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Ultrafine-grained (UFG) high-Mn austenitic steel exhibited unusual discontinuous yielding on its stress-strain curve, characterized by a yield drop followed by a stress plateau, indicative of Lüders deformation. Utilizing the digital image correlation (DIC) technique, a strain-localized region known as a Lüders band was observed to propagate during Lüders deformation. Following microstructural observations using state-of-the-art techniques such as in-situ synchrotron XRD measurement during the tensile test and ex-situ S/TEM and SEM-ECCI, dislocation multiplication, rather than twinning, was theoretically identified as the primary deformation mechanism responsible for the unusual Lüders deformation in UFG high-Mn austenitic steel.

The Internet of Things (IoT) network infrastructures are becoming more susceptible to distributed denial of service (DDoS) attacks because of the proliferation of IoT devices. Detecting and predicting such attacks in this complex and dynamic environment requires specialized techniques. This study presents an approach to detecting and predicting DDoS attacks from a realistic multidimensional dataset specifically tailored to IoT network environments, named DDoSNet. At the beginning of the data preprocessing phase, the dataset must be cleaned up, missing values must be handled, and the data needs to be transformed into an acceptable format for analysis. Several preprocessing approaches, including data-cleaning algorithms and imputation methods, are used to improve the accuracy and dependability of the data. Following this, feature selection uses the African Buffalo Optimization with Decision Tree (ABO-DT) method. This nature-inspired metaheuristic algorithm imitates the behaviour of African buffalos to determine which traits are the most important. By integrating ABO with the decision tree, a subset of features is selected that maximizes the discrimination between regular network traffic and DDoS attacks. After feature selection, an echo-state network (ESN) classifier is employed for detection and prediction. A recurrent neural network (RNN) that has shown potential for managing time-series data is known as an ESN. The ESN classifier utilizes the selected features to learn the underlying patterns and dynamics of network traffic, enabling accurate identification of DDoS attacks. Based on the simulations, the proposed DDOSNet had an accuracy of 98.98 %, a sensitivity of 98.62 %, a specificity of 98.85 %, an F-measure of 98.86 %, a precision of 98.27 %, an MCC of 98.95 %, a Dice coefficient of 98.04 %, and a Jaccard coefficient of 98.09 %, which are better than the current best methods.

Background and Aims: Simulation is one of the important learning tools when it comes to skill acquisition and as a supplemental tool for training in high stake situations like COVID-19. The aim of this study is to meet the global requirements of knowledge on ventilatory management, prepare and to evaluate the effectiveness of the teaching module for non-anesthesiology trainees on COVID-19 patients. Methods: Quasi experimental cross sectional pilot study was conducted with a sample of twenty-six trainees. A teaching module was prepared and validated which consisted of lectures, audio-video sessions, demonstrations with hands-on training, debriefing, analytical-phase and reflection. Pre and Post evaluations from student t-test and direct observation of procedural skills (DOPS) were used for knowledge and skill assessment respectively and feedback obtained from Likert's score. Results: Pre- and Post-tests had a mean score of 7.42 ± 2.12 and 14.92 ± 2.9 respectively (P value 0.00001). DOPS included 16 point score, in which 23 trainees (88.4%) met the expectations and above expectations as per training objectives. A five-point Likert's score feedback revealed satisfactory and highly satisfactory scores of 100% (ABG), 96.1% (mechanical ventilation), and 84.6% (ventilation in COVID-19 patients). Overall satisfaction for the workshop among respondents was 100 per cent. Confidences of handling scores were 84.5% (interpreting ABG), 65.3% (maneuvering mechanical ventilation), and 96.15% (intubation in COVID-19 patients). Conclusion: A planned teaching module in ventilation management helps to train non-anaesthesiologists more effectively as a part of COVID-19 preparedness. Simulation with debriefing based training to the medical fraternity is the best alternative in the present pandemic and it will also ensure the safety of health care professionals.

Melioidosis which is known to be endemic in South-east Asia and Northern Australia is a treatable infection and is more common than currently appreciated. It is now expanding rapidly to other regions of the world predominantly in the Indian subcontinent. The key for successful management of this disease lies in facilitating rapid and accurate diagnosis by expert personnel and timely selection of adequate sensitive antibiotics. We present here a series of three cases of melioidosis involving lung and pleura along with clinico radiological and treatment details. [J Med Allied Sci 2019; 9(1.000): 36-39]

Sarcoidosis is a chronic granulomatous disease involving multiple organs. Most commonly affected organs are lungs, followed by skin, lymph nodes. Hematological manifestations of sarcoidosis are uncommon and may include hemolytic anemia, leukopenia, eosinophilia, peripheral lymphopenia but severe thrombocytopenia is very rare. Our patient presented with petechial rash, papular skin lesions and had severe thrombocytopenia. Skin biopsy showed granulomatous inflammation without necrosis with good clinical, radiological and hematological response to oral prednisolone. [J Med Allied Sci 2018; 8(2.000): 94-97]

Abstract Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM’s high affinity with various analytical options into account. As is well known, STEM’s image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM’s current temporal resolution is far below the conventional TEM’s. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is shown to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution.

Background: Neurocognitive decline and depression are the most common unaddressed but noticeable adverse consequences linked with obstructive sleep apnea (OSA) which can affect work performance, social functioning, and quality of life. It is significant to explore both cognition and mood disorders in OSA, as there is adequate evidence in the literature supporting the efficacy of continuous positive airway pressure (CPAP) in the management. Aims and Objectives: The aim was to assess the neurocognitive profile and depression in patients with OSA in our center. Patients and Methods: This was a cross-sectional observational study conducted in a tertiary care center between January 2017 and January 2018. A total of 92 patients with an established diagnosis of OSA (by polysomnography) were included in the study. All patients were given questionnaires for the assessment of neurocognitive function and depression scoring. Results: Out of 92 OSA patients, 29 (31.5%) had normal cognition, 43 (46.7%) had mild cognitive impairment (CI), and 20 (21.7%) had major CI. Out of twenty patients with major CI, major attention deficit was observed in 17 (85%), memory impairment in 16 (80%), verbal fluency was affected in 13 (65%), deficit in language skills was observed in 7 (35%), and visuospatial abilities were affected in 17 patients (85%). Out of 92 OSA patients, 21 (22.8%) had depression and 71.4% of them were females. Conclusions: OSA is an independent risk factor for both depression and neurocognitive decline. It is highly recommended that patients with OSA should be screened for both, so as to provide better clinical outcomes.

Coxsackievirus group B (CVB) is a member of the genus Enterovirus in the family Picornaviridae. CVB infection has been implicated as a major etiologic agent of viral myocarditis, dilated cardiomyopathy, meningitis, and pancreatitis among children and young adults. Until date, no antiviral agent has been licensed for the treatment of Coxsackievirus infection. In an effort to identify antiviral agents against diseases caused by the CVB, we found that ethyl 3-hydroxyhexanoate (EHX), a volatile compound present in fruits and food additives, is a potent antiviral compound. In this study, we demonstrated that EHX treatment significantly inhibits CVB replication both in vivo and in vitro. Furthermore, EHX possesses antiviral activity at 50% effective concentration (EC50) of 1.2 μM and 50% cytotoxicity (CC50) of 25.6 μM, yielding a selective index (SI) value as high as 20.8. Insights into the mechanism of antiviral activity of EHX showed that it acts at the step of viral RNA replication. Since EHX has received approval as food additives, treatment of CVB-related infections with EHX might be a safe therapeutic option and may be a promising strategy for the development of semi-synthetic antiviral drugs for viral diseases.

Meckel's diverticulum is the commonest congenital abnormality of the gastrointestinal tract. Hemorrhage, obstruction and inflammation are the three main categories of complications resulting from Meckel's diverticulum. Spontaneously perforation of Meckel's diverticulum is very rare and mimics acute appendicitis. We report a case of 26 year-old male,who presented since 5 days worsening abdominal pain predominantly in the right iliac fossa associated with high grade fever. On physical examination his abdomen was distended with guarding and rigidity. A provisional diagnosis of appendiculaire peritonitis was made. Our patient had an emergency laparotomy, where a perforated Meckel's diverticulum and advanced peritonitis were discovered. A diverticulectomy with ileostomy were performed. Heterotopic mucosa of diverticulitis was confirmed on histopathology. The patient made an uneventful recovery postoperatively and ileostomy reconstruction was done two months later.This case report is an interesting and unusual case of Meckel's diverticulum complications and highlights the importance of considering Meckel's diverticulum as a differential diagnosis in every patient presenting with acute abdomen.

El presente trabajo apoya el diagnóstico preliminar del cáncer del cervix uterino. Detennina elestado (normal, displásico o canceroso) en células individuales de muestras dtalógicas utilizandoun sistema de visión artificial. El reconocimiento del estado en las células del cervix uterino serealiza en dos pasos básicos, a saber: Inicialmente se debe clasificar la célula objeto de análisis,como supeificial, intennedia o parabasal, tomando como base su aspecto (color,forma, tamaño,etc.). Posteriormente, se detecta cuales criterios de malignidad o premalignidad se encuentranpresentes, con el fin de hacer el diagnóstico correspondiente en la muestra.

Abstract Introduction The January 2023 COVID-19 omicron wave in China garnered wide publicity partly because it evaded most vaccines at that time and resulted in “breakthrough infections” in previously vaccinated individuals. This study focused on the COVID-19 vaccination status and the response of foreigners of African descent who were in China during the January 2023 Omicron-driven COVID-19 wave. Materials and methods A cross-sectional online survey of Africans in China was conducted in January 2023. Self-report electronic questionnaires were sent to eligible participants across the country, with no restriction on age, gender, or country of origin. Two hundred sixty-six participants were eventually enrolled. Collected data was cleaned and analyzed using SPSS. Descriptive analysis was used to summarize the data in terms of numbers and percentages, while the Chi-square test was used to determine relationships among variables. Results A total of 266 participants were enrolled, 68.8% males and 31.2% females. The majority (97%) were 45 years and below and mostly students (75.2%). 87.2% were vaccinated, with 53.1% having taken at least 2 shots. Sinovac (53.9%) was the most used vaccine brand. 21.4% reported infection with COVID-19 during the January 2023 omicron wave, with 14.0% reporting “breakthrough” infections. No significant difference was seen in the risk of getting infected with COVID-19 between unvaccinated and vaccinated participants; OR 1.2 (95% CI 0.396–3.634, p = 0.747). 35.1% reported mild asymptomatic infections, while 64.9% reported symptoms. The majority of the cases (89.5%) were managed from home. Conclusion In summary, most Africans in China were vaccinated during the January 2023 COVID-19 omicron wave, although “breakthrough” infections were reported. The infection rate among Africans in China was relatively higher than for African Americans and those living in Africa, but the majority were managed from home. Future studies are needed to capture vital COVID-19 information on Africans in China for more trailered responses to future outbreaks.

Human Papillomavirus (HPV)-35 accounts for up 10% of cervical cancers in Sub-Saharan Africa. We herein assessed the genetic diversity of HPV35 in HIV-negative women from Chad (identified as #CHAD) and HIV-infected men having sex with men (MSM) in the Central African Republic (CAR), identified as #CAR. Ten HPV35 DNA from self-collected genital secretions (n = 5) and anal margin samples (n = 5) obtained from women and MSM, respectively, were sequenced using the ABI PRISM® BigDye Sequencing technology. All but one HPV35 strains belonged to the A2 sublineage, and only #CAR5 belonged to A1. HPV35 from #CAR had higher L1 variability compared to #CHAD (mean number of mutations: 16 versus 6). L1 of #CAR5 showed a significant variability (2.29%), suggesting a possible intra-type divergence from HPV35H. Three (BC, DE, and EF) out of the 5 capsid loops domains remained totally conserved, while FG- and HI- loops of #CAR exhibited amino acid variations. #CAR5 also showed the highest LCR variability with a 16bp insertion at binding sites of the YY1. HPV35 from #CHAD exhibited the highest variability in E2 gene (P

Background: Often, patients with idiopathic interstitial pneumonia (IIP) have certain specific clinical features to suggest an autoimmune disease but do not justify the current rheumatologic classification systems to fit into a diagnosis of connective tissue disease (CTD)-associated IIP. There is a great paucity of clinical, serological, and radiological data of these patients from India. Aim: The aim was to study the clinicoradiological and autoantibody profile in patients with interstitial pneumonia with autoimmune features (IPAF). Methodology: It was a prospective, observational study conducted in a tertiary care center between December 2015 and December 2016. A total of 30 patients who satisfied the criteria for IPAF according to the American Thoracic Society/European Respiratory Society research were included in the study. Results: All 30 patients satisfied IPAF criteria, but they did not meet the immunological criteria for CTD. Majority of them were female (86.67%) and nonsmokers. The mean age was 52.5 ± 14.5 years. The most common clinical symptom was inflammatory arthritis in 20 (66.67%) patients, followed by Raynaud's phenomenon in 5 (16%) patients. Nonspecific interstitial pneumonia was the most common radiological pattern seen in 20 (66.67%) patients, while antinuclear antibody (1:320) was the most common autoantibody positive in 18 (60.0%) patients, followed by rheumatoid arthritis factor in 15 (50%) patients. Conclusions: High female predominance along with distinct imaging, histologic and serological characteristic features are seen in patients with IPAF as compared to those with IIP. Further studies in patients with IPAF are needed to understand the natural history and its management.

Scene classification aims to classify various objects and land use classes such as farms, highways, rivers, and airplanes in the remote sensing images. In recent times, the Convolutional Neural Network (CNN) based models have been widely applied in scene classification, due to their efficiency in feature representation. The CNN based models have the limitation of overfitting problems, due to the generation of more features in the convolutional layer and imbalanced data problems. This study proposed Gaussian Mutation–Spider Monkey Optimization (GM-SMO) model for feature selection to solve overfitting and imbalanced data problems in scene classification. The Gaussian mutation changes the position of the solution after exploration to increase the exploitation in feature selection. The GM-SMO model maintains better tradeoff between exploration and exploitation to select relevant features for superior classification. The GM-SMO model selects unique features to overcome overfitting and imbalanced data problems. In this manuscript, the Generative Adversarial Network (GAN) is used for generating the augmented images, and the AlexNet and Visual Geometry Group (VGG) 19 models are applied to extract the features from the augmented images. Then, the GM-SMO model selects unique features, which are given to the Long Short-Term Memory (LSTM) network for classification. In the resulting phase, the GM-SMO model achieves 99.46% of accuracy, where the existing transformer-CNN has achieved only 98.76% on the UCM dataset.

Recycling has been the fascinating topic among the researchers for all times. The present study shows the recycling of steel plant's solid wastes as blast furnace flue dust and sludge towards agglomeration and their use in the production of sinter. These wastes consist of metal oxides and coke fines as a valuable material with some alkali oxides. Using these wastes as it is in the form of fines exacerbate the further processing. Pellets of these wastes are prepared with three types of binders as molasses, dextrin and bentonite. The result reveals that properties as compressive strength, shatter strength, are better in the case of bentonite binder having the productivity of the disc pelletizer machine as 75. After that, these macro pellets used for sintering with iron ore and other ingredients in pot type, down draft laboratory grade sintering machine, which shows very high productivity and good mechanical properties of the sinter as well. The microstructural analysis reveals the presence of re-oxidized hematite and a little bit of a magnetite phase with some slag phases, which confirmed later by XRD analysis. Results also show the decrease in coke rate, i.e. coke consumption to produce sinter and at the same time, this process is highly eco-friendly.