Dielectric spectroscopy (DS) is a promising cell screening method that can be used for diagnostic and drug discovery purposes. The primary challenge of using DS in physiological buffers is the electrode polarization (EP) that overwhelms the impedance signal within a large frequency range. These effects further amplify with miniaturization of the measurement electrodes. In this study, we present a microfluidic system and the associated equivalent circuit models for real-time measurements of cell membrane capacitance and cytoplasm resistance in physiological buffers with 10s increments. The current device captures several hundreds of biological cells in individual microwells through gravitational settling and measures the system’s impedance using microelectrodes covered with dendritic gold nanostructures. Using PC-3 cells (a highly metastatic prostate cancer cell line) suspended in cell growth media (CGM), we demonstrate stable measurements of cell membrane capacitance and cytoplasm resistance in the device for over 15 minutes. We also describe a consistent application of the equivalent circuit model, starting from the reference measurements used to determine the system parameters. The circuit model is tested using devices with varying dimensions, and the obtained cell parameters between different devices are nearly identical. Further analyses of the impedance data have shown that accurate cell membrane capacitance and cytoplasm resistance can be extracted using a limited number of measurements in the 5 MHz to 10 MHz range. This will potentially reduce the timescale required for real-time DS measurements below 1s. Overall the new microfluidic device can be used for dielectric characterization of biological cells in physiological buffers for various cell screening applications.

Abstract The aim of the present review is to discuss the roles of vitamin K and vitamin K-dependent proteins, and the combined action of the vitamins K and D, for maintenance of bone health. The most relevant vitamin K-dependent proteins in this respect are osteocalcin and matrix Gla-protein (MGP). When carboxylated these proteins appear to have the ability to chelate and import calcium from the blood to the bone, thereby reducing the risk of osteoporosis. Carboxylated osteocalcin appears to contribute directly to bone quality and strength. Adequate vitamin K status is required for carboxylation of MGP and osteocalcin. In addition, vitamin K acts on bone metabolism by other mechanism, such as a ligand for the nuclear steroid and xenobiotic receptor (SXR). In this narrative review, we examine the evidence for increased bone mineralization through dietary adequacy of vitamin K (phylloquinone or menaquinone). Summarizing the evidence for a synergistic effect of vitamin K and vitamin D3 we find that an adequate supply of vitamin K on top of an optimal vitamin D status seems to add to the benefit for maintaining bone health. More research related to synergism and possible mechanisms of vitamins D3 and K interaction in bone health is needed.

Coronavirus disease (COVID-19) is an infectious disease caused by a new virus which causes respiratory illness. Older adults and people who have previous chronic medical conditions are at higher risk for more serious complications from COVID-19.Hypovitaminosis D is attributed to the increased risk of lung injury and acute respiratory distress syndrome (ARDS) as well as diabetes, Cardiovascular event and associated comorbidities, which are the main causes of severe clinical problem in COVID-19 patients. Considering the protective role of vitamin D through modulating the innate and adaptive immune system as well as inhibition of Renin Angiotensin System (RAS), vitamin D supplementation might boost the immune system of COVID-19 patients and reduce severity of the disease in vitamin D deficient individuals.

We describe electron temperature measurements in the SSX MHD wind tunnel using two different methods. First, we estimate T_e along a chord by measuring the ratio of the C__III 97.7 nm to C_IV 155 nm line intensities using a vacuum ultraviolet monochrometer. Second, we record a biasing scan to a double Langmuir probe to obtain a local measurement of T_e. The aim of these studies is to increase the Taylor state lifetime, primarily by increasing the electron temperature. Also, a model is proposed to predict magnetic lifetime of relaxed states and is found of predict the lifetime satisfactorily. Furthermore, we find that proton cooling can be explained by equilibration with the electrons.

The narrow process window during intercritical annealing and discontinuous yielding have limited the commercialisation of medium Mn steels. In this study, a double annealing process based on the commercial continuous annealing line is proposed. The cold-rolled medium Mn steels were first fully austenitized and quenched during the first annealing, followed by the intercritical annealing for reverted austenite transformation. The microstructure of duplex lath-shaped austenite and ferrite is produced and the steel exhibit a desirable continuous yielding during tensile deformation. Al is added into the medium Mn steel to enlarge the process window and to improve partitioning efficiency of Mn. The produced steel is more robust with temperature fluctuation during the industrial process due to the enlarged intercritical region. Mn partitioning is more efficient owing to elevated annealing temperature, which results in the improvement of ductility in the Al-added steel with increased austenite stability.

In this work we explored how solvents can affect olefin oxidation reactions catalyzed by MCM-bpy-Mo catalysts and whether their control can be made with those players. The results of this study evidenced that polar and apolar aprotic solvents modulated the reactions in different ways. Experimental data showed that acetonitrile (aprotic polar) could hinder largely the reaction rate whereas toluene (aprotic apolar) did not. In both cases product selectivity at isoconversion was not affected. Further insights were obtained by means of neutron diffraction experiments, which confirmed the kinetic data allowing to propose a model based on substrate-solvent crosstalk by means of hydrogen bonding. In addition, the model was also validated in the ring-opening reaction (overoxidation) of styrene oxide towards benzaldehyde, which progressed when toluene was the solvent (reaching 31% styrene oxide conversion) but was strongly hindered when acetonitrile was used instead (reaching only 7% conversion), due to the establishment of H-bonds in the latter. Although this model was confirmed and validated for olefin oxidation reactions, it can be envisaged that it may also be applied to other catalytic reaction systems where reaction control is critical, while widening its use.

Abstract: Agroforestry has a sustainable attributes with both tangible and nontangible benefits. In this study carbon mitigation and credits potential of traditional agroforestry systems at different elevations were evaluated. These traditional systems are: Agrihortisilviculture system (AHS), Agrihorticulture system (AH) and Agrisilviculture system (AS). Stand density, living biomass carbon and soil carbon were measured in each sample plot. The results were that stand density of woody perennials varied from 61 to 233 tree ha-1 across t elevations and systems, and , Grewia oppositifoila was the predominant tree species occupying most of the agroforestry land use system. Plant and soil organic carbon were significantly different (P ≤ 0.05) among systems and elevations. Total carbon including plant and soil was significantly higher in the AH system at upper elevations. Total carbon emmision mitigation varied with changing elevations and systems, being highest at lower elevation with AHS system. The total carbon credits was also recorded high at lower elevation, whereas the total value of C credits was higher at mid elevation due to the estimated agroforestry area. The total value of C credits from all agroforestry systems was observed (128977.59 €) of the study area.

The genus Fritillaria belongs to the widely distributed family Liliaceae. The bulbs of Fritillaria ussuriensis and Fritillaria cirrhosa are valuable herbaceous medicinal ingredients. However, they are still used indiscriminately in herbal medicine. Identification and molecular phylogenic analysis of Fritillaria species is therefore required. Here, we report the complete chloroplast (cp) genome sequences of F. ussuriensis and F. cirrhosa. The two Fritillaria cp genomes were 151,524 and 151,083 bp in length, respectively, including a pair of inverted repeat regions (52,678 and 52,156 bp) separated by a large single copy region (81,732 and 81,390 bp) and small single copy region (17,114 and 17,537 bp). A total of 111 genes in F. ussuriensis and 112 in F. cirrhosa comprised 77 protein-coding genes in F. ussuriensis and 78 in F. cirrhosa, 30 tRNA genes, and four rRNA genes. The gene order, content, and orientation of the two Fritillaria cp genomes exhibited the general structure of flowering plants, and were similar to those of other Fritillaria species. Comparison of the six Fritillaria species’ cp genomes indicated seven highly divergent regions in intergenic spacers and in the matK, rpoC1, rpoC2, ycf1, ycf2, ndhD, and ndhF coding regions. We established the position of the six species through phylogenic analysis. The complete chloroplast genome sequences of two Fritillaria species will be useful genomics resources for identification of Fritillaria species and for studying the phylogenetic relationship among Fritillaria species within the Liliaceae family.

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.

Energy harvesting from wind turbines has been explored by researchers for more than a century from conventional turbines up to the latest bladeless turbines. Amongst these bladeless turbines, vortex bladeless wind turbine (VBT) harvests energy from oscillation of a turbine body. Due to the novelty of this science and the widespread researches around the world, one of the most important issues is to optimize and predict produced power. To enhance the produced output electrical power of VBT, the fluid-solid interactions (FSI) were analyzed to collect a dataset for predicting procedure. Long short-term memory (LSTM) method has been used to predict the produced power of VBT from the collected data. The reason of choosing LSTM from various artificial neural network methods is that the parameters of VBT study are all time- dependent and the LSTM is one of the most accruable algorithms for predicting time series data. In order to find the relationship between the parameter and the variables used in this research, a correlation matrix was presented. According to the value of 0.3 for the root mean square error (RMSE), a comparative analysis between the simulation results and its prediction shows that the LSTM method is very accurate for these types of research. Furthermore, the LSTM method has significantly reduced the computation time so that the prediction time of desired values has been reduced from an average of 2 and a half hours to two minutes. Also, one of the most important achievements of this study is to suggest a mathematical relation of VBT output power which helps to extend it in a different size of VBT with a high range of parameter variations.

Accurate forecasts of ocean waves energy can not only reduce costs for investment but it is also essential for management and operation of electrical power. This paper presents an innovative approach based on the Long Short Term Memory (LSTM) to predict the power generation of an economical wave energy converter named “Searaser”. The data for analyzing is provided by collecting the experimental data from another study and the exerted data from numerical simulation of searaser. The simulation is done with Flow-3D software which has high capability in analyzing the fluid solid interactions. The lack of relation between wind speed and output power in previous studies needs to be investigated in this field. Therefore, in this study the wind speed and output power are related with a LSTM method. Moreover, it can be inferred that the LSTM Network is able to predict power in terms of height more accurately and faster than the numerical solution in a field of predicting. The network output figures show a great agreement and the root mean square is 0.49 in the mean value related to the accuracy of LSTM method. Furthermore, the mathematical relation between the generated power and wave height was introduced by curve fitting of the power function to the result of LSTM method.

In this paper, closed forms of the sum formulas $\sum_{k=0}^{n}x^{k}W_{k}^{3}$ and $\sum_{k=1}^{n}x^{k}W_{-k}^{3}$ for the cubes of generalized Fibonacci numbers are presented. As special cases, we give sum formulas of Fibonacci, Lucas, Pell, Pell-Lucas, Jacobsthal, Jacobsthal-Lucas numbers.

To stabilize the Earth’s climate a large-scale transition is needed to non-carbon emitting renewable energy technologies like wind and solar energy. Although these renewable energy sources are now lower-cost than fossil fuels, their inherent intermittency make them unable to supply a constant load without storage. To address these challenges rechargeable electric batteries are currently the most promising option; however, their high capital costs limit current deployment velocities. To both reduce the cost as well as improve performance 3D printing technology has emerged as a promising solution. This literature review provides the state-of-the-art enhancements of battery properties with 3D printing including efficiency, mechanical stability, energy and power density, customizability and sizing, production process efficiency, material conservation and environmental sustainability as well as the progress in solid-state batteries. The principles, advantages, limitations, and recent advancements associated with the most common types of 3D printing are reviewed focusing on their contributions to the battery field. 3D printing batteries offer design flexibility, material flexibility, reduces pack weight, minimizes material waste, increases the range of applications and has the potential to reduce costs. As 3D printing technologies become more accessible, the prospect of cost-effective production for customized batteries is extremely promising.

Bacteria play a key role in both human health and disease. One of the most prevalent harmful bacteria is E. coli which is responsible for several illnesses ranging from diarrhea, stomach cramp and fever. In this work we explore the application of moderate electric or magnetic fields for treating deionized water that is contaminated with E. coli. We found that moderate alternating electric (AC) fields (10 V/cm to 1kV/cm) and moderate static magnetic fields (10 to 65 mT) can significantly inactivate E. coli by up to 90% or more. This provides the possibilities of developing a low cost and a practical bacteria inactivation technique using electric or magnetic fields.

The legume-rhizobia symbiosis is one of the most important plant-microbe interactions in sustainable agriculture due to its ability to provide much needed N to cropping systems. This interaction is mediated by the mutual recognition of signaling molecules from the two partners, namely legumes and rhizobia. With legumes, these molecules are in the form of flavonoids and anthocyanins, which are responsible for the pigmentation of plants parts, such as seeds, flowers, fruits and even leaves. Seed coat pigmentation in legumes is a dominant factor influencing gene expression relating to N2 fixation, and may be responsible for the different N2-fixing abilities observed among legume genotypes under field conditions in African soils. Cowpea, Kersting’s bean and Bambara groundnut landraces with black seed coat color are reported to release higher concentrations of nod-gene-inducing flavonoids and anthocyanins when compared to the Red and Cream landraces, hence the black seed coat pigmentation is considered a biomarker for enhanced nodulation and N2 fixation. Cowpea, Bambara groundnut and Kersting’s bean with differing seed coat colors are known to attract different native soil rhizobia, confirmable by PCR-RFLP analysis of bacterial DNA from root nodules of these legumes. Even when seeds of the same legume with diverse seed coat colors were planted together in one hole, the nodulating bradyrhizobia clustered differently in the PCR-RFLP dendrograms. In one study, Kersting’s groundnut, Bambara groundnut and cowpea with differing seed coat colors were selectively nodulated by different bradyrhizobial species. Multilocus sequence analysis showed that different Bradyrhizobium species nodulated the Kersting's bean based on seed coat color. Phylogenetic analysis also placed the bradyrhizobial isolates in close proximity to different Bradyrhizobium species such as B. vignae 7-2T, B. subterraneum 58 2-1T, B. kavangense 14-3T, B. liaoningense 2281 (USDA 3622)T, B. yuanmingense LMG 21827T, B. huanghuaihaiense CCBAU 23303T, B. pachyrhizi PAC48T, and a reference type strain of B. elkanii according to seed coat color. Using 16S rDNA amplicon sequencing, we also found significant selective influences of seed coat pigmentation on microbial community structure in the rhizosphere of five Kersting’s groundnut landraces. For example, the rhizosphere of Belane Mottled landrace was dominated by Proteobacteria, while Bacteroidetes dominated the rhizospheres of the other landraces. With legumes, seed coat pigmentation therefore plays a dominant role in the selection of the bacterial symbiotic partner.

In this paper, the problem of autonomous optimal absolute orbit keeping for a satellite mission in Low Earth Orbit using electric propulsion is considered. The main peculiarity of the approach is to support small satellite missions in which the platform is equipped with a single thruster nozzle which provides acceleration on a single direction at a time. This constraint implies that an attitude maneuver is necessary before or during each thrusting arc to direct the nozzle into the desired direction. In this context, an attitude guidance algorithm specific for the orbit maneuver has been developed. A Model Predictive Control scheme is proposed, where the attitude kinematics are coupled with the orbital dynamics in order to obtain the optimal guidance profiles in terms of satellite state, reference attitude, and thrust magnitude. The proposed control scheme is developed exploiting Formation Flying techniques where the reference orbit is that of a virtual spacecraft that the main satellite is required to rendezvous with. In addition to the controller design, the closed loop configuration is presented supported by numerical simulations. The efficacy of the proposed autonomous orbit keeping approach is shown in several application scenarios.

The effectiveness of Fuzzy Inference Systems (FISs) in manipulating uncertainty and nonlinearity makes them a subject of significant interest for decision-making in embedded systems. Accordingly, optimizing FIS hardware improves its performance, efficiency, and capabilities, leading to a better user experience, increased productivity, and cost savings. To be compatible with the limited power budget in most embedded systems, this paper presents a framework to realize ultra-low power FIS hardware. It supports optimizations for both conventional arithmetic as well as MSDF-computing to be highly consistent with MSDF-based sensors. In MSDF-computing FIS all the processes of fuzzification, inference, and defuzzification are done on serially coming data bits. To demonstrate the efficiency of the proposed framework, we utilized Matlab, Chisel3, and Vivado to implement it from high-level descriptions of FIS to hardware synthesis. We also developed a Scala library in Chisel3 to establish a connection between these tools, bridging the gap, and facilitating design space exploration at the arithmetic level. Furthermore, we realized an FIS for the navigation of autonomous mobile robots in unknown environments. Synthesis results show the superiority of the output of our suggested design framework in terms of resource usage as well as power and energy consumption compared to the Matlab HDL code generator output.

Much has been learned about the interaction between myosin and actin through biochemistry, in vitro motility assays and cryo-electron microscopy of F-actin decorated with myosin heads. Comparatively less is known about actin-myosin interactions within the filament lattice of muscle, where myosin heads function as independent force generators and thus most measurements report an average signal from multiple biochemical and mechanical states. All of the 3-D imaging by electron microscopy that has revealed the interplay of the regular array of actin subunits and myosin heads within the filament lattice has been accomplished using the flight muscle of the large waterbug Lethocerus sp. Lethocerus flight muscle possesses a particularly favorable filament arrangement that enables all the myosin cross-bridges contacting the actin filament to be visualized in a thin section. This review covers the history of this effort and the progress toward visualizing the complex set of conformational changes that myosin heads make when binding to actin in several static states as well as fast frozen actively contracting muscle. The efforts have revealed a consistent pattern of changes to the myosin head structures determined by X-ray crystallography needed to explain the structure of the different acto-myosin interactions observed in situ.

The excessive intake of sodium (Na) and insufficient intake of potassium (K) are major concerns to prevent hypertension. Using low-Na/K seasonings (reducing 25% of the NaCl and adding K salt) may improve the dietary Na/K ratio and help prevent hypertension. To devise an intervention study using low-Na/K seasonings at a company cafeteria, we calculated the Na and K contents of the meals served at the cafeteria and estimated changes in the intakes when suitable low-Na/K seasonings were used. We also considered using milk as a good source of K. We used an ingredient list of a company cafeteria and calculated Na and K contents in each dish. The average amounts of NaCl and K per use were 5.04 g and 718 mg, respectively. Seasonings contributed 70.9% of the NaCl. With the use of low-Na/K seasonings, an estimated reduction in NaCl of 0.8 g/day and an estimated increase in K of 308 mg/day was achieved. An additional serving (200 mL) of milk, NaCl was reduced by 0.57 g/day and K was increased by 610 mg/day, with an overall decrease in the dietary Na/K ratio from 3.20 to 2.40. The use of low-Na/K seasonings and dairy may improve the dietary Na/K ratio among cafeteria users and help prevent hypertension.

Current trends in systemic risk literature provide new insights into multi-hazard risks that interact and compound with built environments, creating more significant impacts on socio-economic and human systems. Recurrent natural hazards and extreme weather events are more likely to compound and cascade into more impactful events, especially in vulnerable societies. In small-island communities (SICS), including large archipelagos and Small Island Developing States (SIDS), the long-term impact of multi-, compounding-, and cascading-hazards (MCC hazards) can result in persistent vulnerability and residual risks. This is due to delayed responses, limited resources, poverty, fewer evacuation options, and inadequate markets and infrastructure. Using Ternate, a densely populated small volcanic island in North Maluku, Indonesia, as a case study, this paper assesses the impacts of seven types of natural hazards: flash floods, landslides, extreme weather, extreme waves and abrasion, earthquakes, tsunamis, and volcanic eruptions. The research focuses on the multi-hazard impact on population, land use, and infrastructure exposures in 60 villages in Ternate. The findings highlight population density, land use, and infrastructure exposure to multi-hazard risks, providing valuable information on potential losses in future hazard events.

As technology evolves, our digital footprint keeps increasing. Now, everything we do is largely related to us being online, connected and logged. Therefore, if someone’s online data is exposed, then their life will be compromised. This is called identity theft and in this era of technology, it has become one of the most serious forms of crime. When someone’s data is compromised, there is a huge chance of harming the person financially, morally and socially. New technology and the knowledge gap it creates when it first comes out is perfect for identity thieves to exploit. If we are not cautious, our future will be very different than what we dream of due to the very technology created to make it better. Hence, we need to understand the technology, identify the loopholes and educate ourselves to avoid being held captive by our digital footprint.

Aflatoxins, which have been classified as a group-1 carcinogen are the well-known mycotoxins produced by Aspergillus flavus. Aflatoxins have been linked to liver diseases, acute hepatic necrosis, resulting in cirrhosis or hepatocellular carcinomas due to which it incurs a loss of value in international trade for peanuts contaminated with it. The four main aflatoxins are B1, B2, G1, and G2 of which B1 is predominant. In plants, the cell wall is the primary barrier against pathogen invasion. Cell wall fortifications such as deposition of callose, cellulose, lignin, phenolic compounds and structural proteins help to prevent the pathogen infection. Further, the host cell’s ability to rapidly repair and reinforce its cell walls will result in a reduction of the penetration efficiency of the pathogen. Peanut seed coat acts as a physical and biochemical cell wall barrier against both pre and post-harvest pathogen infection. The structure of seed coat and the presence of polyphenol compounds have been reported to inhibit the growth of A. flavus, however, not successfully employed to develop A. flavus resistance in peanut. A comprehensive understanding of peanut seed coat development and biochemistry will provide information to design efficient strategies for the seed coat mediated A. flavus resistance and Aflatoxin contamination.

The design of highly efficient sensitizers is one of the most significant areas in dye-sensitized solar cell (DSSC) research. We have studied a series of benzothiadiazole-based D-π-π-A organic dyes, putting emphasis on the influence of the donor moiety on the DSSC’s efficiency. Using linear response time-dependent density functional theory (TDDFT) with the CAM-B3LYP functional different donor groups were characterized in terms of electronic absorption spectra and key photovoltaic parameters. As a reference a dye has been considered which has a benzothiadiazole fragment linked via thiophene rings to a diphenylamine donor and a cyanoacrylic acid acceptor. The different systems are first studied in terms of individual performance parameters, which are eventually aggregated into the power conversion efficiency. Here only the amino-substituted species shows a modest increase, whereas the dimethylamino case even shows a decrease.

Cariogenic oral biofilms cause a considerable amount of recurrent dental caries around composite restorations every year, resulting in unprosperous oral health status and expensive restorative treatment for many patients. Quaternary ammonium monomers that can be copolymerized with the current dental resin systems have been increasingly explored for modulation of dental plaque biofilm growth over dental composite surfaces. Here, we investigated the effect of bis(2-methacryloyloxyethyl) dimethylammonium bromide (QADM), against human overlying mature oral biofilms grown intra-orally in human participants for 7 and 14 days, for the first time. Seventeen volunteers wore palatal devices containing composite specimens containing 10% by mass of QADM or a control composite without QADM. After 7 and 14 days, the adherent biofilms were collected for determination of bacterial counts via colony-forming unit (CFU) counts. The biofilm viability, chronological changes, and percentage coverage were also determined by live/dead staining. QADM composites caused a significant inhibition of S. mutans biofilm formation for up to seven days. No difference in the CFU values were found for the 14-day period. Our findings suggest that (1) QADM composite was successful in inhibiting 1-3 day biofilms in the oral environment in vivo; (2) QADM significantly reduced the portion of S.mutans group in a time course where patients at high risk of caries would develop initial enamel carious lesions; and (3) stronger antibiofilm activity is required for the control of mature long-term cariogenic biofilms. These results provide a perspective on the value of integrating bioactive restorative materials with traditional caries management approaches into clinical practice. Contact-killing strategies via dental materials aiming to prevent or at least reduce high numbers of cariogenic bacteria seem to be a promising approach in patients at high risk of recurrence of dental caries around composites.

Pregnancy entails bidirectional interactions between the developing fetus, the maternal tissues, and the organ systems. To this end, the phenomenon of migration of fetal cells (FCs) into the maternal circulation is poorly understood. Here, we review literature underlying the migration of FCs from the placenta to the maternal circulation, which is likely a dynamic process, including trophoblast invasion, placental angiogenesis, modulation of maternal immune responses, and enlargement of maternal organs. As placental neovascularization fosters direct connections between fetal and maternal circulatory systems, the trophoblast, a pivotal to placental development, adeptly deploys an array of invasive strategies to breach maternal tissue barriers, facilitating FC escapade into the maternal circulation. The intricate balance struck by the maternal immune system, which both acts as a guardian against potential foreign cell threats and orchestrates a niche conducive to FC survival and differentiation, is facilitated by finely tuned interactions among regulatory T cells, cytokines, and inhibitory receptors. FC presence in mothers’ circulation may be clinically relevant and unveil novel molecular participants like lncRNA, exosomes, and intricate signaling pathways that drive innovative clinical approaches for diagnostics and therapeutics. Ongoing research should reshape our knowledge of pregnancy and maternal-fetal health by improving our understanding of fetal-maternal interactions.

Dielectric barrier discharge (DBD) plasma has several applications in different fields. One of these fundamental applications is medical usages, where various methods are employed to improve the plasma treatment process. The combination of different gases is one of the important strategies to improve the performance of plasma in treatment. In this paper, the optimized plasma parameters for one-dimensional radiofrequency discharge produced at low pressures in a helium gas combination is studied. In this research, the optimal combination of H₂O and He is identified to attain the highest amount of reactive oxygen species (ROS). Considered mixture are 5,10,15 and 20 precent of H₂O for one dimensional helium gas discharge. The results show that the parameters of the output plasma are highly dependent on the composition of the input gases. It is found that the greatest concentrations of H+, He+, Hes (excited helium), and OH/ densities are observed when the H₂O percentage is 10%. Moreover, the density distributions of various species and the temperatures of electrons are numerically calculated during the electrical discharge process. These findings provide useful knowledge on how to optimize plasma parameters for biomedical applications, which may lead to improved treatment results in several therapeutic areas.

In this work, the possibility of fabrication magneto-optical ceramics by vacuum sintering of compacts prepared by electrophoretic deposition (EPD) from suspensions of (Ho0.95La0.05)2O3 (HoLa) nanopowders made by self-propagating high-temperature synthesis and (Y0.9La0.1)2O3 (YLa) nanopowders made by laser synthesis was systematically investigated. The processes of the formation of bulk one- and two-layer compacts by the EPD method from non-aqueous suspensions of nanopowders was studied. The use of acetylacetone and polyvinyl butyral (PVB) was shown to make it possible to obtain stable alcohol suspensions of the nanopowders characterized by high zeta potential values (+29…+80 mV) and to carry out a stable EPD process. One-layer compacts were made from the YLa and HoLa nanopowders with a density of 30–43%. It was found out that the introduction of PVB into the suspension leads to a decrease in the mass and thickness of the green bodies deposited, but does not significantly affect their density. A possibility to make two-layers (YLa/HoLa) compacts with a thickness of up to 2.6 mm and a density of up to 46% was demonstrated. Sintering such compacts in a vacuum at a temperature of 1750°C for 10 hours leads to the formation of ceramics with a homogeneous boundary between the YLa/HoLa layers and thickness of the interdiffused ions layer of about 30 μm.

The first two decades of the 21st-century have seen the emergence of the modern citizen science movement, increased demand for niche eco and wildlife tourism experiences, and the willingness of people to voluntarily share information and photographs online. To varying extents, the rapid growth of these three phenomena has been driven by the availability of portable smart devices, access to the Web 2.0 internet from almost anywhere on the planet, and the development of applications and services, including social media/networking sites (SNSs). In addition, the number of peer-reviewed publications that explore how text and images shared on SNSs can be data-mined for academic research has surged in recent years. This systematic quantitative review has two goals. The first goal is to provide an oversight of how the photographs that ecotourists share online are contributing to wildlife tourism research. The second goal is to promote the emerging photovoice technique as a theoretical context for social research based on the photographs and comments that ecotourists share on SNSs. From the perspectives of community benefits, conservation behaviours, and environmental education, there are many similarities between authentic ecotourism experiences and quality ecological citizen science programs. Much of the literature regarding the theory and practice of citizen science reports on the difficulties of attracting, training, motivating and retaining community members. The synthesis of this review is that crowdsourcing wildlife and tourism data from comments and photographs that ecotourists share on SNSs is a credible method of research that provides a self-replenishing pool of citizen scientists.

In this paper, we study the third order semilocal convergence of the Newton-like method for finding the approximate solution of nonlinear operator equations in the setting of Banach spaces. First, we discuss the convergence analysis under ω-continuity condition, which is weaker than the Lipschitz and Hölder continuity conditions. Second, we apply our approach to solve Fredholm integral equations, where the first derivative of involved operator not necessarily satisfy the Hölder and Lipschitz continuity conditions. Finally, we also prove that the R-order of the method is 2p + 1 for any p $\in$ (0,1].

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

This study aims to determine the present and future scopes of the digital economy in Bangladesh to build a developed and prosperous country by 2041. Simultaneously, it analyses the components of the Digital Economy from numerous perspectives from contributing to Bangladeshi economy with an adaptation of the 4th Industrial Revolution and emerging technologies. In the methodology section, qualitative approach is conducted to determine the research objectives where secondary data is used. Around 100 papers are collected and 51 articles are used for conducting this study. The findings of the study are to present the current state of the digital economy which is developing trends that contribute to national GDP for the adaptation of the 4IR for the transformation of smart Bangladesh. From the conceptual implication, companies and individuals are aware of the digital economy, which would lessen digital divide and create a strong link between technology and the economy. Furthermore, establishing customer confidence and trust would be a big issue for Bangladesh's digital platform economy in the future days. From a practical standpoint, IT industries and commercial organizations would have to deal with emerging 4IR and its technologies. The job market would also be expanded in a variety of areas, which would ultimately benefit the national economy. According to the study's conclusions, the digital economy is predicted to expand its commercial and corporate opportunities. Future research might be extended based on qualitative approach towards a digital Bangladesh and create a better developing economy.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

A polymer inclusion membrane (PIM) composed of 50 wt% poly(vinylidenefluoride-co-hexafluoropropylene) (PVDF-HFP) as its base polymer, 40 wt% Aliquat® 336 as its extractant and 10 wt% dibutyl phthalate (DBP) as plasticizer provided efficient extraction of vanadium(V) from its sulfate solutions adjusted to pH 2.5. It was suggested that V(V) was extracted as VO2SO4− via an anion exchange mechanism. Quantitative back-extraction was achieved in a sulfuric acid solution (6 mol L-1) containing 1 v/v% of hydrogen peroxide. It was assumed that the back-extraction process involved the oxidation of VO2+ to VO(O2)+ by hydrogen peroxide. The newly developed PIM with the optimized composition mentioned above exhibited excellent selectivity for V(V) in the presence of metallic species present in digests of spent alumina hydrodesulfurization catalysts (i.e., Al(III), Co(II), Cu(II), Fe(III), Mn(II), and Ni(II)). The co-extraction of Mo(VI) with V(V) was eliminated by its selective extraction at pH 1.1. The optimized PIM was characterized by contact angle measurements, atomic-force microscopy (AFM), energy dispersive X-ray spectroscopy (EDS), thermogravimetric analysis (TGA)/derivatives thermogravimetric analysis (DTGA), and the stress-strain measurements.

In response to the National Institutes of Health (NIH) All of Us Medicine Research Initiative, the Precision Medicine Research (PreMeR) Diversity Consortium was formed by four institutions from the Research Centers in Minority Institutions (RCMI) Translational Research Network (RTRN). This synergistic approach proposed evidence-based, best practices used by experienced researchers to engage, recruit and retain diverse populations in the All of Us initiative. Conceptualization of the proposed approach was aided by social influence theories to better understand how people’s beliefs and opinions should be modified to affect change leading to action [1]. The Social-Ecological Model (SEM), for Health Promotion [2], from Stokols [1] and Community-Based Participatory (CBPR) Models[3],[4] guided proposed engagement, recruitment, and retention strategies contextualized with the individual, interpersonal, organizational, community, and policy spheres of influence. The PreMeR produced a partnership to evaluate and improve the effectiveness of current engagement, recruitment, and retention strategies for minority participation in scientific studies. This approach illustrates the need to incorporate multiple methods of engagement to reach a diverse audience to participate in scientific research. Engagement, recruitment, and retention strategies in community and biomedical research must be viewed as community engaged public health interventions, utilizing the same theoretical principles and approaches.

D-dimer testing in combination with clinical assessment is commonly used to diagnose suspected DVT and pulmonary embolism. However, as D-dimer levels are physiologically higher in elderly patients, this test loses clinical specificity in the setting of geriatric patients. The aim of our study was to investigate the changes in D-dimer levels with age and the specificity of the D-dimer test in the diagnosis of pulmonary embolism. 1617 elderly patients consecutively admitted to the Geriatric Emergency Care Department of the INRCA-IRCCS hospital between January 2013 and February 2014 and for whom D-dimer results were available were included. The D-dimer immunoturbidimetric assay was performed on a cs-2100i Sysmex Siemens using a conventional cut-off level of 500 µg/L. The median D-dimer level was 1200 [550-2990] µg/L FEU, and the percentage of patients with D-dimer levels below the conventional cut-off was only 22.1%. As expected, there was a significant age-related increase in D-dimer, even when sex was considered, and a significant decrease in the specificity of D-dimer assay with age. The most established use of D-dimer testing is in the diagnosis of deep vein thrombosis or pulmonary embolism. Our study confirms the need for an age-adjusted cut-off for D-dimer testing in geriatric patients.

While multiple myeloma (MM) treatment with proteasome inhibitors and other agents yields encouraging results, primary and secondary resistance remains an emerging problem. An important factor in such treatment resistance is the overexpression of several proteins. The present study comprehensively evaluates the expression of POMP, PSMB5, NRF2, XBP1, cMAF and MAFb proteins in plasma cells isolated from the bone marrow of 39 MM patients treated with bortezomib-based regimens using enzyme-linked immunosorbent assay (ELISA). The proteins were selected on the basis of previous laboratory and clinical studies in bortezomib treated MM patients. It was found that the expression of the investigated proteins did not significantly differ between bortezomib-sensitive and bortezomib-refractory patients. However, the expression of some proteins correlated with overall survival (OS); this was significantly shorter in patients with higher POMP expression (HR 2.8, 95% CI: 1.1-7.0, p = 0.0277) and longer in those with higher MAFB expression (HR 0.32, 95% CI: 0.13-0.80, p = 0.0147). Our results indicate that high expression of POMP and MAFB in MM plasma cells may serve as predictors of OS in MM patients treated with bortezomib-based regimens. However, further studies are needed to determine the role of these factors in effective strategies for improving anti-myeloma therapy.

The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedure for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods - whenever available - is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented.

This paper presents a model for archival and retrieval of the videos of natural flowers. To design an efficient video retrieval system the stages namely, keyframe selection, feature extraction, feature dimensionality reduction and indexing are essential for fast browsing and accessing of videos. Three different keyframe selection approaches are proposed using clustering algorithms after segmenting flower regions from its background. Deep Convolutional Neural Network is used as a feature extractor. After keyframe selection, a video is represented with a set of keyframes. To reduce the feature dimension of a video, two feature selection methods are utilized. For an efficient archival and fast retrieval of flower videos an indexing method called KD-tree is recommended. For a given query video, similar videos are retrieved both in relative and absolute search modalities. An extensive experimentation conducted on a relatively large flower video dataset. The data set consists of 7788 videos of 30 different species of flowers. The videos are captured with three different devices in different resolutions. The comparative study reveals proposed keyframe selection approaches gives better results. It has also been observed that the videos retrieved in absolute approach with features selected from Binormal separation metric and indexing gives good results.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

Ship detection from synthetic aperture radar (SAR) imagery is crucial for various fields in real-world applications. Numerous deep learning-based detectors have been investigated for SAR ship detection, which require a substantial amount of labeled data for training. However, SAR data annotation is time-consuming and demands specialized expertise, resulting in that deep learning-based SAR ship detectors struggle due to a lack of annotations. With limited labeled data, semi-supervised learning is a popular approach for boosting detection performance by excavating valuable information from unlabeled data. In this paper, a semi-supervised SAR ship detection network is proposed, termed as Multi-Teacher Dempster-Shafer Evidence Fusion Net-work (MTDSEFN). The MTDSEFN is an enhanced framework based on the basic teacher-student skeleton frame, comprising two branches: the Teacher Group (TG) and the Agency Teacher (AT). The TG utilizes multiple teachers to generate pseudo-labels for different augmentation versions of unlabeled samples, which are then refined to obtain high-quality pseudo-labels by using Dempster-Shafer (D-S) fusion. The AT not only serves to deliver weights of its own teacher to the TG at the end of each epoch, but also updates its own weights after each iteration, enabling the model to effectively learn rich information from unlabeled data. The combination of TG and AT guarantees both reliable pseudo-label generation and learning comprehensive diversity information from numerous unlabeled samples. Extensive experiments were performed on two public SAR ship datasets, and the results demonstrated the effectiveness and superiority of the proposed approach.

This paper reports on the optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation systems for cattle farming in rural areas of Bangladesh. Bangladesh is a lower middle-income country with declining rates of poverty among its 160 million people due to persistent economic growth in conjunction with balanced agricultural improvements. Most of the rural households adopt a mixed farming system by cultivating crops and simultaneously rearing livestock. Among the animals raised, cattle are considered as the most valuable asset for the small/medium-scale farmers in terms of their meat and milk production. Currently, along with the major health issue, the COVID-19 pandemic is hindering the world’s economic growth and has thrust millions into unemployment; Bangladesh is also in this loop. However, natural disasters such as COVID-19 pandemic and floods, largely constrain rural smallholder cattle farmers from climbing out of their poverty. In particular, small and medium-scale cattle farmers face many issues that obstruct them from taking advantage of market opportunities and imposing a greater burden on their families and incomes. An appropriate measure can give a way to make those cattle farmers’ businesses both profitable and sustainable. Optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation system for cattle farming is a new and forward-looking approach for sustainable development of the livestock sector. In this study, we design and optimize a thin-film coating assisted hybrid (photovoltaic-battery-generator) power system by using the Hybrid Optimization of Multiple Energy Resources (HOMER, Version 3.14.0) simulation tool. An analysis of the results has suggested that the off-grid hybrid system is more feasible for small and medium-scale cattle farming systems with long-term sustainability to overcome the significant challenges faced by smallholder cattle farmers in Bangladesh.

In this investigation, we explore the existence and intriguing features of matter wave positons in a nonautonomous one-dimensional Bose-Einstein condensate (BEC) system with attractive interatomic interactions. We focus on the Gross-Pitaevskii (GP) equation/nonlinear Schrödinger (NLS)-type equation with time-modulated nonlinearity and trap potential, governing nonlinear wave propagation in the BEC. Our approach involves constructing second- and third-order matter wave positons using a similarity transformation technique. We also identify the constraints on the time-modulated system parameters that give rise to these nonlinear localized profiles. The study considers three distinct forms of modulated nonlinearities: (i) kink-like, (ii) localized or -like, and (iii) periodic. By varying the parameters associated with the nonlinearity strengths, we observe a rich variety of evolution behaviors in the matter wave positon profiles. These behaviors include stretching, curving, oscillating, breathing, collapsing, amplification, and suppression. Our comprehensive studies shed light on the intricate dynamics of matter wave positons in BECs, providing valuable insights into their behavior and characteristics in the presence of time-modulated nonlinearity and trap potential effects.

Neuronal cell fate is predominantly controlled by the effects of growth factors, such as neurotrophins, and the activation of a variety of signaling pathways acting through neurotrophin receptors, namely Trk and p75 (p75NTR). Despite their beneficial effects on brain function, their therapeutic use is compromised, due to their polypeptidic nature and blood–brain-barrier impermeability. To overcome these limitations, our previous studies have proven that DHEA-derived synthetic analogs can act like neurotrophins, lacking endocrine side effects. The present study focuses on the biological characterization of a newly synthesized analog, ENT-A044, and its role on inducing cell specific functions of p75NTR. We show that ENT-A044 can induce cell death and phosphorylation of JNK protein by activating p75NTR. Additionally, ENT-A044 can induce the phosphorylation of TrkB receptor, indicating that our molecule can activate both neurotrophin receptors, leading towards the protection of neuronal populations that express both receptors. Furthermore, the present study demonstrates for the first time the expression of p75NTR in human induced Pluripotent Stem Cells - derived Neural Progenitor Cells (hiPSCs - derived NPCs) and receptor-dependent cell death induced by ENT-A044 treatment. In conclusion, ENT-A044 could be proven a lead molecule for the development of novel pharmacological agents, aiming on new therapeutic approaches and research tools, by controlling p75NTR actions.

COVID-19 has emerged as deadly pandemic worldwide with no vaccine or suitable antiviral drugs to prevent or cure the disease. Because of the time-consuming process to develop new vaccines or antiviral agents, there has been a growing interest in repurposing some existing drugs to combat SARS-CoV-2. Vitamin D is known to be protective against acute respiratory distress syndrome (ARDS), pneumonia and cytokine storm. Recently it has been used as a repurposed drug for the treatment of H5N1 virus-induced lung injury. Circumstantial evidences indicate that people with low level of vitamin D are more susceptible to SARS-CoV-2. Although, vitamin D was suggested to interfere with viral replication, its interaction with any SARS-CoV-2 protein is unexplored yet. Beside this, ivermectin, a well-known anti-parasitic agent, exhibits potent anti-viral activities in vitro against viruses such as HIV-1 and dengue. Very recently, ivermectin has been found to reduce viral load of SARS-CoV-2 in vitro. We have analyzed available structures of SARS-CoV-2 proteins to identify probable binding partner(s) of vitamin D and ivermectin through knowledge-based docking studies and figured out possible implication of their binding in SARS-CoV-2 infection. Our observations suggest that the non-structural protein nsp7 possesses a potential site to house 25-hydroxyvitamin D3 (VDY) or the active form of Vitamin D, calcitrol. Binding of vitamin D with nsp7 likely to hamper the formation of nsp7-nsp8 complex which is required to bind with RNA dependent RNA polymerase (RdRP), nsp12 for optimal function. On the other hand, potential binding site of ivermectin has been identified in the S2 subunit of trimeric spike(S) glycoprotein of SARS-CoV-2. We propose that deeply inserted mode of ivermectin binding at three inter-subunit junctions may restrict large scale conformational changes of S2 helices which is necessary for efficient fusion of viral and host membrane. Our study, therefore, opens up avenues for further investigations to consider vitamin D and ivermectin as potential drugs against SARS-CoV-2.

The outbreak of Coronavirus, as well as its emerging potential consequences, has become a global challenge worldwide, demanding effective and controlled therapeutic strategies. Potential drug candidates could achieve that with minimal toxicity. The current investigation selected 2-Deoxy-D-glucose prescribed by Defense Research and Development Organization (DRDO), India. The derivative and modified form was tested through in silico analysis against COVID-19 main protease complex with N3 inhibitor. The derived form of 2-Deoxy-D-glucose was generated by replacing the hydroxy group with a hydrogen atom, and Cypate 2-Deoxy-D-glucose was chosen as a derivative against the COVID-19 main protease complex. A molecular docking approach was adopted to identify the stable and competent form among the modified and derivative forms of 2-Deoxy-D-glucose based on binding energy. By further promoting the stabilized complex, these compounds' toxicity was also scrutinized through ADMET analysis to predict the potential candidate. The current investigation suggested that the modified version of 2-Deoxy-D-glucose was more stable with minimal toxicity against COVID-19 main protease.

The nuclear hormone family of receptors regulates gene expression. The androgen receptor (AR) shuttles upon ligand binding and homodimerization from the cytosol into the nucleus to activate gene expression. Thyroid hormone receptors(TR), retinoic acid receptors (RAR), and the vitamin D receptor (VDR) are present in the nucleus bound to chromatin as a heterodimer with the retinoid X receptors (RXR) and repress gene expression. Ligand binding leads to transcription activation. The hormonal ligands for these receptors play crucial roles to ensure the proper conduct of very many tissues and exert effects on prostate cancer (PCa) cells. Androgens support PCa proliferation and deprivation alone or with chemotherapy is the standard therapy for PCa. RAR activation and 3,5,3'-triiodo-L-thyronine (T3) stimulation of TR support the growth of PCa cells. Ligand stimulation of VDR drives growth arrest, differentiation, and apoptosis of PCa cells. Often these receptors are explored as separate avenues to find treatments for PCa and other cancers. However, there is accumulating evidence to support receptor interactions and crosstalk of regulatory events whereby a better understanding might lead to new combinatorial treatments.

The synthesis of the presented benzo[d]thiazol-2-amine derivatives was performed by condensing-(4-chlorobenzylidene) benzo[d]thiazol-2-amine with a number of substituted phenols in the presence of potassium iodide and anhydrous potassium carbonate in dry acetone. IR spectroscopy, 1HNMRspectroscopy and spectroscopy methods were used to characterize the structural properties of newly synthesized derivatives. In order to observe the attributes of drug-like candidates of these derivatives, the number of their molecular properties was estimated. Benzo[d]thiazol-2-amine derivatives were molecularly docked with selective enzymes COX-1 and COX-2. Findings suggested that Compounds G3, G4, G6, G8 and G11 possess higher binding affinity than diclofenac sodium, when docking was performed with enzyme COX-1. Compounds G1, G3, G6, G8and G10 showed lower binding affinity than Indomethacin when docking performed with enzyme COX-2.In vitro evaluation of the COX-1 and COX-2 enzyme inhibitory activities were performed for synthesized compounds. Compounds 10 and 11 exhibited significant COX-1 and COX- enzyme inhibitory action with IC50 values of 5.0 and 10 µM, respectively. Using the hot plate method and the carrageenan-induced rat paw edema model, the synthesized compounds were screened for their biological activities, including analgesic and anti-inflammatory activities. The highest analgesic action was exhibited by derivative G11and the compound G10 showed the highest anti-inflammatory response.

This is a single tertiary center in southwest Romania, population-based, study. We retrospectively compared data obtained in two periods: January 2008 - December 2013 and January 2018 - De-cember 2023, respectively. The global incidence of transposition of great arteries (TGA) - the ter-minated cases added to the ones resulting in live-born pregnancies, remained almost constant. The live-born incidence of TGA decreased (0.34% to 0.013%). The prenatal detection rate increased slightly (71.42% to 87.5%). The median gestational age at the diagnosis decreased, from 29.3 ges-tational weeks (mean 25.4) to 13.4 weeks (mean 17.2). The proportion of terminated pregnancies significantly increased (14.28% to 75%, p = 0.019).

This research aims to apply Artificial Intelligence (AI) methods, specifically Artificial Immune Systems (AIS), to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD (Integral-Proportional Derivative) and PI-D (Proportional-Integral Derivative) control. The motivation for using these variations of PID controllers is that they are functionally implemented in modern industrial controllers, where they provide precise process control. The research results in a novel solution to the control synthesis problem for the industrial system. In particular, the research deals with the synthesis of I-P control for a two-loop system in the technological process of a distillation column. This synthesis is carried out using the AIS algorithm, which is the first application of this technique in this specific context. Methodological approaches are proposed to improve the performance of industrial multivariable control systems by effectively using optimization algorithms and establishing modified quality criteria. The numerical performance index ISE justifies the effectiveness of the AIS-based controllers in comparison with conventional PID controllers (ISE₁ = 1.865, ISE₂ = 1.56). The problem of synthesis of the multi-input multi-output (MIMO) control system is solved, considering the interconnections due to the decoupling procedure.

Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for an improved ecosystem management, based on an accounting of changes and on monitoring of their functioning in time. In Europe, the main legislative driver behind this goal is the European Commission’s Biodiversity Strategy to 2020, on one hand aiming at reducing biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%–1.19% of the study area can be attributed as actual riparian area (considering Strahler’s stream orders 3-8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558–69.128 km². Similarly depending on the accounting approach, the potential riparian zones are accounted for about 3-5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas.

Bangladesh's railway system mostly uses typical manual railway crossing technique or boom gates through its 2,955.53 km rail route all over the country. The accidents are frequently happening in the railway crossings due to not having obstacle detectable and quickly operating gate systems, and also for fewer safety measures in the railway crossing. Currently, there are very few automatic railway crossing systems (without obstacle detectors) available, however, all of them are dependent on the national power grid without a backup plan for any emergency cases. Bangladesh is still running a bit behind in the power generation of its consumption, hence it is not possible to have a continuous power supply at all times all over the countryside. We aim to design and develop a smart railway crossing system with an obstacle detector to prevent common types of accidents in the railway crossing points. We design to use two infrared (IR) sensors to operate the railway crossing systems which will be controlled by the Arduino Uno. This newly designed level crossing system will be run with the help of sustainable renewable energy which is cost-effective, eco-friendly, and apply under the national green energy policy towards achieving sustainable development in Bangladesh as a part of the global sustainable goal to face climate change challenges. We have summarized the simulated results of several renewable energy sources including a hybrid system and optimized the Levelized Cost of Energy (LCOE), and the payback periods.

In the paper, the authors generalize the notion "k-Mittag-Leffler function'', establish some integral transforms of the generalized k-Mittag-Leffler function, and derive several special and known conclusions in terms of the generalized Wright function and the generalized k-Wright function.

Remote Sensing and Geographic Information System are recognized as crucial instruments for conducting geographical and geospatial research. RS and GIS technology was employed to assess the morphological Characteristics of the Kasura River Watershed situated within the Parbhani and Jalna Districts of Maharashtra, India. The entire drainage area of the Kasura River basin measures 490.13 square kilometers (km²). Various morphometric characteristic were calculated and examined, encompassing linear features such as stream number, stream order, mean stream length, stream length, and stream length ratio, areal attributes including elongation ratio, circularity ratio, form factor, constant of channel maintenance, drainage density and drainage texture and relief characteristics such as relief, relief ratio, maximum relief, ruggedness number, relative relief, and length of overland flow. These findings underscore the significance of employing morphometric analysis in watershed assessment, offering a quantitative method for characterizing the surface attributes of a drainage pattern and yielding valuable insights into the topography and runoff dynamics of the region.

Transient receptor potential vanilloid (TRPV) channels act as sensors of pain, temperature, and other external stimuli. We have recently shown that DPV576, an aqueous mixture of nanodiamond (ND) and nanoplatinum (NP), can modulate the activity of TRPV on human primary keratinocytes, suggesting their potential as a possible pain modulator [1]. CD4+ T lymphocytes also express TRPV channels, and we sought with special interest to examine the effect of DPV576 in modulating the functions of TRPV channel expression and secretion of cytokines on human CD4+ T lymphocytes. Human primary CD4+ T cells were activated with anti CD3/CD28 with and without DPV576 at 1:25 and 1:100 dilutions for 24 hours in vitro. TRPV Receptor expression (TRPV1 and TRPV4) on CD4+ T cells was examined by flow cytometry. The capacity of DPV576 to modulate the activity of TRPV1 agonist capsaicin in CD4+ T cells was also determined. Activation of CD4+ T cells was determined by production of cytokines TNF-α, IFN-γ, and IL-10 using specific ELISA kits. DPV576 treatment of CD4+ T cells that were activated with anti CD3/CD28, resulted in increased expression of TRPV1 channel but had no effect on TRPV4. This was accompanied by increased secretion of IFN-g and reduced expression of TRPV1 in capsaicin activated CD4+ T cells. In addition, DPV576 inhibited the capsaicin, induced the production of both IFN-g and TNF-α, and enhanced the secretion of IL-10. We conclude that short term exposure to DPV576 inhibits the activity of TRPV1 channels in CD4+ T lymphocytes, which may suggest its possible beneficial use for pain management.

Fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires but surprisingly very few studies have quantitatively assessed that recovery. Accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne lidar data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height, and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate- and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in lidar-based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate- and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites, and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne lidar data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in lidar and other remotely-sensed data at larger scales.

Chitosan decorated copper nanoparticles (CS/CuNPs) catalysts were synthesized via reduction methods utilizing green protocol. The CS/CuNPs hybrid catalysts were tested for the synthesis of quinoline derivatives utilizing one-pot multicomponent reaction (MCR) under ultrasonic irradiation. The best catalyst (CS/CuNPs) that provided good conversion reaction yield and high turnover frequency (TOF) was characterized using Fourier transform infrared (FTIR), Thermogravimetric analyses (TGA), X-ray diffraction (XRD), , scanning electron microscopy (SEM), transmission electron microscope (TEM) and X-ray photoelectron spectroscopy (XPS) techniques. Generalization of the scope of the proposed catalytic process was studied using different aldehydes. Excellent products yield and high TOF in even shorter reaction time (~5 min) was attained. Recyclability performance of the catalyst over five times re-use without detectable loss in product yield was recorded. The current method is green process utilizing environmentally benign catalyst and considered to be promising sustainable protocol for the synthesis of fine chemicals.

The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of green coffee, clove, cinnamon/clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning green coffee, clove, cinnamon, cinnamon and clove, and nutmeg fine powders based on multivariate analysis of variance and supervised learning on data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography/mass spectrometry. Results showed that 7 volatile compounds namely ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of green coffee, cinnamon, clove, cinnamon and clove and nutmeg, based on selected volatile compounds, and provides further support to the literature by means of possible adulteration given the statistical models developed.

Recent studies have demonstrated a relationship between poor vitamin D status and respiratory infections and diarrhea among young children. Acute lower respiratory infections (ALRI) and diarrhea are among the two most important causes of death in under-5 children. In this analysis, we examine the extent to which vitamin-D deficiency (<10 ng/ml) predicts these outcomes using data from a randomized controlled trial (RCT) of daily folic acid and/ or vitamin B12 supplementation for six months in 6 to 30 months old children conducted in Delhi, India. Of the 960 subjects who had vitamin-D concentrations measured, 331(34.5%) were vitamin-D deficient. We found, after controlling for relevant potential confounders (age, sex, breastfeeding status, wasting, stunting, underweight, anemia status at base line and season), the risk of ALRI was significantly higher among vitamin-D deficient (OR 1.26; 95% CI: 1.03 to 1.55) compared to vitamin-D-replete children in the six months follow-up period. Vitamin-D status was not significantly associated with episodes of diarrhea and clinical pneumonia. The extent of causal relationship of vitamin-D status and ALRI needs to be explored in further studies.

This paper will explore analogs of groups formed by the transformations of two ropes as presented by Minh-Tam Quang Trinh.1 The two operations acting on these ropes are T and S, defined as twists and clockwise turns, respectively. These actions intertwine the ropes, creating tangles. T and S also have the ability to untangle the rope when used in certain combinations. In the two-rope case, these actions expressed as a group presentation were shown to be isomorphic to SL₂(Z). We explored the analog of these opera- tions, T and S, and conjectured the corresponding group to which they are isomorphic. Partial proofs for this conjecture are included and future work would include proving our conjecture as well as generalizing results to k ropes.

Although vitamin D deficiency has been correlated with an increased risk of cardiovascular disease (CVD), there are few data on the association between 25-hydroxyvitamin D (25(OH) D) and atherogenic indices predictive of CVD. This study aimed to investigate the relationship of vitamin D status with lipid profile and atherogenic indices in adult women in Morocco. Three hundred healthy women, aged 18 to 50 years, from Meknes were included. Fasting 25(OH) D and lipid concentrations were determined using a one-step electrochemiluminescence-based immunoassay and an enzymatic method, respectively. Atherogenic indices (Atherogenic index of plasma (AIP), non-HDL cholesterol (Non-HDL-C), Atherogenic coefficient (AC), Castelli risk indices I and II (CRI-I and II), and CHOLIndex (CI)) were calculated using conventional lipid parameters. Logistic regression models and operating characteristic curve (ROC) analysis were used to assess the relationship of the variables and estimate the threshold of 25(OH) D levels associated with high atherogenic indices. 25(OH) D below 20 ng/ml was significantly associated with an enhanced risk of hypertriglyceridemia and elevated values of AIP, AC, Non-HDL-C, and CRI-I with an OR (95% CI) of 4.904 (1.856-12.959); 3.637(2.149-6.158); 3.589(1.673-7.700); 2.074(1.215-3.540), and 2.481(1.481-4.123), respectively. According to ROC analysis, the likelihood of hypertriglyceridemia and high values of AIP, AC, Non-HDL-C, and CRI-I were associated with 25(OH)D thresholds ≤15.15 ng/ml, ≤ 17.5 ng/ml, ≤ 19.8 ng/ml, ≤ 20.1 ng/ml and ≤ 19.5 ng/ml, respectively, all p &lt; 0.01. Based on atherogenic indices, this study indicates that vitamin D below 20 ng/ml may increase the risk of cardiovascular disease in adult women. Additional health efforts are needed to raise awareness among women and healthcare providers in preventing and controlling cardiovascular risk factors.

DNA Topoisomerase IIa (Top2A) is a nuclear enzyme that is a cancer drug target, and there is interest in identifying novel sites on the enzyme to inhibit cancer cells more selectively and to reduce off-target toxicity. The C-terminal domain (CTD) is one potential target, but it is an intrinsically disordered domain, which prevents structural analysis. Therefore, we set out to analyze the sequence of Top2A from 105 species using bioinformatic analysis including the PSICalc algorithm, entropy analysis, and other approaches. Our results demonstrate that large (10th-order) interdependent clusters are found including non-proximal positions across the major domains of Top2A. Further, CTD-specific clusters of 3rd, 4th, and 5th-order were identified that included positions that had been previously analyzed via mutation and biochemical assays. Some of these clusters coincided with positions that when mutated either increased or decreased relaxation activity. Finally, sites of low entropy (i.e., high information content) were identified and mapped as key positions in the CTD. Included in the low entropy sites are phosphorylation sites and charged positions. Together, these results help to build a clearer picture of the critical positions in the CTD and provide potential sites/regions for further analysis.

:Peat substrate is made from peat from drained peatlands, which is a limited resource. A realistic estimate is that 50% of the world’s wetlands have been lost. Peat is used in horticulture, especially for the cultivation of vegetables in greenhouses. The consequences of peatland exploitation are an in-crease in the greenhouse effect and a decrease in carbon stocks. Wood fiber can be used as an al-ternative to peat. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the growing container. This study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) variety “Dirigent H” developed in the Netherlands, were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) con-ventional fertilization (CF); (2) N13; (3) N23; (4) N30. The experiment was carried out in three repli-cations. As the amount of wood fiber increased, the humidity and pH of the growing medium in-creased. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in 50/50 and 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat sub-strate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

: Greenhouse plants are usually grown in containers filled with growing media. Peat is the main component of the growing media used in greenhouses. However, peat substrate is made from peat from drained peatlands, which is a limited resource. Wood fiber can be an alternative to use as a growing media for controlled-climate crops. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the vegetative container. Therefore, this study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) conventional fertilization (CF); (2) N13; (3) N23; (4) N30. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in WF/PS 50/50 and WF/PS 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat substrate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognised in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different type of tissues. Towards this direction, in this paper we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model we formulate the complete pathloss model. The developed theoretical framework is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the theoretical framework in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is capable of boosting the design of optimized communication protocols for a plethora of biomedical applications.

Although Cable driven rehabilitation devices (CDRD) have advantages over traditional link-driven devices, including lightweight, ease of reconfiguration, remote actuation, etc, the majority of existing lower-limb CDRD is limited to rehabilitation in the sagittal plane. In this work, we extend our previous sagittal plane model (2DOF) to accommodate hip motion in the frontal plane (abduction/adduction) toward studying the feasibility of tracking bi-planar motion (combined frontal and sagittal plane motion) via intra-planar cable routing. Two optimization problems have been formulated to estimate an optimal location of the hip cuffs, first to estimate the optimal cuff location at each time step to identify a single ‘averaged’ optimal cuff location and second to calculate a single optimal cuff location for the entire gait cycle. The optimization solutions identified for the 3DOF model revealed that optimization of the location of cuffs on the anterior and posterior side of the hip joint for 4 cable configuration is not sufficient to generate the desired bi-planar motion. For simultaneous tracking of the bi-planar motion, 2 additional cables have been added at hip joints and are routed in an intra-planar manner. The simulation result with the 3DOF model confirmed successful bi-planar trajectory tracking. The various number of cables and cable routings for tracking bi-planar motion will be studied in future work.

Molecular classifications of colorectal cancer (CRC) are benefitting cancer research by providing insights into subtype-specific disease prognosis and better therapeutic intervention. So far different conventional DNA markers such as microsatellite instability (MSI), CpG island methylator phenotype (CIMP), chromosomal instability (CIN), and BRAF and KRAS mutations have been used to classify CRC patients but have not shown promising prognostic values. Here, for the first time, we show classification of CRC tumors from Saudi Arabian patients based on gene expression profile (GEP). An existing method of CRC subtyping has been applied to the GEP of tumors from Saudi CRC patients. Survival analysis was carried out on predicted CRC subtypes. In-silico functional analyses were conducted on the gene signature used for subtype prediction. The predicted subtypes showed distinct but statistically insignificant overall survival distribution (log-rank test, p = 0.069). Comparison of predicted subtypes in Saudi CRC patients with that of the French one showed significant dissimilarity in the two populations (Chi-square test, p = 0.0091). Functional analyses of the gene signature used for subtyping suggest their association with “cancer” and “gastrointestinal diseases”. Most of the signature genes were found differentially expressed in CRC tumors compared to adjacent normal tissues. Such a classification framework might help improve the treatment of colorectal cancer patients.

CGT is composed of fiber residues, leaves, dust particles, soil and others derived during the ginning and yarn spinning process at processing industries,. In the cotton spinning industrial clusters, farmers are using CGT) as one of the alternative roughage feed for their sheep, mainly during forage shortages in the summer months. To have baseline information on farmers using gin and factors driving them to choose CGT as a roughage source, which need to be identified for future planning on the usage of CGT in sheep feeding. Considering the above facts, the present study was undertaken to assess socio-personal characteristics, managemental practices associated with farmers using cotton gin in the feeding of sheep and also identify the factors driving the choice of the CGT as the primary source of roughage in the cotton spinning industry cluster of Tamil Nadu. For this, a survey among 80 sheep farmers was carried out using a pre-tested in-terview schedule. The collected data was analysed using descriptive statistics and logit regres-sion. The results indicated that the majority of male, aged, and large-land farmers were involved in practicing CGT feeding during the summer and also indicated the non-availability of green fodder during the summer season. The coarse type of CGT preferred more than the fine type of CGT trash in that area due to quality perception and price. The replacement level of CGT as roughage ranged from 33 to 75% of the total roughage requirement per day. About 88 percent-age of farmers were highly satisfied with the results of using CGT and they also expressed that the presence of foreign particles and dust were the major problems with using CGT. The choice of CGT as primary roughage among sheep farmers was primarily influenced by selective farming contexts, namely landholding, access to labour, and feeding practices of other livestock with cotton gin. Further, research has to be focused on to improve the quality of CGT in the future, as it is being utilised largely by sheep farmers.

The KcsA is a prokaryotic potassium-oriented channel, which is sourced from the Streptomyces lividans soil bacteria. From extensive studies that have been carried over the KcsA potassium channel, it has been proved that various factors enable the gating and shuttling of the potassium ions into and out of the cells. Some of the factors include the different concentration of protons in the inside and outside membrane. The other factor is the existence of the selectivity filter equipped in the exit of channel pore, which enables the movement of the K⁺ ions. Not only are potassium ions present in the channel but also sodium ions. Potassium and sodium ions are the ions that are essential in the conductivity of a cell because of their charge. An intuitive idea about why K⁺ ions are at least 10,000 times more permeant than Na⁺ ions is presented in various entities. The hypothesis is that the selectivity ratio is probably related to the successive entry of Na⁺ ions, based on the premise that the ratio seems to be relevant to unpredictable quantities caused by Brownian corrosion of ions.

This paper aims to demonstrate that, beyond the small world of Riemann-Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to the different paths taken. Notions of time and scale sequences are introduced and general associated basic derivatives, namely right/stretching and left/shrinking, are defined. A general framework for fractional derivative definitions is reviewed and applied to get both known and new fractional order derivatives. Several fractional derivatives are considered, mainly: Liouville, Hadamard, Euler, bilinear, tempered, q-derivative, and Hahn.

Ionizing radiation exposure is known to induce molecular and cellular injury, inflicting a cascade of potentially catastrophic events leading to tissue and organ damage. Metabolomic analysis allows for the identification and quantification of small molecules downstream of genomic changes induced by radiation exposure. We aimed to characterize metabolomic changes that underscore the prefinal stage of lethally irradiated rhesus nonhuman primates (NHPs). Peripheral blood was drawn at baseline, post-exposure as well as at the preterminal stage of NHPs (immediately prior to death in moribund NHPs), which did not survive exposure with 7.2 Gy total-body radiation (LD70/60). Herein, we analyzed global metabolomic changes using ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight mass spectrometry (QTOF-MS) in plasma samples of NHPs collected at various timepoints in relation to irradiation. The overall goal was to identify metabolic shifts present immediately prior to death. Our findings, for the first time, show that radiation induced significant time dependent metabolic perturbations when compared to pre-irradiation samples, particularly in the glycerophospholipid metabolism and steroid hormone biosynthesis and metabolism pathways. These findings provide valuable insights for identifying biomarkers for lethality, which may be helpful for triage during a mass casualty scenario.

The $k$-means problem is to compute a set of $k$ centers (points) that minimizes the sum of squared distances to a given set of $n$ points in a metric space. Arguably, the most common algorithm to solve it is $k$-means++ which is easy to implement, and provides a provably small approximation factor in time that is linear in $n$. We generalize $k$-means++ to support: (i) non-metric spaces and any pseudo-distance function. In particular, it supports M-estimators functions that handle outliers, e.g. where the distance $\mathrm{dist}(p,x)$ between a pair of points is replaced by $\min {\mathrm{dist}(p,x),1}$. (ii) $k$-means clustering with $m\geq 1$ outliers, i.e., where the $m$ farthest points from the $k$ centers are excluded from the total sum of distances. This is the first algorithm whose running time is linear in $n$ and polynomial in $k$ and $m$.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Every year, General Practitioners (GPs) see over 13 million patients for dermatological concerns making dermatology the highest referring speciality. Artificial Intelligence (AI) systems could improve system efficiency by supporting clinicians in making appropriate referrals, but they are, like human clinicians, imperfect and there may be a trade-off between sensitivity and specificity that is likely to result in false negatives. In this paper, a study is presented to explore two areas. Firstly, the aptitude of GPs to trust appropriately (or not trust) the outputs of a fictitious AI-based decision support tool when assessing skin lesions. Secondly, to identify which individual characteristics could make GPs less prone to adhere to erroneous diagnostics results and to refrain from passive adherence to AI. Findings suggest that when the AI is correct, there is a positive effect on GPs’ performance and confidence suggesting the potential to reduce referrals for benign lesions. However, when an inexperienced GP is presented with a false-negative result, they may passively deviate from their initial clinical judgement to accept the wrong diagnosis provided. AI systems will have a false-negative rate and, when adopting new technologies, this needs to be acknowledged and fed into risk-benefit discussions and considerations around additional safety measures.

Exotic plants are usually problematic for the native species where they coexist. This study evaluated the effect of naturalised alien Cenchrus echinatus L. on native plants in the urban vegetation. A field trial was conducted to assess the effect of this species on cover and diversity of the native vegetation. The allelopathic potential of such species was examined. Plots comprising C. echinatus had lower cover of some native species. Lower floristic diversity was observed at more dense cover of this plant. The soil under Cenchrus attained lower N, P and K contents. This soil had no effect on germination and growth of the native species. It also comprised germinable seeds of some species which were absent from the standing vegetation. Exotic C. echinatus may exert a negative effect on the native vegetation of the urban plant communities. Dense cover of Cenchrus may inhibit germination of native species, leading to reduction in their cover. The reduction in cover and diversity of native species was not attributed to allelopathy. These results suggest that naturalised C. echinatus may be more competitor than the native ones, particularly at higher densities. Furthermore, it may represent a threat for the native plants in the urban vegetation.

Alcoholic liver disease (ALD) develops when the immunotolerant environment of the liver is compromised due to excessive alcohol consumption. ALD progression involves variations in the expression of multiple genes, resulting in liver inflammation and the development of a leaky gut. Molecular mechanism involved for ALD progression is still unclear, and due to that there are currently no FDA-approved drugs available for its treatment. In this study, the protective effects of Graphene oxide nanoparticles (GO) was investigated against ethanol-induced damage in the gut-liver axis in in vitro. GO was synthesized using a modified Hummer's method and characterization was done. Given the general concerns regarding nanoparticle toxicity, assessment of cell viability, lipid accumulation, DNA damage, cell death, and the generation of reactive oxygen species (ROS) were conducted using various techniques. Furthermore, gene expression of pro- and anti-inflammatory cytokines was done using RT-qPCR. The findings revealed that GOs promoted cell viability even against ethanol treatment. Additionally, lipid accumulation significantly decreased when cells were treated with GO alongside ethanol compared to ethanol treatment alone, with similar trends observed for other assays. Gene expression analysis indicated that GO treatment reduced the expression of proinflammatory cytokines while enhancing the expression of antioxidant genes. Moreover, GO treatment led to improvements in gut permeability and a reduction in proinflammatory cytokines in colon cells damaged by ethanol. These findings suggest that GO holds promise as a drug carrier, exhibiting no observed toxic effects. By shedding light on the protective effects of GO against ethanol-induced damage, this study contributes to the burgeoning field of nanoparticle-mediated therapy for ALD.

The atomic structures of Zn and Na borophosphate glasses were studied by X-ray and neutron diffraction. Peaks assigned to the B−O, P−O, and O−O distances confirm that only BO4 units co-exist with the PO4 tetrahedra. The Zn−O and Na−O coordination numbers are found to be a little larger than four. The narrowest peaks of the Zn−O first-neighbor distances exist for the glasses along a line connecting the Zn(PO3)2 and BPO4 compositions (50 mol% P2O5) which is explained by networks of ZnO4, BO4, and PO4 tetrahedra with twofold coordinated oxygens. Calculated amounts of the available oxygen support this interpretation. Broadened peaks occur for glasses with lower P2O5 contents, consistent with the presence of threefold coordinated oxygens. The two distinct P−O peak components of the Zn and Na borophosphate glasses differ in their relative abundances which is interpreted by Na+ cations that coordinate oxygens in some P−O−B bridges, something not seen for the Zn2+ ions.

Sudden cardiac arrest (SAC) is a leading cause of mortality. In recent years, though, many lives have been saved through the use of defibrillators by random bystanders. As a result, defibrillators have been popping up in various locations. In this work we propose a state mandate demanding the presence of a defibrillator at every pharmacy store and argue that it could greatly enhance and augment the impact of the defibrillator network. We support our claim via detailed calculations of the immediate (a defibrillator readily available) and partial (a defibrillator available at a reasonable distance) population coverage achievable by the implementation of our proposal, taking the Argolis area in Peloponnese Greece as a case study. Our findings indicate that, in addition to other benefits, the use of pharmacies to establish a defibrillator network could bring an eight-fold increase in the immediate population coverage of defibrillators and would provide immediate / partial access to a defibrillator to 18 / 24 incidents of SCA per year that would otherwise lead to death, potentially leading to the saving of numerous lives. Alternative scenaria are also discussed.

Hashimoto's thyroiditis (HT) is essentially featured by self-tissue destruction by means of the adaptive immune responses that evade immune regulation. Vitamin D carries out an immunomodulatory role that appears to promote immune tolerance. The aim of this study is to elaborate a narrative review about the relationship between vitamin D status and HT and the role of vitamin D supplementation to reduce HT risk by modulating the immune system. There is an extensive literature confirming that vitamin D levels are significantly lower in HT patients compared to healthy people. On the other hand, after the supplementation with cholecalciferol in patients with HT and vitamin D deficiency, thyroid autoantibody titer decreased significantly, However, there are no conclusive results on the effect of vitamin D supplementation on the thyroid function. The confirmation of the beneficial effects of vitamin D in the prevention and treatment of autoimmune thyroid diseases require additional randomized, double-blind, placebo-controlled trials with longer follow-up.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Indigenous forests cover 24% of New Zealand and provide valuable ecosystem services. However, a national map of forest types, that is, physiognomic types, which would benefit conservation management, does not currently exist at an appropriate level of detail. While traditional forest classification approaches from remote sensing data are based on spectral information alone, the joint use of space-based optical imagery and structural information from synthetic aperture radar (SAR) and canopy metrics from air-borne Light Detection and Ranging (LiDAR) facilitates more detailed and accurate classifications of forest structure. We present a support vector machine (SVM) classification using data from ESA’s Sentinel-1 and 2 missions, ALOS PALSAR, and airborne LiDAR to produce a regional map of physiognomic types of indigenous forest in New Zealand. A five-fold cross-validation of ground data showed that the highest classification accuracy of 80.9% is achieved for bands 2, 3, 4, 5, 8, 11, and 12 from Sentinel-2, the ratio of bands VH and VV from Sentinel-1, HH from PALSAR, and mean canopy height and 97th percentile canopy height from LiDAR. The classification based on the optical bands alone was 73.1% accurate and the addition of structural metrics from SAR and LiDAR increased accuracy by 7.8%. The classification accuracy is sufficient for many management applications for indigenous forest in New Zealand, including biodiversity management, carbon inventory, pest control, ungulate management, and disease management. National application of the method will be possible in several years, once national LiDAR coverage is achieved, and a national canopy height model is available.

Citrus Greening, which is mainly caused by bacteria, is one of the severe citrus diseases affecting all citrus cultivars and causing the deliberate abolition of trees worldwide. This infectious disease cannot be spread by wind, rain, or contact by contaminated personnel. The primary vector that spreads this disease through feeding citrus leaves is the Asian citrus psyllid (ACP), a minuscule insect. The management of citrus greening is also very costly as there is no fruitful technique is developed to cure this disease except removing all infected plants from good ones to eliminate the dissemination of the pathogen. Citrus greening identification is also the most difficult job, as the symptoms are similar to other citrus diseases and nutrient deficiency. Asymmetrical blotchy mottling patterns on leaves are the main symptoms to detect this disease. Here we have discussed some visual signs of citrus greening, which will ultimately help root level farmers to identify and prevent this disease before it drastically impacts citrus plants. Whether it is affected by citrus greening or lack of nutrients, we have also discussed the pen test method of determining the symptoms as symmetrical or asymmetrical across the mid-vein.

Vancomycin is one of the ‘last-line’ classes of antibiotics used in the treatment of life-threatening infections caused by Gram-positive bacteria. Even though vancomycin was discovered in 1950s it was widely used after 1980s for the treatment of infections caused by methicillin-resistant Staphylococci as prevalence of such strains were increased. However, currently it is evident that vancomycin resistant Staphylococcusaureusandvancomycin-resistant Enterococci have been developed as a result of various reasons including use of avaparcin, which is an analog of vancomycin, as feed additive in livestock. In present day context, more attention should be paid on prevention of emergence of resistance for the antibiotics in order to keep antibiotics effective. In order to prevent emergence of resistance, proper guidance for the responsible use of antimicrobials is indispensable. Therefore, almost all stakeholders who use antibiotics should have in depth understanding on the antibiotic they use. As such, it is imperative to be aware of the important aspects of vancomycin. In the present review, efforts have been made to discussthe pharmacokinetics and pharmacodynamics, indications, emergence of resistance, control of resistance, adverse effects and alternative therapy for vancomycin.

Article explores participant specific study of muscle inherehit dynamics hidden inside the diognostic electromyography (D-EMG) signals during load pull exercises, aiming to uncover underlying patterns and nonlinear behaviors. Employing a multi-step analytical framework, the study first evaluates signal stationarity through Quantile-Quantile (Q-Q) plot and surrogate data analyses, revealing insights into signal stability. Subsequent use of phase space reconstruction techniques exposes intrinsic dynamics within the EMG signals, visualized through Poincar´e maps, elucidating attractor geometry and system dynamics. Histogram analysis further dissects the Poincar´e maps, offering insights into signal behavior relative to physiological processes. Additionally, the study quantifies the largest Lyapunov exponent from the Poincar´e maps, providing a measure of dynamical complexity within the muscle EMG signals during load pull exercises. By integrating these methods, this research sheds light on the nuanced interplay between EMG signals and muscle activity during dynamic exercises, offering valuable insights for rehabilitation strategies.

Magneto-optic (MO) imaging and sensing are at present the most developed practical applications of thin-film MO garnet materials. However, future component and system-level sensors and imagers technology improvements are still necessary in order to improve sensitivity for a range of established and also the forward-looking applications. These improvements are expected to originate from new material system development. We propose a set of technological modifications for the RF-magnetron sputtering deposition and crystallization annealing of magneto-optic bismuth-substituted iron-garnet films and investigate the improved material properties. Results show that standard crystallization annealing for the as-deposited ultrathin (sputtered 10 nm thick, amorphous phase) films resulted in more than a factor of two loss in the magneto-optical activity of the films in visible spectral region, compared to the liquid-phase grown epitaxial films. Results also show that an additional 10 nm-thick metal-oxide (Bi2O3) protective layer above the amorphous film results in ~2.7 times increase in the magneto-optical quality of crystallized iron-garnet films. On the other hand, the effects of post-deposition oxygen (O2) plasma treatment on the magneto-optical (MO) properties of Bismuth substituted iron garnet thin films material is investigated. Results show that, in the visible part of the electromagnetic spectrum (at 532 nm), the O2 treated (up to 3 minutes) garnet films retain higher specific Faraday rotation and figure of merit than those of non-treated garnet films.

We compared the efficacy of a tailored and a targeted intervention designed to increase clinical breast exam (CBE), mammography, and genetic services/testing among young breast cancer survivors (YBCS) (diagnosed <45 years old) and their blood relatives. A two-arm cluster randomized trial recruited a random sample of YBCS from the Michigan cancer registry and up to two of their blood relatives. Participants were stratified according to race and randomly assigned as family units to the tailored (n=637) or the targeted (n=595) intervention. Approximately 40% of participants were Black; 12% YBCS and 27% relatives were living in more than 20 different U.S. States. Higher screening rates were reported by YBCS (CBE p=0.05; mammography p=0.04) and relatives (CBE p<0.01; mammography p=0.04) in the tailored arm, and by White/Other YBCS (CBE p=0.02) and relatives (CBE p<0.01; mammography p=0.03). YBCS genetic testing rates increased from 22% to 26% (p=0.11). Black YBCS and relatives reported higher self-efficacy and intention for genetic testing, and higher satisfaction and intervention acceptance. The tailored intervention improved CBE and mammography uptake - despite having minimal contact with participants. Professional referrals will improve genetic testing uptake. Intervention materials increased self-efficacy and satisfaction for Black women but could not overcome multiple access barriers.

Chronic kidney disease (CKD) and cardiovascular disease (CVD) are highly prevalent conditions, each significantly contributing to the global burden of morbidity and mortality. CVD and CKD share a great number of common risk factor, such as hypertension, diabetes, obesity, and smoking among others. Their relationship extends beyond these factors, encompassing intricate interplay between the two systems. Within this complex network of pathophysiological processes, vitamin D has emerged as a potential linchpin, exerting influence over diverse physiological pathways implicated in both CKD and CVD. In recent years, scientific exploration has unveiled a close connection between these two prevalent conditions and vitamin D, a crucial hormone traditionally recognized for its role in bone health. This article aims to provide an extensive review of vitamin D's multifaceted and expanding actions concerning its involvement in CKD and CVD.

Recent data suggest that K-Ras4B (hereafter K-Ras) can drive cancer cell stemness via calmodulin (CaM)-dependent, non-canonical Wnt-signalling. Here we examined whether another Ca2+-binding protein, the CaM-related centrin1, binds to K-Ras and could mediate some K-Ras functions that were previously ascribed to CaM. While CaM and centrin1 appear to distinguish between peptides that were derived from their classical targets, they both bind to K-Ras in cells. Cellular BRET-data suggest that CaM engages more with K-Ras than centrin1 and that the interaction with the C-terminal membrane anchor of K-Ras is sufficient for this. Surprisingly, binding of neither K-Ras nor its membrane anchor alone to CaM or centrin1 is sensitive to inhibition of prenylation. In support of an involvement of the G-domain of K-Ras in cellular complexes with these Ca2+-binding proteins, we find that oncogenic K-RasG12V displays increased engagement with both CaM and centrin1. This is abrogated by addition of the D38A effector-site mutation, suggesting that K-RasG12V is held together with CaM or centrin1 in complexes with effectors. When treated with CaM-inhibitors the BRET-interaction of K-RasG12V with centrin1 was also disrupted in the low micromolar range, comparable to that with CaM. While CaM predominates in regulating functional membrane anchorage of K-Ras, it has a very similar co-distribution with centrin1 on mitotic organelles. Given these results, a significant overlap of the CaM- and centrin1-dependent functions of K-Ras is suggested.

CSZM compounds were synthesized by dry chemistry route with 5, 10, and 15% dopant of Mg dopants in the Ce 0.8-2x Sm 0.2 Zrx Mgx O2-d, {x = 0.05, 0.1 &amp;0.15}. The newly investigated materials were physically, chemically, and electrochemically studied and have shown promising results. The CSZM was crystalized in a fluorite structure with a pure cubic phase in a space group Fm3m and cell parameter a = 5.401742 °A and theoretical density from 7.6 to 8.9 after firing in the air with a final temperature of 1400 °C. characterization of the structure and indexing of electrolyte materials were made after X-ray diffraction (XRD) testing. A Scanning electron microscope (SEM) morphological analysis was used to examine the microstructure details. Electronic impedance spectroscopy (EIS) measurements were achieved from 400 °C to 700 °C showing the highest value of conductivity of 1.0461 x 10+1 S/cm at 700 °C while the minimum value was 2.7329 x 10-2 S/cm at 400 °C and the total activation energy was found (Ea) 0.6865 eV under 5% H2/Ar.

BACKGROUND. Two sequelae of non-alcoholic steatohepatitis (NASH), ESLD and HCC, have become the leading causes for liver transplantation in the Western. The present study aims to approach the cellular metabolic disturbances involved in NASH progression that are associated with microbiota community changes. METHODS. Metabolic effects and microbiota community changes were explored in the murine with NASH progression by blocking the Na/K-ATPase/Src/reactive oxygen amplification loop using the synthetic targeting peptide pNaKtide. DNA from the terminal ileum microbiota habitat was obtained and amplified by PCR to develop DNA bacterial phylogenic sequence analysis of wild type and treated animals at 12, 24 and 48 weeks. Induced changes by pSrc normalization at 24 weeks were correlated with liver morphological changes, intestinal CD4+/CD8+ ratio, and liver macrophage CD14+ expression. Differences among groups were evaluated by ANOVA/t-test and Principal Component Analysis (PCA). RESULTS. Microbiota communities varied significantly at all time points (12, 24 and 48 weeks), with an increase of Verrucomicrobia and a decrease of Bacteroidetes and Firmicutes in the HFD group. Microbiota community changes regressed to their wild-type state at 24 weeks on treated animals, and those changes were associated with a decrease in liver inflammation and senescence, lower ileum CD4+/CD8+ T cells and higher liver CD14+ cells (p<0.05). Concomitantly, the metabolic disturbances in our diet-induced NASH model were normalized by NKA/Src signaling blockage and exercise with a paucity of apoptotic activity, mitigation of cell senescence, and regression of liver fibrosis (p<0.01). CONCLUSIONS. pSrc inhibition at caveolar α1-Na/K-ATPase rescinded NASH-related metabolic disturbances establishing resident physiological microbiota communities with concomitant paucity on apoptotic activity and regression of liver fibrosis; effects that were associated with both gut and liver T-lymphocyte responses.

In this present work, we are reporting a novel route for the synthesis of the tetracyclic ring systems, which is a common core of crinipellin via oxidative dearomatization, cycloaddition and oxa- di-pi-methane rearrangement. We considered to exploring a route to tetracyclic core (1e) of Crinipellin and tricyclic core (1g) of Allicaol B through intermolecular diels alder reaction and photochemically 1,2 acyl shift. Moreover, docking study of compound 13 and 16has been investigated against AcrB multidrug efflux pump of Escherichia coli (PDB ID: 1T9U), main protease of SARS COV-2 (PDB ID: 6W63), DNA gyrase of Streptococcus pneumonia (PDB ID: 4Z2C), human estrogen receptor alpha (PDB ID: 3ERT), human lanosterol 14-alpha-demethylase (CYP51)(PDB ID: 3JUS) and cyclooxygenase-2 (Prostaglandin Synthase-2) (PDB ID: 1CX2). The obtained results herein are important for the exploitation of the therapeutic potential of these derivatives as antimicrobial, antiviral, anticancer, antifungal or anti-inflammatory agents.

We review time expansion wave theory and refine our model showing it to accurately match observed cosmological luminosity data. The theory augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth spatial dimension that we observe as the expansion of the universe. This leads us to explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects. Our model leads to an expansion velocity of 6.87 0.36 × 106 ms-1, which results in a Hubble expansion rate constant of 71.3 3.7 km/s/Mpc. Because of the finite window of time in which we exist, an extra a degree of freedom is available leading to interesting interpretations at the subatomic level. At this size range, then a spin is allowed within the time dimension explaining why wave particle duality occurs and explains the electromagnetic force and other quantum mechanical properties. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The potential quantitative origin of the fine structure constant which governs the size of the electromagnetic force is also strongly indicated by this theory.

Aseptic implant loosening after total joint replacement is partially influenced by material-specific factors when cobalt-chromium alloys are used, including osteolysis induced by wear- and corrosion products, and stress shielding. Here, we aim to characterize a hybrid material consisting of alumina-toughened zirconia ceramics (ATZ) and additively manufactured Ti-35Nb-6Ta (TiNbTa), joined by a glass solder. The structure of the joint, static and fatigue shear strength, the influence of accelerated aging, and the cytotoxicity using an elution assay with human osteoblasts is characterized. Furthermore, the biomechanical properties of functional demonstrators of a femoral component for total knee replacements are evaluated. TiNbTa-ATZ specimens showed a homogenous joint with statistical distributed micro-pores and a slight accumulation of Al-rich compounds at the glass solder-TiNbTa interface. The static shear strength was 26.4 ± 4.2 MPa (Ti-ATZ reference: 38.2 ± 14.4 MPa, p = 0.117), all specimens survived 107 cycles of shear loading to 10 MPa, and aging did not reduce the strength. TiNbTa-ATZ did not impair the proliferation and metabolic activity of human osteoblasts. Functional demonstrators of TiNbTa-ATZ provided a maximum bearable extension-flexion moment of 40.7 ± 2.2 Nm. Biomechanical and biological properties of TiNbTa-ATZ demonstrate potential application for endoprosthetic implants.

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the classical k-means algorithm; however, it has been shown to currently not provide this speed-up for decoding optical-fibre signals due to the embedding of classical data, which introduces inaccuracies and slowdowns. Although still not achieving an exponential speed-up for NISQ implementations, this work proposes the generalised inverse stereographic projection as an improved embedding into the Bloch sphere for quantum distance estimation in k-nearest-neighbour clustering, which allows us to get closer to the classical performance. We also use the generalised inverse stereographic projection to develop an analogous classical clustering algorithm and benchmark its accuracy, runtime and convergence for decoding real-world experimental optical-fibre communication data. This proposed `quantum-inspired' algorithm provides an improvement in both the accuracy and convergence rate with respect to the k-means algorithm. Hence, this work presents two main contributions. Firstly, we propose the general inverse stereographic projection into the Bloch sphere as a better embedding for quantum machine learning algorithms; here, we use the problem of clustering quadrature amplitude modulated optical-fibre signals as an example. Secondly, as a purely classical contribution inspired by the first contribution, we propose and benchmark the use of the general inverse stereographic projection and spherical centroid for clustering optical-fibre signals, showing that optimizing the radius yields a consistent improvement in accuracy and convergence rate.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

Clustering, or otherwise known as cluster analysis, is a learning problem that takes place without any human supervision. This technique has often been utilized, much efficiently, in data analysis, and serves for observing and identifying interesting, useful, or desired patterns in the said data. The clustering technique functions by performing a structured division of the data involved, in similar objects based on the characteristics that it identifies. This process results in the formation of groups, and each group that is formed, is called a cluster. A single said cluster consists of objects from the data, that have similarities among other objects found in the same cluster, and resemble differences when compared to objects identified from the data that now exist in other clusters. The process of clustering is very significant in various aspects of data analysis, as it determines and presents the intrinsic grouping of objects present in the data, based on their attributes, in a batch of unlabeled raw data. A textbook or otherwise said, good criteria, does not exist in this method of cluster analysis. That is because this process is so different and so customizable for every user, that needs it in his/her various and different needs. There is no outright best clustering algorithm, as it massively depends on the user’s scenario and needs. This paper is intended to compare and study two different clustering algorithms. The algorithms under investigation are k-mean and mean shift. These algorithms are compared according to the following factors: time complexity, training, prediction performance and accuracy of the clustering algorithms.

Cancer is a disease caused by the abnormal growth of cells in different parts of body is one of the top causes of death globally. Microarray gene expression data plays a critical role in the identification and classification of cancer tissues. Due to recent advancements in Machine Learning (ML) techniques, researchers are analyzing gene expression data using a variety of such techniques to model the progression rate &amp; treatment of cancer patients with great effect. But high dimensionality alongside the presence of highly correlated columns in gene expression datasets leads to computational difficulties. This paper aims to propose the use of ML classification techniques- Linear Discriminant Analysis (LDA) &amp; Random Forest (RF) for classifying five types of cancer (breast cancer, kidney cancer, colon cancer, lung cancer and prostate cancer) based on high dimensional microarray gene expression data. Principal component analysis (PCA) was used for dimensionality reduction, and principal component scores of the raw data for classification. Six distinct categorization performance measures were used to evaluate these approaches; RF method provided us with higher accuracy than LDA method. The method and results of this article should be helpful to researchers who are dealing with many genes in microarray data.

In the particular configuration of the scalar field K-essence in the Wheeler-DeWitt quantum equation, for some age in the Bianchi type I anisotropic cosmological model, a fractional differential equation for the scalar field arises naturally. The order of the fractional differential equation is $\beta=\frac{2\alpha}{2\alpha - 1}$. This fractional equation belongs to different intervals, depending on the value of the barotropic parameter; when $\omega_{X} \in [0,1]$, the order belongs to the interval $1\leq \beta \leq 2$, and when $\omega_{X}\in[-1,0)$, the order belongs to the interval $0<\beta \leq 1$. In the quantum scheme, we introduce the factor ordering problem in the variables $(\Omega,\phi)$ and its corresponding momenta $(\Pi_\Omega, \Pi_\phi)$, obtaining a linear fractional differential equation with variable coefficients in the scalar field equation, then the solution is found using a fractional power series expansion. The corresponding quantum solutions are also given. We found the classical solution in the usual gauge N obtained in the Hamiltonian formalism and without a gauge. In the last case, the general solution is presented in a transformed time $T(\tau)$, however in the dust era we found a closed solution in the gauge time $\tau$.

The main objective of this paper is to introduce k-fractional derivative operator by using the definition of k-beta function. We establish some results related to the newly defined fractional operator such as Mellin transform and relations to k-hypergeometric and k-Appell's functions. Also, we investigate the k-fractional derivative of k-Mittag-Leffler and Wright hypergeometric functions.

OPMDs (Oral Potentially Malignant Disorders) are a group of disorders affecting the oral mucosa that are characterized by aberrant cell proliferation and a higher risk of malignant transformation. Vitamin D (VitD) and its receptor (VDR) have been extensively studied for their potential contributions to the prevention and therapeutic management of a range of diseases and neoplastic conditions, including oral cancer. Observational studies suggest correlations between VitD deficiency and higher cancer risk, worse prognosis, and increased mortality rates. Interestingly, emerging data also reveals a link between VitD insufficiency and the onset or progression of OPMDs. Understanding the role of the VitD-VDR axis not only in established oral tumors but also in OPMDs might thus enable early detection and prevention of malignant transformation. With this article, we want to provide an overview of current knowledge about OPMDs and VitD, and investigate their potential association and ramifications for clinical management of OPMDs.

In the present work we revise and extend the Characteristic Crystallographic Element (CCE) norm, an algorithm used to simultaneously detect radial and orientational similarity of computer-generated structures with respect to specific reference crystals and local symmetries. Based on the identification of point group symmetry elements, the CCE descriptor is able to gauge local structure with high precision and finely distinguish between competing morphologies. As test cases we use computer-generated monomeric and polymer systems of spherical particles interacting with the hard-sphere and square-well attractive potentials. We demonstrate that the CCE norm is able to detect and differentiate, between others, among: hexagonal close packed (HCP), face centered cubic (FCC), hexagonal (HEX) and body centered cubic (BCC) crystals as well as non-crystallographic fivefold (FIV) local symmetry in bulk 3-D systems; triangular (TRI), square (SQU) and honeycomb (HON) crystals, as well as pentagonal (PEN) local symmetry in thin films of one-layer thickness (2-D systems). The descriptor is general and can be applied to identify the symmetry elements of any point group for arbitrary atomic or particulate system in two or three dimensions, in the bulk or under confinement.