Temporality: Living Through the Time While Doing Doctoral Studies

Doctoral students’ experiences of stay and study abroad determine how they experience and understand time in relation to other existential themes of body, space, and relation. The present study aimed to understand what meanings doctoral students’ assign to time while doing their doctoral studies in different public universities of Austria. Thirteen participants were recruited purposively to understand how did they experience time and how did their experience of time determine the way they live and study in a university and complete their doctoral studies. The questions were explored through conducting and recording the interviews in a semi-structured form and subsequently transcribing and analyzing the transcripts. The participants experienced that time continuously shaped their life experiences with respect to the space they lived in, relationality, and corporeal experiences. The students experienced time as an agent of pressure, perceived as being slow or fast in their studies, feeling connected or disconnected with their family, work and study and a tool to gauge their work performance and completion of their studies. The study has a phenomenological significance of understanding of time as experienced by a group of doctoral students that led to the way they lived, stayed and studied abroad

Quality and Usefulness of Data: Investigating the Discrepancies in Pakistani Public School Data and Implications for the Way Forward

The quality school data contributes to reliable decision making in the school education system. The data provided by different organizations should be consistent, valid and complement each other to establish its quality and usefulness. The present study purports to explore the discrepancies among the different data sources that have implications for improving the quality and usefulness of school data. The available school data from various sources of school education was used followed by an explanation through semi-structured interviews with the teachers employing an explanatory mixed methods design. The results revealed that there were substantial discrepancies among varying school data sources that did not reflect the ‘real’ work efficiency of the schools and the school authorities excessively rely on such data for significant decision-making. This leads to a risk of bringing meaningless reforms in the school education system. These discrepancies found in the school data sources have implications for improving the existing practices of data collection and a performance appraisal mechanism in schools

OCT Angiography-based Evaluation of the Choriocapillaris in Neovascular Age Related Macular Degeneration

Neovascular age-related macular degeneration (AMD) can lead to rapid, irreversible vision loss in untreated eyes. While the pathogenesis of neovascular AMD remains incompletely understood, the choriocapillaris has been hypothesized as the initial site of injury. Due to limitations of dye-based angiography, in vivo imaging of the choriocapillaris has been a longstanding challenge. However, the clinical introduction of optical coherence tomography angiography (OCTA) has enabled researchers and clinicians to noninvasively image the choriocapillaris vasculature, allowing the evaluation of the choriocapillaris in eyes with a variety of pathologies. In this perspective, we review important OCTA-based findings regarding choriocapillaris impairment in neovascular AMD and discuss limitations and future directions of OCTA technologies in the context of this disease

A Review of the Implementation of NumPy and SciPy Packages in Science and Math

In the Python programming language, there are a number of simple case studies of scientific computing. It gives you a multidimensional array object, a lot of organisms (like arrays and masked arrays), and many fast ways to work with arrays. SciPy, which is also called "Sigh Pie," is free math, science, and engineering software. The NumPy library is what the SciPy library is built on. This makes it easy and quick to work with arrays with N dimensions. The SciPy library is made to work with NumPy arrays in particular. It has a lot of easy-to-use and effective numerical methods, like scalar optimization and integration. They work well together, are free, and are easy to set up on all common operating systems. NumPy and SciPy are both easy to learn and use. This paper explains the most popular application of these packages in math-focused scientific researc

Comparative Expression Studies of Fiber Related Genes in Cotton Spp.

Cotton fibers are the seed trichomes that are developed around the seed and are used to make clothes and yarn for the textile industry. Expression profiling of cotton fiber genes is very important to estimate the differential gene expression level at different fiber developmental stages. Expression analysis of fiber developing genes are very important to enhance the fiber length of cotton. The expression profiling of three gene families in five stages (0, 5, 10, 15 and 20 DPA) of cotton fiber tissues was carried out through real-time PCR. Expression analysis revealed that transcripts of GA-20 Oxidase, XTH, and PEPc were elevated from 5 to 20 days post-anthesis (DPA) fibers. Total RNA was extracted from various stages of cotton fiber development and was reverse transcribed to cDNA for PCR amplification. For data normalization, 18s rRNA was used as an internal control. The objective of this study was to explore the expression level of fiber developing genes at specific stages of fiber development. The results showed that most of the genes were expressed during the elongation phase in between 5 DPA to 15 DPA. Results obtained from this study may be helpful for the further identification of fiber genes and the improvement of fiber characteristics in cotton. PEPc and XTH genes that are expressed with a high rate during the fiber development may be used in breeding programmes for the improvement of fiber quality and quantity

Top Python-Based Deep Learning Packages: A Comprehensive Review

Deep learning has transformed artificial intelligence (AI) by empowering machines to execute intricate functions with unparalleled precision. The field claims an array of robust packages and libraries, among which Python, a prominent and celebrated programming language, has emerged as a pivotal choice for deep learning study and development. Python has become a leading language in deep learning due to its simplicity and the vast array of libraries available for developers and researchers.  This article thoroughly examines the most broadly adopted deep learning packages within the Python system. The packages under scrutiny include TensorFlow, PyTorch, Keras, Theano, and Caffe. We exactly assess each of these packages to establish their typical features and capabilities. Moreover, the review explores into an in-depth analysis of the assets and weaknesses inherent in each package. This detailed exploration prepares readers with the information necessary to make informed decisions regarding the variety of the most suitable packages custom-made to their specific needs. This comprehensive review aims to propose a nuanced understanding of the landscape of popular deep learning packages and support practitioners and researchers in creation strategic and well-informed choices for their deep learning actions

Frequency of pregnancy induced hypertension and its association with elevated serum beta human chorionic gonadotropin levels during mid trimester of pregnancy

Objective: To determine the frequency of PIH amongst elevated beta-hCG levels and non-elevated beta-hCG in the mid-trimester of pregnancy. Materials and Methods: It was Descriptive case series conducted for six months (02-12-2019 to 02-06-2020) in OPD of Gynae Unit-II, Holy Family Hospital, Rawalpindi. A total of one hundred and twenty-two (n=122) normotensive pregnant females at 13-20 weeks gestational age and 18-35 years of maternal age were selected in this study after informed consent from every patient. The frequency of PIH in patients with elevated serum beta-hCG was measured. Data were analyzed using SPSS version 20. Effect modifiers were controlled by stratification. A p-value of ≤ 0.05 was considered significant. Results: Mean beta-hCG levels in the total study population were found to be 7305.09±3900.64 IU/mL. Median b-hCG levels in our study population were noted as 6936.15 IU/mL. Pregnancy-induced hypertension was found positive in 16 (13.1%) patients. Raised beta-hCG levels were present in 10 (8.2%) patients. The frequency of PIH in raised beta-HCG levels was found in 7/10 (70%) of patients. We found a statistically significant (p-value ≤ 0.05) difference in the frequency of PIH among patients with elevated and not-elevated beta-hCG levels. Conclusion: It is evident from my study that patients with raised levels of serum β-hCG during mid-trimester pregnancy are at increased risk to develop hypertensive disorders of pregnancy. We further elaborated that there is a statistically significant difference in various effect modifiers such as maternal age, gestational age, residential status, and BMI  for developing  PIH among patients with elevated and non-elevated beta-hCG levels

Emerging Trends in Peripartum Hysterectomy; A High Alert in Obstetrics

Introduction: The high incidence of lower segment caesarean section (LSCS) leading to morbidly adherent placenta and making it a leading cause of peripartum hysterectomy.Objective: Peripartum hysterectomy is one of the major obstetrical procedures that need to be performed electively/emergency in patients having morbidly adherent placenta (MAP) for the sake of the patient’s life. Need to conduct this study arises because we want to highlight the increasing rate of peripartum hysterectomy secondary to MAP, the emerging trend of increased LSCS in our socio-demographic strata, and its effects on maternal morbidity and mortality.Materials and Methods: This was a retrospective study which was carried out in the Department of Obstetrics and Gynaecology Unit II, Holy Family Hospital, Rawalpindi. All patients who underwent peripartum hysterectomy were included in the study. Data was collected from record files and labor room registers in accordance with ethical guidelines.Results: Out of 11,440 deliveries in one year, 60 patients underwent peripartum hysterectomy with an incidence of 5.2 per 1000 deliveries. The majority of patients (87%) fell in the age group of 25-33 years. 4(6.6%) patients undergone peripartum hysterectomy for postpartum hemorrhage (PPH) due to uterine atony, 3(5%) due to the ruptured uterus, and 53(88%) due to MAP. All patients who had undergone a peripartum hysterectomy due to MAP were previously scarred for LSCS (100%). 5% with previous 1 LSCS, 31% with previous 2 LSCS, 44% with previous 3 LSCS and 18% with previous 4 LSCS.Conclusion: The high incidence of peripartum hysterectomies in young patients secondary to MAP highlights the need for critical review and audit of indications of primary LSCS and repeat LSCS. It also highlights the need for expertise at the time of surgery to decrease the rate of maternal morbidity and mortality