Keywords Tissue P System; Wireless Sensor Network; Multi-Objective problem; Task Assignment; Decision Support System; Parallel computing; Sustainable computing Abstract The contemporary wireless sensor applications employ a Heterogeneous Wireless Sensor Network (HeWSN) to achieve its multi-objective missions. Modern wireless nodes constituting the HeWSN are more versatile in terms of its capabilities, functionalities, and applications. Assigning tasks in a dynamic HeWSN environment are challenging due to its inherent heterogeneous properties and capabilities. The investigation of existing task assignment algorithms reveals (i) the majority of the existing task assignment algorithms were designed for the homogeneous environment, (ii) most of the nature-inspired algorithms were built for centralized architecture. Scheduling tasks by existing task assignment algorithms lead to underutilization of resources as well as to the rapid depletion of network resources. To this end, a novel, distributed, heterogeneous task assignment algorithm adhering the modern sensors capabilities, functionalities and sensor application to attain sustainable computing is required. Based on the investigation, Tissue P-System inspired task assignment algorithm for the distributed heterogeneous WSN has been modelled. The experimental analyses of the proposed method have been self-evaluated as well as compared with the corresponding recent benchmark algorithms under various conditions and its performance metrics are analysed. Author Affiliation: Karunya Institute of Technology & Sciences, Coimbatore, Tamil Nadu 641 114, India * Corresponding author. Article History: Received 18 November 2019; Revised 11 June 2020; Accepted 21 June 2020 (footnote) Peer review under responsibility of King Saud University. Byline: Titus Issac [firstname.lastname@example.org] (*), Salaja Silas, Elijah Blessing Rajsingh
Lim SW, Choi IS, Lee BN, Ryu J, Park HJ, and Cho JH
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics [Am J Orthod Dentofacial Orthop] 2022 Jul; Vol. 162 (1), pp. 108-121. Date of Electronic Publication: 2022 Mar 11.
Gan R, Cabezas MD, Pan M, Zhang H, Hu G, Clark LG, Jewett MC, and Nicol R
ACS synthetic biology [ACS Synth Biol] 2022 Jun 17; Vol. 11 (6), pp. 2108-2120. Date of Electronic Publication: 2022 May 12.
Gene Library, Protein Biosynthesis, Synthetic Biology, High-Throughput Screening Assays, and Microfluidics methods
Engineering regulatory parts for improved performance in genetic programs has played a pivotal role in the development of the synthetic biology cell programming toolbox. Here, we report the development of a novel high-throughput platform for regulatory part prototyping and analysis that leverages the advantages of engineered DNA libraries, cell-free protein synthesis (CFPS), high-throughput emulsion droplet microfluidics, standard flow sorting adapted to screen droplet reactions, and next-generation sequencing (NGS). With this integrated platform, we screened the activity of millions of genetic parts within hours, followed by NGS retrieval of the improved designs. This in vitro platform is particularly valuable for engineering regulatory parts of nonmodel organisms, where in vivo high-throughput screening methods are not readily available. The platform can be extended to multipart screening of complete genetic programs to optimize yield and stability.
Piadyk Y, Steers B, Mydlarz C, Salman M, Fuentes M, Khan J, Jiang H, Ozbay K, Bello JP, and Silva C
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 May 17; Vol. 22 (10). Date of Electronic Publication: 2022 May 17.
Humans, Intelligence, and Software
Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, they process it and transform into something useful before uploading to the cloud. However, building sensor networks is costly and very time consuming. It is difficult to build upon other people's work and there are only a few open-source solutions for integrating different devices and sensing modalities. We introduce REIP, a Reconfigurable Environmental Intelligence Platform for fast sensor network prototyping. REIP's first and most central tool, implemented in this work, is an open-source software framework, an SDK, with a flexible modular API for data collection and analysis using multiple sensing modalities. REIP is developed with the aim of being user-friendly, device-agnostic, and easily extensible, allowing for fast prototyping of heterogeneous sensor networks. Furthermore, our software framework is implemented in Python to reduce the entrance barrier for future contributions. We demonstrate the potential and versatility of REIP in real world applications, along with performance studies and benchmark REIP SDK against similar systems.
We present a low-cost, accessible, and rapid fabrication process for electrochemical microfluidic sensors. This work leverages the accessibility of consumer-grade electronic craft cutters as the primary tool for patterning of sensor electrodes and microfluidic circuits, while commodity materials such as gold leaf, silver ink pen, double-sided tape, plastic transparency films, and fabric adhesives are used as its base structural materials. The device consists of three layers, the silver reference electrode layer at the top, the PET fluidic circuits in the middle and the gold sensing electrodes at the bottom. Separation of the silver reference electrode from the gold sensing electrodes reduces the possibility of cross-contamination during surface modification. A novel approach in mesoscale patterning of gold leaf electrodes can produce generic designs with dimensions as small as 250 μm. Silver electrodes with dimensions as small as 385 μm were drawn using a plotter and a silver ink pen, and fluid microchannels as small as 300 μm were fabricated using a sandwich of iron-on adhesives and PET. Device layers are then fused together using an office laminator. The integrated microfluidic electrochemical platform has electrode kinetics/performance of Δ Ep = 91.3 mV, Ipa / Ipc = 0.905, characterized by cyclic voltammetry using a standard ferrocyanide redox probe, and this was compared against a commercial screen-printed gold electrode (Δ Ep = 68.9 mV, Ipa / Ipc = 0.984). To validate the performance of the integrated microfluidic electrochemical platform, a catalytic hydrogen peroxide sensor and enzyme-coupled glucose biosensors were developed as demonstrators. Hydrogen peroxide quantitation achieves a limit of detection of 0.713 mM and sensitivity of 78.37 μA mM -1 cm -2 , while glucose has a limit of detection of 0.111 mM and sensitivity of 12.68 μA mM -1 cm -2 . This rapid process allows an iterative design-build-test cycle in under 2 hours. The upfront cost to set up the system is less than USD 520, with each device costing less than USD 0.12, making this manufacturing process suitable for low-resource laboratories or classroom settings.