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Journal of Integrated Science and Technology
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2321-4635
Published by Integrated Science Publishing Homepage  [3 journals]
  • Association of gender, age, and comorbidities with COVID-19 infection in

    • Authors: Sunita Kumari Yadav; Priya Bhardwaj, Praveen Gupta, Daman Saluja, Sunita Jetly, Jyoti Taneja
      Abstract: Due to a lack of data on various parameters with COVID-19 in the Indian population, this study was carried out to understand the relation among gender, age and comorbidities in Indian population. The data was collected using a questionnaire-based survey form that included questions on demographic characteristics, infection and any pre-underlying conditions (n=1146). The data showed that the male patients had suffered more from COVID-19 (58.6%). Also, the patients suffering from comorbidity are more likely to suffer from a severe form of COVID-19 and obesity/overweight was identified as the most prevalent (n=69) comorbid condition, followed by diabetes (n=35), thyroid (n=19) and hypertension (n=11). In severe COVID-19 cases, 85% of patients had a comorbid condition. In another study of COVID-19 hospitalized-cases, about 97% of patients were found to have an underlying medical condition. Among these, diabetes (55.9%) was identified as the most prevalent comorbidity. Males and older people are at a higher risk of developing COVID-19 infection in Indian population. The comorbid conditions also predisposed individuals to COVID-19 and aggravated the infection.
      PubDate: Mon, 25 Apr 2022 21:13:57 +053
  • An effective feature descriptor method to classify plant leaf diseases
           using eXtreme Gradient Boost

    • Authors: A Usha Ruby; Chaithanya B N, Swasthika Jain T J, Smita Darandale, Sudarshana Kerenalli, Renuka Patil
      Abstract: Identifying plant leaf diseases will be highly difficult due to the difficulties in gathering lesion characteristics from a quickly changing atmosphere, imbalanced illumination reflection of the incoming light source, and numerous other factors. A practical strategy for classifying plant leaf diseases is provided in this research. Using HSV, HU moments, and color histograms, we first created a leaf feature improvement framework that can enhance leaf characteristics in a complicated environment. Then, to increase feature classification capacity, a competent extreme boost method is modelled. Batch normalization is used to avoid network overfitting while also improving the model's resilience. The plant leaf disease feature improvement approach is favorable to boosting the efficiency of the XGBoost classification, as demonstrated in studies from various perspectives. For plant leaf disease photos obtained in the natural environment, our technique displays significant resilience, serving as a benchmark for the intelligent categorization of additional plant leaf diseases.
      PubDate: Sat, 05 Mar 2022 00:00:00 +053
  • Design of efficient S-box for Advanced Encryption Standard

    • Authors: Sarita Devanand Sanap; Vijayshree More
      Abstract: In digital era, data security is a necessary requirement. To establish secure communication modern encryption techniques plays a vital role. By employing an efficient S-box constraints of area, power and speed are achievable. In this paper method for efficient S-box is presented which provides promising solution in terms of required constraints. Comparison of proposed method with other existing method is also done by implementing it on field programmable gate array .It shows that proposed method uses only 6.14% slices resulting 13% improvement in comparison with other methods. Reduction in LUTs are done by 12.42 % in proposed method. Thus optimization is achieved in terms of number of slices and number of LUTs. Delay and memory usage is also reduced significantly.
      PubDate: Sat, 05 Mar 2022 00:00:00 +053
  • Review of computational approaches to model transcranial direct current
           stimulations tDCS and its effectiveness

    • Authors: Utkarsh Vinodchandra Pancholi; Vijay Dave
      Abstract: Neurological and psychological disorders are being treated by health professionals using medical technologies including drug therapy, electrical stimulation, and psychotherapy in some cases. Because of side effects caused by required drugs and social stigma for psychotherapy, these techniques have some limitations for their applicability in Mild cognitive impairment (MCI), Alzheimer’s disease (AD), Huntington disease (HD), dementia, major depressive disorder (MDD) and related neurological abnormalities.  Transcranial direct current stimulation is a non-invasive brain stimulation (NIBS) technique that uses small currents to alter characteristics of a healthy and diseased neuron. Even though sophisticated tDCS devices are being used for treatment, treatment protocol and its efficacy is still a debatable question. Researchers have found ways to model tDCS computationally to know the outcome of treatment. This review provides details of computational approaches used to model tDCS. We have reviewed clinical and computational practices carried out by researchers to model treatment modality for tDCS. 
      PubDate: Fri, 25 Feb 2022 12:49:30 +053
  • The COVID-19 havoc and clues from Sex disaggregated data in the Indian

    • Authors: Divya Bajaj; Varunendra Singh Rawat, Kanika Malik, Neetu Kukreja Wadhwa
      Abstract: The coronavirus infectious disease (COVID-19) has created a turmoil across the globe, with India emerging as one of the worst-hit countries. The Global scenario indicates a gender bias with a higher COVID-19 Case fatality rate (CFR) in males as opposed to females. However, countries like India, Nepal, Vietnam and Slovenia have reported a reverse trend in mortality. Real-time disaggregated data empowers countries to design more effective, sustainable, and people-centered approaches to treat and prevent COVID-19. Our study aimed to procure sex-disaggregated data in the Indian population by using a google form based online health survey. We have analyzed parameters like age, gender, occupation, sex and severity of infection based on CT score, steroid dependence, need for hospitalization, etc. The responses were evaluated by descriptive statistics by excluding arbitrary correlation. We found that the males were at a significantly greater risk of severe disease and mortality (~ twice) than females. We also found that the males as compared to females, presented almost eighteen times the odds of requiring intensive care unit (ICU) admission; reflecting severity of the infection. A sex-informed approach to COVID-19 research would reveal novel responses of the host immune system to SARS-CoV-2, which can then be utilized in formulation of policies for equitable health outcomes.
      PubDate: Fri, 25 Feb 2022 00:00:00 +053
  • Association of ABO blood group and antibody class with susceptibility and
           severity of COVID-19 infection in Indian Population

    • Authors: Jyoti Taneja; Priya Bhardwaj, Sunita K Yadav, Daman Saluja
      Abstract: Since the COVID-19 eruption in December 2019, the investigation has been focused on its treatment and preventing the disease spread. Currently, there is no biomarker available that can predict the predisposition and severity of COVID-19 infection. In the present study, we have used the cross-sectional survey study data to decipher the association between the ABO blood group and susceptibility, severity and breakthrough COVID-19 infections. Further, we have also investigated the association between antibody class and the risk of contracting COVID-19 infection. Our results indicated that individuals with blood group B had higher susceptibility to acquire COVID-19 infection. In contrast, blood group A was found to be associated with a low risk of acquiring severe COVID-19. In addition, we did not find any correlation between ABO blood groups and breakthrough COVID-19 infections. Further, we examined the association of antibodies; anti-A (blood groups B and O) and anti-B (blood groups A and O) with COVID-19 infection. The analysis of antibody classes showed that anti-A antibody associated with a high predisposition to acquire COVID-19 infection. The present study indicates that blood group B and anti-A antibodies are associated with proneness to COVID -19 infection and severity.
      PubDate: Fri, 25 Feb 2022 00:00:00 +053
  • Synthesis, spectral studies and biological activity of novel
           2-(substituted phenyl)-6-phenylimidazo[2,1-b]1,3,4-oxadiazole

    • Authors: Mandeep Kaur; Satvir Singh, Harpreet Kaur, Navni Sharma
      Abstract: Diverse series of 2-(substitutedphenyl)-6-phenylimidazo[2,1-b]1,3,4-oxadiazole were synthesized. Five of the synthesized compounds were evaluated for their anticancer activity on MCF-7 cancer cell lines. The recently synthesized compounds were illustrated by IR, 1HNMR. The anticancer activity of the compounds was carried out at Anti-Cancer Drug Screening Facility (ACDSF), Advanced Centre for Treatment, Research & Education in Cancer (ACTREC),Tata Memorial Centre, Kharghar, Navi Mumbai. The anticancer activity would be evaluated by In vitro testing using SRB assay protocols.All the screened compounds showed good to moderate activity against MCF-7 cancer cell line. Compound 5b, 6c, 7a were found to be active with GI50 <10 µg/ml.All the synthesized compounds were screened against Gram Positive and Gram Negative bacteria Streptococcus aureus, Bacillus subtilisand E.coli respectively.
      PubDate: Fri, 25 Feb 2022 00:00:00 +053
  • Context aware human activity prediction in videos using Hand-Centric
           features and Dynamic programming based prediction algorithm

    • Authors: S.N. Kakarwal; Ashwini Subhash Gavali
      Abstract: Activity prediction in videos deals with predicting human activity before it is fully observed. This work presents a context-aware activity prediction approach that can predict long-duration complex human activities from partially observed video. Here, we consider human poses and interacting objects as a context for activity prediction. The major challenges of context-aware activity predictions are to consider different interacting objects and to differentiate visually similar activity classes, such as cutting a tomato and cutting an apple. This article explores the use of hand-centric features for predicting human activity, consisting of various human-object interactions. A Dynamic Programming Based Activity Prediction Algorithm (DPAPA) is proposed for finding the future activity label based on observed actions. The proposed DPAPA algorithm do not employ Markovian dependencies or Hierarchical representation of activities, and hence is well suited for predicting human activities which are often Non-Markovian and Non-hierarchical. We evaluate results on MPPI Cooking activity dataset which consist of complex and long-duration activities.
      PubDate: Thu, 24 Feb 2022 00:00:00 +053
  • Quadratic difference expansion based Reversible Watermarking for
           relational database

    • Authors: Seema Babusingh Siledar; Sharvari Tamane
      Abstract: With the increase in usage of databases over the internet, it is becoming difficult to recognize genuine database owner. To protect ownership, digital watermarking has emerged as an effective solution. However, embedding watermark into database would result in loss of data quality.  Most state-of-the-art methods introduce distortion into the original data to a large extent.  In this work, reversible watermarking technique using quadratic difference expansion has been proposed. First, the numeric attributes with highest pearson correlation coefficient are selected to reduce distortion in the database.  The watermark is then generated by extracting bits from the selected attributes using quadratic difference expansion. Watermarked database is obtained after the generated watermark is embedded into the original database. To resolve ownership conflict, the genuine owner can easily extract watermark from watermarked database and recover original database. Indian Liver Patient dataset is used to conduct experiments. Results show that the proposed method is 100% robust against insertion attack. In case of 90% modification and 50% deletion atatck, it is observed that around 50% of the watermark can be recovered. Moreover, watermark embedding results in only 0.02% change in the mean of original database. It ensures that distortion caused due to watermarking leads to lower effect on data quality.
      PubDate: Sat, 04 Dec 2021 00:00:00 +053
  • Defected Top diamond shaped Patch Antenna for Multi-band operations

    • Authors: Rahmani Naveed Akhtar; Anupama A. Deshpande, A.K. Kureshi
      Abstract: A compact diamond-shaped antenna has been presented in this research work. This antenna has been designed to cover multiple technologies like WLAN, Wi-MAX, Bluetooth and applications included in S-band, C-band and X-Bands. The proposed antenna design has a diamond-shaped patch with half ground structure with notch and side cuts to achieve more efficient radiation patterns, and characteristic impedance is achieved. The presented antenna has dimensions 60×71.5×1.6 mm3, and the substrate is made of FR-4 material. The novel design and ground defections have achieved the proposed antenna’s wider operational impedance bandwidth of 9.954 GHz. In addition, its frequency bandwidth with VSWR<2 is from 1.294 GHz to 11.248 GHz, which covers multiple technologies like 5G networks, WLAN, Wi-MAX, Bluetooth, satellite and applications included in S-band, C-band and X-Bands or ultra-wideband (UWB). The optimized simulated geometry has a good match with the measured outcomes.
      PubDate: Sat, 04 Dec 2021 00:00:00 +053
  • Musical instrument recognition using audio features with integrated
           entropy method

    • Authors: Seema Chaudhary; Sangeeta Kakarwal, Ratnadeep Deshmukh
      Abstract: Lots of Musical content are uploaded on social media daily. It is time-consuming to search content according to our choice. Musical information retrieval is one of the evolving research fields which deals with retrieving content from audio data. Musical instrument recognition is subdomain of musical information retrieval. Previous research work had mostly focused on various western instruments belonging to distinct families, such as brass, string and woodwind are classified. The purpose of this study is to classify musical instruments using audio Features with Integrated Entropy method. Monophonic recordings of solo instrument artists are used in the experiments. Audio features have taken into account temporal, spectral, the first 13 Mel-frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients(GFCC). The proposed method generates a vector that integrates entropy with extracted features. Musical instruments are classified using generated vector. For classification, a Support Vector Machine (SVM) has been used.
      PubDate: Sat, 04 Dec 2021 00:00:00 +053
  • Onto_TML: Auto-labeling of topic models

    • Authors: Supriya Ashish Kinariwala; Sachin Deshmukh
      Abstract: Text mining is a new branch of AI that employs natural language processing techniques to convert unstructured text into a structured format for easier comprehension. It is becoming increasingly significant in practically every field since it allows users to extract information from large amounts of text or unstructured data. Topic modelling is one of the most important tools in text mining. Topic modelling aids in the discovery of hidden topics, which are the patterns of co-occurring words. Its purpose is to uncover hidden topics in massive amounts of unstructured data. However, because the topics detected are a list of the top n words in a topic, they may not give the viewer with a highly coherent image of the document. As a result, automatic topic labelling has been investigated in order to improve understanding of the topics. In this article we propose a novel method Onto_TML; ontology based auto-labelling for topic modelling algorithms and domain specific CEPS_ontology. Protégé tool is used to design CEPS_Ontology, comprises of four domains: Crime, Environment, Politics and Sports. Onto_TML uses CEPS_Ontology to assign appropriate generic label to the top words generated by topic modelling algorithms. For experimentation we have used two datasets News Headline dataset and News Category V-2 dataset and LDA, NMF and SeaNMF topic modeling algorithms. Empirical evaluation shows that Onto_TML has generated appropriate labels for the top words given by topic modeling algorithms
      PubDate: Thu, 02 Dec 2021 00:00:00 +053
  • Trans Fatty Acids: Sources, associated medical ailments and their
           alternatives - A recent advances review

    • Authors: Poonam Lakra; Indu Nashier Gahlawat, Manisha Wadhwa
      Abstract: Trans fatty acids finds extensive usage in the food industry. The vegetable ghee or Vanaspati obtained from partial hydrogenation of vegetable oil is primary source of trans fats. The trans fats are also naturally found in small amounts in dairy and meat products. The trans fats possess selected good functional properties like higher melting point and longer shelf life, but their use has been associated with a number of health issues like cardiovascular diseases, inflammation, diabetes, cancer, obesity, and allergy. Other adverse effects include increase in the total and LDL cholesterol and decrease HDL cholesterol values which further aggravates atherosclerosis. Several efforts have been initiated at national and international level to reduce the consumption of trans fats. In the Indian scenario, a multisectoral proactive approach at the production and consumer level is required to eliminate trans fats from the food supply.
      PubDate: Tue, 16 Nov 2021 06:51:45 +053
  • Chemical engineering of separation membrane, interfacial strategies, and
           mathematical modeling: a thorough analysis

    • Authors: Rajiv Kumar; Karuna Mahajan, Chinenye Adaobi Igwegbe, Anil K Aggarwal, M A Shah, Sangeetika X
      Abstract: The rapid advancement of membrane science and technology is dependent on significant advancements in the materials used in membrane  design, production, and modification. Membrane separation methods are mostly used in wastewater treatment, water isotope separation, acid concentration, and other applications. The primary goal of this review is to present the current principles and applications of various separation membrane technology, interfacial designs, transport, and separation processes through investigations and significant contributions framed in fields of its application. New nanotechnology-based materials have been used to overcome the constraints of the traditional membrane-separation technique; the most intriguing of efficient materials for the manufacture of nanocomposite membranes are the metal-organic frameworks (MOF)-based membranes. Analysis via mathematical modeling indicates a possibility of further improvement in recently developed smart membranes towards more advanced operations. The review discusses the membrane technology, latest methods, and materials developed along with computational aspects applied towards the concerning fundamental principles and practical applications of separation technology.
      PubDate: Fri, 05 Nov 2021 00:00:00 +053
  • Deep learning Convolutional Neural Network (CNN) for Cotton, Mulberry and
           Sugarcane Classification using Hyperspectral Remote Sensing Data

    • Authors: Kavita Bhosle; Bhakti Ahirwadkar
      Abstract: Crop Classification using remote sensing data is important for calculating crop sown area and predicting the crop production. Accuracy in data will help to regulate marketing of the produce. Present study aims to examine the use of deep learning convolutional neural network (CNN) to overcome the difficulties arising in crop identification with satellite images. In the present work, EO-1 Hyperion hyperspectral images have been used for identifying cotton, sugarcane and mulberry crop. Structured data has been extracted from hyperspectral data for performing experiments. Deep learning convolutional neural network (CNN) is compared with deep feed forward neural network (FFNN). It is observed that, deep learning CNN provided 99.33 % accuracy, while deep FFNN gave 96.6 % accuracy. Empirical results demonstrate that CNN works well in practice and compares appreciatively to deep FFNN methods. Moreover, deep learning CNN has demonstrated efficiently for smaller size dataset.
      PubDate: Thu, 04 Nov 2021 00:00:00 +053
  • Evaluation of cooling efficiency improvement of the simple office for
           small factories using heat dissipation with cold water circulation

    • Authors: Dong-Hyun Cho
      Abstract: This study was conducted to implement the improvement of heating efficiency by the cold water flowing in the X-L pipes inside the walls of a small room according to changes in the mass flow rate of the cold water. More comfortable cooling, which is also beneficial to health, was implemented. The radiant heat transfer cooling was implemented with the absorption of heat energy by the cold water flowing in the X-L pipes inside the walls of the small room without any movement or circulation of the air existing in the interior space of the room. In addition, this study significantly reduced heat energy consumption for radiant cooling and manufacturing costs by investigating accessories for cooling devices suitable for a room not larger than six square meter. As the flow rate of the cold water increased, the heating efficiency of the small room improved proportionally.
      PubDate: Tue, 24 Aug 2021 00:00:00 +053
  • Evaluation of spatial hierarchy in the Elderly Nursing facility according
           to the Circulating Flow system

    • Authors: Hyunmin Lee; Heangwoo Lee
      Abstract: Recently, various and diverse problems related to the elderly have emerged due to the rapid increase of the elderly population. Various studies have been conducted and various attempts are being made to solve these problems. As one of these attempts, the wards of elderly nursing homes are providing the elderly with sociality and autonomy through a circular movement system. This study is to build basic data that can be used to design the wards of elderly nursing homes by performing a quantitative analysis on the wards of elderly nursing homes which have a circular movement system. The analysis of this study results the J-Graph for the analysis target which shows a shallow annular J-graph type with a spatial depth of 7 or 8. This is because of the results of reflecting the design intention to increase the sociality and autonomy of the elderly by applying a circular movement system.
      PubDate: Sat, 21 Aug 2021 00:00:00 +053
  • Extraction of Oxygen-Enriched-Air from Water through Vapor Bubble

    • Authors: Jeong-A Hong; Jong-Soo Lee, Yong-Du Jun
      Abstract: Present study deals with the method of extracting dissolved gas from water and the characterization of the extracted gas in terms of its oxygen concentration and the possible extractable gas amount. This topic has at least two important aspects; one is on the usability of the extracted dissolved gas from water which is believed to have higher oxygen concentration than the atmosphere, and the other is on the achievable level of deaeration by using the present deaeration method. In the present study, a degassing process based on micro-vapor-bubble diffusion is proposed and theoretically reviewed based on the physical laws such as Henry’s law on solubility, Fick’s law of diffusion, and the vapor pressure of water as a condition for vapor bubble generation. An experimental apparatus is set up for the present study which is composed of a sealed water tank (0.65m×0.65m×1.0m, stainless steel) with pressure control, a micro-vapor-bubble generator, and the measurement system with sensors for oxygen (for gas mixture) and dissolved oxygen (for water) contents as well as for pressures and temperatures. The limiting extractable amount of dissolved gas from water and the oxygen concentration of the extracted gas mixture is successfully measured for demonstration through the present experimental work. Through the present study 5.9 liters of extract gas with oxygen concentration of 30% is captured out of 296 liters of water at room conditions of 17℃ and 1 atm.
      PubDate: Sat, 21 Aug 2021 00:00:00 +053
  • A study on the characteristics of Cooling Load due to the heat absorption
           of cold water circulating inside the Ocher Walls of small Cabins of one

    • Authors: Dong-Hyun Cho
      Abstract: This study was conducted to lay cold water X-L pipes inside the ocher walls of a cabin for one person and install cold water X-L pipes inside the cold water panels for radiant cooling with the absorption of thermal energy by the cold water for the first time at home and abroad. The air temperature distribution measured in an experimental study and the air temperature distribution shown in the results of simulations in this study were in good agreement. The air flow rate in the simulations was shown to be much lower than that of cooling by forced convective heat transfer, which is the existing cooling method. The results of simulations in this study verified that cooling is achieved by radiative heat transfer, which is beneficial to health. As the mass flow rate of the cold water circulating in the cold water X-L pipes increases, the air temperature inside the small cabin for one person decreased proportionally.
      PubDate: Sat, 21 Aug 2021 00:00:00 +053
  • A study on the internal and external factors influencing smart plant
           construction in perspective of fourth Industrial revolution (Industry 4.0)

    • Authors: Wonjong Kim; Hyun-chul Jang, Battumur Gerelmaa, Gantumur Khongorzul
      Abstract: This study aims to identify the key factors in Smart Plant construction. In this point, the factors which show influences on expectations for competitiveness were adapted from the previous studies, including organizational factors, technical factors, and environmental factors. In addition, the organizational factors are divided into two sub-dimensions, including leadership of top management, and competency development of organizational members. On the other hand, technical factors are divided into two sub-dimensions, including technology relevance, and risk-taking, while environmental factors consist of government support and influence of business partners. For the empirical study, a survey method has been conducted. To examine the research hypotheses, survey data have been gathered from employees in the related field and the factors have been analyzed by exploratory factor analysis, confirmatory factor analysis, and correlation analysis. Finally, the hypotheses were tested with structural equation model. The results of the study are expected to suggest academic and practical implications to the Smart Plant field.
      PubDate: Sat, 21 Aug 2021 00:00:00 +053
  • Synergistic effect of hybrid fillers on transport behavior of NR/EPDM

    • Authors: Manju V Nair; Anil Kumar S, Susan Joseph, Ajesh K Zachariah, Hanna J Maria, Sabu Thomas
      Abstract: Organically modified nanoclay (OMMT), silane modified halloysite nanotube (MHNT) and a hybrid of both modified nanoclay and halloysite nanotube were added to natural rubber (NR) and ethylene propylene diene rubber (EPDM) blend (60NR:40EPDM) matrix. The addition of these nanofillers affected the morphology and transport behaviour of the matrix considerably. The combinations of OMMT with MHNT having tubular morphology have shown specific result in synergistic behavior of solvent diffusion. The effect of nature of solvent and size of solvent molecule on the transport behavior of NR/EPDM blend nanocomposites in the presence of hybrid fillers were conducted. The cross-link density measurement and morphology analysis by TEM analysis confirms the filler networks and entrapped polymer chain segment. The quantity of immobilized polymer chain due to filler network formation has been determined by dynamic mechanical analysis and a nice connection was settled between the transport characteristics and polymer chain confinement. The analysis of swelling coefficients and diffusion parameters confirmed the excellent barrier property of NR/EPDM matrix filled with dual filler. The mode of transport through the rubber blend nanocomposites remained anomalous. Peppas-Sahlin model is well fitted with results.
      PubDate: Sat, 21 Aug 2021 00:00:00 +053
  • Assessing impact of Air Pollution on behavior of school children in
           Greater Noida, India

    • Authors: Vinod K. Shanwal
      Abstract: Pollution has become one of the most prevalent issues faced by all the countries around the world. Air pollution, the leading form of pollution, is known to cause many diseases like lung problems, early stoke, pulmonary diseases, respiratory infections. Along with physical problems, pollution leads to numerous behavioral and psychological issues. Children are the most vulnerable population that are effected by prolonged pollution. The relevance of worst effects of pollution on children is evident from number of studies that have been conducted over the decades. Despite the availability of vast literature about effects of pollution, there are less studies that focus on an in depth analysis of effects of pollution on children. There is lack of structured measures that can be followed to deal with harmful effects of pollution on children. The current study intends to evaluate the psychosocial implications of air pollution on the behavior of adolescents. It was a descriptive observable cohort study conducted on a sample of 85 school children by using structured interview schedule. The findings of the study indicates significant  influence of air pollution on the behavioral aspects of the children including dependency, confusion, cries a lot, required attention, restlessness and hyperactiveness.
      PubDate: Fri, 11 Jun 2021 15:55:36 +053
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