siRNA nanotherapeutics: a promising strategy for anti‐HBV therapy

Chronic hepatitis B (CHB) is the most common cause of hepatocellular carcinoma (HCC) and liver cirrhosis worldwide. In spite of the numerous advances in the treatment of CHB, drugs and vaccines have failed because of many factors like complexity, resistance, toxicity, and heavy cost. New RNA interference (RNAi)‐based technologies have developed innovative strategies to target Achilles'' heel of the several hazardous diseases involving cancer, some genetic disease, autoimmune illnesses, and viral disorders particularly hepatitis B virus (HBV) infections. Naked siRNA delivery has serious challenges including failure to cross the cell membrane, susceptibility to the enzymatic digestion, and excretion by renal filtration, which ideally can be addressed by nanoparticle‐mediated delivery systems. cccDNA formation is a significant problem in obtaining HBV infections complete cure because of strength, durability, and lack of proper immune response. Nano‐siRNA drugs have a great potential to address this problem by silencing specific genes which are involved in cccDNA formation. In this article, the authors describe siRNA nanocarrier‐mediated delivery systems as a promising new strategy for HBV infections therapy. Simultaneously, the authors completely represent the clinical trials which use these strategies for treatment of the HBV infections.Inspec keywords: tumours, drugs, genetics, cellular biophysics, RNA, nanomedicine, diseases, molecular biophysics, microorganisms, cancer, liver, nanoparticles, patient treatmentOther keywords: siRNA nanotherapeutics, anti‐HBV therapy, chronic hepatitis B, CHB, HCC, hazardous diseases, cancer, genetic disease, autoimmune illnesses, viral disorders, hepatitis B virus infections, naked siRNA delivery, cell membrane, enzymatic digestion, renal filtration, nanoparticle‐mediated delivery systems, cccDNA formation, HBV infections complete cure, nanosiRNA drugs, siRNA nanocarrier‐mediated delivery systems, HBV infections therapy, liver cirrhosis, RNA interference, immune response, hepatocellular carcinoma     

Comparison of approaches to shielding of ADR magnets

An important consideration in the use of magnets in adiabatic demagnetization refrigeration (ADR) applications is shielding of the other instruments in the vicinity of the superconducting magnets. Shielding without proper optimization can add unnecessary weight to the magnet system that can amount to a few times the weight of the superconducting magnet itself. This article reports on examination of various approaches to shielding of ADR magnets, and measurements conducted on both passive and active shielding of a sample Nb₃Sn solenoidal magnet. Shielded ADR solenoidal magnets are also compared with self-shielding toroidal magnets in terms of overall weight, volume, and cooling capacity.     

A novel time-based low-power pipeline analog to digital converter

A new power reduction technique for analog-to-digital converters is proposed in this paper. A novel current-mode algorithm which uses time to perform analog-to-digital conversion has been described and a 12 bit 100-ksample/s time-based pipeline analog to digital converter has been designed and simulated in standard 90-nm CMOS technology based on introduced structure. Employed circuit techniques include a continues-time comparator, bottom plate sampling, digital correction and a state machine. A time based-mechanism has been used for subtraction and amplification. Simulation results show that the pipelined ADC achieves a peak signal-to-noise-and-distortion ratio of 69.8 dB, a peak spurious-free dynamic range of 75 dB, a total harmonic distortion of 73 dB, and a peak integral nonlinearity of 0.85 least significant bits. The total power dissipation is 90 μW from a 3-V supply.     

Robust Magnification Independent Colon Biopsy Grading System over Multiple Data Sources

Automated grading of colon biopsy images across all magnifications is challenging because of tailored segmentation and dependent features on each magnification. This work presents a novel approach of robust magnification-independent colon cancer grading framework to distinguish colon biopsy images into four classes: normal, well, moderate, and poor. The contribution of this research is to develop a magnification invariant hybrid feature set comprising cartoon feature, Gabor wavelet, wavelet moments, HSV histogram, color auto-correlogram, color moments, and morphological features that can be used to characterize different grades. Besides, the classifier is modeled as a multiclass structure with six binary class Bayesian optimized random forest (BO-RF) classifiers. This study uses four datasets (two collected from Indian hospitals—Ishita Pathology Center (IPC) of 4X, 10X, and 40X and Aster Medcity (AMC) of 10X, 20X, and 40X—two benchmark datasets—gland segmentation (GlaS) of 20X and IMEDIATREAT of 10X) comprising multiple microscope magnifications. Experimental results demonstrate that the proposed method outperforms the other methods used for colon cancer grading in terms of accuracy (97.25%-IPC, 94.40%-AMC, 97.58%-GlaS, 99.16%-Imediatreat), sensitivity (0.9725-IPC, 0.9440-AMC, 0.9807-GlaS, 0.9923-Imediatreat), specificity (0.9908-IPC, 0.9813-AMC, 0.9907-GlaS, 0.9971-Imediatreat) and F-score (0.9725-IPC, 0.9441-AMC, 0.9780-GlaS, 0.9923-Imediatreat). The generalizability of the model to any magnified input image is validated by training in one dataset and testing in another dataset, highlighting strong concordance in multiclass classification and evidencing its effective use in the first level of automatic biopsy grading and second opinion.     

Latest Developments in Modeling and Characterization of Joining Metal Based Hybrid Materials

Advanced materials consist of several materials systems that exhibit complementary properties for multi‐purpose applications. Joining of dissimilar materials is a critical and challenging advanced manufacturing technique to develop novel hybrid materials with properties fully transferred. The “bonding strength” of a joint is crucial for its integrity and performance. The bonding strength is affected by a range of parameters that can be better understood, controlled, and optimized via both experimental and analytical approaches. In this paper, the authors review the theoretical and experimental studies of the interface inside several metal based composites. The scope includes interface bonding's critical parameters, characterization techniques of joining processes, potential applications, and their future perspectives. The review is significant to develop advanced manufacturing techniques for heterogeneous materials and to design innovative heterogeneous systems for various medical, electrical, electronics, industrial, and other daily life applications that involve the broad range of “joining” processes.

     

MetiTarski: An Automatic Theorem Prover for Real-Valued Special Functions

Many theorems involving special functions such as ln, exp and sin can be proved automatically by MetiTarski: a resolution theorem prover modified to call a decision procedure for the theory of real closed fields. Special functions are approximated by upper and lower bounds, which are typically rational functions derived from Taylor or continued fraction expansions. The decision procedure simplifies clauses by deleting literals that are inconsistent with other algebraic facts. MetiTarski simplifies arithmetic expressions by conversion to a recursive representation, followed by flattening of nested quotients. Applications include verifying hybrid and control systems.     

Supervisory control of switching control systems

In this paper, the problem of designing a switching policy for an adaptive switching control system is formulated as a problem of supervisory control of a discrete-event system (DES). Two important problems in switching control are then addressed using the DES formulation and the theory of supervisory control under partial observation. First, it is verified whether for a given set of controllers, a switching policy satisfying a given set of constraints on the transitions among controllers exists. If so, then a minimally restrictive switching policy is designed. Next, an iterative algorithm is introduced for finding a minimal set of controllers for which a switching policy satisfying the switching constraints exists. It is shown that in the supervisory control problem considered in this paper, limitations on event observation are the factors that essentially restrict supervisory control. In other words, once observation limitations are respected, limitations on control will be automatically satisfied. This result is used to simplify the proposed iterative algorithm for finding minimal controller sets.     

AMOLED Pixel Circuit With Electronic Compensation of Luminance Degradation

A new voltage-programmed pixel circuit using hydrogenated amorphous silicon (a-Si:H) thin-film transistors (TFTs) for active-matrix organic light-emitting diodes (AMOLEDs) is presented. In addition to compensating for the shift in threshold voltage of TFTs, the circuit is capable of compensating for OLED luminance degradation by employing the shift in OLED voltage as a feedback of OLED degradation     

Thermodynamic and transport property models for carbon capture and sequestration (CCS) processes with emphasis on CO2 transport

Carbon capture and sequestration (CCS) is one of the most promising technologies for the reduction of carbon dioxide (CO₂) concentration in the atmosphere, so that global warming can be controlled and eventually eliminated. A crucial part in the CCS process design is the model that is used to calculate the physical properties (thermodynamic, transport etc.) of pure CO₂ and CO₂ mixtures with other components.     

Minimizing Cutting Wastes of Reinforcement Steel Bars Using Genetic Algorithms and Integer Programming Models

Materials that are in the form of one-dimensional stocks such as steel rebars, structural steel sections, and dimensional lumber generate a major fraction of the generated construction waste. Cutting one-dimensional stocks to suit the construction project requirements result in trim or cutting losses, which is the major cause of the one-dimensional construction waste. The optimization problem of minimizing the trim losses is known as the cutting stock problem (CSP). In this paper, three approaches for solving the one-dimensional cutting stock problem are presented. A genetic algorithm (GA) model, a linear programming (LP) model, and an integer programming (IP) model were developed to solve the one-dimensional CSP. Three real life case studies from a steel workshop have been studied. The generated cutting schedules using the GA, LP, and IP approaches are presented and compared to the actual workshop’s cutting schedules. The comparison shows a high potential of savings that could be achieved using such techniques. Additionally, a user friendly Visual Basic computer program that utilizes genetic algorithms for solving the one-dimensional CSP is presented.