Dynamics of Crossover from a Chaotic to a Power Law State in Jerky Flow

We study the dynamics of an intriguing crossover from a chaotic to a power law state as a function of strain rate within the context of a recently introduced model which reproduces the crossover. While the chaotic regime has a small set of positive Lyapunov exponents, interestingly, the scaling regime has a power law distribution of null exponents which also exhibits a power law. The slow manifold analysis of the model shows that while a large proportion of dislocations are pinned in the chaotic regime, most of them are pushed to the threshold of unpinning in the scaling regime, thus providing insight into the mechanism of crossover.Comment: 5 pages, 3 figures. In print in Phy. Rev. E Rapid Communication

Stratifying Colorectal Cancer stages through CT scan images using Convolutional Neural Networks

Artificial intelligence and deep learning have propelled cancer treatment, achieving a 25% increase in treatment accuracy. By analyzing vast datasets, AI has identified 30% more nuanced patterns, revolutionizing tailored therapies and patient outcomes. The proposed research investigates the feasibility of utilizing Convolutional Neural Networks (CNNs) to determine colorectal cancer staging using CT scan images. We have used VGG16 as the base model by fine- tuning the hyperparameters and the layers to accomplish the desired outcomes. The focus lies in demonstrating CNN’s effectiveness in automating the staging process, potentially providing a reliable and efficient tool for precise cancer diagnosis and treatment planning. In further work the result with tumor stage with patient’s other parameters are integrated to assess the risk level of cancer. The model results in 94.6% accuracy with minimal error rate

Analysis and Edge Detection of Lung Cancer – Survey

Treating cancer in the early stages can provide more treatment options, less invasive surgery, and increases the survival rate. This paper deals with the detection of cancerous cells from Lungs CT scan images. To analyze the cancerous cells, physicians tackle many challenging tasks. Locating lung cancer at an early stage is a challenging task since there are few or no symptoms in this stage of the disease and majority of the cases are diagnosed in the later stages of the disease. The majority of lung cancers originate as a small growth or nodule in the lung. Screening CT scans are extremely sensitive in detecting nodules as small as 2 or 3mm within the lungs. CT screening is efficient in locating majority of lung cancers. Lung CT Scan helps in detecting lung cancers at an early stage when compared with other scans like MRI, X-Ray, etc. This present work proposes a method to detect the cancerous cells effectively from the CT scan images by reducing the detection error made by the physicians’ naked eye for medical study based on canny edge detection

Psychosocial Predictive and Protective Factors for Depression in Pregnancy and Postpartum Period.

INTRODUCTION: Women’s mental health during pregnancy and postpartum Period is a public health priority due to its impact on both maternal and Child health. Antenatal and postpartum period are characterized by Multiple changes in physical, hormonal, psychic and social milieu Which have a direct effect on their mental health. Consequently this Period is considered as high risk times for the onset of psychiatric Illness or exacerbation of preexisting psychiatric illness.1 The interplay of factors like family type, economic state, Education, marital relationship, social support, culture regulate the Intensity of these mental health alterations in pregnancy and Postpartum period. Pregnancy either induces or worsens(exacerbates) pre-existing Stress. This in turn has a negative impact on pregnancy. Sustained Stress can activate the Hypothalamo-Pituitary axis and further Compromise the maternal and fetal health. Depression is the most prevalent mental disorder in pregnancy And postpartum period2.Although pregnancy is considered a time of Emotional well-being, there have been studies to describe rates of Depression around 20% in developing countries,10-15% in developed Countries. Depression whether in pregnancy or postpartum is Categorized by the same criteria as in DSM-4 TR as for any depressive Episode in the general population. Depression with postpartum onset Is only used as a specifier carrying additional information regarding The onset. It can be due to major depressive disorder or bipolar Disorder. In about one third of depressed pregnant females, current Episode represents the first episode of major depression. While women With previous diagnosis of depression maintained on antidepressant Medication happen to be at an especially increased risk for relapse During pregnancy or postpartum. Frequently, depression during pregnancy can remain undetected. Distinguishing symptoms of depression from normal responses to Stressful experiences of pregnancy can be difficult. Such difficult -to - Distinguish symptoms include insomnia or hypersomnia, significant Decrease or increase in appetite, moderate to severe anxiety, somatic Complaints, low energy, etc. Clinical features confirming the diagnosis Of major depression include anhedonia, feelings of guilt, poor selfesteem, Worthlessness, hopelessness and suicidal thoughts. However, Risk of self –injurious or suicidal behaviour appears to be low in Antenatal depression.6,7 Antenatal depression is a non –psychotic depressive episode Arising anytime during pregnancy. Antenatal depression significantly Contributes to the psychiatric morbidity during pregnancy and adverse Obstetric and neonatal outcomes3,4. It is also identified as a serious risk Factor for postpartum depression. Undiagnosed antenatal depression, In the long term can disrupt maternal-child relationship and family Functioning5.Important reasons for antenatal depression remaining Undiagnosed ,untreated or undertreated are social stigma, Embarrasement to disclose low mood at a period of family rejoice by Women, failure to integrate questions regarding psychiatric symptoms And previous treatment into the obstetric history, incomplete or lack of Definitive treatment due to associated potential risks with fetal Exposure to psychotropic drugs. Postpartum is considered the period of increased physical and Emotional demands and a time of risk for the development of Depressive symptoms. Postpartum depression falls along a continuum Of mood disturbances with milder forms diagnosed as postpartum Blues, severe episodes as postpartum psychosis. The prevalence of Postpartum depression is described as falling between 10% and 15%.8,9 In postpartum depression symptoms persists beyond two weeks ,of Mild to moderate severity and causing functional impairment and Indistinguishable from characteristics of MDD that occur at other times In a woman’s life. Risk factors for postpartum depression are antenatal Depression, anxiety features during pregnancy and history of Depression previously. Depression during this period can impact Negatively on a wide range of outcomes like maternal deaths due to Suicide10, maternal-infant relationship11, child psychological Development12, infant nutrition and growth of the child14. Above all women with postpartum depression are at significant Risk with high rates of recurrence; as high as 50% in future Pregnancies15.Sequelae of untreated mood symptoms can lead to Chronic depression or recurrence with greater severity. However Medical causes for mood disturbances like thyroid dysfunction and Anaemia needs to be excluded prior to initiation of psychiatric Treatment. Hence in these women a thorough history, physical Examination and lab investigations pave way for confirming the Diagnosis of depression in postpartum period. Since the last decade there has been a shift from the narrow Concept of postpartum depression to detailed evaluation of the Spectrum of depressive symptoms arising in pregnancy in women. There are very few studies examining how antenatal depression And postpartum depression vary with respect to the demographic and Psychosocial characteristics. Analysis and comparison of the Correlation factors of depression during and after pregnancy will throw More light than exclusively focusing on postpartum depression. So we Have decided to investigate the psycho-social and demographic factors As to evaluate their predictive and protective effects on depression in Pregnancy and postpartum in a tertiary care obstetric setting

Study on Comparison Of Three Methods of Gradual Weaning from Mechanical Ventilators

INTRODUCTION: Mechanical ventilation (MV) is a life-supporting modality that is used in a significant proportion of patients in intensive care units , the term mechanical ventilation refers to various artificial means used to support ventilation and oxygenation1, 2 Mechanical ventilation is commonly delivered in intensive care by positive pressure ventilation. Positive pressure ventilation modes are defined by inspiratory events. Expiration is treated as an independent entity. The primary expiratory parameter, positive end expiratory pressure (PEEP) can be applied to any of the ventilator modes. VENTILATOR MODES: The various modes of ventilation are classified based on the types of breaths that are selected. The modes most commonly used in pediatric practice are discussed here. VOLUME TARGETED MODES : 1. Controlled Mechanical Ventilation (CMV): In this mode, the ventilator controls all the ventilation while patient has minimal or no respiratory effort. This is the mode used at the initiation of mechanical ventilation. 2. Assisted Mechanical Ventilation (AMV): All breaths are triggered when the patient’s inspiratory effort exceeds the preset sensitivity threshold of negative pressure. In all other respects, it is similar to controlled mechanical ventilation. 3. Assist Control Ventilation (ACV): ACV is a combination of AMV and CMV. In this mode, the patient initiates the breathing as in AMV. However, if the patients fails to initiate the breathing within a prescribed time the ventilator triggers the breathing and provides a controlled breath as in CMV, thus ensuring a guaranteed minute ventilation. 4. Intermittent Mandatory Ventilation (IMV): It is essentially a combination of spontaneous breathing and CMV. A modified circuit provides a continuous gas flow that allows the patient to breathe spontaneously with minimal work of breathing, At a predetermined frequency, the ventilator provides a positive pressure breath to the patient. 5. Synchronized Intermittent Mandatory Ventilation (SIMV): SIMV allows the patient to trigger a mandatory breath in the assist mode thereby synchronizing it with the patient’s respiratory effort. However, if the patient does not trigger a breath within an allotted time; the ventilator delivers a conventional breath. AIM OF THE STUDY: To assess the effectiveness of the 3 standard methods of weaning from mechanical ventilators namely T – tube weaning, synchronized intermittent mandatory ventilation (SIMV) , continuous positive airway pressure / pressure support ( CPAP/PSV) ventilation in terms of successful weaning, to assess the incidence of weaning failure and duration of weaning with each and also the duration of hospital stay and outcome of these patients so that the best of the weaning procedure can be followed for successful weaning in future. DISCUSSION: In this randomized control trial of comparing the three methods of weaning ( T – piece trial , CPAP / PSV & SIMV ) from mechanical ventilators in children aged 1 month to 12 years , the results were analysed using appropriate statistical tests. In our study weaning was successful as well as duration of weaning was shorter in T – Piece technique than the other two. Intermittent Mandatory Ventilation Several advantages have been claimed for intermittent mandatory ventilation as a weaning technique: it is supposed to prevent a patient from “fighting” the ventilator, reduce respiratory-muscle fatigue, and expedite weaning. However, there are few data to support these claims24,26Intermittent mandatory ventilation is usually delivered in a synchronized manner with demand- valve circuitry, which increases the work of breathing. The intermittent nature of assistance also poses a problem. It was previously assumed that the degree of respiratory-muscle rest was proportional to the level of machine assistance. However, recent evidence indicates that respiratory-sensor output does not adjust to breath-to-breath changes in respiratory load, and intermittent mandatory ventilation may therefore contribute to the development of respiratory muscle fatigue or prevent recovery from it. Studies of the efficacy of intermittent mandatory ventilation in weaning have serious limitations. Schachtern et al44. compared it with conventional ventilation & noted no difference between the two techniques in the duration of ventilator support. Their study suffers from a retrospective design nonuniform study groups, and inadequate description of the protocol. Esteban etal24 compared it with single daily and multiple daily spontaneous breathing trials with t- piece and pressure ventilation and found SIMV as the poorest method of weaning. On comparison with single daily T – piece trial P value was < 0.006. In our study P value was 0.000. SUMMARY AND CONCLUSION: A randomized trial of comparing three methods of weaning from mechanical ventilators was completed in 88 children. From this study we conclude that, 1. Spontaneous extubation during weaning was least with T – piece trial. 2. Duration of weaning & number of trials needed for weaning was least with T - piece trial. 3. Weaning was ~ 6 times faster with T – piece than with CPAP/PSV and ~ 8 times faster than with SIMV. 4. Weaning success was also highest with T – piece trial. 5. Duration of weaning was not significantly different between CPAP/PSV & SIMV group 6. T – piece trial as a technique for weaning of children from mechanical ventilators is the best as far as duration and success of weaning is concerned. This is independent of age or sex or etiology or duration of ventilation prior to weaning or presence of shock or use of inotropes or the underlying disease process

Comparison of Different Orthographies for Machine Translation of Under-Resourced Dravidian Languages

Under-resourced languages are a significant challenge for statistical approaches to machine translation, and recently it has been shown that the usage of training data from closely-related languages can improve machine translation quality of these languages. While languages within the same language family share many properties, many under-resourced languages are written in their own native script, which makes taking advantage of these language similarities difficult. In this paper, we propose to alleviate the problem of different scripts by transcribing the native script into common representation i.e. the Latin script or the International Phonetic Alphabet (IPA). In particular, we compare the difference between coarse-grained transliteration to the Latin script and fine-grained IPA transliteration. We performed experiments on the language pairs English-Tamil, English-Telugu, and English-Kannada translation task. Our results show improvements in terms of the BLEU, METEOR and chrF scores from transliteration and we find that the transliteration into the Latin script outperforms the fine-grained IPA transcription