Mapping the Process to Improve the Operative and Environmental Performance of Feeder Ports

Container terminals play an important role in linking regional and continental areas for the exchange of goods. Port authorities have to provide their services under competitive prices and service levels to customers. This increasing competition pushes feeder ports to improve their processes. The goal is to increase the port capacity to deal with the increasing demand for containers and, at the same time, to reduce the environmental impact and operative costs. The authors address the gap in the literature regarding alternatives for feeder ports. They analyse best practices adopted in international terminals and evaluate the implementation in feeder ports. They apply a quantitative approach using the simulation software AnyLogic. The model uses market data to analyse the vessel unloading process at the berth. Moreover, an alternative to reduce the CO2 emissions for diesel equipment is presented. A flowchart for the vessel unloading and loading operations is proposed that includes the strategies to increase capacity and efficiency of operations and the utilisation of equipment.

The Electrification of Conventional Industrial Processes: The Use of Mechanical Vapor Compression in an EtOH–Water Distillation Tower

The aim of this study is to analyze the exergetic, environmental, and economic impact of the electrification of a bio-refinery plant, considering the application of Mechanical Vapor Compression (MVC) to a conventional water–ethanol distillation column in the context of bioethanol production. The process was implemented in AspenPlus® and Aspen Exchange Design and Rating (EDR) simulation environments, where a sensitivity analysis was also carried out, considering four scenarios characterized by different compressions’ operative conditions, and including a Coefficient of Performance (CoP) analysis of the proposed solution with MVC. Exergetic and economic analyses were performed, and the relevant impacts on Operative Expenditure (OpEx) and Capital Expenditure (CapEx) were analyzed. Comparing the base case scenario with the proposed solution, a reduction of operative costs of around 63% was achieved. Finally, an environmental analysis was carried out, showing a remarkable reduction in the carbon footprint of the unit, with a carbon dioxide emission reduction of almost 80% for the MVC solution, in line with RED target requirements.

886 Healing Hands and Thrifty Plans! A Prospective, Cost-Effective Trial in Abscess Management

Aim Cutaneous abscesses are ubiquitous presentations requiring surgical drainage in most cases. There is a wide variation across the UK in the surgical practice dealing with such common problem. The aim of this study was to reduce the costs incurred in surgical drainage of acute skin and soft tissue abscess. Method This was a prospective, cost-effective study of the expenses incurred in surgical drainage of acute cutaneous and subcutaneous abscesses treated under the general surgeons' care over one year. Results A consequential saving of £13,962 was achieved during the study period. Between October 2019 and October 2020, 322 patients with soft tissue abscesses were treated by incision and drainage in general surgery. We calculated a total cost of £55.26 per patient for this routine operation. These expenses were based on basic surgical drapes pack, standard surgical gowns, sterile gloves and obtaining and processing the microbiology specimens. We have designed and implemented a new theatre protocol specifically for this procedure, resulting in a substantial reduction of the costs to £11.90 per patient. The total savings of £13,962 do not include savings caused by abscess drainage under local anaesthesia and does not calculate the savings that occurred due to shorter inpatient stay. These extra savings will be calculated and added later. Conclusions Considering the increasing financial burden on the NHS, we could make significant savings of nearly 80% of the operative costs of surgical drainage of a cutaneous abscess. We could achieve that by implementing simple modifications in the current surgical pathways without compromising patients' safety.

Detour-Impact Index Method and Traffic Gathering Algorithm for Assessing Alternative Paths of Disrupted Roads

Infrastructure plays a key role in society. Recent collapses of bridges have underlined their importance for road functionality, causing disruptions to commuters and emergency vehicles. Major issues arise on rural roads, where the lack of redundancy leads to the isolation of entire communities. Actual approaches to assess the resilience of countryside roads rely on the availability of specific datasets, limiting their practical application; this issue is typically related to traffic data. This research aims to propose innovative algorithms to assess the road network’s vulnerability in rural areas, including a novel traffic data collection process and its calibration. The aggregate metric is called Detour-Impact Index (DII) and compares user costs before and after a disruptive event. The method uses traditional network-impact metrics in combination with a new algorithm that allows us to gather quantitative traffic data starting from qualitative information. User travel time showed good agreement between the proposed procedure and traditional web-based methods. Furthermore, the paper provides user delay costs functions accounting for traffic composition, trip purposes, vehicle operative costs, nonlinear volume–capacity relation, and average daily traffic. A significant aspect is the adaptability of this framework, as it is designed to be coupled with existing approaches. The method is demonstrated on a case study in Tuscany (Italy).

Rapid standardized operating rooms (RAPSTOR) in thyroid and parathyroid surgery

Objective To evaluate the impact of a high efficiency rapid standardized OR (RAPSTOR) for hemithyroid/parathyroid surgery using standardized equipment sets (SES) and consecutive case scheduling (CCS) on turnover times (TOT), average case volumes, patient outcomes, hospital costs and OR efficiency/stress. Methods Patients requiring hemithyroidectomy (primary or completion) or unilateral parathyroidectomy in a single surgeon’s practice were scheduled consecutively with SES. Retrospective control groups were classified as sequential (CS) or non-sequential (CNS). A survey regarding OR efficiency/stress was administered. Phenomenography and descriptive statistics were conducted for time points, cost and patient outcome variables. Hospital cost minimization analysis was performed. Results The mean TOT of RAPSTOR procedures (16 min; n = 27) was not significantly different than CS (14 min, n = 14) or CNS (17 min, n = 6). Mean case number per hour was significantly increased in RAPSTOR (1.2) compared to both CS (0.9; p < 0.05) and CNS (0.7; p < 0.05). Average operative time was significantly reduced in RAPSTOR (32 min; n = 28) compared to CNS (48 min; p < 0.05) but not CS (33 min; p = 0.06). Time to discharge was reduced in RAPSTOR (595 min) compared to CNS (1210 min, p < 0.05). There was no difference in complication rate between all groups (p = 0.27). Survey responses suggested improved efficiency, teamwork and workflow. Furthermore, there is associated decrease in direct operative costs for RAPSTOR vs. CS. Conclusion A high efficiency standardized OR for hemithyroid and parathyroid surgery using SES and CCS is associated with improved efficiency and, in this study, led to increased capacity at reduced cost without compromising patient safety. Level of evidence Level 2. Graphical abstract

Implementation of a Fuzzy Logic Controller for the Irrigation of Rose Cultivation in Mexico

The design and implementation of a fuzzy logic controller (FLC) are presented, offering a solution to improve the irrigation of rose crops. The objective is to reduce the water consumption and operative costs, taking advantage of intelligent controllers and environmental characteristics in a specific region. Considering that the main controllable variables that affect the growth of plants are relative humidity (RH) and temperature (T), in this study, these variables are used to create a system whose aim is to provide an adequate amount of water for a rose crop in the State of Mexico. The Mamdani method was used for the FLC design and the membership functions, while the area centroid was considered as the defuzzification strategy. After implementing the FLC proposal using a field-programmable gate array (FPGA) in a domestic greenhouse, integrated by an array of [5 × 3] rose plants under natural restrictions, a reduction of 0.2 L per week with respect to the traditional manual irrigation system was found. The proposed design highlights the technological advantages of using a fuzzy logic-controlled irrigation system over traditional methods.

Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach

This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values.

Laparoscopy in Low-Income Countries: 10-Year Experience and Systematic Literature Review

Laparoscopy is a procedure that ultimately reduces hospital stay time and speeds up post-operative recovery. It is mainly performed in high-income countries but its implementation in many low- and middle-income countries (LMICs) is increasing. However, no aggregate data exist regarding the outcomes of this procedure in resource-limited settings. We retrospectively reviewed all cases of laparoscopy recorded from January 2007 to March 2017 at the Department of Surgery of Beira to assess the related outcomes. Moreover, we performed a systematic review of the laparoscopic practices and outcomes in low-income countries. Data from the Department of Surgery of Beira identified 363 laparoscopic procedures, mainly relating to gynecological diseases, cholelithiasis, and appendicectomy with only a 1.6% complication rate (6 cases) and a 1.9% conversion rate (7 cases) to open surgery. The systematic review showed a pooled risk of overall complications significantly lower in laparoscopic vs. open appendicectomy (OR = 0.43; 95% CI 0.19–0.97; I2 = 85.7%) and a significantly lower risk of infection (OR = 0.53; 95% CI 0.43–0.65; I2 = 0.00%). The pooled SMD in operation duration in laparoscopic vs. open appendectomy was 0.58 (95% CI −0.00; 1.15; I2 = 96.52), while the pooled SMD in hospitalization days was −1.35 (95% CI −1.87; −0.82; I2 = 96.41). Laparoscopy is an expensive procedure to adopt as it requires new equipment and specialized trained health workers. However, it could reduce post-operative costs and complications, especially in terms of infections. It is crucial to increase its accessibility, acceptability, and quality particularly in LMICs, especially during this COVID-19 era when the reduction of patient hospitalization is essential.

State of the art of robotic pancreatoduodenectomy

Current evidence shows that robotic pancreatoduodenectomy (RPD) is feasible with a safety profile equivalent to either open pancreatoduodenectomy (OPD) or laparoscopic pancreatoduodenectomy (LPD). However, major intraoperative bleeding can occur and emergency conversion to OPD may be required. RPD reduces the risk of emergency conversion when compared to LPD. The learning curve of RPD ranges from 20 to 40 procedures, but proficiency is reached only after 250 operations. Once proficiency is achieved, the results of RPD may be superior to those of OPD. As for now, RPD is at least equivalent to OPD and LPD with respect to incidence and severity of POPF, incidence and severity of post-operative complications, and post-operative mortality. A minimal annual number of 20 procedures per center is recommended. In pancreatic cancer (versus OPD), RPD is associated with similar rates of R0 resections, but higher number of examined lymph nodes, lower blood loss, and lower need of blood transfusions. Multivariable analysis shows that RPD could improve patient survival. Data from selected centers show that vein resection and reconstruction is feasible during RPD, but at the price of high conversion rates and frequent use of small tangential resections. The true Achilles heel of RPD is higher operative costs that limit wider implementation of the procedure and accumulation of a large experience at most single centers. In conclusion, when proficiency is achieved, RPD may be superior to OPD with respect to CR-POPF and oncologic outcomes. Achievement of proficiency requires commitment, dedication, and truly high volumes.

Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs

This paper proposes a new hybrid master–slave optimization approach to address the problem of the optimal placement and sizing of distribution static compensators (D-STATCOMs) in electrical distribution grids. The optimal location of the D-STATCOMs is identified by implementing the classical and well-known Chu and Beasley genetic algorithm, which employs an integer codification to select the nodes where these will be installed. To determine the optimal sizes of the D-STATCOMs, a second-order cone programming reformulation of the optimal power flow problem is employed with the aim of minimizing the total costs of the daily energy losses. The objective function considered in this study is the minimization of the annual operative costs associated with energy losses and installation investments in D-STATCOMs. This objective function is subject to classical power balance constraints and device capabilities, which generates a mixed-integer nonlinear programming model that is solved with the proposed genetic-convex strategy. Numerical validations in the 33-node test feeder with radial configuration show the proposed genetic-convex model’s effectiveness to minimize the annual operative costs of the grid when compared with the optimization solvers available in GAMS software.