Study of the effects of deuterium implantation upon the performance of thin-oxide CMOS devices

The use of ultra thin oxide films in modem semiconductor devices makes them increasingly susceptible to damage due to the hot carrier damage. Deuterium in place of hydrogen was introduced by ion implantation at the silicon oxide-silicon interface during fabrication to satisfy the dangling bonds. Deuterium was implanted at energies of 15, 25 and 35 keV and at a dose of 1x1014/cm2. Some of the wafers were subjected to N2O annealing following gate oxide growth. It was demonstrated that ion implantation is an effective means of introduction of deuterium. Deuterium implantation brings about a clear enhancement in gate oxide quality by improving the interface characteristics. N2O annealing further improves device performance. A reduction of electron traps with deutenum was also observed. A combination of deuterium implantation at 25 keV and a dose of 1x1015/cm2, followed by annealing in N2O was observed to have the most positive influence on device behavior. Concurrently, MEMS microheaters being fabricated for an integrated VOC sensor were also tested for their temperature response to an applied voltage. Different channel configurations and materials for the conducting film were compared and the best pattern for rapid heating was identified. Temperature rises of upto 390° C were obtained. The temperature responses after coating spin-on glass in the microchannels were also measured

Transcending Grids: Point Clouds and Surface Representations Powering Neurological Processing

In healthcare, accurately classifying medical images is vital, but conventional methods often hinge on medical data with a consistent grid structure, which may restrict their overall performance. Recent medical research has been focused on tweaking the architectures to attain better performance without giving due consideration to the representation of data. In this paper, we present a novel approach for transforming grid based data into its higher dimensional representations, leveraging unstructured point cloud data structures. We first generate a sparse point cloud from an image by integrating pixel color information as spatial coordinates. Next, we construct a hypersurface composed of points based on the image dimensions, with each smooth section within this hypersurface symbolizing a specific pixel location. Polygonal face construction is achieved using an adjacency tensor. Finally, a dense point cloud is generated by densely sampling the constructed hypersurface, with a focus on regions of higher detail. The effectiveness of our approach is demonstrated on a publicly accessible brain tumor dataset, achieving significant improvements over existing classification techniques. This methodology allows the extraction of intricate details from the original image, opening up new possibilities for advanced image analysis and processing tasks

Comparative evaluation of cost-effectiveness between typical antipsychotic haloperidol and atypical antipsychotics olanzapine, risperidone and aripiprazole in the treatment of stable schizophrenia

Background: Schizophrenia patients mostly require life-long treatment. For such long-term treatments, cost is an important factor. Estimate of cost in terms of efficacy can give idea to prescribers about the relative financial burden posed by various typical and newer antipsychotics in schizophrenic patients.Methods: A total of 98 stable schizophrenic patients were enrolled in this open label study over a period of 1 year. Patients were divided in four groups, group-I received Haloperidol (n=24), group-II received Olanzapine (n=25), group-III received Risperidone (n=25) and group-IV received Aripiprazole (n=24). The patients were given drugs on the basis of physician’s discretion, depending upon the condition of the patient at the time of presentation. Patients were followed up to 16 weeks. Direct treatment costs and efficacy of treatment in terms of Clinical Global Impression - Efficacy Index CGI (EI) noted and average cost-effectiveness worked out.Results: In this open label study, the mean age of patients was 35.05±1.30. The average cost-effectiveness ratio was 26.25 for haloperidol, 10.12 for Olanzapine, 9.83 for Risperidone and 25.92 for Aripiprazole.Conclusions: Risperidone was found to be most cost-effective, followed by olanzapine, then by aripiprazole, whereas haloperidol was found least cost effective

Role of Physiotherapy in Hospitalised Patients of COVID-19 disease

Introduction: Respiratory physiotherapy is one of the therapeutic methods in various respiratory viral infections. Breathing exercises with other interventions, could enhance the total lung capacity and symptom alleviation in patients with virus-related acute respiratory distress syndrome (ARDS). Aim: To study the clinical evaluation of the role of physiotherapy in hospitalised patients of covid-19 diseases. Method: This was an Observational (prospective, cross-sectional) study. 187 patients were recruited and diagnosed as COVID-19 as per RTPCR at NSCB Medical College, Jabalpur (MP). Patients were randomised into the physiotherapy group and controlled group. Patients in the physiotherapy group were undergone positional changes, prone ventilation, Breathing exercise, Resistive training, Passive joint motion, Muscle stretching, Bedside standing training, endurance exercise by a specialized physiotherapist. Mean cough severity index, MMRC grade, respiration rate and peripheral blood saturation were recorded before and after intervention and compared with the controlled group. Result: There was significant improvement found in MMRC grade and respiration rate after physical therapy in the physiotherapy group (p-value < 0.05). Exertional dyspnoea and cough severity index significant deceased in physiotherapy group. The positive change was found in peripheral blood saturation. There was decreased in hospitalization stay in the physiotherapy group as compared to the controlled group. Conclusion: Our study revealed the positive effect of physiotherapy on covid-19 disease in terms of symptoms and hospitalization duration among the physiotherapy group. Physiotherapy exerts a beneficial role in the management of the covid-19 disease

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans

The temporal bone is a part of the lateral skull surface that contains organs responsible for hearing and balance. Mastering surgery of the temporal bone is challenging because of this complex and microscopic three-dimensional anatomy. Segmentation of intra-temporal anatomy based on computed tomography (CT) images is necessary for applications such as surgical training and rehearsal, amongst others. However, temporal bone segmentation is challenging due to the similar intensities and complicated anatomical relationships among critical structures, undetectable small structures on standard clinical CT, and the amount of time required for manual segmentation. This paper describes a single multi-class deep learning-based pipeline as the first fully automated algorithm for segmenting multiple temporal bone structures from CT volumes, including the sigmoid sinus, facial nerve, inner ear, malleus, incus, stapes, internal carotid artery and internal auditory canal. The proposed fully convolutional network, PWD-3DNet, is a patch-wise densely connected (PWD) three-dimensional (3D) network. The accuracy and speed of the proposed algorithm was shown to surpass current manual and semi-automated segmentation techniques. The experimental results yielded significantly high Dice similarity scores and low Hausdorff distances for all temporal bone structures with an average of 86% and 0.755 millimeter (mm), respectively. We illustrated that overlapping in the inference sub-volumes improves the segmentation performance. Moreover, we proposed augmentation layers by using samples with various transformations and image artefacts to increase the robustness of PWD-3DNet against image acquisition protocols, such as smoothing caused by soft tissue scanner settings and larger voxel sizes used for radiation reduction. The proposed algorithm was tested on low-resolution CTs acquired by another center with different scanner parameters than the ones used to create the algorithm and shows potential for application beyond the particular training data used in the study

High level xylitol production by Pichia fermentans using non-detoxified xylose-rich sugarcane bagasse and olive pits hydrolysates

Hemicellulosic sugars, the overlooked fraction of lignocellulosic residues can serve as potential and cost-effective raw material that can be exploited for xylitol production. Xylitol is a top platform chemical with applications in food and pharmaceutical industries. Sugarcane bagasse (SCB) and olive pits (OP) are the major waste streams from sugar and olive oil industries, respectively. The current study evaluated the potential of Pichia fermentans for manufacturing of xylitol from SCB and OP hydrolysates through co-fermentation strategy. The highest xylitol accumulation was noticed with a glucose and xylose ratio of 1:10 followed by feeding with xylose alone. The fed-batch cultivation using pure xylose, SCB, and OP hydrolysates, resulted in xylitol accumulation of 102.5, 86.6 and 71.9 g/L with conversion yield of 0.78, 0.75 and 0.74 g/g, respectively. The non-pathogenic behaviour and ability to accumulate high xylitol levels from agro-industrial residues demonstrates the potential of P. fermentans as microbial cell factory

Challenges and opportunities in mixed method data collection on mental health issues of health care workers during COVID-19 pandemic in India

Background: The present paper describes the key challenges and opportunities of mixed method telephonic data collection for mental health research using field notes and the experiences of the investigators in a multicenter study in ten sites of India. The study was conducted in public and private hospitals to understand the mental health status, social stigma and coping strategies of different healthcare personnel during the COVID-19 pandemic in India.Methods: Qualitative and quantitative interviews were conducted telephonically. The experiences of data collection were noted as a field notes/diary by the data collectors and principal investigators.Results: The interviewers reported challenges such as network issues, lack of transfer of visual cues and sensitive content of data. Although the telephonic interviews present various challenges in mixed method data collection, it can be used as an alternative to face-to-face data collection using available technology.Conclusions: It is important that the investigators are well trained keeping these challenges in mind so that their capacity is built to deal with these challenges and good quality data is obtained

Factors associated with stigma and manifestations experienced by Indian health care workers involved in COVID-19 management in India: A qualitative study

Healthcare personnel who deal with COVID-19 experience stigma. There is a lack of national-level representative qualitative data to study COVID-19-related stigma among healthcare workers in India. The present study explores factors associated with stigma and manifestations experienced by Indian healthcare workers involved in COVID-19 management. We conducted in-depth interviews across 10 centres in India, which were analysed using NVivo software version 12. Thematic and sentiment analysis was performed to gain deep insights into the complex phenomenon by categorising the qualitative data into meaningful and related categories. Healthcare workers (HCW) usually addressed the stigma they encountered when doing their COVID duties under the superordinate theme of stigma. Among them, 77.42% said they had been stigmatised in some way. Analyses revealed seven interrelated themes surrounding stigma among healthcare workers. It can be seen that the majority of the stigma and coping sentiments fall into the mixed category, followed by the negative sentiment category. This study contributes to our understanding of stigma and discrimination in low- and middle-income settings. Our data show that the emergence of fear of the virus has quickly turned into a stigma against healthcare workers

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries