Active management of third stage of labour with special reference to misoprostol

Active management of third stage of labour is an effective method of preventing postpartum hemorrhage. It includes administration of uterotonic immediately after delivery of the baby, delaying cord clamping for at least 1-3 minutes to reduce rates of infant anaemia, performing controlled cord traction for removing the placenta and postpartum vigilance, ie, assess the uterine tone to ensure a contracted uterus; and continue to check every 15 minutes for 2 hours. If there is uterine atony, fundal massage should be performed and patient should be monitored more frequently. Though oxytocin is the best drug for routine prophylaxis, misoprostol is a relatively newer drug which is now included in the various guidelines for prevention and treatment of postpartum hemorrhage. It can be used as an effective and safe drug in areas with poor access to skilled healthcare providers and facilities

Role of diagnostic hysterolaparoscopy in evaluation of female infertility

Background: Infertility affects 10-15% of reproductive age couples. Routine pelvic examination and usual diagnostic procedures can miss majority of the pelvic pathologies. Hysterolaparoscopy is an effective tool for diagnosing these pathologies and additionally therapeutic procedures, like polypectomy, myomectomy, septal resection and adhesiolysis, can be done in the same sitting. Objective of present study was to determine the role of diagnostic hysterolaparoscopy for evaluating the causes of infertility.Methods: It was a prospective study conducted at the Department of OBGY from September 2015 to August 2016. Patients aged 20-40 years with infertility were included in the study. The prevalence of different lesions was analysed.Results: Out of the 30 patients studied, most had primary infertility. Laparoscopic abnormalities (56.6%) were more common than hysteroscopic abnormalities (36.6%). Adnexal adhesions (26.6%) was the most common abnormality detected on laparoscopy, while the common intra-uterine pathologies were uterine septum and synechiae.Conclusions: Hysterolaparoscopy may be recommended as the procedure of choice for evaluation of female infertility, which are usually missed by imaging modalities

Comparative study of maternal and foetal outcome in instrumental vaginal deliveries

Background: The art of instrumental vaginal delivery is fading as more and more obstetricians resort to caesarean sections. Instrumental deliveries are deliveries accomplished with the use of vacuum device or forceps. Once either is applied to the foetal head, outward traction generates forces that augment maternal pushing to deliver the foetus vaginally. Objective of present study was to compare the maternal and foetal outcome of forceps versus ventouse delivery.Methods: It was a prospective observational study conducted in Sassoon Hospital between January 2014 to January 2015. A total of 120 cases, 60 each of forceps and ventouse, admitted in labour room were included in the study. Maternal and neonatal morbidity were compared in terms of perineal lacerations, episiotomy extension, post-partum haemorrhage, Apgar score, instrumental injuries. Chi square test and z test of proportion was used to analyze the data.Results: Maternal morbidity, namely episiotomy extension as well as perineal tears were significant in the forceps group. With regards to neonatal morbidity, no statistically significant difference was noted.Conclusions: Vacuum and forceps should remain appropriate tools in the armamentarium of the modern obstetrician. However, ventouse may be chosen first (if there is no foetal distress) as it is significantly less likely to injure the mother

Data mining for vehicle telemetry

This paper presents a data mining methodology for driving condition monitoring via CAN-bus data that is based on the general data mining process. The approach is applicable to many driving condition problems and the example of road type classification without the use of location information is investigated. Location information from Global Positioning Satellites and related map data are often not available (for business reasons), or cannot represent the full dynamics of road conditions. In this work, Controller Area Network (CAN)-bus signals are used instead as inputs to models produced by machine learning algorithms. Road type classification is formulated as two related labelling problems: Road Type (A, B, C and Motorway) and Carriageway Type (Single or Dual). An investigation is presented into preprocessing steps required prior to applying machine learning algorithms, namely, signal selection, feature extraction, and feature selection. The selection methods used include Principal Components Analysis (PCA) and Mutual Information (MI), which are used to determine the relevance and redundancy of extracted features, and are performed in various combinations. Finally, as there is an inherent bias towards certain road and carriageway labellings, the issue of class imbalance in classification is explained and investigated. A system is produced, which is demonstrated to successfully ascertain road type from CAN-bus data, and it is shown that the classification correlates well with input signals such as vehicle speed, steering wheel angle, and suspension heigh

Data mining for vehicle telemetry

This article presents a data mining methodology for driving-condition monitoring via CAN-bus data that is based on the general data mining process. The approach is applicable to many driving condition problems, and the example of road type classification without the use of location information is investigated. Location information from Global Positioning Satellites and related map data are often not available (for business reasons), or cannot represent the full dynamics of road conditions. In this work, Controller Area Network (CAN)-bus signals are used instead as inputs to models produced by machine learning algorithms. Road type classification is formulated as two related labeling problems: Road Type (A, B, C, and Motorway) and Carriageway Type (Single or Dual). An investigation is presented into preprocessing steps required prior to applying machine learning algorithms, that is, signal selection, feature extraction, and feature selection. The selection methods used include principal components analysis (PCA) and mutual information (MI), which are used to determine the relevance and redundancy of extracted features and are performed in various combinations. Finally, because there is an inherent bias toward certain road and carriageway labelings, the issue of class imbalance in classification is explained and investigated. A system is produced, which is demonstrated to successfully ascertain road type from CAN-bus data, and it is shown that the classification correlates well with input signals such as vehicle speed, steering wheel angle, and suspension height

Innovative biofilm inhibition and anti-microbial behavior of molybdenum sulfide nanostructures generated by microwave-assisted solvothermal route

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A Sensitive Search for Supernova Emission Associated with the Extremely Energetic and Nearby GRB 221009A

We report observations of the optical counterpart of the long gamma-ray burst (LGRB) GRB 221009A. Due to the extreme rarity of being both nearby ($z = 0.151$) and highly energetic ($E_{\gamma,\mathrm{iso}} \geq 10^{54}$ erg), GRB 221009A offers a unique opportunity to probe the connection between massive star core collapse and relativistic jet formation across a very broad range of $\gamma$-ray properties. Adopting a phenomenological power-law model for the afterglow and host galaxy estimates from high-resolution Hubble Space Telescope imaging, we use Bayesian model comparison techniques to determine the likelihood of an associated SN contributing excess flux to the optical light curve. Though not conclusive, we find moderate evidence ($K_{\rm{Bayes}}=10^{1.2}$) for the presence of an additional component arising from an associated supernova, SN 2022xiw, and find that it must be substantially fainter ($<$ 67% as bright at the 99% confidence interval) than SN 1998bw. Given the large and uncertain line-of-sight extinction, we attempt to constrain the supernova parameters ($M_{\mathrm{Ni}}$, $M_{\mathrm{ej}}$, and $E_{\mathrm{KE}}$) under several different assumptions with respect to the host galaxy's extinction. We find properties that are broadly consistent with previous GRB-associated SNe: $M_{\rm{Ni}}=0.05$ - $0.25 \, \rm{M_\odot}$, $M_{\rm{ej}}=3.5$ - $11.1 \, \rm{M_\odot}$, and $E_{\rm{KE}} = (1.6$ - $5.2) \times 10^{52} \, \rm{erg}$. We note that these properties are weakly constrained due to the faintness of the supernova with respect to the afterglow and host emission, but we do find a robust upper limit on the $M_{\rm{Ni}}$ of $M_{\rm{Ni}}<0.36\, \rm{M_\odot}$. Given the tremendous range in isotropic gamma-ray energy release exhibited by GRBs (7 orders of magnitude), the SN emission appears to be decoupled from the central engine in these systems.Comment: 18 pages, accepted to ApJL, 4 tables, 5 figures. Updated abstract in Previe

Fast-transient Searches in Real Time with ZTFReST: Identification of Three Optically-discovered Gamma-ray Burst Afterglows and New Constraints on the Kilonova Rate

While optical surveys regularly discover slow transients like supernovae on their own, the most common way to discover extragalactic fast transients, fading away in a few nights, is via follow-up observations of gamma-ray burst and gravitational-wave triggers. However, wide-field surveys have the potential to also identify rapidly fading transients independently of such external triggers. The volumetric survey speed of the Zwicky Transient Facility (ZTF) makes it sensitive to faint and fast-fading objects as kilonovae, the optical counterparts to binary neutron stars and neutron star-black hole mergers, out to almost 200Mpc. We introduce an open-source software infrastructure, the ZTF REaltime Search and Triggering, ZTFReST, designed to identify kilonovae and fast optical transients in ZTF data. Using the ZTF alert stream combined with forced photometry, we have implemented automated candidate ranking based on their photometric evolution and fitting to kilonova models. Automated triggering of follow-up systems, such as Las Cumbres Observatory, has also been implemented. In 13 months of science validation, we found several extragalactic fast transients independent of any external trigger (though some counterparts were identified later), including at least one supernova with post-shock cooling emission, two known afterglows with an associated gamma-ray burst, two known afterglows without any known gamma-ray counterpart, and three new fast-declining sources (ZTF20abtxwfx, ZTF20acozryr, and ZTF21aagwbjr) that are likely associated with GRB200817A, GRB201103B, and GRB210204A. However, we have not found any objects which appear to be kilonovae; therefore, we constrain the rate of GW170817-like kilonovae to $R < 900$Gpc$^{-3}$yr$^{-1}$. A framework such as ZTFReST could become a prime tool for kilonova and fast transient discovery with the Vera C. Rubin Observatory

Fast-transient Searches in Real Time with ZTFReST: Identification of Three Optically Discovered Gamma-Ray Burst Afterglows and New Constraints on the Kilonova Rate

The most common way to discover extragalactic fast transients, which fade within a few nights in the optical, is via follow-up of gamma-ray burst and gravitational-wave triggers. However, wide-field surveys have the potential to identify rapidly fading transients independently of such external triggers. The volumetric survey speed of the Zwicky Transient Facility (ZTF) makes it sensitive to objects as faint and fast fading as kilonovae, the optical counterparts to binary neutron star mergers, out to almost 200 Mpc. We introduce an open-source software infrastructure, the ZTF REaltime Search and Triggering, ZTFReST, designed to identify kilonovae and fast transients in ZTF data. Using the ZTF alert stream combined with forced point-spread-function photometry, we have implemented automated candidate ranking based on their photometric evolution and fitting to kilonova models. Automated triggering, with a human in the loop for monitoring, of follow-up systems has also been implemented. In 13 months of science validation, we found several extragalactic fast transients independently of any external trigger, including two supernovae with post-shock cooling emission, two known afterglows with an associated gamma-ray burst (ZTF20abbiixp, ZTF20abwysqy), two known afterglows without any known gamma-ray counterpart (ZTF20aajnksq, ZTF21aaeyldq), and three new fast-declining sources (ZTF20abtxwfx, ZTF20acozryr, ZTF21aagwbjr) that are likely associated with GRB200817A, GRB201103B, and GRB210204A. However, we have not found any objects that appear to be kilonovae. We constrain the rate of GW170817-like kilonovae to R &lt; 900 Gpc-3 yr-1 (95% confidence). A framework such as ZTFReST could become a prime tool for kilonova and fast-transient discovery with the Vera Rubin Observatory