The maternal and fetal outcome of repeat previous one caesarean section

Background: The rates of adverse maternal and neonatal outcomes have increased significantly in the last decade. Patients with repeated caesarean deliveries also have a greater risk of placenta previa, placenta accrete, uterine rupture, bowel and bladder injury, and unplanned hysterectomy.Methods: This retrospective study was performed between 01 April 2017 to 31 March 2021, at a private hospital to know about the surgical difficulties and maternal and neonatal complications encountered in cases of repeated LSCS. The outcome of 1028 women admitted with a history of previous LSCS was studied.Results: The 613 patients were given a trial of labour. 40.07% of patients delivered normally. The most common indication for repeat LSCS was CPD in 20.94% and fetal distress 20.12%. The most common complication observed was adhesion in 37.65%. Scar dehiscence in 8.92 %, scar rupture in 0.64%, uterine atony in 4.8%, placenta previa in 3.57%, placenta accrete in 0.64%, injury to the bladder was seen in 0.97%, caesarean hysterectomy was done in only 2 cases and gaped wound was found in 1.13% of cases. 19.15% of neonates were admitted to NICU. Apgar score <7 at 5 minutes in 14.77%. premature neonates were 8.44% RDS was found in 7.62%, birth asphyxia was found in 2.92% cases and neonatal sepsis was found in 1.13%.Conclusions: The dramatic increase in caesarean section rates over the past three decades has been associated with a corresponding increase in maternal morbidity but there a continuous decrease in neonatal morbidity and mortality rates because of advances in neonatal medicine

MalDet-Malware Detection Using Deep Learning and LSTM based Approach to Classify Malware

Computer security requires malware detection. Recent research manually uncovers hazardous features using machine learning-based techniques. MalDet, a cutting-edge malware detection method, is recommended in this paper. MalDet classifies malware using a stacking ensemble and learns from grayscale images and opcode sequences using CNN and LSTM networks. According to the evaluation, MalDet's malware detection validation accuracy is 99.89%. MalDet outperforms other previous research with 99.36% detection accuracy and a significant detection speedup on the Microsoft malware dataset. We classified nine malware families for MalDet

A study to assess knowledge and attitude of antenatal women about maternal nutrition attending a tertiary care centre

Background: Nutrition is the fundamental pillar of human life. All human beings need a balanced amount of nutrients for proper functioning of body system. Inadequate nutrition during pregnancy has a negative impact on the pregnant mother as well as short and long term consequences on the newborn. This study aims to assess knowledge and attitude of antenatal women about maternal nutrition in pregnancy and highlights the need of interventions aimed at promoting awareness about healthy diet during pregnancy in association with various socio demographic factors.Methods: This study was conducted on 850 antenatal women attending the antenatal clinic of UISEMH, Kanpur, Uttar Pradesh, India from August 2015 to February 2016. A 25 point- 10 minute questionnaire was designed to collect information about awareness and myths associated with nutrition in pregnancy from antenatal women.Results: Only 22 % of the women had good knowledge about nutrition during pregnancy and 82% showed willingness to acquire more information about maternal nutrition. Source of information for most pregnant women were immediate family members (41%). Most women were lacking in their knowledge about common local sources of nutrition, adequate weight gain during pregnancy and effects of over and under nutrition.Conclusions: There is need to impart more knowledge to pregnant women about nutrition in pregnancy. More attention should be paid on nutritional guidance among pregnant women especially in young and less well educated women for healthy outcome of mother and babies. This study emphasizes the importance of dietary counselling by attending doctors as an integral part of antenatal care

Game Theory-Based Authentication Framework to Secure Internet of Vehicles with Blockchain

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV's openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities' areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework's credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the suggested framework achieves greater security and functionality characteristics and provides lower transaction and computation overhead than many of the available solutions so far. However, these solutions never considered the prime concerns of physical cloning and side-channel attacks. However, the framework in this paper is capable of handling them along with all the other security attacks the previous work can handle. Finally, the suggested framework has been subjected to a blockchain implementation to demonstrate its efficacy with duel gaming to achieve authentication in addition to its capability of using lower burdened blockchain at the physical layer, which current blockchain-based authentication models for IoVs do not support

Removal of Reactofix Red 3BFN from industrial effluent using adsorption techniques

680-683Wheat husk has been used to adsorb dye using a series of batch experiments. Langmuir model provides best correlation of experimental data. Isotherms have also been used to obtain thermodynamic parameters such as free energy, enthalpy and entropy of adsorption. Various parameters (pH, adsorbent dose, initial dye concentration, temperature, particle size etc.) were optimized

Clinical Outcome of Post placental PPIUCD in a Primigravida Women Delivering by Caesarean Section

Objective- To assess the safety and efficacy of post-partum IUCD during ceasarean section in a primigravida women. Method: This prospective observational study includes 100 women, who gave informed consent for post-partum intrauterine device insertion during cesarean section from Oct 2018 to Oct 2019 in the department of Obstetrics and Gynaecology, GMC Shivpuri associated District hospital Shivpuri Madhya Pradesh. The patients were followed up at 4-6 wk and at 3 months. Result: A total of 100 primigravida women underwent postpartum intracesarean insertion of CuT-375. The most common post insertion complication observed in the immediate post-operative period was wound infection (8%) and febrile morbidity (5%) majority of women (88%)had hospital stay b/w 5-8 days .The common adverse events observed during follow up at 3 month were pelvic pain, menstrual irregularity and other genralized complaints. At the end of 3 months cumulative expulsion, removal, pregnancy/ failure, and continuation rates are 2%, 6%, 0% and 92% respectively. Conclusion- Post placental intracesarean CuT- 375 insertion in primigravida women is a safe and effective method of reversible contraceptive with low expulsion and high continuation rate

Game theory-based authentication framework to secure internet of vehicles with blockchain

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV’s openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities’ areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework’s credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the suggested framework achieves greater security and functionality characteristics and provides lower transaction and computation overhead than many of the available solutions so far. However, these solutions never considered the prime concerns of physical cloning and side-channel attacks. However, the framework in this paper is capable of handling them along with all the other security attacks the previous work can handle. Finally, the suggested framework has been subjected to a blockchain implementation to demonstrate its efficacy with duel gaming to achieve authentication in addition to its capability of using lower burdened blockchain at the physical layer, which current blockchain-based authentication models for IoVs do not support