12 research outputs found
Automated Fruit Quality Testing using an Electrical Impedance Tomography-Enabled Soft Robotic Gripper
Soft robotic grippers are becoming increasingly popular for agricultural and logistics automation. Their passive conformability enables them to adapt to varying product shapes and sizes, providing stable large-area grasps. This work presents a novel methodology for combining soft robotic grippers with electrical impedance tomography-based sensors to infer intrinsic properties of grasped fruits. We use a Fin Ray soft robotic finger with embedded microspines to grab and obtain rich multi-direction electrical properties of the object. Learning-based techniques are then used to infer the desired fruit properties. The framework is extensively tested and validated on multiple fruit groups. Our results show that ripeness parameters and even weight of the grasped fruit can be estimated with reasonable accuracy autonomously using the proposed system
Effectiveness and safety of first-generation protease inhibitors in clinical practice: Hepatitis C virus patients with advanced fibrosis
AIM: To evaluates the effectiveness and safety of the first generation, NS3/4A protease inhibitors (PIs) in clinical practice against chronic C virus, especially in patients with advanced fibrosis.
METHODS: Prospective study and non-experimental analysis of a multicentre cohort of 38 Spanish hospitals that includes patients with chronic hepatitis C genotype 1, treatment-nai¨ve (TN) or treatment-experienced (TE),
who underwent triple therapy with the first generation NS3/4A protease inhibitors, boceprevir (BOC) and telaprevir (TVR), in combination with pegylated interferon and ribavirin. The patients were treatment in routine practice settings. Data on the study population and on adverse clinical and virologic effects were compiled during the treatment period and during follow up.
RESULTS: One thousand and fifty seven patients were included, 405 (38%) were treated with BOC and 652 (62%) with TVR. Of this total, 30% (n = 319) were TN and the remaining were TE: 28% (n = 298) relapsers, 12% (n = 123) partial responders (PR), 25% (n = 260) null-responders (NR) and for 5% (n = 57) with prior response unknown. The rate of sustained virologic response (SVR) by intention-to-treatment (ITT) was greater in those treated with TVR (65%) than in those treated with BOC (52%) (P < 0.0001), whereas by modified intention-to-treatment (mITT) no were found significant differences. By degree of fibrosis, 56% of patients were F4 and the highest SVR rates were recorded in the non-F4 patients, both TN and TE. In the analysis by groups, the TN patients treated with TVR by ITT showed a higher SVR (P = 0.005). However, by mITT there were no significant differences between BOC and TVR. In the multivariate analysis by mITT, the significant SVR factors were relapsers, IL28B CC and non-F4; the type of treatment (BOC or TVR) was not significant. The lowest SVR values were presented by the F4-NR patients, treated with BOC (46%) or with TVR (45%). 28% of the patients interrupted the treatment, mainly by non-viral response (51%): this outcome was more frequent in the TE than in the TN patients (57% vs 40%, P = 0.01). With respect to severe haematological disorders, neutropaenia was more likely to affect the patients treated with BOC (33% vs 20%, P = 0.0001), and thrombocytopaenia and anaemia, the F4 patients (P = 0.000, P = 0.025, respectively).
CONCLUSION: In a real clinical practice setting with a high proportion of patients with advanced fibrosis, effectiveness of first-generation PIs was high except for NR patients, with similar SVR rates being achieved by BOC and TVR
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Static Shape Control of Soft Continuum Robots Using Deep Visual Inverse Kinematic Models
Soft continuum robots are highly flexible and adapt-
able, making them ideal for unstructured environments such as the human body and agriculture. However, their high compliance and manoeuvrability make them difficult to model, sense, and control. Current control strategies focus on Cartesian space control of the end-effector, but few works have explored full-body control. This study presents a novel image-based deep learning approach for closed-loop kinematic shape control of soft continuum robots. The method combines a local inverse kinematics formulation in the image-space with deep convolutional neural networks for accurate shape control that is robust to feedback noise and mechanical changes in the continuum arm. The shape controller is fast and straightforward to implement; it takes only
a few hours to generate training data, train the network, and deploy, requiring only a web camera for feedback. This method offers an intuitive and user-friendly way to control the robot’s 3D shape and configuration through teleoperation using only 2D hand-drawn images of the desired target state without the need for further user instruction or consideration of the robot’s kinematics.This work was supported by the SHERO project, a Fu-
ture and Emerging Technologies (FET) programme of the
European Commission (grant agreement ID 828818), Agri-
FoRwArdS Centre for Doctoral Training programme under
the UKRI grant [EP/S023917/1], the Jersey Farmers Union,
the Springboard Award of the Academy of Medical Sciences
(grant number: SBF003-1109), the Engineering and Physical
Sciences Research Council (grant numbers: EP/R037795/1,
EP/S014039/1 and EP/V01062X/1), the Royal Academy of
Engineering (grant number: IAPP18-19\264), the UCL Dean’s
Prize, UCL Mechanical Engineering, and the China Scholar-
ship Council (CSC). For the purpose of open access, the author
has applied a Creative Commons Attribution (CC BY) licence
to any Author Accepted Manuscript version arising
Determinants of Severity in Acute Pancreatitis : A Nation-wide Multicenter Prospective Cohort Study
OBJECTIVE: The aim of this study was to compare and validate the different classifications of severity in acute pancreatitis (AP) and to investigate which characteristics of the disease are associated with worse outcomes. SUMMARY OF BACKGROUND DATA: AP is a heterogeneous disease, ranging from uneventful cases to patients with considerable morbidity and high mortality rates. Severity classifications based on legitimate determinants of severity are important to correctly describe the course of disease. METHODS: A prospective multicenter cohort study involving patients with AP from 23 hospitals in Spain. The Atlanta Classification (AC), Revised Atlanta Classification (RAC), and Determinant-based Classification (DBC) were compared. Binary logistic multivariate analysis was performed to investigate independent determinants of severity. RESULTS: A total of 1655 patients were included; 70 patients (4.2%) died. RAC and DBC were equally superior to AC for describing the clinical course of AP. Although any kind of organ failure was associated with increased morbidity and mortality, persistent organ failure (POF) was the most significant determinant of severity. All local complications were associated with worse outcomes. Infected pancreatic necrosis correlated with high morbidity, but in the presence of POF, it was not associated to higher mortality when compared with sterile necrotizing pancreatitis. Exacerbation of previous comorbidity was associated with increased morbidity and mortality. CONCLUSION: The RAC and DBC both signify an advance in the description and differentiation of AP patients. Herein, we describe the complications of the disease independently associated to morbidity and mortality. Our findings are valuable not only when designing future studies on AP but also for the improvement of current classifications