The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was dome in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.

Geologists employ high-spatial-resolution (HR) remote sensing (RS) data for many diverse applications as they effectively reflect detailed geological information, enabling high-quality and efficient geological surveys. Applications of HR RS data to geological and related fields have grown recently. By analyzing these applications, we can better understand the results of previous studies and more effectively use the latest data and methods to efficiently extract key geological information. HR optical remote sensing data are widely used in geological hazard assessment, seismic monitoring, mineral exploitation, glacier monitoring, and mineral information extraction due to high accuracy and clear object features. Compared with optical satellite images, synthetic-aperture radar (SAR) images are stereoscopic and exhibit clear relief, strong performance, and good detection of terrain, landforms, and other information. SAR images have been applied to seismic mechanism research, volcanic monitoring, topographic deformation, and fault analysis. Furthermore, a multi-standard maturity analysis of the geological applications of HR images using literature from the Science Citation Index reveals that optical remote sensing data are superior to radar data for mining, geological disaster, lithologic, and volcanic applications, but inferior for earthquake, glacial, and fault applications. Therefore, geological remote sensing research needs to be truly multidisciplinary or interdisciplinary, ensuring more detailed and efficient surveys through cross-linking with other disciplines. Moreover, the recent application of deep learning technology to remote sensing data extraction has improved automatic processing and data analysis capabilities.

We report on the effects of the film morphology on the fluorescence spectra for a thin film including a quinoxaline-based co-polymer (TQ1) and a fullerene derivative (PC₇₀BM). The ratio between the polymer and the fullerene derivative, as well as the processing solvent were varied. Beside the main emission peak at 700 nm in the fluorescence spectra of thin films of this phase-separated blend, a broad emission band is observed with a maximum at 520 - 550 nm. The intensity of this emission band decreases with an increasing degree of mixing in the film and becomes most prominent in thicker films, films with high PC₇₀BM content, and films that were spin-coated from solvents with lower PC₇₀BM solubility. We assign this emission band to aggregated PC₇₀BM.

UAS-based multi-spectral imagery is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate BRDF correction. Future UAS based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

In this paper we provide some bounds for the error in approximating the Riemann-Stieltjes integral $\int_{a}^{b}f (t) du (t)$ by the generalized trapezoidal rule \begin{equation*} \left[ u\left( b\right) -u\left( x\right) \right] f\left( b\right) +\left[ u\left( x\right) -u\left( a\right) \right] f\left( a\right) \end{equation*} under various assumptions for the integrand $f$ and the integrator $u$ for which the above integral exists. Applications for continuous functions of selfadjoint operators and unitary operators in Hilbert spaces are provided as well.

A comprehensive model for designing robust all-in-fiber microresonator-based optical sensing setups is illustrated. The investigated all-in-fiber setups allow light to selectively excite high-Q whispering gallery modes (WGMs) into optical microresonators, thanks to a pair of identical long period gratings (LPGs) written in the same optical fiber. Microspheres and microbubbles are used as microresonators and evanescently side-coupled to a thick fiber taper, with a waist diameter of about 18 µm, in-between the two LPGs. The model is validated by comparing the simulated results with the experimental data. A good agreement between the simulated and experimental results is obtained. As an application example, the sensing of the concentration of an aqueous glycerol solution is demonstrated. The model is general and by exploiting the refractive index and/or absorption characteristics at suitable wavelengths, the sensing of other substances or pollutants can be also predicted.

The attributes of electroplating as a low-cost, simple, scalable and manufacturable semiconductor deposition technique for the fabrication of large-area and nanotechnology-based device applications are discussed. These strengths of electrodeposition are buttressed experimentally using techniques such as X-ray diffraction, Ultraviolet-visible spectroscopy, Scanning electron microscopy, Atomic force microscopy, Energy-dispersive X-ray spectroscopy and photoelectrochemical cell studies. Based on the structural, morphological, compositional optical, and electronic properties evaluated results, it is evident that electroplating possesses the capabilities of producing high-quality semiconductors usable in producing excellent devices. In this paper, we will describe the progress of electroplating technique mainly for the deposition of semiconductor thin film materials, their treatment processes and fabrication of solar cells.

The aim of this article is introduced the concept of double framed T-soft fuzzy set (DFT-soft fuzzy set) which is the combination of soft set and fuzzy set. We also defined the notions and apply this concept in BCK/BCI-algebras. By using example, we also discussed the concept of double framed T-soft fuzzy algebra (DFT-soft fuzzy algebra) and double framed B-soft fuzzy algebra (DFB-soft fuzzy algebra) and also investigated their properties. Each double framed T-soft fuzzy algebra is double framed B-soft fuzzy algebra but by using example, we proved that converse may or may not be possible.

Permafrost covers about 23% ~ 25% of the land in the northern hemisphere, mainly in Russia, Canada, Alaska, Northeast and Qinghai Tibet Plateau (QTP) in China. Many engineering especially the transportation has been in the permafrost regions above. Under the action of highways construction and global warming, permafrost under infrastructures is degraded and causes serious damage. Two phases closed thermosyphon (TPCT) is a widely accepted green countermeasure against the problem in permafrost regions. Although it has been applied to prevent permafrost degradation, their application presents significant challenges on account of the stronger endothermic action of asphalt pavement. This paper focused on the thermosyphon technology and application in the permafrost. Moreover, the article highlighted the excellent working performance of the TPCT that improving the stability of the infrastructures and prevent it degrading due its excellent efficiency of heat transfer. The industrial applications of the TPCT were also summarized, along with their limitations. Finally, the results reported in this paper can provide a valuable guidance for the design of the TPCT and construction of the permafrost regions in the future.

The incidence of hepatocellular carcinoma (HCC) is increasing and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinical available treatments have dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients showing a durable treatment benefit over time, and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with non-viral etiologies, such non-alcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers informative of the best treatment approach are required actions to improve patient survival. Numerous evidence indicated non-coding RNAs (ncRNAs) as pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs.

Power sources that can consistently deliver high levels of energy over extended periods are crucial for various space applications. Among the many methods of energy generation, direct heat-to-electricity conversion without intermediate steps or moving components shows particular promise but also presents significant challenges. The aim of this research is to address these challenges by enhancing the energy efficiency of thermionic conversion, which transforms thermal energy into electrical energy, through the development and utilization of a novel class of emission nanomaterials known as multilayer carbyne-enriched 3D-shaped nano-interfaces. By manipulating the topological, physicochemical, and functional characteristics of these interfaces, we seek to optimize their thermionic conversion capabilities. Building on the recent discovery of collective atomic vibrations called phonon waves within transition domains of multilayer nanostructures, we have devised a new approach to enhance the efficiency of thermionic energy converters. This involves unlocking the predictive functionality of 2D-ordered linear-chain carbon-based multilayer emitters through the excitation and fine-tuning of collective atomic vibrations and nanoarchitecture. To achieve this, we propose employing a combination of techniques that leverage interface effects, enable phonon wave propagation, facilitate energy exchange, and capitalize on synergistic effects offered by the multilayer nano-enhanced interfaces. The resulting devices for thermionic energy conversion have the potential to significantly surpass the efficiency of existing plasma thermionic converters by several orders of magnitude. Moreover, these electricity-generating sources based on thermionic conversion represent fundamental options for the advancement of Lunar and Martian research missions, opening up possibilities for sustainable energy production in extraterrestrial environments.

Due to their wide range of uses in modern technology, nanomaterial’s of silver metallic (Ag-NPs) have engaged considerable concern, driving significant research with development efforts. This study focuses on investigating the antimicrobial properties of Ag-NPs, encompassing their production, characterization, and biological aspects. The eco-friendly extracellular biosynthetic method employed in this work utilized extracts from the marine fungus Aspergillus flavus MK4 as reducing agents for nanoparticle synthesis. Analyzing the colloidal Ag-NPs using UV-visible spectroscopy revealed a peak in absorbance at 460 nm, indicating the presence of plasmonic properties. The electrons imaging of internal structure (TEM) elucidated spherical shape of the Ag-NPs by 15 nm size. Testing against bacterial diversities (Gr-ve & Gr+ve) revealed potent antibacterial and antifungal efficacy. Cytotoxicity versus HepG-2 cell line was assessed using the MTT assay, and antioxidant properties were examined through the radical scavenging (DPPH) assay. In wise of their conceivable applications in the fields of antibacterial, anticancer, and wound-healing, the Ag-NPs that were synthesized exhibit promising features. With its powerful ability to synthesize silver nanoparticles (Ag-NP), Aspergillus flavus MK4 Aspergillus flavus MK4 can generate nanoparticles extensively characterized, demonstrating their antibacterial, antioxidant, anticancer, and wound-healing properties.

In this study, a novel absorbable hemostatic agent was developed using carrageenan (CRG) as a natural polymer and cerium oxide nanoparticles (CeO2 NPs).  CRG-CeO2-0.5 and CRG-CeO2-1 composites were prepared by compositing CRG and CeO2 at a weight ratio of 200:1 and 100:1, respectively. Physio-chemical and structural properties of these compounds were studied and compared with pristine CRG. Upon incorporation of CeO2 nanoparticles into the CRG matrix, significant reductions in hydrogel degradation were observed. In addition, it was noted that CRG-CeO2 exhibited better antibacterial and hemostatic properties than CRG hydrogel without CeO2.The biocompatibility of the materials was tested using the NIH 3T3 cell line and all samples were found to be nontoxic. Particularly, CRG-CeO2-1 demonstrated superior hemostatic effects, biocompatibility, and a lower degradation rate since more CeO2 Nps were present in the CRG matrix. Therefore, CRG-CeO2-1 has the potential to be used as a hemostatic agent and wound dressing.

Primary materials supply is the heart for engineering and sciences; depletion of natural resources and an increase in the human population by a billion in 13 to 15 years pose a critical concern on the sustainability of the materials. Therefore, functionalizing renewable materials, such as nanocellulose, possibly exploiting its properties for various practical applications, has been undertaken worldwide. Nanocellulose has emerged as a dominant green natural material with attractive and tailorable physicochemical properties, renewable, sustainable, biocompatibility, and tunable surface properties. Nanocellulose is derived from cellulose, the most abundant polymer in nature with remarkable properties of nanomaterials. This article provides a comprehensive overview of the methods used for nanocellulose preparation, structure-property and processing-property correlations, and the application of nanocellulose and its nanocomposite materials. This article differentiates the classification of nanocellulose, provides a brief account of the production methods that have been developed for isolating nanocellulose, highlights a range of unique properties of nanocellulose that have been extracted from different kinds of experiments and studies; and elaborates on nanocellulose potential applications in various areas. The present review is anticipated to provide the readers regarding the progress and knowledge related to nanocellulose. Pushing the boundaries of nanocellulose further into cutting edge applications will be of particular interest for the future, especially as cost-effective commercial sources of nanocellulose continue to emerge.

This article introduces ten similarity measures that utilize cosine and cotangent functions to compare (m,n)-rung orthopair fuzzy sets, this a super class of q-rung orthopair fuzzy sets. Further, we applied our established weighted similarity measures to medical diagnosis, pattern recognition,and building material problems and also presented the comparison between established measures with the existing cosine and cotangent measures of q-rung orthopair, pythagorean and intuitionistic fuzzy sets. Lastly, we considered a numerical example that demonstrates the effective and scientific application of these similarity measures in plant leaf disease classification. Furthermore, we present graphical interpretations to demonstrate the effectiveness of our established measures.

Nanomaterials such as pH-responsive polymers are promising for targeted drug delivery systems, due to the difference in pH between tumor and healthy regions. However, there is a significant concern about the application of these materials in this field due to their low mechanical resistance, which can be mitigated by combining these polymers with mechanically resistant inorganic materials such as mesoporous silica nanoparticles (MSN) and hydroxyapatite (HA). Mesoporous silica has interesting properties such as high surface area and hydroxyapatite has been widely studied to aid in bone regeneration, providing special properties adding multifunctionality to the system. Furthermore, fields of medicine involving luminescent elements such as rare earth are an interesting option in cancer treatment. The present work aims to obtain a pH-sensitive hybrid system based on silica and hydroxyapatite with photoluminescent and magnetic properties. The nanocomposites were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption methods, CHN elemental analysis, Zeta Potential, scanning electron microscopy (SEM), and transmission electron microscopy (TEM), vibrational sample magnetometry (VSM), and photoluminescence analysis. Incorporation and release studies of the antitumor drug doxorubicin were performed to evaluate the potential use of these systems in targeted drug delivery. The results showed the luminescent and magnetic properties of the materials and showed suitable characteristics for application in the release of pH-sensitive drugs.

With the rapid development of communication technology, connected vehicles (CV) have the potential, through the sharing of data, to enhance vehicle safety and reduce vehicle energy consumption and emissions. Numerous research efforts have been conducted to quantify the impacts of CV applications, assuming instant and accurate communication among vehicles, devices, pedestrians, infrastructure, the network, the cloud, and the grid, collectively known as V2X (vehicle-to-everything). The use of cellular vehicle-to-everything (C-V2X), to share data is emerging as an efficient means to achieve this objective. C-V2X releases 14 and 15 utilize the 4G LTE technology and release 16 utilizes the new 5G new radio (NR) technology. C-V2X can function without network infrastructure coverage and has a better communication range, improved latency, and greater data rates compared to older technologies. Such highly efficient interchange of information among all participating parts in a CV environment will not only provide timely data to enhance the capacity of the transportation system but can also be used to develop applications that enhance vehicle safety and minimize negative environmental impacts. However, before the full benefits of CV can be achieved, there is a need to thoroughly investigate the effectiveness, strengths, and weaknesses of different CV applications, the communication protocols, the varied results with different CV market penetration rates (MPRs), the interaction of CVs and human driven vehicles, the integration of multiple applications, and the errors and latencies associated with data communication. This paper reviews existing literature on the environmental, mobility and safety impacts of CV applications, identifies the gaps in our current research of CVs and recommends future research directions. The results of this paper will help shape the future research direction for CV applications to realize their full potential benefits.

For many decades, X-ray diffraction (XRD) has been used for material characterization. With the recent development in material science understanding and technology, various new materials are being developed, which requires upgrading the existing analytical techniques such that intricate problems can be solved. Although, XRD is a well-established non-destructive technique, it still requires further improvements in its characterization capabilities, especially when dealing with complex mineral structures. The present review conducts comprehensive discussions on atomic crystal structure, XRD principle, its applications, uncertainty during XRD analysis, and required safety precautions, all in one place. It further discusses the future research directions, especially the use of artificial intelligence and machine learning tools for improving the effectiveness and accuracy of XRD technique for mineral characterization. It has been focused that how XRD patterns can be utilized for a thorough understanding of the crystalline structure, size, and orientation, dislocation density, phase identification, quantification, and transformation, information about lattice parameters, residual stress, and strain, and thermal expansion coefficient of materials. All these important discussions on XRD for mineral characterization are compiled in this short yet comprehensive review that would benefit specialists and engineers in the chemical, mining, iron, metallurgy, and steel industries.

Clove (Syzygium aromaticum L. Myrtaceae) is an aromatic plant widely cultivated in tropical and subtropical countries, rich in volatile compounds and antioxidants such as eugenol, β-caryophyllene, and α-humulene. Clove essential oil has received considerable interest due to its wide application in the perfumery, cosmetic, health, medical, flavoring, and food industries. Clove essential oil has relevant biological activities to human health, including antimicrobial, antioxidant, and insecticide. This review describes the effect of the extraction method (hydrodistillation, steam distillation, ultrasound-assisted extraction, microwave-assisted extraction, cold pressing, and supercritical fluid extraction) on the chemical composition of essential oil and its correlation with their biological activities. Likewise, are summarized the main compounds and their reported biological activities. Furthermore, the main applications in clove essential oil in the food industry are presented. Finally, this review presents the new biological activities such as anti-inflammatory, analgesic, anesthetic, antinociceptive and anticancer, which are beneficial for human health. This review aims to compile the effect of different methods of extracting clove essential oil on chemical composition, food applications, as well as a current description of biological activities of interest to human health. Biological activities have increased interest in research into this essential oil and its future applications in the food or pharmaceutical industry.

Fossil fuels and carbon origin resources are affecting our environment. Therefore, alternative energy sources have to be established to co-produce energy along with fossil fuels and carbon origin resources until it is the right time to replace them. Microbial Fuel Cell (MFC) is a promising technology in the field of energy production. Compared to the conventional power sources it is more efficient and not controlled by the Carnot cycle. Its high efficiencies, low noise, and less pollutant output could make it revolutionize in the power generation industry with a shift from centrally located generating stations and long-distance transmission lines to dispersed power generation at load sites. In this review, several characteristics of the MFC technology will be highlighted. First, a brief history of abiotic to biological fuel cells and subsequently, microbial fuel cells is presented. Second, the focus is then shifted to elements responsible for the making MFC working with efficiency. Setup of the MFC system for every element and their assembly is then introduced, followed by an explanation of the working machinery principle. Finally, microbial fuel cell designs and types of main configurations used are presented along with scalability of the technology for the proper application.

Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, we apply the GRA theory to the HFSs and interval-valued hesitant fuzzy sets (IVHFS) domain. We propose the HFSs grey relational degree, HFSs slope grey relational degree, HFSs synthetic grey relational degree and IVHFSs grey relational degree, which describe the closeness, the variation tendency and both the closeness and variation tendency of HFSs and closeness of IVHFSs, respectively, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs and IVHFSs MADM problems. Finally, combined with two practical MADM examples about energy policy selection with HFSs information and emergency management evaluation with IVHFSs information, we obtain the most desirable decision results, and compared with the previous methods, the validity, effectiveness and accuracy of the proposed grey relational degree for HFSs and IVHFSs are demonstrated in detail.

The Android-based IoT platform just like the existing Android provides an environment that makes it easy to utilize Google's infrastructure services including development tools and APIs through which it helps to control the sensors of IoT devices. Applications running on the Android-based IoT platform are often UI free and are used without the user’s consent to registered permissions. It is difficult to respond to the misuse of permissions as well as to check them when they are registered indiscriminately while updating applications. This paper analyzes the versions of before and after an application the update running on the Android-based IoT platform and the collected permission lists. It aims to identify the same permissions before and after the update, and deleted and newly added permissions after the update were identified, and thereby respond to security threats that can arise from the permissions that is not needed for IoT devices to perform certain functions.

Measure While Drilling (MWD) refers to a comprehensive array of sensors employed to gather performance data throughout the process of rock drilling in mining blast holes. Multiple MWD metrics are collected by researchers depending on the setup of MWD sensors. Trends in MWD data can be correlated with pre-excavation subsurface conditions. The low-cost, extensive MWD data acquisition resolution of blast holes compared to expensive and sparsely collected exploration drill holes make the former one a desirable method for characterizing pre-excavation subsurface conditions. Nevertheless, the application of MWD technology in open pit mining is constrained by a substantial amount of data that requiring manual analysis within a short time. To address this limitation, computerized data acquisition and interpretation of MWD variables has been used to broadly determine open pit mining lithological boundaries. The results of artificial intelligence algorithms, such as Neural Networks, and Gaussian Processes, to recognize subsurface conditions, such as rock type, from MWD data have consistently returned >90% prediction accuracy. However, methods of evaluating the importance of each MWD feature, such as Principal Component Analysis, has not been optimally used. This review focuses on the progression of intelligent MWD analysis using Machine Learning methods in open-pit mining, to determine the geotechnical, geological, and geochemical subsurface characteristics before open-pit mining excavation.

This study reports the synthesis and characterization of novel per-fluorinated organic polymers with azo- and azomethine-based linkers using nucleophilic aromatic substitution. The polymers reveal variations in the fluorine content via the incorporation of decafluorobiphenyl and hexafluorobenzene linkers, which enhanced their hydrophobic nature. The rich fluorine polymers were slightly soluble in THF and have shown molecular weights between 4886 to 11948 g/mol. All polymers exhibit thermal stability in the range of 350-500°C, with varying thermal stability depending on the fluorine and nitrogen content. Conjugation of the polymers was confirmed through changes in the UV-Vis spectra, with a hypsochromic shift observed in all cases, more pronounced in azo-based fluorinated chains due to H-bonding on the nitrogen sites, chain conformations, and planarity. The optical band gap (Eg) of the polymers was determined from the UV-Vis data, with the Eg values of the azo-based fluorinated polymers being 1 eV higher than those of their corresponding linkers. The cross-linking formation was characterized by porosity measurements, with the azo-based polymer exhibiting the highest surface area of 770 m²/g with a pore volume of 0.35 cm³/g, while the open-chain azomethine-based polymer exhibited the lowest surface area of 285 m²/g with a pore volume of 0.0872 cm³/g. Porous structures with varied hydrophobicities were investigated as adsorbents for separating water-benzene and water-phenol mixtures and selectively binding methane/carbon dioxide gases from the air. The most hydrophobic polymers containing the decafluorbiphenyl linker were suitable for benzene separation, while the best methane uptake values were 6.14 and 3.46 mg/g for DAB-Z-1O and DAB-A-1O, respectively. DAB-Z-1h, with the highest surface area and rich in nitrogen sites, exhibited the highest CO₂ uptake at 298 K (17.25).

Background: TP53 alterations have a significant prognostic effect in myeloid neoplasms. Our objective was to investigate the TP53 gene mutation status, p53 protein expression, and their re-lationship in dysplasia-related myeloid neoplasms with varying levels of myeloblast counts. Methods: 76 bone marrow biopsy samples with different blast counts were analyzed. Total and strong (3+) p53 expression was determined. Dual immunohistochemical staining was performed to determine the cell population associated with p53 expression. NGS analysis was performed using the Accel-Amplicon Comprehensive TP53 panel. Results: Both p53 expression and TP53 VAF showed a significant correlation with the myeloblast ratio (p<0.0001), however, p53 expres-sion was present in other cell lineages as well. The VAF value exhibited a significant correlation with p53 expression. A high specificity (0.9800) was observed for TP53 mutation using the ≥10% strong (3+) p53 cut-off value, although the sensitivity (0.4231) was low. Conclusion: Strong (3+) p53 expression using a ≥10% cut-off value accurately predicts TP53 mutation but doesn't reveal the allelic state. The p53 expression is significantly influenced by myeloblast count, and histo-logical interpretation should consider the presence of intermixed non-neoplastic marrow cells with varying physiological p53 expression.

The present paper introduces a method of basis transformation of vector fields that is specifically applicable to polynomials space and differential equations with certain polynomials solutions such as Hermite, Laguerre and Legendre polynomials. The method based on separated transformation of vector space basis by a set of operators that are equivalent to the formal basis transformation and connected to it by linear combination with projection operators. Applying the Forbenius covariants yields a general method that incorporates the Rodrigues formula as a special case in polynomial space. Using the Lie algebra modules, specifically , on polynomial space results in isomorphic algebras whose Cartan sub-algebras are Hermite, Laguerre and Legendre differential operators. Commutation relations of these algebras and Baker-Campbell-Hausdorff formula gives new formulas for special polynomials

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

This paper discovers that current variational principle and Noether theorem for different physics systems with (in)finite freedom systems have missed the double extremum processes of the general extremum functional that both is deduced by variational principle and is necessarily taken in deducing all the physics laws, but these have not been corrected for over a century since Noether's proposing her famous theorem, which result in the crisis deducing relevant mathematical laws and all physics laws. This paper discovers there is the hidden logic cycle that one assumes Euler-Lagrange equations, and then he finally deduces Euler-Lagrange equations via the equivalent relation in the whole processes in all relevant current references. This paper corrects the current key mistakes that when physics systems choose the variational extreme values, the appearing processes of the physics systems are real physics processes, otherwise, are virtual processes in all current articles, reviews and (text)books. The real physics should be after choosing the variational extreme values of physics systems, the general extremum functional of the physics systems needs to further choose the minimum absolute extremum zero of the general extremum functional, otherwise, the appearing processes of physics systems are still virtual processes. Using the double extremum processes of the general extremum functionals, the crisis and the hidden logic cycle in current variational principle and current Noether theorem are solved. Furthermore, the new mathematical and physical double extremum processes and their new mathematical pictures and physics for (in)finite freedom systems are discovered. This paper gives both general variational principle and general Noether theorem as well as their classical and quantum new physics, which would rewrite all relevant current different branches of science, as key tools of studying and processing them.

Good health and well-being is one of the essential SDGs that ensure healthy lives and promote well-being for all ages and further entails providing substantial medical services to the public at low cost and with minimal adverse effects on the environment. Information and communication technologies (ICTs) have taken on an increasingly important function as significant facilitators of healthcare reform, with the goals of enhancing access to health services, the quality of treatment provided, and the overall productivity of the healthcare system. However, the integration of ever-increasing ICT technologies into the healthcare systems, also referred to as digital transformation, is not a straightforward process, but it comes with different types of challenges from integration level to application design level and security level. Although several studies have been proposed to address the integration of ICT technologies into healthcare systems, there is still a need for a comprehensive research study on the integration and design challenges, security and privacy challenges, application areas, and possible positive and negative impacts. Therefore, this paper contributes as the research literature study covering an important SDG, "Good health and well-being," and its digital transformation, along with summarising our research findings in a detailed and taxonomical way. To start with, firstly, we present a detailed comparison of existing studies on healthcare and well-being, mainly focusing on integrating ICT technologies in healthcare in terms of sustainable aspects, security and privacy challenges, design and integration challenges, E-health-related applications, and future directions. We also present an overview and the need for digital transformation in healthcare, discuss its significant components, highlight E-health's importance and benefits, explore its integration and design challenges, and categorise the security and privacy challenges. Next, we present an in-depth discussion on the role of Blockchain technology as today's leading technology in E-health, discussing Blockchain technology and its characteristics, highlighting its benefits, and describing the possible types of Blockchain-based E-health use cases. Furthermore, we discuss the positive and negative impact of ICT integration along with identifying open issues and challenges of integrating ICT technologies into the healthcare systems and discuss future research directions, which provide the strength for researchers to address the issues in future solutions.

Ultrasonic transducers are widely used for non-destructive testing (NDT) and evaluation in various industries. While capacitive micromachined ultrasonic transducers (CMUTs) have emerged as significant novel transducers, their application in NDT has been limited. This study designed and fabricated a novel two-element CMUT device for NDT applications. The CMUT’s structural parameters were introduced, and the device was fabricated using silicon fusion wafer-bonding technology. The transducer’s sensitivity, bandwidth, and pulse-echo response performance were tested and analyzed. Testing with aluminum blocks demonstrated that the two-element transducer can transmit and receive ultrasonic waves, with central operating frequencies of 3.35 MHz. In addition, at 3.4 MHz, the receive sensitivities of both elements were –197.434 dB and –197.413 dB, respectively, meeting the requirements for NDT systems. In pulse-echo response testing, the CMUT successfully detected signals from the aluminum block interface and located the interface’s position. This study highlights the potential of CMUTs for NDT testing and evaluation applications.

Case studies (CS) attempt to help students increase critical thinking skills and engagement while working through a real-life scenario in various disciplines, including medicine, law, and business. However, the CS method has not been heavily utilized in biological sciences. The present study investigated the effect of the CS method on undergraduate biology students’ conceptual understanding, academic outcomes, and perspectives. A case study was applied in a one-semester undergraduate biology course, which was compared to ten semesters of standard sections. Participants completed course pre- and post-tests, pre- and post-case tests, and an online survey to assess their conceptual understanding and engagement. The initial lowest quartiles were determined from the individual course pre-test scores, which were lower than class averages. Results suggested that the CS method helped students in learning outcomes, critical thinking, and conceptual understanding toward biology. In post-test learning gains, the CS group did 20% better than the non-CS group, with the largest benefit seen in the initially lowest pre-test quartile of the class. Moreover, post-case learning gains were 55% improved in the case test. Survey results indicated that students had positive attitudes toward CS for their engagement in plant biology content. Overall, the distribution of A grades improved by 2.6-fold from standard to CS groups. We conclude that the use of CS may address course content engagement and have the potential to effectively boost academic performance, especially for the initially lowest quartile in undergraduate plant biological sciences courses.

The development of novel ionic liquid crystals for energy storage applications has gained significant attention in recent years due to their potential to develop the field of energy storage. Ionic liquid crystals represent a unique class of materials with high ionic conductivity and thermal stability, making them ideal candidates for use in advanced energy storage devices. This research aims to explore the fundamental properties, structure and liquid crystals performance of these novel materials, with the goal of advancing their practical application in next-generation energy storage technologies. By understanding the structure-function relationship of ionic liquid crystals, researchers can tailor their properties to meet specific energy storage requirements, such as high energy density, fast charging capabilities, and long cycle life. This study seeks to contribute to the growing body of knowledge in the field of energy storage by investigating the potential of novel ionic liquid crystals as efficient and sustainable energy storage solutions. The two ionic liquid crystals show mesomorphic behavior and typical zwitterion characteristics that revealed by the cyclic voltammetry techniques. These materials uploaded with lithium ions for more stability and higher ionic conductivity.

Graphene foam prepared by chemical vapor deposition method is a promising thermal interfacial material. However, the thermal properties of graphene foam highly depend on the experimental fabrication conditions during the chemical vapor deposition process. Aiming to reveal how to prepare the appropriate graphene foam for the various thermal management scenarios, the influence of experimental conditions on thermal properties of graphene foam is investigated. Furthermore, the contribution of thermal conductivity and thermal radiation to the effective thermal coefficient of graphene foam is carried out for comparison. Research results show that, the porosity and the cross-section shape of struts of growth template are two critical factors to affect the thermal transport of graphene foam, especially with the increase of temperature. In addition, the deposition time of graphene determines the wall thickness and affects the thermal conductivity directly. The thermal radiation contributes more than thermal conductivity when the temperature climbs continuously. Comparatively, the effective thermal coefficient of graphene foam composite with high porosity and circular shape struts is much superior to others at high temperature. The research findings can provide important guidance for the graphene foam fabrication and its applications in the field of thermal management.

End-of-life electric vehicle (EV) batteries can be reused to reduce their environmental impact and economic costs. However, the growth of a second-life market is limited by the lack of information on the characteristics and performance of these batteries. As the volume of end-of-life EVs may exceed the amount of batteries needed for stationary applications, investigating the possibility of repurposing them in mobile applications is also necessary. This article presents an experimental test that can be used to collect the data necessary to fill a battery passport. The proposed procedure can facilitate the decision making process regarding the suitability of a battery for reuse at the end of its first life. Once the battery passport has been completed, the performance and characteristics of the battery are compared with the requirements of several mobile applications. Mobile charging stations and forklift trucks were identified as relevant applications for the reuse of high capacity prismatic cells. Finally, a definition of a state of health (SoH) is proposed to track the suitability of the battery during use in the second life application considering not only energy but also power and efficiency of the battery. This SoH shows that even taking into account accelerated ageing data, a repurposed battery can have an extended life of 11 years at 25~°C. It has also been shown that energy fade is the most limiting performance for lifetime and that cell-to-cell variation should be tracked as it has been shown to have a significant impact on battery life.

With the increasing occurrence of rotator cuff injuries every year, there is a great need for a reliable treatment option. Wharton’s Jelly contains several components that can positively impact the replacement and repair of musculoskeletal defects. The overall objective of this study is to evaluate the improvement of patient-reported pain scales after applying Wharton’s Jelly (WJ) in rotator cuff defects. Eighty-seven patients with rotator cuff defects who failed at least eight weeks of conservative treatment were selected from the retrospective repository. 2cc of WJ flowable allograft was applied to the specific affected anatomy, the most common being supraspinatus tendon, biceps tendon insertion, labral tear, and subscapularis tear. No adverse reactions were reported. Statistically significant improvements were found from the initial to Day 90 in all scales. Patient satisfaction was calculated using minimal clinically important differences. No statistically significant differences were found in mean changes between gender, BMI, and age. Scanning Electron Microscopy images reveal the similarities between the collagen matrix in WJ and the rotator cuff. The significant improvement in patient outcomes coincides with current literature analyzing WJ applications with other structural defects around the body. WJ is a promising alternative for musculoskeletal defects when the standard of care fails.

This scientific paper presents a comprehensive investigation into transient Fourier analysis in some electrical engineering applications. The article deals with two effective approaches for solving transient analysis whose application is rather novel. The first contribution uses combined the Fourier series analytic Laplace-Carson (L­C) transform methods in the complex domain using complex time vectors, thereby significantly simplifying the calculation of the original function. As the inverse transform goes back into the time domain, it employs the Cauchy-Heaviside (C­H) method. The second contribution uses the Fourier transform (F­Τ)for transient analysis of a power converter electrical circuit with the passive and the active load. The method of complex conjugated amplitudes is used for steady-state analysis. Both contributions represent a new approach to this paper. The starting point is the Fourier series/expansions, computation of the Fourier coefficients, then continuing by solving the steady and transient states of the system and confirming the transient states using the Fourier transform. To validate our findings, the worked-out analytical results are verified by modelling in Matlab/Simulink environment.

A two element Multiple Input Multiple Output UWB (Ultra-wide band) antenna is presented in this paper. The antenna is backed by the FR-4 substrate with a thickness of 1.6 mm and dielectric constant of 4.3 covering an area of 52.8 × 29 mm2. The proposed MIMO antenna consists of two single UWB antennas and a stub placed between the two antennas to reduce the mutual coupling. The proposed antenna achieves the voltage standing wave ratio (VSWR) of less than 2 and more than 86% radiation efficiency over the whole band of interest. Performance of the antenna is examined using both simulation and experiment. The design exhibits good performance characteristics in terms of bandwidth, gain, efficiency, return loss and VSWR. The proposed antenna is analyzed using the CST Microwave Studio software. The prototype model of the antenna is fabricated, tested, and measured to validate the simulation return loss results. There is acceptable agreement between the measured and simulated results.

Machine Learning techniques can be used to identify whether deficits in cognitive functions contribute to antisocial and aggressive behavior. This paper initially presents the results of tests conducted on delinquent and non-delinquent youths to assess their cognitive functions. The dataset extracted from these assessments, consisting of 37 predictor variables and one target. was used to train three algorithms that aim to predict whether the data corresponds to that of a young offender or a non-offending youth. Prior to this, statistical tests were conducted on the data to identify characteristics that exhibited significant differences in order to select the most relevant features and optimize the prediction results. Additionally, other feature selection methods, such as Boruta, RFE, and Filter, were applied, and their effects on the accuracy of each of the three machine learning models used (SVM, RF, and KNN) were compared. 80% of the data were utilized for training, while the remaining 20% were used for validation. The best result was achieved by the K-NN model trained with 19 features selected by the Boruta method, followed by the SVM model trained with 24 features selected by the filter method.

Malignant neoplasms arising from the gastrointestinal (GI) tract are among the most common cancer types with a high mortality rate. Despite advances in treatment in a small subgroup harboring targetable mutations, the outcome remains poor, accounting for one in three cancer-related deaths observed globally. As a promising therapeutic option in various tumor types, immunotherapy with immune checkpoint inhibitors has also been evaluated in GI cancer, albeit with limited efficacy except for a small subgroup expressing microsatellite instability. In the quest for more effective treatment options, energetic efforts have been placed to evaluate the role of several immunotherapy approaches comprising of cancer vaccines, adoptive cell therapies and immune checkpoint inhibitors. In this review, we report our experience with personalized dendritic cell cancer vaccine and cytokine-induced killer cell therapy in three patients with GI cancers and summarize current clinical data on combined immunotherapy strategies.

The calibration of three-dimensional (3D) coordinates in augmented reality (AR) systems is a complex activity. It involves the recognition of environmental characteristics and technology that models the 3D space of the device, determining its position and orientation. In the industrial environment, it is common for AR applications to cover large spaces, making it difficult to maintain attributes such as precision and accuracy. The set of sensors and mapping algorithms available in HoloLens stimulate the development of virtual reality (VR) applications, in particular localization techniques. This study proposes calibration models of the 3D coordinates of the HoloLens for indoor industrial environments. The performance of tests in a relevant environment provides data necessary to evaluate the performance of the proposed models in terms of precision and accuracy in determining point coordinates in the study environment. The results show improvements in determining the axes that define the 3D space, with a direct influence on the position of the points observed in the experiment

Barrier coverage is a fundamental application in wireless sensor networks, which is widely used to protect a region through intruder detection for smart city. In this paper, we study a new branch of barrier coverage, named warning barrier coverage (WBC). Different from the classic barrier coverage, WBC has the inverse protect direction, which protects unexpected visitors by warning them away from the region enclosed by sensor barriers. The WBC holds a promising prospect in many danger keep out applications for smart city. For example, a WBC can enclose the debris area in the sea and alarm any approaching ships in order to avoid their damaging propellers. One special feature of WBC is that the target region is usually dangerous and its boundary is previously unknown. Hence, the scattered mobile nodes need to detect the boundary and form the barrier coverage themselves. It is challenging to form these distributed sensor nodes into a barrier because a node can sense only the local information and there is no global information of the unknown region or other nodes. To this end, we propose a novel solution AutoBar for mobile sensor nodes to automatically form a WBC for smart city. To pursue the high coverage quality, we theoretically derive the optimal distribution pattern of sensor nodes using convex theory. Based on the analysis, we design a fully distributed algorithm that enables nodes to collaboratively move towards the optimal distribution pattern. In addition, AutoBar is able to reorganize the barrier even any node is broken. To validate the feasibility of AutoBar, we develop the prototype of the specialized mobile node, which consists of two kinds of sensors: one for boundary detection and another for visitor detection. Based on the prototype, we conduct extensive real trace driven simulations in various smart city scenarios. Performance results demonstrate that AutoBar outperforms the existing barrier coverage strategies in terms of coverage quality, formation duration, and communication overhead.

In the past decades, the world is actively working towards the global goal of net-zero emission. To decrease emissions, there is a notable trend of electrification in transportation, which is a transition from traditional fuel-based systems to electrical power systems onboard different transportation platforms. For this transition, it is important to study the electrical structure, specifically the onboard microgrid, powered by various energy sources. In this paper, traditional energy management strategies for onboard microgrid systems are discussed, which usually require complicated optimization algorithms and high computation capabilities. Driven by the recent advancements in information technologies, artificial intelligence and digital twin have gained much interest within the transportation sector. These technologies can effectively utilize data to achieve intelligent decision-making, optimize resource utilization, and save energy consumption. This paper presents an overview of the usage of these emerging information technologies in energy management strategies, providing an overall summary and classification of the practical applications. In addition, after examining the potential challenges associated with artificial intelligence and digital twin, this paper also discusses future trends in this field.

With a view to sustainable development and circular economy, this work focused on the possibility to valorize a secondary waste stream of recycled carbon fiber (rCF) to produce a 3D printing usable material with PA6,6 polymer matrix. The reinforcing fibers implemented in the present research are the result of a double recovery action: starting with pyrolysis from which long fibers are obtained, used to produce non-woven fabrics and, subsequently, fiber agglomerate wastes obtained from this last process are ground in a ball mill. The effect of a different amount of reinforcement at 5% and 10% by weight on the mechanical properties of 3D printed thermoplastic composites was investigated. Although the recycled fraction was successfully integrated in the production of filaments for 3D printing and therefore in the production of specimens via Fused Deposition Modeling technique, the results showed that fibers did not improve the mechanical properties as expected, due to an unsuitable average size distribution and the presence of a predominant dusty fraction ascribed to the non-optimized ball milling process. PA6,6 + 10 wt.% rCF composites exhibited a tensile strength of 59.53 MPa and a tensile modulus of 2.24 GPa, which correspond to an improvement in mechanical behavior of 21 5 % and 5 21 % compared to the neat PA6,6 specimens, respectively. The printed composite specimens loaded with the lowest content of rCF provided the greatest improvement in strength (+ 9% over the neat sample). Then, a prediction of the “optimum” critical length of carbon fibers was proposed that could be used for future optimizations of the recycled fiber processing.

Inscription of embedded photoluminescent microbits inside a bulk natural diamond, LiF and CaF2 crystals was performed in sub-filamentation (geometrical focusing) regime by 525nm 0.2ps laser pulses focused by 0.65NA micro-objective as a function of pulse energy, exposure and inter-layer separation. The resulting microbits were visualized by 3Dscanning confocal Raman/photoluminescence microscopy as conglomerates of photo-induced quasi-molecular color centers and tested regarding their annealing. Minimal lateral and longitudinal microbit separations, enabling their robust read-out, were measured in LiF as 1.5 and 13 microns, respectively, to be improved regarding information storage capacity by more elaborate focusing systems. These findings pave a way to novel optical storage platforms utilizing ultrashort-pulse laser inscription of photoluminescent microbits as carriers of archival memory.

The purpose of this research is to present a thorough evaluation of the energy management system, which consists of hybrid energy storage systems, and its control algorithms, which may be used in electric vehicles. This paper outlines the characteristics of electric vehicles, research methods, analysis of the hybrid energy storage system architecture, converter topology, and energy management techniques. The strength and co-occurrence of keywords over the past ten years are shown in this study using a systematic research framework for performing a literature review and using keyword analysis techniques. The study reveals a pattern of recently and frequently used terms in works of literature. Consequently, their suitability, benefits, and drawbacks are assessed. In this study, the hybrid energy storage system and converter circuit architecture are evaluated and rated. Non-isolate DC-DC converter converter connected to SC is a suitable configuration for the hybrid converter because it is simple to build, reliable, and has minimal loss/weight/cost, which improves vehicle performance. In terms of the application of control strategies, it is shown that deterministic and fuzzy rule-based control techniques are successfully assessed using real-scale vehicle experiments and selected for manufacturing. On the other hand, real-time optimization-based energy management techniques have been effectively shown in lab-scale tests and may be used in a future real-scale vehicle.

Deep-learning-based speech enhancement techniques have been recently grown in interest, since their impressive performance can potentially benefit a wide variety of digital voice communication systems. However, such performance has been evaluated mostly in offline audio processing scenarios (i.e. feeding the model, in one go, a complete audio recording, which may extend several seconds). It is of great interest to evaluate and characterize the current state-of-the-art in applications that process audio online (i.e. feeding the model a sequence of segments of audio data, concatenating the results at the output end). Although evaluations and comparisons between speech enhancement techniques have been carried out before, as far as the author knows, the work presented here is the first that evaluates the performance of such techniques in relation to their online applicability. Meaning, this work measures how the output signal-to-interference ratio (as a separation metric), the response time and memory usage (as online metrics) are impacted by the input length (the size of audio segments), in addition to the amount of noise, amount and number of interferences, and amount of reverberation. Three popular models were evaluated, given their availability on public repositories and online viability: MetricGAN+, Spectral Feature Mapping with Mimic Loss, and Demucs-Denoiser. The characterization was carried out using a systematic evaluation protocol based on the Speechbrain framework. Several intuitions are presented and discussed, and some recommendations for future work are proposed.

Ultralong carbon nanotubes (UCNTs) are highly demanded for nanocomposites applications because of their magnificent physical and chemical properties. UCNTs are synthesized by catalytic chemical vapor deposition (CCVD) method and, before using as fillers in nanocomposites, should be purified from residual catalyst and non-CNT particles without significant destruction or scissoring of UCNTs. The role of water vapor for purification of UCNTs is investigated, the importance of water assistance in this process is confirmed. It was shown that wet air treatment of products of UCNTs CCVD synthesis under mild conditions can be used to decrease sufficiently residual catalyst content without significant carbon losses in comparison with the results obtained with dry air, while the residual iron content was shown to influence heavily on the subsequent oxidation of different forms of carbons, including UCNTs. The increasing of D/G ratio of Raman spectra after wet air treatment of products of UCNTs CCVD synthesis makes it possible to conclude that iron catalyst particles transform into iron oxides and hydroxides that caused inner structural strains and destruction of carbon shells improving removal of the catalyst particles by subsequent acid treatment. UCNTs purification with water assistance can be used to develop economically and ecologically friendly methods for obtaining fillers for nanocomposites of different applications.

Small modular reactors (SMR) (&lt;300 MW) offer a potentially attractive nuclear energy option for the middle-east region (MER). Currently, the MER uses a significant amount of fossil fuel to process heat applications such as water desalination and in petroleum refineries and chemical plants, besides generating electricity. SMR technologies represent an opportunity to meet future energy demand in the MER. This paper discusses issues related to the future development and use of SMR technology in nuclear-renewable hybrid energy systems for application in the middle east. SMRs have also been examined as part of a resilient hybrid energy system that combines nuclear energy with renewable energy and traditional fossil energy to produce chemicals, fuels, and electricity. This paper presents the results of a techno-economic analysis of a Nuclear-Renewable-Conventional Hybrid Energy System. The paper concludes that SMR technology will be an essential feature of future hybrid energy systems for the MER.

In this paper, experiences of the last 20 years with the PERALS-technique are described. PERALS stands for Photo Electron Rejecting Alpha Liquid Scintillation. This LSC-technique was developed by Jack McDowell in the 70ies and is a powerful technique for the analyses of many natural alpha nuclides. The principle is based on a selective extraction of the radionuclide from the water phase by means of a complexing or ion pair reagent. The extractant contains also a suitable cocktail for the scintillation counting. Therefore, the extract can be analysed directly after the extraction step. After removing quenchers, such as oxygen, and the proper setting of a pulse shape discriminator, alpha pulses can be counted with a photomultiplier. The paper describes the development of robust analysis schemes for the determination of traces of polonium, radon, radium, strontium, thorium, uranium and other actinides in water samples (groundwater, rain water, river water, drinking water, mineral water, sea water).

In this work, we report the carbon fiber-based wire-type asymmetric supercapacitors (ASCs). The highly conductive carbon fibers were prepared by the carbonized and graphitized process using the polyimide (PI) as a carbon fiber precursor. To assemble the ASC device, the CoMnO2-coated and Fe2O3-coated carbon fibers were used as the cathode and the anode materials, respectively. FE-SEM analysis confirmed that the CoMnO2-coated carbon fiber electrode exhibited the porous hierarchical interconnected nanosheet structures, depending on the added amounts of ammonium persulfate (APS) as an oxidizing agent, and Fe2O3-coated carbon fiber electrode showed a uniform distribution of porous Fe2O3 nanorods over the surface of carbon fibers. The nanostructured CoMnO2 were directly deposited onto carbon fibers by a chemical oxidation route without high temperature treatments. In particular, the electrochemical properties of the CoMnO2-coated carbon fiber with the concentration of 6 mmol APS presented the enhanced electrochemical activity, probably due to its porous morphologies and good conductivity. Further, to reduce the interfacial contact resistance as well as improve the adhesion between transition metal nanostructures and carbon fibers, the carbon fibers were pre-coated with the Ni layer as a seed layer using an electrochemical deposition method. The fabricated ASC device delivered a specific capacitance of 221 F g-1 at 0.7 A g-1 and good rate capability of 34.8% at 4.9 A g-1. Moreover, the wire-type device displayed the superior energy density of 60.16 Wh kg-1 at a power density of 490 W kg-1 and excellent capacitance retention of 95% up to 3,000 charge/discharge cycles.

Motivated by the definition of the type 2 poly-Bernoulli polynomials introduced by Kim-Kim, in the present paper, we consider a class of new generating function for the Frobenius-Genocchi polynomials, called the type 2 poly-Frobenius-Genocchi polynomials, by means of the polyexponential function. Then, we derive some useful relations and properties. We show that the type 2 poly-Frobenius-Genocchi polynomias equal a linear combination of the classical Frobenius-Genocchi polynomials and Stirling numbers of the first kind. In a special case, we give a relation between the type 2 poly-Frobenius-Genocchi polynomials and Bernoulli polynomials of order k. Moreover, inspired by the definition of the unipoly-Bernoulli polynomials introduced by Kim-Kim, we introduce the unipoly-Frobenius-Genocchi polynomials by means of unipoly function and give multifarious properties including derivative and integral properties. Furthermore, we provide a correlation between the unipoly-Frobenius-Genocchi polynomials and the classical Frobenius-Genocchi polynomials.

Containers are gaining popularity in life science research as they provide a solution for encompassing dependencies of provisioned tools, simplify software installations for end users and offer a form of isolation between processes. Scientific workflows are ideal for chaining containers into data analysis pipelines to aid in creating reproducible analyses. In this manuscript we review a number of approaches to using containers as implemented in the workflow tools Nextflow, Galaxy, Pachyderm, Argo, Kubeflow, Luigi and SciPipe, when deployed in cloud environments. A particular focus is placed on the workflow tool’s interaction with the Kubernetes container orchestration framework.

Cryptocurrencies like Bitcoin rely on a proof-of-work system to validate transactions and prevent attacks or double-spending. A new proof-of-work is introduced which seems to be the first number theoretic proof-of-work unrelated to primes: it is based on a new metric associated to the Collatz algorithm whose natural generalization is algorithmically undecidable: the inflation propensity is defined as the cardinality of new maxima in a developing Collatz orbit. It is numerically verified that the distribution of inflation propensity slowly converges to a geometric distribution of parameter $0.714 \approx \frac{(\pi - 1)}{3}$ as the sample size increases. This pseudo-randomness opens the door to a new class of proofs-of-work based on congruential graphs.

This paper presents a configuration of dual output single phase current source inverter with 6 switches for microgrid applications. The inverter is capable of delivering power to two independent set of loads of equal voltages or different voltages at the load end. The control strategy is based on Integral Sliding Mode Control (ISMC). The remote monitoring of the inverter is performed with cyber infrastructure. The cyber physical test bench is developed based on Reconfigurable I/O processor (NI MyRIO-1900) for control and monitoring of the inverter. The inverter prototype is tested in cyber physical test bench in laboratory conditions. The performance of the inverter is analyzed and monitored through the remote system. Also, the inverter is analyzed with different voltage conditions.

Infertility affects approximately 15% of couples worldwide, an estimated 30% of which is related to male factor infertility. Application of low level laser therapy (LLLT) to improve fertility status is a rapidly growing discipline in medicine. Laser therapy triggers a variety of biological processes through interaction with primary cellular photoacceptors. The present review aims at evaluating the literature available in the MEDLINE/ PubMed on cellular and molecular mechanisms of photobiomodulation in the domains of reproductive and veterinary medicine. We primarily focused on the clinical application of laser treatment on seminal quality, in particular its role in promoting spermatozoa motility, as well as the role of phototherapy in modulating assisted reproduction (ART). Additionally, we investigated the strength of evidence in support of the positive impact of photobiomodulation on facilitating ART.

Hydrophilic coatings have recently emerged as a new approach to avoid the adhesion of (bio)organisms on surfaces immersed in water. In these coatings the hydrophilic character is crucial for the anti-fouling (AF) performance. However, this property can be rapidly lost due to the inevitable damages which occur at the surface, reducing the long-term effectiveness of the AF functionality. We report hydrophilic polycarbonate-mPEG polyurethane coatings with tunable hydrophilic properties as well as an excellent and long-term stability in water. The coatings exhibit low protein adhesion values and are able to self-replenish their hydrophilicity after damage, due to the existence of a reservoir of hydrophilic dangling chains incorporated in the bulk. The combination of low T_g and sufficient mobility of the mPEG dangling chains (enabled by chains with higher molecular weight) proved to be crucial to ensure autonomous surface hydrophilicity recovery when the coatings were immersed in water. This coatings and design approach offer new possibilities towards high performance AF coatings with an extended service life-time which can be used in several major applications areas, such as marine and biomedical coatings, with major economic and environmental benefits.

The “stem cells” discipline represents one of the most dynamic areas in biomedicine. While adult marine/aquatic invertebrate stem cell (MISC) biology is of prime research and medical interest, studies on stem cells from organisms outside the classical vertebrate (e.g., human, mouse, zebrafish) and invertebrate (e.g., Drosophila, Caenorhabditis) models have not been pursued vigorously. Marine/aquatic invertebrates constitute the largest biodiversity and the widest phylogenetic radiation on Earth, from morphologically simple organisms (e.g. sponges, cnidarians), to the more complex mollusks, crustaceans, echinoderms and protochordates. These organisms illustrate a kaleidoscope of MISC-types that participate in the production of a large number of novel bioactive-molecules, many of which are of significant potential interest for human health. MISCs further participate in aging and regeneration phenomena, including whole-body regeneration. For years, the European MISC-community has been highly fragmented and scarce ties were established with biomedical industries in attempts to harness MISCs for human welfare. Thus, it is important to: i) consolidate the fragmented European community working on MISCs; ii) promote and coordinate European research on MISC biology; iii) stimulate young researchers to embark on research in MISC-biology; iv) develop, validate, and network novel MISC tools and methodologies; v) establish the MISC discipline as a forefront interest of biomedical disciplines, including nanobiomedicine; vi) establish collaborations with industries to exploit MISCs as sources of bioactive molecules. In order to fill the recognised gaps, the EC-COST Action 16203 “MARISTEM”, has recently been launched. At its initial stage the consortium unites 26 scientists from EC countries, Cooperating countries and Near Neighbor Countries.

This article aims to identify the generating function of modi…ed Apostol type q-Bernoulli polynomials. With the aid of this generating function, some properties of modi…ed Apostol type q-Bernoulli polynomials are given. It is shown that aforementioned polynomials are q-Appell. Hence, we make use of these polynomials to have applications on q-Umbral calculus. From those applications, we derive some theorems in order to get Apostol type modi…ed q-Bernoulli polynomials as a linear combination of some known polynomials which we stated in the paper.

Plant-based essential oils are important natural products rich in volatile compounds, and they have various applications in medicine, food, perfumery and cosmetics. These substances can be produced using various methods, such as steam distillation and solvent extraction. Their chemical composition is influenced by geographical and climatic conditions, production methods, and intrinsic factors. Published articles and literature were scanned to gather the required information. Previous studies have shown that essential oils possess chief health benefits, including antimicrobial, anti-inflammatory, antioxidant, and psychological effects. Consequently, they have wide applications in the food industry as preservatives in food systems and in active packaging, edible coating, probiotic foods, and flavoring. Essential oils can be successfully utilized in flavoring foods and beverages such as cheese, ice cream, and soft drinks. Despite their great antimicrobial and flavoring roles, it is important to further investigate their possible interactions with food components and the physiochemical characteristics of foods flavored with essential oils.

In this research paper, we address the critical role of data security in the rapidly evolving FinTech sector. We explore the challenges and strategies for establishing robust data security systems, emphasizing the consequences of data breaches and common vulnerabilities. The paper highlights the efficacy of technologies like encryption, blockchain, and cloud security, supported by real-world case studies from leading FinTech companies. Additionally, we examine regulatory frameworks and standards essential for maintaining data security. Concluding with the proposal of an integrated security system model, the paper underscores the synergy between technological innovation, regulatory compliance, and proactive risk management in the FinTech industry

The intricate relationship between Gray-Level Co-occurrence Matrix (GLCM) metrics and machine learning model performance underscores the need for rigorous dataset evaluation and selection protocols to ensure the reliability and generalizability of classification outcomes. This study involved a thorough examination of selected publicly available plant diseases datasets, with an emphasis on how well they performed as measured by GLCM metrics. After first classifying the datasets according to their GLCM metrics, dataset_2 (D2) and dataset_5 (D5) were found, respectively, to be the best-performing dataset in all GLCM analyses. The same datasets were then used to train deep learning models, and their classification performances were assessed. A noteworthy association was observed between the results of training deep learning models and the performance ratings derived from GLCM studies. More specifically, dataset_2 (D2) performed best in both GLCM analysis and deep learning model performance, indicating a strong correlation between the accuracy of classification and the textural qualities that GLCM captured. In the context of plant disease identification, in particular, these results highlight the significance of clearly defined dataset selection criteria in deep learning applications. Scholars can improve the accuracy and dependability of deep learning models for diagnosing plant diseases by giving preference to datasets with favorable GLCM metrics. The research also emphasizes the importance of texture features being taken into account in addition to conventional image features, highlighting the necessity of transparency and rigor in dataset selection procedures.

To be used in cutting-edge green and other technologies, rare earth elements (REEs) are in great demand. Rare earth elements (REEs) include the following elements: La, Ce, Pr, Nd, Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu; additionally, they include Sc. Computers, laptops, TVs, generators, DVD players, cell phones, refrigerators, and other electronic equipment that are usually thrown away by their original owners because of their limited lifespan are examples of outdated or end-of-life electronics that make up e-waste. At the moment, these metals are essential to many contemporary devices, from LED light bulbs and wind turbines to cell phones and televisions. The development of new, cutting-edge technologies, especially in the field of electronics, depends on the availability of rare earth elements (REEs), sometimes referred to as the "vitamins" of modern industry. Since e-waste frequently has high concentrations of rare earth elements and is handled in hazardous ways, e-waste may be a significant contributor to the contamination of rare earth elements. Apart from their detrimental effects on the environment, these wastes also result in the loss of precious materials and rare earth elements such as gold, silver, copper, platinum, palladium, and rare earth, among other things. Every year, 50 million tonnes of e-waste are created globally. An enormous amount of e-waste is wasted since only 20% of it is handled correctly worldwide. There have been numerous reports on the recovery and separation of rare earth elements (REEs) from e-waste using various techniques, such as the hydrometallurgical process, siderophores, pyrometallurgical process, bioleaching, and biosorption. According to reports, the demand for rare earth elements (REEs) from clean technologies is expected to reach 51.9 thousand metric tons (kt) of REO in 2030. Nd and Dy, on the other hand, make up 75% and 9% of the world's REE deposits, respectively. REE levels in aquatic settings are rising, particularly in urban areas, in tandem with the growing demand for high-tech applications. Urban wastewater from open sewers and the entrance of a wastewater treatment facility in Cotonou, Benin, was collected, and its rare earth element (REE) contamination was evaluated.

Transdermal drug delivery systems (TDDS) are designed to administer a consistent and effective dose of medication through the patient's skin. These pharmaceutical preparations are self-contained, discrete dosage forms designed to be placed topically on intact skin to release the active component at a controlled rate by penetrating the skin barriers. This medication provides a continuous and prolonged administration of a substance at a consistent rate. TDDS, or transdermal drug delivery system, has gained significant attention as a non-invasive method of administering drugs to vulnerable patient populations, such as pediatric and geriatric patients. This approach is considered easy to administer and helps overcome bioavailability issues associated with conventional drug delivery, which can be hindered by poor absorption and metabolism. TDDS has various advantages compared to conventional methods of drug administration. It is less intrusive, more patient-friendly, and can circumvent first-pass metabolism and the corrosive acidic environment of the stomach that happens when medications are taken orally. Multiple methodologies have been devised to augment the transdermal permeability of diverse pharmaceutical substances. Recent advancements in transdermal drug delivery systems have facilitated the precise delivery of medications to the intended site of action by improving the penetration of drugs through the outermost layer of the skin, known as the stratum corneum, resulting in enhanced drug availability throughout the body. This review seeks to provide a concise overview of the several methods employed in the production of TDDS, as well as their evaluation, therapeutic uses, clinical considerations, and current advancements. These advancements have resulted in the development of intelligent, biodegradable, and highly efficient transdermal drug delivery systems.

Paratuberculosis (PTB) is a chronic granulomatous enteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP) that affects a wide variety of domestic and wild animals. It is considered as one of the diseases with the highest economic impact in the ruminant industry. Despite many efforts and intensive research, PTB control is still controversially discussed and diagnostic and immunoprophylactic tools lack great limitations. Thus, models play a crucial role in understanding the pathogenesis of infection and disease, and in testing novel vaccine candidates. Here, we review the potential and limitations of different experimental approaches currently used in PTB research, focusing on laboratory animals and cell based models. The aim of this review is to offer a vision of the models that have been used and what has been achieved or discovered with each one so that the reader can choose the best model to answer their scientific questions and prove their hypotheses. Also, we bring forward new approaches that we consider worth exploring in the near future.

Atherosclerosis is a chronic systemic inflammatory condition of the vasculature and a leading cause of stroke. Luminal stenosis severity is an important factor in determining vascular risk. Conventional imaging modalities, such as angiography or duplex ultrasonography, are used to quantify stenosis severity and inform clinical care but provide limited information on plaque biology. Inflammatory processes are central to atherosclerotic plaque progression and destabilization. 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a validated technique for quantifying plaque inflammation. In this review, we discuss the evolution of FDG-PET as an imaging modality to quantify plaque vulnerability, challenges to standardization of image acquisition and analysis, its potential application to routine clinical care after stroke, and the possible role it will play in future drug discovery.

Considering the significant interest in the synthesis and various properties of the polymorphs of tin dioxide (SnO2), they are still comparatively rare in modern photovoltaic techniques. The hybrid organic-inorganic lead perovskites have triggered a revolution among solar cell researchers due to their low cost and ultrahigh power conversion efficiency. In this research, the optical properties of seven stable polymorphs (Balakrishnan Kanimozhi et al. ACS omega 7, 12 (2022): 10382-10393) of SnO2 have been investigated using first-principles approaches. The effective mass of stable SnO2 polymorphs has been computed and it is found to vary depending on the specific polymorph and the direction in which it is measured. Moreover, the spectroscopic limited maximum efficiency (SLME) of SnO2 polymorphs was also computed and compared to that of other efficient perovskite solar cells. Both Pnnm and Pbca have equivalent efficiency in comparison to the rutile polymorph. Three of the seven stable polymorphs are effective in solar cell applications. This study is the very first attempt to examine the atomic structure and electronic properties of various SnO2 polymorphs using X-ray absorption near-edge spectroscopy (XANES) at both the Sn-K-edge and O-K-edge wavelengths. Our findings, as mentioned in this paper, may be an important advancement in the understanding of these materials, thereby facilitating the development of more efficient photovoltaic devices.

This study propounds a sustainable alternative to petroleum-based polyurethane (PU) foams aiming to curtail this nonrenewable resource's continued and uncontrolled use. Coconut fatty acid distillate (CFAD) and crude glycerol (CG), both wastes from vegetable oil processes, were utilized for bio-based polyol production for rigid PU foam application. The raw materials were subjected to catalyzed glycerolysis with alkaline-alcohol neutralization and bleaching. The resulting polyol possessed properties suitable for rigid foam application with an average OH number of 215 mg KOH/g, acid number of 7.2983 mg KOH/g, and Gardner color value of 18. The polyol was used to prepare rigid PU foam, and its properties were determined using FTIR, TGA/DTA, and UTM. Additionally, the cell foam morphology was investigated by scanning electron microscope (SEM) in which most of its structure revealed an open-celled network and quantified at 92.71% open cell content using pycnometric testing. The PU foam thermal and mechanical analysis results showed an average compressive strength of 70.59 kPa, thermal conductivity of 46.50 mWm-1K-1, and density of 32.79 kgm-3. These properties showed its applicability as thermal insulating foam, thus, demonstrating the potential use of CFAD and CG in commercial polyol and PU foam production.

In this investigation, Cu-Ni alloys for possible fixed dental prostheses (FDPs), with different aluminum additions were produced using vacuum atmosphere. Annealed alloys (He atmosphere) with low aluminum concentration showed a coarse dendritic structure, while samples with high aluminum concentration showed a refined dendritic structure. Structural defects analyses have shown a relative low vacancy concentrations. Hardness value increases approximately five times for the alloyed samples compared with the as-cast and unalloyed samples. Compression test results have shown a noticeable strengthening improvement, mainly in samples heat treated with 10 at % Al, while samples with 5 at % Al presented also acceptable resistance. Results are discussed in terms of dislocation mobility and hardening precipitation mechanism.

In nowadays, the synthesis of new composite nanomaterials based on graphene oxide (GO) modified with cellulose and its derivatives, as well as nanocellulose, is an important direction and contributes to solve many problems in various fields such as: nanotechnology, information technology, medicine, high-dielectric materials and nanoelectronics. In this work, for the first time, for the production of GO and its membrane with carboxymethylcellulose (CMC), local Kazakhstan “Ognevsky” graphite was used as the initial raw material. In this regard, the preparation of nanocomposites of GO modified with cellulose derivatives, including CMC, attracts great interest from scientists and expands its field of practical application due to the amazing changes of physicochemical properties. In the work, the GO obtained by the Hummers method was modified by CMC, with following study of its physicochemical, structural and electrical characteristics. The GO/CMC membrane was synthesized by mixing 1% GO with crushed solid mass of CMC (0.03 g; 0.06 g; 0.15 g) and then was processed by ultrasound. The surface morphology of the GO/CMC membrane were studied using Scanning electron microscopy (SEM). It has been established that with an increasing in the mass of CMC (0.03 g; 0.06 g; 0.15 g), polymerization of CMC occurs on the surface of GO nanosheets. Cross-sectional micrographs of GO/CMC show the formation of sandwich-like layered structures.

The goal of this paper is to present a low-cost, low-power prototype of a pulsed Ultra Wide Band UWB) oscillator and an UWB elliptical dipole antenna integrated on the same Radio Frequency (RF) Printed Circuit Board (PCB) and its digital control board for Real Time Locating System (RTLS) applications. The design is compatible with IEEE 802.15.4 high rate pulse repetition UWB standard being able to work between 6 GHz and 8.5 GHz with 500 MHz bandwidth and with a pulse duration of 2 ns. The UWB system has been designed using the CST Microwave Studio transient Electro-Magnetic (EM) circuit co-simulation method. This method integrates the functional circuit simulation together with the full wave (EM) simulation of the PCB’s 3D model allowing fast parameter tuning. The PCB has been manufactured and the entire system has been assembled and measured. Simulated and measured results are in excellent agreement with respect to the radiation performances as well as the power consumptions.

In the present work freezing and melting characteristics of water seeded with chemically functionalized graphene nano-platelets in a vertical cylindrical capsule was experimentally studied. The volume percentage of functionalized graphene nano-platelets was varied from 0.1% to 0.5% with an interval of 0.1%. The stability of the synthesised samples were carried out by zeta potential distribution. The thermal conductivity of the nanocomposite samples were experimentally measured using transient hot wire method. A maximum enhancement of ~24% in the thermal conductivity was observed for the 0.5% volume percentage in the liquid state while a ~53% enhancement in the solid state. Freezing and melting behaviour of water dispersed with graphene nanoplatelets were carried out using a cylindrical stainless steel capsule in a constant temperature bath. The bath temperatures considered for studying freezing characteristics were considered to be −6 °C and −10 °C, while to study the melting characteristics the bath temperature was set as 31 °C and 36 °C. The freezing and melting time decreased for all the test conditions when the volume percentage of GnP increased. The freezing rate was enhanced by ~ 43% and ~32% for the bath temperatures of −6 °C and −10 °C respectively at 0.5 vol % of graphene loading. The melting rate was enhanced by ~42% and ~63% for the bath temperature of 31 °C and 36 °C respectively at 0.5 vol % of graphene loading.

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics and knowledge describing the human presence on the planet based mainly on two quantitative factors: i) the spatial distribution (density) of built-up structures and ii) the spatial distribution (density) of resident people. Both factors are observed in the long-term temporal domain and per uniform surface units in order to support trends and indicators for monitoring the implementation of international framework agreements. The GHSL uses various input data including global, multi-temporal archives of fine-scale satellite imagery, census data, and volunteered geographic information. In this paper, we present the characteristics of GHSL information to demonstrate how original frameworks of data and tools rooted on Earth Observation could support Sustainable Development Goals monitoring. In particular, we demonstrate the reach of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for the Sustainable Development Goal 11. Our experiments produce a global estimate for the Land Use Efficiency indicator (SDG 11.3.1) for 10,000 urban centers, calculating the ratio of land consumption to population growth rate that took place between 1990 and 2015. The results of our research demonstrate that there is a potential to lift SDG 11.3.1 from a tier 2 as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata.

Antisense oligonucleotides (ASO), short single-stranded polymers based on DNA or RNA chemistries and synthesized in vitro, regulate gene expression by binding in a sequence-specific manner to an RNA target. The functional activity and selectivity in the action of ASOs largely depends on the combination of nitrogenous bases in a target sequence. This simple and natural property of nucleic acids provides an attractive route by which scientists can create different ASO-based techniques. Over the last 50 years, planned and realized applications in the field of antisense and nucleic acid nanotechnologies have produced astonishing results and posed new challenges for further developments, exemplifying the essence of the post-genomic era. Today the majority of ASOs are chemically modified and/or incorporated within nanoparticles to enhance their stability and cellular uptake. This review critically analyzes some successful cases using the antisense approach in medicine to address severe diseases, such as Duchenne muscular dystrophy and spinal muscular atrophy, and suggests some prospective directions for future research. We also examine in detail the elaboration of unmodified insect-specific DNA insecticides and RNA preparations in the areas of agriculture and forestry, a relatively new branch of ASO that allows circumvention of the use of non-selective chemical insecticides. When considering the variety of successful ASO modifications with an efficient signal-to-noise ratio of action, coupled with the affordability of in vitro oligonucleotide synthesis and post-synthesis procedures, we predict that the next half-century will produce a fruitful yield of tools created from effective ASO-based end products.

Heat metres are used to calculate the consumed energy in central heating systems. The subject of this article is to prepare a method of predicting a failure of a heat meter in the next settlement period. Predicting failures is essential to coordinate the process of exchanging the heat metres and to avoid inaccurate readings, incorrect billing and additional costs. The reliability analysis of heat metres was based on historical data collected over many years. Three independent models of machine learning were proposed, and they were applied to predict failures of metres. The efficiency of the models was confirmed and compared using the selected metrics. The optimisation of hyperparameters characteristics for each of models was successfully applied. The article shows that the diagnostics of devices does not have to rely only on newly collected information, but it is also possible to use the existing big data sets.

Polyesters based advanced thin films have versatile industrial applications, especially in the filed of textiles, packaging and electronics. Recent advances in polymer science and engineering resulted in development of advanced amorphous and semi-crystalline polyesters with exceptional performance compared to conventional polymeric films. Among these, 1,4-cycloheanedimethanol (CHDM) and cyclic monomer-based polyesters have gained considerable attention attention for their exceptional characteristics and potential applications in smart films. This review article provides a comprehensive overview of the recent advances in the synthesis, characterization, and applications of CHDM and cyclic monomer based advanced polymers for smart film applications. It discussed the structure-property relationship of these innovative polyesters and highlights their unique characteristics including thermal, mechanical, and barrier characteristics. Furthermore, this article also emphases the solution, melt, and solid state polymerization of the polymers. Special emphasis is placed on the influence of the addition of 2nd diol or 2nd diacid on the performance characteristics of synthesized polyesters/copolyesters to explore their versatile industrial applications. Additionally, the impact of stereochemistry of the monomers is also explored to optimized the characterization of polyester, suitable for the industrial applications. Furthermore, this article explores the potential of these advanced polyesters to be considered as a potential materials for smart film applications, especially in the filed of flexible electronics. Finally, the article examines the challenges and future recommendations for the development CHDM and cyclic monomer-based polyesters for smart film applications. It discusses potential avenues for further research, including in-depth studies for the synthesis and characterization of polyesters, development of sustainable and biodegradable alternatives cyclic monomers, alternative green approaches for the synthesis of polymers etc. This review article provides a valuable insights for the researcher from academia and industry working in the field of polymer science and materials engineering.

Classical antibacterial drugs were designed to target specific bacterial properties distinct from host human cells to maximize potency and selectivity. These designs were quite effective as they could be easily derivatized to bear next generation drugs. However, the rapid mutation of bacteria and their associated acquired drug resistance have led to the rise of highly pathogenic superbug bacterial strains for which treatment with first line drugs is no match. More than ever, there is a dire need for antibacterial drug design that goes beyond conventional standards. Taking inspiration by the body’s innate immune response to employ its own supply of labile copper ions in a toxic attack against pathogenic bacteria, which have a very low Cu tolerance, this review article examines the feasibility of Cu-centric strategies for antibacterial preventative and therapeutic applications. Promising results are shown for the use of Cu-containing materials in the hospital setting to minimize patient bacterial infections. Studies directed at disrupting bacterial Cu regulatory pathways elucidate new drug targets that can enable toxic increase of Cu levels and perturb bacterial dependence on iron. Likewise, Cu intracellular chelation/prochelation strategies effectively induce bacterial Cu toxicity. Cu-based small molecules and nanoparticles demonstrate the importance of the Cu ions in their mechanism and display potential synergism with classical drugs.

In this paper, we introduce a new formulation based on Floquet (Fourier) spectral analysis combined with a spectral modulation technique (and its spatial form) to study strongly coupled sublattices predefined in the infinite and large finite extent of almost periodic antenna arrays (e.g metasurfaces). This analysis is very relevant for dense massive MIMO, intelligent surfaces, 5G, and 6G applications (used for very small areas with a large number of elements such as millimeter and terahertz waves applications). The numerical method that is adopted to model the structure is the method of moments simplified by equivalent circuits MoM GEC. Other numerical methods (as the ASM array scanning method and windowing Fourier method) used this analysis in their kernel that to treat periodic and pseudo-periodic (or quasi-periodic) arrays.

Matrices and their inverses allow accurate calculations to be produced quickly and compactly and can be used to control any process represented by a system of equations. Singular matrices require extensive workarounds (costing time and money) to solve these systems of equations because they have no inverse. Finding their inverse involves division by zero. Nevertheless, recently a new number set called semi-structured complex numbers was developed to enable division by zero in algebraic equations. The aim of this research was to demonstrate that the inverse of a singular matrix can be found using semi-structured complex numbers. This research reveals (1) Singular matrices and their inverses can be used to find a unique solution to a pair of simultaneous equations that appear to have infinitely many solutions or appear to have no solution; (2) Singular matrices map coordinates in projective space to coordinates in Euclidean space and their inverse maps coordinates in Euclidean space to coordinates in projective space; (3) the inverse of a singular matrix proves that parallel lines in Euclidean space do not intersect but in projective space intersect at a “point at infinity” and (4) collinear lines that intersect at infinitely many points in Euclidean space only intersect at one point in projective space.

This work is the first in literature to tackle the difficult open problem of determining the upper bound and threshold theorem for the TDCDP (time-dependent controller parameter) of the (Fokker Planck Kolmogorov) probability density function. This revolutionary exposition will put control theory and other related inter-disciplinary fields to a higher level towards contemporary control theory. Notably, based on the influential role of control theory in both engineering and industry, this paper will be of great value to all engineering and industry professionals who seek to know more about advanced trends within control theory settings. On the other remit of the spectrum, Fokker Planck Kolmogorov(FPK) equations are of high importance to physicists as well as mathematicians, based on their multiple applicability to information theory, graph theory, data science, finance, economics, and beyond. So, this by default adds more taste and credibility to this study. This leads by nature to introducing a different flavor to this ground-breaking research by highlighting the impact of Fokker Planck Kolmogorov(FPK) to revolutionize crypocurrency,which have received its name because it uses encryption to verify transactions, a new debatable digital payment system that doesn't rely on banks to verify transactions. It’s a peer-to-peer system that can enable anyone anywhere to send and receive payments. The paper ends with closing remarks combined with some challenging open problems and the next phase of research.

Graphene materials synthesized using direct laser writing (laser-induced graphene; LIG) are fa-vorable sensor materials because of their large surface area, ease of fabrication, and cost effec-tiveness. In particular, LIG decorated with metal nanoparticles (NPs) has been used in various sensors, including chemical sensors and electronic and electrochemical biosensors. However, the effect of metal decoration on LIG sensors remains controversial; hypotheses based on computa-tional simulations do not always match experimental results, and even experimental results re-ported by different researchers have not been consistent. In the present study, we explored the effects of metal decorations on LIG gas sensors, with NO2 and NH3 gases as representative oxi-dizing and reducing agents, respectively. To eliminate unwanted side effects arising from metal salt residues, metal NPs were directly deposited by vacuum evaporation. Although the gas sen-sitivities of the sensors deteriorate upon metal decoration irrespective of the metal work function in the case of NO2 gas, they improve upon metal decoration in the case of NH3 exposure. A careful investigation of the chemical structure and morphology of the metal NPs in the LIG sensors shows that the spontaneous oxidation of metal NPs with a low work function changes the be-havior of the LIG gas sensors and that the sensor behaviors under NO2 and NH3 gases follow different principles.

The utilization of gold nanoparticles (AuNPs) has garnered significant attention in recent times, particularly in the field of biomedical research. The utilization of AuNPs in chemical synthesis procedures raises apprehensions regarding their potential toxicity in living organisms, which is inconsistent with their purported eco-friendly and cost-effective aspects. In this investigation, AuNPs were synthesized via the green synthesis approach utilizing Jeju Hallabong peel extract (HPE), a typical fruit variety indigenous to South Korea. The visible-range absorption spectrum of gold nanoparticles from green synthesis (HAuNPs) that are red wine in color occurs at a wavelength of λ = 517 nm. The morphology and particle size distribution were analysed using transmission electron microscopy (TEM) and ImageJ software. The TEM images reveal that the HAuNPs exhibit a high degree of dispersion and uniformity in their spherical shape, with an average size of approximately 7 nm. Moreover, elevating the initial pH level of the mixed solution has an impact on the decrease in particle dimensions, as evidenced by the blue shift observed in the UV-visible spectroscopy absorbance peak. Elevating the reaction temperature may accelerate the synthesis duration. However, it does not exert a substantial impact on the particle dimensions. The outcomes of an avidin-biocytin colorimetric assay provide preliminary analyses of possible sensor tunability using HAuNPs. The cytotoxicity of HAuNPs was evaluated through in vitro studies using the MTT assay on RAW 264.7 cell lines. The results indicated that the HAuNPs exhibited lower cytotoxicity compared to both chemically reduced gold nanoparticles (CAuNPs) and commercially available gold nanoparticles (SAAuNPs).

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization application. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on Surface-Enhanced Raman Spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: 1) integrated Low-Spatial-Frequency LIPSS (LSFL) and High-Spatial-Frequency LIPSS (HSFL), 2) principally LSFL and 3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrate showcased the highest enhancement factor (EF) of 1.38 × 10^6. This pronounced enhancement is attributed to the synergistic effects of Localized Surface Plasmon Resonance (LSPR) and Surface Plasmon Polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to understanding LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms.

This paper presents a proposal for a non-isolated bidirectional converter (NIBC) controlled by a deep neural network (DNN) to enable vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G) charging, which contributes to the development of more efficient and sustainable transportation and energy systems. The DNN controller manages power flow in both directions, making it possible to charge electric vehicles (EVs) and discharge power from EVs to the grid with improved efficiency and performance compared to traditional control methods. The non-isolated topology used in this proposal offers several benefits, including reduced cost, smaller size, and higher efficiency. To train the DNN controller, a large dataset of simulations was used, and the results were validated with a hardware setup. The real-time performance of the DNN controller was compared to a proportional-integral (PI) based controller through simulated results. The findings of the study show that the DNN controller outperforms traditional PI controllers.

This article discusses a transformer-free, high-efficiency DC-DC converter besides renewable energy applications. The traditional buck-boost, classic Zeta, Sepic, and Cuk converter does have the benefits of a simple design, low cost, as well as the capacity to execute voltage step-up and step-down. Conversely, because of the detrimental consequences of the parasitic constraints of the device, the voltage conversion gain of the traditional DC-DC converter is much more restricted and the efficiency is also significantly smaller, whereas this proposed converter does have a higher voltage gain and efficiency because it is used in a single power switch, resulting in reduced switching losses and voltage stress. The said converter's design is very simple, which simplifies the operation control and reduces switching and conduction losses, leading to an efficiency of 97.4 percent. This converter seems to have the same capabilities as the Zeta converter, including continuous desired output current and desired buck-boost operation. Such an article offers the operation principle and steady evaluation, as well as a comparison with other existing high step-up configurations. The proposed converter employs a fuzzy logic controller, which improves the voltage level as well as reduces the time taken to set the voltage output of a conventional PI and ANN controller, especially in comparison to the FLC controller. For deployment, Experimental Result and MATLAB/Simulink has been used, and the modeling results indicate that the proposed controller performance has improved

The influence of the hot isostatic pressing (HIP) post-processing step on structural and phase changes, porosity healing and mechanical strength in a powder metallurgy Ti35Nb2Sn alloy was studied. Powders were pressed at room temperature at 750 MPa, and then sintered at 1,350°C in a vacuum for 3 h. The standard HIP process at 1,200°C and 150 MPa for 3 h was performed to study its effect on a Ti35Nb2Sn powder metallurgy alloy. The influence of the HIP process and cold rate on density, microstructure, the quantity of interstitial elements, mechanical strength and Young's modulus was investigated. HIP post-processing for 2 h at 1,200°C and 150 MPa led to greater porosity reduction and a marked retention of the β phase at room temperature. The slow cooling rate during the HIP process affected phase stability, with a large amount of α”-phase precipitate, which decreased the titanium alloy’s yield strength.

Early reports demonstrated the presence of cells with stem-like properties in bone marrow, with these cells having both hematopoietic and mesenchymal lineages. Over the years, various investigations have purified and characterized mesenchymal stromal/stem cells (MSCs) from different human tissues as cells with multi-lineage differentiation potential under the appropriate conditions. Due to their appealing characteristics and potential, MSCs are leveraged in many applications including medicine, oncology, bioprinting and as recent as treatment of COVID-19. To date, reports indicate mesenchymal stromal/stem cells have varied differentiation capabilities into different cell types and demonstrate immunomodulating and anti-inflammatory properties. Reports indicate that different MSCs microenvironments or niche and the resulting heterogeneity may influence their behavior and differentiation capacity. The potential clinical applications of mesenchymal stromal/stem cells have led to an avalanche of research reports on their properties and hundreds of clinical trials being undertaken. The future looks bright and promising for mesenchymal stem cell research with many clinical trials under way to prove their utility in many applications and in the clinic. This report provides an update on the potential broader use of mesenchymal stromal/stem cells, review early observations of the presence of these cells in the bone marrow and their magnificent differentiation capabilities and immunomodulation.

We introduce the Symplectic Structure of Information Geometry based on Souriau’s Lie Group Thermodynamics model, with a covariant definition of Gibbs equilibrium via invariances through co-adjoint action of a group on its moment space, defining physical observables like energy, heat, and moment as pure geometrical objects. Using Geometric (Planck) Temperature of Souriau model and Symplectic cocycle notion, the Fisher metric is identified as a Souriau Geometric Heat Capacity. Souriau model is based on affine representation of Lie Group and Lie algebra that we compare with Koszul works on G/K homogeneous space and bijective correspondence between the set of G-invariant flat connections on G/K and the set of affine representations of the Lie algebra of G. In the framework of Lie Group Thermodynamics, an Euler-Poincaré equation is elaborated with respect to thermodynamic variables, and a new variational principal for thermodynamics is built through an invariant Poincaré-Cartan-Souriau integral. The Souriau-Fisher metric is linked to KKS (Kostant-Kirillov-Souriau) 2-form that associates a canonical homogeneous symplectic manifold to the co-adjoint orbits. We apply this model in the framework of Information Geometry for the action of an affine Group for exponentiel families, and provide some illustrations of use cases for multivariate Gaussian densities. Information Geometry is presented in the context of seminal work of Fréchet and his Clairaut-Legendre equation. Souriau model of Statistical Physics is validated as compatible with Balian gauge model of thermodynamics. We recall the precursor work of Casalis on affine group invariance for natural exponential families.

In this study, we explored the manipulation of optical properties in the terahertz (THz) frequency band of radio-frequency (RF) sputtered indium-tin-oxide (ITO) thin-films on highly resistive silicon substrate by rapid thermal annealing (RTA). The optical constants of as-deposited and RTA-processed ITO films annealed at 400°C, 600°C and 800°C are determined in the frequency range of 0.2 to 1.0 THz. The transmittance can be changed from ~ 27% for as-deposited to ~ 10% and ~ 39% for ITO films heat-treated at different annealing temperatures, T_a’s. Such variations of optical properties in the far infrared for the samples under study are correlated with their mobility and carrier concentration, which are extracted from Drude-Smith modeling of THz conductivity with plasma frequency, scattering time and the c-parameters as fitting parameters. Resistivities of the films are in the range of 10^-3 to 10^-4 W-cm, confirming that annealed ITO films can potentially be used as transparent conducting electrodes for photonic devices operating at THz frequencies. The highest mobility, m = 47 cm²/V∙s, with carrier concentration, N_c = 1.31´10²¹ cm^-3, was observed for ITO films annealed at T_a = 600°C. The scattering times of the samples were in the range of 8 – 21 fs, with c-values of -0.63 to -0.87, indicating strong back scattering of the carriers, mainly by grain boundaries in the polycrystalline film. To better understand the nature of these films, we have also characterized the surface morphology, microscopic structural properties and chemical composition of as-deposited and RTA-processed ITO thin-films. For comparison, we have summarized the optical properties of ITO films sputtered on fused silica substrates, as-deposited and RTA-annealed, in the visible transparency window of 400-800nm. The optical bandgaps of the ITO thin films were evaluated with a Tauc plot from the absorption spectra.

This literature review offers a comprehensive analysis of antenna designs tailored for 6G applications and THz communications. Various antenna types, including elliptical lens, WHEMS, grid array, CP horn, Quasi Yagi-Uda, patch, transmit array, Vivaldi patch, SRR slotted waveguide array, RCA, and Cassegrain antennas, are scrutinized in terms of their dimensions, characteristics, frequency ranges, and materials. The study highlights existing works on antenna design for 6G applications, exploring different fabrication techniques like PCB technology, LCP technology, Topas fabrication, Wire-cutting EDM, 3D Printing, Laser-drilling processes, and CNC machining. Notably, PCB technology exhibited promise with antennas such as WHEMS, patch, and Vivaldi patch, achieving significant bandwidth and gain. However, gaps remain in research, urging further exploration into additional fabrication methods and antenna designs to meet the demands of 6G networks. The study underlines the need for advanced, intelligent antennas capable of higher bandwidth and better performance in view of future wireless communications technologies such as 6G.

The fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing kThe fractal dimension of is identified in this paper. More importantly, the undertaken research has shown how affects the Koch snowflake . The study has demonstrated the existence of negative values of (Koch snowflake), which connects to a considerable number of extremely intriguing mathematical and physical research areas. The information-theoretic impact on the Sierpiniski Gasket dimension , which corresponds to , was treated in a more fundamental way. Notably, the credibility of this current study adds to the existing knowledge for the information- theoretic fractal dimensions. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.applicative note, this paper offers some potential applications of fractal dimension to smart cities. The investigation of the threshold theorems for and in terms of the triad is part of the next study phase. Additionally, investigating the newly obtained 's corresponding arbitrary Sierpinski Gasket for the first time.

GNSS is nowadays a standard tool for monitoring and studying the Earth’s dynamic environment. However, the development of dense GNSS measurements remains limited in many experiments by the cost of geodetic-class equipments allowing to achieve the high precision required by many applications. Recently, multi-constellation, multi-frequency, low-power and, above all, less expensive GNSS electronic chips have become available. We present a prototype of a low-cost, open-source multi-GNSS station. Our prototype comprises a dual-frequency GNSS chip, a calibrated antenna, a Raspberry Pi card and a 4G key for data transmission. The system is easy to deploy in the field and allows precise positioning in real time and post-processing. We assess the performance of our prototype in terms of raw data quality, and quality of the obtained high rate and daily position one-year-long time series. Our results demonstrate a quality equivalent to geodetic-class equipment and better quality than other low-cost systems proposed so far.

The paper explores the Kullback-Leibler divergence formalism (KLDF) applied to the stable MG1 queue manifold. More potentially, both service time probability and cumulative functions which make KLDF exact are obtained. The credibility of KLDF is justified through consistency axioms. Some potential applications of Kullback-Leibler divergence to Biometry are presented. The paper concludes with closing remarks combined with some challenging open problems and the next phase of research.

This work presents a unique two-element high-isolated orthogonally CPW-fed UWB Multiple Input Multiple Output (Ultra-wideband) antenna. The antenna is supported by the 52.8 × 29 mm2 FR-4 substrate, which has a dielectric constant of 4.3 and a thickness of 1.6 mm. The suggested MIMO antenna reduces mutual coupling by separating the two single UWB antennas that make up the antenna. The suggested antenna achieves a voltage standing wave ratio (VSWR) of less than two and more than 86% radiation efficiency over the whole range of interest. The antenna's performance is assessed using both modeling and experimentation. Return loss, efficiency, gain, bandwidth, and Voltage Standing Wave Ratio (VSWR) are all factors in which the design performs well. The suggested antenna is evaluated using the CST Microwave Studio. The antenna prototype model is constructed, tested, and measured in order to validate the simulation return-loss results. There is good agreement between the measured and simulated results.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated in microchannel structures and characterized with various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was post-processed using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of -47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg grating-based waveguide sensor demonstrates high potential for applications based on lab-on-a-chip concept.

A simple method is presented for the continuous generation of carbon nanotube forests stably anchored on stainless-steel surfaces using a reactive-roll-to-roll (RR2R) configuration. No addition of catalyst nanoparticles is required for the CNT-forest generation, the stainless-steel substrate itself being tuned to generate the catalytic growth sites. The process enables very larges surfaces covered with CNT forests having individual CNT roots anchored to the metallic ground through primary bonds. Fog water harvesting is demonstrated and tested as one potential application using long CNT-covered wires. The RR2R is performed in the gas phase, no solution processing of CNT suspensions is used contrary to usual R2R CNT-based technologies. Full or partial CNT-forest coverage provides tuning of the ratio and shape of hydrophobic and hydrophilic zones on the surface. This enables optimization of fog water harvesters for droplet capture through the hydrophobic CNT forest, and water removal from the hydrophilic SS surface. Water recovery tests using small harp-type harvesters with CNT-forest generate water capture of up to 2.2 g/cm2h under ultrasound-generated fog flow. The strong CNT root anchoring on the stainless steel surfaces provides opportunities for (i) robustness and easy transport of the composite structure, (ii) chemical functionalization and/or nanoparticle decoration of the structures, and opens the road for a series of applications on large scale surfaces, including fog harvesting.

In this study, the effect of ZnO nanoparticles (Zn NPs) on the performance of epoxy resin composites was investigated. The new ZnO/epoxy resin composites were synthesized using halloysite nanotubes (HNT) and different types of ZnO nanoparticles (commercial ZnO and ZnO-ODTES). These ZnO nanoparticles were utilized for intending to enhance the interfacial bonding between the epoxy resin and the reinforcement. Various methods such as FTIR, TGA, DSC, TEM-EDX, and Nanoindentation analyses were used to prove that the ZnO nanoparticles can improve the properties of epoxy resin composites. The thermal properties of the epoxy resin composites were enhanced to a greater extent by the addition of ZnO NPS. DSC testing proved that the epoxy resin composites modified with ZnO NPS are more flexible and elastic than unmodified epoxy resin. It was seen that the epoxy resin modified with ZnO-ODTES shows a much improved hardness and penetration depth compared to the other samples. These findings can pave the way for the developing of ZnO-based marine coatings with improved properties.

The Necessity of Human resources beyond perception of human understanding towards the Evaluation of video quality or Data screening methodology is conducted based on human perception level since it is concerned with how visual content is perceived by a observer based on observations with his/ her perception on a particular video sequence. Therefore, we considered that the subject has to grade the encoded video sequences under certain test environment conditions based on ITU-Recommendations. Since Human perception is considered as the true judgment and precise measurement of visual content, data screening has became quite essential and quite comfortable to general public due to introduction of User Experience(UX) concept by User Experience community. The translations of A recurrent neural network is based on certain principles, for instance we considered natural language processing which is certainly adaptable towards understanding sequential data and use patterns to predict the consistency within observers. In our research, we adapted principles based on Recurrent Neural Networks while assuming consistency within observers for predicting video quality within data screening environment towards subjective experiments. Moreover,this research work explores the trade offs between Human perception on visual content and consistency of observations within individual observer.

This article sets out to examine how digital twins have been used in a multi-national corporation, what technologies have been used, what benefits delivered and the significance of people and process related issues in achieving successful implementation. A qualitative, inductive research method is used, based on interviews provided by key personnel involved in three digital twin projects. The article concludes that digital twin projects are likely to involve incremental rather than disruptive change, and that successful implementation is usually underpinned by ensuring technology, people and process change factors are progressed in a balanced and integrated fashion. Building upon existing frameworks, three “properties” are identified as being of particular value in digital twin projects - workforce adaptability, technology manageability and process agility – and a related set of steps and actions is put forward as a template and point of reference for future digital twin implementations. The findings are a contribution to the developing theory around digital twins and digitalization in general, and are also of relevance to professionals embarking on DT projects.

This study focused on the optimization of the flexural strength of bio-composite samples of palm kernel, whelks, clams, periwinkles shells and bamboo fiber, reinforced with resin for engineering applications. The aim of the study was to: formulate different samples of bio-composite reinforce with resin for engineering applications and to evaluate the flexural strength, of the fabricated composite. The hand lay-up technique was used for the composites produced by incorporating different percentage compositions of the shells/fiber (10%, 15%, 20%, 25% and 30%) into varied proportions of epoxy resin and catalyst. The cured samples after 24hours were subjected to tensile, impact, flexural and water absorption test. The experiments were conducted using Taguchi optimization method L25 (5x5) with five design parameters and five level combinations in Minitab 18 statistical software. The results showed that the average values of flexural was 114.87MPa when compared to the unreinforced of 72.33MPa bio-composite. The study recommended that agricultural waste like palm kernel shells, whelk shells, clams, periwinkle shells and bamboo fiber, should be converted into important engineering applications.

Developing a low-cost wireless energy meter with power quality measurement for smart grid applications represents a significant advancement in efficient and accurate electrical energy monitoring.In increasingly complex and interconnected electrical systems, this device is essential in various applications, such as smart grids, enabling real-time energy usage monitoring. In such a context, smart meters expand the possibilities for sustainable and efficient energy use and promote better utilization of energy sources, especially non-renewable ones. According to the 2020 International Energy Agency (IEA) research, non-renewable energy sources represent 65% of the global total. The smart meter developed in this work is built based on the ESP32 microcontroller and easily accessible components, using a user-friendly development platform that offers a cost-effective solution while ensuring reliable performance. The main objective of the smart meter development was to enhance the software and simplify the hardware. Unlike traditional meters that perform electrical parameter calculations using complex hardware circuits, this project performed the calculations directly on the microcontroller. This approach reduced the complexity of the hardware, simplifying the meter’s design. With the high-performance processing capability of the microcontroller, efficient and accurate calculations of electrical parameters were achieved without the need for additional circuits. This software-driven approach with simplified hardware brought benefits such as reduced production costs, lower energy consumption, and increased meter development and updates flexibility. Furthermore, the integrated wireless connectivity in the microcontroller enables the transmission of collected data to remote monitoring systems for later analysis. The developed smart meter offers cost, energy efficiency, and flexibility benefits. It represents an innovative, efficient, and versatile solution for smart grid applications.