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Disaster preparedness of local governments in Panay Island, Philippines
Disaster preparedness plans reduce future damages, but may lack testing to assess their effectiveness in operation. This study used the state-designed Local Government Unit Disaster Preparedness Journal: Checklist of Minimum Actions for Mayors in assessing the readiness to natural hazards of 92 profiled municipalities in central Philippines inhabited by 2.4 million people. Anchored on the Hyogo Framework for Action 2005–2015, it assessed their preparedness in 4 criteria—systems and structures, policies and plans, building competencies, and equipment and supplies. Data were analyzed using statistical package for social sciences, frequency count, percentage, and weighted mean. The local governments were found highly vulnerable to tropical cyclone and flood while vulnerable to earthquake, drought, and landslide. They were partially prepared regardless of profile, but the coastal, middle-earning, most populated, having the least number of villages, and middle-sized had higher levels of preparedness. Those highly vulnerable to earthquake and forest fire were prepared, yet only partially prepared to flood, storm surge, drought, tropical cyclone, tornado, tsunami and landslide. The diverse attitude of stakeholders, insufficient manpower, and poor database management were the major problems encountered in executing countermeasures. Appointing full-time disaster managers, developing a disaster information management system, massive information drive, organizing village-based volunteers, integrating disaster management into formal education, and mandatory trainings for officials, preparing for a possible major volcanic eruption and crafting a comprehensive plan against emerging emergencies like the COVID-19 pandemic may lead to a 360° preparedness.
Journal Article
Isolation of circulating tumor cells using a microvortex-generating herringbone-chip
Rare circulating tumor cells (CTCs) present in the bloodstream of patients with cancer provide a potentially accessible source for detection, characterization, and monitoring of nonhematological cancers. We previously demonstrated the effectiveness of a microfluidic device, the CTC-Chip, in capturing these epithelial cell adhesion molecule (EpCAM)-expressing cells using antibody-coated microposts. Here, we describe a high-throughput microfluidic mixing device, the herringbone-chip, or “HB-Chip,” which provides an enhanced platform for CTC isolation. The HB-Chip design applies passive mixing of blood cells through the generation of microvortices to significantly increase the number of interactions between target CTCs and the antibody-coated chip surface. Efficient cell capture was validated using defined numbers of cancer cells spiked into control blood, and clinical utility was demonstrated in specimens from patients with prostate cancer. CTCs were detected in 14 of 15 (93%) patients with metastatic disease (median = 63 CTCs/mL, mean = 386 ± 238 CTCs/mL), and the tumor-specific TMPRSS2-ERG translocation was readily identified following RNA isolation and RT-PCR analysis. The use of transparent materials allowed for imaging of the captured CTCs using standard clinical histopathological stains, in addition to immunofluorescence-conjugated antibodies. In a subset of patient samples, the low shear design of the HB-Chip revealed microclusters of CTCs, previously unappreciated tumor cell aggregates that may contribute to the hematogenous dissemination of cancer.
Journal Article
Dynamic Time Warping as Elementary Effects Metric for Morris-Based Global Sensitivity Analysis of High-Dimension Dynamical Models
This work focused on demonstrating the use of dynamic time warping (DTW) as a metric for the elementary effects computation in Morris-based global sensitivity analysis (GSA) of model parameters in multivariate dynamical systems. One of the challenges of GSA on multivariate time-dependent dynamics is the modeling of parameter perturbation effects propagated to all model outputs while capturing time-dependent patterns. The study establishes and demonstrates the use of DTW as a metric of elementary effects across the time domain and the multivariate output domain, which are all aggregated together via the DTW cost function into a single metric value. Unlike the commonly studied coefficient-based functional approximation and covariance decomposition methods, this new DTW-based Morris GSA algorithm implements curve alignment via dynamic programing for cost computation in every parameter perturbation trajectory, which captures the essence of “elementary effect” in the original Morris formulation. This new algorithm eliminates approximations and assumptions about the model outputs while achieving the objective of capturing perturbations across time and the array of model outputs. The technique was demonstrated using an ordinary differential equation (ODE) system of mixed-order adsorption kinetics, Monod-type microbial kinetics, and the Lorenz attractor for chaotic solutions. DTW as a Morris-based GSA metric enables the modeling of parameter sensitivity effects on the entire array of model output variables evolving in the time domain, resulting in parameter rankings attributed to the entire model dynamics.
Journal Article
Formulation of a Simulated Wastewater Influent Composition for Use in the Research of Technologies for Managing Wastewaters Generated during Manned Long-Term Space Exploration and Other Similar Situations—Literature-Based Composition Development
The prospect of humans inhabiting planetary bodies is gaining interest among research and development communities, with the moon being considered as a transitory base camp and Mars the next planet humans will inhabit. NASA’s Mission to Mars program is set to have humans inhabiting Mars within on-planet space camps by the Year 2030, which has tremendously increased research and development for space exploration—including research oriented toward human life support in long-term planetary lodging camps. The sustenance of human life on Mars will not be trivial due to the unavailability of an appropriate atmosphere and usable water. This situation requires a self-sustaining human life support system that can provide the basic needs such are breathable air, potable water, food, and energy. The feasibility of sending a payload with resources adequate to support long-term human inhabitation is not reasonable, which means every resource within a Mars space camp is valuable, including human-produced wastes. A biorefinery system that treats wastewater and can also produce valuable products such as oxygen, food, and energy offers a form of circular utilization of valuable resources. To conduct research for such systems requires a wastewater influent that is representative of the wastewater to be generated by the space crew within this isolated, confined environment, which is different from what is generated on Earth due to limited variability in diet, human activity, and lifestyle in this confined area. Collection of actual wastewater influent from an isolated environment supporting humans is challenging. Additionally, to ensure a safe working environment in the laboratory and avoid the imposed threat of handling actual human feces, the proposed synthetic, non-human feces containing wastewater influent formulation offers an easy-to-produce and safer-to-handle option. This paper reviews several synthetic wastewater compositions that have been formulated for space exploration purposes. None of the formulations were found to be realistic nor adequate for a space-camp-type scenario. Thus, the formulation of a synthetic wastewater for simulating a wastewater influent from a human space-based camp is proposed in this paper. In addition, the physical, chemical, and biodegradation characteristics of the final formulation designed are presented to illustrate the value of the proposed influent formulation.
Journal Article
A spatial atlas of the complement system uncovers unique expression patterns in postnatal brain development in mice
Recent studies have found non-immunological roles of the classical complement pathway (CP) in brain development and its involvement in neuropsychiatric and neurodegenerative diseases. However, multiple complement activation pathways exist beyond the CP, but their expression and function remain poorly understood in the brain. Using MERFISH, we constructed a comprehensive spatial transcriptomic atlas of the complement system in mouse brains from late embryonic stage to adulthood. Here we show that most complement genes are expressed locally with a remarkable degree of cellular, spatial, and temporal heterogeneity and that complement regulatory mechanisms are distinct from the periphery. Beyond confirming the known expression of the CP, our measurements reveal endogenous expression of the alternative pathway (AP), notably the AP activator Masp3 in immature brains. Masp3 deficiency alters molecular structure of the brain and causes working spatial memory defects, indicating a role of Masp3 in brain maturation, potentially via modulation of AP activity.
The complement cascade is increasingly recognized in the brain. Here, with MERFISH, the authors showed developmentally regulated brain endogenous expression of complement genes and a potential role of the alternative pathway in brain development.
Journal Article
A Methodology for Global Sensitivity Analysis of Activated Sludge Models
The main objective of this study was to demonstrate a computational approach of global sensitivity analysis (GSA) integrated with functional principal component analysis (fPCA) for activated sludge models through aggregation of time-dependent model response patterns into time-independent coefficients of functional principal components (PCs). This proposed approach addresses the main issue of time-varying character of GSA indices when calculated solely on the time-dependent model outputs. The GSA-fPCA methodology was implemented using the rigorous model Activated Sludge Model No. 3 (ASM3) as case study. The approach transforms the time-dependent model outputs into functional PCs prior to calculation of GSA indices to remove the time-varying character of the calculated GSA indices. This work focused on the evaluation of the following key computational factors that may significantly influence the performance of the GSA-fPCA methodology: (a) model parameter sampling range, (b) model simulation period, (c) basis functions system, and (d) state of the system being modeled—batch or continuous activated sludge process. Results show that first few functional PCs capture up to 100% of the curve patterns in the time-dependent model outputs. The sensitivity indices calculated from the PC scores via Morris’ GSA technique elucidated parameter sensitivity patterns inherent to the complex mathematical structure of ASM3.
Journal Article
Soft Actor-Critic Reinforcement Learning Improves Distillation Column Internals Design Optimization
Amid the advancements in computer-based chemical process modeling and simulation packages used in commercial applications aimed at accelerating chemical process design and analysis, there are still certain tasks in design optimization, such as distillation column internals design, that become bottlenecks due to inherent limitations in such software packages. This work demonstrates the use of soft actor-critic (SAC) reinforcement learning (RL) in automating the task of determining the optimal design of trayed multistage distillation columns. The design environment was created using the AspenPlus® software (version 12, Aspen Technology Inc., Bedford, Massachusetts, USA) with its RadFrac module for the required rigorous modeling of the column internals. The RL computational work was achieved by developing a Python package that allows interfacing with AspenPlus® and by implementing in OpenAI’s Gymnasium module (version 1.0.0, OpenAI Inc., San Francisco, California, USA) the learning space for the state and action variables. The results evidently show that (1) SAC RL works as an automation approach for the design of distillation column internals, (2) the reward scheme in the SAC model significantly affects SAC performance, (3) column diameter is a significant constraint in achieving column internals design specifications in flooding, and (4) SAC hyperparameters have varying effects on SAC performance. SAC RL can be implemented as a one-shot learning model that can significantly improve the design of multistage distillation column internals by automating the optimization process.
Journal Article
A Techno-Economic Analysis of Integrating an Urban Biorefinery Process Within a Wastewater Treatment Plant to Produce Sustainable Wood Adhesives
Societies are aiming to have a higher ecological consciousness in wastewater treatment operations and achieve a more sustainable future. With this said, global demands for larger quantities of resources and the consequent waste generated will inevitably lead to the exhaustion of current municipal wastewater treatment works. The utilization of biosolids (particularly microbial proteins) from wastewater treatment operations could generate a sustainable bio-adhesive for the wood industry, reduce carbon footprint, mitigate health concerns related to the use of carcinogenic components, and support a more circular economic option for wastewater treatment. A techno-economic analysis for three 10 MGD wastewater treatment operations producing roughly 11,300 dry pounds of biosolids per day, in conjunction with co-feedstock defatted soy flour protein at varying ratios (i.e., 0%, 15%, and 50% wet weight), was conducted. Aspen Capital Cost Estimator V12 was used to design and estimate installed equipment additions for wastewater treatment plant integration into an urban biorefinery process. Due to the mechanical attributes and market competition, the chosen selling prices of each adhesive per pound were set for analysis as USD 0.75 for Plant Option P1, USD 0.85 for Plant Option P2, and USD 1.00 for Plant Option P3. Over a 20-year life, each plant option demonstrated economic viability with high NPVs of USD 107.9M, USD 178.7M, and USD 502.2M and internal rates of return (IRRs) of 24.0%, 29.0%, and 44.2% respectively. The options examined have low production costs of USD 0.14 and USD 0.19 per pound, minimum selling prices of USD 0.42–USD 0.51 per pound, resulting in between 2- and 4-year payback periods. Sensitivity analysis shows the effects biosolid production fluctuations, raw material market price, and adhesive selling price have on economics. The results proved profitable even with large variations in the feedstock and raw material prices, requiring low market selling prices to reach the hurdle rate of examination. This technology is economically enticing, and the positive environmental impact of waste utilization encourages further development and analysis of the bio-adhesive process.
Journal Article
Torrefaction of Pine Using a Pilot-Scale Rotary Reactor: Experimentation, Kinetics, and Process Simulation Using Aspen Plus
Biomass is an excellent sustainable carbon neutral energy source, however its use as a coal/petroleum coke substitute in thermal applications poses several challenges. Several inherent properties of biomass including higher heating value (HHV), bulk density, and its hydrophilic and fibrous nature, all contribute to challenges for it to be used as a solid fuel. Torrefaction or mild pyrolysis is a well-accepted thermal pretreatment technology that solves most of the above-mentioned challenges and results in a product with superior coal-like properties. Torrefaction involves the heating of biomass to moderate temperatures typically between 200 °C and 300 °C in a non-oxidizing atmosphere. This study focused on evaluating the influence of torrefaction operating temperature (204–304 °C) and residence time (10–40 min) on properties of pine. Tests were performed on a continuous 0.3 ton/day indirectly heated rotary reactor. The influence of torrefaction operational conditions on pine was evaluated in terms of the composition of torrefied solids, mass yield, energy yield, and HHV using a simulated model developed in Aspen Plus™ software. A kinetic model was established based on the experimental data generated. An increase in torrefaction severity (increasing temperature and residence time) resulted in an increase in carbon content, accompanied with a decrease in oxygen and hydrogen. Results from the simulated model suggest that the solid and energy yields decreased with an increase in temperature and residence time. Solid yield varied from 80% at 204 °C to 68% at 304 °C, and energy yield varied from 99% at 204 °C to 70% at 304 °C, respectively. On the other hand, HHV improved from 22.8 to 25.1 MJ/kg with an increase in temperature at 20 min residence time. Over the range of 10 to 40 min residence time at 260 °C, solid and energy yields varied from 77% to 59% and 79% to 63%, respectively; however the HHV increased by only 3%. Solid yield, energy yield, and HHV simulated data were within the 5% error margin when compared to the experimental data. Validation of the simulation parameters was achieved by the conformance of the experimental and simulation data obtained under the same testing conditions. These simulated parameters can be utilized to study other operating conditions fundamental for the commercialization of these processes. Desirable torrefaction temperature to achieve the highest solid fuel yield can be determined using the energy yield and mass loss data.
Journal Article