Two-Dimensional Controlled Syntheses of Polypeptide Molecular Brushes via N-Carboxyanhydride Ring-Opening Polymerization and Ring-Opening Metathesis Polymerization.

Well-defined molecular brushes bearing polypeptides as side chains were prepared by a "grafting through" synthetic strategy with two-dimensional control over the brush molecular architectures. By integrating N-carboxyanhydride ring-opening polymerizations (NCA ROPs) and ring-opening metathesis polymerizations (ROMPs), desirable segment lengths of polypeptide side chains and polynorbornene brush backbones were independently constructed in controlled manners. The N2 flow accelerated NCA ROP was utilized to prepare polypeptide macromonomers with different lengths initiated from a norbornene-based primary amine, and those macromonomers were then polymerized via ROMP. It was found that a mixture of dichloromethane and an ionic liquid were required as the solvent system to allow for construction of molecular brush polymers having densely-grafted peptide chains emanating from a polynorbornene backbone, poly(norbornene-graft-poly(β-benzyl-l-aspartate)) (P(NB-g-PBLA)). Highly efficient postpolymerization modification was achieved by aminolysis of PBLA side chains for facile installment of functional moieties onto the molecular brushes

On network flow problems with convex cost

Minimum cost flow (MCF) problem is a typical example of network flow problems, for which an additional constraint of cost is added to each flow. Conventional MCF problems consider the cost constraints as linear functions of flow. In this paper, we extend the MCF problem to cover cost functions as strictly convex and differentiable, and refer to the problem as convex cost flow problem. To address this problem, we derive the optimality conditions for minimising convex and differentiable cost functions, and devise an algorithm based on the primal-dual algorithm commonly used in linear programming. The proposed algorithm minimises the total cost of flow by incrementing the network flow along augmenting paths of minimum cost. Simulation results are provided to demonstrate the efficacy of the proposed algorithm

Treatment for Landfill Leachate via Physicochemical Approaches: An Overview

Leachate waste consists of various mixtures of organic, inorganic, and heavy metal contaminants, which are responsible for groundwater and surface water contamination. Landfills apply physical, chemical, and biological processes for the treatment of leachate. Most studies on leachate treatment by coagulation and flocculation are based on the selection and performance of natural based biopolymers in comparison with various inorganic metal salts and grafted polymers used for the removal of contaminants. In addition, adsorption processes utilizing non-conventional activated carbons as absorbents are the current emerging focus of the researchers in leachate treatment. These adsorbents are low-in-cost, efficient, and renewable compared to conventional adsorbents. The present paper aimed to evaluate and review the technology utilising various greener approaches in coagulation, flocculation, and adsorption as the physicochemical approaches to leachate treatment. The challenges and future work regarding the development of these green products in the commercial markets were comprehensively evaluated. This work is licensed under a Creative Commons Attribution 4.0 International License

Application of AHP algorithm on power distribution of load shedding in island microgrid

This paper proposes a method of load shedding in a microgrid system operated in an Island Mode, which is disconnected with the main power grid and balanced loss of the electrical power. This proposed method calculates the minimum value of the shed power with reference to renewable energy sources such as wind power generator, solar energy and the ability to control the frequency of the generator to restore the frequency to the allowable range and reduce the amount of load that needs to be shed. Computing the load importance factor (LIF) using AHP algorithm supports to determine the order of which load to be shed. The damaged outcome of load shedding, thus, will be noticeably reduced. The experimental results of this proposed method is demonstrated by simulating on IEEE 16-Bus microgrid system with six power sources

Biodiversity of Tintinnids (Tintinnida) in Khanh Hoa - Binh Thuan waters

Tintinnidsarean important protozoan group in the aquatic food web and had been widely studied in various waters. There are about 1000 known species in the world. However, there have beenvery few taxonomic studies in Vietnam and therefore the number of Tintinnid taxa and their distribution are poorly known. Thepresent study documents 65 tintinnids species belonging to 30 genera and 13 families in samples collected from Khanh Hoa - Binh Thuan waters in 2016 and 2017. There were 17 new taxa records for Vietnam protozoan fauna, raising the number of tintinnids recorded in Vietnam to 125 taxa. Tintinnid assemblages in Khanh Hoa-Binh Thuan waters shared about 17 species with Ha Long Bay, 32 species with Con Co island and 26 species with coastal waters of South Vietnam. Analysis of species diversity shows that the Shannon diversity index H' varied from 1.5 to 2.6. Distribution of species numbers and diversity in the Khanh Hoa - Binh Thuan waters revealed possible combined effects of hydrographical activities (e.g. upwelling), Mekong river influent (e.g. salinity), and food available on tintinnid communities.   Citation: Nguyen Thi Kieu, Phan Tan Luom, Nguyen Tam Vinh, Nguyen Ngoc Lam, Josepth P. Montoya, Doan Nhu Hai, 2017. Biodiversity of Tintinnids (Tintinnida) in Khanh Hoa - Binh Thuan waters. Tap chi Sinh hoc, 39(4): 421-433. DOI: 10.15625/0866-7160/v39n4.11033. *Corresponding author:[email protected] Received 19 September 2017, accepted 12 December 2017

A covalently crosslinked bioink for multi-materials drop-on-demand 3D bioprinting of three-dimensional cell cultures

In vitro three-dimensional (3D) cell models have been accepted to better recapitulate aspects of in vivo organ environment than 2D cell culture. Currently, the production of these complex in vitro 3D cell models with multiple cell types and microenvironments remains challenging and prone to human error. Here we report a versatile bioink comprised of a 4-arm PEG based polymer with distal maleimide derivatives as the main ink component and a bis-thiol species as the activator that crosslinks the polymer to form the hydrogel in less than a second. The rapid gelation makes the polymer system compatible with 3D bioprinting. The ink is combined with a drop-on-demand 3D bioprinting platform consisting of eight independently addressable nozzles and high-throughput printing logic for creating complex 3D cell culture models. The combination of multiple nozzles and fast printing logic enables the rapid preparation of many complex 3D structures comprising multiple hydrogel environments in the one structure in a standard 96-well plate format. The platform compatibility for biological applications was validated using pancreatic ductal adenocarcinoma cancer (PDAC) cells with their phenotypic responses controlled by tuning the hydrogel microenvironment

Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients

Muscle ultrasound has been shown to be a valid and safe imaging modality to assess muscle wasting in critically ill patients in the intensive care unit (ICU). This typically involves manual delineation to measure the rectus femoris cross-sectional area (RFCSA), which is a subjective, time-consuming, and laborious task that requires significant expertise. We aimed to develop and evaluate an AI tool that performs automated recognition and measurement of RFCSA to support non-expert operators in measurement of the RFCSA using muscle ultrasound. Twenty patients were recruited between Feb 2023 and July 2023 and were randomized sequentially to operators using AI (n = 10) or non-AI (n = 10). Muscle loss during ICU stay was similar for both methods: 26 ± 15% for AI and 23 ± 11% for the non-AI, respectively (p = 0.13). In total 59 ultrasound examinations were carried out (30 without AI and 29 with AI). When assisted by our AI tool, the operators showed less variability between measurements with higher intraclass correlation coefficients (ICCs 0.999 95% CI 0.998–0.999 vs. 0.982 95% CI 0.962–0.993) and lower Bland Altman limits of agreement (± 1.9% vs. ± 6.6%) compared to not using the AI tool. The time spent on scans reduced significantly from a median of 19.6 min (IQR 16.9–21.7) to 9.4 min (IQR 7.2–11.7) compared to when using the AI tool (p < 0.001). AI-assisted muscle ultrasound removes the need for manual tracing, increases reproducibility and saves time. This system may aid monitoring muscle size in ICU patients assisting rehabilitation programmes