Detection of Malicious Threats Exploiting Clock-Gating Hardware Using Machine Learning.

Embedded system technologies are increasingly being incorporated into manufacturing, smart grid, industrial control systems, and transportation systems. However, the vast majority of today's embedded platforms lack the support of built-in security features which makes such systems highly vulnerable to a wide range of cyber-attacks. Specifically, they are vulnerable to malware injection code that targets the power distribution system of an ARM Cortex-M-based microcontroller chipset (ARM, Cambridge, UK). Through hardware exploitation of the clock-gating distribution system, an attacker is capable of disabling/activating various subsystems on the chip, compromising the reliability of the system during normal operation. This paper proposes the development of an Intrusion Detection System (IDS) capable of detecting clock-gating malware deployed on ARM Cortex-M-based embedded systems. To enhance the robustness and effectiveness of our approach, we fully implemented, tested, and compared six IDSs, each employing different methodologies. These include IDSs based on K-Nearest Classifier, Random Forest, Logistic Regression, Decision Tree, Naive Bayes, and Stochastic Gradient Descent. Each of these IDSs was designed to identify and categorize various variants of clock-gating malware deployed on the system. We have analyzed the performance of these IDSs in terms of detection accuracy against various types of clock-gating malware injection code. Power consumption data collected from the chipset during normal operation and malware code injection attacks were used for models' training and validation. Our simulation results showed that the proposed IDSs, particularly those based on K-Nearest Classifier and Logistic Regression, were capable of achieving high detection rates, with some reaching a detection rate of 0.99. These results underscore the effectiveness of our IDSs in protecting ARM Cortex-M-based embedded systems against clock-gating malware.

Smart Transportation: An Overview of Technologies and Applications.

As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices.

Associations of non-HDL-C and triglyceride/HDL-C ratio with coronary plaque burden and plaque characteristics in young adults.

Coronary artery disease (CAD) is uncommon in young adult patients. However, these patients have different risk factor profiles and high-risk coronary plaques are more common. The aim of this study was to examine the relations between the coronary plaque burden, plaque composition, serum non-high-density lipoprotein cholesterol (non-HDL-C) levels, and triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio in young adults. We analyzed a total of 551 patients under age 45 who had undergone coronary computed tomography angiography (CCTA). Coronary plaque characteristics were analyzed using CCTA. Multivariate linear regression analysis was used to assess the predictors of non-calcified plaque (NCB) and calcified plaque (CB) burdens. Serum non-HDL-C levels and TG/HDL-C ratio were higher in the coronary atherosclerosis patient group. Serum non-HDL-C levels and the TG/HDL-C ratio were higher in the obstructive CAD patient group. The plaque burden was positively correlated with non-HDL-C (r = 0.30; p < 0.001), and TG/HDL-C ratio (r = 0.18; p < 0.001).  NCB was positively correlated with age, gender, smoking status, fasting blood glucose, total cholesterol, low-density lipoprotein cholesterol, serum triglycerides, hbA1c, non-HDL-C, and TG/HDL-C ratio. Non-HDL-C (ß coefficient = 0.13; p = 0.023) and TG/HDL-C ratio (ß = 0.10;  p = 0.042) were independent predictors of NCB. Serum non-HDL-C levels and TG/HDL-C were significantly associated with the presence and burden of coronary plaques. Serum non-HDL-C and TG/HDL-C ratios were independently associated with NCB, suggesting their use as easy-to-compute markers for identifying high-risk groups in young adults.

Successful Treatment of a Patient with Cardiac Arrest Due to Hyperkalemia by Prolonged Cardiopulmonary Resuscitation along with Hemodialysis: A Case Report and Review of the Literature.

Severe hyperkalemia is a potentially life threatening cardiac emergency, especially in patients with renal failure, and can lead to fatal arrhythmias such as ventricular fibrillation or asystole, leading to cardiac arrest. We report a case of a 39-year-old woman who developed sudden cardiac arrest secondary to hyperkalemia (9.95 mEq/L) with renal insufficiency. Despite 20 min of cardiopulmonary resuscitation (CPR) and conventional treatment for hyperkalemia, the cardiac arrest persisted. Hemodialysis was then initiated via the right femoral vein during CPR, and the patient restored spontaneous heartbeat 40 min later. Hemodialysis should be considered in the course of CPR in severe hyperkalemia induced cardiac arrest if conventional therapies fail.

Acute coronary syndrome because of a scorpion sting in a patient with chronic coronary syndrome: A case report and review of the literature.

The occurrence of acute coronary syndrome (ACS) following a scorpion sting has been very rarely reported in literature, and most of the cases presented had a normal coronary angiogram. The possible pathogenetic mechanisms include imbalance in blood pressure and coronary spasm caused by a combination of sympathetic excitation with subsequent thrombosis of coronary vessels developed after the release of vasoactive, inflammatory, and thrombogenic substances contained in the scorpion venom. In this report, we present a case of a scorpion sting complicated by ACS, called Kounis syndrome (KS). His coronary angiogram revealed the presence of significant stenosis of the left anterior descending artery. He was treated successfully with percutaneous transluminal coronary angioplasty, antivenom serum, and supportive therapy.

Can NLR, PLR and LMR be used as prognostic indicators in patients with pulmonary embolism? Author's reply on commentary.

We appreciate the comments made by Dr Bedel and colleagues. NLR, PLR and LMR are affected by various diseases such as oncological, collagen tissue, inflammatory, or severe renal/liver diseases [1]. Because of this, we have listed some of the above-mentioned disorders in the tables. Hematological diseases, collagen tissue disease, inflammatory diseases, congenital heart disease, or severe renal/liver disease were therefore excluded from the study. However, the presence of malignancy did not affect our results in regression analysis. Platelets swell until 120 minutes in ethylene diamine tetra acetic (EDTA) and until 60 minutes in citrate [2]. Authors suggest that optimal measuring time should not exceed 120 minutes. The blood samples of the patients were taken within 1 hour after their emergency admission. All blood samples in our study were tested within 1 hour of collection [3]. We used EDTA for whole blood anticoagulation. The mean duration of symptoms prior to admission was 5.04 ± 6.9 days. The drugs such as corticosteroids affect inflammatory parameters. Therefore, we excluded inflammatory diseases without emphasizing corticosteroids or other anti-inflammatory drugs.

Prognostic role of NLR, PLR, and LMR in patients with pulmonary embolism.

Pulmonary embolism (PE) is associated with significant morbidity and mortality. New biological markers are being investigated for estimating the prognosis of PE patients. Since PE is closely associated with inflammatory status, the neutrophil-lymphocyte (NLR), platelet-lymphocyte (PLR), and lymphocyte-monocyte (LMR) ratios were suggested to be useful in predicting patient outcomes. This study aimed to evaluate the prognostic role of NLR, PLR, and LMR in PE. A total of 103 PE cases from a cardiology department were included in the study. We retrospectively evaluated demographic and clinical characteristics, treatments, laboratory and imaging findings, and outcomes of patients. The median follow-up of PE patients was 39 months, and the 5-year overall survival probability was 73.8%. Out of 103 patients, 20 were classified as high risk PE cases (19.4%). Thrombolytic treatment was administered to 23 patients (22.3%). Systolic pulmonary arterial pressure was measured during one year, showing a significant decrease from 51.7 ± 15.7 mmHg at admission to 26.6 ± 4.0 mmHg at first year assessment. Age (OR: 1.06, p < 0.001) and NLR (OR: 1.52, p < 0.0019) were significantly associated with the disease status. The independent prognostic factors in moderate-low and low risk PE groups were NLR (HR: 1.17, p = 0.033) and LMR (HR: 1.58, p = 0.046). In moderate-high and high risk PE patients, the independent prognostic factors were age (HR: 1.07, p = 0.014) and PLR (HR: 1.01, p = 0.046). NLR, PLR, and LMR were associated with the prognosis of PE patients. The clinical severity of PE should be considered when utilizing these markers to assess patient outcomes.

Relation of platelet indices to severity of coronary artery disease in patients undergoing primary percutaneous coronary intervention.

AIM: We investigated the association between platelet indices and the severity of coronary artery disease (CAD) in patients with ST-segment-elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PPCI). METHODS: A total of 484 consecutive patients who were routinely referred to coronary angiography for STEMI and 81 age- and gender-matched patients with normal coronary arteries were included in the present study. We analyzed the relation between the platelet distribution width (PDW) and the angiographic severity of CAD. The SYNTAX score was used for assessing the severity of coronary atherosclerosis. RESULTS: The mean platelet volume (MPV), the plateletcrit (PCT) and the neutrophil levels were significantly higher in the STEMI group than in the control group. Patients with an elevated SYNTAX score (>32) had higher PDW values. The levels of plateletcrit and the estimated glomerular filtration rate (eGFR) were lower in the high SYNTAX score group compared to the moderate-to-low SYNTAX score group. The PDW was positively correlated with age (r = 0.128, p=0.004) and SYNTAX score (r = 0.209, p<0.001). There was a mild, significant inverse association between the PDW level and the eGFR (r = -0.101, p=0.049), the mean platelet volume (MPV) (r = -290, p<0.001) and the PCT (r = -345, p<001). Using multivariate logistic regression analysis, we found that age (OR = 1.046, 95% CI 1.013-1.079, p=0.005), diabetes (OR = 4.779, 95% CI 2.339-9.767, p<0.001) and PDW (OR = 1.229, 95% CI 1.072-1409, p=0.003) were independent correlates of high SYNTAX score. CONCLUSION: Platelet distribution width, an inexpensive and easily measurable laboratory variable, is independently associated with high SYNTAX score.

Predictors of slow flow in angiographically normal coronary arteries.

INTRODUCTION: Slow coronary flow (SCF) is a well-known angiographic finding; however, the pathophysiology of SCF remains only partially understood. In this study, we have examined the risk factors of slow coronary flow. METHODS: Seventy patients with angiographically proven SCF were studied along with 60 control participants. Patients were divided into 2 groups based on the angiographic findings as with or without SCF. In both groups, clinical information was collected and laboratory parameters were measured and compared. RESULTS: Patients with SCF had higher serum uric acid, creatinine and hemoglobin levels. They also more commonly had a history of smoking. On the other hand, C-reactive protein and hematologic parameters such as mean platelet volume (MPV), red cell distribution width (RDW), and neutrophil to lymphocyte (N/L) ratio did not differ significantly between the two groups. In the logistic regression analysis, only uric acid (odds ratio [OR]=1.583, 95% confidence interval [CI]=1.011-2.349, P=0.034) was found as an independent correlate of SCF. CONCLUSIONS: This study demonstrates that serum uric acid level is significantly correlated with SCF and may play a role in the development of the condition. These findings provide impetus for additional studies to confirm these results and treatment of SCF.