Abstract:The main purpose of this study was to investigate gender differences as for predictors of entrepreneurial intention among students in Iranian higher entrepreneurship education system. A survey of all students in entrepreneurship faculty of Tehran University was carried out (N = 211). 136 students were selected for the study using a stratified random sampling method. The result showed there were a significant positive relationship between entrepreneurial intentions of male students and their attitudes towards entrepreneurship, social norms and self-efficacy beliefs. While among the female students, attitudes towards entrepreneurship and self-belief had a significant positive relationship with entrepreneurial intentions. The results of the analysis showed students \'self-efficacy beliefs in male and female students\' attitudes toward entrepreneurship had the most direct and significant impact on their entrepreneurial intentions. Also, comparing the results suggested significant impact of gender on attitudes towards entrepreneurship; social norms and self-efficacy beliefs of students. The results of this study can have implications for higher education planners dealing with entrepreneurship to enhance students\' entrepreneurial intentions and behavior and reduce the gender gap in their entrepreneurial activities in the future.
Abstract:A total of 32 emergency cases of buffaloes with esophageal obstruction resulting from\nthe devouring of potato tubers during their grazing. Treatment comprised immediate\nrumen trocarisation by a 14 g. syringe’s needle, premedication with IM xylazine (0.05\nmg/kg) and passing a designed stout flexible tube to dislodge the obstruction to the\nrumen. The results was 100% successful recovery without any complications.
Abstract:The association and interaction among metals in bitumen polluted water may affect the availability of the metals even at toxic levels to the surrounding environment and biota that are dependent on such water. The study was carried out at Ode-Irele in Ondo State bitumen belt, Southwest of Nigeria, where there are bitumen seepages, and Ebute-Irele where there are no records of seepages served as control. Composite samples of surface water were collected to a depth of 30cm midstream on the sites. Heavy metals ï¿½ Manganese, Iron, copper, zinc, lead, chromium, cadmium, nickel, vanadium, arsenic, calcium, magnesium, potassium, and sodium were determined using standard methods. Data on metalsï¿½ concentrations were analyzed using descriptive statistics and t-test at p < 0.05. The associations that exist among metals of surface water were analysed using regressive correlation to determine which metal increased or decreased with rise and fall in the level of other metals. Values obtained were compared with Federal Environmental Protection (FEPA) and World Health Organisation (WHO) Guidelines. Results of the study revealed that nickel, calcium, magnesium, and sodium were higher in seepage site than that of control, but, nickel was significantly higher in surface water of seepage site, 0.40 ï¿½ 0.00mg/L than that of control, 0.30 ï¿½ 0.00mg/L. Manganese, iron, copper, zinc, chromium, cadmium, nickel, vanadium, and arsenic, as well as calcium were higher than guideline levels. Nickel, iron, manganese, vanadium, calcium and sodium which are elemental components of bitumen could pose serious environmental problems. There were significant positive associations between iron and copper, manganese and vanadium, iron and sodium, calcium and magnesium, as well as between magnesium and sodium. The finding also revealed significant negative association between lead and zinc. The heavy metals in surface water that were higher in seepage site and higher than guideline values in Ondo State bitumen belt and especially those that are elemental components of bitumen could have toxic effects on the environment, and so they should be closely monitored during the bitumen development phase.
Abstract:The global 2019 coronavirus disease (COVID-19) pandemic has spread over The whole planet within months. Social and economic life in many countries is badly disrupted as a result of this major epidemic. As well as the environmental risk is rise Because of personal protective equipment (PPE) such as the Medical Face Safety Masks (MFSM). As well as, careful hand washing and physical space between personals and to avoid transmission of COVID-19, the wearing of medical face masks is advised. . Under conditions of extreme lack of availability of surgical masks, for the general population the only use of clothes masks is recommended . Both patients and healthcare personnel wear disposable surgical face masks to reduce the incidence of coronaviruses . Coronaviruses diseases result in a rise in medical care costs. The consistency of surgical face masks is therefore important and is defined by the regular testing mechanism established by standards such as ASTM and European standards. With a durability of over 50 cycles, disposable surgical masks may be sterilized and washed for reuse. . However, reuse surgical masks have much less safety quality relative to new mask. . If the frequency of washing cycles is increased, the quality of safety for recycled ones is diminished. Repeated washing of recycled medical face masks will also use more resources and supply the environment with more polluted water. Polypropylene is used as the raw material for medical face safety masks production . It has several advances such as water and moisture barrier, can produced in fabric form so it breathable and flexible beside is lightweight and non-toxic. Polypropylene is used to a non-woven fabrics and fishing nets manufacture due to is can float in the surface of seawater . Conservationists since discovering disposable masks floating like jellyfish. Dynamics of waste generation and hence special attention has been needed. The unforeseen variations in the composition and quantity of waste often require policymakers to react dynamically. During an epidemic of COVID-19, several kinds of medical and toxic materials are created, including contaminated masks for faces , gloves for hand and other safety clothing, along with a higher amount of infected products of the patients food baggage. There has been a high increase in demand for goggles , gloves, hand sanitizers, and other important items since the news of human coronavirus transmission reached the press. A need of 89 million surgical masks and 76 million hand gloves for the COVID-19 produced every month was calculated by the WHO modelling, although international demand for eye protector is 1.6 million per month . This research highlights the problems encountered since the pandemic by the solid waste management industry and the underlying possibility of filling current loopholes in the system. Due to increasing hygiene issues , especially for items used for personal safety and medical purposes, single-use plastic item is expected to bounce back. Leading to enhanced conscious purchasing of high non-perishable goods during lockdown and attributable to food scarcity issues, household food waste production is anticipated to decrease. The report also suggests several key guidelines for policymakers to better holistically manage potential future pandemics, if any.
Abstract:As a cheap and effective corrosion inhibition of mild steel in 1 M HCl, ethanol extract of Posidonia oceanic leaves based on Polyvinylpyrrolidone is used using weight reduction, open circuit potential and potentiodynamic polarization methods. The results explained that the productivity of hindrance increments as the concentration of extract increases, which at 1000 ppm discovered greatest restraint efficiency ~ 81 percent. The FTIR investigation of ethanolic extract confirmed the creation of kaolin-traced phenolic and polysaccharide compounds responsible for adsorption on the surface of mild steel. Using SEM study to inhibitive action against steel in corrosive arrangement, the surface morphology was considered. It is presumed that ethanol removes from Posidonia oceanic leaves can fill in as compelling gentle steel consumption inhibitors in hydrochloric acid.
Abstract:The aromatic sulfonates are contemplated as the oldest organic chemicals. They are used in the manufacture of dyestuffs and also as eclectic intermediates in the production of organic compounds. 2 amino benzene sulfonate is a sulfonated aromatic compound used in the textile industry and considered as one of the dyes intermediate. The present study was executed to analyze the toxicity induced by 2 ABS in blood cells of freshwater fish Channa punctatus. After LD50 determination, two sublethal doses were selected i.e., 2.83 mg/30g b.w. and 5.66 mg/30g b.w. Fishes were injected intraperitoneally. Blood samples were collected after 24h, 48h, 72h, 96h respectively. Recovery was noticed up to 720h (30 days) postexposure. Behavioural alterations, hematological parameters, oxidative stress (malondialdehyde content) and genotoxicity (micronuclei assay and comet assay) were assessed as biochemical markers. The results of the study revealed altered behaviour patterns and haematological parameters. Significant increase in MDA content, MNC and AC frequency and DNA damage were also observed as compared to control group (p≤0.05). Further diminution in all the aforementioned parameters marks the efficient extent of recovery. The findings of the present study indicate 2 ABS induced toxicity among aquatic organisms.
Abstract:In light of the current pandemic, the Corona pandemic, researchers are making a great effort to try to understand and appreciate the characteristics of the SARS-CoV-2 epidemic in order to reach some solutions that may lead to eliminating the disease or preventing its spread. Beginning and as mentioned by the World Health Organization (WHO), one of the most important causes of the spread of SARS-CoV-2 virus are respiratory droplets or close contact inside closed doors where the infection is transmitted through aerosols or by close contact. From our vision after see the regions of coronaviruses spread in whole world map and link it with the weather of the countries in the world maps. It was founded that the virus is increasing in many regions and countries that have achieved clear success in combating environmental pollution or that are not exposed to dusty storm, and infections are increasing again in the same country with different densities of sick people according to the weather temperature and windy season. The relationship between coronaviruses spread and dust storm is reversible this due to the dust is almost contain 90 % of metal oxide that act as nature photocatalysts for O●-2 and ●OH production. This oxidizing spices are capable to destroy SARS-Cov-2.
Abstract:The present work is focused on co-doping TiO2 with N and C atoms from chicken egg white in order to enhance its activity under visible light for removal of congo-red dye from water through photodegradation. The co-doping TiO2 was prepared by interacting TiO2 suspended in water with chicken egg white with various weight through hydrothermal technique in an autoclave. The co-doped TiO2 photocatalysts were characterized by FTIR, XRD, DRUV, TEM, and SEM-EDX instruments. The photocatalytic activity is evaluated for degradation of congo-red dye in water through batch experiment. The characterization data assigned that doping TiO2 with C and N atoms from protein of chicken egg white has noticeably narrowed the gap, that shifted the absorption into visible region. The narrowing gap indicated by declining band gap energy (Eg), was found to be influenced by the weight of the chicken egg white for a constant TiO2 weigh, and the most significant decrease of the Eg, that was 2.70 eV from 3.2 eV, was shown by TiO2/N-C with ratio weight of TiO2 : chicken egg = 1:2. The co-doping TiO2 has considerably enhanced the photodegradation of congo-red dye in water under visible light, compared to the un-doped one. The highest photodegradation of 10 mg/L congo-red dye was reached by TiO2/N-C with 1:2 ratio, in 45 min of time, at pH 7, and 50 mg photocatalyts/100 mL solution. that was about 98% under visible light, while over undoped TiO2 was found to be 60%.
Abstract:Bisphenol A (BPA) is one of the emerging contaminants associated with deleterious health effects on both public and wildlife and is extensively incorporated into different industrial products. BPA is ubiquitously and frequently detected in the environment and has become a serious health issue due to its presence in food organisms and in drinking water. The distribution of BPA has recently become an important issue worldwide, but investigations on the toxicity of BPA remain limited. A review of the literature reveals that BPA has a widespread presence in environmental media, such as indoor dust, surface water, sediments, and sewage sludge. In the present review, an overview of the research studies dealing with the occurrence, fate, exposure, and toxicity of BPA is discussed. Recent studies have raised worry over the potentially harmful implications of BPA exposure in humans and wildlife. However, further investigation on the potential risks of BPA to humans and its mechanisms of toxicity should be conducted to better understand and control the risks of such novel chemicals.
Abstract:In the future, medical diagnosis by artificial intelligence is expected to become widespread. Therefore, we considered a method for diagnosing a disease based on a checklist using Bayesian inference. In this paper, we describe the development of basic theory and algorithms for that purpose. Nowadays, neural networks or deep learning have become synonymous with artificial intelligence (AI), and the idea that human intellectual work will soon be replaced by AI has been born. However, deep learning is not perfect. For example, it is known that there are many problems such as \"inference is a black box\", \"unexpected answer due to overfitting\", and \"large-scale network and long-time learning\". Bayesian inference can provide learning and inference that is completely different from neural networks. Therefore, it may be possible to overcome the problems of neural networks. In this paper, we discuss the application of Bayesian inference to disease diagnosis.