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The presence of persistent heavy fog in northern India during winter creates hazardous situations for transportation systems and disrupts the lives of about 400 million people. The meteorological factors responsible for its genesis and predictability are not yet completely understood in this region. Given its high potential for socioeconomic impact, there is a pressing need for extensive research that understands the inherently complex nature of the phenomena through field observations and modeling exercises. WiFEX is a first-of-its-kind multi-institutional initiative dealing with intensive ground-based measurement campaigns for developing a suitable fog forecasting capability under the aegis of the smart cities mission of India. Measuring campaigns were conducted during the 2015–20 winters at the Indira Gandhi International Airport, New Delhi, covering more than 90 dense fog events. The field experiments involved extensive suites of in situ instruments and gathered simultaneous observations of micrometeorological conditions, radiative fluxes, turbulence, droplet/aerosol microphysics, aerosol optical properties, fog water chemistry, and vertical thermodynamical structure to describe the environmental stability in which fog develops. An operational modeling framework, the WRF Model, was set up to provide fog predictions during the measurement campaign. These field observations helped to interpret the strengths and deficiencies in the numerical modeling framework. Four scientific objectives were pursued: (i) the life cycle of optically thin and thick fog, (ii) microphysical properties in the polluted boundary layer, (iii) fog water chemistry, gas–aerosol partitioning during the fog life cycle, and (iv) numerical prediction of fog. This paper presents an overview of WiFEX and a synthesis of selected observational and modeling analyses/findings related to the abovementioned scientific topics.

Incisional hernias are hernias which occur as a result of excessive tension and inadequate healing of a previous incision1. Incidence of these hernias is 9.9% worldwide. These hernias arise through a defect in the musculo-fascial layers of the abdominal wall in the region of a postoperative scar. They can enlarge over time, leading to pain, obstruction, incarceration and strangulation. With loss of domain, the natural rigidity of the abdominal wall becomes compromised and the abdominal musculature is often retracted. Treatment includes Meshplasty or Abdominoplasty. In meshplasty surgery, the abdominal contents are reduced and the defect is closed. Following this, an onlay or inlay mesh is placed which secures the primary repair as well as allows brosis of the anterior abdominal wall by capillary and broblasts neovascularization in the spaces between the mesh. The advantage of using a mesh is for closing large defects or for defects in which abdomen cannot be closed by primary intention. Infection of the mesh, seroma, abscess formation, recurrence, surgical site infection, changes or loss in the abdominal domain are a few complications associated with this surgery. Another method of repair of these incisional hernias in our study is by abdominoplasty. In Abdominoplasty, we will plicate the linea alba from xiphisternum to pubic symphysis after closure of defect. The biggest drawback of meshplasty which is infection, is prevented in abdominoplasty. Additionally, abdominoplasty can provide an added advantage of it being cost effective. Here in this study, we will to compare and evaluate Primary Repair with Open Meshplasty v/s Abdominoplasty in cases of incisional hernias, on the their surgical outcome on the basis of rate of infection, ap necrosis, rate of recurrence and post-operative cosmesis.

The campaign mode observational program 'Winter Fog Experiment' (WiFEX) was set up at the Indira Gandhi International Airport (IGIA), New Delhi, during the winter months of 2016-17 and 2017-18. Using the WiFEX data, in this study, we examine the microphysical structure of fog formed in a polluted environment and attempt to predict visibility (V-is) using the fog index approach. The examination of eleven fog events demonstrates that the mean droplet concentration (up to 674.94 #/cm(-3)) and liquid water content (LWC, up to 0.29 g m(-3)) are high in dense fog cases (V-is < 200 m). The droplet spectrum shows bi-modal distribution and dominance of smaller droplets in the 3-7 mu m range. For most fog cases, the droplet spectrum extends up to 50 mu m. The mature phase of the fog depicts a relatively increased population of droplets in the higher-sized bins, highlighting the formation of larger droplets. Moreover, we found that V-is is inversely related to the liquid water content and the fog droplet number concentration. Fog index-based visibility parameterization has been developed to diagnostically compute visibility for the different categories of fog events, namely category-IIIB (CAT-IIIB) and category-IIIC (CAT-IIIC), using the meteorological variables. Out of 14 CAT-IIIB and 19 CAT-IIIC fog events, the 'WiFEX-in' could predict seven CAT-IIIB and 12 CAT-IIIC fog events, respectively. However, significant under-prediction was evident for the total CAT-IIIB fog hours and over-prediction for the total CAT-IIIC fog hours. It is found that the observed and predicted fog hour differences were related to the errors in the fog onset, dissipation, and magnitude of predicted liquid water content during CAT-IIIB and CAT-IIIC events and the same are discussed. WOS:000843086400002

Resumes are unstructured documents and the language used in the resume will be ambiguous and variable. Screening documents in large amounts is a difficult operation, and recruiters and hiring managers waste a lot of time going through each and every CV of the candidates. The extraction of valuable information from a resume is difficult due to this variability. It necessitates an urgent need to comprehend the context in which words are used. Using spaCy, a powerful natural language processing (NLP) package, this study suggests a machine learning method to phrase matching in resumes, focused on the extraction of specific entities. Like a human recruiter, it can examine and extract comprehensive information from resumes. While parsing, it maintains track of the terms in order to classify people. Specific Important entities are extracted from the resume document and then it is stored for later classification. Document ranking is processed and the final rankings are depicted in descending order with respect to the score of the resume in order to make it easy for the recruiters to shortlist the resumes quickly and efficiently. Recruiters may pick the needed applicants based on the scores rather than sifting through stacks of resumes from unqualified prospects.

Dense fog events and their micrometeorological characteristics and structural evolution at Indira Gandhi International Airport (IGIA), New Delhi, during the Winter Fog Experiment (WiFEX) are illustrated in this study. Four dense fog events that occurred in January 2016 for which visibility dropped below 200 m have been selected. Depending on the visibility and micrometeorological structure, the fog processes were classified into (i) an initial formation as a thermally stable optically thin fog and (ii) a subsequent mature, weakly unstable deep fog. Surface radiative cooling supported by a deep saturated layer in the nocturnal surface layer promotes the rapid development and intensification of the initial shallow fog into the extremely dense fog. Optically thin fog appeared to develop when a thin saturated layer of air formed near the ground under low-turbulence kinetic energy (

Production of non-centrifugal sugar (NCS) is a traditional business, practiced for a few centuries, however, mainly restricted to small-scale production. It is produced by concentrating sugarcane juice by evaporation. At present, the NCS production is declining owing to many drawbacks, mainly drudgery-driven labor-intensive work and energy-inefficient process. The revival of the NCS production process requires overcoming such challenges by developing the scientific understanding of each step. However, the reported scientific studies on NCS as a product and its production process are very limited. In this paper, we describe the current manufacturing practices involved in NCS production and presented data from field and laboratory experiments to provide a scientific basis behind each process. They include sugarcane selection, juice clarification, thermochemical treatments, crystallization, molding, etc. The role of these steps on the product quality is discussed in detail. Various experiments were conducted to understand the logic behind the artisanal skill used by producers for qualitative assessment of raw material, processing parameters, and product quality. The understanding provides more clarity on the influence of critical parameters related to the traditional process and so on the final product. Few recommendations have been provided to produce NCS of desired quality and longer shelf life. The understanding opens up avenues to improve the current process, scales it up to avail benefits of economy of scale, and also applies automation in the production for the consistent quality products with lesser drudgery.