Use of intracervical Foley catheter for pre-induction cervical ripening in women planned for vaginal birth after previous caesarean section

Background: Vaginal birth after previous caesarean section is challenging for obstetricians due to increased risk of uterine rupture. Common methods for labour induction in post caesarean pregnancies are membrane sweeping, balloon catheters, prostaglandins (PGE2), and oxytocin. As currently available data is limited, the evidence of safest method of induction is lacking. The present study aimed to assess the effectiveness of intra-cervical Foley catheter for pre-induction cervical ripening in women planned for vaginal birth after caesarean section.Methods: This prospective cross-sectional study included 24 pregnant women with a history of previous caesarean section, admitted for induction of labour. Induction was performed in patients with unfavourable modified Bishop Score by intra-cervical Foley catheter. The change in modified Bishop Score, oxytocin requirement, induction-delivery interval, mode of delivery, maternal complications and neonatal outcome were observed.Results: There was significant improvement in modified BS noted at the end of trans-cervical Foley catheter induction and this improvement in mean of modified BS was observed to be statistically significant (p<0.0001). The vaginal delivery rate was 29.2% while 70.8% of patients underwent caesarean section. No significant maternal or foetal complications were observed with Foley catheter induction except for one case of vaginal bleeding. There was no case of intrapartum or postpartum maternal infection.Conclusions: Foley catheter may be a cheap and effective method for pre-induction cervical ripening and induction of labour in patients with previous caesarean section

What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling

We introduce the self-Relative Binding Free Energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model. The results of this validation provide evidence that a significant fraction of the errors observed in benchmark studies reflect the statistical fluctuations of unconverged estimates rather than the models' accuracy. Furthermore, we find that ligand reorganization is a significant contributing factor to the statistical variance of binding free energy estimates and that metadynamics-accelerated conformational sampling of torsional degrees of freedom of the ligand can drastically reduce the time to convergence

Pulmonary rehabilitation improves functional outcomes and quality of life in post-SARS-CoV-2 mild-to-moderate infection patients: a pilot study

: SARS-CoV-2 infection impairs functional outcomes and quality of life, even in its mild-to-moderate form. It is therefore appropriate to draw attention to the role played by respiratory rehabilitation and physiotherapists in the pulmonary rehabilitation process that post-SARS-CoV-2 patients must undergo. We enrolled 80 patients in a prospective case-control study; 40 cases (mild-to-moderate post-SARS-CoV-2 infection patients) and 38 control subjects (i.e. patients affected by other respiratory diseases) completed a full pulmonary rehabilitation cycle. 6 Minute Walking Distance, Borg CR10 Scale, modified Medical Research Council (mMRC) Dyspnoea scale, EuroQoL EQ-5D-3L questionnaire, Barthel scale, arterial blood gas test and peripheral oxygen saturation (SpO2) were compared for all patients before and after rehabilitation. All patients experienced significant improvements in all parameters analyzed, except for arterial blood gas test. Results were similar for both groups, in particular both groups experienced improvements in mMRC scale, EuroQoL questionnaire, Barthel scale and 6-minute walking distance. Pulmonary rehabilitation appears to improve exercise tolerance, dyspnea and quality of life in patients recovering from mild-to-moderate SARS-CoV-2 infection. Further studies are needed on larger sample size population to validate these results

Transparency and traceability in the textile value chain

A textile and apparel value chain is one of the most important customer commodity industries with long linear supply chains. They are considered to be among the most polluting industries globally (Niinimäki et al., 2020; Virta and Räisänen, 2021). The textiles sector contributes to 8–10% of global climate change (Quantis, 2018; UNFCCC, 2018). For example, garment manufacturing requires large amounts of water and energy in fibres and textile production. Pollution and vast land use are additional problems. Without proper treatment before discharge, wet processing wastewater contains harmful chemicals that can contaminate exhaust air, wastewater, and the fabric itself, causing severe ecological damage. Moreover, the overproduction and overconsumption of apparel products haveled to a massive load on landfills. All these reasons and more make it critical to understand,evaluate, and reform the functioning of this value chain with the help of new technologies and digitalisation

Leukemic transformation in myelodysplastic syndrome: A case report with review of risk factors

Myelodysplastic syndromes are a group of clonal disorders affecting the hemopoietic stem cells and characterized by peripheral&nbsp;cytopenias with normocellular to hypercellular bone marrow and various morphological abnormalities in one or more hemopoietic&nbsp;cell lines. MDS carries a high risk of progression to acute myeloid leukemia especially in subtypes with increased myeloblasts.&nbsp;Here, we present the case of leukemic transformation in MDSin a 41-year-old male who presented with complaints of generalized&nbsp;weakness, loss of appetite for 2 months and fever on and off for 1 week. The patient was diagnosed as MDS-multilineage dysplasia&nbsp;after blood examination and bone marrow biopsy but the patient refused for further treatment

Discoloration of Teeth: A Literature Review

The psychological and social impact of tooth staining on patient has been greatly reported. Tooth staining may be the result of different etiological factors, it may have different appearances, location and severity. Tooth discoloration is mainly caused by intrinsic and extrinsic factors. There are various types of treatment available and it depends upon the underlying etiology and depth of the lesion. Treatment can be microabrasion of enamel, bleaching, veneers and crowns

A Hybrid Approach for Data Hiding using Cryptography Schemes

Abstract -The use of internet increases for communication and for other more aspects. There are number of Cryptography scheme that used to increase security where we discuss about the confidential information transfer. As unauthorized access &amp; data loss increases so, in this work we proposed a hybrid approach to hide secret data in other file that it can&apos;t be lost or accessed by unauthorized user. This hybrid technique can be proposed by using advance hill cipher and DES to enhance the security which can be measured by calculating PSNR &amp; MSE values. This technique is a new technique for hiding text data behind the image file and increase the security

La gestion du big data par l’intelligence artificielle dans la chaîne d'approvisionnement de l'industrie textile : opportunités et défis

L’industrie de l'habillement a bénéficié, au cours de la dernière décennie, de l'application de big data et de l'intelligence artificielle pour résoudre divers problèmes commerciaux. Face à la concurrence accrue sur le marché et aux attentes des clients en matière de personnalisation, ces industriels sont en permanence à la recherche des moyens d'améliorer leurs stratégies commerciales afin d'accroître leur rapidité et leur rentabilité. A cet égard, les solutions de gestion de big data offrent aux enseignes de la distribution textile la possibilité d'explorer leur chaîne d'approvisionnement et d'identifier les ressources de données importantes. Ces ressources précieuses, rares et inimitables permettent de créer des stratégies axées sur les données (data-driven) et d'établir des capacités dynamiques à maintenir dans un environnement commercial incertain. Grâce à ces stratégies data-driven, les enseignes de prêt-à-porter sont en mesure de confectionner des vêtements de façon intelligente afin de fournir à leurs clients un article adapté à leurs besoins et, par conséquent, d'adopter des pratiques de consommation et de production durables.Dans ce contexte, la thèse étudie les avantages de l'utilisation de big data et de l'intelligence artificielle (IA) dans les entreprises de l'habillement, afin d'améliorer leurs opérations commerciales tout en recherchant des opportunités de gestion de big data à l'aide de solutions d'IA. Dans un premier temps, cette thèse identifie et classifie les techniques d'IA qui peuvent être utilisées à différents stades de la chaîne d'approvisionnement pour améliorer les opérations commerciales existantes. Dans un deuxième temps, des données relatives aux produits sont présentées afin de créer un modèle de classification et des règles de conception susceptibles de fournir des recommandations personnalisées ou une personnalisation permettant une meilleure expérience d'achat pour le client. Dans un troisième et dernier temps, la thèse s'appuie sur les évidences de l'industrie de l'habillement et la littérature existante pour suggérer des propositions qui peuvent guider les responsables dans le développement de stratégies data-driven pour améliorer la satisfaction du client par des services personnalisés. Enfin, cette thèse montre l'efficacité des solutions analytiques basées sur les données pour maintenir un avantage concurrentiel grâce aux données et aux connaissances déjà présentes dans une chaîne d'approvisionnement de l'habillement. Plus précisément, cette thèse contribue au domaine textile en identifiant des opportunités spécifiques de gestion de big data à l'aide de solutions d'intelligence artificielle. Ces opportunités peuvent être une source de référence pour d'autres travaux de recherche dans le domaine de la technologie et de la gestion.Over the past decade, the apparel industry has seen several applications of big data and artificial intelligence (AI) in dealing with various business problems. With the increase in competition and customer demands for the personalization of products and services which can enhance their brand experience and satisfaction, supply-chain managers in apparel firms are constantly looking for ways to improve their business strategies so as to bring speed and cost efficiency to their organizations. The big data management solutions presented in this thesis highlight opportunities for apparel firms to look into their supply chains and identify big data resources that may be valuable, rare, and inimitable, and to use them to create data-driven strategies and establish dynamic capabilities to sustain their businesses in an uncertain business environment. With the help of these data-driven strategies, apparel firms can produce garments smartly to provide customers with a product that closer meets their needs, and as such drive sustainable consumption and production practices.In this context, this thesis aims to investigate whether apparel firms can improve their business operations by employing big data and AI, and in so doing, seek big data management opportunities using AI solutions. Firstly, the thesis identifies and classifies AI techniques that can be used at various stages of the supply chain to improve existing business operations. Secondly, the thesis presents product-related data to create a classification model and design rules that can create opportunities for providing personalized recommendations or customization, enabling better shopping experiences for customers. Thirdly, this thesis draws from the evidence in the industry and existing literature to make suggestions that may guide managers in developing data-driven strategies for improving customer satisfaction through personalized services. Finally, this thesis shows the effectiveness of data-driven analytical solutions in sustaining competitive advantage via the data and knowledge already present within the apparel supply chain. More importantly, this thesis also contributes to the field by identifying specific opportunities with big data management using AI solutions. These opportunities can be a starting point for other research in the field of technology and management

Big data in fashion industry

Significant work has been done in the field of big data in last decade. The concept of big data includes analysing voluminous data to extract valuable information. In the fashion world, big data is increasingly playing a part in trend forecasting, analysing consumer behaviour, preference and emotions. The purpose of this paper is to introduce the term fashion data and why it can be considered as big data. It also gives a broad classification of the types of fashion data and briefly defines them. Also, the methodology and working of a system that will use this data is briefly described