This work investigates the use of Non-destructive tests as a tool for monitoring the structural performance of concrete structures. The investigation encompassed four phases; the first of which involved the use of destructive and non-destructive mechanisms to assess concrete strength on cube specimens. The second phase research focused on site assessment for a twin engineering theatre located at the Faculty of Engineering, University of Lagos using rebound hammer and ultrasonic pulse velocity tester. The third phase was the use of linear regression analysis model with MATLAB to establish a relationship between calibrated strength as well as ultrasonic pulse velocities with their corresponding compressive strength values on cubes and values obtained from existing structures. Results show that the root-mean squared-R² values for rebound hammer ranged between 0.275 and 0.742 while ultrasonic pulse velocity R² values were in the range of 0.649 and 0.952 for air curing and water curing systems respectively. It initially appeared that the Ultrasonic pulse velocity was more suitable for predicting concrete strength than rebound hammer but further investigations showed that the latter was adequate for early age concrete while the former was more suited for aging concrete. Hence, a combined use is recommended in this work.

Economists have long been interested in examining inflation-growth nexus. Nevertheless, the nature of their relationship and the optimal level of inflation threshold for economic growth have still remained controversial in both theoretical and empirical works. Accordingly, this study investigates the existence of threshold effects of inflation on economic growth in Ethiopia over the period 1975-2018 using a Two-regime Threshold Auto-regressive (TAR) model. The study mainly departs from previous works since it estimates sector-specific inflation threshold level in food and non-food sectors. Our preliminary analyses clearly reveal that inflation in food sector has become more volatile, less-persistent and key contributor to the general inflation as compared to its non-food counterpart. Further, The TAR model results and robustness checks indicate the existence of inflation threshold in a range of 9-10%. In particular, the threshold level for food inflation is 10% and 8% for non-food inflation. In all cases, our results robustly confirm growth-detrimental effects of inflation after the threshold levels. After all, this study suggests the need for considering specific behaviors of food and non-food prices, and implementing appropriate fiscal and monetary policies to bring inflation down to a single-digit level.

In the present study, a hybrid optimizing algorithm has been proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for Artificial Neural Network (ANN) to improve the estimation of electricity demand of the state of Tamil Nadu in India. The GA-PSO model optimizes the coefficients of factors of gross state domestic product (GSDP), per capita demand, income and consumer price index (CPI) that affect the electricity demand. Based on historical data of 25 years from 1991 till 2015 , the simulation results of GA-PSO models are having greater accuracy and reliability than single optimization methods based on either PSO or GA. The forecasting results of ANN-GA-PSO are better than models based on single optimization such as ANN-BP, ANN-GA, ANN-PSO models. Further the paper also forecasts the electricity demand of Tamil Nadu based on two scenarios. First scenario is the "as-it-is" scenario , the second scenario is based on milestones set for achieving goals of "Vision 2023" document for the state. The present research also explores the causality between the economic growth and electricity demand in case of Tamil Nadu. The research indicates that the direct causality exists between GSDP and the electricity demand of the state.

It is well established in literature that the public debt and economic growth bear positive and non-linear relationship. However, in recent literature, evidence of no causal relationship is found when accounted for endogeneity in case of advanced economies (Panizza & Presbitero, 2014). Chudik, Mohaddes, Pesaran, & Raissi, (2017) analyse the data on forty countries and find no evidence of universally applicable threshold effect in the relationship between debt and growth. These advancements in the debt-growth literature provides the motivation to re-explore the relationship between public debt and economic growth under non-linearity and endogeneity in context of developing economies of South Asia including Pakistan, India, Bangladesh and Sri-Lanka for the period 1980-2014. There exists a significant, positive but nonlinear relationship between the public debt and economic growth for the selected set of developing countries when accounted for endogeneity and non-linearity. The negative association between the public debt and economic growth for SAARC region is found when the debt level is higher than 61% of GDP which is quite lower than developed economies (90% of GDP). Individual threshold levels for debt-to-GDP ratio divulge that Sri Lanka, Pakistan and India need to control their public borrowings as their current debt levels are higher and/or around the respective threshold levels.

Most of the pore-scale imaging and simulations of non-Newtonian fluid are based on the simplifying geometry of network modeling and overlook the fluid rheology and heat transfer. In the present paper, we developed a non-isothermal and non-Newtonian numerical model of the flow properties at pore-scale by direct simulation of the 3D micro-CT images using a Finite Volume Method (FVM). The numerical model is based on the resolution of the momentum and energy conservation equations. Owing to an adaptive meshing technique and appropriate boundary conditions, rock permeability and mobility are accurately computed. A temperature and concentration-dependent power-law viscosity model in line with the experimental measurement of the fluid rheology is adopted. The model is first applied at isothermal condition to 2 benchmark samples, namely Fontainebleau sandstone and Grosmont carbonate, and is found to be in good agreement with the Lattice Boltzmann method (LBM). Finally, at non-isothermal conditions, an effective mobility is introduced that enables to perform a numerical sensitivity study to fluid rheology, heat transfer, and operating conditions. While the mobility seems to evolve linearly with polymer concentration, the effect of the temperature seems negligible by comparison. However, a sharp contrast is found between carbonate and sandstone under the effect of a constant temperature gradient. Besides concerning the flow index and consistency factor, a good master curve is derived when normalizing the mobility for both the carbonate and the sandstone.

Background: The presence of fungal species on the surface skin and hair is a known finding in many mammalian species and humans are no exception. Superficial fungal infections are sometimes a chronic and recurring condition that affects approximately 10-20% of the world’s population. However, most species that are isolated from humans tend to occur as co-existing flora. This study was conducted to determine the diversity of fungal species isolated from the hair and nails of workers in the central region of Saudi Arabia where there are not many observational studies on the mycological species. Materials and Methods: Male workers from Riyadh, Saudi Arabia were recruited for this study and samples were obtained from their nails and hair for mycological analysis which was done using Saboraud’s agar and sterile wet soil. Fungal isolates were examined microscopically. Results: Twenty four hair samples yielded a total of 26 species from 19 fungal genera. Chaetomiumglobosum was the most commonly isolated fungal species followed by Emericellanidulans, Cochliobolusneergaardii, and Penicilliumoxalicum. Three fungal species were isolated from nail samples, namely, Alternariaalternata, Aureobasidiumpullulans, and Penicilliumchrysogenum. Most of the isolated fungal species (17 of the 26 or 65.38% of the isolated fungal species) have not been thoroughly characterised nor morphologically classified. Conclusion: This study demonstrates the presence of previously undescribed fungal species that contribute to the normal flora of the skin and its appendages and may have a role in their pathogenies.

In this work, we report the fabrication of the new heterojunction of two 2D hybrid layered semiconductors, ZnO(stearic acid)/V₂O₅(hexadecylamine), and its behavior in the degradation of aqueous methylene blue under visible light irradiation. The optimal photocatalyst efficiency, reached at a ZnO(stearic acid)/ V₂O₅(hexadecylamine) ratio of 1:0.25, results to be about six times higher than that of pristine zinc oxide. Reusability test shows that after three photocatalysis cycles no significant changes in neither the dye degradation efficiency loss nor photocatalyst structure occur. Visible light photocatalytic performance observed indicates there is synergetic effect between both 2D nanocomposites used in the heterojunction. The visible light absorption enhancement promoted by the narrower bandgap V₂O₅ based components; an increased photo generated charge separation favored by extensive interface area; and abundance of hydrophobic sites for dye adsorption appear as probable causes of the improved photocatalytic efficiency in this hybrid semiconductors heterojunction. Estimated band-edge positions for both conduction and valence band of semiconductors together with experiments using specific radical scavengers allow a plausible photodegradation mechanism.

RNAi is considered a major antiviral defense mechanism in insects but its relative importance compared to other antiviral pathways has not been evaluated comprehensively. Here, it is attempted to give an overview of the antiviral defense mechanisms in Drosophila that involve both RNAi and non-RNAi to acquire a sense of their relative importance. While RNAi is considered important in most viral infections, many other pathways can exist that confer antiviral resistance. It is noted that very few direct recognition mechanisms of virus infections have been identified in Drosophila and that the activation of immune pathways may be accomplished indirectly through cell damage incurred by viral replication. In several cases, protection against viral infection can be obtained in RNAi mutants by non-RNAi mechanisms, confirming the variability of the RNAi defense mechanism according to the type of infection and the physiological status of the host. This analysis invites to investigate more systematically the relative contribution of RNAi in the antiviral response and more specifically to ask whether RNAi efficiency is affected when other defense mechanisms predominate. While Drosophila can function as a useful model, this issue may be more critical for economically important insects that are either controlled (agricultural pests and vectors of diseases) or protected from parasite infection (beneficial insects as bees) by RNAi products.

This work updates the characterization of winter fish communities in salt marsh areas of Guadiana estuary (SE-Portugal) and discusses the potential risks of habitat dominance by a non-indigenous species (NIS). To this effect, six field campaigns were carried out during winter season targeting the collection of fish species. Individuals from seven different families (marine and estuarine) were collected although the community was dominated by two estuarine species – the native Pomatoschistus sp. (goby) and the NIS Fundulus heteroclitus (mummichog). Goby controlled the majority of salt marsh habitats, except one specific, marsh pool, where extreme environmental conditions were registered, namely high temperature and salinity. Such conditions may have boosted the intrusion of mummichog in this area. This species is well adapted to a wide range of abiotic factors enabling them to colonize habitats where no predators inhabit. Impacts of mummichog intrusion in the Guadiana salt marsh area are still unpredictable since this is the first recorded in such high density. Nevertheless, in scenarios of increased anthropogenic pressure and, consequently, habitat degradation, there is a potential risk of mummichog spread to other habitats and therefore compete for space and food resources with native species.

In this paper, the connections between quantum non-locality and permutation symmetries are explored. This includes two types of symmetries: permutation across a superposition and permutation of qubits in a quantum system. An algorithm is proposed for nding the separability class of a quantum state using a method based on factorizing an arbitrary multipartite state into possible partitions, cyclically permuting qubits of the vectors in a superposition to check which separability class it falls into and thereafter using a reduced density-matrix analysis of the system is proposed. For the case of mixed quantum states, conditions for separability are found in terms of the partial transposition of the density matrices of the quantum system. One of these conditions turns out to be the Partial Positive Transpose (PPT) condition. A graphical method for analyzing separability is also proposed. The concept of permutation of qubits is shown to be useful in dening a new entanglement measure in the `engle'.

Considering the negative impacts of climate changes along with the rapid increase in population in Islamic dominated states, e.g., the Middle East, water tension among upstream and downstream states is increasing. Despite the importance of water management in Islamic culture, the role of religion has been under-valued and under-emphasized by the scholars. The paper has sought to compare and contrast Islamic water management principles (IWMP) with international water law principles (IWLP). The findings from this analysis show not only that IWMP are in conformity with IWLP, but that in many cases, IWMP can be more effective. For instance, where international water accords between riparian states of a shared river basin are poorly developed and lack enforcement mechanisms under IWLP, those upstream states can abuse their geographical locations depriving those downstream-ers. In contrast, IWMPs stress the equitable and reasonable use of water resources among upstream and downstream users of a shared watercourse. Moreover, although IWLPs emphasize the conservation and preservation of ecosystems and the environment at the basin level, the inter-basin states especially those upstream can pose significant harm to the ecosystems. On the other side, Islam as the religion of peace, has placed much emphasis on the preservation of nature. For example, the verse, “.... And waste not by excess, for Allah loves not the wasters” [Quran, 7:31], illustrates the importance of the sustainable use of water and the environment. It is argued that if Islamic Water Management Principles are incorporated into the management instrument of Islamic States, the issue of equitable and sustainable use of water among Muslim-dominated riparian states (e.g., Iran, Afghanistan, etc.) will be solved.

This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT) models (such as log-normal, log-Cauchy, and log-logistic FT models) as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC) sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt) prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. In this paper, following a short introductory summary and definitions, this paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of NDT techniques in aerospace industry. In addition to this, within a some of significant NDT application extents, prognosis of composites is also briefly discussed.

This paper considers a two-way relay network, where two source nodes exchange messages through several relays in the presence of an eavesdropper, and the channel state information (CSI) of the eavesdropper is imperfectly known. The amplify-and-forward relay protocol is used and the relay beamforming weights are designed. The model is built up to minimize the total relay transmit power while guaranteeing the quality of service at users and preventing the eavesdropper from decoding the signals. Due to the imperfect CSI, a semi-infinite programming problem is obtained. An algorithm is proposed to solve the problem, and the iterative points are updated through the linesearch technique, where the feasibility are preserved during iterations. The optimality property is analyzed. The obtained subproblems are quadratic constrained quadratic programming problems, either with less than $4$ constraints or with only one variable, which are solved optimally. Simulation results demonstrate the importance of the proposed model, and imply that the proposed algorithm is efficient and converges very fast, where more than 85% of the problems are solved optimally.

We study the changes in quantum Fisher information (QFI) values for one quantum system consisting of a superposition of W and GHZ states. In a recent work [6], QFI values of this mentioned system studied. In this work, we extend this problem for the changes of QFI values in some noisy channels. We show the change in QFI depending on noise parameters. We report interesting results for different type of decoherence channels.

In light of the worldwide spreading requirements related to the disclosure of non-financial information, which are aligning to the Sustainable Development Goals (SDGs) developed by the United Nations (UN) in 2015, the study aims to analyse the influence of sustainability and other non-financial reporting on companies’ engagement in earnings management practices, through a pre-post adoption of European Directive 2014/95/EU comparative analysis for firms listed on the Bucharest Stock Exchange (BSE) in the period 2015-2019. To conduct the investigation, the research involves the assessment and analysis of three earnings management metrics resulted by running multiple linear regression models on a sample of 31 companies listed on BSE. Research findings emphasise a decrease in the use of income smoothing practices by sampled companies in the post-adoption period 2017-2019, compared to the period preceding the implementation of the EU directive related to mandatory disclosure of non-financial information, 2015-2016. Thus, firms characterised by a higher transparency in terms of sustainability reporting are less inclined to engage in earnings management practices. This research complements the literature in the field of sustainability reporting and earnings management, providing empirical evidence on the significance and impact of publishing non-financial information.

A cuprous oxide (Cu₂O) thin layer served as the base for a non-enzymatic glucose sensor in an alkaline medium, 0.1 NaOH solution, with a linear range of 50-200 mg/dL using differential pulse voltammetry (DPV) measurement. An X-ray photoelectron spectroscopy (XPS) study confirmed the formation of the cuprous oxide layer on the thin gold film sensor prototype. Quantitative detection of glucose in both phosphate-buffered saline (PBS) and undiluted human serum were carried out. Neither ascorbic acid nor uric acid even at a relatively high concentration level of 100mg/dL in serum interfered with the glucose detection, demonstrating the excellent selectivity of this non-enzymatic cuprous oxide thin layer based glucose sensor. Chronoamperometry (CA) and single potential amperometric voltammetry were used to verify the measurements obtained by differential pulse voltammetry (DPV), and the positive results validated that the detection of glucose in a 0.1 M NaOH alkaline medium by DPV measurement was effective. Nickel, platinum and copper are commonly used metals for non-enzymatic glucose detection. The performance of these metal-based sensors for glucose detection using DPV were also evaluated. Cuprous oxide (Cu₂O) thin layer based sensor showed the best sensitivity for glucose detection among the sensors evaluated.

The garnet Li₇La₃Zr₂O₁₂ (LLZO) has been widely investigated because of its high conductivity, wide electrochemical window and chemical stability to lithium metal. However, the usual preparation process of LLZO requires a long time of high-temperature sintering and a lot of mother powders against the lithium evaporation. The submicron Li₆.6La₃Zr₁.6Nb₀.4O₁₂ (LLZNO) powders are prepared by conventional solid-state reaction method and attrition milling process, which are stable cubic phase and have high sintering activity, and Li stoichiometric LLZNO ceramics are obtained by sintering at a relative lower temperature or for a short time by using these powders which are difficult to control under high sintering temperature and long sintering time. The particle size distribution, phase structure, microstructure, distribution of element, total ionic conductivity, relative density and activation energy of submicron LLZNO powders and LLZNO ceramics are tested and analyzed by laser diffraction particle size analyzer, XRD, SEM, EIS and Archimedean method. The total ionic conductivity of sample sintered at 1200 °C for 30 min is 5.09 × 10-4 S·cm-1, the activation energy is 0.311 eV, and the relative density is 87.3%, and sintered at 1150 °C for 60 min total ionic conductivity is 3.49 × 10-4 S·cm-1, the activation energy is 0.316 eV, and the relative density is 90.4%. At the same time, all-solid-state batteries are assembled with LiMn₂O₄ as positive electrode and submicron LLZNO powders as solid state electrolyte. After 50 cycles, the discharge specific capacity is 105.5 mAh/g and the columbic efficiency is above 95%.

The purpose of this paper is to simulate a two-dimensional Rayleigh-Taylor instability problem using the classical method of Finite Element analysis of a multiphase model using ANSYS FLUENT 19.2. The governing equations consist of a system of coupled nonlinear partial differential equations for conservation of mass, momentum and phase transport equations. The study focuses on the transient state simulation of Rayleigh Taylor waves and subsequent turbulent mixing in the two phases incorporated in the model. The Rayleigh Taylor instability is an instability of an interface between two fluids of different densities which occurs when the lighter fluid is pushing the heavier fluid in a gravitational field. The problem was governed by the Navier-Stokes and Cahn-Hilliard equations in a primitive variable formulation. The Cahn- Hilliard equations were used to capture the interface between two fluids systems. The objective of this article is to perform grid dependency test on Rayleigh Taylor Instability for 2 different mesh size and compare the results for the variation in Atwood Number. The results were validated with the observations from previous published literatures.

The General equilibrium theory tries to show how and why all free markets tend toward equilibrium in the long run. However, what is meant by equilibrium in this paper is more from a thermodynamical point of view. In order to understand the actual situation, it is necessary to study open systems which are complex. In physics, such a behavior in a complex system can be explain by using Non Equilibrium Thermodynamics. A system is able to self-organize and sustain itself away from equilibrium. Economic systems may fluctuate around a particular point. To sustain it far from the equilibrium state, it needs to degrade more energy and materials. In this study, the energy consumption patterns of Sri Lanka and USA are discussed. The pattern concerning Sri Lanka is close to the model proposed here, whereas the energy consumption pattern of USA is more complicated due to external factors.

The most common liver disorder nowadays is non-alcoholic fatty liver disease(NAFLD) and it is a progressive disease that rises in severity from steatosis to nonalcoholic steatohepatitis(NASH), fibrosis and cirrhosis to increase risk of developing hepatocellular carcinoma. It is a cause of great concern as there is an estimated seventy million Americans who are currently affected by NAFLD, and this is expected to only increase because of its association with obesity and diabetes and also a lack of therapies to keep its development and progression in check. In this particular study we performed a gene set enrichment analysis(GSEA) of differentially expressed genes in a green tea against methionine-choline deficient diet in high-fat patients in the development of non-alcoholic fatty liver disease(NAFLD). The downregulated genes were used to perform an enrichment analysis and in the ARCHS4 TFs Coexpression database the most significant gene was found to be KLF5_human_tf_ARCHS4_coexpression. In the ARCHS4 Kinases Coexpression pathway database STYK1_human_kinase_ARCHS4 Coexpression was found to be the most significant gene. And finally for the upregulated genes a similar enrichment analysis was performed and in the humancy database γ-linolenate biosynthesis_Homo sapiens_PWY-6000 gene was discovered to be the most significant one. This study has used bioinformatics tools and the Enrichr software to perform a comparative analysis of differentially expressed gene sets for high-fat patients having a diet consisting of green tea against a methionine-choline deficient diet. Green tea is known to contain several antioxidants and polyphenols which provide protection against many liver diseases such as non-alcoholic fatty liver disease(NAFLD). The present study simply tries to build awareness of this to the general public and allow them to learn more about certain diets which have protective effects against liver diseases. Hopefully by implementing these in their daily lifestyles the public can gain some form of protection against these types of liver disorders.

Quantum Fisher Information (QFI) is a very useful concept for analyzing situations that require phase sensitivity. It become a popular topic especially in Quantum Metrology domain. In this work, we study the changes in quantum Fisher information (QFI) values for one relative arbitrary phased quantum system consisting of a superposition of N Qubits W and GHZ states. In a recent work [7], QFI values of this mentioned system for N qubits were studied. In this work, we extend this problem for the changes of QFI values in some noisy channels for the studied system. We show the changes in QFI depending on noise parameters. We report interesting results for different type of decoherence channels. We show the general case results for this problem.

In this paper, the design of a low cost portable ventilator with performance analysis have been done to solve the scarcity of respiratory ventilators for COVID-19 patients. The materials used to build the system are: DC motor, rotating disc and pneumatic piston. The system input is the patient heart beat and the output is volume of air to the patient lung with adjusted breathing rate. This ventilator adjusts the breathing rate to the patient depending on his heart beat rate. The performance analysis of this system have been done using Proportional Integral Derivative (PID) and Full State Feedback H2 controllers. Comparison of the system with the proposed controllers have been done using a step change and a random change of the patient heart beat and a promising result have been analyzed successfully.

The present study provides an observation and documentation on the effect of static magnetic field on the growth of Triticum aestivum. The seeds are allowed to germinate and the seedlings are grown in an environment of the controlled static magnetic field while other physical factors such as temperature, light exposure, soil pH, etc. are held constant. Also, a comparison of influence on the average height between both the poles of the magnet is estimated and north pole oriented magnet is found to imply a significant difference. Finally some of the potential applications of the study in non-invasive protein silencing, GMO production, Vertical farming and Terraforming are briefly discussed.

Thresholding is considered as a statistical-decision making theory which can lessen the average error incurred in allocating pixels to two or more groups. The traditional Bayes decision rule can be applied with the prior knowledge of the Probability Density Function (PDF) of each class. It is surmised that a threshold resulting in the best class separation is the optimal one. In this paper, Otsu’s thresholding for image segmentation has been implemented. The well-known Otsu’s method is to learn a threshold that can maximize the between-class variance or equivalently make light of the within-class variance of the entire image. At first, a color image of a tree is taken. After that, the image is transformed into a grayscale image. Then in the first part, two-level thresholding is conducted, and later on, three-level thresholding is also applied. Again, two-level thresholding, as well as three level thresholding, are also applied to some other images. Finally, the comparison is made between two level thresholding and three level thresholding

Southern highbush blueberry plantations have been expanded into worldwide non-traditional growing areas with elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems – alternatives to traditional open field production – such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to the open field production. In addition, potential solutions have been provided for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high quality berries. Alternative systems, compared to the field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have potential to be profitable.

Two-photon imaging of light stimulus-evoked neuronal activity has been used to study all neuron classes in the vertebrate retina, from the photoreceptors to the retinal ganglion cells. Clearly, the ability to study retinal circuits down to the level of single synapses or zoomed out at the level of complete populations of neurons, has been a major asset in our understanding of this beautiful circuit. In this chapter, we discuss the possibilities and pitfalls of using an all-optical approach in this highly light-sensitive part of the brain.

The excited-state lifetimes of the anticoagulant drug warfarin (W) in water and in the absence and presence of methyl-β-cyclodextrins (Me-β-CD) were recorded using time-resolved fluorescence measurements. Selective excitation of the open and cyclic protonated isomers of W were acquired with laser emitting diodes (LED) producing 320 and 280 nm excitation pulses, respectively. Formation of the inclusion complex was checked by UV–visible absorption spectroscopy, and the values of binding constants (2.9 × 10³ M^–1 and 4.2 × 10² M^–1 for protonated and deprotonated forms, respectively) were extracted from the spectrophotometric data. Both absorption and time-resolved fluorescence results established that the interior of the macromolecular host binds preferentially the open protonated form, red shifts the maximum of its absorption of light at ~305 nm, extends its excited-state lifetime, and decreases its emission quantum yield (ФF). Collectively, sequestration of the open guest molecules decreases markedly their radiative rate constants (kr), likely due to formation of hydrogen-bonded complexes in both the ground and excited states. Due to lack of interactions, no change was observed in the excited-state lifetime of the cyclic form in the presence of Me-β-CD. The host also increases the excited-state lifetime and ФF of the drug deprotonated form (W¯). These later findings could be attributed to the increased rigidity inside the cavity of Me-β-CD. The pKa values extracted from the variations of the UV–visible absorption spectra of W versus the pH of aqueous solution showed that the open isomer is more acidic in both ground and excited states. The positive shifts in pKa values induced by three derivatives of cyclodextrins: HE-β-CD, Ac-β-CD, and Me-β-CD supported the preferential binding of these hosts to open isomers over cyclic.

Despite huge effort has been devoted to the design of the initiators and reaction conditions, it remains challenging to synthesize high molecular weight polypeptides with conventional solution phase synthesis. In this work, surface-initiated vapor deposition polymerization (SI-VDP) was utilized to graft synthetic polypeptides poly (γ-benzyl L-glutamate) (PBLG) from polystyrene (PS) resin beads by ring-opening polymerization of N-carboxyanhydrides (NCAs). It was demonstrated for the first time that high molecular weight bulk PBLG (> 500,000) could be readily obtained within one hour via solvent-free synthetic method which paves the way for the synthesis of copolypeptides with high molecular weight.

In the paper is described the control electronics for an industrial pneumatic – hydraulic system based on a low-cost PLC. The developed system is a hydraulic pulse system and it generates series of high pressure hydraulic pulses (max. 200 bar). We describe requirements, an overall concept of the embedded control system, user interface, security features and network connectivity. In the description of the software solution we describe implementation of hierarchical ordered program threads (multithreaded program) and main control state machine. At the conclusion, we describe the calibration method of the system and calibration curves and we present the schematic diagram and a photo of a functional prototype of the system.

A new variant of two-echelon routing problem is investigated, where the truck and the drone are used to cooperatively complete the deliveries of all parcels. The truck not only acts as a tool for parcel delivery, but also serves as a moving depot for the drone. The drone can carry several parcels and take off from the truck, while returning to the truck after completing the delivery. The energy consumption model for the routing process of the drone is analyzed, when it is utilized to deliver multiple parcels. A two-stage route-based modelling approach is proposed to optimize both the truck’s main route and the drone’s adjoint flying routes. A hybrid heuristic integrating nearest neighbor and cost saving strategies is developed to quickly construct a feasible solution. The simulated annealing algorithm is applied to improve the quality of the solution, where a Tabu list is employed to improve the search efficiency. Random instances at different scales are used to test the performance of the proposed algorithm. A case study based on the practical road network in Changsha, China, is presented, through which the sensitivity analysis is conducted with respect to some critical factors.

We extended the usage of the expansion method based on Sine-Gordon equation to the two dimensional Fisher equation. The relation between the trigonometric and hyperbolic functions are derived from the Sine-Gordon equation dened in two space dimension. The complex-valued traveling wave solutions to the two dimensional Fisher and Nagumo equations are set in forms a nite series of multiplications of powers of sech(.) and tanh(.) functions.

Hearing impairment is an immensely diagnosed genetic cause, 5% of the total world population effects with different kind of congenital hearing loss (HL). In third-world countries or countries where consanguineous marriages are more common the frequency rate of genetic disorders are at its zenith. Approximately, the incidence of hearing afflictions is ostensibly 7-8:1000 individuals whereas it is estimated that about 466 million peoples suffer with significant HL, and of theses deaf cases 34 million are children’s up to March, 2020. Several genes and colossal numbers of pathogenic variants cause hearing impairment, which aided in next-generation with recessive, dominant or X-linked inheritance traits. This review highlights on syndromic and non-syndromic HL (SHL and NSHL), and categorized as conductive, sensorineural and mixed HL, which having autosomal dominant and recessive, and X-linked or mitochondrial mode of inheritance. Many hundred genes involved in HL are reported, and their mutation spectrum becomes very wide. Mapping of pathogenic genes in consanguinity family is facilitated to understand the disease history. Review presents the bases of HL and also focused on various genetic factors that cause deafness like the basics of genetic inheritance, and classic and well-characterized inherited factors of it. It also overviews the application of linkage analysis, SNPs genotyping and whole exome sequencing methods, in mapping and identification of new locus, causative genes and their variants in families inherited with HL. Conclusively, this review supports researchers in understanding the location of chromosome, the causative genes and specific locus which causing deafness in humans.

External quantum efficiency of industrial-grade green InGaN light-emitting diodes (LEDs) has been measured in a wide range of operating currents at various temperatures from 13 K to 300 K. Unlike blue LEDs, the efficiency as a function of current is found to have a multi-peak character, which could not be fitted by a simple ABC-model. This observation correlated with splitting of LED emission spectra into two peaks at certain currents. The characterization data are interpreted in terms of non-uniformity of the LED active region, which is tentatively attributed to extended defects like V-pits. We suggest a new approach to evaluation of temperature-dependent light extraction and internal quantum efficiencies taking into account the active region non-uniformity. As a result, the temperature dependence of light extraction and internal quantum efficiencies have been evaluated in the temperature range mentioned above and compared with those of blue LEDs.

This article presents answers to the questions on superresolution and structured illumination microscopy as raised in the editorial of a recent publication [K. Prakash et al. arXiv, 2102.13649, 2021]. The answers are based on my personal views on superresolution in light microscopy, supported by reasoning. Discussed are the definition of superresolution, Abbe’s resolution limit and the classification of superresolution methods into non-linear-, prior-knowledge- and near-field-based superresolution. A further focus is put on capabilities and technical aspects of present and future structured illumination microscopy (SIM) methods.

Over the past decade, the credit quality of loan portfolios across most countries in the world remained relatively stable until the financial crises hit the global economy in 2007–2008. In this paper I discuss, the relationship between non-performing loans and economic landscape. Since 2008, nonperforming loans have been an increasingly hot topic in the international scene, due to their important and rising volume and their impact on the economy as a whole, on the banking system and on its credit supply. Since then, average bank asset quality deteriorated sharply due to the global economic recession. Yet the deterioration of loan performance was very uneven across countries. I am interested in explaining these differences in bank asset quality across countries and over time. In this paper, I therefore study the empirical determinants of non-performing loan (NPL) ratios using a data set for EU countries covering the past decade. The paper assumes that the spatial organization of banking systems and the geographical distribution of comercial banks branches, ATMs and GDP growth are major factors influencing the effectiveness in credit system. The aim of this paper is to construct a continuous and quantifiable model, which will demonstrate a role of economic condition, technology, competition, policy, business climate in Financial Stability. Main hypotheses suggests, that GDP growth, interest rate, new business, FDI, ATMs and geographical distribution of branches have an influences on NPL (non-performing loans).

Atoms in Molecules (AIM), Natural Bond Orbital (NBO), and normal coordinate analysis have been carried out at the global minimum structures of TH₅⁺ (T = C/Si/Ge). All these analyses lead to a consistent structure for these three protonated TH₄ molecules. The CH₅⁺ has a structure with three short and two long C-H covalent bonds and no H-H bond. Hence, the popular characterization of protonated methane as a weakly bound CH₃⁺ and H₂ is inconsistent with these results. However, SiH₅⁺ and GeH₅⁺ are both indeed a complex formed between TH₃⁺ and H₂ stabilized by a tetrel bond, with the H₂ being the tetrel bond acceptor. The three-center-two-electron bond (3c-2e) in CH₅⁺ has an open structure, which can be characterized as a V-type 3c-2e bond and that found in SiH₅⁺ and GeH₅⁺ is a T-type 3c-2e bond. This difference could be understood based on the typical C-H, Si-H, Ge-H and H-H bond energies. Moreover, this structural difference observed in TH₅⁺ can explain the trend in proton affinity of TH₄. Carbon is selective in forming a ‘tetrel bond’ and when it does, it might be worthwhile to highlight it as a ‘carbon bond’.

Omega-3 polyunsaturated fatty acids (ω3-PUFAs), including docosahexaenoic acid (DHA), have been shown to exert anticancer effects by inducing apoptotic cell death. However, the mechanism for DHA-induced cell death in lung cancer is not fully understood. Here, we show that DHA induces apoptosis in two human EGFR mutant non-small cell lung cancer (NSCLC) cell lines, and that DHA-induced cell death is accompanied by SIRT6 activation and attenuated Hedgehog (Hh) signaling. Knockdown of SIRT6 using siRNAs inhibited DHA-induced apoptosis, whereas SIRT6 overexpression increased apoptotic cell death. DHA-induced SIRT6 activation was associated with downregulation of Hh signaling, and knockdown of SIRT6 resulted in augmentation of Hh signaling. Pretreatment of NSCLC cells with a Smoothened agonist prevented DHA-induced decreases in the levels of Hh signaling proteins and increases in cleaved PARP levels. Moreover, endogenous production of ω3-PUFAs in PC9 cells via fat-1 expression resulted in elevated SIRT6 levels and reduced levels of Hh signaling molecules, including Gli, following DHA treatment. Overall, these results implicate that ω3-PUFAs induce apoptosis by downregulating Hh signaling via SIRT6 activation in human EGFR mutant NSCLC cells. These findings suggest that ω3-PUFAs potentially represent an effective therapy for the chemoprevention and treatment of NSCLC.

This paper aims to present a smart high speed battery charger, powered by a photovoltaic module array, for a LiFePO4 battery as a solar energy storage device. With a battery charging strategy, the presented battery charger involves a Buck converter as the core equipped with a simple maximum power point (MPP) tracker. Considering complexity reduction and easy hardware implementation, a constant voltage MPP tracking approach is adopted such that the maximum amount of output power can be delivered to the load in response to an arbitrary change in the solar radiation. A smart two-stage charging strategy, with a constant current mode followed by a constant voltage mode, is employed in such a way that the battery charge process can be accelerated largely, while the damage caused by overcharging can be prevented. In the end, the performance of this proposal is validated experimentally.

The present paper aims to increase knowlodge of the methods of resistance estimating of concrete in situ by means of non-destructive tests used to integrate the quantitative results from cylindrical specimens (core). The results of experimental investigations carried out on concrete conglomerate samples of a school building are shown. The experimental campaign then will be presented like a case study, conducted on a series of concrete beams and pillars of an existing building. The distructive tests on cores were conducted at the Civil Structures Laboratory of the Engineering Department of the University of Campania "Luigi Vanvitelli". The expression obtained through the calibration procedure of the values of non-destructive tests with those provided by the core drills allowed to estimate the average values of the compressive strength of the concrete. It is highlighted how this result was achieved with a very limited core number provided that they are extracted in selected points and that there was a proportionality link with the resistances obtained from non distructive tests.

With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

This paper focuses on evaluating airline service quality from the perspective of passengers view. Until now a lot of researches has performed in airline service quality evaluation in the world but a little research has been conducted in Iran, yet. In this research a framework for measuring airline service quality in Iran is proposed. After reviewing airline service quality criteria, SSQAI model was selected because of its comprehensiveness in covering airline service quality dimensions. SSQAI questionnaire items were redesigned to adopt with Iranian airlines requirements and environmental circumstances in the Iran's economic and cultural context. This study includes fuzzy decision-making theory, considering the possible fuzzy subjective judgment of the evaluators during airline service quality evaluation. Fuzzy TOPSIS have been applied for ranking airlines service quality performances. Three major Iranian airlines which have the most passenger transfer volumes in domestic and foreign flights, were chosen for evaluation in this research. Results demonstrated Mahan airline has got the best service quality performance rank in gaining passengers' satisfaction with delivery of high quality services to its passengers, among the three major Iranian airlines. IranAir and Aseman airlines placed in the second and third rank, respectively, according to passenger's evaluation.Statistical analysis have been used in analyzing passenger responses. Due to abnormality of data, Non-parametric tests were applied. To demonstrate airline ranks in every criterion separately, Friedman test was performed. Variance analysis and Tukey test were applied to study the influence of increasing in age and educational level of passengers' on degree of their satisfaction from airline's service quality. Results showed that age has not significant relation with passenger satisfaction of airlines, however increasing in educational level demonstrated a negative impact on passengers' satisfaction from airline's service quality.

This paper proposes a game-theoretic framework for quantifying effects of strategic bidding behavior of load aggregators (LAs) on wholesale electricity market equilibrium. The independent system operator (ISO) employs double-sided auction design to settle transactions in the wholesale electricity market. Generating companies (GENCOs) and LAs submit their bids to the ISO in the economic model of supply function equilibrium. Under the smart grid paradigm, a LA participates in the electricity market on behalf of end-consumers to minimize their total payment for purchasing electricity. In this paper, bi-level programming (BLP) method is employed to determine optimal bidding strategy of self-interested market participants. In the upper level, the profit of intended market participant is maximized and in the lower level, the ISO clears the market via a bid-based security constrained economic dispatch (SCED). Also, competition of GENCOs and LAs is modeled as a non-cooperative game. To examine the effects of strategic bidding behavior of LAs on market equilibrium, the proposed model is applied to the IEEE 9-bus and the IEEE 30-bus test systems. According to numerical results, to allow the LAs to behave strategically along with the GENCOs makes the former better off and the latter worse off, while the net effect of this on total social welfare turns out to be case-contingent.

Laws and regulations make powerful contribution in addressing multitudes of public health concerns. We examined the Public Health Act (PHA) in Malawi to understand its relevance to the ever-growing and changing threats posed by infectious and non-infectious diseases. The current Public Health Act of Malawi came into effect in 1948 to protect and preserve public health. The Act has undergone several amendments, the last one being in 1975. It draws much of its inspiration and standards from the 19th century British laws on insanitary housing, poor ventilation, and drainage. Such laws are silent on emerging major public health concerns including non-communicable diseases (NCDs) such as cardiovascular diseases and diabetes as well as road traffic injuries. This makes the Act outdated and ill equipped to address the 21st century public health concerns. Although supplementary legislation such as the HIV/AIDS Act and Mental Treatment Act have recently been enacted, they are yet to be consolidated into the Public Health Act. Consequently, existing policies and strategic plans that are meant to address gaps in public health and ensure coordinated effort lack support of laws and regulations. The Act also places great emphasis on mandatory vaccinations, quarantine and isolation against smallpox, a disease that has long been eradicated. Furthermore, although the Public Health Act outlines powers, duties and penalties, it fails to reinforce acceptable behaviour due to the insignificant penalties for noncompliance. There is a need for immediate and prompt revision and restructuring of the Public Health Act based on scientific evidence. Such laws require adequate consultation and interaction with key experts and stakeholders from a wide range of disciplines.

Ongoing COVID-19 Pandemic has resulted into massive damage to various platforms of global economy which has caused disruption to human livelihood. Natural Language Processing has been extensively used in different organizations to categorize sentiments, perform recommendation, summarizing information and topic modelling. This research aims to understand the non-medical impact of COVID-19 on global economy by leveraging the natural language processing methodology. This methodology comprises of text classification which includes topic modelling on unstructured COVID-19 media articles dataset provided by Anacode. Like other Natural Language Processing algorithms, Latent Dirichlet allocation (LDA) and Non-negative matrix factorization (NMF) has been proposed to classify the media articles dataset in order to analyze COVID-19 pandemic impacts in the different sectors of global economy. Model Accuracy was examined based on the coherence and perplexity score which came out to be 0.51 and -10.90 using LDA algorithm. Both the LDA and NMF algorithm identified similar prevalent topics that was impacted by COVID-19 pandemic in multiple sectors of economy. Through intertopic distance map visualization produced by LDA algorithm, it can be reciprocated that general industries which includes children schooling, parental care, and family gatherings had the major impact followed by business sector and the financial industry.

Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i) A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii) Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform) distance which is endowed with the intensity information is used to measure the scale space extrema. (iii) To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV) and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

Forest community connections are crucial to ensure forest stewardship and sustainability. We explored the potential of mushrooming to enable such connections in contexts where these connections have been historically broken, alienating local people from forests. Taking the case of the recent devolution of a community forest (baldios) in central Portugal to the local population, we present a five-year pilot project to rework mycology from a mushroom-centered approach to a mushroom-in-baldios approach. Mushrooms were used as an entry-point to connect the forest ecology with the challenges of governance and community building. The devised activities provided an opportunity for people inside and outside the local community to adventure into the woods and find out more about their socio-ecological history, develop communal and convivial relationships and engage in the responsible gathering of wild mushrooms. However, the hosting of mushroomers to know, value and engage with the community forest recovery has constantly working against the enclosure of mushrooms to provide marketable forms of leisure. The outcome of these activities depends on the relationships established between mushrooms, mycologists, local administrators, commoners and poachers, all operating within a framework that favors the eradication of resources instead of long-term relationships that sustain places.

According to the operation conditions of time unlimited passive containment heat removal system (TUPAC), a separate effect experiment facility was established to investigate the heat transfer performance of steam condensation in presence of non-condensable gas. The effect of wall subcooling temperature, total pressure and mass fraction of the air on heat transfer process was analyzed. The heat transfer model was also developed. The results showed that the heat transfer coefficient decreased with the rising of subcooling temperature, the decreasing of the total pressure and air mass fraction. It was revealed that Dehbi’s correlation predicted the heat transfer coefficient conservatively, especially in the low pressure and low temperature region. The novel correlation was fitted by the data obtained in the following range: 0.20~0.45 MPa in pressure, 20% ~ 80% in mass fraction, 15°C ~ 45°C in temperature. The discrepancy of the correlation and experiment data was with ±20%.

VpStyA1 and VpStyA2B of Variovorax paradoxus EPS is annotated and characterized as the first representative of an E2-type styrene monooxygenase of proteobacteria. It comprises a single epoxidase (VpStyA1) and a fusion protein (VpStyA2B) which serves mainly as NADH:FAD-oxidoreductase. VpStyA2B had a Km of 33.6 ± 4.0 µM for FAD and a kcat of 22.3 ± 1.1 s-1. VpStyA2B and VpStyA1 showed monooxygenase activity on styrene of 0.14 U mg-1 and 0.46 U mg-1 as well as on benzyl methyl sulfide of 1.62 U mg-1 and of 3.11 U mg-1. A putative fusion region at position 408 (AREAV) was mutated to provide insights on VpStyA2B-function. The best mutant (408-AAAAA) obtained showed a 6.6-times higher affinity for FAD while keeping the NADH-affinity and -oxidation activity. Corresponding epoxidase activity increased (1.6-times). But, other mutants showed still NADH:FAD-oxidoreductase activity, but lost mostly their epoxidase activity indicating effects on the monooxygenase-part as well. Thus, this monooxygenase system represents an interesting candidate for biocatalyst development.

The remaining capacity can only be measured with offline method. This brings great challenge for the online prediction of Li-ion battery’s RUL. A novel online prediction method for Li-ion battery’s RUL was proposed, which is based on multiple health indicators (HIs) and can be derived from the batteries’ historical operation data. Firstly, four indirect HIs were built according to the battery’s operation current, voltage and temperature data respectively. On that basis, a generalized regression neural network (GRNN) was developed to estimate the battery’s remaining capacity, and the non-linear autoregressive approach (NAR) was utilized to predict the battery’s RUL based on the estimated capacity value. Furthermore, to reduce the interference, twice wavelet denoising were performed with different thresholds. A case study is conducted with a NASA battery dataset to demonstrate the effectiveness of the method. The result shows that the proposed method can obtain Li-ion batteries’ RUL effectively.

Preconception lifestyle modification and reducing several known risk factors may have an influence on the future pregnancy outcome. The aim of the study was to analyse health behaviour and personal values, as well as to assess the relationship of these factors in women without children, in pregnant ones and in women who had already delivered babies. The questionnaire survey included Health Behaviour Inventory (HBI), Personal Value List (PVL) and the sociodemographic data and was conducted in 538 women. These women were divided into 3 groups: women who recently delivered (n = 235), pregnant women (n = 121) and childless women (n = 182). Pregnant women demonstrated a significantly higher level of declared health behaviours and also they rated higher subscales values "positive mental attitude" and "health practices" in comparison to women who recently delivered and to childless women. In all tested groups the highest rated personal value was "a successful family life", while the most appreciated symbol of happiness was "love and friendship". Our results suggest that the system of values and the perception of happiness symbols may influence women's health behaviours. Positioning “health” in the hierarchy of personal values as the most important one may facilitate introduction of healthy behaviours. This in turn could reduce several adverse pregnancy outcomes that are potentially modifiable with changing preconception health attitudes. Our results also identify several unanswered questions and highlights areas where new research is needed.

Bacterial infections occur when wound healing fails to reach the final stage of healing, usually hindered by the presence of different pathogens. Different topical antimicrobial agents are used to inhibit bacterial growth due to antibiotic failure in reaching the infected site accompanied very often by an increased drug resistance and other side effects. In this review, we focus on antimicrobial peptides (AMPs), especially those with a high potential of efficacy against multidrug-resistant and biofilm-forming bacteria and fungi present in wound infections. Currently, different AMPs undergo preclinical and clinical phase to combat infection-related diseases. AMP dendrimers (AMPDs) have been mentioned as potent microbial agents. Various AMP delivery strategies, such as polymers, scaffolds, films and wound dressings, organic and inorganic nanoparticles, to combat infection and modulate the healing rate have been discussed as well. New technologies such as CRISPR-Cas are taken into consideration as potential future tools for AMP delivery in skin therapy.

3D meso-scale structures that can reach up to centimeters in overall size but retain micro- or nano-features, proved to be promising in various science fields ranging from micro-mechanical metamaterials to photonics and bio-medical scaffolds. In this work we present synchronization of the linear and galvano scanners for efficient femtosecond 3D optical printing of objects at the meso-scale (from sub-μm to sub-cm spanning five orders of magnitude). In such configuration the linear stages provide stitch-free structuring at nearly limitless (up to tens-of-cm) working area, while galvo-scanners allow to achieve translation velocities in the range of mm/s-cm/s without sacrificing nano-scale positioning accuracy and preserving undistorted shape of the final print. The principle behind this approach is demonstrated, proving its inherent advantages in comparison to separate use of only linear stages or scanners. The printing rate is calculated in terms voxels/s, showcasing the capability to maintain an optimal feature size while increasing throughput. Full capabilities of this approach are demonstrated by fabricating structures that reach millimeters in size but still retain μm-scale features: scaffolds for cell growth, microlenses and photonic crystals. All this is combined into a benchmark structure: a meso-butterfly. Provided results show that synchronization of two scan modes is crucial for the end goal of industrial-scale implementation of this technology and makes the laser printing well aligned with similar approaches in nanofabrication by electron and ion beams.

We aimed at analyzing Chlorophyll-a and CDOM dynamics from field measurements and at assessing the potential of multispectral satellite data for retrieving water-quality parameters in three small surface reservoirs in the Brazilian semiarid region. More specifically, this work comprises i) analysis of Chl-a and trophic dynamics; ii) characterization of CDOM; iii) estimation of Chl-a and CDOM from OLI/Landsat-8 and RapidEye imagery. The monitoring lasted 20 months within a multi-year drought, which contributed to water-quality deterioration. Chl-a and trophic state analysis showed a highly eutrophic status for the perennial reservoir during the entire study period, while the non-perennial reservoirs ranged from oligotrophic to eutrophic, with changes associated with the first events of the rainy season. CDOM characterization suggests that the perennial reservoir is mostly influenced by autochthonous sources, while allochthonous sources dominate the non-perennial ones. Spectral-group classification assigned the perennial as CDOM-moderate and highly eutrophic reservoir, whereas the non-perennial ones were assigned as CDOM-rich and oligotrophic-dystrophic reservoirs. The remote sensing initiative was partially successful: the Chl-a was best modelled using RapidEye for the perennial; whereas CDOM performed best with Landsat-8 for non-perennial reservoirs. This investigation showed high potential for retrieving water quality parameters in dry areas with small reservoirs.

In this short communication, we conducted first-principles calculations to explore the stability of boron monochalcogenides (BX, X=S, Se or Te), as a new class of two-dimensional (2D) materials. We predicted BX monolayers with two different atomic stacking sequences of ABBA and ABBC, referred in this work to 2H and 1T, respectively. Analysis of phonon dispersions confirm the dynamical stability of BX nanosheets with the both 2H and 1T atomic lattices. Ab-initio molecular dynamics simulations reveal the outstanding thermal stability of all predicted monolayers at high temperatures over 1500 K. BX structures were found to exhibit high elastic modulus and tensile strengths. It was found that BS and BTe nanosheets can show high stretchability, comparable to that of the graphene. It was found that all predicted monolayers exhibit semiconducting electronic character, in which 2H structures present lower band-gaps as compared with 1T lattices. The band-gap values were found to decrease from BS to BTe. According to the HSE06 results, 1T-BS and 2H-BTe show respectively, the maximum (4.0 eV) and minimum (2.06 eV) electronic band-gaps. This investigation introduces boron monochalcogenides as a novel class of 2D semiconductors with remarkable thermal, dynamical and mechanical stability.

This is a report on a dynamic autonomous magnetic interaction which does not depend on polarities resulting in short ranged repulsion involving one or more inertial bodies and a new class of bound state based on this interaction. Both effects are new to the literature, found so far. Experimental results are generalized and reported qualitatively. Working principles of these effects are provided within classical mechanics and found consistent with observations and simulations. The effects are based on the interaction of a rigid and finite inertial body (an object having mass and moment of inertia) endowed with a magnetic moment with a cyclic inhomogeneous magnetic field which does not require to have a local minimum. Such a body having some DoF involved in driven harmonic motion by this interaction can experience a net force in the direction of the weak field regardless of its position and orientation or can find stable equilibrium with the field itself autonomously. The former is called polarity free magnetic repulsion and the latter magnetic bound state. Experiments show that a bound state can be obtained between two free bodies having magnetic dipole moment. Various schemes of trapping bodies having magnetic moments by rotating fields are realized as well as rotating bodies trapped by a static dipole field in presence of gravity. Also, a special case of bound state called bipolar bound state between free dipole bodies is investigated.

Since coffee has been shown to influence positively the metabolism of subjects with metabolic syndrome (MetS), we aimed to evaluate the short- and long-term effects of a coffee-based supplement on different features of diet-induced MetS. 24 Sprague Dawley rats were divided into control or nutraceuticals groups to receive a high-fat/high fructose diet with or without a mixture of caffeic acid (30 mg/day), trigonelline (20 mg/day), and cafestol (1 mg/day) for 12 weeks. An additional 11 rats were assigned to an acute crossover study. In the chronic experiment, nutraceuticals did not alter body weight or glycemic control but improved fed hyperinsulinemia and HOMA-IR, and plasma adiponectin levels. The impact of nutraceuticals on post-prandial glycemia tended to be more pronounced after acute administration than at the end of the chronic study. Circulating and intrahepatocellular alanine transaminase activity, assessed by hyperpolarized-¹³C NMR spectroscopy, were reduced by coffee nutraceuticals at endpoint. There was also a tendency towards lower liver triglyceride content and histological steatosis score in the intervention group. In conclusion, a mixture of coffee nutraceuticals improved insulin sensitivity and exhibited hepatoprotective effects in a rat model of MetS. Higher dosages with or without caffeine deserve to be studied in the future.

This article puts forward the bi-matrix games with crisp parametric payoffs based on interval value function approach. We conclude that the equilibrium solution of the game model can converted into optimal solutions of the pair of the non-linear optimization problem. Finally, experiment results show the efficiency of the model.

Water soluble polymers have gained an increasing interest in enhanced oil recovery (EOR) processes, especially as polymer flooding. Despite the fact that the flow of polymer in porous medium has been a research subject for many decades with numerous publications, there are still some research areas that need progress. The prediction of polymer injectivity remains elusive. Polymers with similar shear viscosity might have different in-situ rheological behaviors and may be exposed to different extent of mechanical degradation. Hence, determining polymer in-situ rheological behavior is of great significance for defining its utility. In this study, an investigation of rheological properties and mechanical degradation of different HPAM (partially hydrolyzed polyacrylamide) polymers was performed using Bentheimer sandstone outcrop cores. Results show that, HPAM in-situ rheology is different from bulk rheology measured in rheometer. Specifically, shear thickening behavior occurs at high rates, and near-Newtonian behavior is measured at low rates in porous media. This deviates strongly from measurements in the rheometer. Polymer molecular weight and concentration influence its viscoelasticity and subsequently its flow characteristics in porous media. Exposure to mechanical degradation by flow at high rate through porous media leads to significant reduction in shear thickening and thereby improved injectivity. More importantly, the degraded polymer maintained in-situ viscosity at low flow rates indicating that improved injectivity can be achieved without compromising viscosity at reservoir flow rates. This is explained by reduction in viscoelasticity. Mechanical degradation also leads to reduced residual resistance factor (RRF), especially for high polymer concentrations. For some of the polymer injections, successive degradation (increased degradation with transport length in porous media) was observed. The results presented here may be used to optimize polymer injectivity.

The Urban Heat Island (UHI) is one of the more serious consequences of urbanization resulting in impacts on thermal comfort levels, heat stress, and even mortality. For Municipal Beirut, implementation of “cool” surface materials and green spaces have been recommended to counterbalance the UHI. This paper builds on previous findings on the topic of non-constructible parcels within the district of Bachoura in Municipal Beirut and examines the possibility of implementing “cool” surface or paving materials and urban vegetation which can improve thermal conditions especially during the summer period and with the viewto project the positive findings of this case study to the entire Municipal Beirut area. A numerical analysis using ENVI-met 4.0 investigates the thermal performance of these non-constructibles further to implementation of high reflective surfaces and urban vegetation within a broad neighborhood scale in Bachoura. Results show reductions in ambient temperatures up to 1K on a summer day.. Within the framework of an integrated approach to planning, this form of urban acupuncture aims for substantial UHI reduction. Energy performance of buildings further to implementation of these mitigation measures is also recommended for future studies and to validate the findings in this paper.

Estimation of core and surface temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. While, it is impractical to measure core temperature using physical sensors, implementing a complex estimation strategy in on-board low-cost BMS is challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models having different levels of accuracy and complexity. Broadly, there are first-order and second-order heat capacitor-resistor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study to access suitability in online prediction and onboard BMS. The aim is to guide whether it’s worth investing towards developing a second-order model instead of a first-order model with respect to prediction accuracy considering modelling complexity, experiments required and the computational cost. Both the thermal models along with the parameter estimation scheme are modelled and simulated using MATLAB/Simulink environment. Models are validated using laboratory test data of a cylindrical 18650 LIB cell. Further, a Kalman Filter with appropriate process and measurement noise levels are used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models are analyzed for comparison purposes.

This paper presents a new scientific contribution on the two-dimensional (2-D) subdomain technique in polar coordinates taking into account the finite relative permeability of the ferromagnetic material. The constant relative permeability corresponds to linear part of the nonlinear B(H) curve. As in conventional technique, the method of separation of variables and the Fourier’s series are used for the resolution of magnetostatic Maxwell’s equations in each region. Although, the general solutions of magnetic field in the subdomains and boundary conditions (BCs) between regions are different in the conventional and proposed method. In this later, the magnetic field solution in each subdomain is a superposition of two magnetic quantities in the two directions (i.e., r- and Q-axis) and the BCs between two regions are also in both directions. For example, the scientific contribution has been applied to an air- or iron-cored coil supplied by a constant current. The distribution of local quantities (i.e., the magnetic vector potential and flux density) has been validated by a corresponding 2-D finite-element analysis (FEA). The obtained semi-analytical results are in very good agreement with those of numerical method.

Small non-coding RNAs (sRNAs) are ubiquitously found in the three domains of life playing large-scale roles in gene regulation, transposable element silencing, and defense against foreign elements. While a substantial body of experimental work has been done to uncover function of sRNAs in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. Recently, high throughput studies using RNA-sequencing revealed that sRNAs are broadly expressed in the Archaea, comprising thousands of transcripts within the transcriptome during non-challenged and stressed conditions. Antisense sRNAs, which overlap a portion of a gene on the opposite strand (cis-acting), are the most abundantly expressed non-coding RNAs and they can be classified based on their binding patterns to mRNAs (3’ UTR, 5’ UTR, CDS-binding). These antisense sRNAs target many genes and pathways, suggesting extensive roles in gene regulation. Intergenic sRNAs are less abundantly expressed and their targets are difficult to find because of a lack of complete overlap between sRNAs and target mRNAs (trans-acting). While many sRNAs have been validated experimentally, a regulatory role has only been reported for very few of them. Further work is needed to elucidate sRNA-RNA binding mechanisms, the molecular determinants of sRNA-mediated regulation, whether protein components are involved, and how sRNAs integrate with complex regulatory networks.

The mitigation of NLOS (non-line-of-sight) propagation conditions is one of main challenges in wireless signals based indoor localization. When RFID localization technology is applied in applications, RSS fluctuates frequently due to the shade and multipath effect of RF signal, which could result in localization inaccuracy. In particularly, when tags carriers are walking in LOS (line-of-sight) and NLOS hybrid environment, great attenuation of RSS will happen, which would result in great location deviation. The paper proposes an IMU-assisted (Inertial Measurement Unit) RFID based indoor localization in LOS/NLOS hybrid environment. The proposed method includes three improvements over previous RSS based positioning methods: IMU aided RSS filtering, IMU aided LOS/NLOS distinguishing and IMU aided LOS/NLOS environment switching. Also, CRLB (Cramér-Rao Low Bound) is calculated to prove theoretically that indoor positioning accuracy for proposed method in LOS/NLOS mixed environment is higher than position precision of only use RSS information. Simulation and experiments are conducted to show that proposed method can reduce the mean positioning error to around 3 meters without site survey.

LASER cladding is a technique which has as main purpose to improve mechanical properties of materials surface with the addition of thin layers of other materials. Cladding/coating/addition material can be transferred to the substrate by powder injection, wire feeding or paste feeding and by the method of pre-placing the powders on the substrate. LASER cladding as a technique has only about 40 years. Is not yet a current technology and more work is needed, namely in the characterization of mechanical properties of new alloys used as base or cladding materials in this process. In this paper will be done initially an historical approach, followed by a description of the principles of the LASER cladding, a description of the applicability of the process and its advantages and limitations and the paper will end with a state of the art about the advances in new metallic alloys. So, this paper presents a review and the state of the art of the technological process and will be a contribution for the divulgation of this recent technique.

Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrated that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result obtained was compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions.

Acquisition of real-time hydraulic data is an essential component for flood forecasting. However, we frequently face difficulties in obtaining discharge data using classical contact methods during high magnitude floods and for systems experiencing rapid hydro-geomorphological adjustment. Therefore, we developed low-cost, non-contact sensors and platforms that are designed to overcome these difficulties. These advances enable flood flow properties to be monitored at multiple locations across a river catchment, at low-cost, and communicated in near real-time by using an image velocimetry method. This is an optics-based approach for stream flow measurement using commercially available near-infrared digital cameras to acquire video footage in full HD (30fps). Video footage is then subjected to optical flow tracking techniques based on cross-correlation, and feature-based tracking, enabling the displacement rates of detected features (for example natural foam, seeds, woody debris, and turbulent structures) to be computed. This manual provides step by step guidance to install an image-based gauging station. It contains the list of necessary components, the calibration process of a new camera and the assembly procedure of the system.

Human factors are the most relevant issues contributing to adverse events in obstetrics. Specific training of Crisis Resource Management (CRM) skills (i.e., problem solving and team management, resource allocation, awareness of environment, and dynamic decision-making) are now widespread and are often based on High Fidelity Simulation. In order to be used as a guideline in simulated scenarios, they need to be translated into specific and observable behavioral markers. To this purpose, we developed a set of observable behaviors related to the main elements of CRM in the delivery room. The observational tool was then adopted in a two-days seminar on obstetric hemorrhage where teams working in obstetric wards of six Italian hospitals took part to simulations. The tool was used as guide for the Io and as a peer-to-peer feedback. It was then rated for its usefulness in facilitating the reflection upon one’s own behavior, its ease of use, and its usefulness for the peer-to-peer feedback. The ratings were highly positive, around 4 in a 5-point scale. The CRM observational tool is therefore a useful, quick and easy solution to facilitate the debriefing, the peer-to-peer feedback and, most of all, the transfer of safe behavior from simulation to everyday practice.

The importance and near ubiquity of the Golden Ratio in disciplines like chemistry and biology is well known, but only recently has it come to light in areas pertaining to the Quantum domain. By using a modified tool-kit of hyper-complex numbers (known as Dimensional Gate Operators) and numerical analysis, we uncover a connection between hyper-dimensional objects, the Fibonacci sequence and that of quasiparticles and excitations. The results show that dimensionality increases in step with the Fibonacci sequence.

Stagnation is the transient state of a solar thermal system under high solar irradiation where the useful solar gain is zero. Both flat-plate collectors with selective absorber coatings and vacuum-tube collectors exhibit stagnation temperatures far above the saturation temperature of the glycol-based heat carriers within the range of typical system pressures. Therefore, stagnation is always associated with vaporization and propagation of vapor into the pipes of the solar circuit. It is therefore essential to design the system in such a way that vapor never reaches components that cannot withstand high temperatures. In this article, a thermal-hydraulic model based on the integral form of a two-phase mixture model and a drift-flux correlation is presented. The model is applicable to solar thermal flat-plate collectors with meander-shaped absorber tubes and selective absorber coatings. Experimental data from stagnation experiments on two systems, which are identical except for the optical properties of the absorber coating, allowed comparison with simulations carried out under the same boundary conditions. The absorber of one system features a conventional highly selective coating, while the absorber of the other system features a thermochromic coating, which exhibits a significantly lower stagnation temperature. Comparison of simulation results and experimental data show good conformity. This model is implemented into an open-source software tool called “THD” for the thermal-hydraulic dimensioning of solar systems. The latest version of THD, updated by the results of this article, enables planners to achieve cost-optimal design of solar thermal systems and to ensure failsafe operation by predicting the steam range under the initial and boundary conditions of worst-case scenarios.

This publication delves into the intricate world of human communication, extending beyond the realm of spoken and written language to explore the profound influence of non-verbal communication. Focusing on body language—comprising gestures, facial expressions, postures, and movements—it reveals the pivotal role it plays in conveying emotions, intentions, and psychological states. The rapidly evolving fields of neuroscience and cognitive science are investigating the neural mechanisms and cognitive processes that underpin the interpretation and utilization of these non-verbal cues. Notably, the amygdala's involvement in processing emotional facial expressions has provided a neurological foundation for our emotional understanding in non-verbal communication. Concurrently, cognitive psychology sheds light on how perception, attention, and memory influence our interpretation of non-verbal cues and communication strategies.In our modern, technologically advancing society characterized by global interconnectivity and cultural diversity, the significance of non-verbal communication, especially in digital and virtual contexts, is paramount. The transformation of non-verbal expression into digital symbols like emoticons and emojis raises questions regarding its ability to maintain authenticity and emotional understanding. This publication endeavors to comprehensively explore the fundamental role of body language and non-verbal communication in contemporary society. By integrating insights from psychology, neuroscience, social sciences, and digital technologies, it aims to elucidate the underlying mechanisms guiding non-verbal communication. Additionally, it delves into the implications of non-verbal communication across diverse domains, including interpersonal communication, the workplace, politics, advertising, and the virtual world.The research presented herein strives to offer a thorough understanding of interpersonal dynamics, relationships, and social behavior, with the goal of promoting the development of more effective, conscious, and ethically guided communication strategies. Ultimately, this analysis aspires to inspire further interdisciplinary research and reflection, addressing emerging challenges and fully leveraging the potential of non-verbal communication in modern society. This, in turn, guides our path towards a communication landscape that is more inclusive, authentic, and empathetic.

Magnetic nanoparticles are met across many biological species ranging from magnetosensitive bacteria, fishes, bees, bats, rats, birds, to humans. They can be both of biogenetic origin and due to environmental contamination, being either in paramagnetic or ferromagnetic state. The energy of such naturally occurring single-domain magnetic nanoparticles can reach up to 10-20 room k_BT in the magnetic field of the Earth, which naturally led to supposition that they can serve as sensory elements in various animals. This work explores within a stochastic modeling framework a fascinating hypothesis of magnetosensitive ion channels with magnetic nanoparticles serving as sensory elements, especially, how realistic it is given a highly dissipative viscoelastic interior of living cells and typical sizes of nanoparticles possibly involved.

Biomimicry in additive manufacturing often refers to topology optimization and the use of lattice structures, due to the organic shape of the topology-optimized designs, and the lattices often looking similar to many light-weight structures found in nature such as trabecular bone, wood, sponges, coral, to name a few. Real biomimetic design however involves the use of design principles taken in some way from natural systems. In this work we use a methodology whereby high resolution 3D analysis of a natural material with desirable properties is “reverse-engineered” and the design tested for the purpose. This allows more accurate replication of the desired properties, and adaption of the design parameters to the material used for production (which usually differs from the biological material). One such example is the impact-protective natural design of the glyptodont body armour. In this paper we report on the production of body armour models in metal (Ti4Al4V) and analyze the resulting mechanical properties, assessing their potential for impact protective applications. This is the first biomimetic study using metal additive manufacturing to date.

Breast cancer is the most common malignancies in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER, PR and HER2 expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether HDACi would be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enrich breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence based live cell non-invasive apoptosis detection sensor (IADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also be accompanied with chemotherapeutic agent such as doxorubicin to synergic drug sensitivity on TNBC cell (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in clinic.

Extracellular vesicles (EVs) represent a heterogeneous population of small vesicles, consisting of a phospholipidic bilayer surrounding a soluble interior cargo. Almost all cell types release EVs, thus they are naturally present in all body fluids. Among the several potential applications, EVs could be used as drug delivery vehicles in disease treatment, in immune therapy because of their immunomodulatory properties and in regenerative medicine. In addition to general markers, EVs are characterized by the presence of specific biomarkers (proteins, miRNAs) that allow the identification of their cell- or tissue-origin. For these features, they represent a potential powerful diagnostic tool to monitor state and progression of specific diseases. As regards, a large body of studies supports the idea that endothelial derived (EMPs) together with platelet-derived microparticles (PMPs) are deeply involved in the pathogenesis of diseases characterized by micro- and macrovascular damages, including diabetes. Existing literature suggests that the detection of circulating EMPs and PMPs and their specific miRNA profile may represent a very useful non-invasive signature to achieve informations about the onset of peculiar disease manifestations. In this Review, we discuss the possible utility of EVs in the early diagnosis of diabetes-associated microvascular complications, specifically related to kidney.

We apply principles of Gibbs phase plane chemistry to and across the entire ocean-atmospheric interface. Surface tension increments support a two dimensional, tangential pressure well known to determine rates of bulk gas, bubble, salt, spray and momentum transfer plus both sensible and latent heat fluxes. Hence it is worth asking whether tension mapping follows from current understanding of two dimensional composition. A history is provided dating back centuries and demonstrating that detrital organic macromolecules are central; subtle surfactant functional variation creates a microforcing field which dissipates turbulent energy at the sub-meter scale. Since we have just distributed major biopolymeric classes emitted as primary organic aerosol, further climate links can be established by considering full planar thermochemistry. Organic microlayer behaviors are reviewed with attention to confined, analog phase transitions among two dimensional “solid, liquid, (and) gaseous” states serving as elasticity indicators. We also discuss surfactant properties of general marine dissolved organic carbon, demonstrating that only proteins and lipids are capable of occupying significant local micro-area. The literature often suggests albumin and stearic acid as best proxies, and so we distribute their concentrations through multilevel global ecodynamic simulations. Consensus distributions are obtained in order to control adsorptive equilibria. Working from conservation of planar free energy, a parametric equation of state is devised relating excess coverage to the surface pressure-modulus. Constant settings for the proxy pair are drawn from laboratory study, and they successfully reproduce frequencies for surfactant solid-to-gas occurrence in ambient compression experiments. Functionally resolved organic measurements are rare and so we group them into super-ecological province tables showing that our bulk concentration estimates are reasonable. Outputs are then fed into a coverage-tension-elasticity code. Resulting contours traverse the critical range for piston velocity, bubble-spray and damping effects on either a regional or seasonal basis. There is also a possibility for widespread microlayer crystallization in polar seas. The concepts are a direct extension of our organic aerosol work, and the two approaches could be inserted into Earth System Models in tandem. Uncertainties in the logic are enumerated and include kinetic and thermochemical factors at multiple scales. But the problems are reducible through molecular modeling coupled to renewed laboratory and field study. Connections to marine colloids-gels, microlayer iron chelation, and linings of the ice channel network are discussed additionally.

Below T_CO=157 K the quasi-one-dimensional charge-transfer salt (TMTTF)_2SbF_6 undergoes a pronounced phase transition to a charge-ordered ground state. We have explored the non-linear and photoconductive behavior as a function of applied voltage, laser pulse energy and temperature. Besides a decay of the photoconductive signal in a double exponential fashion in the millisecond range, we discover current oscillations in the kHz range induced by the application of short laser pulses. While the resonance frequencies do not depend on voltage or laser intensity and vary only slightly with temperature, the amplitude changes linearly with the laser intensity and voltage. The findings are discussed and compared to comparable phenomena in other low-dimensional electron systems.

Medical institutions, where several patients are treated and medical workers engaged, are always exposed to secondary viral and bacterial infections. It is critical to prevent infection transmission by indirect as well as direct contact through air or splash. The infections of most diseases can be transmitted through the air. HEPA filters installed in air conditioning equipment are used to prevent infection transmission through air in medical institutions, but air circulation takes a long time in a large space. Virus and bacteria smaller than 0.3 μm cannot be removed by the HEPA filter; hence, those microbes remain alive throughout the air ventilation. A plasma sterilizer has the capability to provide environmental friendly sterilization by employing reactive oxide species and reactive nitrogen species at a low cost. We developed an excellent plasma sterilizer by using a non-thermal atmospheric-pressure biocompatible plasma (NBP). Ozone concentration in plasma sources has been derived by Kuhn et al. [1]. The diffusion coefficients inside (D₀) and outside (D₁) the plasma sterilizer have been calculated to be 0.0641 m² s^-1 and 0.717 m² s^-1, respectively. To sustain high O₃ concentrations over 121 ppm inside the plasma source and low O₃ concentrations below 0.05 ppm outside the sterilizer, it is necessary to keep O₃ concentrations at the exit of plasma sterilizer below 0.28 ppm. so that diffusion coefficient D₁ has been designed to be as large as 11 times of D₀.

A methodological similarity between Thomas Hobbes and Pëtr Kropotkin is the intention to spread a theoretical foundation to everyone, in the sense that they are willing to give to all the people a clear description of the reality and a subsequent political view. To do so, they use a scientific method, deductive (starting from empirical observations) in the case of Hobbes, inductive-deductive in the case of Kropotkin. Kropotkin underlines the educational value of the scientific method.In this work we want to highlight that, although they both start their argumentations from a materialist ontology, Hobbes and Kropotkin conjecture two completely different states of nature. Hobbes describes the state of nature through the two famous metaphors homo homini lupus (citing Plautus) and bellum omnium contra omnes, while Kropotkin introduced the theory of mutual aid. Both the theory of a state of war by Hobbes and the theory of mutual aid by Kropotkin have been revolutionary. Hobbes has been influenced by the scientific revolution initiated by Francis Bacon, one of his mentors, and Galileo Galilei, together with a criticism towards the ancient Greece philosophers, in particular Aristotle. Kropotkin has been influenced by the ground-breaking writings of Charles Darwin together with a very fruitful Russian scientific environment.We want to stress here that the disenchanted view of the human nature in Hobbes, a state of war due to the fact that everyone has rights on everything, helps him to legitimate sovereignty, while the positive view of human nature in Kropotkin, a spontaneous mutual aid among people in a community, helps him to legitimate anarchy. Therefore, the fascinating scientific methods of the two materialists Hobbes and Kropotkin to structure a solid political theory cannot neglect different views on human nature due to their historical contexts.

With the development of data science, more and more machine learning technologies have been designed to solve complicated and challenging real-world tasks containing a large volume of data. And many significant real-world datasets contain data in the form of networks or graphs. Graph Neural Networks is one of the powerful machine learning tools, which could provide a perfect solution to processing a large amount of non-Euclidean data. And because most bio information data in bioinformatics is in the non-Euclidean domain, Graph Neural Networks could then directly be applied to solve problems in bioinformatics. Much research has been done in the field of GNN, and there are also some surveys related to GNN and its applications. However, there has been little research focusing on GNN in bioinformatics, and we think in the future we could better utilize GNN in the field of biology, so we would like to write a literature review to help take a comprehensive look at GNN and their applications in the field of bioinformatics. In this paper, we would first introduce SOTA models in Graph Neural Networks, and second, introduce their applications in bio information. And then we would provide future directions of Graph Neural Networks in bioinformatics.

The popular motor drive systems with a single two-level voltage source inverter (VSI) have one main problem that is the occurrence of the common-mode voltage (CMV), which is an effect of the electromagnetic interference, shaft voltage, bearing currents, leakage current. These cause the high stress, increasung temperature and early mechanical failure in machine. To overcome this problem, the technology of the dual two-level VSI fed open-end three-phase ac loads is now available to eliminate the CMV at the ac/induction motor load with the 120-degree modulation technique for controlling each inverter. In this paper, the discontinuous space vector modulation (DSVM) schemes are proposed and applied for the dual two-level VSI fed open-end load. It is based on the 120-degree modulation technique by using only 12 active voltage vectors and the 10 zero voltage vectors from the total 64 voltage vectors along with the different five-segment swicthing sequence designs with centralizing pulse width modulation technqiue in order to not only cancel the CMV in the ac load, but also reduce the switching number/switching loss of the conversion system. Among the various DSVM schemes, their performances are compared in this paper, such as the number of the switching, the step and peak value of the CMV in each inverter, and the quality of the output waveform, etc. The details of the verfication and comparison are carried out by simulation using Matlab/Simulink software.

Past public health crises (e.g. tobacco, alcohol, opioids, cholera, HIV, lead, pollution, venereal disease, even COVID-19) have been met with interventions targeted both at the individual and all of society. While the healthcare community is very aware that the global pandemic of non-communicable diseases (NCD’s) has its origins in our Western ultraprocessed food diet, society has been slow to initiate any interventions other than public education, which has been ineffective, in part due to food industry interference. This article provides the rationale for such public health interventions, by compiling the evidence that added sugar, and by proxy the ultraprocessed food category, meets the four criteria set by the public health community as necessary and sufficient for regulation — addiction, toxicity, ubiquity, and externalities (how does your consumption affect me?). To its credit, some countries have recently heeded this science and have instituted sugar taxation policies to help ameliorate NCD’s within their borders. This article also supplies scientific counters to food industry talking points, in order to guide both scientists and policy makers in instituting further appropriate public health measures to quell this pandemic.

This paper studied the nonlinear vibrations of top tensioned cantilevered pipes conveying pressurized steady two-phase flow under thermal loading. The coupled axial and transverse governing partial differential equations of motion of the system were derived based on Hamilton’s mechanics with the centreline assumed to be extensible. Multiple scale perturbation method was used to resolve the governing equations, which resulted to an analytical approach for assessing the natural frequency, mode shape and the nonlinear coupled axial and transverse steady state response of the pipe. The analytical assessment reveals that at some frequencies the system is uncoupled, while at some frequencies a 1:2 coupling exists between the axial and the transverse frequencies of the pipe. Nonlinear frequencies versus the amplitude displacement of the cantilever pipe conveying two-phase flow at super critical mixture velocity for the uncoupled scenario exhibit a nonlinear hardening behaviour, an increment in the void fractions of the two-phase flow resulted to a reduction in the pipe’s transverse vibration frequencies and the coupled amplitude of the system. However, increasing the temperature difference, pressure and the presence of top tension were observed to increase the pipe’s transverse vibration frequencies without a significant change in the coupled amplitude of the system.

Efficiently targeted cancer therapy without causing detrimental side effects is necessary for alleviating patient care and improving survival rates. This paper presents observations of morphological changes in H1299 human lung cancer cells following W-band MMW irradiation (75 – 105 GHz) at a non-thermal power density of 0.2 mW/cm², investigated over 14 days of subsequent physiological incubation following exposure. Microscopic analyses of physical parameters measured indicate MMW irradiation induces significant morphological changes characteristic of apoptosis and senescence. The Immediate short-term responses translate into long-term effects, retained over the duration of the experiment(s); reminiscent of the phenomenon of Accelerated Cellular Senescence (ACS) achieving terminal tumorigenic cell growth. Further, results were observed to be treatment-specific in energy (dose) dependent manner and were achieved without the use of chemotherapeutic agents, ionizing radiation or thermal ablation employed in conventional methods; thereby overcoming associated side effects. Adaptation of the experimental parameters of this study for clinical oncology concomitant with current developmental trends of non-invasive medical endoscopy alleviates MMW therapy as an effective treatment procedure for human non-small cell lung cancer (NSCLC).

A review of influence of drag-reducing agents on curved pipe flows is presented in this work. In addition, this review outlined proposed mechanism, friction factor and fluid flux models for drag-reducing agents in curved pipe flows. Our finding reveals that drag reduction by additives in curved pipes is quite significant but generally lower than the corresponding drag reduction in straight pipes. It decreases with increase in curvature ratio and more pronounced in the transition and turbulent flow regimes. Drag reduction strongly depends on the polymers and surfactants’ concentrations as well as the bubble fraction of micro-bubbles. It is also reported that drag reduction in curved pipes depends on temperature and existence of dissolved salts in the fluids. Maximum drag reduction asymptote differed between straight and curved pipes and between polymer and surfactant. No definite conclusion could be drawn as regards drag reduction for two-phase flow in curved pipes due to the limited studies in this area. Many questions such as the mechanism of drag reduction in curved pipes and how drag-reducing agents interact with secondary flows still remained unanswered. Hence, some research gaps have been identified with recommendations for areas of future researches.

Power disaggregation aims at determining the appliance-by-appliance electricity consumption leveraging upon a single meter only, which measures the entire power demand. Data-driven procedures based on Factorial Hidden Markov Models have been proven remarkable results on energy disaggregation. Nevertheless, those procedures have various weaknesses: there is a scalability problem as the number of devices to observe raises and the algorithmic complexity of the inference step is severe. DNN architectures, such as Convolutional Neural Networks, have demonstrated to be a viable solution to deal with FHMMs shortcomings. Nonetheless, there are two significant limitations: a complicated and time-consuming training system based on back-propagation has to be employed to estimates the neural architecture parameters, and large amounts of training data covering as many operation conditions as possible need to be collected to attain top performances. In this work, we aim to overcome those limitations by leveraging upon the unique and useful characteristics of the extreme learning machine technique, which is based on a collection of randomly chosen hidden units and analytically defined output weights. Experiment evaluation has been conducted using the UK-DALE corpus. We find that the suggested approach achieves similar performances to recently proposed ANN-based methods and outperforms FHMMs. Besides, our solution generalises well to unseen houses.

Depending on human body conditions and environmental conditions, it is sometimes difficult to conduct subject experiments. In such cases, it is effective to use a thermal manikin. There are few studies that investigate the effect of the non-uniform and asymmetric outdoor thermal environment on the mean skin temperature. The purpose of this study is to clarify the influence of the non-uniform and asymmetric thermal radiation of short-wavelength solar radiation in an outdoor environment on the calculation of the mean skin temperature. The skin temperature of the front of the coronal surface, which was facing the sun and where the body received direct short-wavelength solar radiation, and the skin temperature of the rear of the coronal surface, which was in the shadow and did not receive direct short-wavelength solar radiation were respectively measured. The feet, upper arm, forearm, hand and lower leg, which are susceptible to short-wavelength solar radiation in a standing posture, had a noticeable difference in skin temperature between sites in the sun and in shade. The mean skin temperature of sites facing the sun was significantly higher than the mean skin temperature of those in the shade.

The Gilles de la Tourette syndrome (GTS) and Non-Coeliac Gluten Sensitivity (NCGS) may be associated. We analyse the efficacy of a gluten-free diet (GFD) in 29 patients with GTS (23 children; 6 adults) in a prospective pilot study. All of them followed a GFD for one year. The YGTSS, Y-BOCS/CY-BOCS and GTS-QOL questionnaires were compared before and after the GFD. 74% of children and 50% of adults were males, not significant (NS). At the beginning of the study, 69% of children and 100% of adults had associated OCD (NS). At baseline, the YGTSS scores were 55.0 ± 17.5 (children) and 55.8 ± 19.8 (adults) (NS), the Y-BOCS/CY-BOCS scores were 15.3 (SD = 12.3) (children) and 26.8 (9.2) (adults) (p = 0.043), and the GTS-QOL scores were 42.8 ± 18.5 (children) and 64 ± 7.9 (adults) (p = 0.000). NCGS was frequent in both groups, with headaches reported by 47.0% of children and 83.6% of adults (p = 0.001). After one year on a GFD there was a marked reduction in measures of tics (YGTSS) (p = 0.001), and the intensity and frequency of OCD (Y-BOCS/CY-BOCS) (p = 0.001), along with improved QOL (p = 0.001) in children and adults. In conclusion, a GFD maintained for one year in GTS patients led to a marked reduction in tics and OCD both in children and adults.

The growth of regularly generated data from many financial activities has significant implications for every corner of financial modeling. This study has investigated the utilization of these continuous growing data by a means of an automated process. The automated process can be developed by using Machine learning based techniques that analyze the data and gain experience from the underlying data. Different important domains of financial fields such as Credit card fraud detection, bankruptcy detection, loan default prediction, investment prediction, marketing and many other financial models can be modeled by implementing machine learning models. Among several machine learning based techniques, the use of parametric and non-parametric based methods are approached by this research. Two parametric models namely Logistic Regression, Gaussian Naive Bayes models and two non-parametric methods such as Random Forest, Decision Tree are implemented in this paper. All the mentioned models are developed and implemented in the field of Credit card fraud detection, bankruptcy detection, loan default prediction. In each of the aforementioned cases, the comparative study among the classification techniques is drawn and the best model is identified. The performance of each classifier on each considered domain is evaluated by various performance metrics such as accuracy, recall, precision, F1-score and mean squared error. In the credit card fraud detection model the decision tree classifier performs the best with an accuracy of 99.1% and, in the loan default prediction and bankruptcy detection model, the random forest classifier gives the best accuracy of 97% and 96.84% respectively.

Predicting the growth response of seedlings from the environmental responses of photosynthesis and metabolism may be improved by considering the dynamics of non-structural carbohydrate, NSC, over a diurnal cycle. Attenuation of growth metabolism when NSC content is low could explain why some NSC is conserved through the night. A dynamic model, incorporating diurnal variation in NSC, was developed to simulate growth of seedlings hour-by-hour. I compared predictions of this model to published growth and NSC data for seedlings that varied according to temperature, light, day length, or CO₂. Prolonged-darkness experiments showed a temperature dependent upper limit on the respiration capacity. Respiration was attenuated as NSC was depleted. Furthermore, when NSC was high at dawn, inhibition of photosynthesis could attenuate the accumulation of NSC under low temperature, or high light, or high CO₂. These concepts were used to simulate plant metabolism and growth rates and diurnal variation of NSC in tomato seedlings under two light levels and various temperatures. Comparison of other results using the same model parameters showed the dynamic model could predict results for starch and starch-less plants, and when growth was affected by CO₂ enrichment and day length.

We introduce poly-symplectic extension of Souriau Lie groups Thermodynamics based on higher-order model of statistical physics introduced by R.S. Ingarden. This extended model could be used for small data analytics and Machine Learning on Lie groups. Souriau Geometric Theory of Heat is well adapted to describe density of probability (Maximum Entropy Gibbs density) of data living on groups or on homogeneous manifolds. For Small Data Analytics (Rarified Gases , sparse statistical survey,…), density of maximum entropy should consider Higher Order Moments constraints (Gibbs density is not only defined by first moment but fluctuations request 2nd order and higher moments) as introduced by R.S. Ingarden. We use Poly-sympletic model introduced by Christian Günther, replacing the symplectic form by a vector-valued form. The poly-symplectic approach generalizes the Noether theorem, the existence of momentum mappings, the Lie algebra structure of the space of currents, the (non-)equivariant cohomology and the classification of G-homogeneous systems. The formalism is covariant, i.e. no special coordinates or coordinate systems on the parameter space are used to construct the Hamiltonian equations. We underline the contextures of these models, and the process to build these generic structures.

Quantum computing arrives. Preceded by Mādhava of Sangamagrāma and other Hindu mathematicians, around 1,500 CE, and our previous work, we show at least 4 quantum properties that are indeed universal in some number systems; here we use them to enable quantum computing. Using the sets B={0,1}, B^n, N, Z, Q, and Q*, one has +4 quantum properties that one can trust, as archetypes of easy communication to friends and foes, to ignoranti or cognoscenti, and for quantum consciousness. Therefore, this work applies to computer calculations, apps in cell phones, algebra, atoms, mathematics, physics, and the human mind.

Real estate market analysis and place-based decision-making can both benefit from understanding house price development. Although considerable amounts of interest have been devoted to housing price modelling, the assessment of house price fluctuation still requires further comparing studies. Housing price prediction is challenging as contributing factors are quite dynamic and subject to a variety of regulating elements. The future understanding of the housing market trends not only provides sufficient customers’ investment trust potential but also enables the financial support to progress more realistic in advance. In this study, a comprehensive data-informed framework is developed to investigate and anticipate real estate house prices using historical data by combining explanatory features. We examined about 500 houses in the Boston area as a case study and discussed how the increase in housing prices could vary by each of the contributing components. Fourteen Machine Learning (ML) regressors imply to the dataset and lead to a comparative study of the accuracy of all the models. ML-based regressors forecast real estate home prices as a function of thirteen influencing factors. The most informative features were also selected by conducting the Permutation Feature Importance technique on all the features The study provides a comprehensive tool for evaluating the robustness and efficiency of ML models for housing price predictions. The results highlighted Random Forest as the best model has an R2 equals to 0.88 and Voting Regressor as the second highest rated model has R2 equals to 0.87. Results of multivariate exploratory data analysis also implied that the average number of rooms and percentage of the lower status of the population have the most significant impact on the price range predictions.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

In this paper, a two-stage stochastic programming modelling is proposed to design a multi-period, multistage, and single-commodity integrated forward/reverse logistics network design problem under uncertainty. The problem involves both strategic and tactical decision levels. The first stage deals with strategic decisions, which are the number, capacity, and location of forward and reverse facilities. At the second stage tactical decisions such as base stock level as an inventory policy is determined. The generic introduced model consists of suppliers, manufactures, and distribution centers in forward logistic and collection centers, remanufactures, redistribution, and disposal centers in reverse logistic. The strength of proposed model is its applicability to various industries. The problem is formulated as a mixed-integer linear programming model and is solved by using Benders’ Decomposition (BD) approach. In order to accelerate the Benders’ decomposition, a number of valid inequalities are added to the master problem. The proposed accelerated BD is evaluated through small-, medium-, and large-sized test problems. Numerical results reveal that proposed solution algorithm increases convergence of lower bound and upper bound of BD and is able to reach an acceptable optimality gap in a convenient CPU time.

This paper considers a non-mixture cure model for right censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluate the performance of the method. Comparing with Weibull and exponentiated exponential distributions, the non-mixture Fréchet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.

Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

In this paper, a 3 DOF gyrscope position control have been designed and controlled using optimal control theory. An input torque has been given to the first axis and the angular position of the second axis have been analyzed while the third axis are kept free from rotation. The system mathematical model is controllable and observable. Linear Quadratic Integral (LQI) and Linear Quadratic State Feedback Regulator (LQRY) controllers have been used to improve the performance of the system. Comparison of the system with the proposed controllers for tracking a desired step and random angular position have been done using Matlab/Simulink Toolbox and a promising results has been analyzed.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver–pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver–pickup, also termed as transmitter-receiver (T-R) sensor is designed with a small mean radius of 1 mm. Besides, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution , with a limit of 0.2 μm and selected as 0.25 mm. Experiments have been out on the voltage imaging of an aluminium sheet with 7 machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10 % for tilt angles up to 60 degrees.

We present a generalized state-space model formulation particularly motivated by an online scheduling perspective. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings.