Systems-focussed risk and process safety education

PresentationRisk management and safety are at the core of performance in the process and manufacturing industries. Global studies by major consultancies show that mature risk management drives performance. That maturity considers a multifaceted risk perspective. Given the complexity of risk and process safety situations in industry a strong systems focus provides an effective means for establishing learning designs and driving student outcomes. This paper describes the design principles, implementation, learning activities of two compulsory, integrated units in risk management and process safety within the School of Chemical Engineering at The University of Queensland. Two courses, one in the 4th year of the Bachelor’s degree, and another in the 5th year of our Integrated Masters program were designed on the educational basis of the Knowing, Acting, Being (K-A-B) schema. This curriculum model considers the key knowledge domains in each course, their interlinking, as well as active learning strategies to exercise the knowledge areas within a socio-technical systems approach. The ‘Being’ aspect focusses on the personal transformation in thinking, professional attitudes and dispositions of students. It aims at preparing students for professional practice. Course design was done in conjunction with industry personnel, who continue to be involved throughout the course delivery, using live industry projects, and site visits to major hazard facilities. Learning activities are coupled to individual and group assessments that include significant industry case studies, consulting projects and professional standard reporting. Oral assessments or defence are used to get deeper insight into student learning. The transformation and expansion of previous UQ risk and safety courses that are fully immersed in socio-technical systems has provided an extensive, solid educational framework that informs, challenges and equips student engineers for entry to professional practice

The development of novel methods for the targeting and manipulation of neural circuits in vivo

Neural networks are at the core of the brain’s ability to compute complex responses to our external environment. Clinically, network dysfunction is emerging as a key component of several psychiatric and neurodegenerative disorders such as Alzheimer’s disease or schizophrenia. However, our ability to precisely and safely manipulate neural networks for research and deliver network-specific therapy remains limited. To address this problem, our lab recently developed a monosynaptically restricted Self-Inactivating Rabies virus (SiR) which enables the targeting of neural circuits without cytotoxicity. To expand the scope of SiR we further developed the technology in two directions: A) By incorporating the CRISPR/CAS9 gene-editing machinery into the SiR genome to successfully edit endogenous loci in vitro and in vivo. B) By designing an improved second generation SiR virus (SiR 2.0) which applies the same SiR technology to a challenge rabies strain (CVS-N2C). SiR 2.0 demonstrates increased neurotropism, increased trans-synaptic transfer efficiency and markedly decreased immunogenicity compared to the SiR 1.0 vector. These advancements expand the scope of SiR viruses to be used in the genome-editing of circuits in vivo. A combined SiR 2.0 CAS9 virus, in physiology, allows us to investigate the roles of genes within circuits in the brain function of live animals. For therapy, it paves the way for the rabies virus’ potential use to edit disease-related genes in dysfunctional circuits. Despite the circuit-basis of many neurological disorders, existing gene therapy vectors are not circuit specific. In addition, the practical difficulties of delivering therapeutic agents at high doses into the central nervous system exacerbates our inability to achieve high therapeutic loads into affected circuits. In contrast, a SiR 2.0 CAS9 virus would, following injection into peripheral organs, trans-synaptically spread into desired circuits of the central nervous system that are affected in neurological disease (e.g. networks demonstrating pathological protein propagation in neurodegenerative disorders) and edit disease-related genes. Lastly, our interest in network-level pathological protein propagation also led us to investigate the biology behind this observation. Due to additional evidence that a significant number of other proteins in physiology also show interneuronal movement, we hypothesised that perhaps this is an overlooked phenomena in neurobiology which could have key implication

Klasifikasi Suara Paru Normal Dan Abnormal Menggunakan Deep Neural Network dan Support Vector Machine

Penyakit pernapasan masih menjadi pembunuh tertinggi setelah stroke dan penyakit jantung, hal ini disebabkan teknik diagnosis yang masih terbatas pada auskultasi. Melalui auskultasi ditemukan bahwa paru-paru memiliki suara yang berbeda-beda, sesuai dengan kondisi kesehatan seseorang. Oleh karena itu, dimulailah penelitian untuk mengklasifikasikan jenis suara paru. Berbagai metode telah digunakan untuk penelitian di bidang tersebut, tidak terkecuali deep learning. Diantara sekian banyak metode yang berkembang di bawah label deep learning, ternyata Autoencoder hanya digunakan sekali dalam sejarah penelitian klasifikasi data suara paru. Autoencoder (AE) merupakan salah satu arsitektur Deep Neural Network yang mampu merekonstruksi suatu data. Kemampuan ini dapat dimanfaatkan sebagai metode ekstraksi ciri sehingga classfier dapat mengklasifikasikan suatu data dengan lebih baik. Oleh karena itu, autoencoder diajukan sebagai metode ekstraksi ciri pada tugas akhir ini. Kemampuan Autoencoder sebagai metode ekstraksi ciri akan diuji oleh Support Vector Machine (SVM). Vektor ciri dipersiapkan dengan continouos wavelet transform (CWT) dan tiga pemrosesan lebih lanjut, lalu diinputkan ke dalam Autoencoder. Dari dua macam pengujian, sistem klasifikasi AE-SVM berhasil mencapai akurasi sebesar 82,38%

Analysis and optimization of equitable US cancer clinical trial center access by travel time

Importance: Racially minoritized and socioeconomically disadvantaged populations are currently underrepresented in clinical trials. Data-driven, quantitative analyses and strategies are required to help address this inequity. Objective: To systematically analyze the geographical distribution of self-identified racial and socioeconomic demographics within commuting distance to cancer clinical trial centers and other hospitals in the US. Design, Setting, and Participants: This longitudinal quantitative study used data from the US Census 2020 Decennial and American community survey (which collects data from all US residents), OpenStreetMap, National Cancer Institute–designated Cancer Centers list, Nature Index of Cancer Research Health Institutions, National Trial registry, and National Homeland Infrastructure Foundation-Level Data. Statistical analyses were performed on data collected between 2006 and 2020. Main Outcomes and Measures: Population distributions of socioeconomic deprivation indices and self-identified race within 30-, 60-, and 120-minute 1-way driving commute times from US cancer trial sites. Map overlay of high deprivation index and high diversity areas with existing hospitals, existing major cancer trial centers, and commuting distance to the closest cancer trial center. Results: The 78 major US cancer trial centers that are involved in 94% of all US cancer trials and included in this study were found to be located in areas with socioeconomically more affluent populations with higher proportions of self-identified White individuals (+10.1% unpaired mean difference; 95% CI, +6.8% to +13.7%) compared with the national average. The top 10th percentile of all US hospitals has catchment populations with a range of absolute sum difference from 2.4% to 35% from one-third each of Asian/multiracial/other (Asian alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, some other race alone, population of 2 or more races), Black or African American, and White populations. Currently available data are sufficient to identify diverse census tracks within preset commuting times (30, 60, or 120 minutes) from all hospitals in the US (N = 7623). Maps are presented for each US city above 500 000 inhabitants, which display all prospective hospitals and major cancer trial sites within commutable distance to racially diverse and socioeconomically disadvantaged populations. Conclusion and Relevance: This study identified biases in the sociodemographics of populations living within commuting distance to US-based cancer trial sites and enables the determination of more equitably commutable prospective satellite hospital sites that could be mobilized for enhanced racial and socioeconomic representation in clinical trials. The maps generated in this work may inform the design of future clinical trials or investigations in enrollment and retention strategies for clinical trials; however, other recruitment barriers still need to be addressed to ensure racial and socioeconomic demographics within the geographical vicinity of a clinical site can translate to equitable trial participant representation

Use of sonic anemometry for the study of confined swirling flows in large industrial units

This work explores the methodology and errors involved in using a commercial sonic anemometer to study confined industrial swirling air flows, such as those in large cyclones or dryers in the order of hundreds of m³. Common sources of uncertainty in time-of-flight techniques and multiple-path anemometry are evaluated and corrections and methodology guidelines are proposed to deal with issues typical of full scale measurement. In particular, this paper focuses on quantifying the error associated with the disruption of the local flow caused by a HS − 50 horizontal sonic anemometer under a range of turbulence characteristic of industrial swirl towers. Under the guidelines proposed and the conditions studied here, the presence of the instrument originates a measurement error <1 − 4 % in velocity, <1 − 3 ° in direction and < 7 − 31 % in turbulent kinetic energy for an isothermal flow in the absence of solids. These ranges are above traditional uses of sonic anemometry in meteorology due to the limitations inherent to industrial units, but remain within reasonable margins for engineering applications. Laser diagnostic methods are widely used in laboratory and pilot scale cyclones or dryers but are rarely applicable to large production scales. In this context, the data collected with sonic anemometers render much lower resolution but appear in agreement with historical Particle Image Velocimetry. Methods such as the one proposed here can be a useful alternative to improve the level of detail of fluid dynamic studies in industrial units, which are often qualitative or with a limited validation

Cystatin C is glucocorticoid responsive, directs recruitment of Trem2+ macrophages, and predicts failure of cancer immunotherapy

Cystatin C (CyC), a secreted cysteine protease inhibitor, has unclear biological functions. Many patients exhibit elevated plasma CyC levels, particularly during glucocorticoid (GC) treatment. This study links GCs with CyC’s systemic regulation by utilizing genome-wide association and structural equation modeling to determine CyC production genetics in the UK Biobank. Both CyC production and a polygenic score (PGS) capturing predisposition to CyC production were associated with increased all-cause and cancer-specific mortality. We found that the GC receptor directly targets CyC, leading to GC-responsive CyC secretion in macrophages and cancer cells. CyC-knockout tumors displayed significantly reduced growth and diminished recruitment of TREM2+ macrophages, which have been connected to cancer immunotherapy failure. Furthermore, the CyC-production PGS predicted checkpoint immunotherapy failure in 685 patients with metastatic cancer from combined clinical trial cohorts. In conclusion, CyC may act as a GC effector pathway via TREM2+ macrophage recruitment and may be a potential target for combination cancer immunotherapy.publishedVersio

Lake salinization drives consistent losses of zooplankton abundance and diversity across coordinated mesocosm experiments

Human-induced salinization increasingly threatens inland waters; yet we know little about the multifaceted response of lake communities to salt contamination. By conducting a coordinated mesocosm experiment of lake salinization across 16 sites in North America and Europe, we quantified the response of zooplankton abundance and (taxonomic and functional) community structure to a broad gradient of environmentally relevant chloride concentrations, ranging from 4 to ca. 1400 mg Cl- L-1. We found that crustaceans were distinctly more sensitive to elevated chloride than rotifers; yet, rotifers did not show compensatory abundance increases in response to crustacean declines. For crustaceans, our among-site comparisons indicate: (1) highly consistent decreases in abundance and taxon richness with salinity; (2) widespread chloride sensitivity across major taxonomic groups (Cladocera, Cyclopoida, and Calanoida); and (3) weaker loss of functional than taxonomic diversity. Overall, our study demonstrates that aggregate properties of zooplankton communities can be adversely affected at chloride concentrations relevant to anthropogenic salinization in lakes.Peer reviewe

Current water quality guidelines across North America and Europe do not protect lakes from salinization

Human-induced salinization caused by the use of road deicing salts, agricultural practices, mining operations, and climate change is a major threat to the biodiversity and functioning of freshwater ecosystems. Yet, it is unclear if freshwater ecosystems are protected from salinization by current water quality guidelines. Leveraging an experimental network of land-based and in-lake mesocosms across North America and Europe, we tested how salinization-indicated as elevated chloride (C-) concentration-will affect lake food webs and if two of the lowest Cl- thresholds found globally are sufficient to protect these food webs. Our results indicated that salinization will cause substantial zooplankton mortality at the lowest Cl- thresholds established in Canada (120 mg Cl-/L) and the United States (230 mg Cl-/L) and throughout Europe where Cl- thresholds are generally higher. For instance, at 73% of our study sites, Cl- concentrations that caused a >= 50% reduction in cladoceran abundance were at or below Cl thresholds in Canada, in the United States, and throughout Europe. Similar trends occurred for copepod and rotifer zooplankton. The loss of zooplankton triggered a cascading effect causing an increase in phytoplankton biomass at 47% of study sites. Such changes in lake food webs could alter nutrient cycling and water clarity and trigger declines in fish production. Current Cl- thresholds across North America and Europe clearly do not adequately protect lake food webs. Water quality guidelines should be developed where they do not exist, and there is an urgent need to reassess existing guidelines to protect lake ecosystems from human-induced salinization.Peer reviewe