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
Medicina (Kaunas, Lithuania) [Medicina (Kaunas)] 2022 Jul 19; Vol. 58 (7). Date of Electronic Publication: 2022 Jul 19.
Adult, Computers, Humans, Technology, Transplantation, Autologous methods, Cone-Beam Computed Tomography methods, and Molar, Third surgery
The use of computer-aided rapid prototyping (CARP) models was considered to reduce surgical trauma and improve outcomes when autotransplantation of teeth (ATT) became a viable alternative for dental rehabilitation. However, ATT is considered technique-sensitive due to its series of complicated surgical procedures and unfavorable outcomes in complex cases. This study reported a novel autotransplantation technique of a 28-year-old patient with an unrestorable lower first molar (#36) with double roots. Regardless of a large shape deviation, a lower third molar (#38) with a completely single root formation was used as the donor tooth. ATT was performed with a combined use of virtual simulation, CARP model-based rehearsed surgery, and tooth replica-guided surgery. A 3D virtual model of the donor and recipient site was generated from cone-beam computed tomographic (CBCT) radiographs prior to surgery for direct virtual superimposition simulation and CARP model fabrication. The virtual simulation indicated that it was necessary to retain cervical alveolar bone during the surgical socket preparation, and an intensive surgical rehearsal was performed on the CARP models. The donor tooth replica was used during the procedure to guide precise socket preparation and avoid periodontal ligament injury. Without an additional fitting trial and extra-alveolar storage, the donor tooth settled naturally into the recipient socket within 30 s. The transplanted tooth showed excellent stability and received routine root canal treatment three weeks post-surgery, and the one-year follow-up examination verified the PDL healing outcome and normal functioning. Patient was satisfied with the transplanted tooth. This cutting-edge technology combines virtual simulation, digital surgery planning, and guided surgery implementation to ensure predictable and minimally invasive therapy in complex cases.
Esquirol L, McNeale D, Douglas T, Vickers CE, and Sainsbury F
ACS synthetic biology [ACS Synth Biol] 2022 Jul 26. Date of Electronic Publication: 2022 Jul 26.
Protein cages are attractive as molecular scaffolds for the fundamental study of enzymes and metabolons and for the creation of biocatalytic nanoreactors for in vitro and in vivo use. Virus-like particles (VLPs) such as those derived from the P22 bacteriophage capsid protein make versatile self-assembling protein cages and can be used to encapsulate a broad range of protein cargos. In vivo encapsulation of enzymes within VLPs requires fusion to the coat protein or a scaffold protein. However, the expression level, stability, and activity of cargo proteins can vary upon fusion. Moreover, it has been shown that molecular crowding of enzymes inside VLPs can affect their catalytic properties. Consequently, testing of numerous parameters is required for production of the most efficient nanoreactor for a given cargo enzyme. Here, we present a set of acceptor vectors that provide a quick and efficient way to build, test, and optimize cargo loading inside P22 VLPs. We prototyped the system using a yellow fluorescent protein and then applied it to mevalonate kinases (MKs), a key enzyme class in the industrially important terpene (isoprenoid) synthesis pathway. Different MKs required considerably different approaches to deliver maximal encapsulation as well as optimal kinetic parameters, demonstrating the value of being able to rapidly access a variety of encapsulation strategies. The vector system described here provides an approach to optimize cargo enzyme behavior in bespoke P22 nanoreactors. This will facilitate industrial applications as well as basic research on nanoreactor-cargo behavior.
Lab on a chip [Lab Chip] 2022 Jul 12; Vol. 22 (14), pp. 2682-2694. Date of Electronic Publication: 2022 Jul 12.
Humans, Hydrogels, Microvessels, Neovascularization, Pathologic, Lab-On-A-Chip Devices, and Microtechnology
Reconstruction of 3D vascularized microtissues within microfabricated devices has rapidly developed in biomedical engineering, which can better mimic the tissue microphysiological function and accurately model human diseases in vitro . However, the traditional PDMS-based microfluidic devices suffer from the microfabrication with complex processes and usage limitations of either material properties or microstructure design, which drive the demand for easy processing and more accessible devices with a user-friendly interface. Here, we present an open microfluidic device through a rapid prototyping method by laser cutting in a cost-effective manner with high flexibility and compatibility. This device allows highly efficient and robust hydrogel patterning under a liquid guiding rail by spontaneous capillary action without the need for surface treatment. Different vascularization mechanisms including vasculogenesis and angiogenesis were performed to construct a 3D perfusable microvasculature inside a tissue chamber with various shapes under different microenvironment factors. Furthermore, as a proof-of-concept we have created a vascularized spheroid by placing a monoculture spheroid into the central through-hole of this device, which formed angiogenesis between the spheroid and microvascular network. This open microfluidic device has great potential for mass customization without the need for complex microfabrication equipment in the cleanroom, which can facilitate studies requiring high-throughput and high-content screening.
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.
Bicuspid transplantation, Child, Female, Humans, Maxilla, Transplantation, Autologous, Malocclusion, Angle Class II surgery, and Periodontal Ligament
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.
ACS applied materials & interfaces [ACS Appl Mater Interfaces] 2022 Mar 30; Vol. 14 (12), pp. 14774-14782. Date of Electronic Publication: 2022 Mar 17.
This paper demonstrates laser forming, localized heating with a laser to induce plastic deformation, can self-fold 2D printed circuit boards (PCBs) into 3D structures with electronic function. There are many methods for self-folding but few are compatible with electronic materials. We use a low-cost commercial laser writer to both cut and fold a commercial flexible PCB. Laser settings are tuned to select between cutting and folding with higher power resulting in cutting and lower power resulting in localized heating for folding into 3D shapes. Since the thin copper traces used in commercial PCBs are highly reflective and difficult to directly fold, two approaches are explored for enabling folding: plating with a nickel/gold coating or using a single, high-power laser exposure to oxidize the surface and improve laser absorption. We characterized the physical effect of the exposure on the sample as well as the fold angle as a function of laser passes and demonstrate the ability to lift weights comparable with circuit packages and passive components. This technique can form complex, multifold structures with integrated electronics; as a demonstrator, we fold a commercial board with a common timing circuit. Laser forming to add a third dimension to printed circuit boards is an important technology to enable the rapid prototyping of complex 3D electronics.
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.
Pleșoianu FA, Pleșoianu CE, Bararu Bojan I, Bojan A, Țăruș A, and Tinică G
Bioengineering (Basel, Switzerland) [Bioengineering (Basel)] 2022 May 06; Vol. 9 (5). Date of Electronic Publication: 2022 May 06.
Despite evidence associating the use of mechanical circulatory support (MCS) devices with increased survival and quality of life in patients with advanced heart failure (HF), significant complications and high costs limit their clinical use. We aimed to design an innovative MCS device to address three important needs: low cost, minimally invasive implantation techniques, and low risk of infection. We used mathematical modeling to calculate the pump characteristics to deliver variable flows at different pump diameters, turbomachinery design software CFturbo (2020 R2.4 CFturbo GmbH, Dresden, Germany) to create the conceptual design of the pump, computational fluid dynamics analysis with Solidworks Flow Simulation to in silico test pump performance, Solidworks (Dassault Systèmes SolidWorks Corporation, Waltham, MA, USA) to further refine the design, 3D printing with polycarbonate filament for the initial prototype, and a stereolithography printer (Form 2, Formlabs, Somerville, MA, USA) for the second variant materialization. We present the concept, design, and early prototyping of a low-cost, minimally invasive, fully implantable in a subcutaneous pocket MCS device for long-term use and partial support in patients with advanced HF which unloads the left heart into the arterial system containing a rim-driven, hubless axial-flow pump and the wireless transmission of energy. We describe a low-cost, fully implantable, low-invasive, wireless power transmission left ventricular assist device that has the potential to address patients with advanced HF with higher impact, especially in developing countries. In vitro testing will provide input for further optimization of the device before proceeding to a completely functional prototype that can be implanted in animals.
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.
Human gait is a unique behavioral characteristic that can be used to recognize individuals. Collecting gait information widely by the means of wearable devices and recognizing people by the data has become a topic of research. While most prior studies collected gait information using inertial measurement units, we gather the data from 40 people using insoles, including pressure sensors, and precisely identify the gait phases from the long time series using the pressure data. In terms of recognizing people, there have been a few recent studies on neural network-based approaches for solving the open set gait recognition problem using wearable devices. Typically, these approaches determine decision boundaries in the latent space with a limited number of samples. Motivated by the fact that such methods are sensitive to the values of hyper-parameters, as our first contribution, we propose a new network model that is less sensitive to changes in the values using a new prototyping encoder-decoder network architecture. As our second contribution, to overcome the inherent limitations due to the lack of transparency and interpretability of neural networks, we propose a new module that enables us to analyze which part of the input is relevant to the overall recognition performance using explainable tools such as sensitivity analysis (SA) and layer-wise relevance propagation (LRP).