides be properly regulated to prevent easy accessibility and misuse. A population-based study is warranted to reveal the actual problem of pesticides exposure and intoxication in the community.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•A significant reduction in HF and all-cause hospitalizations was found.•No effect on HF and all-cause mortality was found.•The overall trend was an improvement in medication adherence.•A significant ...improvement in HF knowledge was found.
There is evidence that heart failure (HF) patients who receive pharmacist care have better clinical outcomes.
English-language peer-reviewed randomized controlled trials comparing the pharmacist-involved multidisciplinary intervention with usual care were included. We searched PubMed, MEDLINE, EMBASE, CINAHL, Web of Science, Scopus, and the Cochrane Library from inception through March 2017. Cochrane method for risk of bias was used to assess within and between studies. 18 RCTs (n = 4630) were included for systematic review, and 16 (n = 4447) for meta-analysis. Meta-analysis showed a significant reduction in HF hospitalizations {odds ratio (OR) 0.72 95% confidence interval (CI) 0.55-0.93, P = .01, I2 = 39%} but no effect on HF mortality. Similarly, a significant reduction in all-cause hospitalizations OR 0.76, 95% CI (0.60-0.96), P = .02, I2 = 52% but no effect on all-cause mortality was revealed. The overall trend was an improvement in medication adherence. There were significant improvements in HF knowledge (P<.05), but no significant improvements were found on health care costs and self-care.
The pharmacist is a vital member of a multidisciplinary team in HF management to improve clinical outcomes. There was a great deal of variability about which specific intervention is most effective in improving clinical outcomes.
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