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In this paper, an on-line closed-loop identification of mainly mass and inertia of an under-actuated aerial vehicle, namely a quadrotor acting as an aerial manipulator, is presented. Being treated as a rigid body, only one set of eighteen- or six tri-axial linear accelerometers is used to facilitate such estimation. Force and torque disturbances acting upon the vehicle during identification are also estimated which will refine the overall estimation quality of the unknown parameters. Namely, recursive linear and nonlinear least squares methods are used to obtain initial and refined estimations, respectively. Random disturbances are introduced to the closed-loop system to ensure enough excitation of the overall system. Issues related to identifiability, stability and performance are discussed. Since the proposed method depends on general kinematical and dynamical analyses of motion, it is claimed that the presented method will be also applicable to a wider range of, mainly, aerial vehicles. [ABSTRACT FROM AUTHOR]

Post-thyroidectomy bleeding is a fortunately rare but potentially life-threatening complication that may increase postoperative morbidity and hospital stay. In this case series, we demonstrate the relation between the measurement of neck circumference and haemorrhage following thyroid surgery and the value of this measurement in predicting post-thyroidectomy haemorrhage. Currently, there is no simple and reliable method available for the early detection of post-thyroidectomy bleeding. Continuous pressure measurement could be a potential tool for the early detection of haemorrhage but is invasive, and more data are required to recommend threshold values for revision surgery. Early recognition and prompt surgical intervention are key to the management of cervical haematoma. Measurement of the neck circumference is a valuable adjunct tool in the early recognition of post-thyroidectomy bleeding. In this case series, we concluded that a 4-cm increase in neck circumference may trigger the clinical decision for cervical exploration. [ABSTRACT FROM AUTHOR]

Objective: Rare disease Background: Rat bite fever (RBF) is a rare but fatal zoonotic disease caused by infections with various bacteria, which are transmitted from rats or other rodents. Only a few patients worldwide are diagnosed with RBF annually. RBF can be fatal if left untreated, with a mortality rate of about 10% in patients with severe RBF. Case Report: A case 37-year-old previously healthy man presented to the emergency department with acute gastroenteritis, sepsis and multi-organ failure requiring ventilatory support. He was later diagnosed with RBF due to Streptobacillus moniliformis. He recovered rapidly after administration of intravenous penicillin G and was discharged from the hospital 10 days later. Conclusions: This report describes a patient with RBF and multi-organ involvement requiring ventilatory support. He was successfully treated with intravenous penicillin G. To our knowledge, this is the first report of a patient from Qatar with RBF. [ABSTRACT FROM AUTHOR]

The authors urge clinicians to consider the possibility of Arnold‐Chiari Malformation type 1 with other central causes especially in cases where acute respiratory failure is unexplainable. [ABSTRACT FROM AUTHOR]

Multiphase flow measurement is a very challenging issue in process industry. There are several techniques to estimate multiphase flow parameters. However, these techniques need correct identification of the flow patterns first. Artificial Intelligence is one of the promising technique for identifying the flow patterns. In this paper, we used an Artificial Neural Network (ANN) for flow pattern identification but with pre-processing stage using natural logarithmic normalization. This pre-processing stage helps to normalize large data range and to reduce overlapping between flow patterns. Thus, the validity of the model was extended by using dimensionless inputs to be implemented for horizontal pipes of various diameters, liquid densities and viscosities. The concept was validated by building and testing the model using experimental data as well as well-known multiphase flow models. An ANN model was built using three dimensionless parameters only, namely, Liquid Reynolds Number, Gas Reynolds Number and Pressure Drop Multiplier. The present model achieved more than 97% accuracy in classifying the flow patterns for wide range of flow conditions. [ABSTRACT FROM AUTHOR]

Many industrial sectors built cogeneration plants to secure their power supplies reliably and to efficiently produce the plant demand of steam through the associated heat. Due to the rise of fuel cost and tightening environmental regulations, the number of cogeneration plants will increase in lieu to individual boilers and steam turbine generators. Most of the recent cogeneration plants are equipped with hardware-based analyzer which is a continuous emission monitoring system (CEMS) to monitor the NOx emissions from the plant stack as per US. Environmental Protection Agency (EPA) regulations. The CEMS is unreliable due to high failure rates and requires high capita! cost, high maintenance cost, high operational cost in addition to being subject to long lag time and having slow response. In this work, a software-based analyzer is designed by applying artificial neural networks (ANNs) on process data collected from cogeneration plant (156 MW X 2 combustion gas turbine generators (CGTGs)) equipped with CEMS for NOx monitoring. The developed soft analyzer will be used to verify the existing CEMS readings and used as a reliable tool to monitor the NOx emissions that will eventually replace the CEMS. By providing a relationship between the process and the emissions, the soft analyzer will also assist in understanding the NOx behavior in reference to the process variations and thus enables better emission control. [ABSTRACT FROM AUTHOR]

In many cogeneration systems, one or more boilers are used in hot standby to meet the plant demand of steam in case of failure or upset in the cogeneration unit. Such boilers need to quickly respond to sudden and large steam load changes. However, fast changes in the firing rate cause transient changes in both the drum-boiler steam pressure and drum level, in addition to the potential of developing of thermal stresses in the walls of steam risers. A genetic algorithm (GA) based optimization scheme is proposed for tuning the conventional boiler control loops to maximize the ability of the boiler to respond to large steam demand while keeping the fluctuations in pressure, drum level, and feed rate within acceptable operation limits. A nonlinear model for an actual boiler is first built, validated, and then, it is used to demonstrate the performance of the boiler with the proposed control loop optimization. [ABSTRACT FROM AUTHOR]

Changing the position of the Center of Gravity (CoG) for an aerial vehicle is a challenging part in navigation, and control of such vehicles. In this paper, an all-accelerometers-based inertial measurement unit is presented, with a proposed method for on-line estimation of the position of the CoG. The accelerometers' readings are used to find and correct the vehicle's angular velocity and acceleration using an Extended Kalman Filter. Next, the accelerometers' readings along with the estimated angular velocity and acceleration are used in an identification scheme to estimate the position of the CoG and the vehicle's linear acceleration. The estimated position of the CoG and motion measurements can then be used to update the control rules to achieve better trim conditions for the air vehicle. [ABSTRACT FROM AUTHOR]

Abstract: Inferential sensing, or soft sensing, gained popularity in recent years as an alternative to continuous emission monitoring systems because of its simplicity, reliability, and cost effectiveness as compared to analogous hardware sensors. In this paper we address the problem of NO x emission using a model of furnace of an industrial boiler, and propose a neural network structure for high performance prediction of NO x as well as O2. The studied boiler is 160MW, gas fired with natural gas, water-tube boiler, having two vertically aligned burners. The boiler model is a 3D problem that involves turbulence, combustion, radiation in addition to NO x modeling. The 3D computational fluid dynamic model is developed using Fluent simulation package. The model provides calculations of the 3D temperature distribution as well as the rate of formation of the NO x pollutant, enabling a better understanding on how and where NO x are produced. The boiler was simulated under various operating conditions. The generated data is then used for initial development and assessment of neural network soft sensors for emission prediction based on the conventional process variable measurements. The performance of the proposed soft sensor is then evaluated using actual data from an industrial boiler. The developed soft sensor achieves comparable accuracy to the continuous emission monitor analyzer, however, with substantial reduction in the cost of equipment and maintenance. [Copyright &y& Elsevier]

COVID-19 is a global pandemic that caused a dramatic loss of human life worldwide, leading to accelerated research for antiviral drug discovery. Herbal medicine is one of the most commonly used alternative medicine for the prevention and treatment of many conditions including respiratory system diseases. In this study, a computational pipeline was employed, including network pharmacology, molecular docking simulations, and molecular dynamics simulations, to analyze the common phytochemicals of ginger rhizomes and identify candidate constituents as viral inhibitors. Furthermore, experimental assays were performed to analyze the volatile and non-volatile compounds of ginger and to assess the antiviral activity of ginger oil and hydroalcoholic extract. Network pharmacology analysis showed that ginger compounds target human genes that are involved in related cellular processes to the viral infection. Docking analysis highlighted five pungent compounds and zingiberenol as potential inhibitors for the main protease (Mpro), spike receptor-binding domain (RBD), and human angiotensin-converting enzyme 2 (ACE2). Then, (6)-gingerdiacetate was selected for molecular dynamics (MD) simulations as it exhibited the best binding interactions and free energies over the three target proteins. Trajectories analysis of the three complexes showed that RBD and ACE2 complexes with the ligand preserved similar patterns of root mean square deviation (RMSD) and radius of gyration (Rg) values to their respective native structures. Finally, experimental validation of the ginger hydroalcoholic extract confirmed the existence of (6)-gingerdiacetate and revealed the strong antiviral activity of the hydroalcoholic extract with IC 50 of 2.727 μ g / ml . Our study provides insights into the potential antiviral activity of (6)-gingerdiacetate that may enhance the host immune response and block RBD binding to ACE2, thereby, inhibiting SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Background: Thoracic duct ligation (TDL) during esophagectomy has been proposed to reduce the risk of postoperative chylothorax. Because of its role in immunoregulation, some authors argued that it had an unfavorable TDL effect on survival. The aim of this study was to analyze the effect of TDL on overall survival (OS). Methods: PubMed, MEDLINE, Scopus, and Web of Science were searched through December 2023. The primary outcome was 5-year OS. The restricted mean survival time difference (RMSTD), hazard ratios (HRs), and 95% confidence intervals (CI) were used as pooled effect size measures. The GRADE methodology was used to summarize the certainty of the evidence. Results: Five studies (3291 patients) were included. TDL was reported in 54% patients. The patients' age ranged from 49 to 69, 76% were males, and BMI ranged from 18 to 26. At the 5-year follow-up, the combined effect from the multivariate meta-analysis is -3.5 months (95% CI −6.1, −0.8) indicating that patients undergoing TDL lived 3.5 months less compared to those without TDL. TDL was associated with a significantly higher hazard for mortality at 12 months (HR 1.54, 95% CI 1.38–1.73), 24 months (HR 1.21, 95% CI 1.12–1.35), and 28 months (HR 1.14, 95% CI 1.02–1.28). TDL and noTDL seem comparable in terms of the postoperative risk for chylothorax (RR = 0.66; p = 0.35). Conclusions: In this study, concurrent TDL was associated with reduced 5-year OS after esophagectomy. This may suggest the need of a rigorous follow-up within the first two years of follow-up. [ABSTRACT FROM AUTHOR]

Pregnant women are potentially more susceptible to respiratory tract infections making them a high‐risk group. We describe the successful management of a 35‐year‐old pregnant woman, G3, P1, with a history of a cesarean section who tested positive for COVID‐19 at 26 weeks and required critical care support. [ABSTRACT FROM AUTHOR]

Background: Critical illness-associated cerebral microbleeds and leukoencephalopathy connected to coronavirus disease 2019 (COVID-19) infection are emerging areas of concern in current medical literature. Methods: We reviewed cases of patients with COVID-19-associated neurological manifestations to study the prevalence and outcome of such conditions. Case Series Findings: Our review yielded seven distinct patients. Six exhibited cerebral microbleeds, primarily localized in the juxtacortical white matter and the corpus callosum. In contrast, one individual presented with leukoencephalopathy. Tragically, of these patients, five succumbed to their ailments. One was discharged with mild cognitive impairments, while another underwent a tracheostomy and was subsequently moved to a long-term care establishment. Conclusion: Our findings underscore the significance of neuro-radiological observations in those grappling with severe manifestations of COVID-19, drawing attention to the possible neurological repercussions of the virus. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports within the issue on topics including the Quranic speech database for Arabic speaker recognition, the representation of semantic lexicons through an ontology model, and the authentication of Hadiths with the creation of an ontology of Hadiths narration.

Boiler's efficiency is one of the important performance indicators of boiler. To keep track of operation cost, efficiency needs to be calculated with adequate accuracy by employing effective mathematical tools. In this work, a new modification in conventional mathematical formulation of efficiency is presented based on time-varying efficiency using timevarying operational variables of boiler. This modification was accomplished using indirect method of efficiency by applying experimental data of variables for certain time span. Moreover a second-order dynamic model of flue gas temperature (FGT) has been derived to construct the mathematical formulation of efficiency only in terms of available inputs. The resulting input-output-based model proved to be in quite agreement with efficiency calculated from experimental data. After modeling, influence of variations in air to fuel ratio (AFR) and fuel flow rate (FFR) upon efficiency has been discussed and it has been shown that time-varying efficiency covers deeper aspect of dynamic relation between efficiency and other input of boiler especially AFR and FFR. Moreover, it has been established that efficiency interacts with the dynamics of boiler, and in this respect, a dynamic relation between combustion process and boiler dynamics has been constructed via efficiency. [ABSTRACT FROM AUTHOR]

Background: The main reason for treatment failure after curative surgical resection of gastric cancer is intra-abdominal spread, with 40-50% peritoneal seeding as primary localization of recurrence. Peritoneal relapse is seen in 60-70% of tumors of diffuse type, compared to only 20-30% of intestinal type. Hyperthermic IntraPEritoneal Chemoperfusion (HIPEC) is an increasingly used therapy method for patients with peritoneal metastases. The preventive use of HIPEC could represent an elegant approach for patients (pts) before macroscopic peritoneal seeding, since pts. with operable disease are fit and may have potential risk of microscopic involvement, thus having a theoretical chance of cure with HIPEC even without the need for cytoreduction. No results from a PCRT from the Western hemisphere have yet been published.Methods: This is a multicenter, randomized, controlled, open-label study including a total of 200 pts. with localized and locally advanced diffuse or mixed type (Laurens's classification) adenocarcinoma of the stomach and Type II/III GEJ. All enrolled pts. will have received 3-6 pre-operative cycles of biweekly FLOT (Docetaxel 50 mg/m2; Oxaliplatin 85 mg/m2; Leucovorin 200 mg/m2; 5-FU 2600 mg/m2, q2wk). Pts will be randomized 1:1 to receive surgery only and postoperative FLOT (control arm) or surgery + intraoperative HIPEC (cisplatin 75 mg/m2 solution administered at a temperature of 42 °C for 90 min) and postoperative FLOT (experimental arm). Surgery is carried out as gastrectomy or transhiatal extended gastrectomy. Primary endpoint is PFS/DFS, major secondary endpoints are OS, rate of pts. with peritoneal relapse at 2 and 3 years, perioperative morbidity/mortality and quality of life. The trial starts with a safety run-in phase. After 20 pts. had curatively intended resection in Arm B, an interim safety analysis is performed. Recruitment has already started and first patient in was on January 18th, 2021.Discussion: If the PREVENT concept proves to be effective, this could potentially lead to a new standard of therapy. On the contrary, if the outcome is negative, pts. with gastric cancer and no peritoneal involvement will not be treated with HIPEC during surgery.Trial Registration: The study is registered on June 25th, 2020 under ClinicalTrials.gov Identifier: NCT04447352 ; EudraCT: 2017-003832-35 . [ABSTRACT FROM AUTHOR]

Portomesenteric vein thrombosis (PMVT) is a rare post-operative complication of bariatric procedures, occurring in between 0.3% and 1% of cases. A structured questionnaire consisting of 27 items was available online to members of the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) to investigate the occurrence of PMVT. A total of 89 bariatric surgeons from 61 countries participated. Twenty-six (29.21%) reported at least one case of PMVT (46.15% males; 53.84% females). The surgery most associated with PMVT occurrence was sleeve gastrectomy (84.6%), followed by Roux-en-Y gastric bypass (RYGB) (7.69%), and laparoscopic adjustable gastric banding (LAGB) (7.69%). The time gap between surgery and PMVT was 19.28 ± 8.72 days. The predominant symptom was abdominal pain in 96.15% of patients, followed by fever in 26.9%. Complete occlusion of the portal vein was reported in 34.6% of cases, with involvement of the portal system in 69%, extension to the superior mesenteric district in 23%, and extension to the splenic vein in two patients (7.7%). Our survey, which is the largest regarding PMVT to date, revealed a diffuse lack of standardization in the choice, duration, and dosing of prophylaxis regimens as well as treatment modalities, reflecting the literature gap on the topic. [ABSTRACT FROM AUTHOR]

Most of the post‐renal transplant patients are taking immunosuppressive medications, including calcineurin inhibitors, anti‐proliferative agents, and steroids. This case series highlights the clinical characteristics and outcomes of eight post‐renal transplant patients with severe COVID‐19 infection admitted to the intensive care unit. [ABSTRACT FROM AUTHOR]

This article presents an alternative technique to the common Toupet fundoplication. It is a modern combination of the standard Toupet procedure and an additional fundophrenicopexie of the gastric wrap. In 1963 Toupet first described his technique of a fundoplication for reflux surgery. Over the past years this procedure has been modified and expanded many times. We have learned that the short gastric vessels need to be divided to get the wrap closer and easier around the esophagus. Furthermore, it is likely necessary to perform a balanced hiatoplasty to avoid slippage of the wrap. Our procedure is a modification of the standard Toupet fundoplication, but is extended by fixing the wrap to the anterior wall of the diaphragm. We consider our modification successful and safe in treating gastroesophageal reflux disease in patients with type I/II hiatal hernia and prevent postoperative complications such as dysphagia or slippage of the wrap. [ABSTRACT FROM AUTHOR]

Burning fossil fuels is a major concern for global warming control. In Saudi Arabia, steam power plants that relay on boilers to produce the steam accounted for around 50% of the total electricity generation capacity in 2021, in addition to 15% capacity from co-generation power plants. Fossil-based energy production produces harmful emissions, mostly NOx. The case of combustion efficiency and NOx emissions is complicated and cannot be addressed by simple theoretical model. This paper investigates the existing literature exploring data driven approaches via Artificial Intelligence (AI) and machine learning (ML) in a variety of applications, including mainly boiler optimization for efficient and clean energy production. The study discusses the importance of energy intelligence for industries in supporting decision making and prediction considering supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Expert systems, artificial neural networks (ANN), genetic algorithms (GA), fuzzy logic (FL), and different hybrid systems, which incorporate two or more techniques, are all included in AI systems. A condensed review of some recent literature is presented on the applications of support vector machines, ANN, GA, FL, and hybrid systems to combustion systems for emphasizing boilers' performance and emissions. An overview of boiler dynamics and control are presented and the use of AI for trade-off between boiler's efficiency and NOx emissions is discussed, with special focus being made on hydrogen combustion. The reported findings in this study demonstrate the promise of AI in control of emissions and optimization of performance in boilers with the least amount of construction and operating expenditures. The complexity and a number of restrictions present in emissions control systems, however, may reduce the likelihood of success. The specific perspectives are found to be data availability, data reliability, validity of methodology, and system complexity. It is concluded that wide variety of AI approaches have been used in a diversity of disciplines for modelling, predicting performance and controlling emissions of combustion processes. It is indicated that data representing the history and performance of real systems along with the proper selection of the AI model are crucial for setting up such systems. Based on this study, it can be stated that AI models are great tools towards better performance of boilers at minimum emissions. [ABSTRACT FROM AUTHOR]

Patient: Female, 40 Final Diagnosis: Dexmedetomidine withdrawal Symptoms: Severe agitation • sweating • tachycardia Medication: -- Clinical Procedure: None Specialty: Critical Care Medicine Objective: Unusual or unexpected effect of treatment Background: Dexmedetomidine is a sedating agent approved for use in non-intubated patients and procedural sedation due to its efficacy in conscious sedation and minimal risks of respiratory depression. Previous reports proved the effectiveness of clonidine in treatment of withdrawal symptoms, but none have discussed cases with co-existing non-controlled psychiatric illness and prolonged duration of dexmedetomidine exposure. Case Report: We report a case of a 40-year-old woman diagnosed with viral meningitis. Due to her complicated psychiatric illness and viral meningitis, she developed severe agitation unresponsive to standard therapy. The patient had to be placed on dexmedetomidine, to which she developed dependence. There were several attempts to gradually withdraw dexmedetomidine but these were unsuccessful despite adding multiple antipsychotic medications. Withdrawal was manifested in multiple symptoms, including severe agitation, sweating, and tachycardia. Clonidine was used and was an effective treatment option to successfully withdraw the patient from dexmedetomidine. A smaller initial dose was used due to low baseline systolic blood pressure, which was successful. Conclusions: This report proves that clonidine is an effective option for treatment of dexmedetomidine dependence compared to other antipsychotic agents. The present report is the first to discuss severe psychiatric illness and prolonged dexmedetomidine duration (>7 days) in a non-intubated patient. Dexmedetomidine withdrawal must be considered in the differential diagnosis of patients with psychiatric illness, which can be easily treated with clonidine. [ABSTRACT FROM AUTHOR]

Deviated, horizontal, and multilateral wells are drilled to increase the contact area between the well path and the reservoir and as a result, the well productivity will be increased. Directional steering systems (DSS) are used to control the direction in nonvertical wells. Rotary steerable system (RSS) is the current state of the art of DSS. In this research, the problem of real-time control of autonomous RSS with unknown formation rock strength was presented. The aim of this study is to develop a real-time control scheme for real-time optimization of drilling parameters to (1) maximize the rate of penetration (ROP), (2) minimize the deviation from the planned well bore trajectory, (3) reduce the stick-slip oscillations, and (4) assess the degree of bit wear. Nonlinear model for the drilling operation was developed using energy balance equation, where rock specific energy (RSE) is used to calculate the minimum power required for a given ROP. A proposed mass spring system was used to represent the phenomena of stick-slip oscillation. The model parameters have been adaptively estimated at each control iteration to tackle any disturbances or variations in the formation properties. The bit wear is mathematically represented using Bourgoyne model. Detailed mathematical formulation and computer simulation were used for evaluation of the performance of the proposed technique based on real well field data. The obtained results showed excellent ability to accommodate the changes in the formation properties. In addition, the rates of bit wear and stick-slip oscillations have been optimized. [ABSTRACT FROM AUTHOR]

Statistical process control is being used along with classical feedback control systems (which are also termed as Engineering Process Control, EPC) for the purposes of detecting faults and avoiding over adjustment of the processes. This paper evaluates the effectiveness of integrating SPC with EPC for both fault detection and control. A novel framework for fault detection using Multivariate Statistical Process Control (MSPC) is proposed here and illustrated with a case study. The simultaneous application of MSPC control charts to process inputs and outputs or in other words 'joint monitoring' of process inputs and outputs is shown here to provide efficient fault detection capabilities. An example of Heating Ventilation and Air Conditioning (HVAC) systems is simulated here and used as a case study to demonstrate the detection capabilities of the proposed framework. Moreover, the capabilities of the proposed framework were enhanced by inclusion of a corrective action scheme, thus leading to a complete control system with fault detection and correction. [ABSTRACT FROM AUTHOR]

This paper describes the preparation, recording, analyzing, and evaluation of a new speech corpus for Modern Standard Arabic (MSA). The speech corpus contains a total of 415 sentences recorded by 40 (20 male and 20 female) Arabic native speakers from 11 different Arab countries representing three major regions (Levant, Gulf, and Africa). Three hundred and sixty seven sentences are considered as phonetically rich and balanced, which are used for training Arabic Automatic Speech Recognition (ASR) systems. The rich characteristic is in the sense that it must contain all phonemes of Arabic language, whereas the balanced characteristic is in the sense that it must preserve the phonetic distribution of Arabic language. The remaining 48 sentences are created for testing purposes, which are mostly foreign to the training sentences and there are hardly any similarities in words. In order to evaluate the speech corpus, Arabic ASR systems were developed using the Carnegie Mellon University (CMU) Sphinx 3 tools at both training and testing/decoding levels. The speech engine uses 3-emitting state Hidden Markov Models (HMM) for tri-phone based acoustic models. Based on experimental analysis of about 8 h of training speech data, the acoustic model is best using continuous observation's probability model of 16 Gaussian mixture distributions and the state distributions were tied to 500 senones. The language model contains uni-grams, bi-grams, and tri-grams. For same speakers with different sentences, Arabic ASR systems obtained average Word Error Rate (WER) of 9.70%. For different speakers with same sentences, Arabic ASR systems obtained average WER of 4.58%, whereas for different speakers with different sentences, Arabic ASR systems obtained average WER of 12.39%. [ABSTRACT FROM AUTHOR]

Objectives: To assess the effect of anticoagulation with bivalirudin administered intravenously on gas-exchange in patients with COVID-19 and respiratory failure using invasive mechanical ventilation.Trial Design: This is a single centre parallel group, superiority, randomized (1:1 allocation ratio) controlled trial.Participants: All patients admitted to the Hamad Medical Corporation -ICU in Qatar for COVID-19 associated respiratory distress and in need of mechanical ventilation are screened for eligibility.Inclusion Criteria: all adult patients admitted to the ICU who test positive for COVID-19 by PCR-test and in need for mechanical ventilation are eligible for inclusion. Upon crossing the limit of D-dimers (1.2 mg/L) these patients are routinely treated with an increased dose of anticoagulant according to our local protocol. This will be the start of randomization.Exclusion Criteria: pregnancy, allergic to the drug, inherited coagulation abnormalities, no informed consent.Intervention and Comparator: The intervention group will receive the anticoagulant bivalirudin intravenously with a target aPTT of 45-70 sec for three days while the control group will stay on the standard treatment with low-molecular-weight heparins /unfractionated heparin subcutaneously (see scheme in Additional file 1). All other treatment will be unchanged and left to the attending physicians.Main Outcomes: As a surrogate parameter for clinical improvement and primary outcome we will use the PaO2/FiO2 (P/F) ratio.Randomisation: After inclusion, the patients will be randomized using a closed envelope method into the conventional treatment group, which uses the standard strategy and the experimental group which receives anticoagulation treatment with bivalirudin using an allocation ratio of 1:1.Blinding (masking): Due to logistical and safety reasons (assessment of aPTT to titrate the study drug) only the data-analyst will be blinded to the groups.Numbers To Be Randomised (sample Size): We performed a sample size calculation and assumed the data for P/F ratio (according to literature) is normally distributed and used the mean which would be: 160 and SD is 80. We expect the treatment will improve this by 30%. In order to reach a power of 80% we would need 44 patients per group (in total 88 patients). Taking approximately 10% of dropout into account we will include 100 patients (50 in each group).Trial Status: The local registration number is MRC-05-082 with the protocol version number 2. The date of approval is 18th June 2020. Recruitment started on 28th June and is expected to end in November 2020.Trial Registration: The protocol is registered before starting subject recruitment under the title: "Anticoagulation in patients suffering from COVID-19 disease. The ANTI-CO Trial" in ClinicalTrials.org with the registration number: NCT04445935 . Registered on 24 June 2020.Full Protocol: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 2). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol. [ABSTRACT FROM AUTHOR]