New Insights on Avoiding the Causes of Projects Delays: A Framework

In this paper, we study and analyze the reasons behind the delay of some projects. Our aim is shed light on how one reduces the effect of the different obstacles and improves achievement either in quality or time. Different challenges play the main reasons in the stalled project including planning, designing, construction, and weak leaders or poor administrative decisions. We focus on developing a framework that helps in improving the management of the projects and finishing the projects on time. This includes developing a contingency plan and coordination mechanism between internal and external stakeholders. Following the steps of the methodology will help project managers to avoid project delay and solve the problems of the staled ones. Finally, we represent some managerial insights and recommendations that related parties should follow with the projects

Assessment of Grasslands and Livestock Production in Kangra Valley of Himachal Pradesh

In Himachal Pradesh 89.96 percent as per 2011 census of population lives in rural areas. The mainstay of the people of Himachal Pradesh is agriculture and has an important place in the economy of the State. Agricultural census shows that 87.95 percent of the total holdings are of small and marginal. Rearing of livestock is an integral component of rural economy (Anonymous, 2014). Livestock depend to a certain extent on fodder and grass grown on common property resources (CPR) as well as on crops and residues. Animal production is an integral part and forms part of the earning of small and marginal farmers. Almost every household in the State maintains a few heads of livestock of one kind or the other. The indigenous livestock population, and in many cases their cross bred progeny are dependent on grazing/pasture land and forest. When these animals become unproductive, old or sick, there is a tendency to abandon them rather than be responsible for feeding them. Grassland/pastures produce far below their potential and there is a gap between demand and supply of green fodder. The geographical area of Kangra is 5, 63,832.3 ha and area under grasslands is 69,781.7 ha that comes around 27. 51%. (Singh et al., 2009). The problem of animal productivity has been exacerbated by the shortage of fodder as holdings have become smaller and the extent and productivity of common grazing lands has also reduced over time. There are mainly two reasons which are responsible for poor performance of livestock, i.e., low productive animals and low availability of fodder

Modeling Camera Effects to Improve Visual Learning from Synthetic Data

Recent work has focused on generating synthetic imagery to increase the size and variability of training data for learning visual tasks in urban scenes. This includes increasing the occurrence of occlusions or varying environmental and weather effects. However, few have addressed modeling variation in the sensor domain. Sensor effects can degrade real images, limiting generalizability of network performance on visual tasks trained on synthetic data and tested in real environments. This paper proposes an efficient, automatic, physically-based augmentation pipeline to vary sensor effects --chromatic aberration, blur, exposure, noise, and color cast-- for synthetic imagery. In particular, this paper illustrates that augmenting synthetic training datasets with the proposed pipeline reduces the domain gap between synthetic and real domains for the task of object detection in urban driving scenes

Socio-economic Assessing of Researchers Perceptions and Farmers Willingness to Adopt Silage Technology in Palestine-West Bank

In this paper the animal breeder in Palestine has many challenges including high feed prices, high-cost input, low-quality pasture, limited access to rangeland with high quality, and high cost of feed. In Tubas and Tulkarm areas, extensive irrigated agriculture is dominant. Large quantities of agricultural by-products are wasted. As one of the important interventions to decrease feeding costs, the study focused on silage technology adoption from the view of researchers and farmers. It meant using these agricultural by-products to make them beneficial and eatable for the animal. On the one hand, we removed these by-products from the environment and second, we fed to animals and ultimately, we reduced the input cost of animal feed. The main objective is to improve dissemination strategies and approaches that promote the adoption of silage technologies by identifying both researcher and farmer perceptions and constraints. A field `survey was conducted targeting 70 farmers (35 have knowledge and practice silage technology and 35 do not) from Tubas and Tulkarm areas. The binary logistic model was used for analysis in SPSS and Excel was used for data analysis. The main finding was that age and education play a very important role in the level of adoption, both have negative effects, and access to credit and land tenure may increase the chance of adoption. farming experience has a less negative impact on the level of adoption, while family size has also a negative impact, family size also affects the level of adoption. People in the targeted area try to diversify their income and educated people to leave their parents, either settle outside or come home at the weekend. The study recommended that being a member of a community-based organization increases your chance of access to new technology and increases your chance of adoption. Public awareness and approaches to CBO are crucial for the adoption of this technology. The size of the herd is important for adoption and cost analysis

An unusual presentation of nabothian cyst: a case report

Nabothian cysts are common gynecologic findings and rarely of clinical significance. They are not problematic unless they are sizeable and present secondary symptoms like in this case. Nabothian cysts are usually associated with chronic cervicitis, an inflammatory condition of cervix, and are harmless and usually disappear on their own. Here we report an interesting case of multiple large nabothian cysts presented with continuous, thin & copious watery discharge, a distressing symptom, mimicking genitourinary fistula. This case is reported for the rarity of symptoms of continuous copious thin watery discharge per vaginum. Very rarely nabothian cyst needs hysterectomy as in our case

Polypropylene Composites Reinforced by Marine Posidonia Fiber Waste: Effect of Silane and Alkali treatment

This paper investigates the effects of chemical treatment and the reinforcement rate on the mechanical properties of polypropylene composites reinforced with Posidonia waste fibers. Increasing the reinforcement rate from 20% to 30% improved Young’s modulus and the flexural modulus of the composite. Silane treatment had a positive effect on all the mechanical properties of the composite; on the other hand, the alkali treatment improved the tensile strength but decreased the flexural property of the composite. The greatest Young’s and flexural moduli were obtained in the case of 30% reinforcement treated with silane. The increases in these properties were 57.95% and 44.84% for the tensile and flexural moduli, respectively, compared to pure polypropylene. The mechanical properties of the composite obtained were higher than those of hemp and jute produced under the same conditions using the single-screw extrusion process. The results show that Posidonia waste fiber is an effective candidate to be utilized to produce composites for the automotive industry, such as rear shelves, boot linings, spare wheel compartments, and interior doors, and that it has economic and ecologic advantages in comparison with hemp and jute fibers

The CMBR ISW and HI 21-cm Cross-correlation Angular Power Spectrum

The late-time growth of large scale structures (LSS) is imprinted in the CMBR anisotropy through the Integrated Sachs Wolfe (ISW) effect. This is perceived to be a very important observational probe of dark energy. Future observations of redshifted 21-cm radiation from the cosmological neutral hydrogen (HI) distribution hold the potential of probing the LSS over a large redshift range. We have investigated the possibility of detecting the ISW through cross-correlations between the CMBR anisotropies and redshifted 21-cm observations. Assuming that the HI traces the dark matter, we find that the ISW-HI cross-correlation angular power spectrum at an angular multipole l is proportional to the dark matter power spectrum evaluated at the comoving wave number l/r, where r is the comoving distance to the redshift from which the HI signal originated. The amplitude of the cross-correlation signal depends on parameters related to the HI distribution and the growth of cosmological perturbations. However the cross-correlation is extremely weak as compared to the CMBR anisotropies and the predicted HI signal. As a consequence the cross-correlation signal is smaller than the cosmic variance, and a statistically significant detection is not very likely.Comment: 13 pages, 4 eps figures, submitte

Persistence of Primary and Secondary Pollutants in Delhi : Concentrations and Composition from 2017 through the COVID Pandemic

We assess impacts of the 2020 COVID-19 lockdown on ambient air quality in Delhi, building on over three years of real-time measurements of black carbon (BC) and nonrefractory submicrometer aerosol (NR-PM1) composition from the Delhi Aerosol Supersite and public data from the regulatory monitoring network. We performed source apportionment of organic aerosol (OA) and robust statistical analyses to differentiate lockdown-related impacts from baseline seasonal and interannual variability. The primary pollutants NOx, CO, and BC were most reduced, primarily due to lower transportation emissions. Local and regional emissions such as agricultural burning decreased during the lockdown. PM2.5 declined but remained well above WHO guidelines. Despite the lockdown, NR-PM1 changed only moderately compared to prior years. Differences in the trends of hydrocarbon-like OA and BC suggest that some sources of primary aerosol may have increased. Despite notable reductions in some primary pollutants, the lockdown restrictions led to rather small perturbations in the primary fraction of NR-PM1, with secondary aerosol continuing to dominate. Overall, our results demonstrate the impact of secondary and primary pollution on Delhi's air quality and show that large changes in emissions within Delhi alone are insufficient to bring about needed improvements in air quality.Peer reviewe

Persistence of Primary and Secondary Pollutants in Delhi : Concentrations and Composition from 2017 through the COVID Pandemic

We assess impacts of the 2020 COVID-19 lockdown on ambient air quality in Delhi, building on over three years of real-time measurements of black carbon (BC) and nonrefractory submicrometer aerosol (NR-PM1) composition from the Delhi Aerosol Supersite and public data from the regulatory monitoring network. We performed source apportionment of organic aerosol (OA) and robust statistical analyses to differentiate lockdown-related impacts from baseline seasonal and interannual variability. The primary pollutants NOx, CO, and BC were most reduced, primarily due to lower transportation emissions. Local and regional emissions such as agricultural burning decreased during the lockdown. PM2.5 declined but remained well above WHO guidelines. Despite the lockdown, NR-PM1 changed only moderately compared to prior years. Differences in the trends of hydrocarbon-like OA and BC suggest that some sources of primary aerosol may have increased. Despite notable reductions in some primary pollutants, the lockdown restrictions led to rather small perturbations in the primary fraction of NR-PM1, with secondary aerosol continuing to dominate. Overall, our results demonstrate the impact of secondary and primary pollution on Delhi's air quality and show that large changes in emissions within Delhi alone are insufficient to bring about needed improvements in air quality.Peer reviewe

Predictive modeling of haloacetonitriles under uniform formation conditions

Highlights • HAN model linearity is highly affected by water type • pH is the most influential parameter for HAN modeling for chlorination and chloramination • A positive correlation between DON/DOC term and HANs models was observed in EfOM impacted waters • The r2 of DCAN model in chlorination (r2=0.88) was higher than chloramination (r2=0.49) • Higher correlation between HAN4 and THM4 was found at pH range of 7 to 8The objective of this study was to develop models to predict the formation of HANs under uniform formation conditions (UFC) in chlorinated, choraminated, and perchlorinated/chloraminated waters of different origins. Model equations were developed using multiple linear regression analysis to predict the formation of dichloroacetonitrile (DCAN), HAN4 (trichloroacetonitrile [TCAN], DCAN, bromochloroacetonitrile [BCAN], and dibromoacetonitrile [DBAN]) and HAN6 (HAN4 plus monochloroacetonitrile, monobromoacetonitrile). The independent variables covered a wide range of values, and included ultraviolet absorbance, dissolved organic carbon, dissolved organic nitrogen, SUVA254, bromide, pH, oxidant dose, contact time, and temperature. The r2 values of HAN4 and HAN6 models of NOM, AOM, and EfOM impacted waters were within the range of 60-88%, while the r2 values of HAN4 and DCAN models for both groundwater and distribution systems were lower, in the range of 41-66%. The r2 values for the DCAN model were mostly higher in the individual types as compared to the cumulative analysis of all source water data together. This was attributed to differences in HAN precursor characteristics. For chlorination, among all variables, pH was found to be the most significant descriptor in the model equations describing the formation of DCAN, HAN4, and HAN6, and it was negatively correlated with HAN formation in the distribution system, groundwater, AOM, and NOM samples, while it showed an inverse relationship with HAN6 formation in effluent organic matter (EfOM) impacted waters. During chloramination, pH was the most influential model descriptor for DCAN formation in the NOM. Prechlorination dose was the most predominant parameter for prechlorination/chloramination, and it was positively correlated with HAN4 formation in AOM impacted waters