Local Industrialization Based Lucrative Farming Using Machine Learning Technique

In recent times, agriculture have gained lot of attention of researchers. More precisely, crop prediction is trending topic for research as it leads agri-business to success or failure. Crop prediction totally rest on climatic and chemical changes. In the past which crop to promote was elected by rancher. All the decisions related to its cultivation, fertilizing, harvesting and farm maintenance was taken by rancher himself with his experience. But as we can see because of constant fluctuations in atmospheric conditions coming to any conclusion have become very tough. Picking correct crop to grow at right times under right circumstances can help rancher to make more business. To achieve what we cannot do manually we have started building machine learning models for it nowadays. To predict the crop deciding which parameters to consider and whose impact will be more on final decision is also equally important. For this we use feature selection models. This will alter the underdone data into more precise one. Though there have been various techniques to resolve this problem better performance is still desirable. In this research we have provided more precise & optimum solution for crop prediction keeping Satara, Sangli, Kolhapur region of Maharashtra. Along with crop & composts to increase harvest we are offering industrialization around so rancher can trade the yield & earn more profit. The proposed solution is using machine learning algorithms like KNN, Random Forest, Naïve Bayes where Random Forest outperforms others so we are using it to build our final framework to predict crop

MUCOADHESIVE MICROSPHERES: AN EMINENT ROLE IN CONTROLLED DRUG DELIVERY

ABSTRACT Mucoadhesion is simply known as interfacial force interactions between polymeric materials and mucosal tissues. In the last two decades mucoadhesive microspheres have received considerable attention for design of novel drug delivery systems due to their ability to prolong the residence time of dosage forms and to enhance drug bioavailability. Mucoadhesive microspheres have advantages like efficient absorption and enhanced bioavailability of the drugs due to a high surface to volume ratio, a much more intimate contact with the mucus layer, controlled and sustained release of drug from dosage form and specific targeting of drugs to the absorption site. Microspheres are the carrier linked drug delivery system in which particle size is ranges from 1-1000 μm range in diameter having a core of drug and entirely outer layers of polymer as coating material. Keywords: mucoadhesion, microspheres, controlled release, residence time. INTRODUCTION Since many years several kinds of diseases that may be acute or chronic diseases can be treated by using pharmaceutical dosage form like solutions, tablets, capsules, syrups, suspension, emulsion, ointments, creams, gels which can be used as orally, topically, or intravascular route. To get the proper therapeutic effect of these pharmaceutical dosage forms they should be administered several times a day, this results consequently undesirable toxicity, fluctuation in drug level and poor efficiency or therapeutic effect. Controlled release dosage form plays eminent role to overcome the problems which are discussed above. The most important example of controlled drug delivery system is mucoadhesive microspheres which can improve the therapeutic effect of administered drug. Also bioavailability of drug is also better than other conventional system because mucoadhesive microspheres remain close to the mucous membrane and absorption tissue. Drug delivery systems (DDS) that can precisely control the release rates or target drugs to a specific body site have had an enormous impact on the healthcare system. The last two and developing novel delivery systems referred to as "mucoadhesive microspheres". [1] Physiology of mucin Mucus is produced in the eye, ear, nose and mouth. It also lines the respiratory, gastrointestinal and reproductive tracts. Its primary functions are the protection and lubrication of the underlying epithelium. Human cervical mucus, for instance, plays an integral role in both conception and contraception. It is essential to understand the structure and physical chemistry of mucus if the latter is to be exploited as a site for bioadhesive controlled drug release. Since the gastrointestinal tract is the primary site for drug absorption, the physiology of this site will be the focus of this discussion. The gelling properties which are essential to the function of mucus are the direct result of the glycoprotein present in the mucosal secretion. This glycoprotein is generally the same for various secretion sites within the body; however, specific and subtle biochemical differences have been identified. Mucus may be either constantly or intermittently secreted. The amount of mucus secreted also varies. The glycoproteinic component of mucus is a high molecular weight, highly glycosylated macromolecular system. This polydisperse natural polymer makes up between 0.5 and 5% of the fully hydrated mucus secretion. [10] The size of the intact molecule is approximately 1.8 x 10 6 , but the molecular weight of undegraded gastric mucin is as high as 4.5 x 10 7 . These macromolecules are highly expanded random coils made up of monomeric glycoproteins which for humans range from 5.5 x 1o 5 in the stomach to 2.4 x lo 5 in the small intestine. Oligosaccharide branches are attached to 63% of the protein core while the remainder of There are 34 disulphide bridges per molecule of rat goblet cell mucin, which has a molecular weight of 2 x 10 6 , while porcine intestinal mucin has 28 bridges per molecule. Human mucin has a similar density of disulphide bonds. The protein spine of the macromolecule has about 800 amino acid residues. Sugar chains are attached at about every three residues along the glycosylated regions; this results in approximately 200 side chains per molecule. This molecule is resistant to proteolytic attack in the glycosylated regions only. Thus, charge interactions may have a significant effect on the behaviour of mucus glycoproteins. The mucous gel covering the epithelium varies in thickness. In the human stomach, the mean thickness is 192 pm, while in the duodenum the thickness ranges from 10 to 400 pm In the gastrointestinal tract, mucus facilitates the passage of food and boluses through the alimentary canal. It also helps shield the epithelium from shear forces induced by peristaltic waves, and resists auto digestion. These functions are promoted by the constant secretion of mucus to replenish losses from turbulence and degradation. In response to an irritant, the amount of acidic side chains in the glycoprotein increases from 50 to 80%, making the macromolecule more negatively charged. The submucosal gland layer increases in depth and the number of goblet cells increases. The total content of non dialysable solids and pH also increase. In the GI tract, DNA and albumin thicken mucus in the diseased state. Mucosal irritation, such as exposure to alcohol or bile salts, elicits accelerated mucin release. Disease can significantly alter the nature and thickness of the mucus. This may lead to a change in the behaviour of the delivery system. Any drug delivery system which is intended to adhere to the mucus epithelium will need to adapt to a substrate which varies in depth and consistency, and may also change biochemically. Hypersecretion, which is more common than hyposecretion during disease, increases the transit rate through the GI tract, and thus reduces the residence time of a mucoadhesive device. Thus, it is essential to consider the physiology of the system when optimizing the formulation of an adhesive controlled release device. CLASSIFICATION OF MUCOADHESIVE POLYMERS Mucoadhesion is defined as interfacial force interactions between polymeric materials and mucosal tissues. In the last two decades mucoadhesive polymers have received considerable attention for design of novel drug delivery systems due to their ability to prolong the residence time of dosage forms and to enhance drug bioavailability. Various administration routes, such as ocular, nasal, gastrointestinal, vaginal and rectal, make mucoadhesive drug delivery systems attractive and flexible in dosage forms development. Mucoadhesive polymers can be classified as,- I. Traditional non-specific first-generation mucoadhesive polymers First-generation mucoadhesive polymers may be divided into three main subsets, namely: (1) Anionic polymers:-Anionic polymers are widely employed for its greatest mucoadhesive strength and low toxicity. These polymers are characterised by the presence of sulphate and carboxyl group that gives rise to net negative charge at PH values exceeding the pka of polymer. Example:-polyacrylic acid (PAA) & its weakly cross linked derivatives, Sodium carboxymethyl cellulose (NACMC) [30] (2) Cationic polymers: -The most conveniently and widely used cationic polymer is chitosan which is produced by deacetylation of chitin. Chitin is a natural polysaccharide found predominantly in the shells of crustaceans such as crabs and shrimp, the cuticles of insects, and the cell walls of fungi. It is one of the most abundant biopolymers next to cellulose Most of the naturally occurring polysaccharides, e.g. cellulose, dextran, pectin, alginic acid, agar, agarose and carrageenans, are neutral or acidic in nature, whereas chitin and chitosan are examples of highly basic polysaccharides. The unique properties include II.Novel second-generation mucoadhesive polymers: The major disadvantage in using traditional nonspecific mucoadhesive systems (first generation) is that adhesion may occur at sites other than those intended. Unlike first-generation non-specific platforms, certain second-generation polymer platforms are less susceptible to mucus turnover rates, with some species binding directly to mucosal surfaces; more accurately termed ''cytoadhesives". Furthermore as surface carbohydrate and protein composition at potential target sites vary regionally, more accurate drug delivery may be achievable. MUCOADHESION Due its relative complexity, it is likely that the process of mucoadhesion cannot be described by just one of these theories. In considering the mechanism of mucoadhesion, a whole range 'scenarios' for in-vivo mucoadhesive bond formation are possible. These include: A). Dry or partially hydrated dosage forms contacting surfaces with substantial mucus layers (typically particulates administered into the nasal cavity). B). fully hydrated dosage forms contacting surfaces with substantial mucus layers (typically particulates of many 'First Generation'mucoadhesives that have hydrated in the luminal contents on delivery to the lower gastrointestinal tract). C). Dry or partially hydrated dosage forms contacting surfaces with thin/discontinuous mucus layers (typically tablets or patches in the oral cavity or vagina). D). fully hydrated dosage forms contacting surfaces with thin/discontinuous mucus layers (typically aqueous semisolids or liquids administered into the oesophagus or eye). It is unlikely that the mucoadhesive process will be the same in each case. In the study of adhesion generally, two steps in the adhesive process have been identified Step 2 -Consolidation stage: Various physicochemical interactions occur to consolidate and strengthen the adhesive joint, leading to prolonged adhesion. THEORIES ON MUCOADHESION [4, 5] Various kinds of theories are there which can explain the mechanism of mucoadhesion they are discussed below, TYPES OF MICROSPHERES Mucoadhesive microspheres:-Adhesion can be defined as sticking of drug to the membrane by using the sticking property of the water soluble polymers. Adhesion of drug delivery device to the mucosal membrane such as buccal, ocular, rectal, nasal etc can be termed as bio -adhesion. These kinds of microspheres exhibit a prolonged residence time at the site of application and causes intimate contact with the absorption site and produces better therapeutic action. [26] Magnetic microspheres:-This kind of delivery system is very much important which localises the drug to the disease site. In this larger amount of freely circulating drug can be replaced by smaller amount of magnetically targeted drug. Magnetic carriers receive magnetic responses to a magnetic field from incorporated materials that are used for magnetic microspheres are chitosan, dextran etc. The different type are, Therapeutic magnetic microspheres: Are used to deliver chemotherapeutic agent to liver tumour. Drugs like proteins and peptides can also be targeted through this system.6 Diagnostic microspheres: Can be used for imaging liver metastases and also can be used to distinguish bowel loops from other abdominal structures by forming nano size particles supramagnetic iron oxides. Floating microspheres:-In this type of microspheres the bulk density is less than the gastric fluid and so remains buoyant in stomach without affecting gastric emptying rate. The release rate of drug is slow at the desired rate, if the system is floating on gasteric content and increases gastric residence and increases fluctuation in plasma concentration

Systematic In Vivo Analysis of the Intrinsic Determinants of Amyloid β Pathogenicity

Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Aβ42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Aβ42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Aβ and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism

Finite Size Effects in Simulations of Protein Aggregation

It is becoming increasingly clear that the soluble protofibrillar species that proceed amyloid fibril formation are associated with a range of neurodegenerative disorders such as Alzheimer's and Parkinson diseases. Computer simulations of the processes that lead to the formation of these oligomeric species are starting to make significant contributions to our understanding of the determinants of protein aggregation. We simulate different systems at constant concentration but with a different number of peptides and we study the how the finite number of proteins affects the underlying free energy of the system and therefore the relative stability of the species involved in the process. If not taken into account, this finite size effect can undermine the validity of theoretical predictions regarding the relative stability of the species involved and the rates of conversion from one to the other. We discuss the reasons that give rise to this finite size effect form both a probabilistic and energy fluctuations point of view and also how this problem can be dealt by a finite size scaling analysis

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Performance Of Lfac System For Steady State

HVAC power transmission using submarine power cables has limitation of charging current at nominal frequency. Therefore, HVDC power transmission technology has been established. However, a new intermediate technology of Low Frequency AC Transmission is established for transmission of power. This paper deals with the performance of a low-frequency ac (20Hz) transmission system for steady state. The LFAC system is interconnected with the 50Hz grid with a cycloconverter. The wind power from the offshore is in the form of dc, and is interconnected to the LFAC transmission line with a twelve-pulse thyristor inverter. The waveforms at the sending end and receiving end of the transmission line are plotted. The circuit model of LFAC system is simulated in MATLAB/SIMULINK

Design And Development Of Tumbling Machine

Every good manufactured in an industry is passing through different processes. Finally a product is salable in market if finishing carried out over the product is effective. For small products it is very difficult to provide finishing with human and hence a machine is necessary to smooth finish a product. Finishing not only provides better look to the product but it also processes the product through removal of rust and polishing of product. Authors have designed and developed the tumbling machine for finishing of the small products in mechanical manufacturing companies. The detail calculations of design and model developed in CAD is presented in this paper