Early prediction of bumblebee flight task using machine learning

This work demonstrates the development of a neural network algorithm able to determine the function of a bee's flight within six measurements (≈18 s with current radar technology) of its relative position on leaving a nest. Engineering advancements have created technology to track individual insects, unlocking research possibilities to investigate how bumblebees react to their environment in more detail. This includes how they discover and make use of resources. The development of an intelligent algorithm would allow for the automated monitoring of resource use and nest health. An imbalance of bee flight tasks may indicate a shortage of resources or over-reliance on a plant that may soon stop flowering. Recent developments using drones to track insects can benefit from an intelligent target acquisition system given limited drone battery life. Such knowledge will also benefit the tracking itself by allowing for customised flight parameters to match target flight patterns. Data captured by these tracking techniques are taxing to parse manually using human expertise. Artificial intelligence can produce meaningful knowledge faster with equal precision. In this work, a comparison between a neural network (NN), random forest (RF), and support vector machine (SVM) is provided to distinguish the best model for the task by comparing cross entropy loss and accuracy across the dataset, showing improved results as time goes on. In situations where the radar lost sight of the target, a purpose-built filter was created to mitigate signal losses. The generated model provides results with a peak accuracy of 92%. This model, combined with the filter, create an opportunity to monitor the number of bees leaving the nest for each flight task with smaller, cheaper, and stationary receiver solutions with shorter ranges by removing the need to track a bee for its entire flight to ascertain its errand

Maintaining a minimally invasive surgical service during a pandemic

PURPOSE: The safety of minimally invasive surgery (MIS) was questioned in the COVID-19 pandemic due to concern regarding disease spread. We continued MIS during the pandemic with appropriate protective measures. This study aims to assess the safety of MIS compared to Open Surgery (OS) in this setting. METHODS: Operations performed during 2020 lockdown were compared with operations from the same time-period in 2019 and 2021. Outcomes reviewed included all complications, respiratory complications, length of stay (LOS) and operating surgeon COVID-19 infections (OSI). RESULTS: In 2020, MIS comprised 52% of procedures. 29% of MIS 2020 had complications (2019: 24%, 2021: 15%; p = 0.08) vs 47% in OS 2020 (p = 0.04 vs MIS). 8.5% of MIS 2020 had respiratory complications (2019: 7.7%, 2021: 6.9%; p = 0.9) vs 10.5% in OS 2020 (p = 0.8 vs MIS). Median LOS[IQR] for MIS 2020 was 2.5[6] days vs 5[23] days in OS 2020 (p = 0.06). In 2020, 2 patients (1.2%) were COVID-19 positive (MIS: 1, OS: 1) and there were no OSI. CONCLUSION: Despite extensive use of MIS during the pandemic, there was no associated increase in respiratory or other complications, and no OSI. Our study suggests that, with appropriate protective measures, MIS can be performed safely despite high levels of COVID-19 in the population

Minimal access surgery for congenital diaphragmatic hernia: surgical tricks to facilitate anchoring the patches to the ribs

Objective: Minimal Access Surgery (MAS) for Congenital Diaphragmatic Hernia (CDH) repair is well described, yet only a minority of surgeons report this as their preferred operative approach. Some surgeons find it particularly difficult to repair the defect using MAS and convert to laparotomy when a patch is required. We present in this study our institutional experience in using an easy and relatively cheap methodology to anchor the patch around the ribs using Endo Close™. This device has an application in MAS for tissue approximation using percutaneous suturing. Methods and technique: We retrospectively reviewed our database for patients undergoing MAS repair of CDH between 2009 and 2021. Outcome measures included length of surgery and recurrence rates after patch repair. Endo Close™ was used in all patients who required patch repair. We declare no conflict of interest and to not having received any funding from Medtronic (UK). The technique is as follows: (1) The edges of the diaphragm are delineated by dissection. When primary suture repair of the diaphragmatic hernia was unfeasible without tension, a patch was used. (2) The patch is anchored in place by two corner stitches at the medial and lateral borders. (3) The posterior border of the patch is fixed to the diaphragmatic edge by running or interrupted stitches. (4) For securing the anterior border, a non-absorbable suture is passed through the anterior chest wall and the patch border is taken with intracorporeal instruments. (5) Without making another stab incision, the Endo Close™ is tunnelled subcutaneously through the anterior chest wall. (6) The suture end is pulled through the Endo Close™ and the knot is tied around the rib. This procedure can be performed as many times as required to secure the patch. Results: 58 patients underwent MAS surgery for repair of CDH between 2009 and 2021. 48 (82%) presented with a left defect. 34 (58%) had a patch repair. The length of patch repair surgery for CDH ranged from 100–343 min (median 197). There was only one patient (3%) in the patch repair cohort that had a recurrent hernia, diagnosed 12 months after the initial surgery. Conclusions: In our experience, MAS repair of CDH is feasible. We adopted a low threshold in using a patch to achieve a tension-free repair. We believe that the Endo Close™ is a cheap and safe method to help securing the patch around the ribs