A Size‐Selective Intracellular Delivery Platform

Identifying and separating a subpopulation of cells from a heterogeneous mixture are essential elements of biological research. Current approaches require detailed knowledge of unique cell surface properties of the target cell population. A method is described that exploits size differences of cells to facilitate selective intracellular delivery using a high throughput microfluidic device. Cells traversing a constriction within this device undergo a transient disruption of the cell membrane that allows for cytoplasmic delivery of cargo. Unique constriction widths allow for optimization of delivery to cells of different sizes. For example, a 4 μm wide constriction is effective for delivery of cargo to primary human T‐cells that have an average diameter of 6.7 μm. In contrast, a 6 or 7 μm wide constriction is best for large pancreatic cancer cell lines BxPc3 (10.8 μm) and PANC‐1 (12.3 μm). These small differences in cell diameter are sufficient to allow for selective delivery of cargo to pancreatic cancer cells within a heterogeneous mixture containing T‐cells. The application of this approach is demonstrated by selectively delivering dextran‐conjugated fluorophores to circulating tumor cells in patient blood allowing for their subsequent isolation and genomic characterization.     

Histogram-Based Decision Support System for Extraction and Classification of Leukemia in Blood Smear Images

An abnormality that develops in white blood cells is called leukemia. The diagnosis of leukemia is made possible by microscopic investigation of the smear in the periphery. Prior training is necessary to complete the morphological examination of the blood smear for leukemia diagnosis. This paper proposes a Histogram Threshold Segmentation Classifier (HTsC) for a decision support system. The proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear images. Arithmetic operations are used to crop the nucleus based on automated approximation. White Blood Cell (WBC) segmentation is calculated using the active contour model to determine the contrast between image regions using the color transfer approach. Through entropy-adaptive mask generation, WBCs accurately detect the circularity region for identification of the nucleus. The proposed HTsC addressed the cytoplasm region based on variations in size and shape concerning addition and rotation operations. Variation in WBC imaging characteristics depends on the cytoplasmic and nuclear regions. The computation of the variation between image features in the cytoplasm and nuclei regions of the WBCs is used to classify blood smear images. The classification of the blood smear is performed with conventional machine-learning techniques integrated with the features of the deep-learning regression classifier. The designed HTsC classifier comprises the binary classifier with the classification of the lymphocytes, monocytes, neutrophils, eosinophils, and abnormalities in the WBCs. The proposed HTsC identifies the abnormal activity in the WBC, considering the color and shape features. It exhibits a higher classification accuracy value of 99.6% when combined with the other classifiers. The comparative analysis expressed that the proposed HTsC model exhibits an overall accuracy value of 98%, which is approximately 3%–12% higher than the conventional technique.     

MayGAN: Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia Form Blood Smear Images

Leukemia, often called blood cancer, is a disease that primarily affects white blood cells (WBCs), which harms a person’s tissues and plasma. This condition may be fatal when if it is not diagnosed and recognized at an early stage. The physical technique and lab procedures for Leukaemia identification are considered time-consuming. It is crucial to use a quick and unexpected way to identify different forms of Leukaemia. Timely screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require treatment. Various deep-learning (DL) model-based segmentation and categorization techniques have already been introduced, although they still have certain drawbacks. In order to enhance feature extraction and classification in such a practical way, Mayfly optimization with Generative Adversarial Network (MayGAN) is introduced in this research. Furthermore, Generative Adversarial System (GAS) is integrated with Principal Component Analysis (PCA) in the feature-extracted model to classify the type of blood cancer in the data. The semantic technique and morphological procedures using geometric features are used to segment the cells that makeup Leukaemia. Acute lymphocytic Leukaemia (ALL), acute myelogenous Leukaemia (AML), chronic lymphocytic Leukaemia (CLL), chronic myelogenous Leukaemia (CML), and aberrant White Blood Cancers (WBCs) are all successfully classified by the proposed MayGAN model. The proposed MayGAN identifies the abnormal activity in the WBC, considering the geometric features. Compared with the state-of-the-art methods, the proposed MayGAN achieves 99.8% accuracy, 98.5% precision, 99.7% recall, 97.4% F1-score, and 98.5% Dice similarity coefficient (DSC).     

A survey on routing algorithms for wireless Ad-Hoc and mesh networks

Wireless networking technology is evolving as an inexpensive alternative for building federated and community networks (relative to the traditional wired networking approach). Besides its cost-effectiveness, a wireless network brings operational efficiencies, namely mobility and untethered convenience to the end user. A wireless network can operate in both the “Ad-Hoc” mode, where users are self-managed, and the “Infrastructure” mode, where an authority manages the network with some Infrastructure such as fixed wireless routers, base stations, access points, etc. An Ad-Hoc network generally supports multi-hopping, where a data packet may travel over multiple hops to reach its destination. Among the Infrastructure-based networks, a Wireless Mesh Network (with a set of wireless routers located at strategic points to provide overall network connectivity) also provides the flexibility of multi-hopping. Therefore, how to route packets efficiently in wireless networks is a very important problem.A variety of wireless routing solutions have been proposed in the literature. This paper presents a survey of the routing algorithms proposed for wireless networks. Unlike routing in a wired network, wireless routing introduces new paradigms and challenges such as interference from other transmissions, varying channel characteristics, etc. In a wireless network, routing algorithms are classified into various categories such as Geographical, Geo-casting, Hierarchical, Multi-path, Power-aware, and Hybrid routing algorithms. Due to the large number of surveys that study different routing-algorithm categories, we select a limited but representative number of these surveys to be reviewed in our work. This survey offers a comprehensive review of these categories of routing algorithms.In the early stages of development of wireless networks, basic routing algorithms, such as Dynamic Source Routing (DSR) and Ad-Hoc On-demand Distance Vector (AODV) routing, were designed to control traffic on the network. However, it was found that applying these basic routing algorithms directly on wireless networks could lead to some issues such as large area of flooding, Greedy Forwarding empty set of neighbors, flat addressing, widely-distributed information, large power consumption, interference, and load-balancing problems. Therefore, a number of routing algorithms have been proposed as extensions to these basic routing algorithms to enhance their performance in wireless networks. Hence, we study the features of routing algorithms, which are compatible with the wireless environment and which can overcome these problems.     

High‐performance flexible epoxy/ZnO nanocomposites with enhanced mechanical and thermal properties

Flexible epoxy/ZnO nanocomposites were prepared using different loadings of ZnO nanoparticles (NPs) and nanotubes (NTs) via in situ curing of epoxy with polyoxyethylene diamines (ED₆₀₀). ZnO precursor was synthesized via precipitation method and ZnO NPs with an average size of 25 nm were used in the preparation of the nanocomposites. ZnO NTs with an average outer diameter, length of 200 nm and 2.4 µm respectively, were prepared by the wet method (hydrothermal method). The morphology, structure, and composition of the nanocomposites were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X‐ray diffraction (XRD), Fourier transform infrared spectroscopy (FT‐IR), and thermo‐gravimetric analysis (TGA). The effect of morphology and content of nano‐ZnO materials on the thermal and mechanical properties of flexible epoxy was studied. In addition, the hardness and indentation depth were calculated by means of nanoindentation. Results showed that the mechanical and thermal properties of flexible epoxy were enhanced by incorporation of ZnO nanostructure into the polymer matrix. POLYM. ENG. SCI., 57:932–946, 2017. © 2016 Society of Plastics Engineers     

On the reduction of desalting energy and its cost in Kuwait

All seawater desalting processes, multi-stage flash (MSF), multi-effect boiling (MEB), mechanical vapor compression (MVC) and seawater reverse osmosis (SWRO) consume significant amounts of energy. The recent increase of fuel oil cost raises the cost of energy consumed for desalting water and the final water cost, and creates more interest in using more energy efficient desalting systems.

The most used desalting systems by distillation (MSF and MEB) are usually combined with power plants in what is called co-generation power desalting plants, CPDP. Fuel is supplied to the CPDP to produce both desalted water D and power W, and the fuel cost is shared between D and W. Exergy analysis and equivalent work are among the methods used to determine the fuel energy charged to each product. When desalting systems, such as SWRO and MVC, are not combined with a power plant, the fuel energy can be directly determined from its electrical power consumption.

In this paper, the fuel energy cost charged to desalting seawater in the presently used CPDP in Kuwait is calculated based on exergy analysis. The MSF, known by its high energy consumption, is the only desalting method used in Kuwait. The MSF units consume 258 kJ/kg thermal energy by steam supplied to the brine heater BH, 16 kJ/kg by steam supplied to steam ejectors, and 4 kWh/m3 mechanical energy for pumping. These MSF units are operated either by:

(1) Steam extracted from extraction/condensing steam turbines EC/ST as in as in Doha West, Azzour, and Sabbiya CPDP. This practice is used in most Gulf area.

(2) Steam supplied directly from boilers as occurred in single purpose desalting plants as Al Shuwaikh plant; or in winter time when no steam turbines are in operation in the CPDP to supply steam to the desalting units.

The CPDP have limited water to power production ratio. While they can cope with the increase of power demand, it cannot satisfy the water demand, which is increasing with higher pace than the power demand.

The case of steam CPDP used in Kuwait is presented in this paper as a reference plant to evaluate the amount of fuel energy consumed to desalt water in MJ/m3, its cost in $/m3. The resulted high fuel cost calls for some modifications in the reference CPDP to lower the energy cost, and to increase its water to power ratio. The modifications include the use of an auxiliary back-pressure steam turbine ABPST supplied with the steam presently extracted to the MSF units. The power output of the ABPST operates MVC or SWRO desalting units; while the ABPST discharged steam operates LT-MEB desalting unit. The desalting fuel energy costs when applying these modifications are also calculated by the exergy analysis and compared with that present situation.

It is also suggested to increase desalted water output by using separate SWRO desalting units operated by the existing power plants of typical η_c = 0.388, or by new combined gas/steam turbines power cycle GT/ST-CC of typical η_c = 0.54 under construction. The SWRO with energy recovery is assumed to consume typical 5.2 kWh/m³ electric energy.     

Isolation of Salmonella typhimurium from outbreak-associated cake mix

During May and June of 2005, 26 persons in several states were infected by a single strain (isolates indistinguishable by pulsed-field gel electrophoresis) of Salmonella enterica serotype Typhimurium after eating cake batter ice cream. The cake mix used to prepare the cake batter in the ice cream was implicated by epidemiologic investigation as the source of Salmonella contamination. Initial tests did not detect Salmonella in cake mix collected during the outbreak investigation. The objective of this study was to evaluate different procedures to isolate Salmonella from the implicated cake mix, cake, and ice cream. All outbreak-associated food samples (14 samples) were collected during the outbreak investigation by health departments of several of the states involved. Different combinations of Salmonella isolation procedures, including sample size, preenrichment broth, enrichment broth, enrichment temperature, and isolation medium, were used. Salmonella Typhimurium was isolated from two cake mix samples; the food isolates were indistinguishable from the outbreak pattern by pulsed-field gel electrophoresis subtyping. Universal preenrichment broth was substantially better than was lactose broth for preenrichment, and tetrathionate broth was better than was Rappaport-Vassiliadis broth for isolating Salmonella from the two positive cake mix samples. Although more typical Salmonella colonies were observed on plates from enrichment cultures grown at 35 degrees C, more confirmed Salmonella isolates were obtained from plates of enrichment cultures grown at 42 degrees C. Brilliant green agar, xylose lysine tergitol 4 agar, xylose lysine desoxycholate agar, Hektoen enteric agar, and bismuth sulfite agar plates were equally effective in isolating Salmonella from cake mix. The best combination of preenrichment-enrichment conditions for isolating the outbreak strain of Salmonella was preenrichment of cake mix samples in universal preenrichment broth at 35 degrees C for 24 h, followed by enrichment in tetrathionate broth at 42 degrees C for 24 h.     

A Network-Failure-Tolerant Message-Passing System for Terascale Clusters

The Los Alamos Message Passing Interface (LA-MPI) is an end-to-end network-failure-tolerant message-passing system designed for terascale clusters. LA-MPI is a standard-compliant implementation of MPI designed to tolerate network-related failures including I/O bus errors, network card errors, and wire-transmission errors. This paper details the distinguishing features of LA-MPI, including support for concurrent use of multiple types of network interface, and reliable message transmission utilizing multiple network paths and routes between a given source and destination. In addition, performance measurements on production-grade platforms are presented.     

Controllability of cross-flow heat exchangers

The operation of heat exchangers and other thermal equipment in the face of variable loads is usually controlled by manipulating inlet fluid temperatures or mass flow rates. This is a fundamental study of the basic issues regarding state and output controllability in such systems. A numerical method based on finite-differences is developed to approximate infinite-dimensional equations by finite-dimensional ones for the study of a conduction-convection system. The dynamics of a single-pass cross-flow heat exchanger with simultaneous advection, convection and conduction, in which water and air are the in- and over-tube fluids, respectively, is represented by a coupled set of partial differential equations. The numerical method is used to analyze the behavior of the heat exchanger equations. Using the water or air inlet temperature as the manipulated variable leads to a linear problem, and for the water flow rate it is non-linear. Controllability results for different choices of the manipulated variable are presented.