Search results for: Surabhi Singhal

Authors: Anant Sagar, Manisha Rana, Surabhi Singhal

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This study was aimed at analysing the effectiveness of manager-subordinate relationship and the different factors contributing to its effectiveness in a mid-sized IT organization. To define effectiveness in context of a manager-subordinate relationship, a model was framed which analyses personal and professional need fulfilment of subordinates. On basis of this need satisfaction based effectiveness model, relationships are categorized into four types anchored on two scales; Personal Need Satisfaction and Professional Need Satisfaction. These spatial effectiveness scores of a managerial relationship are further mapped with the relationship style of the manager to identify relationship styles which are associated with different effectiveness levels. The relationship style is analysed by using Impact Message Inventory-Circumplex (IMI-C). The results show that managerial relationship’s effectiveness is contingent on manager’s affiliation scores, subordinate’s previous work experience and the ability of managers to influence the personal and professional needs of employees through organizational policies. The findings reflect that effectiveness of manager-subordinate relationship increased in a friendly workplace where managers were adequately empowered to acknowledge employee needs.

Keywords: relationship effectiveness, need fulfilment, managerial style, impact message inventory-circumplex

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Authors: Gouresh Singhal, Rajib Kumar Panigrahi

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In this paper, we try to examine historical and technological changes in lighting industry. We propose a (proto) technical solution at block diagram and circuit level. Untapped and upcoming technologies such as Cloud and 6LoWPAN are further explored. The paper presents a robust hardware realistic design. A mobile application is also provided to provide last mile user interface. The paper highlights the current challenges to be faced and concludes with a pragmatic view of lighting industry.

Keywords: 6lowpan, internet of things, mobile application, led

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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Authors: Abhinav Singhal, Sanjeev A. Sahu

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Propagation of Rayleigh-type surface waves in an initially stressed piezomagnetic half- space with irregular boundary is investigated. The materials are assumed to be transversely isotropic crystals. The dispersion relations have been derived for electrically open and short cases. Effect of initial stress and corrugation have been shown graphically. It is also found that piezomagnetic material properties have an important effect on wave propagation. The result is relevant to the analysis and design of various acoustic surface wave devices constructed from piezomagnetic materials.

Keywords: corrugation, frequency equation, piezomagnetic, rayleigh-type wave

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Authors: Akshit Singhal, Xuan Wang, Zhijun Wang, Hao Che, Hong Jiang

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Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity to improve the throughput, reliability and network resource utilization. However, the existing solutions may discourage users to adopt the solutions in the face of multipath scenario where different paths are charged based on different pricing structures, e.g., WiFi vs cellular connections, widely available for mobile phones. In this paper, we propose a Hybrid MPTCP (H-MPTCP) with a built-in mechanism to incentivize users to use multiple paths with different pricing structures. In the meantime, H-MPTCP preserves the nice properties enjoyed by the state-of-the-art MPTCP solutions. Extensive real Linux implementation results verify that H-MPTCP can indeed achieve the design objectives.

Keywords: network, TCP, WiFi, cellular, congestion control

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Tripti Singhal, C. Tara Satyavathi, S. P. Singh, Aruna Kumar, Mukesh Sankar S., C. Bhardwaj, Mallik M., Jayant Bhat, N. Anuradha, Nirupma Singh

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Pearl millet is a climate-resilient nutritious crop. We report iron and zinc content QTLs from 3 divergent locations. The content of grain Fe in the RILs ranged between 36 and 114 mg/kg, and that of Zn from 20 to 106 mg/kg across the three years at over 3 locations (Delhi, Dharwad, and Jodhpur). We used SSRs to generate a linkage map using 210 F₆ RIL derived from the (PPMI 683 × PPMI 627) cross. The linkage map of 151 loci was 3403.6 cM in length. QTL analysis revealed a total of 22 QTLs for both traits at all locations. Inside QTLs, candidate genes were identified using bioinformatics approaches.

Keywords: yield, pearl millet, QTL mapping, multi-environment, RILs

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Authors: Vasudha Govil, Suresh Singhal

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Introduction: Patients with oropharyngeal masses pose a challenge for an anaesthetist in terms of ventilation and tracheal intubation. Thus, preoperative assessment and preparation become an integral part of managing such anticipated difficult airway cases. Case report: A 45- year old female presented with growth in the oropharynx causing dysphagia and hoarseness of voice. Clinical examination and investigations predicted a difficult airway. It was managed with fibreoptic nasotracheal intubation with a successful perioperative outcome. Tracheostomy was kept as plan B in case of the CVCI situation. Conclusion: Careful preoperative examination and assessment is required to prepare oneself for difficult airway. Fibreoptic bronchoscope-guided nasotracheal intubation in a spontaneously breathing patient is a safe and successful airway management technique in difficult airway cases.

Keywords: airway, difficult, mass, oropharyngeal

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Authors: Sanchay Vaidya, Sourabh Gupta, Gouresh Singhal

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There are various modes of transport in metro cities in India, auto-rickshaws being one of them. Auto-rickshaws provide connectivity to all the places in the city offering last mile connectivity. Among all the modes of transport, the auto-rickshaw industry is the most unorganized and inefficient. Although unions exist in different cities they aren’t good enough to cope up with the upcoming advancements in the field of technology. An introduction of simple technology in this field may do wonder and help increase the revenues. This paper aims to organize this segment under a single umbrella using GPS devices and mobile phones. The paper includes surveys of about 300 auto-rickshaw drivers and 1000 plus commuters across 6 metro cities in India. Carrying out research and analysis provides a base for the development of this model and implementation of this innovative technique, which is discussed in this paper in detail with ample emphasis given on the implementation of this model.

Keywords: auto-rickshaws, business model, GPS device, mobile application

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Authors: Surjeet Bakshi, Surabhi Sharma

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Objective: To assess the impact of educational sessions by reputed regional faculties on knowledge of primary care physicians on evidence based diabetes management methods and practice. Study Design: Retrospective pre-post intervention study. Methodology: Nine cities in Kerala from August to October, 2012 were selected for the study. 125 MBBS doctors participated in the study. 11 regional faculties provided six educational sessions throughout the period. Validated questionnaires were used to evaluate the knowledge of the participants on evidence based diabetes management methods before and after the intervention. Results: The mean score on pre-test was 8 and the mean score on post-test was 9. A paired t-test was conducted on participant’s pre- and post test score and the results were statistically significant (p<0.001). Conclusion: Even though the general attitude to and level of knowledge of diabetes management is good among the primary care physicians in India, there do exist some knowledge gaps which might influence their future practices when it comes to counselling and information on diabetes management methods. In the present study, the performance and awareness level of the participants have expressively improved among primary care physicians. There is a significant improvement in the test score and the training conducted. It seems that if such study programmes are included in the students study programme, it will give higher score in the knowledge and attitude towards diabetes management.

Keywords: diabetes, management, primary care physicians, evidence base, improvement score, knowledge

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Authors: Vipin Kumar Singhal, Rohit Kumar Mittal, Pavitra Ranjan Maiti

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Damage analysis is one of the preliminary activities to be done after an earthquake so as to enhance the seismic building design technologies and prevent similar type of failure in future during earthquakes. This research article investigates the damage pattern and most probable reason of failure by observing photographs of seven major buildings collapsed/damaged which were evenly spread over the region during Mw7.8, Nepal earthquake 2015 followed by more than 400 aftershocks of Mw4 with one aftershock reaching a magnitude of Mw7.3. Over 250,000 buildings got damaged, and more than 9000 people got injured in this earthquake. Photographs of these buildings were collected after the earthquake and the cause of failure was estimated along with the severity of damage and comment on the reparability of structure has been made. Based on observations, it was concluded that the damage in reinforced concrete buildings was less compared to masonry structures. The number of buildings damaged was high near Kathmandu region due to high building density in that region. This type of damage analysis can be used as a cost effective and quick method for damage assessment during earthquakes.

Keywords: Nepal earthquake, damage analysis, damage assessment, damage scales

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Authors: Rama Bhargava, Surabhi Nishad

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The infusion of nanofluids has dramatically enhanced the heat-carrying capacity of the fluids, applicable to many engineering and medical process where the temperature below freezing is required. Cryosurgery is an efficient therapy for the treatment of cancer, but sometimes the excessive cooling may harm the nearby healthy cells. Efforts are therefore done to develop a model which can cause to generate the low temperature as required. In the present study, a mathematical model is developed based on the bioheat transfer equation to simulate the heat transfer from the probe on a tumor (with irregular domain) using the hybrid technique consisting of element free Galerkin method with αα-family of approximation. The probe is loaded will nano-particles. The effects of different nanoparticles, namely Al₂O₃, Fe₃O₄, Au on the heat-producing rate, is obtained. It is observed that the temperature can be brought to (60°C)-(-30°C) at a faster freezing rate on the infusion of different nanoparticles. Besides increasing the freezing rate, the volume of the nanoparticle can also control the size and growth of ice crystals formed during the freezing process. The study is also made to find the time required to achieve the desired temperature. The problem is further extended for multi tumors of different shapes and sizes. The irregular shape of the frozen domain and the direction of ice growth are very sensitive issues, posing a challenge for simulation. The Meshfree method has been one of the accurate methods in such problems as a domain is naturally irregular. The discretization is done using the nodes only. MLS approximation is taken in order to generate the shape functions. Sufficiently accurate results are obtained.

Keywords: cryosurgery, EFGM, hybrid, nanoparticles

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Madhurima S. Waghmare, Shaleen Singhal

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The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Surabhi Pandey, Pavuluri Srinivasa Rao

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Extrusion processing is a high-temperature short time (HTST) treatment which can improve protein quality and digestibility together with retaining active nutrients. In-vitro protein digestibility of plant protein-based foods is generally enhanced by extrusion. The current study aimed to investigate the effect of extrusion cooking on in-vitro protein digestibility (IVPD) and conformational modification of protein in green banana flour extrudates. Green banana flour was extruded through a co-rotating twin-screw extruder varying the moisture content, barrel temperature, screw speed in the range of 10-20 %, 60-80 °C, 200-300 rpm, respectively, at constant feed rate. Response surface methodology was used to optimise the result for IVPD. Fourier-transform infrared spectroscopy (FTIR) analysis provided a convenient and powerful means to monitor interactions and changes in functional and conformational properties of extrudates. Results showed that protein digestibility was highest in extrudate produced at 80°C, 250 rpm and 15% feed moisture. FTIR analysis was done for the optimised sample having highest IVPD. FTIR analysis showed that there were no changes in primary structure of protein while the secondary protein structure changed. In order to explain this behaviour, infrared spectroscopy analysis was carried out, mainly in the amide I and II regions. Moreover, curve fitting analysis showed the conformational changes produced in the flour due to protein denaturation. The quantitative analysis of the changes in the amide I and II regions provided information about the modifications produced in banana flour extrudates.

Keywords: extrusion, FTIR, protein conformation, raw banana flour, SDS-PAGE method

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Authors: Surabhi Agrawal Kohli, Sunita Gupta, Esha Khanuja, Parul Garg, P. Gupta

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Background: Adenomyosis is a common gynaecological condition that affects the menstruating women. Uterine enlargement, dysmenorrhoea, and menorrhagia are regarded as the cardinal clinical symptoms of adenomyosis. Classically it was thought, compared with ultrasonography, when adenomyosis is suspected, MRI enables more accurate diagnosis of the disease. Materials and Methods: 172 subjects were enrolled after an informed consent that had complaints of HMB, dyspareunia, dysmenorrhea, and chronic pelvic pain. Detailed history of the enrolled subjects was taken, followed by a clinical examination. These patients were then subjected to TVS where myometrial echo texture, presence of myometrial cysts, blurring of endomyometrial junction was noted. MRI was followed which noted the presence of junctional zone thickness and myometrial cysts. After hysterectomy, histopathological diagnosis was obtained. Results: 78 participants were analysed. The mean age was 44.2 years. 43.5% had parity of 4 or more. heavy menstrual bleeding (HMB) was present in 97.8% and dysmenorrhea in 93.48 % of HPE positive patient. Transvaginal sonography (TVS) and MRI had a sensitivity of 89.13% and 80.43%, specificity of 90.62% and 84.37%, positive likelihood ratio of 9.51 and 5.15, negative likelihood ratio of 0.12 and 0.23, positive predictive value of 93.18% and 88.1%, negative predictive value of 85.29% and 75% and a diagnostic accuracy of 89.74% and 82.5%. Comparison of sensitivity (p=0.289) and specificity (p=0.625) showed no statistically significant difference between TVS and MRI. Conclusion: Prevalence of 30.23%. HMB with dysmenorrhoea and chronic pelvic pain helps in diagnosis. TVS (Endomyometrial junction blurring) is both sensitive and specific in diagnosing adenomyosis without need for additional diagnostic tool. Both TVS and MRI are equally efficient, however because of certain additional advantages of TVS over MRI, it may be used as the first choice of imaging. MRI may be used additionally in difficult cases as well as in patients with existing co-pathologies.

Keywords: adenomyosis, heavy menstrual bleeding, MRI, TVS

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Authors: Manju Kanu, Subrata Sinha, Surabhi Johari

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Viral proteins of Ebola viruses belong to one of the best studied viruses; however no effective prevention against EBOV has been developed. Epitope-based vaccines provide a new strategy for prophylactic and therapeutic application of pathogen-specific immunity. A critical requirement of this strategy is the identification and selection of T-cell epitopes that act as vaccine targets. This study describes current methodologies for the selection process, with Ebola virus as a model system. Hence great challenge in the field of ebola virus research is to design universal vaccine. A combination of publicly available bioinformatics algorithms and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertypes Human Leukocyte Antigen (HLA) alleles. MUSCLE and MOTIF tools were used to find out most conserved peptide sequences of viral proteins. Immunoinformatics tools were used for prediction of immunogenic peptides of viral proteins in zaire strains of Ebola virus. Putative epitopes for viral proteins (VP) were predicted from conserved peptide sequences of VP. Three tools NetCTL 1.2, BIMAS and Syfpeithi were used to predict the Class I putative epitopes while three tools, ProPred, IEDB-SMM-align and NetMHCII 2.2 were used to predict the Class II putative epitopes. B cell epitopes were predicted by BCPREDS 1.0. Immunogenic peptides were identified and selected manually by putative epitopes predicted from online tools individually for both MHC classes. Finally sequences of predicted peptides for both MHC classes were looked for common region which was selected as common immunogenic peptide. The immunogenic peptides were found for viral proteins of Ebola virus: epitopes FLESGAVKY, SSLAKHGEY. These predicted peptides could be promising candidates to be used as target for vaccine design.

Keywords: epitope, b cell, immunogenicity, ebola

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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Authors: Abhishek Sharma, Amit Gupta, Manish Singhal

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Background: The management of patients with penetrating neck injuries in the prehospital setting and in the emergency department has evolved with regard to the use of multidetector computed tomographic (MDCT) imaging. Hence, there is a shift in the management of neck injuries from mandatory exploration in certain anatomic areas to more conservative approach using imaging and so-called “no zone approach”. Objective: To study the no zone approach in the management of penetrating neck injury using routine imaging in all stable patients. Methods: 137 patients with penetrating neck injury attending emergency department of level 1 trauma centre at AIIMS between 2008–2014 were retrospectively analysed. All hemodynamically stable patients were evaluated using CT scanning. Results: Stab injury is most common (55.91%) mode of pni in civilian population followed by gunshot(18.33%). The majority of patients could be managed with imaging and close observation. 39 patients (28.46%) required operative intervention. The most common indication for operative intervention was vascular followed by airway injury manifesting as hemodynamic destabilisation.There was no statistical difference between the zonal distribution of injuries in patients managed conservatively and those taken to OR. Conclusions: Study shows that patients with penetrating neck trauma who are haemodynamically stable and exhibit no “hard signs” of vascular injury or airway injury may be evaluated initially by MDCT imaging even when platysma violation is present. “No Zone” policy may be superior to traditional zone wise management.

Keywords: penetrating neck injury, zone approach, CT scanning, multidetector computed tomographic (MDCT)

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

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Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Surabhi Gautam, Uma Kumar, Rima Dada

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A sustained acute-phase response in Rheumatoid Arthritis (RA) is associated with increased joint damage and inflammation leading to progressive disability. It is induced continuously by consecutive stimuli of proinflammatory cytokines, following a wide range of pathophysiological reactions, leading to increased synthesis of acute phase proteins like C - reactive protein (CRP) and dysregulation in levels of immunomodulatory soluble Human Leukocyte Antigen-G (HLA-G) molecule. This study was designed to explore the effect of yoga and meditation based lifestyle intervention (YMLI) on inflammatory markers in RA patients. Blood samples of 50 patients were collected at baseline (day 0) and after 30 days of YMLI. Patients underwent a pretested YMLI under the supervision of a certified yoga instructor for 30 days including different Asanas (physical postures), Pranayama (breathing exercises), and Dhayna (meditation). Levels of CRP, IL-6, IL-17A, soluble HLA-G and erythrocyte sedimentation rate (ESR) were measured at day 0 and 30 interval. Parameters of disease activity, disability quotient, pain acuity and quality of life were also assessed by disease activity score (DAS28), health assessment questionnaire (HAQ), visual analogue scale (VAS), and World Health Organization Quality of Life (WHOQOL-BREF) respectively. There was reduction in mean levels of CRP (p < 0.05), IL-6 (interleukin-6) (p < 0.05), IL-17A (interleukin-17A) (p < 0.05) and ESR (p < 0.05) and elevation in soluble HLA-G (p < 0.05) at 30 days compared to baseline level (day 0). There was reduction seen in DAS28-ESR (p < 0.05), VAS (p < 0.05) and HAQ (p < 0.05) after 30 days with respect to the base line levels (day 0) and significant increase in WHOQOL-BREF scale (p < 0.05) in all 4 domains of physical health, psychological health, social relationships, and environmental health. The present study has demonstrated that yoga practices are associated with regression of inflammatory processes by reducing inflammatory parameters and regulating the levels of soluble HLA-G significantly in active RA patients. Short term YMLI has significantly improved pain perception, disability quotient, disease activity and quality of life. Thus this simple life style intervention can reduce disease severity and dose of drugs used in the treatment of RA.

Keywords: inflammation, quality of life, rheumatoid arthritis, yoga and meditation

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Authors: Dhanashree Moghe, Roberta Bullingham, Rizwan Ahmed, Tarun Singhal

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Aim: The NHS Bowel Screening Programme recommends the use of endoscopic tattooing for suspected malignant lesions that later require surgical or endoscopic localisation, using local protocols as guidance. This is in accordance with guidance from the BSG (The British Society of Gastroenterologists). We used a well-recognised local protocol as a standard to audit current tattooing practice in a large district general hospital with no current local guidelines. Method: A retrospective quantitative analysis of 50 patients who underwent segmental colonic resection for cancer over a 6-month period in 2021. We reviewed historic electronic endoscopy reports recording relevant data on tattoo indication and placement. Secondly, we carried out an anonymous survey of 16 independent lower GI endoscopists on self-reported details of their practice. Results: In our study, 28 patients (56%) had a tattoo placed at the time of their colonoscopy. Of these, only 53% (n=15) had the tattoo distal to the lesion, with the measured distance of the tattoo from the lesion only being documented in 8 reports. Only seven patients (25%) had a circumferential (4 quadrant) placement of the tattoo. 13 patients had lesions either in the caecum or rectum, locations deemed unnecessary as per BSG guidelines. Of the survey responses collected, there were four different protocols being used to guide practice. Only 50% of respondents placed tattoos at the correct distance from the lesion, and 83% placed the correct number of tattoos. Conclusion: There is a lack of standardisation of practices in colonic tattooing demonstrated in our study with incomplete compliance to our standard. The inadequate documentation of tattoo location can contribute to confusion and inaccuracy in the intraoperative localisation of lesions. This has the potential to increase operation length and morbidity. There is a need to standardise both technique and documentation in colonoscopic tattooing practice.

Keywords: colorectal cancer, endoscopic tattooing, colonoscopy, NHS BSCP

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Authors: Shimayali Kaushal, Nitesh Priyadarshi, Nitin Kumar Singhal

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Food borne bacterial species have been identified as major pathogens in most of the severe pathogen-related diseases among humans which result in great loss to human health and food industry. Conventional methods like plating and enzyme-linked immune sorbent assay (ELISA) are time-consuming, laborious and require specialized instruments. Nanotechnology has emerged as a great field in case of rapid detection of pathogens in recent years. The AuNRs material has good electro-optical properties due to its larger light absorption band and scattering in surface plasmon resonance wavelength regions. By exploiting the sugar-based adhesion properties of microorganism, we can use the glycoconjugates capped gold nanorods as a potential nanobiosensor to detect the foodborne pathogen. In the present study, polyethylene glycol (PEG) coated gold nanorods (AuNRs) were prepared and functionalized with different types of carbohydrates and further characterized by UV-Visible spectrophotometry, dynamic light scattering (DLS), transmission electron microscopy (TEM). The reactivity of above said nano-biosensor was probed by lectin binding assay and also by different strains of foodborne bacteria by using spectrophotometric and microscopic techniques. Due to the specific interaction of probe with foodborne bacteria (Escherichia coli, Pseudomonas aeruginosa), our nanoprobe has shown significant and selective ablation of targeted bacteria. Our findings suggest that our nanoprobe can be an ideal candidate for selective optical detection of food pathogens and can reduce loss to the food industry.

Keywords: glyco-conjugates, gold nanorods, nanobiosensor, nanoprobe

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Authors: A. Kumar, D. Himanshu, Ak Vaish, K. Usman , A. Singh, R. Misra, V. Atam, S. P. Verma, S. Singhal

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Introduction: Resistant and uncontrolled hypertension offer great challenge, in terms of higher risk of morbidity, mortality and not the least, difficulty in diagnosis and management. Our study tries to identify the importance of two crucial aspects of hypertension management, i.e. drug compliance and optimum dosing and also the effect of spironolactone on blood pressure in cases of resistant hypertension. Methodology: A prospective study was carried out among patients, who were referred as case of resistant hypertension to Hypertension Clinic at Gandhi memorial and associated hospital, Lucknow, India from August, 2013 to July 2014. A total of 122 Subjects having uncontrolled BP with ≥3 antihypertensives were selected. After ruling out secondary resistance and with appropriate lifestyle modifications, effect of adherence and optimum doses was seen with monitoring of BP. Only those having blood pressure still uncontrolled were true resistant. These patients were given spironolactone to see its effect on BP over next 12 weeks. Results: Mean baseline BP of all (n=122) patients was 150.4±7.2 mmHg systolic and 92.1±5.7 mmHg diastolic. After promoting adherence to the regimen, there was reduction of 4.20±3.65 mmHg systolic and 2.08±4.74 mmHg Diastolic blood pressure, with 26 patients achieving target blood pressure goal. Further reduction of 6.66±5.99 mmHg in systolic and 2.59±3.67 mmHg in diastolic BP was observed after optimizing the drug doses with another 66 patients achieving target blood pressure goal. Only 30 patients were true resistant hypertensive and prescribed spironolactone. Over 12 weeks, mean reduction of 20.62±3.65 mmHg in systolic and 10.08 ± 6.46 mmHg in diastolic BP was observed. Out of these 30, BP was controlled in 24 patients. Side effects observed were hyperkalemia in 2 patients and breast tenderness in 2 patients. Conclusion: Improper adherence and suboptimal regimen appear to be the important reasons for uncontrolled hypertension. By virtue of maintaining proper adherence to an optimum regimen, target BP goal can be reached in many without adding much to the regimen. Spironolactone is effective in patients with resistant hypertension, in terms of blood pressure reduction with minimal side effects.

Keywords: resistant, hypertension, spironolactone, blood pressure

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Authors: Michelle V. Tomczak, Reyhaneh Bakhtiari, Aaron Granley, Anthony Singhal

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Objective: Cannabis and cocaine are associated with a range of mental and physical effects that can impair aspects of human behavior. Driving is a complex cognitive behavior that is an essential part of everyday life and can be broken down into many subcomponents, each of which can uniquely impact road safety. With the growing movement of jurisdictions to legalize cannabis, there is an increased focus on impairment and driving. The purpose of this study was to identify driving-related cognitive-performance deficits that are impacted by recreational drug use. Design and Methods: With the assistance of law enforcement agencies, we recruited over 300 participants under the influence of various drugs including cannabis and cocaine. These individuals performed a battery of computer-based tasks scientifically proven to be re-lated to on-road driving performance and designed to test response-speed, memory processes, perceptual-motor skills, and decision making. Data from a control group with healthy non-drug using adults was collected as well. Results: Compared to controls, the drug group showed def-icits in all tasks. The data also showed clear differences between the cannabis and cocaine groups where cannabis users were faster, and performed better on some aspects of the decision-making and perceptual-motor tasks. Memory performance was better in the cocaine group for simple tasks but not more complex tasks. Finally, the participants who consumed both drugs performed most similarly to the cannabis group. Conclusions: Our results show distinct and combined effects of cannabis and cocaine on human performance relating to driving. These dif-ferential effects are likely related to the unique effects of each drug on the human brain and how they distinctly contribute to mental states. Our results have important implications for road safety associated with driver impairment.

Keywords: driving, cognitive impairment, recreational drug use, cannabis and cocaine

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Authors: Mudrika Singhal

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The research paper is basically about how the genetically modified organisms evolved and their significance in today’s world. It also highlights about the various pros and cons of the genetically modified organisms and the progress of India in this field. A genetically modified organism is the one whose genetic material has been altered using genetic engineering techniques. They have a wide range of uses such as transgenic plants, genetically modified mammals such as mouse and also in insects and aquatic life. Their use is rooted back to the time around 12,000 B.C. when humans domesticated plants and animals. At that humans used genetically modified organisms produced by the procedure of selective breeding and not by genetic engineering techniques. Selective breeding is the procedure in which selective traits are bred in plants and animals and then are domesticated. Domestication of wild plants into a suitable cultigen is a well known example of this technique. GMOs have uses in varied fields ranging from biological and medical research, production of pharmaceutical drugs to agricultural fields. The first organisms to be genetically modified were the microbes because of their simpler genetics. At present the genetically modified protein insulin is used to treat diabetes. In the case of plants transgenic plants, genetically modified crops and cisgenic plants are the examples of genetic modification. In the case of mammals, transgenic animals such as mice, rats etc. serve various purposes such as researching human diseases, improvement in animal health etc. Now coming upon the pros and cons related to the genetically modified organisms, pros include crops with higher yield, less growth time and more predictable in comparison to traditional breeding. Cons include that they are dangerous to mammals such as rats, these products contain protein which would trigger allergic reactions. In India presently, group of GMOs include GM microorganisms, transgenic crops and animals. There are varied applications in the field of healthcare and agriculture. In the nutshell, the research paper is about the progress in the field of genetic modification, taking along the effects in today’s world.

Keywords: applications, mammals, transgenic, engineering and technology

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Authors: Bliss Singhal

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Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

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Authors: Suneet Jagdev, Siddharth Singhal, Dhrubajyoti Bordoloi, Peesari Vamshidhar Reddy

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There is no universally accepted definition of what constitutes a Smart City. It means different things to different people. The definition varies from place to place depending on the level of development and the willingness of people to change and reform. It tries to improve the quality of resource management and service provisions for the people living in the cities. Smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions in a secure fashion to manage the assets of a city. But most of these projects are misinterpreted as being technology projects only. Due to urbanization, a lot of informal as well government funded settlements have come up during the last few decades, thus increasing the consumption of the limited resources available. The people of each city have their own definition of Smart City. In the imagination of any city dweller in India is the picture of a Smart City which contains a wish list of infrastructure and services that describe his or her level of aspiration. The research involved a comparative study of the Smart City models in India and in China. Behavioral changes experienced by the people living in the pilot/first ever smart cities have been identified and compared. This paper discussed what is the target of the quality of life for the people in India and in China and how well could that be realized with the facilities being included in these Smart City projects. Logical and comparative analyses of important data have been done, collected from government sources, government papers and research papers by various experts on the topic. Existing cities with historically grown infrastructure and administration systems will require a more moderate step-by-step approach to modernization. The models were compared using many different motivators and the data is collected from past journals, interacting with the people involved, videos and past submissions. In conclusion, we have identified how these projects could be combined with the ongoing small scale initiatives by the local people/ small group of individuals and what might be the outcome if these existing practices were implemented on a bigger scale.

Keywords: behavior change, mission monitoring, pilot smart cities, social capital

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Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger

Abstract:

Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.

Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia

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