Quantitative and qualitative workload assessment in steep terrain forest operations: fostering a safer work environment through yarder automation.

Many forestry roles have changed from being manual tasks with a high physical workload to being a machine operator task with a high mental workload. Automation can support a decrease in mental fatigue by removing tasks that are repetitive and monotonous for the operators. Cable yarding presents an ideal opportunity for early adoption of automation technology; specifically the carriage movement along a defined corridor. A Valentini V-850 cable yarder was used in an Italian harvesting setting, in order to gauge the ergonomic benefit of carriage control automation. The study showed that automating yarder carriage movements improved the ergonomic situation of the workers directly involved in the related primary tasks. However, the caveat is that improving one work task may negatively affect the other work tasks, and therefore introducing automation to a worksite must be done after considering all impacts on the whole system. Practitioner summary: Automation decreased the winch operator's mental workload while improving overall productivity. At the same time, the mental and physiological workload of the operator tasked with bucking were slightly increased. Ideally, winch automation should be coupled with bucking mechanisation to balance the intervention and boost both operator well-being and productivity.

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Expanding our global testing capacity is critical to preventing and containing pandemics1-9. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are required10-14. Pooled testing can be extremely efficient if the pooling strategy is based on local viral prevalence15-20; however, it requires automation, small sample volume handling and feedback not available in current bulky, capital-intensive liquid handling technologies21-29. Here we use a swarm of millimetre-sized magnets as mobile robotic agents ('ferrobots') for precise and robust handling of magnetized sample droplets and high-fidelity delivery of flexible workflows based on nucleic acid amplification tests to overcome these limitations. Within a palm-sized printed circuit board-based programmable platform, we demonstrated the myriad of laboratory-equivalent operations involved in pooled testing. These operations were guided by an introduced square matrix pooled testing algorithm to identify the samples from infected patients, while maximizing the testing efficiency. We applied this automated technology for the loop-mediated isothermal amplification and detection of the SARS-CoV-2 virus in clinical samples, in which the test results completely matched those obtained off-chip. This technology is easily manufacturable and distributable, and its adoption for viral testing could lead to a 10-300-fold reduction in reagent costs (depending on the viral prevalence) and three orders of magnitude reduction in instrumentation cost. Therefore, it is a promising solution to expand our testing capacity for pandemic preparedness and to reimagine the automated clinical laboratory of the future.

Pandemic effects to autonomous vehicles test operations in California.

Companies developing automated driving system (ADS) technologies have spent heavily in recent years to conduct live testing of autonomous vehicles operating in real world environments to ensure their reliable and safe operations. However, the unexpected onset and ongoing resurgent effects of the Covid-19 pandemic starting in March 2020 has serve to halt, change, or delay the achievement of these new product development test objectives. This study draws on data obtained from the California automated vehicle test program to determine the extent that testing trends, test resumptions, and test environments have been affected by the pandemic. The importance of government policies to support and enable autonomous vehicles development during pandemic conditions is highlighted.

Comparison of four commercial, automated antigen tests to detect SARS-CoV-2 variants of concern.

A versatile portfolio of diagnostic tests is essential for the containment of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Besides nucleic acid-based test systems and point-of-care (POCT) antigen (Ag) tests, quantitative, laboratory-based nucleocapsid Ag tests for SARS-CoV-2 have recently been launched. Here, we evaluated four commercial Ag tests on automated platforms and one POCT to detect SARS-CoV-2. We evaluated PCR-positive (n = 107) and PCR-negative (n = 303) respiratory swabs from asymptomatic and symptomatic patients at the end of the second pandemic wave in Germany (February-March 2021) as well as clinical isolates EU1 (B.1.117), variant of concern (VOC) Alpha (B.1.1.7) or Beta (B.1.351), which had been expanded in a biosafety level 3 laboratory. The specificities of automated SARS-CoV-2 Ag tests ranged between 97.0 and 99.7% (Lumipulse G SARS-CoV-2 Ag (Fujirebio): 97.03%, Elecsys SARS-CoV-2 Ag (Roche Diagnostics): 97.69%; LIAISON® SARS-CoV-2 Ag (Diasorin) and SARS-CoV-2 Ag ELISA (Euroimmun): 99.67%). In this study cohort of hospitalized patients, the clinical sensitivities of tests were low, ranging from 17.76 to 52.34%, and analytical sensitivities ranged from 420,000 to 25,000,000 Geq/ml. In comparison, the detection limit of the Roche Rapid Ag Test (RAT) was 9,300,000 Geq/ml, detecting 23.58% of respiratory samples. Receiver-operating-characteristics (ROCs) and Youden's index analyses were performed to further characterize the assays' overall performance and determine optimal assay cutoffs for sensitivity and specificity. VOCs carrying up to four amino acid mutations in nucleocapsid were detected by all five assays with characteristics comparable to non-VOCs. In summary, automated, quantitative SARS-CoV-2 Ag tests show variable performance and are not necessarily superior to a standard POCT. The efficacy of any alternative testing strategies to complement nucleic acid-based assays must be carefully evaluated by independent laboratories prior to widespread implementation.

Systematic review automation tools improve efficiency but lack of knowledge impedes their adoption: a survey.

OBJECTIVE: We investigated systematic review automation tool use by systematic reviewers, health technology assessors and clinical guideline developerst. STUDY DESIGN AND SETTING: An online, 16-question survey was distributed across several evidence synthesis, health technology assessment and guideline development organizations. We asked the respondents what tools they use and abandon, how often and when do they use the tools, their perceived time savings and accuracy, and desired new tools. Descriptive statistics were used to report the results. RESULTS: A total of 253 respondents completed the survey; 89% have used systematic review automation tools - most frequently whilst screening (79%). Respondents' "top 3" tools included: Covidence (45%), RevMan (35%), Rayyan and GRADEPro (both 22%); most commonly abandoned were Rayyan (19%), Covidence (15%), DistillerSR (14%) and RevMan (13%). Tools saved time (80%) and increased accuracy (54%). Respondents taught themselves to how to use the tools (72%); lack of knowledge was the most frequent barrier to tool adoption (51%). New tool development was suggested for the searching and data extraction stages. CONCLUSION: Automation tools will likely have an increasingly important role in high-quality and timely reviews. Further work is required in training and dissemination of automation tools and ensuring they meet the desirable features of those conducting systematic reviews.

Regional development potentials of Industry 4.0: Open data indicators of the Industry 4.0+ model.

This paper aims to identify the regional potential of Industry 4.0 (I4.0). Although the regional background of a company significantly determines how the concept of I4.0 can be introduced, the regional aspects of digital transformation are often neglected with regard to the analysis of I4.0 readiness. Based on the analysis of the I4.0 readiness models, the external regional success factors of the implementation of I4.0 solutions are determined. An I4.0+ (regional Industry 4.0) readiness model, a specific indicator system is developed to foster medium-term regional I4.0 readiness analysis and foresight planning. The indicator system is based on three types of data sources: (1) open governmental data; (2) alternative metrics like the number of I4.0-related publications and patent applications; and (3) the number of news stories related to economic and industrial development. The indicators are aggregated to the statistical regions (NUTS 2), and their relationships analyzed using the Sum of Ranking Differences (SRD) and Promethee II methods. The developed I4.0+ readiness index correlates with regional economic, innovation and competitiveness indexes, which indicates the importance of boosting regional I4.0 readiness.

Protocol for quantitative assessment of social cooperation in mice.

Social cooperation in rodents was recently validated in rats, and we recently successfully applied a modified automated analysis to mice. Here, we describe a detailed procedure for using this paradigm in mice that relies on reward-based mutual communication that is automatically detected by a software algorithm embedded in the custom-made equipment. We also describe exemplary results of analyses in mice as a guide to broader neuroscience research applications employing transgenic knockout mice modeling neuropsychiatric disorders and mice of various ages. For complete details on the use and execution of this protocol, please refer to Han et al. (2020).

Advancing automation in Compound Management: a novel industrial process underpinning drug discovery.

Faced with ageing infrastructure and ever-increasing demands from hit discovery and lead optimisation functions, AstraZeneca has chosen to develop innovative technologies and process solutions to support the future of drug discovery. These include the miniaturisation of compound storage tubes for high-density storage and rapid access to the corporate collection for feeding samples to the predicted tripling number of high throughput screening (HTS) campaigns. The acoustically- compatible tubes also enable the first fully-acoustic plate production process for faster sample supply to screening with less waste and continued high quality. Operating at a smaller scale reduces compound synthesis, storage, and consumption, prompting miniaturisation of upstream chemistry and downstream biological assays, while offering a transformative and sustainable solution to many drug discovery issues applicable across the industry.

Historical Trend of Work-Related Musculoskeletal Disorders in the Meatpacking and Auto Industries, 1980s-Present.

Occupational Applications This paper provides a historical overview of the rise of Work-Related Musculoskeletal Disorders (WMSDs) in the U.S. from the 1980s to the present, with a special focus on the two industries with the highest recorded rates: Meatpacking and Auto Assembly. The activities underlying this account amount to a major occupational health success story (although still incomplete) in the recognition of these disorders and the development of a nation-wide effort for prevention. An obstacle in creating the data presented here was that the system of recordkeeping changed in multiple ways, making it difficult to compare WMSD rates over time. The work summarized here evaluated the effect of these changes and combined temporal segments that were judged to be the most accurate to create an overall trend line. These results can aid in: 1) showing the overall history of the recognition and prevention of WMSDs, 2) understanding the effects of the recordkeeping changes, and 3) allowing international comparisons of the trends.

Promoting fertility awareness and preconception health using a chatbot: a randomized controlled trial.

RESEARCH QUESTION: What are the effects of using a fertility education chatbot, i.e. automatic conversation programme, on knowledge, intentions to improve preconception behaviour and anxiety? DESIGN: A three-armed, randomized controlled trial was conducted using an online social research panel. Participants included 927 women aged 20-34 years who were randomly allocated to one of three groups: a fertility education chatbot (intervention group), a document about fertility and preconception health (control group 1) or a document about an irrelevant topic (control group 2). Participants' scores on the Cardiff Fertility Knowledge Scale and the State-Trait Anxiety Inventory, their intentions to optimize preconception behaviours, e.g. taking folic acid, and the free-text feedback provided by chatbot users were assessed. RESULTS: A repeated-measures analysis of variance showed significant fertility knowledge gains after the intervention in the intervention group (+9.1 points) and control group 1 (+14.9 points) but no significant change in control group 2 (+1.1 points). Post-test increases in the intentions to optimize behaviours were significantly higher in the intervention group than in control group 2, and were similar to those in control group 1. Post-test state anxiety scores were significantly lower in the intervention group than in control group 1 and control group 2. User feedbacks about the chatbot suggested technical limitations, e.g. low comprehension of users' words, and pros and cons of using the chatbot, e.g. convenient versus coldness. CONCLUSIONS: Providing fertility education using a chatbot improved fertility knowledge and intentions to optimize preconception behaviour without increasing anxiety, but the improvement in knowledge was small. Further technical development and exploration of personal affinity for technology is required.

Fully Automated Cardiac Assessment for Diagnostic and Prognostic Stratification Following Myocardial Infarction.

Background Cardiovascular magnetic resonance imaging is considered the reference methodology for cardiac morphology and function but requires manual postprocessing. Whether novel artificial intelligence-based automated analyses deliver similar information for risk stratification is unknown. Therefore, this study aimed to investigate feasibility and prognostic implications of artificial intelligence-based, commercially available software analyses. Methods and Results Cardiovascular magnetic resonance data (n=1017 patients) from 2 myocardial infarction multicenter trials were included. Analyses of biventricular parameters including ejection fraction (EF) were manually and automatically assessed using conventional and artificial intelligence-based software. Obtained parameters entered regression analyses for prediction of major adverse cardiac events, defined as death, reinfarction, or congestive heart failure, within 1 year after the acute event. Both manual and uncorrected automated volumetric assessments showed similar impact on outcome in univariate analyses (left ventricular EF, manual: hazard ratio [HR], 0.93 [95% CI 0.91-0.95]; P<0.001; automated: HR, 0.94 [95% CI, 0.92-0.96]; P<0.001) and multivariable analyses (left ventricular EF, manual: HR, 0.95 [95% CI, 0.92-0.98]; P=0.001; automated: HR, 0.95 [95% CI, 0.92-0.98]; P=0.001). Manual correction of the automated contours did not lead to improved risk prediction (left ventricular EF, area under the curve: 0.67 automated versus 0.68 automated corrected; P=0.49). There was acceptable agreement (left ventricular EF: bias, 2.6%; 95% limits of agreement, -9.1% to 14.2%; intraclass correlation coefficient, 0.88 [95% CI, 0.77-0.93]) of manual and automated volumetric assessments. Conclusions User-independent volumetric analyses performed by fully automated software are feasible, and results are equally predictive of major adverse cardiac events compared with conventional analyses in patients following myocardial infarction. Registration URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00712101 and NCT01612312.

Cost-Utility Analysis of Continuous Ambulatory Peritoneal Dialysis and Automated Peritoneal Dialysis for Thai Patients With End-Stage Renal Disease.

BACKGROUND: Continuous ambulatory peritoneal dialysis (CAPD) is the first option for patients with end-stage renal disease under the benefit package of Thailand. Nevertheless, automated peritoneal dialysis (APD) may benefit these patients in terms of both medical and quality-of-life aspects, but it is more expensive. The economic evidence for the comparison between CAPD and APD is not inconclusive. Thus, this study aims to evaluate the cost-effectiveness of CAPD compared with APD in PD patients. OBJECTIVES: To assess the health-related quality of life and costs between patients treated with CAPD and APD. METHODS: A Markov model was developed to evaluate the cost-effectiveness of CAPD and APD from the societal perspective. Costs and outcomes were calculated over a lifetime horizon and discounted at an annual rate of 3%. The outcomes were presented as quality-adjusted life-years (QALYs) of CAPD and APD. Utility scores were calculated from the utility values of the 5-level EuroQol questionnaire. A probabilistic sensitivity analysis using 5000 Monte Carlo simulations was performed to evaluate the stability of the results. RESULTS: The costs of APD and CAPD were 12 868 080 and 11 144 786 Thai baht, respectively, whereas the QALYs were 24.28 and 24.72 QALYs, respectively. APD was more costly but less effective than CAPD. The most sensitive parameter was direct medical cost of outpatient visits. When the willingness-to-pay threshold was 160 000 Thai baht per QALY, the probability of APD providing a cost-effective alternative to CAPD was 19%. CONCLUSION: APD was not a cost-effective strategy as compared with CAPD at the current Thai threshold. These findings should encourage clinicians and policy makers to encompass the use of CAPD as a good value for money for PD treatment.

Optimization of XCMS parameters for LC-MS metabolomics: an assessment of automated versus manual tuning and its effect on the final results.

INTRODUCTION: Several software packages containing diverse algorithms are available for processing Liquid Chromatography-Mass Spectrometry (LC-MS) chromatographic data and within these deconvolution packages different parameters settings can lead to different outcomes. XCMS is the most widely used peak picking and deconvolution software for metabolomics, but the parameter selection can be hard for inexpert users. To solve this issue, the automatic optimization tools such as Isotopologue Parameters Optimization (IPO) can be extremely helpful. OBJECTIVES: To evaluate the suitability of IPO as a tool for XCMS parameters optimization and compare the results with those manually obtained by an exhaustive examination of the LC-MS characteristics and performance. METHODS: Raw HPLC-TOF-MS data from two types of biological samples (liver and plasma) analysed in both positive and negative electrospray ionization modes from three groups of piglets were processed with XCMS using parameters optimized following two different approaches: IPO and Manual. The outcomes were compared to determine the advantages and disadvantages of using each method. RESULTS: IPO processing produced the higher number of repeatable (%RSD < 20) and significant features for all data sets and allowed the different piglet groups to be distinguished. Nevertheless, on multivariate level, similar clustering results were obtained by Principal Component Analysis (PCA) when applied to IPO and manual matrices. CONCLUSION: IPO is a useful optimization tool that helps in choosing the appropriate parameters. It works well on data with a good LC-MS performance but the lack of such adequate data can result in unrealistic parameter settings, which might require further investigation and manual tuning. On the contrary, manual selection criteria requires deeper knowledge on LC-MS, programming language and XCMS parameter interpretation, but allows a better fine-tuning of the parameters, and thus more robust deconvolution.

Towards Automated Manufacturing for Cell Therapies.

PURPOSE OF REVIEW: Many cell therapy products are beginning to reach the commercial finish line and a rapidly escalating pipeline of products are in clinical development. The need to develop manufacturing capability that will support a successful commercial business model has become a top priority as many cell therapy developers look to secure long-term visions to enable both funding and treatment success. RECENT FINDINGS: Manufacturing automation is both highly compelling and very challenging at the same time as a key tactic to address quality, cost of goods, scale, and sustainability that are fundamental drivers for commercially viable manufacturing. This paper presents an overview and strategic drivers for application of automation to cell therapy manufacturing. It also explores unique automation considerations for patient-specific cell therapy (PSCT) where each full-scale lot is for one patient vs off-the-shelf cell therapy (OTSCT) where a full-scale lot will treat many patients, and finally some practical considerations for implementing automation.

Assessing the efficacy and cost of detergents used in a primary care automated washer disinfector.

Background: Cleaning of re-usable medical devices is a critical control point in the decontamination cycle, although defined end-points of the process are controversial. Objective: Investigate cleaning efficacy and cost of different detergent classes in an automated washer disinfector (AWD) designed for dental practice. Methods: Loads comprised test soiled dental hand instruments in cassettes and extraction forceps. Residual protein assayed using the International standard method (ISO 15883-5:2005) 1% SDS elution with ortho-phthalaldehyde (OPA) or GBox technology (on instrument OPA analysis). Short (60 minutes) and long (97 minutes) AWD cycles were used with four different classes of detergents, tap water and reverse osmosis water. Results: SDS elution analysis (N = 612 instruments) demonstrated four detergents with both wash cycles achieved equivalent cleanliness levels and below a threshold of 200 µg protein/instrument. GBox methodology (N = 575) using UK Department of Health threshold of 5 µg/instrument side demonstrated that tap water performed with the greatest efficacy for all types of instruments and cycle types. Conclusions: Using International standard methodology, different detergent classes had equivalence in cleaning efficacy. Cheaper detergents used in this study performed with similar efficacy to more expensive solutions. Findings emphasise the importance of validating the detergent (type and concentration) for each AWD.