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Micromixers play an imperative role in chemical and biomedical systems. Designing compact micromixers for laminar flows owning a low Reynolds number is more challenging than flows with higher turbulence. Machine learning models can enable the optimization of the designs and capabilities of microfluidic systems by receiving input from a training library and producing algorithms that can predict the outcomes prior to the fabrication process to minimize development cost and time. Here, an educational interactive microfluidic module is developed to enable the design of compact and efficient micromixers at low Reynolds regimes for Newtonian and non-Newtonian fluids. The optimization of Newtonian fluids designs was based on a machine learning model, which was trained by simulating and calculating the mixing index of 1890 different micromixer designs. This approach utilized a combination of six design parameters and the results as an input data set to a two-layer deep neural network with 100 nodes in each hidden layer. A trained model was achieved with R2 = 0.9543 that can be used to predict the mixing index and find the optimal parameters needed to design micromixers. Non-Newtonian fluid cases were also optimized using 56700 simulated designs with eight varying input parameters, reduced to 1890 designs, and then trained using the same deep neural network used for Newtonian fluids to obtain R2 = 0.9063. The framework was subsequently used as an interactive educational module, demonstrating a well-structured integration of technology-based modules such as using artificial intelligence in the engineering curriculum, which can highly contribute to engineering education. [ABSTRACT FROM AUTHOR]

Microneedle arrays are patches of needles at micro- and nano-scale, which are competent and versatile technologies that have been merged with microfluidic systems to construct more capable devices for biomedical applications, such as drug delivery, wound healing, biosensing, and sampling body fluids. In this paper, several designs and applications are reviewed. In addition, modeling approaches used in microneedle designs for fluid flow and mass transfer are discussed, and the challenges are highlighted. [ABSTRACT FROM AUTHOR]

The application of microneedles (MNs) for minimally invasive biological fluid sampling is rapidly emerging, offering a user-friendly approach with decreased insertion pain and less harm to the tissues compared to conventional needles. Here, a finger-powered microneedle array (MNA) integrated with a microfluidic chip was conceptualized to extract body fluid samples. Actuated by finger pressure, the microfluidic device enables an efficient approach for the user to collect their own body fluids in a simple and fast manner without the requirement for a healthcare worker. The processes for extracting human blood and interstitial fluid (ISF) from the body and the flow across the device, estimating the amount of the extracted fluid, were simulated. The design in this work can be utilized for the minimally invasive personalized medical equipment offering a simple usage procedure. [ABSTRACT FROM AUTHOR]

BACKGROUND: Pistachio fruits suffer from postharvest decay, caused by Aspergillus flavus. This results in aflatoxin B1 (AFB1) accumulation in kernels, which is hazardous for human health due to its carcinogenic activity. In this study, the mechanism used by exogenous β‐aminobutyric acid (BABA) treatment for attenuating Aspergillus decay, minimizing aflatoxin B1 (AFB1) accumulation, and maintaining nutritional quality in fresh‐in‐hull pistachio kernels, infected by A. flavus during storage at 25 °C for 18 days, was investigated. RESULT: Results of an in vivo assay showed that the spore germination and germ tube elongation of A. flavus was repressed by BABA treatment at 7.5 mM. Aspergillus decay accompanied by AFB1 accumulation was also minimized in fresh‐in‐hull pistachio kernels treated with BABA at 7.5 mM and infected by A. flavus. Fresh‐in‐hull pistachio kernels, infected by A. flavus, treated with BABA at 7.5 mM, also exhibited higher phenol and flavonoid accumulation and 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) scavenging capacity accompanied by higher phenylalanine ammonia lyase (PAL) enzyme activity. CONCLUSION: Promoting phenylpropanoid pathway activity with higher PAL enzyme activity in fresh‐in‐hull pistachio kernels treated with BABA may not only reduce Aspergillus decay in kernels by cell wall fortification but also may be favorable for maintaining the kernels' nutritional quality through its effects on ROS scavenging capacity. As oxidative stress, represented by ROS accumulation, is responsible for A. flavus growth and AFB1 accumulation, higher phenol and flavonoid accumulation in fresh‐in‐hull pistachio kernels treated with BABA may be beneficial for attenuating Aspergillus decay and minimizing AFB1 accumulation. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Shot hole disease is one of the most important diseases of stone fruit trees in Iran. The disease is wide spread among orchards of Prunus spp. During spring and summer of 2007, 80 monoconidial isolates of the pathogen were recovered from infected leaves, fruits and twigs of different Prunus spp. in West Azerbaijan, Tehran, Ghazvin and Razavi Khorasan provinces of Iran and were studied taxonomically. Based on morphological and physiological characteristics and growth optimal temperature, all isolates were identified as Wilsonomyces carpophilus. Seedlings of stone fruits (apricot, almond, peach, nectarine, plum, sweet cherry and sour cherry) were used for pathogenicity tests. All seedlings were susceptible to the fungal isolates and showed disease symptoms on twigs, leaves, buds and petioles. Genetic diversity of 28 selected fungal isolates was investigated based on DNA fingerprinting by random amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR), using four random primers. Based on cluster analysis of the PCR results from the four primers, 10 fingerprinting groups (clonal lineages) and 27 haplotypes were identified. Clonal lineages “C”, “D” and “E”, each with six haplotypes formed the biggest clonal lineages, but other clonal lineages (“B”, “F”, “G”, “H”, “I” and “J”) included only one isolate. No correlation was detected among clonal lineages with the location of selected isolates and their host species. A correlation was found between the substrate (fruit, twig or leaf) and clonal lineages, particularly in “C” clonal lineage. The results showed that the fungus population had high genetic diversity which is distributed among the different areas of Iran. [ABSTRACT FROM PUBLISHER]