A Spatial and Operations Modeling Method for Automatic Parking Systems

Automatic or Automated Parking Systems (APSs) would have spatial configurations that depend on both or any of the following factors: 1) its operations and 2) the physical structure design. Without a modeling method, designing and configuring an APS could be relatively challenging and result to special instances of APSs. On the other hand, a modeling method for this purpose would facilitate representing the spaces and operations used by APSs thus aid their design and configuration, and possibly make them adaptive to physical space constraints. This study developed such method for modeling the spaces and operations of APSs allowing their design and configuration to be highly flexible. It involved defining an approach for spatial representations and establishing a model for representing the operations of autonomous parking devices of APSs. The implementation of the spatial representations and operations model into a data structure suitable for computer programming was also described. A number of configuration examples based on those offered by current APS service providersand a few hypothetical APS designs were used to test the applicability of the method. The test was facilitated by simulation software that allowed input of varied APS configurations, input of basic car parking and retrieval operations, and showing results of such operations. Results show that basic operations are correctly executed thus indicating that the model is applicable. Keywords: modeling method, Automatic Parking Systems (APS), autonomous parking devices, spatial model, parking device operations mode

Gains and Challenges of the Barangay Health Worker (BHW) Program During COVID-19 in Selected Cities in the Philippines

Background: The Philippine Barangay Health Worker (BHW) program extends the accessibility of health care services at the community level. BHWs are trained volunteers who perform various health-promoting and health-educating tasks and provide primary health care (PHC) services within their communities. However, the weak implementation of policies meant to protect their welfare, like the BHW Benefits and Incentives Act (Republic Act No. 7883), translates to challenges that impact the sustainability of the BHW program. This qualitative study aimed to explore the BHWs\u27 experiences with RA 7883 and how its implementation shaped their overall role as frontline health workers during the pandemic. Method: The researchers conducted key informant interviews in selected barangays in Biñan, Laguna, and Project 7, Quezon City. The participants included BHWs, community health workers (CHWs), co-workers, supervisors, clients, city program coordinators, and BHW district presidents. The researchers thematically coded the interview transcripts to analyze the data. Results: The experiences of the BHWs showed how the gaps in RA 7883 implementation influenced the different aspects of their position. The BHWs expressed the need for sufficient support through remuneration and training opportunities to strengthen their competence and confidence in accomplishing their extensive tasks. The politicization of BHW through patronage politics also created inefficiencies that were detrimental to achieving the program\u27s goals. Conclusion: The poor implementation of RA 7883 undeniably affected the BHWs\u27 motivation and the full realization of their roles. These inadequacies hindered the program\u27s goal of equitable and accessible health services

Machine Learning Nucleation Collective Variables with Graph Neural Networks

The efficient calculation of nucleation collective variables (CVs) is one of the main limitations to the application of enhanced sampling methods to the investigation of nucleation processes in realistic environments. Here we discuss the development of a graph-based model for the approximation of nucleation CVs that enables orders-of-magnitude gains in computational efficiency in the on-the-fly evaluation of nucleation CVs. By performing simulations on a nucleating colloidal system mimicking a multistep nucleation process from solution, we assess the model's efficiency in both postprocessing and on-the-fly biasing of nucleation trajectories with pulling, umbrella sampling, and metadynamics simulations. Moreover, we probe and discuss the transferability of graph-based models of nucleation CVs across systems using the model of a CV based on sixth-order Steinhardt parameters trained on a colloidal system to drive the nucleation of crystalline copper from its melt. Our approach is general and potentially transferable to more complex systems as well as to different CVs

Tunable Protein and Bacterial Cell Adsorption on Colloidally Templated Superhydrophobic Polythiophene Films

A facile approach for enabling or inhibiting the adsorption of protein and adhesion of bacterial cells on a potential-induced reversibly wettable polythiophene film is described. The superhydrophobic polymeric surface was first prepared by a two-step process that combines the layering of polystyrene (PS) latex particles via a Langmuir–Blodgett (LB)-like technique followed by cyclic voltammetric (CV)–electrodeposition of polythiophene from a terthiophene ester monomer. The polythiophene conducting polymer coating enabled control of the wettability of the surface by simply changing its redox property via potential switching. The influence of morphology on this switching behavior is also described. The wettability in return controls the adsorption of protein and adhesion of bacterial cells. For instance, the undoped polythiophene film, which is superhydrophobic, inhibits the adhesion of fibrinogen proteins and Escherichia coli (E. coli) cells. On the other hand, the doped film, which is hydrophilic, leads to increased attachment of both protein and bacteria. Unlike most synthetic antiwetting surfaces, the as-prepared superhydrophobic coating is nonfluorinated. It maintains its superhydrophobic property at a wide range of pH (pH 1–13) and temperature (below ?10 °C and between 4 and 80 °C). Moreover, the surface demonstrated self-cleaning properties at a sliding angle as low as 3° ± 1. The proposed methodology and material should find application in the preparation of smart or tunable biomaterial surfaces that can be either resistant or susceptible to proteins and bacterial cell adhesion by a simple potential switching

Antimicrobial Applications of Electroactive PVK-SWNT Nanocomposites

The antibacterial properties of a nanocomposite containing an electroactive polymer, polyvinyl-N-carbazole (PVK) (97 wt %), and single-walled carbon nanotubes (SWNT) (3 wt %) was investigated as suspensions in water and as thin film coatings. The toxic effects of four different PVK-SWNT (97:3 wt %) nanocomposite concentrations (1, 0.5, 0.05, and 0.01 mg/mL) containing 0.03, 0.015, 0.0015, and 0.0003 mg/mL of SWNT, respectively, were determined for planktonic cells and biofilms of Escherichia coli (E. coli) and Bacillus subtilis (B. subtilis). The results showed that the nanocomposite PVK-SWNT had antibacterial activity on planktonic cells and biofilms at all concentration levels. Higher bacterial inactivation (94% for E. coli and 90% for B. subtilis) were achieved in planktonic cells at a PVK-SWNT concentration of 1 mg/mL. Atomic force microscopy (AFM) imaging showed significant reduction of biofilm growth on PVK-SWNT coated surfaces. This study established for the first time that the improved dispersion of SWNTs in aqueous solutions in the presence of PVK enhances the antimicrobial effects of SWNTs at very low concentrations. Furthermore, PVK-SWNT can be used as an effective thin film coating material to resist biofilm formation

Permeability of anti-fouling PEGylated surfaces probed by fluorescence correlation spectroscopy

The present work reports on in situ observations of the interaction of organic dye probe molecules and dye-labeled protein with different poly(ethylene glycol) (PEG) architectures (linear, dendron, and bottle brush). Fluorescence correlation spectroscopy (FCS) and single molecule event analysis were used to examine the nature and extent of probe朠EG interactions. The data support a sieve-like model in which size-exclusion principles determine the extent of probe朠EG interactions. Small probes are trapped by more dense PEG architectures and large probes interact more with less dense PEG surfaces. These results, and the tunable pore structure of the PEG dendrons employed in this work, suggest the viability of electrochemically-active materials for tunable surfaces