ABSTRACT
Organizations regardless of their size are rapidly transforming, adopting and embracing digitalization amid the COVID pandemic. The pandemic forced organizations to ratio- nalize offline operations and swift towards online operations. Many organizations have digitized their services and have witnessed increasing Multistage cyber-attacks. Further, a lot of organizations have enabled remote access to the enterprise resources and services. As a result, organizations are striving to defend against Multistage cyber-attacks. These multistage attacks often spread across many stages, which is best described by MITRE Adversarial Tactics, Techniques, and Common Knowl- edge (ATT&CK) Framework. There are many research efforts for static detection of malicious binaries but very few or limited research targeting run-time detection of malicious processes in the system. Detection of these malicious processes are key for identifying new variants of multistage attacks or malware in the real world. This paper proposes a system for detecting multistage attacks in real-time or run-time by leveraging Machine learning and MITRE ATT&CK Framework. Machine learning facilitates detecting the malicious process in the system, and the MITRE ATT&CK framework offers insight into adversary techniques. Combination of these two is very effective in detecting multistage attacks and identifying individual stages. The proposed system shows promising results when tested on real-time/latest malware. Test result shows that our system can achieve 95.83% of accuracy. This paper discusses the challenges in detection of runtime malware, dataset generation © 2022 IEEE.
ABSTRACT
Aim and background: Mechanical Power in ARDS has predictive value for both VILI and mortality. Driving pressure and mechanical power are two new targets in the mechanical ventilation of ARDS patients. COVID-19 pneumonia has two different phenotypes H type and L type which have different lung compliance, elasticity, and recrutability with different ventilatory strategies. We want to observe how Mechanical Power behaves in H type COVID-19 ARDS and its correlation with compliance and driving pressure. Objective: To study the correlation of Mechanical Power with Driving Pressure and Compliance in H type of COVID-19 pneumonia. Materials and methods: It is a prospective observational study conducted in COVID-19 patients admitted to the Medical Intensive Care unit. We included 65 adult COVID-19 patients aged between 18 and 70 years requiring invasive mechanical ventilation for at least 24 hours. Patients who developed spontaneous pneumothorax and pneumomediastinum before initiation of mechanical ventilation were excluded. Patients were categorised to H type based on lung compliance (<40 mL/cmH2O), recrutability, and lung weight. The Mechanical Power was calculated using the following equation, MP = 0.098 ∼ TV ∼ RR (Paw-1/2 for). Paw-peak airway pressure, for-driving pressure, TV-tidal volume, RR-respiratory rate. The variables are taken at 3 different time intervals in the first 24 hours of invasive mechanical ventilation. All patients are ventilated according to ARDSNET protocol. The Driving pressure and compliance were recorded. The correlation of Mechanical Power with Driving pressure and Compliance were analysed using Pearson Correlation. Results: The mean age of the patients was 57.04 ) 13.96 years (mean ) SD), gender distribution 75% were males and 25% were females. A positive correlation was observed between Mechanical power and Driving pressure (Pearson correlation 0.245) which is statistically significant p = 0.049. A negative correlation was observed between Mechanical power and Compliance (Pearson correlation 0.183) which is not statistically significant. Conclusion: The Mechanical Power and Driving pressure the new targets of Ventilator-Induced Lung Injury (VILI) and also predictors of mortality in ARDS patients. The positive correlation between Mechanical Power and Driving pressure was observed in H type of COVID-19 patients which behaves similar to other ARDS and independent risk factors of mortality in H type of COVID-19 ARDS too.
ABSTRACT
Acute undifferentiated febrile illnesses (AUFIs) are associated with specific characterizations like fever of less than two weeks' duration with no organ-specific symptoms at onset. These range from mild and self-limiting disease to progressive, life-threatening illness. Acute undifferentiated febrile illnesses are classified into malaria and non-malarial illnesses on the basis of microscopy or malariadiagnostic tests. Various challenges, such as comorbidities, geriatrics, pregnancy, and immune-compromised profile of the patient, impede the treatment regimen. Identifying the root cause of undifferentiated fever becomes critical and involves correct diagnostic tests along with empirical treatment initiation. Doxycycline, being a broad-spectrum antibiotic, confers activity against many Gram-positive, Gram-negative, and "atypical" bacteria. Apart from antimicrobial activity, Doxycycline demonstrates the potential to inhibit dengue virus replication and exhibits anti-inflammatory activity by down-regulating proinflammatory cytokine levels. As coronavirus disease 2019 (COVID-19) spreads, the clinical management of associated cytokine storm remains unanswered. Considering the probable beneficial effect of doxycycline, it has been recommended by the national and international experts for the empirical management of COVID-19. © Journal of the Association of Physicians of India 2011.
ABSTRACT
Acute undifferentiated febrile illnesses (AUFIs) are associated with specific characterizations like fever of less than two weeks’duration with no organ-specific symptoms at onset. These range from mild and self-limiting disease to progressive, life-threatening illness. Acute undifferentiated febrile illnesses are classified into malaria and non-malarial illnesses on the basis of microscopy or malaria-diagnostic tests. Various challenges, such as comorbidities, geriatrics, pregnancy, and immune-compromised profile of the patient, impede the treatment regimen. Identifying the root cause of undifferentiated fever becomes critical and involves correct diagnostic tests along with empirical treatment initiation. Doxycycline, being a broad-spectrum antibiotic, confers activity against many Gram-positive, Gram-negative, and “atypical” bacteria. Apart from antimicrobial activity, Doxycycline demonstrates the potential to inhibit dengue virus replication and exhibits anti-inflammatory activity by down-regulating proinflammatory cytokine levels. As coronavirus disease 2019 (COVID-19) spreads, the clinical management of associated cytokine storm remains unanswered. Considering the probable beneficial effect of doxycycline, it has been recommended by the national and international experts for the empirical management of COVID-19. © 2021 Journal of Association of Physicians of India. All rights reserved.
ABSTRACT
Introduction: RT-PCR test is the standard method for the diagnosis of SARS-CoV-2 infection. This test is based upon the amplification of the fluorescent signal. Number of cycles that fluorescent signal undergoes to reach the threshold called as Cycle threshold (CT). It is inversely related to the nucleic acid content of the sample. Objectives: To study the correlation between cycle threshold of RT-PCR test is confirmed COVID-19 patients with severity of the disease. Materials and methods: This is a single-center retrospective observational study. We have included a total of 192 patients. SARSCoV- 2 infection was confirmed by the RT-PCR test. Entire data have been collected from electronic medical records. The primary outcome was 28-day mortality, secondary outcomes were ICU admission, invasive ventilation, AKI, RRT, shock and CORAD SCORE on HRCT chest, the total length of stay in the hospital, number of ICU days, and ventilator days. Results: We have concluded mean CT value for all groups and calculated p-value for statistically significance.For total length of stay in hospital,number of ICU days and ventilator days were applied pearson correlation coefficient. P value was statistically significant for mortality, ICU admission and shock groups. Cycle threshold and length of ICU stay were inversely correlated with statistically significant p-value. Discussions: In our study, it is concluded that low CT is associated with the severity of the disease. Conclusion: Low CT associated with increased ICU admission, high mortality, shock, and increased length of ICU stay.