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Automatic Urdu handwritten text recognition is a challenging task in the OCR industry. Unlike printed text, Urdu handwriting lacks a uniform font and structure. This lack of uniformity causes data inconsistencies and recognition issues. Different writing styles, cursive scripts, and limited data make Urdu text recognition a complicated task. Major languages, such as English, have experienced advances in automated recognition, whereas low-resource languages, such as Urdu, still lag. Transformer-based models are promising for automated recognition in high- and low-resource languages such as Urdu. This paper presents a transformer-based method called ET-Network that integrates self-attention into EfficientNet for feature extraction and a transformer for language modeling. The use of self-attention layers in EfficientNet helps to extract global and local features that capture long-range dependencies. These features proceeded into a vanilla transformer to generate text, and a prefix beam search is used for the finest outcome. NUST-UHWR, UPTI2.0, and MMU-OCR-21 are three datasets used to train and test the ET Network for a handwritten Urdu script. The ET-Network improved the character error rate by 4% and the word error rate by 1.55%, while establishing a new state-of-the-art character error rate of 5.27% and a word error rate of 19.09% for Urdu handwritten text.

Control algorithms are the most critical aspects in the successful control of civil structures subjected to earthquake and wind forces. In recent years, adaptive intelligent control algorithms are emerging as an acceptable substitute method to conventional model-based control algorithms. These algorithms mainly work on the principles of artificial intelligence (AI) and soft computing (SC) methods that make them highly efficient in controlling highly nonlinear, time-varying, and time-delayed complex civil structures. The current research probes to control algorithms, that this article set forth an inclusive state-of-the-art review of adaptive intelligent control (AIC) algorithms for vibration control of smart civil structures. First, a general introduction to adaptive intelligent control is presented along with its advantages over conventional control algorithms. Second, their classification concerning artificial intelligence and soft computing methods is provided that mainly consists of artificial neural network-based controller, brain emotional learning-based intelligent controller, replicator dynamics-based controller, multi-agent system-based controller, support vector machine-based controller, fuzzy logic control, adaptive neuro-fuzzy inference system-based controller, adaptive filters-base controller, and meta-heuristic algorithms-based hybrid controllers. Third, a brief review of these algorithms with their developments on the theory and applications is provided. Fourth, we demonstrate a summarized overview of the cited literature with a brief trend analysis is presented. Finally, this study presents an overview of these innovative AIC methods that can demonstrate future directions. The contribution of this article is the anticipation of detailed and in-depth discussion into the perspective of AI and SC-based AIC method advances that enabled practical applications in attenuating vibration response of smart civil structures. Moreover, the review demonstrates the computing advantages of AIC over conventional controllers that are important in creating the next generation of smart civil structures.

The wood cellulose fiber (WCF) reinforced polylactic acid (PLA) offers cost effectiveness, ease of mass production, short processing time, structural stability, high quality and efficient recyclability. In the study presented orientation of fiber, microstructure and thermomechanical property of composites are beingexamined by using X-ray tomography, scanning electron microscopy (SEM), and dynamic mechanical thermal analysis (DMA). Also, the mechanical properties of WCF–PLA–MAH composites were characterized and analyzed. The results demonstrated that the best outcome of elastic modulus and tensile strength were accomplished at 30%WCF–PLA–3%MAH composite. The DMA result explains that by adding MAH in WCF–PLA as an interfacial coupling agent enhanced the storage modulus and increased the toughness of WCF–PLA composite by decreasing the tanδ peak. X-ray tomography of the PLA/WCF/FB composite shows that the degree of anisotropy is accomplished 25% higher when WCF was 30% in PLA matrix. In addition, the SEM micrograph shows that when MAH was used the interfacial compatibility between the PLA matrix and WCF improved.

Betaine-based natural deep eutectic solvents (NADESs), a new class of green solvents, were immobilized into a porous polyvinylidene fluoride (PVDF) support and evaluated for the separation of CO 2 from CO 2 /N 2 and CO 2 /CH 4 mixtures. Two types of NADESs were synthesized by mixing betaine (hydrogen bond acceptor-HBA) with malic acid and tartaric acid (hydrogen bond donors-HBD) respectively. FTIR and Raman spectroscopy were studied to confirm the synthesis and purity of the NADESs. The thermal strength of the NADESs was investigated using thermogravimetric analysis. The gas permeation results of the fabricated NADES-based-supported liquid membranes (NADES-SLMs) showed that the permeability of CO 2 increased from 25.55 to 29.33 Barrer on substitution of hydrogen bond donor from tartaric acid to malic acid. Similarly, the ideal CO 2 /CH 4 selectivity varied from 51.1 to 56.4 as tartaric acid was replaced by malic acid as the HBD. The performance of NADES-SLMs was compared with the competing imidazolium-based-supported ionic liquid membranes, and proved NADES-SLMs as a promising alternative considering their green potential and comparable gas separation performance. The current effort for the exploitation of NADESs into PVDF membranes in this study is expected to open new routes for the efficient separation of CO 2 from the industrial gas mixture.

Radiative cooling is a new large-scale cooling technology with the promise of lowering costs and decreasing global warning. Currently, daytime radiative cooling is achieved via the application of reflective metal layers and complicated multilayer structures, limiting its application on a massive scale. In our research, we explored and tested the daytime subambient cooling effect with the help of single-layer films consisting of BaSO4, TiO2, and BaSO4/TiO2 microparticles embedded in PVDF/PTFE polymers. The film, consisting of BaSO4/TiO2 microparticles, offers a low solar absorbance and high atmospheric window emissivity. The solar reflectance is enhanced by micropores in the PVDF/PTFE polymers, without any significant influence on the thermal emissivity. The BaSO4/TiO2/PVDF/PTFE microparticle film attains 0.97 solar reflectance and 0.95 high sky-window emissivity when the broadly distributed pore size reaches 180 nm. Our field test demonstrated that the single-layer BaSO4/TiO2/PVDF/PTFE microparticle film achieved a temperature 5.2 °C below the ambient temperature and accomplished a cooling power of 74 W/m2. Also, the results show that, when the humidity rises from 33% to 38% at 12:30 pm, it hinders the cooling of the body surface and lowers the cooling effect to 8%.

A passive cooling method with great potential to lower space-cooling costs, counteract the urban heat island effect, and slow down worldwide warming is radiant cooling. The solutions available frequently require complex layered structures, costly products, or a reflective layer of metal to accomplish daytime radiative cooling, which restricts their applications in many avenues. Furthermore, single-layer paints have been used in attempts to accomplish passive daytime radiative cooling, but these usually require a compact coating or only exhibit limited cooling in daytime. In our study, we investigated and evaluated in daytime the surrounding cooling outcome with aid of one layer coating composed of BaSO4/TiO2 microparticles in various concentrations implanted in the PVDF-HF polymers on a concrete substrate. The 30% BaSO4/TiO2 microparticle in the PVDF-HF coating shows less solar absorbance and excessive emissivity. The value of solar reflectance is improved by employing micro-pores in the structure of PVDF polymers without noticeable effect on thermal emissivity. The 30% BaSO4/TiO2/PVDF coating is accountable for the hydrophobicity and proportionate solar reflection in the UV band, resulting in efficient solar reflectivity of about 95.0%, with emissivity of 95.1% and hydrophobicity exhibiting a 117.1° water contact angle. Also, the developed coating could cool to about 5.1 °C and 3.9 °C below the surrounding temperature beneath the average solar irradiance of 900 W/m−2. Finally, the results demonstrate that the 30% BaSO4/TiO2/PVDF-HF microparticle coating illustrates a typical figure of merit of 0.60 and is also capable of delivering outstanding dependability and harmony with the manufacturing process.

Today, tissue engineered scaffolds made by electrospinning are becoming a central focus of vascular prostheses research due to their ability to assist native tissue recovery. Compared to a single material, multifunctional composite scaffold could provide more suitable microenvironment for the tissue regeneration. In this study, electrospun composite scaffolds are developed by reinforcing a matrix of poly (lactic acid) (PLA) and poly (butylene succinate) (PBS) by cellulose nano-fibrils (CNFs). Initially, PLA/PBS fibrous scaffolds with different ratio were prepared. The best properties and bioactivity of the scaffolds were obtained at equal ratio of PLA and PBS. Overall performance of electrospun scaffolds improved greatly by introduction of CNF into the PLA/PBS scaffolds. The developed composite scaffolds were found to meet some of the essential requirements for vascular tissue regeneration. They showed a uniform fibrous structure with desirable size dimension, cell-friendly surface characteristics, sustainable biodegradation behaviour and sustainable mechanical property compared to native tissue. In addition, the CNF composite scaffolds supported attachment and proliferation of human fibroblast cells more than PLA, PBS or their blends alone. Overall the developed composite scaffolds demonstrated their potency for vascular tissue engineering application.

The organic Rankine cycle (ORC) exhibits considerable promise in efficiently utilizing low-to-medium-grade heat. Currently, there is a range of organic fluids available in the market, and selecting the appropriate one for a specific application involves considering factors such as the cycle’s thermodynamic performance, plant size, and compatibility with turbomachinery. The objective of our study is to examine the exergetic performance of the ORC with internal heat regeneration. We analyze 12 different organic fluids to evaluate their suitability based on parameters like exergy efficiency and heat exchange area requirements. Additionally, we investigate the need for internal heat regeneration by comparing the overall exergy performance with a simpler ORC configuration. To ensure broad applicability, we consider source temperatures ranging from 150 to 300 °C, which are relevant to industrial waste heat, geothermal sources, and solar energy. For each case, we calculate specific net power output and the UA value (heat exchanger conductance) to gain insights into selecting the appropriate organic fluid for specific source temperatures. Cyclohexane, benzene, isopropyl alcohol, and hexafluorobenzene show poor exergy efficiency due to their high boiling points. Pentane and cyclopentane provides the highest exergy efficiency of 62.2% at source temperature of 300 °C, whereas pentane is found to be the most suitable at source temperatures of 200 and 150 °C with exergy efficiency of 67.7% and 61.7%, respectively. At 200 °C source temperature, RE347mcc achieves 65.9% exergy efficiency. The choice of organic fluid for a given heat source is highly influenced by its critical properties. Moreover, the normal boiling temperature of the organic fluid significantly impacts exergy destruction during the condensation process within the cycle.

Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials.

One of the ideal energy carriers for the future is hydrogen. It has a high energy density and is a source of clean energy. A crucial step in the development of the hydrogen economy is the safety and affordable storage of a large amount of hydrogen. Thus, owing to its large storage capacity, good reversibility, and low cost, Magnesium hydride (MgH2) was taken into consideration. Unfortunately, MgH2 has a high desorption temperature and slow ab/desorption kinetics. Using the ball milling technique, adding cobalt lanthanum oxide (LaCoO3) to MgH2 improves its hydrogen storage performance. The results show that adding 10 wt.% LaCoO3 relatively lowers the starting hydrogen release, compared with pure MgH2 and milled MgH2. On the other hand, faster ab/desorption after the introduction of 10 wt.% LaCoO3 could be observed when compared with milled MgH2 under the same circumstances. Besides this, the apparent activation energy for MgH2–10 wt.% LaCoO3 was greatly reduced when compared with that of milled MgH2. From the X-ray diffraction analysis, it could be shown that in-situ forms of MgO, CoO, and La2O3, produced from the reactions between MgH2 and LaCoO3, play a vital role in enhancing the properties of hydrogen storage of MgH2.