Consultancy services in marine fisheries- A profile of technologies and experts

The ICAR system currently needs very effective partnership between the researchers and the user groups. The Central Marine Fisheries Research Institute, a premier Institute under the ICAR, has taken effective steps to introduce the services and technologies in the marine fisheries sector, achieved over the last 50 years R & D activities. With a viev/ to institutionalising transfer of technologies, the institute has constituted a Consultancy Processing Cell (CPC) in 1997 for effectively serving the needs of our clients, through the short term and long term trainings, consultancies, contract services and contract research

Evaluating Macroscopic DTA Models – For Who, When and How?

Over the past few decades, transport authorities globally have resorted to transport models for testing policy interventions and simulating the results as part of the ex-ante analysis. Within the domains of traffic assignment, there is a greater focus on the dynamic representation of traffic, which has proved to be more accurate when compared to their static counterparts. This has put Dynamic Traffic Assignment (DTA) Models at the forefront of development. Departing from the classical traffic flow theories Macroscopic DTA’s simulates aggregated traffic analogous to the flow of fluids or gases. This aggregation enables high-speed computation with the ability to achieve a stable equilibrium state within feasible model run times. Due to the large number of Macroscopic DTA models developed worldwide, the model user is posed with the problem of using the correct model for the correct application. The current research aims to provide an answer to this problem through the design, development, and validation of an evaluation framework for Macroscopic DTA’s. The objective evaluation of the DTA’s is performed through certain Measures of Performances (MoPs). The subjective side of evaluation showcases the differences in importance associated with model features which vary from model users to application domains. Three macroscopic DTA models popular in the Netherlands are used for the application of the framework: the MARPLE (Model for Assignment and Regional Policy Evaluation), StreamLine: MaDAM (Macroscopic Dynamic Assignment Model), and StreamLine: eGLTM (event-based Generalized Link Transmission Model). From the results, it is observed that For a Strategic Planning application, both MARPLE and StreamLine: eGLTM proved to be better alternatives, as they performed exceedingly better in achieving a stable state of convergence. However, as the time horizons of application became smaller as is the case with Tactical and Operational planning, the final score for StreamLine: MaDAM improved substantially due to its accuracy involved in link-level propagation and queuing. The evaluation scores also showcase the fundamental trade-off between model complexity and computational speed was visible from the results. We can observe variations across model users, which validates our original hypothesis that the right choice of a model primary depends on the person using it and the application it is deployed for.Civil Engineering | Transport and Plannin

Non-oncologic incidental uptake on FAPI PET/CT imaging.

Fibroblast-activation protein (FAP) is a serine protease classified in the dipeptidyl peptidase 4 (DPP4) family. FAP is predominantly expressed in activated fibroblasts such as the cancer-associated fibroblasts (CAFs). FAP expression in CAFs is associated with tumor progression and poor prognosis in solid cancers. Recently, radiolabeled FAP inhibitors (FAPI) has been developed, which enables positron emission tomography (PET) imaging of FAP. FAPI PET/CT can provide a higher tumor-to-background ratio (TBR) than 18F-fludeoxyglucose PET/CT in various cancers, and thus has attracted substantial attention. As studies on FAPI PET grow in number and size, incidental findings related to non-oncologic conditions have been increasingly reported. FAPI PET uptake has been reported in various conditions such as benign tumors, fibrotic, granulomatosis, scarring/wound, degenerative diseases, and inflammatory diseases.The knowledge of physiological and non-oncologic causes of FAPI uptake is indispensable for accurate FAPI PET/CT interpretation and can help appropriate management of incidental findings on FAPI PET/CT in patients referred for cancer staging indications. In this review article, we describe for each organ system (Brain, Oral mucosa, Salivary Glands, Thyroid, Lung, Myocardium, Breast, Esophagus, Stomach, Intestine, Liver, Gallbladder, Pancreas, Spleen, Kidney, , Uterus, Bone marrow, Joints, Muscle, Vessels, Lymph nodes), the patterns of physiological FAPI uptake and the main causes of non-oncological uptake reported from the literature with FAPI-02, FAPI-04 and FAPI-46. We also illustrate some examples from our institutional database at UCLA

Risk factors for severe illness in hospitalized Covid-19 patients at a regional hospital

BACKGROUND: The Covid-19 pandemic threatens to overwhelm scarce clinical resources. Risk factors for severe illness must be identified to make efficient resource allocations. OBJECTIVE: To evaluate risk factors for severe illness. DESIGN: Retrospective, observational case series. SETTING: Single-institution. PARTICIPANTS: First 117 consecutive patients hospitalized for Covid-19 from March 1 to April 12, 2020. EXPOSURE: None. MAIN OUTCOMES AND MEASURES: Intensive care unit admission or death. RESULTS: In-hospital mortality was 24.8% and average total length of stay was 11.82 days (95% CI: 10.01 to 13.63 days). 30.8% of patients required intensive care unit admission and 29.1% required mechanical ventilation. Multivariate regression identified the amount of supplemental oxygen required at admission (OR: 1.208, 95% CI: 1.011–1.443, p = .037), sputum production (OR: 6.734, 95% CI: 1.630–27.812, p = .008), insulin dependent diabetes mellitus (OR: 11.873, 95% CI: 2.218–63.555, p = .004) and chronic kidney disease (OR: 4.793, 95% CI: 1.528–15.037, p = .007) as significant risk factors for intensive care unit admission or death. Of the 48 patients who were admitted to the intensive care unit or died, this occurred within 3 days of arrival in 42%, within 6 days in 71%, and within 9 days in 88% of patients. CONCLUSIONS: At our regional medical center, patients with Covid-19 had an average length of stay just under 12 days, required ICU care in 31% of cases, and had a 25% mortality rate. Patients with increased sputum production and higher supplemental oxygen requirements at admission, and insulin dependent diabetes or chronic kidney disease may be at increased risk for severe illness. A model for predicting intensive care unit admission or death with excellent discrimination was created that may aid in treatment decisions and resource allocation. Early identification of patients at increased risk for severe illness may lead to improved outcomes in patients hospitalized with Covid-19

Simulation Capacity Building in Rural Indian Hospitals: a 1-year Follow-up Qualitative Analysis

Introduction: The benefits of simulation-based medical training are well described. The most effective way to plant and scale simulation training in rural locations remains undescribed. We sought to plant simulation training programmes for anaesthesia emergencies in two rural Indian hospitals. Methods: Two Indian consultant anaesthetists without experience in medical simulation underwent a 3-day course at the Boston Children’s Hospital’s (BCH) Simulator Program. They returned to their institutions and launched simulation programmes with an airway manikin and mock patient monitor. The 1-year experience was evaluated using individual, in-depth interviews of simulation facilitators. Three staff members (responsible for facilitating medical simulations over the prior year) at two rural hospitals in India were interviewed. None attended the BCH training; instead, they received on-the-job training from the BCH-trained, consultant anaesthetist colleagues. Results: Successes included organisational adoption of simulation training with exercises 1 year after the initial BCH-training, increased interdisciplinary teamwork and improved clinical competency in managing emergencies. Barriers to effective, local implementation of simulation programmes fell into three categories: time required to run simulations, fixed and rigid roles, and variable resources. Thematic improvement requests were for standardised resources to help train simulation facilitators and demonstrate to participants a well-run simulation, in addition to context-sensitive scenarios. Conclusion: An in-person training of simulation facilitators to promote medical simulation programmes in rural hospitals produced ongoing simulation programmes 1 year later. In order to make these programmes sustainable, however, increased investment in developing simulation facilitators is required. In particular, simulation facilitators must be prepared to formally train other simulation facilitators, too