Null.

The introduction of IMO2020, the outbreak of COVID-19, and the oil price drop in 2020 had a significant impact on operators operating profits. Therefore, a competitive analysis of bunkering spots that suggests the optimal location for bunkering is of interest. This paper uses a combination of primary and secondary research, both from operators and suppliers side, to identify the key performance factors (KPFs) affecting the decision-making process of a bunkering port selection process. Answers were then combined by using a fuzzy TOPSIS analytical approach to quantify the competitive position of each port in the Amsterdam-Rotterdam-Antwerp (ARA) region. Results suggest that availability of low sulfur bunkers, bunker quality, bunker price, reliability, punctuality, and safety of bunkering services, as well as usage and availability of barges are the key KPFs in order of importance. Sulfur cap has not changed the competitive environment in the region as the geographic advantage of the port of Rotterdam plays a crucial role in the comparison with the other ports, in contrast to expressed concerns in the industry.

BACKGROUND: The recent COVID-19 outbreak in Wuhan, China, has quickly spread throughout the world. In this study, we systematically reviewed the clinical features and outcomes of pregnant women with COVID-19. METHODS: PubMed, Web of Science, EMBASE and MEDLINE were searched from January 1, 2020, to April 16, 2020. Case reports and case series of pregnant women infected with SARS-CoV-2 were included. Two reviewers screened 366 studies and 14 studies were included. Four reviewers independently extracted the features from the studies. We used a random-effects model to analyse the incidence (P) and 95% confidence interval (95% CI). Heterogeneity was assessed using the I2 statistic. RESULTS: The meta-analysis included 236 pregnant women with COVID-19. The results were as follows: positive CT findings (71%; 95% CI, 0.49-0.93), caesarean section (65%; 95% CI, 0.42-0.87), fever (51%; 95% CI, 0.35-0.67), lymphopenia (49%; 95% CI, 0.29-0.70), coexisting disorders (33%; 95% CI, 0.21-0.44), cough (31%; 95% CI, 0.23-0.39), fetal distress (29%; 95% CI, 0.08-0.49), preterm labor (23%; 95% CI, 0.14-0.32), and severe case or death (12%; 95% CI, 0.03-0.20). The subgroup analysis showed that compared with non-pregnant patients, pregnant women with COVID-19 had significantly lower incidences of fever (pregnant women, 51%; non-pregnant patients, 91%; P < 0.00001) and cough (pregnant women, 31%; non-pregnant patients, 67%; P < 0.0001). CONCLUSIONS: The incidences of fever, cough and positive CT findings in pregnant women with COVID-19 are less than those in the normal population with COVID-19, but the rate of preterm labor is higher among pregnant with COVID-19 than among normal pregnant women. There is currently no evidence that COVID-19 can spread through vertical transmission.

In this cross-sectional study, we investigated the seroprevalence of SARS-CoV-2 antibodies in workers of radio and television (TV) in Sergipe state, Northeast Brazil. The study was conducted from December 1 to December 20, 2020, considered the beginning of the second wave of COVID-19 in the state. Our findings showed a high seroprevalence of SARS-CoV-2 antibodies in radio and TV workers, especially among those in the production and operation teams. Prevention and control protocols against COVID-19 should be revised and implemented by media companies. Broadcast media workers should be prioritized in COVID-19 vaccine strategies.

Since its discovery, more than 37 million people have been infected by SARS-CoV-2 with deaths around 1 million worldwide. The prevalence is not known because infected individuals may be asymptomatic. In addition, the use of specific diagnostic tests is not always conclusive, raising doubts about the etiology of the disease. The best diagnostic method and the ideal time of collection remains the subject of study. The gold standard for diagnosing COVID 19 is the RT PCR molecular test, usually using an oropharynx and nasopharynx swab. Its sensitivity is 70% and drops significantly after the second week of symptoms. Serological tests, in turn, have increased sensitivity after 14 days, and can contribute to the diagnosis when SARS-CoV-2 infection is suspected, even with negative RT PCR. Our study showed sensitivity and specificity of 100% of the serological test (ELISA method) for cases of viral pneumonia caused by the new coronavirus, suggesting that this test could assist in the diagnosis of pulmonary interstitial changes that have not yet been etiologically clarified. We found a greater immune response in men, regardless of the severity of symptoms. The greater the severity, the higher the levels of IgA and IgG, mainly found in patients with multilobar impairment and in need for oxygen. We concluded that the serological test collected around 30 days after the onset of symptoms is the best diagnostic tool in the convalescence phase, not only for epidemiological purposes, but also for the etiological clarification of pulmonary changes that have not yet been diagnosed.

The use of imaging data has been reported to be useful for rapid diagnosis of COVID-19. Although computed tomography (CT) scans show a variety of signs caused by the viral infection, given a large amount of images, these visual features are difficult and can take a long time to be recognized by radiologists. Artificial intelligence methods for automated classification of COVID-19 on CT scans have been found to be very promising. However, current investigation of pretrained convolutional neural networks (CNNs) for COVID-19 diagnosis using CT data is limited. This study presents an investigation on 16 pretrained CNNs for classification of COVID-19 using a large public database of CT scans collected from COVID-19 patients and non-COVID-19 subjects. The results show that, using only 6 epochs for training, the CNNs achieved very high performance on the classification task. Among the 16 CNNs, DenseNet-201, which is the deepest net, is the best in terms of accuracy, balance between sensitivity and specificity, [Formula: see text] score, and area under curve. Furthermore, the implementation of transfer learning with the direct input of whole image slices and without the use of data augmentation provided better classification rates than the use of data augmentation. Such a finding alleviates the task of data augmentation and manual extraction of regions of interest on CT images, which are adopted by current implementation of deep-learning models for COVID-19 classification.

The lack of practical methods for a laboratory diagnosis of influenza C virus infections and the seemingly benign nature of the virus contribute to the fact that 50 years after its first isolation, relatively little is known about the epidemiology and the clinical impact of this virus. Reverse transcriptionCpolymerase chain reaction (RT-PCR) was used to amplify influenza C RNA fragments from clinical specimens. Two hundred otherwise healthy adults with recent onset of a common cold were studied. Nasopharyngeal aspirates were collected at entry to the study and 1 week later. Serum samples for antibody determinations were obtained at the first visit and after 3 weeks. Influenza C was detected in 7 of the 200 patients by 2 different RT-PCR formats. All 7 patients had a significant increase in antibody titers between serum samples collected during the acute and convalescent phases of the illness. Influenza C appears to be one of the many viruses that cause acute upper respiratory tract infections in adults

The current scenario of the pandemic COVID-19 has been a source of anchorage for researchers, healthcare professionals, and statisticians. Based on the immense data, it has been observed that the role of statistics has been crucial in researching and at the same for predicting the COVID-19 scenario of the entire globe. This paper deals with extensive data collection and predictive modeling to derive a CARD model using statistical tools like regression curve fitting. The exponential growth model has been prevalent in live updates via COVID-19 dashboards maintained by different organizations like WHO, Johns Hopkins University, Indian Council of Medical Research. In a similar tone, the paper discusses a time-varying exponential growth model specific to the Indian condition. However, a generic model has been derived by different researchers of other countries. The model accuracy has been considered satisfactory. Moreover, a State-wise Evaluation Indexing has been performed considering parameters like sanitation, population below the poverty line, literacy rate, and population density. Results have been shown for better data visualization through cartograms. The conclusions are noteworthy, and the CARD model can be trained and developed with better accuracy using the concept of machine and deep learning, keeping in context the huge amount of instantaneous data being generated every day all over the world.

Cardiovascular diseases (CVD) including acute myocardial infarction (AMI) rank first in worldwide mortality and according to the World Health Organization (WHO), they will stay at this rank until 2030. Prompt revascularization of the occluded artery to reperfuse the myocardium is the only recommended treatment (by angioplasty or thrombolysis) to decrease infarct size (IS). However, despite beneficial effects on ischemic lesions, reperfusion leads to ischemia-reperfusion (IR) injury related mainly to apoptosis. Improvement of revascularization techniques and patient care has decreased myocardial infarction (MI) mortality however heart failure (HF) morbidity is increasing, contributing to the cost-intense worldwide HF epidemic. Currently, there is no treatment for reperfusion injury despite promising results in animal models. There is now an obvious need to develop new cardioprotective strategies to decrease morbidity/mortality of CVD, which is increasing due to the aging of the population and the rising prevalence rates of diabetes and obesity. In this review, we will summarize the different therapeutic peptides developed or used focused on the treatment of myocardial IR injury (MIRI). Therapeutic peptides will be presented depending on their interacting mechanisms (apoptosis, necroptosis, and inflammation) reported as playing an important role in reperfusion injury following myocardial ischemia. The search and development of therapeutic peptides have become very active, with increasing numbers of candidates entering clinical trials. Their optimization and their potential application in the treatment of patients with AMI will be discussed.

BACKGROUND: Surgical intervention for neck of femur fractures continues to be prioritised during the Covid-19 pandemic. However, there remains a lack of clarity for clinicians during the consent process. This study quantifies additional perioperative risks for Covid-19 positive patients undergoing neck of femur fracture surgery and establishes an evidence-based framework for facilitating informed consent during the Covid-19 pandemic. METHOD: 259 patients undergoing neck of femur fracture surgery in four hospitals at the epicentre of the United Kingdoms first wave of Covid-19 were recruited. 51 patients were positive for Covid-19. Predefined outcomes were recorded in a 30-day postoperative period. RESULTS: Odds of intensive care admission were 4.64 times higher (95% CI 1.59-13.50, p = 0.005) and odds of 30-day mortality were 3 times higher (95% CI 1.22-7.40, p = 0.02) in Covid-19 positive patients. 74.5% of Covid-19 positive patients suffered post-operative complications. 35.3% of Covid-19 positive patients developed lower respiratory tract infection with 13.7% progressing to acute respiratory distress syndrome. 9.8% of Covid-19 positive patients experienced symptomatic thromboembolic events with a 3.9% incidence of pulmonary emboli. CONCLUSIONS: The implications of Covid-19 on the informed consent process for neck of femur fracture surgery are profound. Covid-19 positive patients should be consented for increased risk of postoperative complications (including lower respiratory tract infection, acute respiratory distress syndrome and thromboembolic events), longer inpatient stay, increased frequency of intensive care admission and higher risk of mortality.

Die H?matologie umfasst alle Erkrankungen, die das Blut, Blutbestandteile und die Blutfunktionen betreffen. In diesem Kapitel werden die ?tiologie, Pathologie, Klinik, Diagnostik und Therapie der wichtigsten An?mien (u. a. Eisenmangel-, Kugelzell-, Sichelzell?namie) und der akuten Leuk?mien (AML bzw. ALL) behandelt. Des Weiteren stehen maligne Lymphome und das multiple Myelom im Fokus. Darber hinaus ist ein eigener Abschnitt den Gerinnungsst?rungen gewidmet, darunter die Thrombozytopenien, H?mophilien und Koagulopathien. Abschlie?end wird auf Immundefizienzen und die Amyloidose eingegangen.

PURPOSE: The COVID-19 pandemic has affected health care systems worldwide, resulting in critical shortages of essential items and materials. The available guidelines are of little use for cancer hospitals in low-income and low-middleCincome countries. They have been designed for community hospitals serving in a centralized health care network. This study aimed to draft and field test a framework to establish a list of essential supplies that should be stockpiled for subsequent waves of the COVID-19 virus by a tertiary care cancer hospital in a low-middleCincome country. MATERIALS AND METHODS: A model was formulated using the consumption trends during the peak month of the first wave of COVID-19 infection to compile a list of essential materials and supplies. Furthermore, costing analyses were conducted to determine the financial benefits of stockpiling. RESULTS: A proposed list of items to stockpile, including personal protective equipment, radiology supplies, laboratory reagents, medication, and oxygen, was shared with the hospital administration. However, the hospital administration only accepted the proposals for stockpiling personal protective equipment and oxygen. CONCLUSION: This paper provides a framework and strategies that cancer hospitals and health care systems can modify and use as per individual, institutional requirements and specifications for stockpiling essential items during the COVID-19 or other similar pandemics.

BACKGROUND: Patients with cancer may be at high risk of adverse outcomes from SARS-CoV-2 infection. We analyzed a cohort of patients with cancer and COVID-19 reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anti-cancer therapies. PATIENTS AND METHODS: Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between March 17-November 18, 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anti-cancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients). RESULTS: 4,966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2,872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic Black race, Hispanic ethnicity, worse ECOG performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count, high absolute neutrophil count, low platelet count, abnormal creatinine, troponin, LDH, and CRP were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anti-cancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality. CONCLUSIONS: Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anti-cancer therapies.

OBJECTIVE: The global COVID-19 pandemic has changed healthcare across the world. Efforts have concentrated on managing this crisis, with impact on cancer care unclear. We investigated the impact on endoscopy services and gastrointestinal (GI) cancer diagnosis in the UK. DESIGN: Analysis of endoscopy procedures and cancer diagnosis at a UK Major General Hospital. Procedure rates and diagnosis of GI malignancy were examined over 8-week periods in spring, summer and autumn 2019 before the start of the crisis and were compared with rates since onset of national lockdown and restrictions on elective endoscopy. The number of CT scans performed and malignancies diagnosed in the two corresponding periods in 2019 and 2020 were also evaluated. RESULTS: 2 698 2516 and 3074 endoscopic procedures were performed in 2019, diagnosing 64, 73 and 78 cancers, respectively, the majority being in patients with alarm symptoms and fecal immunochemical test+ve bowel cancer screening population. Following initiation of new guidelines for management of endoscopy services 245 procedures were performed in a 6 week duration, diagnosing 18 cancers. This equates to potentially delayed diagnosis of 37 cancers per million population per month. Clinician triage improved, resulting in 13.6 procedures performed to diagnose one cancer. CONCLUSIONS: Our data demonstrate an 88% reduction in procedures during the first 6 weeks of COVID-19 crisis, resulting in 66% fewer GI cancer diagnoses. Triage changes reduced the number of procedures required to diagnose cancer. Our data can help healthcare planning to manage the extra workload on endoscopy departments during the recovery period from COVID-19.

Pandemics, such as Covid-19 and AIDS, tend to be highly contagious and have the characteristics of global spread and existence of multiple virus strains. To analyze the competition among different strains, a high dimensional SIR model studying multiple strains' competition in patchy environments is introduced in this work. By introducing the basic reproductive number of different strains, we found global stability conditions of disease-free equilibrium and persistence conditions of the model. The competition exclusion conditions of that model are also given. This work gives some insights into the properties of the multiple strain patchy model and all of the analysis methods used in this work could be used in other related high dimension systems.

OBJECTIVES: The novel coronavirus 2019 (COVID-19) has spread worldwide threatening human health. To reduce transmission, a 'lockdown' was introduced in Ireland between March-May 2020. The aim of this study is to capture the experiences of Consultant Psychiatrists during lockdown and their perception of it's impact on Mental Health Services. METHODS: A questionnaire designed by the Royal College of Psychiatrists was adapted and circulated to Consultant members of the College of Psychiatrists following the easing of restrictions. The questionnaire assessed the perceived impact on referral rates, mental health act provision, availability of Information Technology (IT), consultant well-being and availability of Personal Protective Equipment (PPE). Thematic analysis was employed to analyse free-text sections. RESULTS: Response rate was 32% (N=197/623). Consultants reported an initial decrease/significant decrease in referrals in the first month of lockdown (68%, N=95/140) followed by an increase/significant increase in the second month for both new (83%, N=100/137) and previously attending patients (65%, N=88/136). Social isolation and reduced face-to-face mental health supports were among the main reasons identified. The needs of children and older adults were highlighted. Most consultants (76%, N=98/129) felt their working day was affected and their well-being reduced (52%, N=61/119). The majority felt IT equipment availability was inadequate (67%, N=88/132). Main themes identified from free-text sections were service management, relationship between patients and healthcare service and effects on consultants' lives. CONCLUSIONS: The COVID19 pandemic has placed increased pressure on service provision and consultant wellness. This further supports the longstanding need to increase mental health service investment in Ireland.

BACKGROUND: the purpose is to gather and analyze the statistical datas of wrist and hand injuries admitted to the Hand and Reconstructive Microsurgery and Replantation Hub center of Careggi Hospital, Florence during the first two months of COVID-19 epidemic in Italy. The Authors investigated how the drastic changes in daily activities modified the epidemiology of hand trauma lesions. METHODS: The Authors analyzed the characteristics of hand and wrist traumatic disorders during the months of February and March comparing 2019 to 2020. Collected data included age distribution, traumatic etiology, diagnosis and type of surgical procedures. RESULTS: The total number of orthopedic and trauma patients significantly decrease in 2020 compared to 2019 (3360 vs 1470). The number of hand and wrist injuries didn't show a significant difference between 2019 and 2020 instead (192 vs 131). The overall number of patients hospitalized and surgically treated at our Operative Unit (OU) was 168 in 2019 and 120 in 2020. Male patients resulted prevalent (60,7 M vs 39,3F/2019; 63,2 M vs 36,8F/2020). In terms of patient age, in 2020 we registered a significant reduction of cases in the 20-35-year-old age group and a significant increase in the 51C65 and 66-80-year-old age groups. Traffic-related, sport-related and fortuitous injuries significantly decreased in 2020, while the number of domestic accidents significantly increased. Analyzing the Hospital Discharge Records (HDR), we found a significant increase in the number of proximal and middle phalanx fractures; no significant differences were found for other kinds of discharge diagnosis. As for the choice of surgical treatment options, no differences were found between 2019 and 2020. CONCLUSION: Even during drastic movement restrictions and the prolonged suspension of work and leisure activities secondary to COVID-19 epidemic in 2020, hand and wrist traumas rate remained almost the same compared to the same period of the previous year. Nevertheless, a significant change in the etiology and patient age was registered. In fact, sport and traffic-related traumas decreased respect to domestic traumas, while the previous prevalent involvement of young adults was surpassed by accidental hand traumas in the elderly and active adults.

Coronavirus disease (COVID-19) is highly contagious and pathogenic. Currently, the diagnosis of COVID-19 is based on nucleic acid testing, but it has false negatives and hysteresis. The use of lung CT scans can help screen and effectively monitor diagnosed cases. The application of computer-aided diagnosis technology can reduce the burden on doctors, which is conducive to rapid and large-scale diagnostic screening. In this paper, we proposed an automatic detection method for COVID-19 based on spatiotemporal information fusion. Using the segmentation network in the deep learning method to segment the lung area and the lesion area, the spatiotemporal information features of multiple CT scans are extracted to perform auxiliary diagnosis analysis. The performance of this method was verified on the collected dataset. We achieved the classification of COVID-19 CT scans and non-COVID-19 CT scans and analyzed the development of the patients' condition through the CT scans. The average accuracy rate is 96.7%, sensitivity is 95.2%, and F1 score is 95.9%. Each scan takes about 30 seconds for detection.

In general, during the COVID-19 pandemic there has been a growth in the use of digital technological solutions in many sectors, from that of consumption, to Digital Health and in particular to mobile health (mHealth) where an important role has been played by mobile technology (mTech). However, this has not always happened in a uniform way. In fact, in many cases, citizens found themselves unable to take advantage of these opportunities due to the phenomenon of the Digital Divide (). It depends on multifaceted aspects ranging from the lack of access to instrumental and network resources, to cultural and social barriers and also to possible forms of communication disability. In the study we set ourselves the articulated goal of developing a probing methodology that addresses the problems connected to in a broad sense, capable of minimizing the bias of a purely electronic submission and evaluating its effectiveness and outcome. At the moment, we have submitted the survey both electronically (with an embedded solution to spread it inside the families/acquaintances) and using the wire phone. The results highlighted three polarities (a) the coherence of the two methods; (b) the outcome of the entire submission in relation to key issues (e.g., familiarity on contact tracing Apps, medical Apps, social Apps, messaging Apps, Digital-health, non-medical Apps); (c) a Digital Divide strongly dependent on age and in particular for the elderly is mainly evident in the use of mTech in general and in particular in mHealth applications. Future developments of the study foresee, after adequate data-mining, an in-depth study of all the aspects proposed in the survey, from those relating to access to resources, training, disability and other cultural factors.

In the contemporary world, frugal innovation (FI) is the most discussed area to enhance corporate sustainable performance (CSP) in manufacturing firms. The knowledge management process (KMP) is also a key determinant of FI. Existing literature is limited to knowledge management (KM) and its impact on CSP. This study aims to determine the effect of the KMP (acquisition, dissemination, and application) on sustainable corporate performance with the association of FI. The survey method was used to collect data from 356 small and medium enterprises (SMEs) in China. Structure equation modeling was applied to obtain the results of collected data. Results show that all three dimensions of KM have a significant impact on CSP. Furthermore, FI also has a significant and positive impact on CSP. Results further show that FI partially mediates the relationship of the knowledge dissemination, knowledge application and sustainable corporate performance but no mediation role FI was found between knowledge acquisition and CSP. The findings of this study will provide useful insights for experts and manufacturers. It will help to understand the role of KM in their organizational behavior by being an economical manufacturing process. This study underscored the importance of the KMP to policymakers. In countries such as China that have global orders, KM is an essential determinant of FI. KM is a tool used to achieve CSP goals inside and outside of an enterprise, thus the development firms need to focus on KM.