Assessment of prevalence and risk factors of postnatal depression in postnatal mothers
Background: Affective disorders occur commonly in postpartum period, ranging in severity from mild and transient “baby blues” experienced by 50–80 % of women to postpartum psychosis which affects <1 % of women . Postpartum major depression lies along this spectrum of postnatal mood disorder. The debilitating effects of postpartum depression (PPD) can involve an entire family, and women afflicted with PPD are at high risk for recurrent depression. Majority of them exhibit symptoms by 6 week postpartum and if not treated, many women continue to be depressed at the end of the first postpartum year. Despite its serious consequences and amenity to treatment, PPD often remains unrecognized. Numerous studies carried out in developed countries provide compelling evidence that postnatal depression is associated with long term emotional, cognitive, and intellectual problems in children Materials & Methods: Non-experimental exploratory descriptive research designed is used to conduct the study. Non-Probability Purposive sampling technique was used to select the samples and Sample size was 140 postnatal mothers. Edinburgh Postnatal depression scale, standardized research tool and self structured risk factors questionnaires were used for data collection. The reliability of research tool is 0.75, which is reliable. Result: The study results showed the majority of samples (60%) 84 postnatal mothers is having mild depression, (22%) 31 postnatal mothers are having moderate depression and (18%) 25 postnatal mothers are having severe depression. Chi square was calculated to analyzed the association between the prevalence and risk factors of postnatal depression among postnatal mothers findings revealed that there was significant association between prevalence and risk factors with complications during pregnancy, self history of depression, family history of depression and condition of baby It emphasizes that the planned teaching programme on postnatal depression prevention, care and treatment can reduce the prevalence of postnatal depression. It may minimize the complications and reduce the morbidity rate due to postnatal depression. Keywords: Postnatal Depression, Prevalence, Risk factors, Postnatal mothers
Published by: Marylin Shinde
Author: Marylin Shinde
Paper ID: V7I3-1915
Paper Status: published
Published: June 17, 2021
Gypsum Plaster
Alabaster is a form of gypsum used both in building and as a plaster material. Gypsum was discovered near Paris, and “Plaster of Paris” became popular building material. Gypsum plaster is investigated experimentally at fire temperatures with respect to their thermophysical properties i.e., thermal conductivity, effective heat capacity, and density. It is shown that depending on different ingredients (carbonates) different endothermic reactions occur between room temperature and 900°C. These reactions strongly influence the temperature dependence of the mentioned properties which in turn affect the response of the material to fire. Based on these experimental results the thermal reaction of a gypsum-protected steel column in fire is modeled for the four types of gypsum. The results of numerical simulations demonstrate clearly the advantages caused by certain ingredients of the chemical composition of gypsum plaster.
Published by: Shriyash Bhondve
Author: Shriyash Bhondve
Paper ID: V7I3-1908
Paper Status: published
Published: June 16, 2021
A rare case of Factor XIII Deficiency and spontaneous rupture of the Spleen
Introduction Factor XIII deficiency is an extremely rare occurrence & a patient presenting with spontaneous rupture of the spleen is challenging to diagnose and manage. Case Report We present here a case report of a patient diagnosed to have factor XIII deficiency since early childhood, presenting with acute onset abdominal pain with hemorrhagic shock at middle age. On evaluation, the Patient was found to have spontaneous splenic rupture which was managed by emergency splenectomy with adequate blood products transfusion. Conclusion Factor XIII plays a major role in the final step of the coagulation cascade in stabilizing fibrin clot & factor XIII deficiency is a very rare inherited or acquired disorder. Manifestations of factor XIII deficiency vary from being asymptomatic to life-threatening hemorrhagic conditions. Patients may have to be dependent on repeated specific blood product transfusions in order to avoid bleeding diathesis.
Published by: Niket Shah, Babu Elangovan, K. Sreenivasan
Author: Niket Shah
Paper ID: V7I3-1896
Paper Status: published
Published: June 16, 2021
Obstacles and possible enablers to corporate governance practices in Yemen
The main objective is to measure and evaluate the stakeholders’ views regarding the barriers and potential enablers to the application of corporate governance in Yemen. Executives and internal auditors work in the banking sector as internal stakeholders and external auditors as external stakeholders. A questionnaire is the data collection tool. The study concluded that 'the spread of corruption in the government sector is the most crucial barrier. Simultaneously, 'the cost of applying governance is higher than its benefits' is the least affected barrier. In contrast, enhancing professional accounting and auditing bodies, the inclusion of corporate governance in the University Education program; the adoption of international accounting and auditing standards are the most crucial enablers. A study recommended that the government should update financial and supervisory laws and legislations, and the executive authority should monitor their implementation, supporting the anti-corruption process, establish the stock market, spreading the concept of governance in Yemeni society, adding corporate governance as a scientific subject taught in universities and develop and implement training programs to raise the awareness of corporate governance among employees.
Published by: Aiman Alasbahi, Ishwara P.
Author: Aiman Alasbahi
Paper ID: V7I3-1903
Paper Status: published
Published: June 16, 2021
Deploying Plant Tissue Culture Simulation use case for E-Infrastructures
E-Infrastructures can be defined as networked tools, data, and resources that support a community of practice (CoP), broadly including all those who participate in and benefit from research. During the UNESCO-HP BGI project (2009-2012), the University of Nigeria team conducted experiments on plant tissue culture under the theme, “sustaining the plant tissue culture component of grid computing”. Plant Tissue culture is a method for plant propagation under in vitro conditions. Different types and parts of plants (known as explants) may be cultivated in vitro. Because plant tissue culture is still in its empirical stage, it is time-consuming, cost-intensive, and manpower demanding. These necessitated the design and development of a plant tissue culture simulation application that predicts explant yields using multiple regression models. The initial version that was developed during the BGI project with a prediction accuracy of about 67%, unfortunately, was not deployable on an e-infrastructure like the grid or the cloud. Hence, during the Sci-GaIA project (2014-2017), a use case for the development of a newer version, Plantisc2, that is deployable on e-infrastructure was proposed. The outcome of which is reported in this paper.
Published by: Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe
Author: Dr. Collins N. Udanor
Paper ID: V7I3-1825
Paper Status: published
Published: June 16, 2021
Automatic Helmet Detection and License plate recognition using CNN and GAN
Enforcing use of helmet on every bike- rider is mandatory nowadays because of high accident rate and poor road conditions. There are laws regarding safety measures which ensure use of helmet. But for now, they involve manual intervention which is not so effective as of now because bike-riders sometimes tend to escape without any penalty/fine after breaking the safety rules like wearing a helmet while riding. Automation is better way to deal with this problem but automation in this area comes with its own challenges. To name a few, Low quality image frames (low image resolution, pixel density etc.), rain, dew and fog and partly hidden faces. The robustness of detection methodology strongly depends on the strength of extracted features and also the ability to deal with the lower quality of extracted data. The first goal of this project is to boost the potency of helmet detection and then recognizing the license number plate recognition. This model consists of many essential steps developed using today’s most advanced amp; optimized CNN, GAN models amp; libraries. It is a classification based model that uses supervised learning approach to train CNN and Character Segmentation algorithm. The proposed helmet detection model can be used to detect helmet and recognizes license plate even in adverse conditions using character segmentation and CNN.
Published by: Pranav Sanjay Patil, Damini Kailas Pawar, Shruti Vilas Bairagi, Varun Deepak Bharambe, Nilesh Wankhede
Author: Pranav Sanjay Patil
Paper ID: V7I3-1885
Paper Status: published
Published: June 16, 2021
