Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Photostabilization of ascorbic acid with citric acid, tartaric acid and boric acid in cream formulations

This study involves the evaluation of the effect of certain stabilizers, that is, citric acid (CT), tartaric acid (TA) and boric acid (BA) on the degradation of ascorbic acid (AH(2) ) in oil-in-water cream formulations exposed to the UV light and stored in the dark. The apparent first-order rate constants (0.34-0.95 × 10(-3) min(-1) in light, 0.38-1.24 × 10(-2) day(-1) in dark) for the degradation reactions in the presence of the stabilizers have been determined. These rate constants have been used to derive the second-order rate constants (0.26-1.45 × 10(-2) M(-1) min(-1) in light, 3.75-8.50 × 10(-3) M(-1) day(-1) in dark) for the interaction of AH(2) and the individual stabilizers. These stabilizers are effective in causing the inhibition of the rate of degradation of AH(2) both in the light and in the dark. The inhibitory effect of the stabilizers is in the order of CT > TA > BA. The rate of degradation of AH(2) in the presence of these stabilizers in the light is about 120 times higher than that in the dark. This could be explained on the basis of the deactivation of AH(2) -excited triplet state by CT and TA and by the inhibition of AH(2) degradation through complex formation with BA. AH(2) leads to the formation of dehydroascorbic acid (A) by chemical and photooxidation in cream formulations.     

Effect of molecular weight distribution on polymer diffusion during film formation of two-component high-/low-molecular weight latex particles

We describe fluorescence resonance energy transfer (FRET) studies of film formation by a new type of two-component latex particles. These particles consist of a miscible blend of two components that have a similar composition but very different molecular weights. In our approach, we used sequential seeded emulsion polymerization to generate (in situ) a fraction of oligomer in poly(butyl acrylate-co-methyl methacrylate) P(BA-MMA) seed particles that contained a relatively high molecular weight (high-M) dye-labeled polymer. In this way we could systematically change the molecular weight distribution of polymer inside the particles. We varied the amount and the molecular weight of the oligomers. For latex films cast from these two-component particles, we studied the diffusion rate of the high molecular weight polymer by FRET. These measurements revealed that oligomers promoted diffusion rate during latex film formation (oligoplasticization). We analyzed our diffusion data in terms of the Fujita–Doolittle free-volume model and showed that higher molecular weight oligomers are less efficient as plasticizers. In separate experiments, oligomers with similar molecular weights as those in the two-component particles were introduced via latex blending. We compared oligoplasticization in latex blends films with that in the two-component particles films. Finally, we investigated the rheological behavior of the two-component polymers with compositions adjusted to have a common T_g (2 °C). The higher the molecular weight of the oligomer, the more that had to be added to achieve T_g = 2 °C. All of the oligomers were much shorter than the entanglement length and act as diluents of the entanglements in the high-M polymer. We found that incorporating larger amounts of oligomers with a higher molecular weight resulted in a more pronounced drop in polymer viscosity, associated with the decrease in the entanglement density.     

Effects of feeding bentonite clay upon ochratoxin A–induced immunosuppression in broiler chicks

A presence of mycotoxins in feed is one of the most alarming issues in the poultry feed industry. Ochratoxins, produced by several Aspergillus and Penicillium species, are important mycotoxin regarding the health status of poultry birds. Ochratoxins are further classified into to several subtypes (A, B, C, etc) depending on their chemical structures, but ochratoxin A (OTA) is considered the most important and toxic. Bentonite clay, belonging to phyllosilicates and formed from weathering of volcanic ashes, has adsorbent ability for several mycotoxins. The present study was designed to study the effects of bentonite clay upon OTA-induced immunosuppression in broiler chicks. For this, 480 day-old broiler chicks were procured from a local hatchery and then different combinations of OTA (0.15, 0.3, or 1.0 mg/kg) and bentonite clay (5, 10, and 20 g/kg) were incorporated into their feed. At 13, 30, and 42 days of age, parameters such as antibody responses to sheep red blood cells, in situ lymphoproliferative responses to mitogen (PHA-P), and in situ phagocytic activity (i.e., via carbon clearance) were determined respectively. The results indicated there was a significant reduction of total antibody and immunoglobulin titres, lymphoproliferative responses, and phagocytic potential in OTA-treated birds, suggesting clear immunosuppression by OTA in birds in a dose-dependent manner. These results were also significantly lower in all combination groups (OTA with bentonite clay), suggesting few to no effects of feeding bentonite clay upon OTA- induced alterations in different immune parameters.     

Geometrical model to calculate the consumption of sewing thread for 504 over-edge stitch

Sewing thread is one of the most important components of a sewn product that contributes significantly in the useful life of a product. Stitch class 504 is the one which is used in all types of sewn products. Its thread consumption is higher than class 300 and class 400. A mathematical model to predict the sewing thread consumption of stitch class 504 has been proposed in this paper. The model is based on the geometry of the stitch. The proposed model takes into account material thickness and stitch density. The model was validated by using 24 samples (with different material thickness and stitch densities). The accuracy of the model was found to be 99%. Sensitivity analysis revealed that stitch density has 62% effect and material thickness has 38% effect on thread consumption. The proposed model can predict the thread consumption accurately; therefore, it can be used for better estimation of required thread and encourage its better utilization in sewn product industry.     

Photothermal nanoblade for large cargo delivery into mammalian cells

It is difficult to achieve controlled cutting of elastic, mechanically fragile, and rapidly resealing mammalian cell membranes. Here, we report a photothermal nanoblade that utilizes a metallic nanostructure to harvest short laser pulse energy and convert it into a highly localized explosive vapor bubble, which rapidly punctures a lightly contacting cell membrane via high-speed fluidic flows and induced transient shear stress. The cavitation bubble pattern is controlled by the metallic structure configuration and laser pulse duration and energy. Integration of the metallic nanostructure with a micropipet, the nanoblade generates a micrometer-sized membrane access port for delivering highly concentrated cargo (5 × 10(8) live bacteria/mL) with high efficiency (46%) and cell viability (>90%) into mammalian cells. Additional biologic and inanimate cargo over 3-orders of magnitude in size including DNA, RNA, 200 nm polystyrene beads, to 2 μm bacteria have also been delivered into multiple mammalian cell types. Overall, the photothermal nanoblade is a new approach for delivering difficult cargo into mammalian cells.     

Statistical segmentation and structural recognition for floor plan interpretation

A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.     

A scalable and low power VLIW DSP core for embedded system design

Aims to provide the block architecture of CoStar3400 DSP that is a high performance, low power and scalable VLIW DSP core, it efficiently deployed a variable-length execution set （VLES） execution model which utilizes the maximum parallelism by allowing multiple address generations and data arithmetic logic units to execute multiple instructions in a single clock cycle. The scalability was provided mainly in using more or less number of functional units according to the intended application. Low power support was added by careful architectural design techniques such as fine-grain clock gating and activation of only the required number of control signals at each stage of the pipeline. The said features of the core make it a suitable candidate for many SoC configurations, especially for compute intensive applications such as wire-line and wireless communications, including infrastructure and subscriber communications. The embedded system designers can efficiently use the scalability and VLIW features of the core by scaling the number of execution units according to specific needs of the application to effectively reduce the power consumption, chip area and time to market the intended final product.     

Metal Organic Framework-MXene Nanoarchitecture for Fast Responsive and Ultra-Stable Electro-Ionic Artificial Muscles

Electro-ionic soft actuators, capable of continuous deformations replacing non-compliant rigid mechanical components, attract increasing interest in the field of next-generation metaverse interfaces and soft robotics. Here, a novel MXene (Ti₃C₂T_x) electrode anchoring manganese-based 1,3,5-benzenetricarboxylate metal-organic framework (MnBTC) for ultrastable electro-ionic artificial muscles is reported. By a facile supramolecular self-assembly, the Ti₃C₂T_x-MnBTC hybrid nanoarchitecture forms coordinate bond, hydrogen bond, and hydrophilic interaction with the conducting polymer of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), resulting in a mechanically flexible and electro-ionically active electrode. The superior electrical and electrochemical performances of the electrode stem from the synergistic effects between intrinsically hierarchical nanoarchitecture of MnBTC and rapid electron transport behavior of Mxene, leading to fast diffusion and accommodation of ions in the ion-exchangeable membrane. The developed artificial muscle based on Ti₃C₂T_x-MnBTC is found to exhibit high bending displacement (12.5 mm) and ultrafast response time (0.77 s) under a low driving voltage (0.5 V), along with wide frequency response (0.1–10 Hz) and exceptional stability (98% retention at 43,200 s) without any distortion of actuation performance. Furthermore, the designed electro-active artificial muscle is successfully used to demonstrate mimicry of eye motions including eyelid blinking and eyeball movement in a doll.     

Google Scholar University Ranking Algorithm to Evaluate the Quality of Institutional Research

Education quality has undoubtedly become an important local and international benchmark for education, and an institute’s ranking is assessed based on the quality of education, research projects, theses, and dissertations, which has always been controversial. Hence, this research paper is influenced by the institutes ranking all over the world. The data of institutes are obtained through Google Scholar (GS), as input to investigate the United Kingdom’s Research Excellence Framework (UK-REF) process. For this purpose, the current research used a Bespoke Program to evaluate the institutes’ ranking based on their source. The bespoke program requires changes to improve the results by addressing these methodological issues: Firstly, Redundant profiles, which increased their citation and rank to produce false results. Secondly, the exclusion of theses and dissertation documents to retrieve the actual publications to count for citations. Thirdly, the elimination of falsely owned articles from scholars’ profiles. To accomplish this task, the experimental design referred to collecting data from 120 UK-REF institutes and GS for the present year to enhance its correlation analysis in this new evaluation. The data extracted from GS is processed into structured data, and afterward, it is utilized to generate statistical computations of citations’ analysis that contribute to the ranking based on their citations. The research promoted the predictive approach of correlational research. Furthermore, experimental evaluation reported encouraging results in comparison to the previous modification made by the proposed taxonomy. This paper discussed the limitations of the current evaluation and suggested the potential paths to improve the research impact algorithm.