World Millions Research Articles

Screening of Bacteria Isolated from Arctic Atmospheric Aerosols for Oil Degradation Ability

Currently, a significant part of the world's soil cover is exposed to negative pollution, leading to its degradation. Oil hydrocarbons play a significant role among numerous soil pollutants. Sources of pollution are enterprises of oil extraction, oil refining, oil and oil products transportation. Every year in the world millions of tons of oil and oil products are lost during extraction, transportation, storage and use. Biological remediation based on the potential of microorganisms to transform pollutants of different origin is the most promising and environmentally safe method of restoring soil fertility, so the search for new strains to create and improve such biological preparations is still relevant. Atmospheric aerosols are a source of both transient and endogenous microbiota, which are metabolically active in relation to pollutants. During a complex airborne expedition on atmospheric sounding over the Arctic Ocean seas samples of aerosols were collected for microbiological analysis. The isolated cultures of microorganisms belonging to the genera Bacillus, Acinetobacter, Rhodococcus were tested for the ability to oil destruction when growing on agarized and liquid medium with the addition of oil to 2% as the only source of carbon and incubation for 10 days. The bioemulsifying and biodegrading abilities of microorganisms during growth in liquid medium were estimated visually by destruction of the surface film of oil, turbidity of the nutrient medium due to an increase in the biomass of microorganisms, formation of a uniform emulsion of oil in the medium, microscopy of cultural suspensions, and by their seeding on agarized nutrient medium to determine the titer of viable cells. Highly effective mesophilic and psychrotolerant oil destructor bacteria were isolated from northern atmospheric aerosols, which can be used to create complex biopreparations capable of assimilating a wider range of oil hydrocarbons for remediation of polluted soils and grounds in cold territories of Siberia and the Arctic.

Post-covid syndrome: psychoneurological disorders in focus

The outbreak of the novel coronavirus infection pandemic has spread all over the world millions of people have been recovered from it that makes necessary the research of their health status after the acute infection phase. The accumulated data about previous coronavirus epidemics showed their prolonged impacton the nervous system with the manifestation of mental and neurological symptoms. Specialists from different countries from the beginning of the pandemic have revealed typical symptoms in patients recovered from coronavirus infection with negative tests still complained on residual respiratory, gastroenterological and psychoneurological symptoms that manifested with asthenic, cognitive, dissomnic and affective disorders, anosmia and changes in taste preferences. No correlation between infection severity and symptoms set in the reconvalescence period has been found. Different countries have been used different terms to describe it like prolonged, long, chronic covid.The leading medical centers have made their impact in this problem analysis During the two recent years a big international research base, including the data from electronic medical histories has been accumulated concerning COVID 19 reconvalescents health status. WHO has presented the postcovid 19 syndrome work definition, in its structure psychoneurological symptoms such as asthenia, anxietydepressive and cognitive disorders, insomnia play an important role. The healthcare provision for the patients with postcovid syndrome remains the issue needed further elaboration , the most promising treatment plan seems the combination of pharmacotherapy with psychosocial interventions. Tofizopam as a drug with anxiolytic, secondary precognitive and aniastenic effects can be recommended for the postocovid syndrome psychoneurological symptoms.

“Costs, Returns of Sorghum in Bhind District of Madhya Pradesh”

Sorghum (Sorghum Bicolor L. Moench) is one of the four major food grains of the world millions of people in Africa and Asia depend on sorghum as the staple food. Bhind district of Madhya Pradesh was selected purposively Mehgaon block was selected purposively to fulfil the objectives of the present study. 20 respondents were selected by simple random sampling method. Thus total 60 respondents were considered for detail investigation. Survey method was used for collection of the relevant data from selected respondents. Sorghum crop was higher production as compare to Pearl-millet crop. It can be concluded that Sorghum crop was higher profitable as compare to Pearl-millet crops. Farm business income and family labour income were higher in Sorghum followed by Pearl-millet crops. Cost of production per quintal was observed that higher in Sorghum followed by Pearl-millet crops respectively.Input output ratio was also found higher in case of Sorghum crop at cost C3 level followed by Pearl-millet crops per hectare in the study area.

EpistoNet: an ensemble of Epistocracy-optimized mixture of experts for detecting COVID-19 on chest X-ray images

The Coronavirus has spread across the world and infected millions of people, causing devastating damage to the public health and global economies. To mitigate the impact of the coronavirus a reliable, fast, and accurate diagnostic system should be promptly implemented. In this study, we propose EpistoNet, a decision tree-based ensemble model using two mixtures of discriminative experts to classify COVID-19 lung infection from chest X-ray images. To optimize the architecture and hyper-parameters of the designed neural networks, we employed Epistocracy algorithm, a recently proposed hyper-heuristic evolutionary method. Using 2500 chest X-ray images consisting of 1250 COVID-19 and 1250 non-COVID-19 cases, we left out 500 images for testing and partitioned the remaining 2000 images into 5 different clusters using K-means clustering algorithm. We trained multiple deep convolutional neural networks on each cluster to help build a mixture of strong discriminative experts from the top-performing models supervised by a gating network. The final ensemble model obtained 95% accuracy on COVID-19 images and 93% accuracy on non-COVID-19. The experimental results show that EpistoNet can accurately, and reliably be used to detect COVID-19 infection in the chest X-ray images, and Epistocracy algorithm can be effectively used to optimize the hyper-parameters of the proposed models.

Modeling global transfusion medicine education.

Modeling global transfusion medicine education.

DEPRESSION, ANXIETY, STRESS AND BEHAVIORAL RESPONSE RELATED TO COVID-19 PANDEMIC AMONG GENERAL POPULATION

Background: Since the December 2019, a novel corona virus disease (COVID-19) first identi­fied in China, spreading around the world and infected millions of people. This pandemic has severely affected the socio-economic and mental health status of people due to lockdown and great uncertainty of elimination of the virus. This study aim to identify the depression, anxiety, stress and behavioral response related to COVID-19 pandemic among general popu­lation of Kathmandu Valley. Methods: A descriptive cross sectional study carried out using convenient sampling duringCO­VID-19 Pandemic. Data was collected by using structured standard DASS 21 scale. The SPSS version 22 was used to analyze data. Results: There were total 411 general people participated, among them 25.3%, 22.9%, and 11.9% had mild to extreme severe level of depression, anxiety and stress respectively were prevalent. There is a statistical significant association between marital status, educational level and level of depression at 95% confidence level (p value< 0.05). Majority of respondents had change their behavior as maintaining hand hygiene, wore a mask and had limited physical contact with people. There is a statistical significant between age, gender and level of education with recently avoiding smoking and drinking related behavior. Conclusions: This study concludes that the general population had depression, anxiety and stress because of the fear of getting infection; people were more likely change their behavior to prevent the risk of infection. This study suggests addressing the need of mental health services such as counseling, hotline services and desk by the stakeholders to promote mental wellbeing of people.

Biopsychosocial Facets of Women Undergoing Infertility Treatment in Pondicherry: A Preliminary Study

Background: Physical and mental health are interrelated and influenced by various factors. Infertility is a physical condition that impacts the mental health of individuals experiencing it. It is a well-established fact that all over the world millions of couples are affected by infertility. In India many couples are infertile. Discovering that one is infertile is more than just another stressful event in one’s life. Being confronted by failure and helplessness, one feels increasingly anxious and immobilized. Aim: To understand the psychosocial problems faced by women due to infertility. Methodology: A Descriptive research design was adopted for the study. Women attending the clinic for treatment of infertility were the respondents. A semi-structured interview schedule was used to obtain the data. Results: Majority of the educated women married at a young age and sought treatment within five years of the marriage. They had menstrual problems and were referred by their families for treatment. Most of them had identified the problems and were into treatment. They were anxious, yet hopeful of success. They experienced problems of stigmatization in their own families and society and desired acceptance. Conclusion: This study highlighted the situation of couples facing infertility and the need for awareness of the condition of infertility. Support for couples by the multidisciplinary team inclusive of the Social Worker through the process of diagnosis and treatment, to maintain their health and mental health as they overcome the challenge of infertility is the need of the hour.
 Keywords: Infertility, psychosocial problems, stigma

A Machine Learning-Based Intelligent System for Predicting Diabetes

In this era of technological growth, the diagnosis of diseases and finding cures, personal health parameter management and predicting the possibility of susceptibility to some diseases have become accessible and easy. Although all over the world millions of people are falling victim to diabetes, in most of the cases they are not even aware of their situation due to the silent nature of diabetes. Therefore, the objective of this research is to propose an intelligent system based on a machine learning algorithm to improve the accuracy of predicting diabetes. To attain this objective, an algorithm was proposed based on Naïve Bayes with prior clustering. Second, the performance of the proposed algorithm was evaluated using 532 data related to diabetic patients. Finally, the performance of the existing Naïve Bayes algorithm was compared with the proposed algorithm. The results of the comparative study showed that the improvement in the accuracy has been made apparent for the proposed algorithm.

Emek Göçü ve Uluslararası Çalışma Standartları: Emek Piyasası Açısından Bir Değerlendirme

Migration is a complex process and has many dimensions to deal with, such as governance, the protection of migrant workers, development linkages and international cooperation. Labour migration is also related to wage differentials, the relative ease or difficulty of relocating to another country and the absence of support networks. In the world millions of workers (labour) are travelling within and outside their countries in order to get jobs, better opportunities of employment and life. According to the ILO statistics its estimated that 232 million workers are international migrants in 2015. It’s been foreseen by ILO that globalization, demographic shifts, conflicts and climate change will be increasing the number of workers who will be seeking employment and security outside their countries. The economic globalization has increased that number especially in the developing countries in where there is a huge problem of unemployment and poverty.

Predictive modelling and analytics for diabetes using a machine learning approach

Diabetes is a major metabolic disorder which can affect entire body system adversely. Undiagnosed diabetes can increase the risk of cardiac stroke, diabetic nephropathy and other disorders. All over the world millions of people are affected by this disease. Early detection of diabetes is very important to maintain a healthy life. This disease is a reason of global concern as the cases of diabetes are rising rapidly. Machine learning (ML) is a computational method for automatic learning from experience and improves the performance to make more accurate predictions. In the current research we have utilized machine learning technique in Pima Indian diabetes dataset to develop trends and detect patterns with risk factors using R data manipulation tool. To classify the patients into diabetic and non-diabetic we have developed and analyzed five different predictive models using R data manipulation tool. For this purpose we used supervised machine learning algorithms namely linear kernel support vector machine (SVM-linear), radial basis function (RBF) kernel support vector machine, k-nearest neighbour (k-NN), artificial neural network (ANN) and multifactor dimensionality reduction (MDR).

Malnutrition Incidence and Determination of Effecting Factors at 1-4 Years Old Children in Konya

Background and Aim: Every year in the world millions of children die from malnutrition and infectious diseases. Children under the age of five are affected more quickly than other age groups from negative conditions. This study is aimed to determine the risk factors of malnutrition and incidence of malnutrition in children aged 1-4 years living in Konya. Materials and Methods: This is a cross-sectional epidemiological study. The survey about demographical information about the child and their family, child's nutrition and anthropometric measurements described by both Z-scoring and GOMEZ classification, was conducted between May-December,2016 with 1000 children aged 1-4 years in Konya province. Descriptive statistics, chi-square test, student t-test and multivariate logistic regression were performed by SPSS 18.0 considering p<0.05 as statistically significant. Results: According to the GOMEZ classification, 18.7% of children living in Konya are malnourished. According to Z-score, 3.5% (n=35) of the children were found to be underweight and 7.2% (n=72) were found as stunted. Factors affecting the malnutrition were the age range of children, the working status of the mother, the kinship status between the parents, the number of living children, maternal age, birth weight, the duration of breastfeeding, the time spent on TV/computer, the attitude and anxiety level of the mother when her child does not eat and the mother's nutrition education. Conclusion: Malnutrition is a common problem and its rate is high in Konya. It is suggested that health professionals should educate the society, especially mothers by organizing various training meetings. Moreover, it can be emphasized that health planners should prepare a program to determine malnourished children considering the risk factors of malnutrition in health screens and first step medical centers.

Organ Printing With Life Cells: A Review

Human Organ Printing is one of the latest advancements in medical industry of today's world. With the help of current Bioprinting technology, it is possible to printed human organs directly with Bio-life cells. In the current world millions of dollars were spend in many research and educational institutes to eliminate the boundaries in organ printing. The goal of researchers is to replace a human organ with Bioprinted organ successfully. In process of organ printing various machines and materials are used across the globe. The most printed organs with this technology are liver, cartilage, skin, heart and bone tissues etc. Even though the approach may be differ from one to other but everyone is moving towards organ printing with life cells. In this some of them are very successful at their preclinical trials. Some of the major challenges in this technologies are printing organs with life (life time of printed organ), printing environment and post processing (like Autoclave) process. The advancements in this area clearly show that researchers are very near to the future, where replacement of human organ with printed organ is achievable. This paper majorly discusses on the current technologies in organ printing along with their applications, materials, case studies along with future advancements.

Birth registration and child undernutrition in sub-Saharan Africa.

In many countries of the world millions of people are not registered at birth. However, in order to assess children's nutritional status it is necessary to have an exact knowledge of their age. In the present paper we discuss the effects of insufficient or imprecise age data on estimates of undernutrition prevalence. Birth registration rates and levels of stunting, underweight and wasting were retrieved from Multiple Indicator Cluster Surveys and Demographic and Health Surveys of thirty-seven sub-Saharan African countries, considering the subdivision in wealth quintiles. The composition of the cross-sectional sample used for nutritional evaluation was analysed using a permutation test. Logistic regression was applied to analyse the relationship between birth registration and undernutrition. The 95 % probability intervals and Student's t test were used to evaluate the effect of age bias and error. Heterogeneous sampling designs were detected among countries, with different percentages of children selected for anthropometry. Further, registered children were slightly more represented within samples used for nutritional analysis than in the total sample. A negative relationship between birth registration and undernutrition was recognized, with registered children showing a better nutritional status than unregistered ones, even within each wealth quintile. The over- or underestimation of undernutrition in the case of systematic over- or underestimation of age, respectively, the latter being more probable, was quantified up to 28 %. Age imprecision was shown to slightly overestimate undernutrition. Selection bias towards registered children and underestimation of children's age can lead to an underestimation of the prevalence of undernutrition.

Telepractice in University Au.D. Programs: Survey of Program Directors

Permanent hearing loss is a global health care burden; 360 million people, including 32 million (9%) children, have disabling hearing loss (Chadha & Stevens, 2013, p. 2). About 80 percent of these people live in developing nations without access to hearing care services. The American Academy of Audiology (AAA, 2014) has reported “ongoing efforts to explore and enhance the use of telepractice…to expand the availability and accessibility of hearing and balance care” to individuals across the world. The American Speech-Language-Hearing Association (2014c) has also endorsed advances in telepractice for the world's millions with hearing loss and related disorders, and encouraged institutional involvement as a future direction for audiology training. In the first publishing of this nature, this report shares survey responses from 28 of the nation's 74 graduate programs about their inclusion of telepractice in the Clinical Doctor of Audiology (Au.D.) curriculum. Results suggest a slow response from university programs and challenges in addressing telepractice in current course and clinical offerings. Results also support a direction of change to include telepractice in future Au.D. curricula.

Survey of Traffic Congestion Detection using VANET

Traffic congestion is a major problem in modern societies where around the world millions of hours and gallons of fuel are wasted everyday by vehicles stuck in traffic. Traffic congestion estimation using vehicular ad hoc networks can have many interesting applications. This survey summarizes the research on traffic information systems based on vehicular ad hoc networks. Two classes of such systems are studied: Infrastructureless solutions based on inter-vehicle communication and infrastructure-based solutions. Systems within Infrastructureless class are briefly introduced and their strengths and weaknesses

Ammonium nitrate explosion hazards

Ammonium nitrate (AN) primarily is used as a fertilizer but it is also very important compound in the production of industrial explosives. The application of ammonium nitrate in the production of industrial explosives was related with the early era of Nobel dynamite and widely increased with the appearance of blasting agents such as ANFO and Slurry, in the middle of the last Century. Throughout the world millions of tons of ammonium nitrate are produced annually and handled without incident. Although ammonium nitrate generally is used safely, accidental explosions involving AN have high impact resulting in loss of lives and destruction of property. The paper presents the basic properties of ammonium nitrate as well as hazards in handling of ammonium nitrate in order to prevent accidents. Several accidents with explosions of ammonium nitrate resulted in catastrophic consequences are listed in the paper as examples of non-compliance with prescribed procedures.

Review of 500 migraine cases treated with combination of antidepressant & CBT & specific group of dietary supplement with 6 month follow up

Migraine is a condition which consumes maximum revenue of a family, state & nation & still the suffering goes on. In the world millions are suffering from Migraine .. & having pain killer medicine & suffering from their side effect like kidney failure etc Migraine sufferers may have depression deep down... but psychiatry being a stigma - very few sufferer goes for consultation to psychiatrist. History of migraine needs a long time to listen & the ability to listen ,.... which normally a psychiatrist does not have time to listen the painful past & long details without getting revenue - or fee or financially paid for - so depression goes unnoticed. Depression assessment scale -although available - but very few psychiatrist has a team work in India & most of the countries.

A Duty to Adopt?

AbstractAll over the world millions of children are without parental care. As a consequence they are liable to suffer serious harm. I argue the general duty to assist those in need extends to children without parental care and that some people are under a moral duty to adopt rather than have biological children. I defend this claim against the following objections: (1) intimate decisions are excluded from the duty to assist, (2) adopting children is too costly to be required by morality, (3) the duty to assist is a collective duty, (4) the duty to assist is an imperfect duty, and (5) there are, in fact, very few adoptable children.

Tıbbi Bir Bitki Olarak Gül

In today’s world millions of people lead a low quality of life, or even lose their lives because of highly expensive medical treatments. Cheap and accessible treatments, on the other hand, protect the continuity of human life and thus protect the health of societies. In this context, various treatment methods have been researched and the importance of herbal and plant based treatments have emerged. As a part of herbal and plant based treatments roses, which are relatively easy to grow and process, have attracted great attention. There are about 1300 species of rose. Among these, Rose Canina, also known as rosehip, and the pink, layered and aromatic Rosa Damascena, also known as “Isparta Rose” have emerged in importance as they are actively used in various treatments. Researchers have found that roses have 89 active, beneficial ingredients. The flower drums and petals are used in the treatment process. With Rosa Canina the flower drums are used. In a recent research, it was found that rose petals contain antioxidant agents. Rosewater, which is thought to nurture the soul with its fine aroma, is used in treating patients with nausea, palpitations, fainting and vertigo. We are informed that with the tasting of the plant nausea and vomiting is reduced and with drinking its water the stomach is given extra strength. Rosewater, which helps reduce headaches, also has positive effects on the workings of the brain, helping the faculty of cognition. We are also informed that rose water vapour helps in the treatment of eye diseases. Roses are also used in the treatment of mental illnesses since they are pleasant flowers

Coda: Snared in Bureaucracy

Coda: Snared in Bureaucracy