Worst Case Scenarios! Complications Related to Hernial Disease

Incarceration, obstruction and strangulation are well recognized common complications of hernias. Several risk factors determine patients’ morbidity and mortality. Hernia surgery complications encompass infections, fascial dehiscence, recurrence, neuralgia, visceral injury, and mesh erosion or migration predetermined by many risk factors. The types and criteria for surgical site infections are defined by the extent of the infection. Whether the open or laparoscopic approaches are attempted, the rates of the respective complications depend on the approach. Post-operative hernias are appreciated because of their prevalence and complications. The criteria for enhanced recovery after surgery depend on whether patient is in the pre-operative, intra-operative or post-operative phase. Within the pediatric population, the risk of developing umbilical and inguinal is variable

Quarantining arriving travelers in the era of COVID-19: balancing the risk and benefits a learning experience from Bahrain

The quarantine period imposed to travelers in many countries due to COVID19 is a major obstacle for any traveler. Lifting the quarantine period could lead to significant improvement in people’s quality of life and any country’s economy. Bahrain have used two quarantine models from arriving passengers. We report data about the incidence of COVID19 on arriving passengers at Bahrain International airport. Infection rates were reported on arrival, during quarantine and after leaving quarantine. Results showed that travelers had low incidence of COVID19 on arriving and during the quarantine period, while becoming at higher risk after leaving quarantine. We concluded that quarantine requirement maybe lifted for arriving travelers. Testing upon arrival with implementation of the public health preventative measures can minimize the risk of transmission

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Leak Detection in Fluid Distribution Networks

Leakage is an undesired abnormality that causes economical losses and impacts the environment. Leak detection tests in pipe networks are usually interpreted using water-hammer equations (WHE). These equations are nonlinear hyperbolic partial differential equations (PDEs) used to describe transient flows in pipes. The associated uncertainties in initial and boundary conditions, parameters, and leak strength and location increases the stochastic behavior of these equations. The method of distributions is used to derive a deterministic PDE for probability density function (PDF) of pressure head and flow velocity under uncertain initial conditions. The derivation requires a closure approximation that ensures its consistency with the mean and the variance of the state variables. A series of numerical experiments confirms the computational gain of this method over Monte Carlo simulations.The PDF of pressure head obtained using the method of distributions serves as a prior PDF for data assimilation. Bayesian framework is used to update this distribution with a statistical model for observations obtained from the data collected by a pressure sensor. The result is posterior PDFs for leak location and leak strength. Series of numerical experiments are conducted for a single pipe and pipe networks under uncertain initial velocity and measurement noise to identify leak location and leak strength. The results are compared with the best fitness function that is used in inverse transient analysis

Leak Detection in Fluid Distribution Networks

Leakage is an undesired abnormality that causes economical losses and impacts the environment. Leak detection tests in pipe networks are usually interpreted using water-hammer equations (WHE). These equations are nonlinear hyperbolic partial differential equations (PDEs) used to describe transient flows in pipes. The associated uncertainties in initial and boundary conditions, parameters, and leak strength and location increases the stochastic behavior of these equations. The method of distributions is used to derive a deterministic PDE for probability density function (PDF) of pressure head and flow velocity under uncertain initial conditions. The derivation requires a closure approximation that ensures its consistency with the mean and the variance of the state variables. A series of numerical experiments confirms the computational gain of this method over Monte Carlo simulations.The PDF of pressure head obtained using the method of distributions serves as a prior PDF for data assimilation. Bayesian framework is used to update this distribution with a statistical model for observations obtained from the data collected by a pressure sensor. The result is posterior PDFs for leak location and leak strength. Series of numerical experiments are conducted for a single pipe and pipe networks under uncertain initial velocity and measurement noise to identify leak location and leak strength. The results are compared with the best fitness function that is used in inverse transient analysis

Dynamic radius for context- aware recommender system

In the field of transportation and smart cities, context-aware recommendation is a trending subject that targets users’ satisfaction and comfort. The subject has developed from e-commerce to cover different domains including path planning at urban areas. Researchers were competed in delivering the level of contribution in many areas. Search radius is considered a major pillar at any context-aware recommender framework, however, in many studies the search radius is not having a major contribution in the delivered systems. In this paper, a dynamic search radius algorithm is introduced as part of a context-aware recommender framework. Agglomerations and competition effects are used to enhance search radius results. Deep neural network is a major artificial intelligence method used in this research to tackle cold-start problem and to improve recommendation outcomes

High-level transportation framework for outdoor context-aware recommender

In smart transportation era, user journey is considered one of major aspect where researchers introduced different frameworks and systems to deliver level of optimization that satisfy drivers at outdoor environment. Context-aware recommendation is one of the techniques used to accomplish such an optimization for a trip by utilizing driver’s and location’s information. Many scenarios were covered in the previous studies, in particular, gas station scenario. In this paper, we highlight recent academia that focus on context-aware recommendation systems for the purpose of introducing an optimized high-level and conceptual context-aware recommender based on real-time feed specification, user feedback, dynamic profile insertion, dynamic radius search and deep neural network modules

Business Owners’ Feedback toward Adoption of Open Data: A Case Study in Kuwait

The world intention toward open data technology has increased in the past years, and governments started to explore open data technology in the public and private sectors and tried to check its advantages and disadvantages. However, in the Arab world and especially in Kuwait, there is no solid structured attention about the technology in both sectors. As a result, we tried in this paper to determine if business owners in Kuwait have enough knowledge of the open data (OD) concept and if they have the willingness to use it for enhancing their services. The purpose of this research is to measure the acceptance of OD technology in Kuwait and to gather business owners' opinions about the ability to adopt the OD concept. Making online and hardcopy survey was our method for gathering different reactions and points of view about this technology. We intended to focus on the private sector and we targeted people who own a business and wish to introduce better services for their customers. Overall, the results have shown clear features about open data technology in Kuwait and the substantial need of education and awareness of the importance of this technology. The results of this study may positively and directly affect the level of motivation for other existing studies

Optimal path planning for urban vehicles using Internet of Things: a new navigation perspective

One of the important applications in intelligent transportationsystem is path planning for vehicles at urban areas. A driver can reach a destination in a short time with a pleasant ride using less fuel and reach his or her destination safely. However, the destination status may change, and no more becomes a desired destination. In this paper we highlighted, discussed and analyzed related works for vehicle’s path planning using Internet of Things (IoT). A new perspective for the destination was also proposed which defines how important considering the updated information of the destination in real-time using IoT that brings driver’s attention when planning for a trip. A mathematical model for an optimal path planning was introduced which composes of two cost functions; path planning function and destination function. A gas station scenario was introduced as an example to demonstrate the proposed model. Futuristic look at integration design for the proposedsystem was also highlighted