The development in the field of ceramics has been increasing over the past several decades. Among all of the dental ceramics, zirconia ceramics show very good mechanical properties and a significant improvement in mechanical function. However, it is properly established that each step of the fabrication process of zirconia ceramics must be controlled to achieve the expected mechanical properties. These steps include the block constructing, sintering process, machining and surface processing. Recent advances have focused on zirconia ceramics in forming and sintering processes, mechanical properties, combining with various materials, and on surface processing. All these items provide conceptions about the formability and machinability of the zirconia. Until now, very excellent studies have been done to specify the evolution of microstructures, phase and mechanical properties of zirconia ceramics during the sintering process. However, more studies are required in this field. This paper aims to demonstrate general views and various studies in the field of zirconia ceramics. The properties, applications and tests performed and the recent developments in the field of zirconia bioceramics are discussed.

In this paper, we study a generalised CIR process with externally-exciting and self-exciting jumps, and focus on the distributional properties and applications of this process and its aggregated process. The first and second moments of this jump-diffusion process are used to calculate the insurance premium based on mean-variance principle. The Laplace transform of the aggregated process is derived, and this leads to an application for pricing default-free bonds which could capture the impacts of both exogenous and endogenous shocks. Illustrative numerical examples and comparisons with other models are also provided.

Diseases in articular cartilages have affected millions of people globally. Although the biochemical and cellular composition of articular cartilages is relatively simple, there is the limitation in self-repair ability of cartilage. Therefore, developing the strategies for cartilage repair is very important. Here, we reported a new manufacturing process of water-based polyurethane based photosensitive materials with hyaluronic acid and applied the materials for 3D printed customized cartilage scaffolds. The scaffold has high cytocompatibility and is one that closely mimics the mechanical properties of articular cartilages. It is suitable for culturing human Wharton's jelly mesenchymal stem cells (hWJMSCs) and the cells showed an excellent chondrogenic differentiation capacity. We consider that the 3D printing hybrid scaffolds may have potential in customized tissue engineering and facilitate the development of cartilage tissue engineering.

Red raspberry fruit production is increasing worldwide due to the growing consumer interest in foods with high antioxidant properties. However, raspberries are very perishable fruit with a short shelf life. Chitosan applications have shown promising results in promoting the storage of different berry fruit. This work aimed at analysing the effects of chitosan applied in pre- and/or post-harvest on the quality and antioxidant properties of raspberry fruit during the cold storage and room temperature conditions (i.e., 6 d at 4 °C and 3 d at 20 °C, respectively). Pre-harvest chi-tosan applications reduced fruit weight loss during cold storage and room temperature condi-tions but also reduced fruit decay at room temperature conditions. Furthermore, pre-harvest treatments with chitosan increased the total phenol and anthocyanin contents and promoted the highest total antioxidant activity with respect to other treatments. Of note, after the cold storage, post-harvest chitosan application drastically reduced the development of fungi that cause fruit decay, thus minimizing the potential risk of mycotoxin production. Overall, this study demon-strates that applications of chitosan in pre-harvest are sufficient to ensure the goal of maintaining and/or increasing the quality and antioxidant properties of fruit during cold storage and room temperature conditions.

The use of analytical techniques is important and critical in all areas of REE research such as exploration, mining, extraction, and metallurgical activities at different stages. At every stage of these activities, rock, ore, mineral, and other related materials have to be analysed for their REE contents in terms of elemental, isotopic, and mineralogical concentrations using different analytical techniques. Spectacular developments have taken place in the area of analytical instrumentations during the last four decades, with some of them having shrunk in size and become hand-held. Among laboratory-based techniques, F-AAS, GF-AAS, ICP-OES, and MP-AES have become very popular. Because of high sensitivity, less interference effects, and ease of use. ICP-MS techniques such as quadrupole-ICP-MS, ICP-MS/MS, ICP-TOF-MS, MH-ICP-MS, HR-ICP-MS, and MC-ICP-MS, with both solution nebulisation as well as direct solid analysis using laser ablation sample introduction methods, have become extremely popular for REE analysis. For direct analysis of solids INAA, XRF, and LIBS techniques besides LA-based ICP-MS techniques are being extensively utilised. LIBS technique in particular requires little to no sample preparation. TIMS, SIMS, and SHRIMP techniques are being used for isotopic as well as dating REE depots. Portable analytical techniques such as pXRF, pLIBS, and Raman spectrometers are able to do in situ analysis even in the field helping to take fast decisions during exploration studies. At present hyperspectral remote sensing techniques including hand-held, drone, and satellite-based techniques have become very popular in REE exploration studies because of their ability to cover larger areas in a limited time and thus became very cost-effective. Deployment of microanalytical devices/sensors mounted in remotely operated vehicles (ROV) is being successfully utilized in detecting REE-rich deposits in the deep oceans. Providing updated in-depth information on all these important aspects with suitable examples, especially from the point of view of REE research studies is the focal point of this review article.

Decades of research identified numerous gene biomarkers of cardiac diseases whose restored sequence or/and expression level was hoped to recover the normal cardiac function. However, each human has unique and dynamic pathophysiological characteristics resulting from the unrepeatable combination of favoring factors such are: race, sex, age, medical history, diet, stress, exposure to toxins, habits etc. As such, no treatment fits everybody and finding personalized solutions is a top priority for medicine of 21st century. The Genomic Fabric Paradigm (GFP) provides the most theoretically possible comprehensive characterization of the transcriptome, its alterations in disease and recovery following a treatment. By attaching to each gene the independent average expression level, expression variation and expression coordination with each other gene, GFP delivers thousands times more information than the traditional analysis. This report presents the theoretical bases of the GFP and some applications to our microarray data from mouse models of post ischemic, and constant and intermittent hypoxia-induced heart failure. The GFP analyses revealed novel transcriptomic aspects of the gene expression control and networking under ischemic conditions. Through all-inclusive characterization of the transcriptome and the unrepeatable gene hierarchy in each condition, GFP is an essential avenue towards development of a truly personalized cardiogenomic therapy.

This work discusses laboratory measurements of atomic and diatomic molecular species in laser-plasma generated in gases. Noticeable self-absorption of the Balmer series hydrogen alpha line occurs for electron densities of the order of one tenth of standard ambient temperature and pressure density. Emission spectra of selected diatomic molecules in air or specific gaseous mixtures at or near atmospheric pressure reveal minimal plasma re-absorption. Abel inversion of the plasma in selected gases and gas mixtures confirm expansion dynamics that unravel regions of atomic and molecular species of different electron temperature and density. Time resolved spectroscopy diagnoses self-absorption of hydrogen alpha and hydrogen beta lines in ultra-high pure hydrogen gas. Radiation from a Nd:YAG laser device induces micro-plasma for pulse widths in the range of 6 ns to 14 ns, energies in the range of 100 mJ to 800 mJ, and for peak irradiance of the order 1 to 10 TW/cm². Atomic line profiles yield electron density and temperature from fitting of line profiles to wavelength and sensitivity corrected spectral radiance data. Analysis of measured diatomic emission data yields excitation temperature of primarily molecular recombination spectra. Applications of the laboratory experiments extend to investigations of stellar astrophysics white dwarf spectra.

Titanium dioxide (TiO₂) micro and nano architectures have been intensively studied in the past years because of many varied applications in environmental, energy conversion, and storage fields, such as heterogeneous catalysis, dye-sensitized solar cells, lithium/sodium ion batteries, lithium-sulfur (Li-S) batteries, and bio-nanotechnology, etc. Especially the surface and interface structures in the TiO₂ structures play important roles in those applications. This mini review article focuses on TiO₂ micro and nano architectures with the prevalent crystal structures (anatase, rutile, brookite, and TiO₂(B)), and summarizes major advances in the surface and interface engineering and applications in environmental and electrochemical applications. We present the principles and growth mechanisms of TiO₂ nanostructures via different strategies, with an emphasis on rational control of the surface and interface structures. We further discuss the applications of TiO₂ micro and nano architectures in photocatalysis, lithium/sodium ion batteries, and Li-S batteries. Throughout the discussion, the relationship between the device performance and the surface structures of TiO₂ micro/nano structures will be highlighted. Then we discuss the phase transitions of TiO₂ nanostructures and possible strategies of improving the phase stability. The review concludes with a perspective on the current challenges and future research directions.

Alpha emitters like plutonium pose severe health risks when ingested, damaging DNA and potentially causing cancer. Traditional detection methods require proximity within millimeters of the contamination source, presenting safety risks and operational inefficiencies. Long-range detection through alpha radioluminescence (RL) offers a promising alternative. However, most of the previous experiments have been carried out under controlled conditions that preclude the overwhelming effect of ambient light. This study demonstrates successful detection of a 3 MBq alpha emitter in an open environment using a newly developed, lightweight compact alpha camera. This camera incorporates a deep-cooled CCD and a specially designed lens system with a low f-number to maximum the signal intensity. The lens was also designed to minimize blue shift effects of filters. Nighttime imaging was achieved with a dual-filter system using a sandwich filters assembly centered at 337 nm and 343 nm for capturing alpha RL and subtracting background light, respectively. At night, the alpha source was detected from 1 meter away within one minute. The system was also evaluated under simulated urban lighting conditions. For daytime imaging, a stack of tilted 276 nm short pass filters minimized sunlight interference, enabling clear detection of the alpha source at 70 cm within 10 minutes under indirect sunlight. This research not only underscores the viability of long-range optical detection of alpha emitters for environmental monitoring and scientific research but also highlights its ability to enhance nuclear safety and public health in real-world settings.

The Model-View-Controller (MVC) architecture, a cornerstone of modern software engineering, offers a robust framework for developing dynamic user interfaces. This paper conducts a broad analysis of MVC’s deployment across various sectors, emphasizing its critical role in technological advancement and market integration. By examining implementation strategies in web development, mobile applications, and enterprise solutions, the study illustrates how MVC enhances application manageability, promotes efficient code reuse, and facilitates parallel development. The paper explores the adoption of MVC principles within major technologies such as Java, .NET, and JavaScript frameworks, underlining its widespread acceptance. Additionally, the analysis covers the preferential use of MVC frameworks within diverse market sectors including technology enterprises, educational institutions, e-commerce, and financial services, which leverage MVC for superior data management and user experience. Emerging trends such as the shift towards the Model-View-ViewModel (MVVM) architecture and the integration of MVC with artificial intelligence and machine learning technologies are also discussed. This comprehensive review not only reaffirms MVC’s enduring relevance but also its adaptive evolution in response to emerging technological demands and market needs.

As the global transition towards renewable energy accelerates, the integration of grid-scale energy storage systems has become increasingly critical for stabilizing energy supply and enhancing grid reliability. Among various storage technologies, lithium-ion batteries stand out for their high energy density, scalability, and relatively low environmental impact. This study investigates the performance and longevity of lithium-ion batteries in grid-scale applications, focusing on the impact of operational parameters such as cycling frequency, depth of discharge, temperature fluctuations, and charging/discharging rates. Employing a mixed-methods approach, we combined quantitative analysis of performance metrics (cycle life, capacity fade, efficiency) with qualitative assessments from case studies of existing grid-scale projects. Our findings reveal that while lithium-ion batteries exhibit robust performance in grid-scale storage, their longevity and efficiency are significantly influenced by operational conditions. Specifically, temperature management and optimized cycling strategies were identified as key factors in mitigating degradation and extending battery life. This research provides a comprehensive understanding of lithium-ion battery behavior in grid-scale environments, offering valuable insights for the design, optimization, and management of energy storage systems. By addressing the challenges of battery performance and longevity, our study contributes to the development of more sustainable and reliable grid storage solutions, facilitating the broader adoption of renewable energy sources.

A labyrinth metamaterial wall with glass coverage is measured in a reverberating chamber and after its installation in a restaurant. Glass is used to meet two aims, namely acoustic absorption and visual design demands. The wall consists of five multiple labyrinth elements of 1.83 m$^2$ each. Glass was taken to make the wall act as a room lightning device where a translucent cover material is needed. Absorption measurements show about four times improved absorption compared to typical glass. Due to the metamaterial behavior, absorption is high in the low-frequency range below 300 Hz where damping is problematic with traditional materials. Especially in this range, the glass metamaterial wall is an excellent compromise between room acoustic and visual design demands, as loud low-frequencies make visitors speak louder and experience less intimacy with additionally reduced speech intelligibility. For mid-frequencies, absorption is shown less effective and improvements are discussed.

Organ-on-a-chip (OOC) is an emerging technology that simulates an artificial organ within a microfluidic cell culture chip. Current cell biology research focuses on in vitro cell culture due to various limitations of in vivo testing. Unfortunately, in vitro cell culture fails to provide an accurate microenvironment, and in vivo cell culture is expensive and has historically been a source of ethical controversy. OOC aims to overcome these shortcomings and provide the best of both in vivo and in vitro cell culture research. The key component of the OOC design is utilizing microfluidics to ensure a stable concentration gradient, dynamic mechanical stress modeling, and accurate reconstruction of a cellular microenvironment. OOC also has the advantage of complete observation and control of the system, which is impossible to recreate in in vivo research. Multiple throughputs, channels, membranes, and chambers are constructed in a polydimethylsiloxane (PDMS) array to simulate various organs on a chip. Various experiments can be performed utilizing OOC technology, including drug delivery research and toxicology. Current technological expansions involve multiple organ microenvironments on a single chip, allowing for studying inter-tissue interactions. Other developments in the OOC technology include finding a more suitable material as a replacement for PDMS and minimizing artefactual error and non-translatable differences.

In this manuscript, we first introduce some properties of r-fuzzy soft α-open sets in fuzzy soft topological spaces based on the manuscript Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). In addition, we define the concepts of fuzzy soft α-closure (α-interior) operators, and investigate some properties of them. Furthermore, the concept of r-fuzzy soft α-connected sets is defined and characterized with help of fuzzy soft α-closure operators. Thereafter, we introduce and study the concepts of fuzzy soft almost (weakly) α-continuous mappings, which are weaker forms of fuzzy soft α-continuous mappings, and we discuss some properties of fuzzy soft α-continuity. Moreover, we establish that fuzzy soft α-continuity → fuzzy soft almost α-continuity → fuzzy soft weakly α-continuity, but the converse may not be true. It is also we show that the composition is fuzzy soft almost α-continuous mapping if, is fuzzy soft α-continuous mapping and is fuzzy soft almost continuous mapping. Finally, some new types of compactness via r-fuzzy soft α-open sets are defined, and the relationships between them are examined.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

In response to the growing need for efficient energy conversion technologies, this pa-per introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically de-signed for high-efficiency conversion of waste heat into electrical energy. Unlike conven-tional flat plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring ther-moelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion. Comprehensive simulations and analyses form the core of this study, where the per-formance of the TTEG is rigorously compared with traditional FTEGs. These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat plate counterparts but also presents a scalable and adaptable so-lution for waste heat recovery in a wide range of industrial and automotive applications. This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.

The requirement for developing tools capable of detecting and monitoring heavy metals (HMs) has recently taken on more significance due to worries about their toxic effect on human health and aquatic habitats. In this study, a simple electrochemical sensing carbon paste electrode (CPE) based on composite of Zinc/Iron layered double hydroxide (LDH) and polyaniline (PANI) was developed for the determination of lead ions in aquatic solutions. For this purpose, Zn-Fe LDH/PANI was prepared and characterized by Fourier transform infrared (FTIR), X ray diffraction (XRD), and scanning electron microscopy (SEM). Modified carbon electrode based Zn-Fe LDH/PANI was electrochemically characterized compared with unmodified electrode in FCN as a redox probe using cyclic voltammetry (CV). Thus, Zn-Fe LDH/PANI was utilized as sensing material for the electrochemical determination of lead ions using differential pulse voltammetry (DPV). Zn-Fe LDH/PANI/CPE show limits of detection (LOD) and quantification (LOQ) of 167.8 nM and 559.4 nM, respectively. Zn/Mg/Fe LDH was prepared using co-precipitation method and characterized by XRD, FTIR, SEM and BET, used for removal of Pb+2 ions. Removal process was investigated at different conditions as pH, metal ion concentrations, starting adsorbent dose at first and contact time. Zn/Mg/Fe LDH was evaluated as an effective adsorbent material for lead ions elimination in aquatic solutions, with capacity of adsorption 700 mg/g. The elimination of lead ions on Zn/Mg/Fe LDH fitted the pseudo first-order kinetics model and the isotherm was matched with Langmuir model. Studies revealed that the ideal removal conditions were pH = 5.0, an adsorbent mass of 0.05 g, and 20 ml of 50 ppm metal ion concentration at 60 min. The Zn-Fe LDH/PANI composite also showed potential anti-cancer properties against lung cancer cells (A549) while maintaining safety for normal lung fibroblast cells (WI-38). Collectively, advancements in electrochemical sensors offer promising solutions for lead ion detection, with wide-reaching applications in wastewater treatment and cytotoxicity assessment. These innovations have the potential to enhance environmental monitoring and public health safety.

This review will deal with the most relevant unmet needs and clinical questions concerning scintigraphy with bone tracers in ATTR-CA, providing expert opinions on possible future developments in the clinical application of these radiotracers, in order to offer practical information for interpretation of nuclear images to physicians involved in the care of patients with this ATTR-CA.

Vertical III-V semiconductor nanowires have shown promising absorption of light for solar cell and photodetector applications. The absorption properties can be tuned through the choice of III-V materials and geometry of the nanowires. Here, we review recent progress in the design of the absorption properties of both individual nanowires and nanowire arrays. Future directions for the research field are proposed.

Mice are one of the frequently used animal models in science research whose behavioral characteristics can provide much valuable information in biology, neuroscience, and pharmacology. Nowadays, artificial intelligence is widely used in mice behavior analysis. Integrated AI systems such as ChatGPT and VisualGPT are already available, and we discuss the feasibility of MiceGPT to help researchers identify and classify mouse behavior more easily. We review the applications of mice behavior analysis, analyze the tasks of deep learning on these applications based on an AI pyramid, and finally summarize the AI approaches to solve these tasks. Based on these summaries, we propose three MiceGPT architectures to demonstrate the theoretical feasibility of MiceGPT.

The contribution aims to bring forth a novel synthesis route in developing transparent UV-LED curable coatings accounting various exposure options. A selection of perfluoropolyether (PFPE)-urethane methacrylate and acrylate resins, free-radical photo-initiator Omnirad 2100, and two distinct silane based crosslinking agents were blended under a weight ratio of 75:20:5 (without crosslinker) and 70:15:5:10, respectively. The coatings were cured under a UV-LED 4 x 3 matrix light emitting source, in a chamber under controlled atmosphere, by means of an in-house developed conveyor belt type platform, at different conveyor belt speed (5, 50, 150, 250, and 500 mm/s). The morphologies of fabricated coatings were characterized by FTIR revealing high conversion rates (e.g., from 98 to 100%) for increased exposure time as resulted from the 5 or 50 mm/s values, on all combinations. Dynamic-mechanical and optical properties of UV-LED cured transparent coatings were also investigated. A negative shift of a glass transition temperature values with a decrease in exposure time, in all combinations, from about 60 °C to 30 °C, along with storage moduli lowering in the glassy plateau further favor on higher exposure times for curing. The refractive indices of polymers were from 1.38 to 1.40, whereas the thermo-optic coefficients are showing minor changes around value of 2.55∙10-4 K-1.

Localized surface plasmon resonance (LSPR) based sensors exhibit enormous potential in the areas of medical diagnosis, food safety regulation and environmental monitoring. While, the broadband spectral lineshape of LSPR hampers the observation of wavelength shifts in sensing processes, thus preventing their widespread applications in sensors. Here, we describe an improved plasmonic sensor based on Fano resonances between LSPR and Rayleigh anomaly (RA) in a metal-insulator-metal (MIM) meta-grating, which is constructed by silver nanoshells array, an isolation grating mask and a continuous gold film. The MIM configuration offers more freedoms to control the optical properties of LSPR, RA and the Fano resonance between them. Strong couplings between LSPR and RA form a series of narrowband reflection peaks (with a linewidth of ~20 nm in full width at half maximum (FWHM) and a reflectivity closing to 100%) within a LSPR based broadband extinction window in experiment, making the meta-grating promising for applications of high-efficiency reflective filters. While, a well-optimized Fano resonance between LSPR and RA by carefully adjusting the angles of incident light can switch such nano-device to an improved biological/chemical sensor with the figure of merit (FOM) large than 60 and capability for detecting the local refractive index changes caused by the bonding of target molecules on surface of the nano-devices. The figure of merit of hybrid sensor in detection of target molecules is 6 and 15 times higher than the simple RA and LSPR based sensors, respectively.

Mobile software applications (apps) have transformed how individuals oversee and maintain their own health. One way that girls can monitor their menstrual cycles is through the increasingly widespread use of mobile menstrual tracking apps. This study aims to examine menstrual symptom tracking for adolescents in English and Chinese apps, exploring menstrual literacy, cross-cultural differences, and framing, or presentation, of symptoms. The mixed methods content analysis involved 15 popular free menstrual tracking apps in English (n = 8) and Chinese (n = 7). Quantitative analysis of qualitative data was conducted through manual coding of content and automatically analyzing sentiment, or emotional tone, using a computational approach. We found that: (1) Menstrual literacy on symptom management or treatment was generally insufficient, (2) There were more available emotional than physical symptoms in English than Chinese apps, (3) Symptoms were framed more negatively than positively, somewhat more in Chinese than English apps. Findings emphasize the importance of improving information in digital menstrual trackers. Our findings further reflect cultural differences in emotional expression and negative attitudes toward menstruation. Since adolescence is a critical developmental stage that requires ample support, digital menstrual trackers can uniquely shape attitudes and experiences, ultimately, empowering teenagers to better manage their menstrual health.

Cross coupling reactions have changed the way complex molecules are synthesized. In particular, Suzuki-Miyaura and Buchwald-Hartwig amination reactions have given opportunities to elegantly make pharmaceutical ingredients. Indeed, these reactions are forefront at both the stages of drug development, medicinal chemistry, and process chemistry. On one hand, these reactions have given medicinal chemists a tool to derivatize the core molecule to arrive at scaffold rapidly. On the other hand, these cross couplings have offered the process chemists a smart tool to synthesize the development candidates safely, quickly, and efficiently. Generally, the application of cross coupling reactions is broad, and this review will specifically focus on their real (pharma) world applications in large scale synthesis those appeared in last two years.

Reaction of 2-mercapto-3-phenylquinazolin-4(3H)-one (MPQ) with both 4-vinyl benzyl chloride and allyl bromide furnished the reactive heterocyclic monomers 3-phenyl-2-((4-vinylbenzyl) thio) quinazolin-4(3H)-one (PVTQ) and 2-(allylthio)-3-phenylquinazolin-4(3H)-one (APQ), respectively. Copolymerization of PVTQ monomer with styrene and methyl methacrylate in the presence of 2,2′-azobisisobutyronitrile (AIBN) afforded the copolymers PS-co-PPVTQ and PMMA-co-PPVTQ, respectively. Similarly, copolymerization of monomer APQ with styrene and methyl methacrylate (MMA) afforded the copolymers PS-co-PAPQ and PMMA-co-PAPQ, respectively. The resulted copolymers were characterized by using FT-IR, 1H-NMR and GPC techniques. Silver nanocomposites of PS, PMMA, PS-co-PPVTQ, PMMA-co-PPVTQ, PS-co-PAPQ and PMMA-co-PAPQ were synthesized by the addition of silver nitrate into the polymer solution. The reduction of silver ions into silver nanoparticles was performed in DMF and water. Thermogravimetric (TGA) analysis was used to determine the thermal stability of the copolymers and their silver nanocomposites. The X-ray diffraction (XRD) analysis indicated the amorphous structures of the co-polymers and confirmed the formation of silver nanoparticles. The antitumor and antibacterial activities were screened for the copolymers and enhanced by the formation of their silver nanocomposites. In vivo antitumor activity in Ehrlich Ascitic Carcinoma (EAC) mice model showed that PS-co-PPVTQ/Ag NPs, PMMA-co-PPVTQ/Ag NPs, and PMMA-co-PAPQ/Ag NPs displayed promising inhibitory effects against EAC and induce apoptosis against MCF-7 cells.

The paper describes a method of solving some stochastic processes using generating functions. A general theorem of generating functions of a particular type is derived. A generating function of this type is applied to a stochastic process yielding polynomial time algorithms for certain partitions. The method is generalized to a stochastic process describing a rather general linear transform. Finally, the main idea of the method is used in deriving a theoretical polynomial time algorithm to the knapsack problem.

There is great importance and need of improving existing carbon materials fabrication methods. As such, this work proposes to discuss, interrogate, and propose viable hydrothermal, solvothermal, and other advanced carbon materials synthetic methods. The advanced carbon materials to be interrogated will include the synthesis of carbon dots, carbon nanotubes, nitrogen/titania-doped carbons, graphene quantum dots, and their nanocomposites with solid/polymeric/metal oxide supports. This will be done with special mind to microwave-assisted solvothermal and hydrothermal synthesis due to their favourable properties such as rapidity, low cost, and green/environmentally-friendliness. Thus, these methods are important during the current and future synthesis and modification of advanced carbon materials for application in energy, gas separation, sensing, and water treatment. Simultaneously, the work will pay special cognizance to methods reducing the fabrication costs and environmental impact while enhancing the properties as a direct result of the synthesis methods. As a direct result, the expectation is to impart a significant contribution to the scientific body of work regarding the improvement of the said fabrication methods.

In recent years, new metaheuristic algorithms have been developed taking as reference the inspiration on biological and natural phenomena. This nature-inspired approach for algorithm development has been widely used by many researchers in solving optimization problem. These algorithms have been compared with the traditional ones algorithms and have demonstrated to be superior in complex problems. This paper attempts to describe the algorithms based on nature, that are used in fuzzy clustering. We briefly describe the optimization methods, the most cited nature-inspired algorithms published in recent years, authors, networks and relationship of the works, etc. We believe the paper can serve as a basis for analysis of the new are of nature and bio-inspired optimization of fuzzy clustering.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

Scattering of elastic waves in heterogeneous media has become one of the most important problems in the field of wave propagation due to its broad applications in seismology, natural resource exploration, ultrasonic nondestructive evaluation and biomedical ultrasound. Nevertheless, it is one of the most challenging problems because of the complicated medium inhomogeneity and the complexity of the elastodynamic equations. A widely accepted model for the propagation and scattering of elastic waves, which properly incorporates the multiple scattering phenomenon and the statistical information of the inhomogeneities is still missing. In this work, the author developed a multiple scattering model for heterogeneous elastic continua with strong property fluctuation and obtained the exact solution to the dispersion equation under the first-order smoothing approximation. The model establishes an accurate quantitative relation between the microstructural properties and the coherent wave propagation parameters and can be used for characterization or inversion of microstructures. Starting from the elastodynamic differential equations, a system of integral equation for the Green functions of the heterogeneous medium was developed by using Green’s functions of a homogeneous reference medium. After properly eliminating the singularity of the Green tensor and introducing a new set of renormalized field variables, the original integral equation is reformulated into a system of renormalized integral equations. Dyson’s equation and its first-order smoothing approximation, describing the ensemble averaged response of the heterogeneous system, are then derived with the aid of Feynman’s diagram technique. The dispersion equations for the longitudinal and transverse coherent waves are then obtained by applying Fourier transform to the Dyson equation. The exact solution to the dispersion equations are obtained numerically. To validate the new model, the results for weak-property-fluctuation materials are compared to the predictions given by an improved weak-fluctuation multiple scattering theory. It is shown that the new model is capable of giving a more robust and accurate prediction of the dispersion behavior of weak-property-fluctuation materials. Numerical results further show that the new model is still able to provide accurate results for strong-property-fluctuation materials while the weak-fluctuation model is completely failed. As applications of the new model, dispersion and attenuation curves for coherent waves in the Earth’s lithosphere, the porous and two-phase alloys, and human cortical bone are calculated. Detailed analysis shows the model can capture the major dispersion and attenuation characteristics, such as the longitudinal and transverse wave Q-factors and their ratios, existence of two propagation modes, anomalous negative dispersion, nonlinear attenuation-frequency relation, and even the disappearance of coherent waves. Additionally, it helps gain new insights into a series of longstanding problems, such as the dominant mechanism of seismic attenuation and the existence of the Mohorovičić discontinuity. This work provides a general and accurate theoretical framework for quantitative characterization of microstructures in a broad spectrum of heterogeneous materials and it is anticipated to have vital applications in seismology, ultrasonic nondestructive evaluation and biomedical ultrasound.

Owing to fascinating applications of ZnO in modern devices, it is interesting to explore its more features for future devices. Hence, herein, we have synthesized the high quality ZnO spherical nanoparticles (SNPs) through a facile green synthesis route and robust structural and biomedical studies are carried out. Hexagonal phase with 93.2% crystallinity was confirmed through XRD analysis. ZnO nanoparticles were tested for their bioactivities both in vivo (acute cytotoxicity test) and in vitro (Anti-cancer activities on liver (HepG2) and cervical (Hela) cancer cell lines, stimulatory/inhibitory effects on normal rat splenic cells and hemolytic effects on red blood cells). Results showed that ZnO SNPs has no cytotoxic effects on vital organ like liver and has no hemolytic action on red blood cells. ZnO SNPs showed inhibitory consequence on normal rat splenic cells growth at all tested concentrations. ZnO nanoparticles showed an inhibitory effect on HepG2 cell line. While showed stimulatory effect on Hela cell line. Current study presents the synthesized ZnO SNPs as highly applicable in bio-optoelectronics.

Technology advancements are evident in the healthcare field; numerous new opportunities and applications have emerged during the last years based on embedded intelligence and related to real-time diagnosis of medical issues, tele-care and telemedicine, remote monitoring of patients, computer-assisted “smart” transportation in case of emergencies, as well as new types of remotely controlled surgical operations. This paper aims to provide an overview of the application of embedded intelligence in the field of healthcare; it gathers the main critical requirements, related technologies and research advancements up to date, and it presents the most important challenges that are yet to be faced. The main focus is given in the development and optimization of Body Area Networks (BANs) based on advanced embedded sensing devices, the optimization of smart gateways in such networks, and the provision of holistic scalable and secure solutions in the healthcare domain. In addition, the paper presents two principal use cases that stem from the combination of novel information and communication technologies with classic healthcare practices, explaining the functional and non-functional requirements, as well as the mixed criticality characteristics of the associated systems.

The VLSI industry is facing parasitic effects that trouble development in the nanoscale domain. However, instead of replacing the traditional MOSFET design, it would be more advantageous to apply different doping profiles and discerning which deal with specific parasitic effects the best. With a review of Gaussian doping, Uniform doping, and Delta doping profiles and analysis of the FET technology characteristics that use these doping profiles, a comparison can be made among them for integrated circuit design engineers. These doping profiles are compared based on how well they perform against non-ideal and ideal environments. Also, both digital and analog performance are measured to ensure the uniqueness of each doping profile that is present. After getting a list of benefits from each doping profile, it is derived to determine which doping profile works best against a host of parasitic effects and what type of application do these doping profiles have

Animal-focused research has been crucial for scientific advancement however, in this matter, rodents are still taking a starring role. Coming out from merely being supportive of evidence found in rodents, the use of fish models has slowly taken a more central role and expanded its overall contributions in areas such as social sciences, evolution, physiology, and recently in translational medical research. In neurosciences, zebrafish has been widely adopted, contributing to our understanding of the genetic control of brain processes, and the effects of pharmacological manipulations. However, discussion continues regarding the paradox of function versus structure, when fish and mammals are compared, and on the potentially evolutionarily conserved nature of behaviour across fish species. From the behavioural stand point we explored aversive/stress and social behaviour in selected fish models, and refer to the extensive contributions of stress and monoaminergic systems. We suggest that, in spite of marked neuroanatomical differences between fish and mammals, stress and sociality are conserved at the behavioural and molecular levels. We also suggest that stress and sociality are mediated by monoamines in predictable and non-trivial ways, and that monoamines could “bridge” the relationship between stress and social behaviour. To reconcile the level of divergence with the level of similarity, we need neuroanatomical, pharmacological, behavioural, and ecological studies conducted in the laboratory and in nature. These areas need to add to each other to enhance our understanding of fish behaviour and ultimately how this all may translate to better model systems for translational studies.

An oxidation resistant coating on cemented tungsten carbides is characterised in this work. Cemented tungsten carbides (cWCs) are routinely used in mining and manufacturing but are also candidate materials for compact radiation shielding in fusion power generation. In both environments, cWCs will suffer significant degradation due to oxidation at relatively low temperatures. In a recent study, a Si-deposition coating method was demonstrated to improve the oxidation resistance of cWCs by up to a factor of 1,000. This work focusses on the growth kinetics, phase composition, and mechanical properties of these coatings. By combining quantitative X-ray diffraction, electron microscopy and nanoindentation, we show that the coating layer has a 20 % higher hardness than the substrate, which was explained on the basis of a previously-unknown presence of a fine distribution of very hard SiC laths. To interpret the coating stability, a coating growth map is developed. The map shows the structure is stable under a broad range of processing temperatures and composite compositions, demonstrating the potential application of these coatings in a variety of nuclear shielding cWCs.

In this paper, we discuss the most significant application opportunities and outline the challenges in performing a real-time and energy-efficient management of the distributed resources available at mobile devices and Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing (VFC) that operates at the edge of a vehicular network, connected to the served Vehicular Clients (VCs) through an Infrastructure-to-Vehicular (I2V) over multiple Foglets (Fls). The scheduler optimizes the energy by leveraging the heterogeneity of Fls, where the Fl provider shapes the system workload by maximizing the task admission rate over data transfer and computation. The presented scheduling algorithm demonstrates that the resulting adaptive scheduler allows scalable and distributed implementation.

The identification of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims to analyse the capability of machine-learning (ML) methods to map informal areas in Jeddah, Saudi Arabia, using very-high-resolution (VHR) imagery and terrain data. Fourteen indicators of settlement characteristics were derived and mapped using an object-based ML approach and VHR imagery. These indicators were categorised according to three different spatial levels: environ, settlement and object. The most useful indicators for prediction were found to be density and texture measures, (with random forest (RF) relative importance measures of over 25% and 23% respectively). The success of this approach was evaluated using a small, fully independent validation dataset. Informal areas were mapped with an overall accuracy of 91%. Object-based ML as a hybrid approach performed better (8%) than object-based image analysis alone due to its ability to encompass all available geospatial levels.

In this work, we study the equation of the catenary curve in the context of the Caputo derivative. We solve this equation and compare the solution with real physical models. From the experiments, we find that the best approximation is achieved in the classical case. Therefore, introducing a fractional parameter arbitrarily can be detrimental. However, we observe that when adding a certain weight to the chain, fractional calculus produces better results than classical calculus for modeling the minimum height.

The development of sensitive and specific exosome detection devices is highly desirable because it is believed to deliver specific important information for cancer screening, diagnosis, and monitoring. Among many detection techniques, nanoplasmonic sensors are optical detection methods that offer advantages in sensitivity and detection speed and this makes the sample analysis process faster and more accurate. This paper summarizes the development of nanoplasmonic biosensors, especially Surface Plasmon Resonance (SPR) and Localized Surface Plasmon Resonance (LSPR)-based biosensors for exosome detection. There are three main parts in this paper. The first part will focus on introducing the theoretical background regarding the working principles of SPR and LSPR biosensors. After that, we will introduce several methods that can be used for exosome isolation. This article will close by explaining the engineering of nanoplasmonic sensors both in terms of transducer modification to amplify the signal and functionalization strategies to increase sensor specificity. In this section, the detection mechanism, the type of exosomes detected, and the resulting detection limits are some of the points highlighted in this paper.

This study investigated the potential of electrospun collagen/Hyaluronic Acid nanofibers in biomedicine and skincare. Needleless electrospinning technology employed in the production process resulted in nanofibers with consistent fiber diameters and improved mechanical properties. The composite nanofibers demonstrated impressive tensile strength and elongation capabilities, indicating a favorable interaction between collagen and HA. Cellular assays revealed that the collagen/HA scaffolds facilitated superior cell adhesion and proliferation compared to the control scaffolds, indicating their biocompatibility and potential for tissue engineering. This biomaterial offers an environment-friendly alternative to conventional skincare products by eliminating the need for preservatives and reducing waste. Although the initial costs are high, the long-term benefits of material durability and active ingredient efficacy provide a compelling case for industrial adoption. Our findings suggest that collagen/HA nanofibers have the potential to be next-generation materials for regenerative medicine and skincare, and further research is needed to optimize their production and assess the economic feasibility of skincare and tissue engineering applications.

Many quantum devices signals are proportional to the number of the participating atoms that take part in the detection devices. Among these are optical magnetometers, atomic clocks, and atoms interferometers. One way to enhance the signal to noise ratio is to introduce atoms entanglement that increases the signal in a super-radiant like effect. An initial novel experiment to test the realization of atoms correlation is described here. A Cs optical magnetometer is used as a tool to test the operation of a cell-in-cavity laser and its characteristics. A vapor cell is inserted in-to an elongated external cavity of the pump laser in Littrow configuration. Higher atom polarization and reduced laser linewidth are obtained leading to better magnetometer sensitivity and signal-to-noise ratio. The Larmor frequency changes of the Free Induction Decay of optically pumped Cs atomic polarization in ambient earth magnetic field at room temperature is measured. Temporal changes in the magnetic field of less than 10 pT/Hz are measured. The first order dependence of the magnetic field on temperature and temperature gradients is eliminated, important in many practical applications. Single and gradiometric magnetometer con-figurations are presented.

Extracellular vesicles (EVs), including exosomes, microvesicles, and other lipid vesicles derived from cells, play a pivotal role in intercellular communication by transferring information between cells. EVs secreted by progenitor and stem cells have been associated with the therapeutic effects observed in cell-based therapies, and they also contribute to tissue regeneration following injury, such as in orthopedic surgery cases. This review briefly explores the involvement of EVs in tissue repair and nerve regeneration, their potential as drug carriers, and their significance in stem cell research and cell-based therapies. It underscores the importance for bioengineers to comprehend and manipulate EV activity to optimize the efficacy of tissue engineering and regenerative therapies.

Measuring the Sun’s magnetic field is a key component of monitoring solar activity and forecasting space weather. The main goal of the research presented in this paper is to investigate the possibility of reducing the dimensions and weight of a solar magnetograph while preserving its optical quality. This article presents a range of different designs, along with their advantages and disadvantages, and an analysis of the optical performance of each. All proposed designs are based on the Magneto Optical Filter (MOF) technique. As a result of the design study, a miniaturised solar magnetograph is proposed with an ultra-compact layout. The dimensions are 345mm × 54mm × 54mm and the optical quality is almost at the diffraction limit. The design has an entrance focal-ratio of F/17.65, with a plate scale of 83.58 arcsec/mm at the telescope image focal plane and produces a magnification of 0.79. The field of view is 1920 arcsec diameter, equivalent to ±0.27degrees, sufficient to cover the entire solar disk.

Fasting, a practice with historical roots in various cultures, has recently garnered significant interest in the field of medicine. In this article, we delve into the mechanisms underlying fasting-induced autophagy and its therapeutic applications for spike protein associated pathology. We explore the therapeutic potential of fasting on spike protein-related pathology. Additionally, we discuss factors that affect fasting, such as duration, type (dry vs. water), and the role of specific compounds like spermidine, resveratrol, rapamycin, and metformin. Furthermore, we analyse the interactions between fasting and other practices such as exercise, and highlight important considerations regarding participant characteristics, including pregnancy, breastfeeding, medication interactions, and metabolic disorders. In conclusion, fasting, coupled with an understanding of its nuances, holds promise as a therapeutic intervention with broad implications for human health.

The paper presents the conceptualization and realization of a novel platform for additive manu-facturing, an industrial robot arm-based system for additive manufacturing applications. Tradi-tional 3D printers, especially those employing fused deposition modelling (FDM) processes, are restricted to depositing material in a single toolpath plane (e.g. x-y plane). The focus of this study was to explore the feasibility of integrating commercial off the shelf (COTS) additive manufac-turing technologies with a six degree of freedom industrial robot arm to yield a 3D additive manufacturing system with the capability to perform free-form six degree of freedom fused deposition modelling. The present paper presents the development of a platform from stage 0, i.e. materials to its use, and finally a printed product with the developed extruder.

Compared with conventional semiconductors, halide perovskite nanocrystals (NCs) have a unique crystal structure and outstanding optoelectronic properties, which offer a wide potential for applications in optoelectronic devices such as solar cells, photodetectors, light emitting diodes, lasers and displays. Rational technological design is providing vital support for the development of perovskite optoelectronics. Herein, high-quality and monodisperse all-inorganic halide perovskite nanocrystals with consistent morphology, concentrated size distribution and cubic crystal phase were synthesized employing a modified one-pot hot injection method to independently modulate the stoichiometric ratios of three precursors involving cesium salt, lead source and halide. Mixing two kinds of perovskite NCs with different halogens, in combination with an anion exchange reaction, enables a transition from violet emission to green and finally to red emission over the entire visible region. Our work will be applied to enhance optoelectronic properties and stability of all-inorganic perovskite NCs for serving as light-emitting components in optoelectronic devices, as well as expanding the application areas of perovskite semiconductors for photocatalytic hydrogen generation, CO2 reduction and dye degradation.

This review article deals with the design of bioactive calcium phosphate coatings deposited on metallic substrates to produce bone implants. The bioceramic coating properties are used to create a strong bonding between the bone implants and the surrounding bone tissue. They provide a fast response after implantation and increase the lifespan of the implant in the body environment. The first part of the article describes the different compounds belonging to the calcium phosphate family and their main properties for applications in biomaterials science. The calcium to phosphorus atomic ratio (Ca/P)at. and the solubility (Ks) of these compounds define their behavior in a physiological environment. Hydroxyapatite is the gold standard among calcium phosphate materials, but other chemical compositions/stoichiometries have also been studied for their interesting properties. The second part reviews the most usual deposition processes to produce bioactive calcium phosphate coatings for bone implant applications. Plasma spraying is the main industrial process, but magnetron sputtering, pulsed laser deposition, electrospray deposition, electrophoretic deposition, and electrodeposition are also widely studied in academic and industrial research. The last part describes the main physicochemical properties of calcium phosphate coatings and their impact on the bioactivity of bone implants in a physiological environment.

This study describes an eco-friendly synthesis of ZnO nanoparticles using aqueous oat extract. The advanced electrochemical and optical features of green synthesized ZnONPs displayed excellent antibacterial activity, and exhibited an important role in pharmaceutical determinations. The formation of nanoscale ZnO was confirmed using various spectroscopic and microscopic investigations. The formed nanoparticles were found to be around 100 nm. The as-prepared ZnONPs were monitored for their antibacterial potential against different bacterial strains. The inhibition zones for ZnONPs were found as E. coli (16 mm), P. aeruginosa (17 mm), S. aureus (12 mm) and B. subtilis (11 mm) using 30 µg mL-1 sample concentration. Also, ZnONPs exhibited significant antioxidant effects 58 to 67 % with an average IC50 value of 0.88 ± 0.03 scavenging activity and 53 to 71 % (IC50 value 0.73 ± 0.05) against the DPPH and ABTS scavenging free radicals, respectively. The photocatalytic potential of ZnONPs for Rhodamine B dye degradation dye under UV irradiation was performed. The photodegradation process was carried out as a function of time-dependent and the complete degradation (nearly 98 %) with color removal after 120 min. Conclusively, the synthesized ZnONPs using oat biomass might provide a great promise in the future for biomedical applications.

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman Filter to enhance the perception performance. In addition, a back-end UAV path planning for surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

One of the important research directions in the field of photovoltaics is integration with construction. The integration of solar cell systems with a building can reduce installation costs and help optimize the used space. One of the interesting types of cells is dye-sensitized solar cells. In addition to their interesting properties, they also have aesthetic value. In the classic arrangement, they are constructed using glass with a transparent conductive layer (TCL). This article describes replacing a classic glass counter electrode with an electrode based on a ceramic tile and nickel foil. This solution makes it possible to expand their construction applications. The advantage of this solution is full integration with construction while simultaneously generating electricity. A dye-sensitized solar cell was built layer-by-layer on ceramic tile and nickel foil. An atomization method was used to deposit fluorine-doped tin oxide, and then a screen printing method was used to deposit a platinum layer. The electrical parameters of the manufactured DSSCs with and without a counter electrode tile were characterized by measuring their current-voltage characteristics under standard AM 1.5 radiation. A dye-sensitized solar cell integrated with ceramic tiles and nickel foil was produced and displayed an efficiency of over 4%.

Intermetallic alloys like e.g. Iron-Aluminides, Titanium-Aluminides or Molybdenum- Silizides are prospective materials for high-temperature applications. For additive manufacturing (AM) intermetallic structural materials are particularly challenging due to their high melting points, oxygen susceptibility and low temperature brittleness. The feasibility of manufacturing intermetallic Mo-Si-B alloys with the laser additive manufacturing process of direct energy deposition (DED) is demonstrated and recent results in characterizing rapidly solidified material with respect to correlations between process, composition and microstructures are presented. The possibility to dope the material with Yttrium oxide (Y2O3) for dispersion is successfully demonstrated. Current challenges, e.g. homogenous distribution of alloying elements and applicability are addressed.

Light management in single nanowires (NWs) is of great importance for photovoltaic applications. However, square NWs (SNWs) can limit their light-trapping ability due to high geometrical symmetry. In this work, we present a detailed study of light management in single silicon NWs with a rectangular cross-section (RNWs). We demonstrate that the RNWs exhibit significantly enhanced light-harvesting compared with the SNWs, which can be attributed to the symmetry-broken structure that can orthogonalize the direction of light illumination and the leaky mode resonances (LMRs). That is, the rectangular cross-section can simultaneously increase the light path length by increasing the vertical side and reshape the LMR modes by decreasing the horizontal side. We found that the light absorption can be engineered via tuning the horizontal and vertical sides, the photocurrent is significantly enhanced by 276.5% or 82.9% in comparison with that of the SNWs with the same side length as the horizontal side of 100 nm or the vertical side of 1000 nm, respectively. This work advances our understanding of how to improve light-harvesting based on the symmetry breaking from the SNWs to RNWs and provides an effective way for designing high-efficiency single NW photovoltaic devices.

The explosion of data has transformed the world since much more information is available for collection and analysis than ever before. To extract valuable information from the data in different dimensions, various deep learning models have been developed in the past years. Although these models have demonstrated their strong capability on improving products and services in various applications, training them is still a time-consuming and resource-intensive process. Presently, cloud, one of the most powerful computing infrastructures, has been used for the training. However, how to manage cloud computing resources and to perform the training efficiently is still challenging current techniques. For example, general resource scheduling approaches, such as spread priority and balanced resource schedulers, actually do not work well with deep learning workloads. Besides, the resource allocation problem on a cluster can be divide into two subproblems: (1) local resource optimization: improve resource configuration for a single machine; (2) global resource optimization: improve the cluster-wide resource allocation. In this thesis, we propose two novel container schedulers, FlowCon and SpeCon, that are designed to address these two subproblems respectively and specifically to optimize performance of short-lived deep learning applications in the cloud. FlowCon focuses on resource configuration of single-node in a cluster, as show that it efficiently improves deep learning tasks completion time and resource utilization, and reduces the completion time of a specific job by up to 42.06\% without sacrificing the overall system time. SpeCon targets on cluster-wide resource configuration that speculatively migrate slow-growing models to release resources for fast-growing ones. Based on our experiments, SpeCon improves makespan for up to 24.7\%, compared to current approaches.

The commercial popularity of Virtual Reality attracted educators’ interest and brought new opportunities to the educational landscape. At the same time, Learning Analytics emerged with the promise to revolutionise the traditional practices by introducing ways to systematically assess and improve the effectiveness of instruction. However, the collection of ‘big’ educational data is mostly associated with web-based platforms as they offer direct access to learners’ activities with minimal effort. On the antipode, the nature of VR limits the opportunities for such data collection. Hence, in the context of this work, we present a four-dimensional theoretical framework, that accounts the information that can be gathered from VR-supported instruction, and propose a set of structural elements which can be utilised for the development of a Learning Analytics prototype system. The outcomes of this work are expected to support practitioners to maximise the potential of their interventions and provide inspiration for new ones.

Multi-gap Resistive Plate Chamber has been attracting increasing attention and has been studied in recent decades because of its good efficiency, high time resolution and relatively low cost. It has become a new standard technology for the Time of Flight system in particle and high energy physics experiments. In this paper, we introduce the operation principle and structure of the MRPC detector and review the applications on the Time of Flight system in several famous experiments, such as STAR, CBM and SoLID. The performances including time resolution and particle identification are discussed in detail. Some recent advances and perspectives with regard to the future development of the next generation MRPC are also outlined.

ABSTRACT Surfactants are a broad category of tensio-active biomolecules with multifunctional properties applications in diverse industrial sectors and processes. Surfactants are produced synthetically and biologically. The biologically derived surfactants (biosurfactants) are produced from microorganisms with Pseudomonas aeruginosa, Bacillus subtilis Candida albicans and Acinetobacter calcoaceticus as dominant species. Rhamnolipids, sophorolipids, mannosylerithritol lipids, surfactin, and emulsan are well known in terms of their biotechnological applications. Biosurfactants can compete with the synthetic surfactants in terms of performance with established advantages over the synthetic ones including eco-friendliness, biodegradability, low toxicity, and stability over a wide variability of environmental factors. However, at present, the synthetic surfactants are a preferred option in different industrial applications, because of their availability in commercial quantities, unlike the biosurfactants. Usage of synthetic surfactants introduce new species of recalcitrant pollutants to the environment and lead to undesired results where a wrong selection of surfactants is made. Substituting synthetic surfactants with biosurfactants resolves these drawbacks, thus, interest has been intensified in biosurfactant applications in a wide range of industries hitherto considered as experimental fields. This review, therefore, intends to offer an overview of diverse applications where biosurfactants have found useful, with emphases in petroleum biotechnology, environmental remediation and in the agriculture sector. Application of biosurfactant in these settings would lead to industrial growth and environmental sustainability.

Two-dimensional arrays of hollow nanotubes made of TiO2 are a promising platform for sensing, spectroscopy and light harvesting applications. Their straightforward fabrication via electrochemical anodization, growing nanotube pillars of finite length from a Ti foil, allows precise tailoring of geometry and, thus, material properties. We investigate these photonic crystal structures with respect to reduction of front surface reflection, achievable field enhancement, and photonic bands. With the Rigorous Coupled Wave Analysis (RCWA), we study the optical response of photonic crystals made of thin-walled nanotubes relative to the bare Ti foil substrate, including under additional charge carrier doping.

VANET networks are a class of peer-to-peer wireless networks that are used to organize communication between cars (V2V), cars and infrastructure (V2I) and between cars and other types of nodes (V2X). These networks are based on the DSRC, 802.11 standards and are mainly intended for organizing the exchange of various types of messages, mainly emergency ones, to prevent road accidents or alert when road accident occur, or control the priority of the driveway. Initially it was assumed that cars would only interact with each other, but later, with the advent of the concept of Internet of things (IoT). Researchers began to analyze connectivity with other devices, which in general will allow to combine various road users and other devices that can used in the creation of intelligent transport infrastructure in a single smart city management system. Infrastructure is necessary for the provision of services, monitoring and management of the VANET network. As infrastructure objects it is proposed to use stationary objects of Roadside unit (RSU). The aim of this paper is to analyze the use of mobile edge computing to decrease the load to the base station and latency between RSU clouds and provide a real experiment using software defined networking and mobile edge computing for RSU.

Molecular dynamics(MD) simulations are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals the solvent structure and preferential interaction sites (hot spots) on the protein surface. This information is largely transferable across all classes of protein ligands (from water to drugs) and can be used very effectively to understand ligand recognition and improve the predictive capability of well-established methods such as molecular docking. MD simulations for protein and drug or drug-like compounds are now being used but are still computationally expensive and can only be applied to specific cases. On the other hand, MDmix simulations can now be used in SBDD and we will describe the latest developments and implementations. We expect to see an increase in the application of these techniques to a plethora of protein targets to identify new drug candidates with the advent of new tools and faster computers.

In the field of tissue engineering, conductive hydrogels have been the most effective biomaterials to mimic the biological and electrical properties of tissues in the human body. The main advantages of conductive hydrogel include not only its physical properties, but also its adequate electrical properties, thus providing electrical signals to cells efficiently. However, when introducing a conductive material into a non-conductive hydrogel, a conflicting relationship between the electrical and mechanical properties may develop. This review examines the strengths and weaknesses of the generation of conductive hydrogels using various conductive materials and introduces the use of these conductive hydrogels in tissue engineering applications.

In this paper we establish some generalizations of Opial’s inequal- ities for Riemann-Stieltjes integral and for two functions. Applications related to trapezoid and Grüss’ ’type inequalities are also given.

This paper has three objectives, the first is to present a detailed overview in the form of a tutorial for the developments of several key quantile time series modelling approaches. The second objective is to develop a general framework to represent such quantile models in a unifying manner in order to easily develop extensions and connections between existing models that can then be developed to further extend these models in practice. In this regard, the core theme of the paper is to provide perspectives to a general audience of core components that go into construction of a quantile time series model and then to explore each of these core components in detail. The paper is not addressing the concerns of estimation of these models, as there is existing literature on these aspects in many settings, we provide references to relevant works on these aspects in several classes of model. Instead, the focus is rather to provide a unified framework to construct such models for practitioners, therefore the focus is instead on the properties of the models and links between such models from a constructive perspective. The third objective is to compare and discuss the application of the different quantile time series models on several sets of interesting demographic and mortality based time series data sets of relevance to life insurance analysis. The exploration included detailed mortality, fertility, births and morbidity data in several countries with more detailed analysis of regional data in England, Wales and Scotland.

This article reports a novel and efficient method to synthesize graphene by thermal decomposition process. In this method, silicon carbide (SiC) thin films grown on Si(100) wafers with an AlN buffer layer were used as substrates. A CO₂ laser beam heating without vacuum or controlled atmosphere was applied for SiC thermal decomposition. The physical, chemical, morphological, and electrical properties of the laser-produced graphene were investigated for different laser energy densities. The results demonstrate that graphene was produced in form of small islands with quality, density and properties depending on the applied laser energy density. Furthermore, the produced graphene exhibits a sheet resistance characteristic similar to graphene grown on mono-crystalline SiC wafer, which indicates its potential for electronic device applications.

Functional Near Infrared Spectroscopy (fNIRS) systems for e-health applications usually suffer of poor signal detection mainly due to a low end-to-end signal to noise ratio of the electronics chain. Lock-In Amplifiers (LIA) historically represent a powerful technique helping to improve performances in such circumstances. In this work it has been designed and implemented a digital LIA system, based on a Zynq® Field Programmable Gate Array (FPGA), trying to explore if this technique might improve fNIRS system performances. More broadly, FPGA based solution flexibility has been investigated, with particular emphasis applied to digital filter parameters, needed in the digital LIA, and it has been evaluated its impact on the final signal detection and noise rejection capability. The realized architecture was a mixed solution between VHDL hardware modules and software ones, running within a softcore microprocessor. Experimental results have shown the goodness of the proposed solutions and comparative details among different implementation will be detailed. Finally a key aspect taken into account throughout the design was its modularity, allowing an ease increase of the input channels while avoiding the growth of the design cost of the electronics system.

Human induced pluripotent stem cells (hiPSCs) are reprogrammed cells that have hallmarks similar to embryonic stem cells including the capacity of self-renewal and differentiation into cardiac myocytes. The improvements in reprogramming and differentiating methods achieved in the past 10 years widened the use of hiPSCs, especially in cardiac research. hiPSC-derived cardiac myocytes (CMs) recapitulate phenotypic differences caused by genetic variations, making them human attractive disease models and useful tools for drug discovery and toxicology testing. In addition, hiPSCs can be used as source cells for cardiac regeneration in animal models. Here, we review the advances in the genetic and epigenetic control of cardiomyogenesis that underlies the significant improvement of the induced reprogramming of somatic cells to CMs. We also cover the phenotypic characteristics of the hiPSCs derived CMs, their ability to rescue injured CMs through paracrine effects, the novel approaches in tissue engineering for hiPSC-derived cardiac tissue generation, and finally, their potential use in biomedical applications.

Tanning, crucial for leather production, relies heavily on chromium yet poses risks due to chromium's oxidative conversion, leading to significant wastewater and solid waste generation. Physico-chemical methods are typically used for heavy metal removal, but they have drawbacks, prompting interest in eco-friendly biological remediation techniques like biosorption, bioaccumulation, and biotransformation. The EU Directive (2018/850) mandates alternatives to landfilling or incineration for industrial textile waste management, highlighting the importance of environmentally conscious practices for leather products' end-of-life management, with com-posting being the most researched and viable option. This study aimed to isolate microorganisms from tannery wastewater and identify those responsible for different types of tanned leather biodegradation. Using a leather biodegradation assay (ISO 20136) with tannery and municipal wastewaters as inoculum, bacterial shifts during leather biodegradation were observed. Over 10,000 bacterial species were identified in all analyzed samples, with 8 bacterial strains isolated from tannery wastewater. Identification of bacterial genera like Acinetobacter, Brevundimo-nas, and Mycolicibacterium provides insights into potential microbial candidates for enhancing leather biodegradability, wastewater treatment, and heavy metal bioremediation in industrial applications.

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

Cutting-edge technologies are intensifying into new skylines and this remarkable progress has been successfully influenced by the tiny level engineering of carbon dots technology, their syn-thesis advancement and impressive applications in the field of allied sciences. The advances of science and its conjugation with interdisciplinary fields emerged in carbon dots making, their controlled characterization and applications into faster, cheaper as well as more reliable prod-ucts in various scientific domains. Thus, a new era in nanotechnology has developed into carbon dots technology. The understanding of the generation process, control on making processes and selected applications of carbon dots such as energy storage, environmental monitoring, catalysis, contaminates detections and complex environmental forensics, drug delivery, drug targeting and other biomedical applications etc. are among the most promising applications of carbon dots and thus a thrust area of research today. In this regard, various types of carbon dots nano-materials such as oxides, their composites and conjugations etc. have been flocking significant attention due to their remarkable potential in this thrust area of energy, the environment and technology. Thus, the present paper highlights the role and importance of carbon dots, recent advancements in their synthesis methods, properties and emerging applications.

Genetic testing has expanded out of the research laboratory into medical practice and the direct-to-consumer market, and rapid analysis of the resulting genotype data can now have significant impact. We present a method for summarizing personal genotypes as ‘genotype fingerprints’ that meet these needs. Genotype fingerprints can be derived from any single nucleotide polymorphism (SNP)-based assay, and remain comparable as chip designs evolve to higher marker densities. We demonstrate that they support distinguishing types of relationships among closely related individuals and closely related individuals from individuals from the same background population, as well as high-throughput identification of identical genotypes, individuals in known background populations, and de novo separation of subpopulations within a large cohort through extremely rapid comparisons. While fingerprints do not preserve anonymity, they provide a useful degree of privacy by summarizing a genotype in a way that prevents reconstruction of individual marker states. Genotype fingerprints are therefore well-suited as a format for public aggregation of genetic information to support ancestry and relatedness determination without revealing personal health risk status.

Versatile hybrid organic polymers are prepared using two active intermediates such as cynuric chloride and chitosan derivatives. The prepared chalcones are characterized by using FT-IR, UV, and proton NMR, thermal analysis and Minimum inhibitory Concentration. Thermal stability of the synthesized hybrid polymer is found using TGA and the hybrid chitosan derivative chalcone is thermally stable up to 270 °C. The antimicrobial activity of the prepared chitosan containing chalcone moiety are find out using Minimum Inhibitory Concentration (MIC) method. The synthesized versatile chalcone shows excellent antimicrobial activity against gram-negative bacteria such as Pseudomonas aeruginosa; and Gram-positive bacteria Chalcone containing halogen moiety shows high activity (MIC 7.8 µg/mL) than the hydroxyl containing chalcone. Cytotoxicity activity of the synthesized composites shows high activity.

Biochar (BC) is a carbonaceous material obtained by pyrolysis at 200−1000 °C in the limited presence of O2 of different vegetable and animal biomass feedstocks. BC has demonstrated great potential, mainly in environmental applications, due to its high sorption ability and persistent free radicals (PFRs) content. These characteristics enable BCs to carry out the direct and PFRs-mediated removal/degradation of environmental organic and inorganic contaminants. The types of PFRs possibly present in BC depend mainly on the pyrolysis temperature and the kind of pristine biomass. Since they also can cause ecological and human damage, a systematic evaluation of the environmental behavior, risks, or management techniques of BC-derived PFRs is urgent. PFRs generally could consist of a mixture of carbon- and oxygen-centered radicals, and of oxygenated carbon-centered radicals, depending on the pyrolytic conditions. Here, to promote a more productive and beneficial use of BC and related PFRs and stimulate further studies to make them environmentally safer and less hazardous to humans, we have first reviewed the most common methods used to produce BC, its main environmental applications, the primary mechanisms by which BC remove xenobiotics, as well as the reported mechanisms for PFRs formation in BCs. Secondly, we have discussed the PFRs environmental migration and transformation; we have reported the main PFRs-mediated applications of BCs to degrade inorganic and organic pollutants, the correlated environmental potential risks, and the possible strategies to limit them.

Nanotechnology is concerned with the creation of particles and materials at nanoscale levels. Nanocomposite is a combination or matrix, in which different materials combine to develop new properties of the materials ensuring that one of the materials have size in range of 1-100 nm. Nanocomposites are classified according to the types of reinforcement materials and matrix materials used in their construction. Nanocomposites are divided into three types based on the matrix material: ceramic matrix nanocomposites (CMNC), polymer matrix nanocomposites (PMNC), and metal matrix nanocomposites (MMNC) (MMNC). The synthetic methods of nanocomposites are frequently classified in to two classes. These are top-down and bottom up approaches. The type of synthetic technique used is determined by the nanocomposites' intended properties. There are different wet methods for synthesis of metal nanoparticles and nanocomposites among these co-precipitations, sol gel and hydrothermal methods are cost effective as compared to other methods. The synthesized nanocomposites can be characterized using different techniques to get insight into the morphology, particle size, phase, composition, thermal stability, optical, magnetic, electrical and thermal properties. Also, nanocomposites are used in medical, pharmaceutical industry, food packaging, to electronics and energy industry. Thus this review focuses on the main ideas about synthesis, characterization and application of nanocomposites.

Antimicrobial peptides (AMPs) are essential components of the innate immune system, present across a spectrum of organisms. Their versatility lies in their ability to effectively inhibit a wide range of pathogens including bacteria, fungi, parasites, and viruses. As the challenge of antibiotic resistance escalates and concerns surrounding antibiotic use grow, AMPs have emerged as promising alternatives. Their applications span diverse domains such as medicine, agriculture, food production, animal husbandry, and aquaculture, primarily due to their efficacy against resistant pathogens, signifying their crucial role in combating infections. Beyond their antimicrobial properties, research illuminates their intricate involvement in the immune response network. These peptides impact crucial processes including cytokine release, chemotaxis, wound healing, angiogenesis and the activation of the adaptive immune system. This comprehensive review delves into the multifaceted realm of AMPs, encompassing their classification, varied applications across industries and notably, their significance in diverse disease conditions like infections, skin diseases, cancer, oral diseases, lung diseases and cardiovascular ailments. Special attention is directed towards current advancements in clinical applications of peptide-based therapeutics, offering invaluable insights into their potential future integration within clinical settings.

The wound management sector has attracted considerable attention due to the increasing challenge posed by antimicrobial resistance (AMR) and the specialized care required for chronic wounds. Effective wound care involves selecting appropriate dressings tailored with antimicrobial agents to prevent bacterial infection. Among various types of wound dressings, fibers and electrospun fibers, with their unique characteristics, have emerged as innovative new materials. However, the rise of AMR necessitates the exploration of new antimicrobial agents for wound dressings, particularly for addressing bacterial pathogens like methicillin-resistant Staphylococcus aureus (MRSA). Endophytic fungi, known for producing diverse bioactive compounds, including novel antibacterial agents, represent a promising source of such new agents. This study tested thirty-two endophytic fungi from thirteen distinct Australian native plants for their antibacterial activity against S. aureus, the most common wound-associated bacteria. Ethyl acetate (EtOAc) extracts from fungal culture filtrates exhibited inhibitory effects against both methicillin-sensitive S. aureus ATCC 25923 and MRSA strains M173525 and M180920. DNA sequence analysis was employed for fungal identification, with EtOAc extracts from the most active sample, EL 19 (Chaetomium globosum), selected for further bactericidal and antibiofilm testing against the chosen bacteria. Biofilm of S. aureus ATCC 25923 was reduced by 55% by EtOAc extracts of EL 19 at 1/2 × MIC. To demonstrate the potential application in wound dressing materials, three different concentrations of the extract were incorporated into Polycaprolactone fiber mats through electrospinning, with resultant inhibition of S. aureus ATCC 25923 being observed. This research underscores the potential of endophytic fungi from Australian plants as sources of substances effective against common wound pathogens. Further exploration of the responsible compounds and their mechanisms could facilitate the development of wound dressings effective against MRSA and innovative biofilm-resistant electrospun fibers, contributing to the global efforts to combat AMR.

Present study focuses on the synthesis and characterisation of a lightweight ceramic material with electromagnetic interference (EMI) shielding properties, achieved using mullite containing micrometer-sized hollow spheres (cenospheres) and CoFe2O4 nanoparticles. The research explores compositions with varying CoFe2O4 content, ranging from 0 up to 20 wt.%. Сonventional sintering in an air atmosphere is carried out at a temperature between 1100-1300 °C. The addition of ferrite nanoparticles was found to enhance the sintering process of cenospheres, resulting in improved material density and mechanical properties. Furthermore, the study reveals a direct correlation between the concentration of ferrite nanoparticles and the electromagnetic properties of the. By increasing the concentration of ferrite nanoparticles, the electromagnetic shielding effect of the material (saturation magnetization (Ms) and remanent magnetization (Mr)) was observed to strengthen. These findings provide valuable insights into the design and development of lightweight ceramic materials with enhanced electromagnetic shielding capabilities. The synthesized ceramic material holds promise for various applications that require effective electromagnetic shielding, such as in electronics, telecommunications, and aerospace industries.

Developing a biomolecular detection method that minimizes photodamage while maintaining an environment suitable for biological constituents to maintain their physiological state is expected to drive new diagnostic and mechanistic breakthroughs. In addition, ultra-sensitive diagnostic platforms are needed for rapid and point-of-care technologies for various diseases. Considering this, surface-enhanced Raman scattering (SERS) is proposed as a non-destructive and sensitive approach to address the limitations of fluorescence, electrochemical, and other optical detection techniques. However, to advance the applications of SERS, novel approaches to enhance the signal of substrate materials are needed to improve reproducibility and costs associated with manu-facture and scale-up. Due to their physical properties and synthesis, semiconductor-based nanostructures have gained increasing recognition as SERS substrates; however, low signal en-hancements have offset their widespread adoption. To address this limitation and assess the po-tential for use in biological applications, zinc oxide (ZnO) was coated with different concentra-tions (0.01-0.1 M) of gold (Au) precursor. When crystal violet (CV) was used as a model target with the synthesized substrates, the highest enhancement was obtained with ZnO coated with 0.05 M Au precursor. This substrate was subsequently applied to differentiate exosomes derived from three cell types to provide insight into their molecular diversity. We anticipate this work will serve as a platform for colloidal hybrid SERS substrates in future bio-sensing applications.

The Internet of Things (IoT) is still a relatively new field of research, and its potential for use in the healthcare and medical sectors is enormous. In the last five years, IoT has been a go-to option for various applications such as using sensors for different features, machine-to-machine communication, etc., but precisely, in the medical sector, it is still lagging far behind compared to other sectors. Hence, this study emphasizes the IoT applications in medical fields, Medical IoT sensors and devices, IoT platforms for data visualization, and artificial intelligence in medical applica-tions. A systematic review considering PRISMA guidelines on research articles as well as the websites on IoMT sensors and devices have been carried out. A total of 986 articles after the year 2001 have been initially selected, and by applying the inclusion-exclusion criterion, a total of 597 articles have been identified. From these, 23 studies have been finally selected for this systematic review. This review analyzes different sensor monitoring circuits in detail, considering an Inten-sive Care Unit (ICU) scenario, device applications, and the data management system, including IoT platforms for the patients. Lastly, detailed discussion and challenges have been outlined, and possible prospects have been presented.

In this paper a more flexible extension of the Fréchet distribution is introduced. The new distribution is defined by means of the stochastic representation as the quotient of two independent random variables, a Fréchet distribution and the power of a random variable with uniform distribution in the interval (0,1). We will call this new extension the Slash Fréchet distribution and one of its main characteristics is that its tails are heavier than the Fréchet distribution. The general density of this distribution and some basic properties are determined. Its moments, skewness coefficients and kurtosis are calculated. In addition, the estimation of the model parameters is obtained by the method of moments and maximum likelihood. Finally, two applications with real data are performed by fitting the new model and comparing it with the Fréchet distribution.

Quorum sensing (QS), a well-established phenomenon in microorganisms, involves the communication between cells through chemical signals, which is dependent on cell density. Extensive research has been conducted on this microbial ability, encompassing the early stages of understanding QS to the latest advancements in the identification and characterization of its mechanisms. This minireview comprehensively examines the role of QS in various aspects, including biofilm formation, virulence in pathogenic bacteria such as Helicobacter pylori and Pseudomonas sp., as well as its influence on biogeochemical cycling in deep-sea environments. Furthermore, future progress in the field will be achieved by combining state-of-the-art methods for observing QS in the deep sea with a deeper understanding of the underlying processes, which will facilitate the engineering of microorganisms for improved degradation of persistent environmental pollutants and other biotechnological applications.

In this paper, we report orthogonal fuzzy versions of some celebrated iterative mappings. We provide various concrete conditions on the real valued functions J,S:(0,1]→(−∞,∞) for the existence of fixed-points of (J,S)-fuzzy iterative mappings. We obtain many fixed point theorems in orthogonal fuzzy metric spaces. We apply (J,S)-fuzzy version of Banach fixed point theorem to show the existence and uniqueness of the solution. We support these results with several non-trivial examples and applications to Volterra-type integral equations and fractional differential equations.

Isokinetic testing of the knee joint is the “gold standard” in strength assessment in sport especially in soccer, where it is part of pre-season screening to establish norms in case of injuries. There are many devices on the market that make it difficult to use of normative data. Isokinetics literature in females’ soccer players is scarce in comparison to males. Furthermore, evaluation protocols strongly differ from each other, using different ranges of speeds, movement patterns and output data. Thus, it is difficult for the researcher and the clinician to choose a correct protocol for isokinetic evaluation in female soccer players. The indexes of isokinetic performance that are widely accepted are the hamstring/quadriceps (H/Q) ratio and dominant/non-dominant (D/ND) ratio as reference. In this review are highlighted some common features of isokinetic testing in female soccer players of different levels of qualification. From this study, it emerges that, for a reliable test, 3 reps at the speed of 60°/sec in knee flexion/extension is preferable due to the high reliability and that an optimal H/Q ratio in healthy female soccer players of different level of qualification and age is 50%, while the interlimb differences (D/ND) should be below 10%.

The performance of two bio inoculants either in single or in combined applications with organic fertilizer was tested to determine their effect on plant growth and yield under normal and unfavorable field conditions such as low pH value and low content of P. Arbuscular Mycorrhiza Fungi ((AMF; three species of Glomus) and the plant growth-promoting bacterial strain Kosakonia radicincitans DSM16656 were applied to barley in two years field experiment with different soil pH levels and available nutrients. Grain yield, content of P, N, K, Mg, and soil microbial parameters were measured. Grain yield and content of nutrients were significantly increased by the applications of mineral fertilizer, organic fertilizer, AMF, K. radicincitans, and combined application of organic fertilizer with AMF and with K. radicincitans over the control under normal growth conditions. Under low pH and low P conditions, only the combined application of the organic fertilizer with K. radicincitans and organic fertilizer with AMF could increase grain yield and content of nutrients of barley over the control.

In the traditional power system, customers respond to their primary electricity consumption pattern based on price or incentive to take additional advantages. By developing energy hubs (EHs) where electricity, heat, natural gas and other forms of energy are coupled together, all types of energy customers even the inelastic loads can participate in demand response (DR) program. This novel vision has led to the concept of "integrated demand response (IDR)". IDR programs (IDRPs) in EHs involve coordinating multiple DR activities across different energy systems, such as buildings, industrial complexes, and transportation networks. The main purpose of IDR is that multi-energy users can respond not only by shifting or reducing energy consumption from the demand side, but also by changing the type of energy consumed, in response to the dispatching center. The integration of IDRPs in EHs can help to reduce energy costs, improve grid stability, and increase the penetration of renewable energy sources (RES) in the power system. Moreover, by synchronizing DR activities across different energy systems, IDRPs can provide additional benefits, such as improved energy efficiency, reduced greenhouse gas emissions, and increased resilience to power outages and other disruptions. In this paper, we provide a review, assessment, and classification of fundamental principles, modeling techniques and optimization methods for IDR programs in EHs.

Pharmacophores are an established concept for the modelling of ligand-receptor interactions based on the abstract representations of stereoelectronic molecular features. They became widely popular as filters for the fast virtual screening of large compound libraries. Until today a lot of effort has been put into the development of sophisticated algorithms and strategies to increase the computational efficiency of the screening process. However, hardly any focus was put on the development of automated procedures that optimise pharmacophores towards higher discriminatory power, which until today still has to be done manually by a human expert. In the age of machine learning, the researcher has become the decision-maker at the top level, outsourcing analysis tasks and recurrent work to advanced algorithms and automation workflows. Here we propose an algorithm for the automated selection of features driving pharmacophore model quality using SAR information extracted from validated QPhAR models. By integrating the developed method into an end-to-end workflow, we present a fully automated method that is able to derive best-quality pharmacophores from a given input dataset. Finally, we show how the QPhAR-generated models can be used to guide the researcher with insights regarding (un-)favourable interactions for compounds of interest.

Graphene is a remarkable material with numerous applications. Due to its thin and lightweight design, it is ideal for a variety of applications. The synthesis of high-quality graphene in a cost-effective and environmentally friendly manner continues to be a significant challenge. Chemical reduction is considered to be the most advantageous method for preparing reduced graphene oxide (rGO). However, this process necessitates the use of toxic and harmful substances, which can have a detrimental effect on the environment and human health. Thus, to accomplish the objective, the green synthesis principle has prompted researchers worldwide to develop a simple method for green reduction of graphene oxide (GO), which is readily accessible, sustainable, economical, renewable, and environmentally friendly in nature. For example, the use of natural materials such as plants is generally considered safe. Furthermore, plants contain reducing and capping agents. The current review will focus on the discovery and application of rGO synthesis using extracts from a variety of different parts of the plant. The review aims to aid current and future researchers in their search for a novel plant extract that acts as a reductant in the green synthesis of rGO. The review aims to assist current and future researchers in their research for a novel plant extract that acts as a reductant in the green synthesis of rGO as well as their potential applications in a variety of industries.

The present review is dedicated to using of peat on the example of fen peat in high added-value products and applications. Mainly, but not limited, last decade literature was analysed from the perspective of innovation potential of peat applications in environmental technologies on examples of studies from the Baltic Sea region. Paper covers a wide range of applications of peat products started from agriculture to medicine and cosmetics. A separate chapter is devoted to the deep-processed peat product - humic substances (humate, humic and fulvic salts and acids). Generalised dependence of product extraction rate and its properties, depending on the process parameters are provided. Widely are described applications of the humic sub-stance applications covering economic aspects, such as production costs. In the last chapter of the review are given recommendations for applications considering the most recent trends of peat-based product developments. This accumulated information could be useful for future production, development of new, environmentally friendly products and start-ups establishment.

Metallic thin-film materials and nanoparticles (mainly Silver (Ag)-based) are recently being used in many nano-technological applications including sensors, reflective heat-mirror coatings, and antibacterial coatings as well. The physical vapor deposition technique attracts significant attention for Ag-based nanocomposites with tailoring the structural and optical properties of metallic thin films thus allowing further improvements and application possibilities in various existing fields namely electronics, catalysis, magnetics, optics in alongside the environment and health and new emergent fields in, particularly thin-film coatings. This study highlights the preparation, characterization, properties, and possible future application directions of several types of Silver (Ag)-based nanocomposite thin films prepared by using physical vapor deposition techniques.

Natural products endowed of biological activity represent a primary source of commodities ranging from nutrition to therapeutic agents, as well as cosmetic tools, and recreational principles. These natural means have been used by mankind since centuries if not millennia. They are commonly used all over the world and socio-economical contexts but are particularly attractive in disadvantaged area or economically emerging situations all over the world. This is very likely due to the relatively easy recovery of these bioactive principles from the environment, to the low if any cost as well as ease of administration and to the general popular compliance concerning their consumption/ingestion. In this concise review, we focus on some popular bioactive principles of botanical origin which find a wide use in the Madagascan populations. But, due to space limitations only some most common and largely diffused principles in this country are considered. Finally, a possible nanotechnological administration is discussed in the case where a potential therapeutic usage is envisaged.

The concept of using eye-tracking in virtual reality for education has been researched in various fields over the past years. With this review, we aim to discuss the recent advancements and applications in this area, explain the technological aspects, highlight the advantages of this approach and inspire interest in the field. Eye-tracking has already been used in science for many decades and now has been substantially reinforced by the addition of virtual and augmented reality technologies. The first part of the review is a general overview of eye-tracking concepts and its applications. In the second part, the focus shifted towards application of eye-tracking in virtual reality. The third part is the description of the recently emerged concept of eye-tracking in virtual reality when applied to education and studying, which has not been thoroughly described before. We describe the main findings, technological aspects and advantages of this approach.

The geometry of mesoscopic inhomogeneities plays an important role in determining the macroscopic propagation behaviors of elastic waves in a heterogeneous medium. Non-equiaxed inhomogeneities can lead to anisotropic wave velocity and attenuation. Developing an accurate scattering theory to describe the quantitative relation between the microstructure features and wave propagation parameters is of fundamental importance for seismology and ultrasonic nondestructive characterization. This work presents a multiple scattering theory for strongly scattering elastic media with general tri-axial heterogeneities. A closed analytical expression of the shape-dependent singularity of the anisotropic Green’s tensor for the homogeneous reference medium is derived by introducing a proper non-orthogonal ellipsoidal coordinate. Renormalized Dyson’s equation for the coherent wave field is then derived with the help of Feynman’s diagram technique and the first-order-smoothing approximation. The exact dispersion curves and the inverse Q-factors of coherent waves in several representative medium models for the heterogeneous lithosphere are calculated numerically. Numerical results for small-scale heterogeneities with the aspect ratio varying from 1 to 7 show satisfactory agreement with those obtained from real earthquakes. The results for velocity dispersion give rise to a novel explanation to the formation mechanism of different seismic phases. The new model has potential applications in seismology and ultrasonic microstructure characterization.

The appearance of the novel betacoronavirus 2019-nCoV represents a major threat to human health, and its diffusion around the world is predicted to have dramatic economic consequences. The knowledge of the 3D structures of 2019-nCoV proteins can facilitate the development of diagnostic and therapeutic molecules. Herein, we apply our energy-based method for the prediction of potential epitopes on viral proteins to design peptide-based molecules that can subsequently be used in diagnostic and therapeutic applications. We discuss these aspects in the paper.The designs have not been tested. Our aim is to share information that can be useful in the development of novel biomolecules with potential interesting activities against 2019-nCoV.

This work promotes new methods in Mathematical Modeling, consisting in the use of the methods of Non-standard Analysis in Topoi, having as its main purpose, the mathematical definitions of the pseudoparticles from the title, with arguments from Biology/Physiology (Mathematical Neuroscience), Physics (String Theory and Emergent Quantum Mechanics), and Cybernetics (Global Brain, including Natural and Artificial Intelligence). The connections between brain and mind will be scketched via the genetic/epigenetic interplay. The topoi model the intuitionistic logic (multi-valued) and have been used in Quantum Physics while Non-Standard Analysis in SET (= the Category of sets) has been applied in Mathematical Economics; topics from Theory of Categories were also used in the study of Consciousness; however, the combination topoi - non-standard analysis was never used until now in Applied Mathematics. Another important objective is to produce progress in this aria of Pure Mathematics also - the build of non-standard analysis in classes of topoi, already used in Physics. We propose the logic of non-standard extensions in topoi as a model of the human thinking (based on infons/receptons), these theories representing new top and very difficult results in Abstract Mathematics either.

A novel configuration for a super-wide impedance planar antenna is presented based on a 2 × 2 microstrip patch antenna (MPA). The antenna comprises a symmetrical arrangement of four-square patches that are interconnected to each other with cross-shaped high impedance microstrip lines. The antenna array is exciting through a single feedline connected to one of the patches. The proposed antenna array configuration overcomes the main drawback of conventional MPA of narrow bandwidth that is typically <5%. The antenna exhibits a super-wide frequency bandwidth from 20 GHz to 120 GHz for S₁₁<−15 dB, which corresponds to a fractional bandwidth of 142.85%. The antenna’s performance of bandwidth, impedance match, and radiation gain were enhanced by etching slots on the patches. The slotted microstrip patch essentially acts like a left-handed capacitance to exhibit metamaterial properties over a given frequency range. With the inclusion of the slot the maximum radiation gain and efficiency of the MPA have increased to 15.11 dBi and 85.79% at 80 GHz, which show an improvement of 2.58 dBi and 12.54%, respectively. The dimension of each patch antenna is 30 × 30 mm². The results show that the proposed MPA is useful for various communications existing and emerging systems such as ultra-wideband (UWB) communications, RFID systems, massive multiple-output multiple-input (MIMO) for 5G, and radar systems.

Opportunistic routing uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward.

Today with enhancement in technology, sciences, there is also an increase in global heating rate. There is an urgent need of any alternate efficient source to reduce the wastage of energy and to utilize it efficiently. The advanced preparation of Expanded graphite ,lauric acid, stearic acid as shape stabilized phase change material deals with different energy harvesting applications. The main reason behind the need for synthesis of this matrix is to prepare a material that can be used in low temperature energy storage applications. Mixture of lauric acid , stearic acid impregnated in expanded graphite through vacuum impregnation followed by Vacuum Drying and Microwave acid treatment serves as novel shape stabilized phase change material of its type. The microwave acid treatment was done in order to increase the removal of moisture from the sample thus initiating proper bonding of its constituents. The mixture was produced in 1:1:1 ratio where all expanded graphite, lauric acid , stearic acid has one proportions of each other. The product obtained after microwave acid treatment was subjected to SEM, DSC analysis

Microbubbles and nanobubbles can be prepared using various shells, such as phospholipids, polymers, proteins, and surfactants. They are echogenic and can be used as contrast agents for ultrasonic and photoacoustic imaging. These bubbles can be engineered in various sizes as vehicles for gas and drug delivery applications with novel properties and flexible structures. Hypoxic areas in tumors develop owing to an imbalance of oxygen supply and demand. In tumors, hypoxic regions have shown more resistance to chemotherapy, radiotherapy, and photodynamic therapies. The efficacy of photodynamic therapy depends on the availability of oxygen in the tumor to generate reactive oxygen species. Micro/nanobubbles have been shown to reverse hypoxic conditions and increase tissue oxygen levels. This review summarizes the synthesis methods and shell compositions of micro/nanobubbles and methods deployed for oxygen delivery. In addition, the shortcomings and prospects of engineering micro/nanobubbles are discussed for their potential use in photodynamic therapy.

Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

Thermal-expandable microcapsules (TEMs) for water-based coatings were synthesized with co-polymer of Acrylonitrile (AN) - Methyl methacrylate (MMA) - Ethylhexyl acrylate (EHA) - Divinylbenzene (DVB) as shell and toluene-p-sulfonyl hydrazide as core by suspension polymerization method. It was found that the microcapsules with desirable thermal expansion property and good heat stability could be obtained with a shell monomers composition of 70% AN /20% MMA /9% EHA /1% DVB. When 2% styrene-maleic acid copolymer (SMC) as emulsifier and 3% poly (vinyl pyrrolidone) (PVP) as dispersing agent were used, well defined spherical and more uniform microcapsules could be prepared. It was also found that when the shell/core mass ratio was 3:1, an encapsulation efficiency of ca. 94.5% could be achieved. Beyond this ratio, the increase of encapsulation efficiency reached a plateau. The 100 μm thickness film of water-based coating containing 5% microcapsules could be expanded to the thickness of 450 μm after exposed at 150 °C for 2 minutes. TG analysis revealed the mass loss start temperature of coating increased by more than 30 °C when 5% microcapsules were added to water-based coatings, which demonstrated the flame-retardant function of the coatings.

Background: Evaluating muscle mass and function among stroke patients is important. However, evaluating muscle volume and function is not easy due to the disturbance of consciousness and paresis. Temporal muscle thickness (TMT) has been introduced as a novel surrogate marker for muscle mass, function, and nutritional status. We herein performed a narrative literature review on temporal muscle and stroke to understand the current meaning of the TMT in the clinical stroke practice. Methods: The search was performed in PubMed, last updated in October 2021. Report on temporal muscle morphomics and stroke-related diseases or clinical entities were collected. Results: Four studies reported on TMT and subarachnoid hemorrhage, 2 intracerebral hemorrhage, 2 ischemic stroke, 2 standard TMT values, and 2 nutritional status. TMT was reported as a prognostic factor for several diseases, surrogate markers for skeletal muscle mass, and an indicator of nutritional status. Computed tomography, magnetic resonance imaging, and ultrasonography were used to measure TMT. Conclusions: TMT is gradually used as a prognostic factor of stroke or surrogate marker for skeletal muscle mass and nutritional status. Establishing standard methods to measure TMT and large prospective studies to investigate the further relationship between TMT and diseases are needed.

The globe and more particularly the economically developed regions of the world are currently in the era of the fourth Industrial revolution (4IR). Conversely; the economically developing regions in the world and more particularly the African continent have not yet even fully passed through the Third Industrial Revolution (3IR) wave and its economy is still heavily dependent on the agricultural field. On the other hand, the state of global food insecurity is worsening on an annual basis thanks to the exponential growth of the global human population which continuously heightens the food demand in both quantity and quality. This justifies the significance of the focus on digitizing agricultural practices to improve the farm yield to meet up with the steep food demand and stabilize the economy of the African continent and countries like India whose economy is mainly dependent on Agriculture. The tools we have at our disposal to utilize in the digitization of farming practices include space technology and Global Navigation and Satellite System (GNSS) in particular, Machine learning (ML), precision agriculture and communication systems such as the Internet of Things (IoT) and Information And Communication Technologies (ICT). The most pressing challenges in the farming field include the monitoring of diseases, pests, weeds and nutrient deficiencies in the crops as early detection translates to swift and timely correction actions and hence more yield at the end of a farming cycle. Vast opportunities in the field of precision agriculture still exist that can amount to further research studies such as the lack of real-time monitoring and real-time corrective action focus.