Molecular detection of Mycoplasma gallisepticum in different poultry breeds of Abbottabad and Rawalpindi, Pakistan

The poultry sector in Pakistan is contributing mainly in bridging gap between demand and supply for protein. Mycoplasma gallisepticum is an emerging bacterium causing serious problems in poultry industry of Pakistan. A cross-sectional study was conducted to evaluate the M. gallisepticum load in poultry populated regions of Pakistan. Total 600 serum and 600 swab samples were collected, 200 from each broiler, layers and breeders poultry in Rawalpindi and Abbottabad districts. Serum samples were analyzed through ELISA for seroprevalence. Swabs were cultured on Frey’s medium followed by PCR and partial mgc2 gene sequencing. Results of seroprevalence of M. gallisepticum showed that layers (75%, n=150) are more positive as compared to breeders (70%, n=140) and broilers (50%, n=100). Typical colonies of the M. gallisepticum were observed in breeder (26.5%), followed by layer (21%) and broilers (9%). A total of 37.1% (n=42) samples were identified positive through PCR out of total 113 cultured based positive samples. A total of six M. gallisepticum isolates of current study showed 98-99 percent similarity with previously reported isolates on the basis of mgc2 gene partial sequencing. The M. gallisepticum was found highly prevalent in different poultry breads. Results of this study would add into basic data and provide a direction for livestock sector to strengthen a control strategy for mycoplasmosis in poultry farms.

Assessment of Population pressure on Urban Housing in Ngwa Road, Ohanku and Obohia Parts of Aba South, Abia State Nigeria

The effect of population growth on urban housing is a global challenge but the worst examples are found in the developing world which has led to an increased growth of poorly planned cities in the developing world, and loss of aesthetics. The aim of this research is to assess the level of population pressure on urban housing within Ngwa Road, Ohanku and Obohia environs in Aba South local government area in Abia State. The research evaluated housing demand and supply in the area, condition of houses in the area, factors encouraging population growth in the study area and level of compliance of buildings with town planning laws. The study area has an estimated 2021 population of 138017 as projected from 88,951 in 2016 with a growth rate of 2.94%. The research data was collected through household survey, Aba South Town Planning Authority, National Population Commission and the Aba South Street Naming and House Numbering Office. The simple random sampling technique and the purposive sampling technique were employed by the researcher with a sample size of 399.9 at 0.05 confidence level which was determined using the Taro Yamane method for sample size collection. The Principle Component Analysis (PCA), Principle Component Regression (PCR), standard deviation, weighted mean, percentages/proportions to analyze the data collected. The Principal Component Analysis result showed that component I have the highest loading with eigen value of 6.721 while component II has an eigen value of 3.279. The result showed that ease of access to commercial activities and educational level of heads of households are major factors encouraging population growth in the study area. The research revealed a housing demand and supply cluster estimate of 60.11% which was not considered statistically high. The average response of 93.2% is that houses in the study area are in a poor condition. The Aba South town planning authority revealed a 0.741 standard deviation which shows a high level of non-compliance with town planning laws. The research hypothesis was tested using Spearman Rank Correlation test at 0.05 level of confidence and the null hypothesis was accepted. Looking at the Land-UseLand-Cover images of the area obtained for 3 epochs from 1980-2020, the study area experienced an major growth in rate of housing stock after year 2000 and with increasing population growth, the area may soon be unable to carry the population that will be found there. This research calls the attention of the Abia State government in particular and the federal government in general to address these challenges through recommended public-private partnership and decentralization of pull factors. These recommendat

THE HISTORY OF THE COVID 19, AND ITS IMPACT ON THE CRUDE OIL PRICE CHANGES (IN CONTEXT OF INDIA`S COVID 19 CONTEXT)

Oil is the most essential fuel for the world presently and the world, India is the third largest oil importer in the world, with 9.7 percent of the world oil imports, after China and USA, India imports around 80 percent of its oil needs and aims to bring down to 67 percent by 2022, by replacing it by local exploration, renewable energy and indigenous ethanol fuel, but in India there is lack of demand for crude oil and oil products due to Covid-19 epidemic, which made Indian government to imply restrictions, to lockdown of various firms, industries, public and private sector institutions, as health emergency, according to the report of IEA ( International Energy Agency) India’s 40 days lockdown has led to decrease in 30 percent fall in countries demand for energy. Price inflexibility is concern for Indian oil producers, as it is the biggest shock since the Second World War, The global economy is expected to enter recessionary zone in 2020, as countries have shut down there normal business activities, to fight the pandemic led to imbalances in demand and supply of oil prices in the Indian market, Indian oil companies are waiting for the tax reductions and packages by the government, in the short term imbalance in oil demand and supply situation. The purpose of the research paper is that, Indian government has a great task to fight against pandemic as a health emergency and oil prices fluctuations in the year 2020. KEY WORDS: History of the pandemic covid social growth and crude oil prices (PETROLEUM),

Effect of different date of transplanting for off-season onion production in Central Uttar Pradesh

Off-season onion production of is an important issue to challenge the price fluctuation during different time of year and in different location of the country. The present experiment was conducted at sub-tropical region of central Uttar Pradesh (Lucknow) during kharif, late kharif season of 2018-20 to find out the optimum date of transplanting and choice of suitable cultivar of onion for off-season production. The experiment consisted of eight dates of transplanting (30th August, 10, 20, 30th September, 10, 20, 30th October and 10th November) and two cultivars (Agrifound Dark Red and L-883) which was laid out in factorial randomized block design with three replications. Transplanting on 30th September showed maximum vegetative growth in terms of plant height (66.93 cm), number of leaves per plant (14.99), maxi-mum length of leaf (47.60 cm), neck thickness (23.19 mm) at 120 days after transplanting as well as highest average bulb weight (79.53 g) and bulb yield ( 10.02kg/plot and 382.68 q/ha). Among the two varieties L-883 showed the better performance in respect of growth and yield in off season production. Therefore, it may be concluded that the cultivation of L-883 variety and transplanting on 30th September was found best for off –season production in the sub –tropical agro- climatic region of Center Uttar Pradesh (Lucknow) which may be beneficial for increasing farmers’ income as well as for benefit of costumers keeping the balance between demand and supply.

Rebalancing Autonomous Vehicles using Deep Reinforcement Learning

The shared autonomous mobility-on-demand (AMoD) system is a promising business model in the coming future which provides a more efficient and affordable urban travel mode. However, to maintain the efficient operation of AMoD and address the demand and supply mismatching, a good rebalancing strategy is required. This paper proposes a reinforcement learning-based rebalancing strategy to minimize passengers’ waiting in a shared AMoD system. The state is defined as the nearby supply and demand information of a vehicle. The action is defined as moving to a nearby area with eight different directions or staying idle. A 4.6 4.4 km2 region in Cambridge, Massachusetts, is used as the case study. We trained and tested the rebalancing strategy in two different demand patterns: random and first-mile. Results show the proposed method can reduce passenger’s waiting time by 7% for random demand patterns and 10% for first-mile demand patterns.

The Role of Technology in Nigerian Catfish Production: A Review

This article examines the state of Catfish production in Nigeria and the roles technology has played over the past decades. Heightened demand as a result of increased population puts considerable pressure on production. In response to this pressure aquaculturists ramped up production activities, this demand-driven increase exposes the major gaps as the industry struggles to cope with the absence of fundamental structures like inadequate structured funding, markets, processing and preservation facilities among others. Such gaps exist in all aspects of aquaculture and technology is a viable plug for many of them. The aquaculture of developing nations has certain peculiarities which predispose it to slow development. Many fishermen and aquaculturists in low-income regions are trapped in economic systems that result in relative poverty. Many reasons have been put forward to explain the dynamics behind these consequences with technology playing a major role from the consensus. Rapid advances in hatchery, water quality and molecular technology have been identified as some of the active drivers of Catfish production in Nigeria. The article focuses on the history, progress and prospects of aquaculture technology in Nigeria. It does so by reviewing the technologies already established in Catfish farming and the impact of their roles in balancing fish demand and supply.

Registered nurses: can our supply meet the demand during a disaster?

Background Death and destructions are often reported during natural disasters; yet little is known about how hospitals operate during disasters and if there are sufficient resources available for hospitals to provide ongoing care during these catastrophic events. The purpose of this study was to determine if the State of New Jersey had a supply of registered nurses (RNs) that was sufficient to meet the needs of hospitalized patients during a natural disaster – Hurricane Sandy. Methods Secondary data were used to forecast the demand and supply of New Jersey RNs during Hurricane Sandy. Data sources from November 2011 and 2012 included the State Inpatient Databases (SID), American Hospital Association (AHA) Annual Survey on hospital characteristics and staffing data from New Jersey Department of Health. Three models were used to estimate the RN shortage for each hospital, which was the difference between the demand and supply of RN full-time equivalents. Results Data were available on 66 New Jersey hospitals, more than half of which experienced a shortage of RNs during Hurricane Sandy. For hospitals with a RN shortage in ICUs, a 20% increase in observed RN supply was needed to meet the demand; and a 10% increase in observed RN supply was necessary to meet the demand for hospitals with a RN shortage in non-ICUs. Conclusion Findings from this study suggest that many hospitals in New Jersey had a shortage of RNs during Hurricane Sandy. Efforts are needed to improve the availability of nurse resources during a natural disaster.