Search

Objectives To compare the perioperative and postoperative outcomes of single port robotic pyeloplasty and multiport robotic pyeloplasty using a propensity-score matched analysis. Materials and Methods We performed a chart review of all patients who underwent single port robotic pyeloplasty from January 2019 to October 2020 and multiport robotic pyeloplasty from January 2016 to October 2020. Patient demographics, intraoperative data, and postoperative outcomes were collected and analyzed. Propensity-score matching was performed on sex, body mass index, and history of previous pyeloplasty to adjust for potential baseline confounders. A post hoc sensitivity analysis for operative time was performed to examine the robustness of the results. Results In total, 24 and 41 patients underwent single port and multiport robotic pyeloplasty, respectively. Following propensity-score matching, 21 multiport cases were matched 1:1 to single port cases. The SP group was shown to have longer median operative times (128.0 vs 88.0 minutes, p=0.0411) and shorter follow up time (9.3 vs 18.7 months, p=0.0066). In a sensitivity analysis, single port robotic pyeloplasty was marginally associated with increased operative time (95% CI -0.25, 29.72, p=0.0540). Conclusions Single port robotic pyeloplasty is a safe and acceptable alternative to multiport robotic pyeloplasty, achieving comparable perioperative and postoperative outcomes.

Immunotherapy has dramatically changed the cancer treatment landscape during the past decade, but very limited efficacy has been reported against pancreatic cancer. Several factors unique to pancreatic cancer may explain the resistance: the well-recognized suppressive elements in the tumor microenvironment, the functional and structural barrier imposed by the stroma components, T-cell exhaustion, the choice of perhaps the wrong immune targets, and microbial factors including gut dysbiosis and the unexpected presence of tumor microbes. Furthermore, we discuss various strategies to overcome these barriers.

Objectives Despite having close contact with the general public, members of the San Francisco Fire Department (SFFD) reported relatively few cases of COVID-19 during the first half of 2020. Our objective was to explore evidence for prior undetected infections by conducting a seroprevalence survey, and to document both risk and protective factors for prior COVID-19 infection. Methods This cross-sectional study assessed workplace practices and exposures of SFFD personnel during the first 6 months of 2020 via questionnaire and documented prior COVID-19 infections by serologic antibody testing using an orthogonal testing protocol. Results Of 1231 participating emergency responders, three (0.25%) had confirmed positive COVID-19 antibody results. Conclusions Safe workplace practices, community public health intervention, and low community infection rates appear to have been protective factors for emergency responders in San Francisco during our study period.

We identified the occupations that employ California women and a list of chemicals of concern for breast cancer. We evaluated the likelihood of on-the-job exposure to the categories of chemicals by occupation among formally and informally employed women. We selected 145 occupations representing more than 6.6 million women (85% of California working women), along with an additional sixteen occupations for informal workers only. We organized 1012 chemicals (including mammary gland carcinogens, developmental toxicants, and endocrine-disrupting chemicals) into twenty-five categories. More than 80 percent of occupations investigated had possible or probable exposure to at least one category of chemicals. This is the first categorization of occupational exposure to chemicals of concern for breast cancer among California working women. Our investigation revealed significant data gaps, which could be improved by policy changes resulting in enhanced collection of data on occupation and chemical exposure.

Background The clinical utility of a blood-based biomarker in squamous cell carcinoma of the anus (SCCA) is unknown. We analyzed carcinoembryonic antigen (CEA), a commonly employed assay for patients with colorectal adenocarcinoma, as a serum biomarker for patients with biopsy-proven SCCA. Materials and methods Medical records from 219 patients with biopsy-proven SCCA at the University of Texas MD Anderson Cancer Center were reviewed under an IRB-approved protocol from 2013 to 2020 to assess for correlations between CEA levels and corresponding clinical and pathologic characteristics. Results The mean CEA among subgroups by clinical status at the time of presentation to our institution was highest among those patients with metastatic SCCA to visceral organs (M-V, 20.7 ng/mL), however this finding was not statistically significant by ANOVA (p = .74). By clinical subgroup, the percentage of patients with an abnormally elevated CEA was highest in those patients with metastatic disease to lymph nodes (M-L, 41.2%) followed by recurrent/unresectable SCCA (36.8%), and metastatic SCCA to visceral organs (M-V, 35.2%), and was statistically significant between groups (Fisher's exact test p = .02). Using RECIST criteria for tumor progression and disease response, the mean change in CEA for patients with progression was an increase in 19 ng/mL, compared to a change of -7.3 ng/mL in those with disease response (p = .004). We likewise assessed whether CEA levels were associated with survival outcomes for all patients with metastatic SCCA, and found no correlation between CEA and likelihood for survival in a ROC analysis (multivariate, age-adjusted analysis for CEA cutoff of 8, HR = 1.01, 95% CI 0.52-1.96). Conclusions Despite interesting patterns of abnormally high CEA in SCCA patients with advanced disease, and correlation of increased CEA with disease progression (and conversely decreased CEA with disease response), CEA is not associated with survival outcomes in SCCA, and is not a clinically relevant biomarker in this disease.

Objectives This article presents a comparative study of two Health Level Seven International (HL7) standards for clinical knowledge representation, the Arden Syntax and the Clinical Quality Language (CQL), regarding their expressiveness and utility to represent knowledge for clinical decision support (CDS) systems. Methods We compiled a concatenated set of features from both languages and made descriptive comparisons of 27 categories covering areas of language characteristics, data, control statements, and operators. Results Both Arden and CQL have similar constructs that can be used for representing CDS knowledge but also have unique constructs that could support distinct use cases. They have constructs that fully or partially address several of the categories used in the comparison, except for data models and terminologies in Arden and event triggering and iteration statements in CQL. Conclusion These standards can facilitate the sharing, management, and reuse of computable knowledge, and permit knowledge to be represented with their languages and converted to a machine-friendly executable code that can be shared and reused by other systems. Having support for standard data models and terminologies will continue to be a differential for adoption of a language. The HL7 working groups responsible for developing these standards can direct future development to enhance the functions of the standard and address the gaps identified in this study.

Virtual Engineering (VE) has always been a great aid in the design phase of manufacturing systems in terms of structural system description, behaviour simulation and interfacing between the different subsystems. To this end, virtual engineering capabilities have a strong potential to be employed in manufacturing system sustainability at different phases of the system life cycle beyond the design phase. In response to the sustainable manufacturing requirements (namely 6R), this paper discusses the opportunities VE provides to support sustainable manufacturing over the life cycle phases considering the latest industrial developments in manufacturing i.e. Industry 4.0 and smart manufacturing. A framework of virtual engineering tools integration with 6R is introduced, then a discussion of the expected contributions follows. To demonstrate the applicability of the previously mentioned concepts, a case study of an on-going industrial project is exemplified with its results discussion.

Background As climate change increases global temperatures, heat-related morbidity and mortality are projected to rise. Outdoor workers and those who perform exertional tasks are particularly susceptible to heat-related illness (HRI). Using workers' compensation data, we aimed to describe rates of occupational HRI in California and identify demographic and occupational risk factors to inform prevention efforts. Methods We identified HRI cases during 2000-2017 in the California Workers' Compensation Information System (WCIS) using International Classification of Diseases Ninth and Tenth Revision codes, WCIS nature and cause of injury codes, and HRI keywords. We assigned industry and occupation codes using the NIOSH Industry and Occupation Computerized Coding System (NIOCCS). We calculated HRI rates by sex, age group, year, county, industry, and occupation, and estimated confidence intervals using generalized linear models. Results We identified 15,996 HRI cases during 2000-2017 (6.0 cases/100,000 workers). Workers aged 16-24 years had the highest HRI rate (7.6) among age groups, and men (8.1) had a higher rate than women (3.5). Industry sectors with the highest HRI rates were Agriculture, Farming, Fishing, and Forestry (38.6), and Public Administration (35.3). Occupational groups with the highest HRI rates were Protective Services (56.6) and Farming, Fishing, and Forestry (36.6). Firefighters had the highest HRI rate (389.6) among individual occupations. Conclusions Workers in certain demographic and occupational groups are particularly susceptible to HRI. Additional prevention efforts, including outreach and enforcement targeting high-risk groups, are needed to reduce occupational HRI. Workers' compensation data can provide timely information about temporal trends and risk factors for HRI.

With growing evidence of inhalation of small infectious particles as an important mode of transmission for SARS-CoV-2, workplace risk assessments should focus on eliminating or minimizing such exposures by applying the hierarchy of controls. We adapt a control banding model for aerosol-transmissible infectious disease pandemic planning to encourage the use of source and pathway controls before receptor controls (personal protective equipment). Built on the recognition that aerosol-transmissible organisms are likely to exhibit a dose–response function, such that higher exposures result from longer contact times or higher air concentrations, this control banding model offers a systematic method for identifying a set of source and pathway controls that could eliminate or reduce the need for receptor controls. We describe several examples for workers at high risk of exposure in essential or return to work categories. The goal of using control banding for such workers is to develop effective infection and disease prevention programs and conserve personal protective equipment.

BackgroundInformation on the occupational distribution of COVID-19 mortality is limited.ObjectiveTo characterize COVID-19 fatalities among working Californians.DesignRetrospective study of laboratory-confirmed COVID-19 fatalities with dates of death from January 1 to December 31, 2020.SettingCalifornia.ParticipantsCOVID-19 accounted for 8,050 (9.9%) of 81,468 fatalities among Californians 18-64 years old. Of these decedents, 2,486 (30.9%) were matched to state employment records and classified as “confirmed working.” The remainder were classified as “likely working” (n=4,121 [51.2%]) or “not working” (n=1,443 [17.9%]) using death certificate and case registry data.MeasurementsWe calculated age-adjusted overall and occupation-specific COVID-19 mortality rates using 2019 American Community Survey denominators.ResultsConfirmed and likely working COVID-19 decedents were predominantly male (76.3%), Latino (68.7%), and foreign-born (59.6%), with high school or less education (67.9%); 7.8% were Black. The overall age-adjusted COVID-19 mortality rate was 30.0 per 100,000 workers (95% confidence interval [CI], 29.3-30.8). Workers in nine occupational groups had mortality rates higher than this overall rate, including those in farming (78.0; 95% CI, 68.7-88.2); material moving (77.8; 95% CI, 70.2-85.9); construction (62.4; 95% CI, 57.7-67.4); production (60.2; 95% CI, 55.7-65.0); and transportation (57.2; 95% CI, 52.2-62.5) occupations. While occupational differences in mortality were evident across demographic groups, mortality rates were three-fold higher for male compared with female workers and three- to seven-fold higher for Latino and Black workers compared with Asian and White workers.LimitationsThe requirement that fatalities be laboratory-confirmed and the use of 2019 denominator data may underestimate the occupational burden of COVID-19 mortality.ConclusionCalifornians in manual labor and in-person service occupations experienced disproportionate COVID-19 mortality, with the highest rates observed among male, Latino, and Black workers.

Introduction & Objective: Scant literature is available on surgical outcomes of radical cystectomies on the new single-port (SP) system. This study compares short term outcomes in patients undergoi...

IntroductionBCG vaccination modulates immune responses to unrelated pathogens. This off-target effect could reduce the impact of emerging pathogens. As a readily available, inexpensive intervention that has a well-established safety profile, BCG is a good candidate for protecting healthcare workers (HCWs) and other vulnerable groups against COVID-19.Methods and analysisThis international multicentre phase III randomised controlled trial aims to determine if BCG vaccination reduces the incidence of symptomatic and severe COVID-19 at 6 months (co-primary outcomes) compared with no BCG vaccination. We plan to randomise 10 078 HCWs from Australia, The Netherlands, Spain, the UK and Brazil in a 1:1 ratio to BCG vaccination or no BCG (control group). The participants will be followed for 1 year with questionnaires and collection of blood samples. For any episode of illness, clinical details will be collected daily, and the participant will be tested for SARS-CoV-2 infection. The secondary objectives are to determine if BCG vaccination reduces the rate, incidence, and severity of any febrile or respiratory illness (including SARS-CoV-2), as well as work absenteeism. The safety of BCG vaccination in HCWs will also be evaluated. Immunological analyses will assess changes in the immune system following vaccination, and identify factors associated with susceptibility to or protection against SARS-CoV-2 and other infections.Ethics and disseminationEthical and governance approval will be obtained from participating sites. Results will be published in peer-reviewed open-access journals. The final cleaned and locked database will be deposited in a data sharing repository archiving system.Trial registrationClinicalTrials.gov NCT04327206

INTRODUCTION AND OBJECTIVE:IRIS is an interactive, three-dimensional (3D) anatomical model system designed to assist surgeons with pre-surgical planning and provide a reference intraoperatively. Ge...

INTRODUCTION AND OBJECTIVE:In this study we set out to compare perioperative and follow-up outcomes between single port robot-assisted laparoscopic pyeloplasty (SP-LRP) and multiport robot-assisted...

INTRODUCTION AND OBJECTIVE:This study seeks to compare perioperative outcomes between single port (SP) and multiport (MP) robot-assisted laparoscopic radical prostatectomy (RALP) cases utilizing pr...

INTRODUCTION AND OBJECTIVE:Single-port (SP) robotic surgery is a new technology and early in its adoption curve. There has been significant interest in utilizing this platform for partial nephrecto...

INTRODUCTION AND OBJECTIVE:Robotic ureteroneocystostomy can be performed via nontransecting side-to-side anastomosis, which eschews ureteral transection to preserve distal vascularity. We have prev...

INTRODUCTION AND OBJECTIVE:Scant literature is available on surgical outcomes of radical cystectomies on the new single-port (SP) system. This study compares short term outcomes in patients undergo...

Objective To describe the frequency of work-related asthma (WRA) and characteristics of individuals with exposure to cleaning products 1998 to 2012, compared with 1993 to 1997. Methods Cases of WRA from products used for cleaning or disinfecting surfaces were identified from California, Massachusetts, Michigan (1998 to 2012), New Jersey (1998 to 2011), and New York (2009 to 2012). Results There were 1199 (12.4%) cleaning product cases among all 9667 WRA cases; 77.8% women, 62.1% white non-Hispanic, and average age of 43 years. The highest percentages worked in healthcare (41.1%), and were building cleaners (20.3%), or registered nurses (14.1%). Conclusions The percentage of WRA cases from exposure to cleaning products from 1998 to 2012 was unchanged from 1993 to 1997 indicating that continued and additional prevention efforts are needed to reduce unnecessary use, identify safer products, and implement safer work processes.

Industry 4.0 is reshaping modern manufacturing with increased data availability and accessibility. Therefore, further support of the system and product lifecycles is provided. On the other hand, sustainable manufacturing gains more attention due to the environmental concerns and resource consumption. The green impact of lean six sigma has been approached in literature. However, the changes to a manufacturing system’s nature provide new insights to employ lean six sigma quality tools for further sustainability. This paper proposes a framework of using six sigma to achieve the sustainable manufacturing requirements from the perspective of Industry 4.0 and its enablers. The influence of information and communication technologies (ICTs) on the relationship between sustainable manufacturing 6R and lean six sigma DMAIC is studied. A case study of cylindrical cell battery assembly line is used to investigate the effectiveness of the proposed approach. The framework can be adjusted to suit different types of manufacturing processes and systems.

The burden and prognosis of malignant mesothelioma in the United States have remained largely unchanged for decades, with approximately 3200 new cases and 2400 deaths reported annually. To address care and research gaps contributing to poor outcomes, in March of 2019 the Mesothelioma Applied Research Foundation convened a workshop on the potential usefulness and feasibility of a national mesothelioma registry. The workshop included formal presentations by subject matter experts and a moderated group discussion. Workshop participants identified top priorities for a registry to be (a) connecting patients with high-quality care and clinical trials soon after diagnosis, and (b) making useful data and biospecimens available to researchers in a timely manner. Existing databases that capture mesothelioma cases are limited by factors such as delays in reporting, deidentification, and lack of exposure information critical to understanding as yet unrecognized causes of disease. National disease registries for amyotrophic lateral sclerosis (ALS) in the United States and for mesothelioma in other countries, provide examples of how a registry could be structured to meet the needs of patients and the scientific community. Small-scale pilot initiatives should be undertaken to validate methods for rapid case identification, develop procedures to facilitate patient access to guidelines-based standard care and investigational therapies, and explore approaches to data sharing with researchers. Ultimately, federal coordination and funding will be critical to the success of a National Mesothelioma Registry in improving mesothelioma outcomes and preventing future cases of this devastating disease.

Highly diverse factors including technological advancements, uncertain global market and mass personalisation are believed to be main causes of ever-growing complexity of manufacturing systems. Although complex systems may be needed to achieve global manufacturing requirements, complexity affects on various factors, such as: system development effort and cost, ease of re-configuration, level of skill required across the system life-cycle (e.g. design, operate and maintain). This article aims to develop a scientifically valid and industrially applicable complexity assessment approach to support early life-cycle phases of component-based automation systems against unwanted implications of structural system complexity. The presented approach defines component-based automation system as a constellation of basic components which can be represented in various design domains, such as: mechanical, electrical, pneumatic, control, etc. Accordingly, structural complexity is expressed as the combination of both inherent complexity of system entities and topological complexity resulting from the integration of elements of such constellations in a multi-layered network. The proposed approach is used to specify and implement a complexity assessment module which can be integrated into a series of virtual system design software solutions, in order to add complexity assessment as part of the design support and validation tools used by manufacturing engineers. Consequently, the proposed approach is integrated into the vueOne virtual engineering tool, wherein virtual automation system design data can be streamlined and used as input to the theoretical complexity model. In the developed tool, only mechanical and logical design domains are considered due to the limited data availability in early design phase. Inherent complexity of both mechanical and logical system entities and their interactions are expressed as a function of domain-specific design elements, and topological complexity is defined as the graph energy of the corresponding design connectivity matrix. Furthermore, the values of mathematical model parameters are determined based on an optimisation study, where subjective opinions of system/control engineers regarding the effort/difficulty associated with the development of thirty different component-based automation system designs are correlated with the corresponding complexity model outputs to minimise the prediction errors. The proposed approach is also demonstrated on a modular production system consisting of four sub-modules. The study shows that the approach can help designers/managers to better identify root causes of structural system complexity, and provides a systemic approach to compare alternate system designs during early system planning phase.

Silicosis is an incurable occupational lung disease caused by inhaling particles of respirable crystalline silica. These particles trigger inflammation and fibrosis in the lungs, leading to progressive, irreversible, and potentially disabling disease. Silica exposure is also associated with increased risk for lung infection (notably, tuberculosis), lung cancer, emphysema, autoimmune diseases, and kidney disease (1). Because quartz, a type of crystalline silica, is commonly found in stone, workers who cut, polish, or grind stone materials can be exposed to silica dust. Recently, silicosis outbreaks have been reported in several countries among workers who cut and finish stone slabs for countertops, a process known as stone fabrication (2-5). Most worked with engineered stone, a manufactured, quartz-based composite material that can contain >90% crystalline silica (6). This report describes 18 cases of silicosis, including the first two fatalities reported in the United States, among workers in the stone fabrication industry in California, Colorado, Texas, and Washington. Several patients had severe progressive disease, and some had associated autoimmune diseases and latent tuberculosis infection. Cases were identified through independent investigations in each state and confirmed based on computed tomography (CT) scan of the chest or lung biopsy findings. Silica dust exposure reduction and effective regulatory enforcement, along with enhanced workplace medical and public health surveillance, are urgently needed to address the emerging public health threat of silicosis in the stone fabrication industry.

Modern manufacturing relies heavily on digital technologies, and the recent changes in the manufacturing environment are the reflection of the advancements in information and communication technologies. Web-based Digital Twin (WDT) will constitute the future of manufacturing giving a greater potential of process/product data interaction, where Digital Twin functions on a web browser and connects to its Physical Twin to exchange data. To this end, the research work on WDT is still in the first stages. Therefore, the current paper presents a framework for developing WDT taking into account the possibility of utilising WDT for education, research and industrial applications. A case study adopted from a mini-scale assembly line is used to illustrate the proposed concept.\ud

Protecting Olympic Participants from Covid-19 Plans to protect participants and the public from Covid-19 during the Olympics aren’t built on rigorous risk assessment. They fail to consider the ways...

The shift towards utilising web-based technologies is trending as a reflection of the new business model of modern manufacturing. Web-based digital twin (WDT) has great potential for promoting sustainability in industrial cyber-physical systems. The current work demonstrates the mechanism by which a WDT architecture is established and utilised for improving sustainability. This is achieved by: a) accessing the control parameters that influence energy consumption, b) logging the energy consumption data and c) producing predictions by means of a computational algorithm. The objective is to support the system developer in delivering verified machine functionality along with trusted productivity and sustainability. The implementation is exemplified by an industrial case study adopted from a battery assembly production line.\ud

Importance Methylene chloride is a halogenated organic solvent widely used in paint strippers, cleaners, adhesives, and sealants. Despite label warnings and occupational standards, methylene chloride–related fatalities continue to occur in the United States. Objective To identify and analyze methylene chloride–related fatalities in the US. Design, Setting, and Participants For this case series, we conducted systematic searches of sources, including PubMed and government databases, for unintentional fatalities in the US that were associated with exposure to methylene chloride or products containing methylene chloride between 1980 and 2018. We reviewed all available information, including inspection reports, autopsy reports, and medical records; data analyses were conducted from August 2018 to August 2020. Cases were categorized as those occurring in the home (consumer deaths) or at work (occupational deaths). Exposures Methylene chloride or products containing methylene chloride. Main Outcomes and Measures To determine characteristics of the methylene chloride–related fatalities, we recorded demographic information; the setting; circumstances, including information on safety measures used, if available; and products used. Where medical records were available, we recorded toxicology results and autopsy findings. We also obtained data about nonfatal methylene chloride cases from the American Association of Poison Control Centers. Results From 1980 to 2018, 85 methylene chloride–related fatalities were identified in the US, including 74 (87%) in occupational settings; of those who died, 75 (94%) were men, and for the 70 cases with available information, the median (interquartile range) age of the decedents was 31 (24-46) years. Paint strippers were the most common products involved in methylene chloride–related fatalities (n = 60). The proportion of occupational fatalities related to paint stripping increased from 22 (55%) before 2000 to 30 (88%) after 2000. Similarly, occupational fatalities associated with bathtub or paint stripping in bathrooms increased from 2 (5%) before 2000 to 21 (62%) after 2000. From 1985 to 2017, the American Association of Poison Control Centers documented 37 201 nonfatal methylene chloride cases, with a decrease in the annual number of cases starting in the late 1990s. Conclusions and Relevance Results of this case series demonstrated that despite regulations to address the toxic effects of methylene chloride use for consumers and workers, there are continuing fatalities in the US, particularly in occupational settings. Prevention of fatalities associated with methylene chloride exposure should emphasize the use of safer substitutes, rather than hazard warnings or reliance on personal protective equipment.

The literature on the modeling and management of data generated through the lifecycle of a manufacturing system is split into two main paradigms: product lifecycle management (PLM) and product, process, resource (PPR) modeling. These paradigms are complementary, and the latter could be considered a more neutral version of the former. There are two main technologies associated with these paradigms: ontologies and databases. Database technology is widespread in industry and is well established. Ontologies remain largely a plaything of the academic community which, despite numerous projects and publications, have seen limited implementations in industrial manufacturing applications. The main objective of this paper is to provide a comparison between ontologies and databases, offering both qualitative and quantitative analyses in the context of PLM and PPR. To achieve this, the article presents (1) a literature review within the context of manufacturing systems that use databases and ontologies, identifying their respective strengths and weaknesses, and (2) an implementation in a real industrial scenario that demonstrates how different modeling approaches can be used for the same purpose. This experiment is used to enable discussion and comparative analysis of both modeling strategies.

The potential benefits of the adoption of cyber–physical production systems (CPPSs) and their significant role in enabling smart manufacturing is well recognized today. However, it is less clear how such CPPS can be most effectively and consistently engineered and maintained throughout their lifecycle due to the existing divide in the information technology (IT) and operational technology (OT) landscape and ad hoc integration practices that result in inconsistent data and data models at various levels of manufacturing processes. The work presented in this article addresses this problem by envisioning a connective framework to support the engineering of CPPS through the use of a set of digital twins consistent with the real system throughout its lifecycle, not just used in the design and deployment phases. A review of the latest perspectives on using digital integration frameworks, methods, and solutions for lifecycle engineering of CPPS is provided in this article. This article demonstrates how a suitable framework, named SIMPLE, can be realized to effectively address the lack of consistent data models throughout the engineering lifecycle, including implementation details and example cases developed by the authors at the Warwick Manufacturing Group (WMG) in selected industrial sectors. Consideration is given to supporting cyber-to-physical systems’ connectivity and extendable engineering toolsets, forming the basis for multidisciplinary digital engineering environments. Key discussion points include the role and importance of effective integration of IT and OT, suitable frameworks for integration and collaboration.

Inflammatory breast cancer is a rare and aggressive malignancy that is often initially misdiagnosed because of its similar presentation to more benign breast pathologies such as mastitis, resulting in treatment delays. Presenting symptoms of inflammatory breast cancer include erythema, skin changes such as peau d' orange or nipple inversion, edema, and warmth of the affected breast. The average age at diagnosis is younger than in noninflammatory breast cancer cases. Known risk factors include African American race and obesity. Diagnostic criteria include erythema occupying at least one-third of the breast, edema, peau d' orange, and/or warmth, with or without an underlying mass; a rapid onset of

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly.

Highlights • Elastomeric respirators offer protection equivalent to N95 filtering facepiece respirators (FFRs), are designed to be re-used many times, and can result in considerable supply and cost savings immediately and over time. • Every healthcare worker could receive their own easily accessible, re-useable, personal elastomeric respirator available whenever needed during patient care activities. • The use of elastomeric respirators by healthcare workers would free up supplies of N95 FFRs for workers at lower risk in healthcare and other essential workplaces. • Incorporating elastomeric respirators requires some additional procedures that are relatively easy to add to an existing respiratory protection program., Graphical abstract Image, graphical abstract

The purpose of this systematic review is to determine the frequency of violent or aggressive behaviour towards healthcare workers in inpatient psychiatric settings in the United States. To achieve this aim, five databases were searched to find English-language quantitative studies reporting prevalence or incidence data of violence or aggression directed towards staff members in inpatient psychiatric settings. No limitations were set based on publication date, and intervention studies were included only if baseline data were provided. Of 335 total studies found, 38 full-text articles were suitable for full-text analysis based on inclusion and exclusion criteria, and 14 were included in the final review. Years of data collection ranged from 1986 to 2018, and a range of psychiatric facilities were represented, from small, private hospital units to large forensic institutions. Researchers utilized surveys, real-time incident reporting tools, and government databases, or a combination of strategies, to collect data related to workers' experiences on the job. Included research indicates that workplace violence in the U.S. inpatient psychiatric setting is a widespread problem, with 25-85% of survey respondents reporting an incident of physical aggression within the year prior to survey, and statewide workers' compensation findings indicating 2-7 claims due to assault per 100 000 employee hours. There are substantial differences between findings based on measurement strategy, making it difficult to arrive at a single estimate of prevalence nationally. As management of this persistent problem receives continued attention from stakeholders, it becomes increasingly important to define and measure the problem with the most appropriate tools.

Digital modelling and simulation of manufacturing processes find increasing use in the manufacturing industry. This provides an opportunity to use model information and carry them over into the software development phase to realise automatic PLC code generation. This paper extends the work presented in [1] to enable generation of function blocks for resource components rather than manually coding FBs. The approach is based on mapping table based that allow users to select required functionality, such as auto and manual control, diagnostic, return to initial position for machine components. This mapping table is filled by a programmer and links the information together. The approach provides a structured code that is generated in the IEC 61131–3 Structured Text. Additionally, the paper presents a use case as a proof of concept implementation. The approach is formalized and justified from the viewpoint of the RAM14.0 specification and resulted in between 62 – 81 per cent time saving compared to manual coding of the FBs.

Commercial competence to satisfy customer demands requires companies to provide the necessary skilled engineering staff and fight against time to achieve that. Learning Factories (LF) aim to provide training and education so that the manufacturing facility can respond to its production aims. However, the implementation of learning factories concept is adopting different styles especially with the rise of Industry 4.0. On the other hand, sustainability concerns are becoming more serious and need to be fulfilled due to the recent climate changes. In this paper, a literature survey of the recent developments in this field is conducted with regards to energy sustainability. In particular, an analysis of the pedagogical aspect in terms of the applied learning theories, curriculum design and learning environment is explored. Further, some criticisms based on the analysis are put forward, and some research topics are suggested in relation to both the pedagogical and technical aspects.

Background In California, state prison inmates are employed to fight wildfires, which involves performing soil-disrupting work. Wildfires have become more common, including areas where Coccidioides, the soil-dwelling fungus that causes coccidioidomycosis, proliferates. However, work practices that place wildland firefighters at risk for coccidioidomycosis have not been investigated. Methods On August 17, 2017, the California Department of Public Health was notified of a cluster of coccidioidomycosis cases among Wildfire A inmate wildland firefighters. We collected data through medical record abstraction from suspected case-patients and mailed a survey assessing potential job task risk factors to Wildfire A inmate firefighters. We described respondent characteristics and conducted a retrospective case-control investigation to assess coccidioidomycosis risk factors. Results Among 198 inmate firefighters who worked on Wildfire A, 112 (57%) completed the survey. Of 10 case-patients (four clinical and six laboratory-confirmed), two were hospitalized. In the case-control analysis of 71 inmate firefighters, frequently cutting fire lines with a McLeod tool (odds ratio [OR]: 5.5; 95% confidence interval [CI]: 1.1-37.2) and being in a dust cloud or storm (OR: 4.3; 95% CI: 1.1-17.4) were associated with illness. Two of 112 inmate firefighters reported receiving coccidioidomycosis training; none reported wearing respiratory protection on this wildfire. Conclusions Wildland firefighters who use hand tools and work in dusty conditions where Coccidioides proliferates are at risk for coccidioidomycosis. Agencies that employ them should provide training about coccidioidomycosis and risk reduction, limit dust exposure, and implement respiratory protection programs that specify where respirator use is feasible and appropriate.

In order to meet the increasing demand for industrial cyber physical systems, highly qualified professionals are required who possess both excellent professional knowledge and skills as well as soft skills. The interdisciplinarity of industrial cyber physical systems makes teaching the necessary skill challenging. The approach known from the education of software engineering, in which students form a team to develop a software product, is not sufficient. There is also a lack of soft skills, which are often seen as key success factors for engineering projects. To close the existing gaps in education of industrial cyber-physical systems engineering, the task-centric holistic agile teaching approach (T-CHAT) is proposed. This approach will be implemented in a newly developed curriculum for industrial cyber physical systems at the ITMO University St. Petersburg, Russia. It focuses on teaching of both technical and soft skills.

This paper presents a holistic approach that enables manufacturers to systematically select appropriate Key Performance Indicators (KPIs) for their shop floor operations assessment. The approach is based on the contemplation that KPIs can be selected on the basis of a set of measures that are theoretically grounded. The approach consists of five layers namely: information layer, discernment layer, scheming layer, origin of data layer and assisting technology to capture the data layer. Each layer consists of set of measures dedicated to provide vital information that will assist manufacturers in better monitoring of their shop floor operations and improve decision-making capabilities. The practicality of the proposed approach is demonstrated through its application to an automotive seat manufacturing company.

Manufacturing industry is in the midst of reshaping modern manufacturing by employing digital technologies due to its promising results. More and more companies are marching towards migrating their product offering and production infrastructure into Industry 4.0-compliant solutions. In this new era of industrial scenario, companies will need technicians and workers with digital skills mainly having abilities and competences in the Industry 4.0 Key Enabling Technologies (KET). However, lack of digital skills in the UK is considered perhaps the most serious obstacle to the practical implementation and investment in manufacturing digitalization technologies and is thus a major contributing factor to the UK productivity gap. Aiming to bridge the gap between the implementation of Industry 4.0 and educational organizations that focus on this field, the study presented here focuses on the development of a degree apprenticeship program in Digital technology solutions (DTS). The DTS program is developed in collaboration with leading UK industry partners to acquaint apprentices with appropriate knowledge that can help them to contribute towards digital transformation of their businesses

The academia-industry gap in computer science persists since last two decades at least. Industry expects that computer science graduates possess not only profound technical knowledge and skills but also transferable skills such as communication and collaboration in team, problem-solving ability. Students need to learn those skills during their university studies to be competitive in the market after their graduation. This paper first examines the skill gap between graduates and industry expectations, and the existing didactic approaches in computer science education. The authors then present how the Java programming course has been taught using the task-centric holistic agile teaching approach T-CHAT to enhance both technical skills and transferable skills in students. The learning process is described with learning activities and assessments that are constructively aligned with the intended learning outcomes of the course. This is work in progress, so evaluation of the course is planned for future work.

Background This study evaluated the impact of California's safe patient handling (SPH) legislation on musculoskeletal injury prevention among hospital nurses. Methods Two serial cross-sectional surveys were conducted using postal and online questionnaires in statewide random samples of California registered nurses in 2013 and 2016. Analysis included hospital nurses who performed patient handling (n = 254 and n = 281, respectively). Results In 2016, there were significant improvements in nurses' knowledge of a SPH policy in their hospital (87%), receipt of annual SPH training (73%), and availability of lift equipment (80%); 33% perceived their hospital's SPH programs as excellent or very good. Significant prevalence reduction was observed for work-related musculoskeletal symptoms (61% vs 52%; Adjusted Prevalence Ratio = 0.78, 95% CI 0.66-0.91). Conclusions Our findings indicate the significant role of SPH legislation with positive impacts on SPH policies and programs at the hospital level and on musculoskeletal health outcomes at the worker level.

Carpal tunnel syndrome (CTS) occurs when the median nerve becomes compressed as it passes through the wrist within the carpal tunnel, resulting in pain, tingling, weakness, or numbness in the hand or the wrist. Occupational risk factors for CTS include engaging in work activities that require forceful, repetitive tasks, prolonged use of the hands or wrists in an awkward posture, or vibration (1). To assess trends and identify high-risk industries and occupations for CTS, the California Department of Public Health (CDPH) analyzed California workers' compensation claims for CTS by industry (2007-2014) and occupation (2014) and calculated rates per full-time equivalent (FTE) worker. During 2007-2014, a total of 139,336 CTS cases were reported (incidence = 6.3 cases per 10,000 FTE) in California workers; the rate among women (8.2) was 3.3 times higher than that among men (2.5). Industries with the highest rates of CTS were textile, fabric finishing, and coating mills (44.9), apparel accessories and other apparel manufacturing (43.1), and animal slaughtering and processing (39.8). Industries with high rates of CTS should consider implementing intervention measures, including ergonomic evaluations and development of tools and instruments that require less repetition and force and that correct awkward postures.

In 2017, the Council of State and Territorial Epidemiologists performed its sixth periodic Epidemiology Capacity Assessment, a national assessment that evaluates trends in workforce size, funding, and epidemiology capacity among state health departments. A standardized web-based questionnaire was sent to the state epidemiologist in the 50 states, the District of Columbia (DC), and the U.S. territories and the Federated States of Micronesia inquiring about the number of current and optimal epidemiologist positions; sources of epidemiology activity and personnel funding; and each department’s self-perceived capacity to lead activities, provide subject matter expertise, and obtain and manage resources for the four Essential Public Health Services (EPHS)* most closely linked to epidemiology. From 2013 to 2017, the number of state health department epidemiologists† increased 22%, from 2,752 to 3,369, the greatest number of workers since the first full Epidemiology Capacity Assessment enumeration in 2004. The federal government provided most (77%) of the funding for epidemiologic activities and personnel. Substantial to full capacity (50%–100%) was highest for investigating health problems (92% of health departments) and monitoring health status (84%), whereas capacity for evaluating effectiveness (39%) and applied research (29%) was considerably lower. An estimated additional 1,200 epidemiologists are needed to reach full capacity to conduct the four EPHS. Additional resources might be needed to ensure that state health department epidemiologists possess the specialized skills to deliver EPHS, particularly in evaluation and applied epidemiologic research.

The paradigm shift from mass production to mass customisation and reduced product lifecycles requires continuous re-engineering/configuration of modern manufacturing systems. Although efforts are being made to design and build manufacturing systems based on the paradigms of changeability, reconfigurability, and flexibility, the knowledge of the system's capability remains unstructured and isolated from product design and engineering tools. As a result, introducing product design changes are costly, time-consuming and error-prone. To address this problem, this research utilises a Product, Process, and Resource (PPR) ontology with a view to supporting changes through information integration and knowledge generation. The approach moves away from product-centric tools such as Product Lifecycle Management (PLM) and thus a heterarchical model of the system is created. The contribution of this work is to demonstrate how modular ontologies can be utilised in a practical and industrially relevant manner by integrating the data structure of a set of component-based virtual engineering tools into the Resource domain. The research presents a proof-of-concept of the proposed approach using an automated engine assembly station as a case study. Inferences are made from explicit knowledge through rules and mapping as to whether both Product and Process requirements are met by Resource domain capabilities. The approach used in this work has the potential to significantly improve the workflow as and when new products are introduced or modifications need to be made as the scope of change can be assessed rapidly resulting in more focused engineering and design work.

Electric vehicles are currently on the rise due to environmental and legal concerns. Furthermore, improvements made in battery assembly steadily boosts the efficiency of electric vehicles. A well-prevalent method to overcome the uncertainties that emerge from the ever-changing battery technology, is to assemble products using pilot production lines. However, literature pertaining to the scale-up of pilot production lines for full scale production is scarce. Therefore, in this paper, potential scale-up scenarios for battery module assembly line are proposed in a discrete event simulation software and results are compared. Furthermore, the benefits of the proposed method are discussed with a test case.

94 Background: Increasingly, dedicated clinics have been established to expedite patients with suspicion of malignancy into cancer care. The Lyndon B. Johnson General Hospital (LBJGH) is part of the Harris County Hospital District (HCHD), serving the third largest county in the United States. A 2012 study at our institution found long mean ambulatory wait times for the diagnosis of breast, colon, and lung cancers (77.1 days, 65.4 days, and 70.8 days, respectively). The LBJGH Oncology Diagnostic and Screening clinic (DSC) was subsequently established to reduce ambulatory diagnostic times, decrease frequency of admissions, and improve patient outcomes. Our present study sought to establish the effectiveness of the DSC in bringing patients into care. Methods: The charts of 100 new patients seen in the DSC between August 2018 and November 2020 were reviewed. Demographic data, insurance status, date of referral to the DSC, date of first DSC visit, date biopsy or outside pathology ordered, date biopsy performed or outside pathology obtained, total number of visits to the DSC, and total time from initial DSC visit to initial oncology clinic visit were collected, as well as cancer stage upon arrival to the oncology clinic. The project was approved by the MD Anderson Quality Improvement Assessment Board and the Harris Health Quality Improvement Committee. Results: 57% of patients seen in the DSC were referred by the emergency department, and 23% by a PCP. The median time from referral to initial visit in the DSC was 19 days. 26% of patients had a known cancer diagnosis at the time of referral. The median time from biopsy ordered to performed was 39 days, and the median time from pathology requested to obtained was 23 days. The median total number of visits per patient to the DSC was 2. 48% of patients seen in the DSC were ultimately diagnosed with cancer, 29% had a benign condition, and 23% were lost to follow up. Of those patients with confirmed malignancy, 46% of patients had stage IV disease at their first oncology clinic visit. The average time from initial DSC visit to initial visit at the oncology clinic was 53 days. Conclusions: Establishment of an oncology DSC has improved the ambulatory wait time for entry into oncologic care from an average of approximately 70 days to an average of 53 days. However, almost half of patients referred from the DSC had stage IV disease at their initial oncology visit, indicating an urgent need to further expedite entry of these patients into oncologic care. Avenues for future quality improvement efforts include an expedited process to obtain outside pathology results, implementation of an “e-consult” option for PCPs to avoid unnecessary referrals, and a close analysis of insurance and financial barriers to entry into care. Reference: Mougalian SS, Wang J, Zarzour M et al. Feasibility and savings of a suspicion of cancer clinic at a large county hospital. JCO 2012; 30 (34 supplement): 104.