Prostate Segmentation in MRI Images using Transfer Learning based Mask RCNN.

INTRODUCTION: The second highest cause of death among males is Prostate Cancer (PCa) in America. Over the globe, it's the usual case in men, and the annual PCa ratio is very surprising. Identical to other prognosis and diagnostic medical systems, deep learning-based automated recognition and detection systems (i.e., Computer Aided Detection (CAD) systems) have gained enormous attention in PCA. METHODS: These paradigms have attained promising results with a high segmentation, detection, and classification accuracy ratio. Numerous researchers claimed efficient results from deep learning-based approaches compared to other ordinary systems that utilized pathological samples. RESULTS: This research is intended to perform prostate segmentation using transfer learning-based Mask R-CNN, which is consequently helpful in prostate cancer detection. CONCLUSION: Lastly, limitations in current work, research findings, and prospects have been discussed.

Learned-SBL-GAMP based hybrid precoders/combiners in millimeter wave massive MIMO systems.

In Millimeter-Wave (mm-Wave) massive Multiple-Input Multiple-Output (MIMO) systems, hybrid precoders/combiners must be designed to improve antenna gain and reduce hardware complexity. Sparse Bayesian learning via Expectation Maximization (SBL-EM) algorithm is not practically feasible for high signal dimensions because estimating sparse signals and designing optimal hybrid precoders/combiners using SBL-EM still provide high computational complexity for higher signal dimensions. To overcome the issues of high computational complexity along with making it suitable for larger data sets, in this paper, we propose Learned-Sparse Bayesian Learning with Generalized Approximate Message Passing algorithm (L-SBL-GAMP) algorithm for designing optimal hybrid precoders/combiners suitable for mmWave Massive MIMO systems. The L-SBL-GAMP algorithm is an extension of the SBL-GAMP algorithm that incorporates a Deep Neural Network (DNN) to improve the system performance. Based on the nature of the training data, the L-SBL-GAMP can design the optimal Hybrid precoders/combiners, which enhances the spectral efficiency of mmWave massive MIMO systems. The proposed L-SBL-GAMP algorithm reduces the iterations, training overhead, and computational complexity compared to the SBL-EM algorithm. The simulation results unveil that the proposed L-SBL-GAMP provides higher achievable rates, better accuracy, and low computational complexity compared to the existing algorithm, such as Orthogonal Matching Pursuit (OMP), Simultaneous Orthogonal Matching Pursuit (SOMP), SBL-EM and SBL-GAMP for mmWave massive MIMO architectures.

A Novel Decentralized Blockchain Architecture for the Preservation of Privacy and Data Security against Cyberattacks in Healthcare.

Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.

Microfluidic device for the Separation of non-metastatic (MCF-7) and non-tumor (MCF-10A) breast cancer cells using AC Dielectrophoresis.

Dielectrophoretic devices are capable of the detection and manipulation of cancer cells in a label-free, cost-effective, robust, and accurate manner using the principle of the polarization of the cancer cells in the sample volume by applying an external electric field. This article demonstrates how a microfluidic platform can be utilized for high-throughput continuous sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using hydrodynamic dielectrophoresis (HDEP) from the cell mixture. By generating an electric field between two electrodes placed side-by-side with a micron-sized gap between them in an HDEP microfluidic chip, non-tumor breast epithelial cells (MCF-10A) can be pushed away, exhibiting negative DEP inside the main channel, while the non-metastatic breast cancer cells follow their course unaffected when suspended in cell medium due to having conductivity higher than the membrane conductivity. To demonstrate this concept, simulations were performed for different values of medium conductivity, and the sorting of cells was studied. A parametric study was carried out, and a suitable cell mixture conductivity was found to be 0.4 S/m. By keeping the medium conductivity fixed, an adequate AC frequency of 0.8 MHz was established, giving maximum sorting efficiency, by varying the electric field frequency. Using the demonstrated method, after choosing the appropriate cell mixture suspension medium conductivity and frequency of the applied AC, maximum sorting efficiency can be achieved.

An AI-enabled lightweight data fusion and load optimization approach for Internet of Things.

In the densely populated Internet of Things (IoT) applications, sensing range of the nodes might overlap frequently. In these applications, the nodes gather highly correlated and redundant data in their vicinity. Processing these data depletes the energy of nodes and their upstream transmission towards remote datacentres, in the fog infrastructure, may result in an unbalanced load at the network gateways and edge servers. Due to heterogeneity of edge servers, few of them might be overwhelmed while others may remain less-utilized. As a result, time-critical and delay-sensitive applications may experience excessive delays, packet loss, and degradation in their Quality of Service (QoS). To ensure QoS of IoT applications, in this paper, we eliminate correlation in the gathered data via a lightweight data fusion approach. The buffer of each node is partitioned into strata that broadcast only non-correlated data to edge servers via the network gateways. Furthermore, we propose a dynamic service migration technique to reconfigure the load across various edge servers. We assume this as an optimization problem and use two meta-heuristic algorithms, along with a migration approach, to maintain an optimal Gateway-Edge configuration in the network. These algorithms monitor the load at each server, and once it surpasses a threshold value (which is dynamically computed with a simple machine learning method), an exhaustive search is performed for an optimal and balanced periodic reconfiguration. The experimental results of our approach justify its efficiency for large-scale and densely populated IoT applications.

Chloramphenicol enhances Photosystem II photodamage in intact cells of the cyanobacterium Synechocystis PCC 6803.

The effect of chloramphenicol, an often used protein synthesis inhibitor, in photosynthetic systems was studied on the rate of Photosystem II (PSII) photodamage in the cyanobacterium Synechocystis PCC 6803. Light-induced loss of PSII activity was compared in the presence of chloramphenicol and another protein synthesis inhibitor, lincomycin, by measuring the rate of oxygen evolution in Synechocystis 6803 cells. Our data show that the rate of PSII photodamage was significantly enhanced by chloramphenicol, at the usually applied 200 µg mL-1 concentration, relative to that obtained in the presence of lincomycin. Chloramphenicol-induced enhancement of photodamage has been observed earlier in isolated PSII membrane particles, and has been assigned to the damaging effect of chloramphenicol-mediated superoxide production (Rehman et al. 2016, Front Plant Sci 7:479). This effect points to the involvement of superoxide as damaging agent in the presence of chloramphenicol also in Synechocystis cells. The chloramphenicol-induced enhancement of photodamage was observed not only in wild-type Synechocystis 6803, which contains both Photosystem I (PSI) and PSII, but also in a PSI-less mutant which contains only PSII. Importantly, the rate of PSII photodamage was also enhanced by the absence of PSI when compared to that in the wild-type strain under all conditions studied here, i.e., without addition and in the presence of protein synthesis inhibitors. We conclude that chloramphenicol enhances photodamage mostly by its interaction with PSII, leading probably to superoxide production. The presence of PSI is also an important regulatory factor of PSII photodamage most likely via decreasing excitation pressure on PSII.

Consensus tracking of nonlinear multi-agent systems under input saturation with applications: A sector-based approach.

This paper focuses on the consensus tracking control of nonlinear multi-agent systems by utilizing the quadratic inner-bounded (QIB) and the one-sided Lipschitz (OSL) conditions in the presence of input saturation constraint under a directed communication topology. A novel sector constraint for the saturation function to formulate consensus control of nonlinear systems under saturating inputs is derived. This sector condition is applied to develop a leader-following consensus of nonlinear agents. A local treatment of the consensus control, ensuring a guaranteed region of stability in the presence of input constraints is provided herein. A computationally simple convex routine-based approach is attained for extraction of the coupling weight and gain of the relative state feedback-based consensus protocol along with the enlargement of the region of stability. Unlike the conventional schemes, the proposed approach can deal with OSL nonlinear agents, effectively employs the information of communication topology in the sector condition, and can be applied to both linear and nonlinear regions of actuators. Moreover, a useful consensus approach for the Lipschitz nonlinear agents is obtained as a particular scenario of the resultant method. Numerical examples to demonstrate the applications and effectiveness of the proposed approach for the input-constrained nonlinear mobile and robotic agents are provided.

Detection of Singlet Oxygen Formation inside Photoactive Biohybrid Composite Material.

Photosynthetic reaction center proteins (RCs) are the most efficient light energy converter systems in nature. The first steps of the primary charge separation in photosynthesis take place in these proteins. Due to their unique properties, combining RCs with nano-structures promising applications can be predicted in optoelectronic systems. In the present work RCs purified from Rhodobacter sphaeroides purple bacteria were immobilized on multiwalled carbon nanotubes (CNTs). Carboxyl-and amine-functionalised CNTs were used, so different binding procedures, physical sorption and chemical sorption as well, could be applied as immobilization techniques. Light-induced singlet oxygen production was measured in the prepared photoactive biocomposites in water-based suspension by histidine mediated chemical trapping. Carbon nanotubes were applied under different conditions in order to understand their role in the equilibration of singlet oxygen concentration in the suspension. CNTs acted as effective quenchers of ¹O2 either by physical (resonance) energy transfer or by chemical (oxidation) reaction and their efficiency showed dependence on the diffusion distance of ¹O2.

The Cyanobacterial Photoactive Orange Carotenoid Protein Is an Excellent Singlet Oxygen Quencher.

Cyanobacteria have developed a photoprotective mechanism that decreases the energy arriving at the photosynthetic reaction centers under high-light conditions. The photoactive orange carotenoid protein (OCP) is essential in this mechanism as a light sensor and energy quencher. When OCP is photoactivated by strong blue-green light, it is able to dissipate excess energy as heat by interacting with phycobilisomes. As a consequence, charge separation and recombination leading to the formation of singlet oxygen diminishes. Here, we demonstrate that OCP has another essential role. We observed that OCP also protects Synechocystis cells from strong orange-red light, a condition in which OCP is not photoactivated. We first showed that this photoprotection is related to a decrease of singlet oxygen concentration due to OCP action. Then, we demonstrated that, in vitro, OCP is a very good singlet oxygen quencher. By contrast, another carotenoid protein having a high similarity with the N-terminal domain of OCP is not more efficient as a singlet oxygen quencher than a protein without carotenoid. Although OCP is a soluble protein, it is able to quench the singlet oxygen generated in the thylakoid membranes. Thus, OCP has dual and complementary photoprotective functions as an energy quencher and a singlet oxygen quencher.

Inhibition of photosynthetic CO2 fixation in the coral Pocillopora damicornis and its relationship to thermal bleaching.

Two inhibitors of the Calvin-Benson cycle [glycolaldehyde (GA) and potassium cyanide (KCN)] were used in cultured Symbiodinium cells and in nubbins of the coral Pocillopora damicornis to test the hypothesis that inhibition of the Calvin-Benson cycle triggers coral bleaching. Inhibitor concentration range-finding trials aimed to determine the appropriate concentration to generate inhibition of the Calvin-Benson cycle, but avoid other metabolic impacts to the symbiont and the animal host. Both 3 mmol l(-1) GA and 20 µmol l(-1) KCN caused minimal inhibition of host respiration, but did induce photosynthetic impairment, measured by a loss of photosystem II function and oxygen production. GA did not affect the severity of bleaching, nor induce bleaching in the absence of thermal stress, suggesting inhibition of the Calvin-Benson cycle by GA does not initiate bleaching in P. damicornis. In contrast, KCN did activate a bleaching response through symbiont expulsion, which occurred in the presence and absence of thermal stress. While KCN is an inhibitor of the Calvin-Benson cycle, it also promotes reactive oxygen species formation, and it is likely that this was the principal agent in the coral bleaching process. These findings do not support the hypothesis that temperature-induced inhibition of the Calvin-Benson cycle alone induces coral bleaching.

Translocation of α-helix chains through a nanopore.

The translocation of α-helix chains through a nanopore is studied through Langevin dynamics simulations. The α-helix chains exhibit several different characteristics about their average translocation times and the α-helix structures when they transport through the nanopores under the driving forces. First, the relationship between average translocation times τ and the chain length N satisfies the scaling law, τ∼N(α), and the scaling exponent α depends on the driving force f for the small forces while it is close to the Flory exponent (ν) in the other force regions. For the chains with given chain lengths, it is observed that the dependence of the average translocation times can be expressed as τ∼f(-1/2) for the small forces while can be described as τ∼f in the large force regions. Second, for the large driving force, the average number of α-helix structures N(h) decreases first and then increases in the translocation process. The average waiting time of each bead, especially of the first bead, is also dependent on the driving forces. Furthermore, an elasticity spring model is presented to reasonably explain the change of the α-helix number during the translocation and its elasticity can be locally damaged by the large driving forces. Our results demonstrate the unique behaviors of α-helix chains transporting through the pores, which can enrich our insights into and knowledge on biopolymers transporting through membranes.