End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around the globe. Nonetheless, this is not eminently efficacious considering human inspection of medical images can yield a high false positive rate. Ineffective and inefficient diagnosis is a crucial reason for such a high mortality rate for this malady. However, the conspicuous advancements in deep learning and artificial intelligence have stimulated the development of exceedingly precise diagnosis systems. The development and performance of these systems rely prominently on the data that is used to train these systems. A standard problem witnessed in publicly available medical image datasets is the severe imbalance of data between different classes. This grave imbalance of data can make a deep learning model biased towards the dominant class and unable to generalize. This study aims to present an end-to-end convolutional neural network that can accurately differentiate lung nodules from non-nodules and reduce the false positive rate to a bare minimum. To tackle the problem of data imbalance, we oversampled the data by transforming available images in the minority class. The average false positive rate in the proposed method is a mere 1.5 percent. However, the average false negative rate is 31.76 percent. The proposed neural network has 68.66 percent sensitivity and 98.42 percent specificity.     

WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Microalgae-Based Biohybrid Microrobot for Accelerated Diabetic Wound Healing

A variety of wound healing platforms have been proposed to alleviate the hypoxic condition and/or to modulate the immune responses for the treatment of chronic wounds in diabetes. However, these platforms with the passive diffusion of therapeutic agents through the blood clot result in the relatively low delivery efficiency into the deep wound site. Here, a microalgae-based biohybrid microrobot for accelerated diabetic wound healing is developed. The biohybrid microrobot autonomously moves at velocity of 33.3 µm s⁻¹ and generates oxygen for the alleviation of hypoxic condition. In addition, the microrobot efficiently bound with inflammatory chemokines of interleukin-8 (IL-8) and monocyte chemoattractant protein-1 (MCP-1) for modulating the immune responses. The enhanced penetration of microrobot is corroborated by measuring fibrin clots in biomimetic wound using microfluidic devices and the enhanced retention of microrobot is confirmed in the real wounded mouse skin tissue. After deposition on the chronic wound in diabetic mice without wound dressing, the wounds treated with microrobots are completely healed after 9 days with the significant decrease of inflammatory cytokines below 31% of the control level and the upregulated angiogenesis above 20 times of CD31⁺ cells. These results confirm the feasibility of microrobots as a next-generation platform for diabetic wound healing.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Localization of atrial natriuretic peptide receptors in the rat tongue and hard palate

The effect of a naturally occurring plant phenolic constituent (the acylphloroglucinol derivative, jensenone, derived from Eucalyptus jensenii) on the food intake of two folivorous marsupials, the common ringtail (Pseudocheirus peregrinus) and the common brushtail possum (Trichosurus vulpecula) was studied. When fed diets containing varying concentrations of jensenone, both species regulated their intake of jensenone so as not to exceed a ceiling intake. This ceiling was about twice as high for common ringtails as for common brushtails from northern Australia. Southern populations of common ringtails showed greatly reduced capacities to tolerate jensenone. When common brushtails were injected (0.5 mg.kg-0.75 body mass) with ondansetron (a selective antagonist of serotonin 5HT3 receptors), they ate significantly more jensenone than animals injected with physiological saline. The same pattern was observed when common ringtails were fed diets containing both jensenone and ondansetron (0.0035 mg.g-1 wet mass of diet). Ondansetron injection had no effect on food intake when the food did not contain jensenone while the addition of higher doses of ondansetron to diets of common ringtails very slightly reduced food intakes of a non-jensenone diet. When common brushtails were given 50 mg of jensenone by gastric lavage, their average subsequent intake of dietary jensenone matched the difference between the daily threshold and the dose given, although the response of individuals was highly variable. Lavage with water alone had no effect on subsequent jensenone intake compared with the pre-dose period. We interpret these results as evidence that the antifeedant effects of jensenone and related compounds are partly mediated by serotonin action on 5HT3 receptors most likely via "nausea" to condition a food aversion.     

NRP/B, a novel nuclear matrix protein, associates with p110(RB) and is involved in neuronal differentiation

The nuclear matrix is defined as the insoluble framework of the nucleus and has been implicated in the regulation of gene expression, the cell cycle, and nuclear structural integrity via linkage to intermediate filaments of the cytoskeleton. We have discovered a novel nuclear matrix protein, NRP/B (nuclear restricted protein/brain), which contains two major structural elements: a BTB domain-like structure in the predicted NH2 terminus, and a "kelch motif" in the predicted COOH-terminal domain. NRP/B mRNA (5.5 kb) is predominantly expressed in human fetal and adult brain with minor expression in kidney and pancreas. During mouse embryogenesis, NRP/B mRNA expression is upregulated in the nervous system. The NRP/B protein is expressed in rat primary hippocampal neurons, but not in primary astrocytes. NRP/B expression was upregulated during the differentiation of murine Neuro 2A and human SH-SY5Y neuroblastoma cells. Overexpression of NRP/B in these cells augmented neuronal process formation. Treatment with antisense NRP/B oligodeoxynucleotides inhibited the neurite development of rat primary hippocampal neurons as well as the neuronal process formation during neuronal differentiation of PC-12 cells. Since the hypophosphorylated form of retinoblastoma protein (p110(RB)) is found to be associated with the nuclear matrix and overexpression of p110(RB) induces neuronal differentiation, we investigated whether NRP/B is associated with p110(RB). Both in vivo and in vitro experiments demonstrate that NRP/B can be phosphorylated and can bind to the functionally active hypophosphorylated form of the p110(RB) during neuronal differentiation of SH-SY5Y neuroblastoma cells induced by retinoic acid. Our studies indicate that NRP/B is a novel nuclear matrix protein, specifically expressed in primary neurons, that interacts with p110(RB) and participates in the regulation of neuronal process formation.     

Homology and functional similarity of an hrp-linked pathogenicity locus, dspEF, of Erwinia amylovora and the avirulence locus avrE of Pseudomonas syringae pathovar tomato

The "disease-specific" (dsp) region next to the hrp gene cluster of Erwinia amylovora is required for pathogenicity but not for elicitation of the hypersensitive reaction. A 6.6-kb apparent operon, dspEF, was found responsible for this phenotype. The operon contains genes dspE and dspF and is positively regulated by hrpL. A BLAST search revealed similarity in the dspE gene to a partial sequence of the avrE locus of Pseudomonas syringae pathovar tomato. The entire avrE locus was sequenced. Homologs of dspE and dspF were found in juxtaposed operons and were designated avrE and avrF. Introduced on a plasmid, the dspEF locus rendered P. syringae pv. glycinea race 4 avirulent on soybean. An E. amylovora dspE mutant, however, elicited a hypersensitive reaction in soybean. The avrE locus in trans restored pathogenicity to dspE strains of E. amylovora, although restored strains were low in virulence. DspE and AvrE are large (198 kDa and 195 kDa) and hydrophilic. DspF and AvrF are small (16 kDa and 14 kDa) and acidic with predicted amphipathic alpha helices in their C termini; they resemble chaperones for virulence factors secreted by type III secretion systems of animal pathogens.     

Absorption effect in the calculation of a second-order nonlinear coefficient from the data of a maker fringe experiment

The effect of light absorption by sample in the analysis of Makerfringe data for estimating a second-order nonlinear coefficient hasbeen studied experimentally. Two theories, one by Jerphagnon andKurtz that neglects the absorption effect and one by Herman and Haydenthat takes into account the absorption effect, were compared with theexperimental results. It was found that Jerphagnon and Kurtz'sformula was unable to predict correctly not only the magnitude but alsothe incident angle dependence or the sample thickness dependence of thesecond harmonic signal generated by the sample with strong absorption, whereas the theory by Herman and Hayden was able to make thosepredictions fairly well. It was also found that the error in theestimated nonlinear coefficient when one uses Jerphagnon and Kurtz'sformula could be as large as 2-4 times the true value, depending onsample thickness.     

Simple model for the observed plasmon conical radiation interference patterns in a kretschmann configuration

In two previous papers we presented experimental results of measurements with a scanning plasmon optical microscope constructed in the Kretschmann configuration. The angular distribution of the conical radiation from the scanning tip was measured, and the multiple-scattering images of simple surface irregularities were detected. We make a simple model of the multiple-scattering images and compare it with our data, deriving excellent results.