In this study, we considered the structural stability, electronic properties, and phonon dispersion of the cubic (c-ZrO₂), tetragonal (t-ZrO₂), and monoclinic (m-ZrO₂) phases of ZrO₂. We found that the monoclinic phase of zirconium dioxide is the most stable among the three phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic properties. The smallest negative modes were found for m-ZrO₂. Our analysis of the electronic properties showed that during the m–t phase transformation of ZrO₂, the Fermi level first shifts by 0.125 eV toward higher energies and then decreases by 0.08 eV in the t–c cross-section. The band gaps for c-ZrO₂, t-ZrO₂, and m-ZrO₂ are 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35, and 16.15 mol. %Y₂O₃ onto the m-ZrO₂ structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO₂ and an increase in its defectiveness. A doping-induced and concentration-dependent phase transition in ZrO₂ under the influence of Y₂O₃ was discovered, due to which the position of the Fermi level changes and the energy gap decreases. It has been established that, not only for pure systems but including those doped with Y₂O₃, the main contribution to the formation of the conduction band is made by the p-states of electrons. The t-ZrO₂ (101) and t-YSZ (101) surface models were selected as optimal surfaces for water adsorption based on a comparison of their surface energies. An analysis of the mechanism of water adsorption on the surface of t-ZrO₂ (101) and t-YSZ (101) showed that H₂O on unstabilized t-ZrO₂ (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of - 0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom. The results show that ab initio approaches are able to describe the mechanism of doping-induced phase transitions in (ZrO₂+Y₂O₃)-like systems, based on which it can be assumed that DFT calculations can also flawlessly evaluate other physical and chemical properties of YSZ, which have not yet been studied quantum chemical research. The obtained results complement the database of research works carried out in the field of the application of biocompatible zirconium dioxide crystals and ceramics in green energy generation and can be used in designing humidity-to-electricity converters and creating solid oxide fuel cells based on ZrO₂.

In this study, we considered the structural stability, electronic properties, and phonon dispersion of the cubic (c-ZrO₂), tetragonal (t-ZrO₂), and monoclinic (m-ZrO₂) phases of ZrO₂. We found that the monoclinic phase of zirconium dioxide is the most stable among the three phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic properties. The smallest negative modes were found for m-ZrO₂. Our analysis of the electronic properties showed that during the m–t phase transformation of ZrO₂, the Fermi level first shifts by 0.125 eV toward higher energies and then decreases by 0.08 eV in the t–c cross-section. The band gaps for c-ZrO₂, t-ZrO₂, and m-ZrO₂ are 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35, and 16.15 mol. %Y₂O₃ onto the m-ZrO₂ structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO₂ and an increase in its defectiveness. In this case, the position of the Fermi level changes abruptly, and the energy gap decreases. It has been established that, not only for pure systems but including those doped with Y₂O₃, the main contribution to the formation of the conduction band is made by the p-states of electrons. The t-ZrO₂ (101) and t-YSZ (101) surface models were selected as optimal surfaces for water adsorption based on a comparison of their surface energies. An analysis of the mechanism of water adsorption on the surface of t-ZrO₂ (101) and t-YSZ (101) showed that H₂O on unstabilized t-ZrO₂ (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of - 0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom. The obtained results complement the database of research works carried out in the field of the application of biocompatible zirconium dioxide crystals and ceramics in green energy generation and can be used in designing humidity-to-electricity converters and creating solid oxide fuel cells based on ZrO₂.

Silicon-based photodetectors, as low-cost and environmentally friendly optical sensors, are attractive. Also, their compatibility with complementary metal-oxide-semiconductor (CMOS) technology is advantageous for the development of silicon photonics systems. However, extending optical responsivity of silicon-based photodetectors to the mid-infrared (mid-IR) wavelength range remains challenging. In developing mid-IR infrared Schottky detectors, nanoscale metals are critical. Nonetheless, one key factor is the Fermi level pinning effect at the metal/silicon interface and the presence of metal-induced gap states (MIGS). Here, we demonstrate the utilization of the passivated surface layer on semiconductor materials as an insulating material in metal-insulator-semiconductor (MIS) contacts to mitigate the Fermi level pinning effect. The removal of Fermi level pinning effectively reduces the Schottky barrier height by 12.5% to 16%. The demonstrated devices exhibit a high responsivity of up to 234 μA/W at a wavelength of 2 μm, 48.2 μA/W at 3 μm, and 1.75 μA/W at 6 μm. The corresponding detectivities at 2 and 3 μm are 1.17×10^8 cm Hz^1/2 W^-1 and 2.41×10^7 cm Hz^1/2 W^-1, respectively. The expanded sensing wavelength range contributes to the application development of future silicon photonics integration platforms.

An equation for the Fermi level of impurity isotropic semiconductors is considered when the bottom of the conduction band and the top of the valence band are at the center of the first Brillouin zone. The energy of charge carriers in the valence and conduction bands of semiconductors is considered taking into account the real positions of the top of the valence band and the bottom of the conduction band in the first Brillouin zone. A universal equation for determining the Fermi levels of impurity isotropic semiconductors is presented.

Laser Photoacoustic Spectrometers (LPAS), which provide photoacoustic spectra for detecting food frauds or adulteration, and fluorescence-based systems for recognition of contamination by heavy metal ions in water are two important families of sensors for health and environmental purposes. Both sensor families require one or more low-frequency Lock-In Amplifiers (LIAs) to extract the signal of interest from background noise. In the cited applications, the required LIA frequency is quite low (up to 1kHz), and this leads to a simplification of the hardware with consequent good results in portability, economy, reduced size, weight and low-cost characteristics. The present system, called ENEA DSP Box Due, is based on a very inexpensive microcontroller proto-board and can replace four commercial LIAs, resulting in significant savings in both cost and space. Furthermore, it incorporates a dual-channel oscilloscope and a sinusoidal function generator. This article outlines the architecture of the ENEA DSP Box Due, its electrical characterization and its applications within a project concerning laser techniques for food and water safety.

The study aimed to analyze thoracic and lumbar erector spinae muscle activations during 3D elongation exercises in individuals with adolescent idiopathic scoliosis (AIS). Participants included 24 adolescents, meeting specific criteria such as a Cobb angle between 10° and 20°, and not having undergone surgical or brace treatments. EMG data were collected to evaluate muscle activations. The study found no significant interaction between exercise type and the side of the curve, but a significant main effect of exercise type on muscle activation, irrespective of Cobb angle. Different exercise types significantly affected muscle activity, with the highest activations in the TheraBand exercise, followed by manual and without equipment conditions. This suggests that exercise type significantly impacts muscle engagement in AIS patients, providing valuable insights for targeted exercise program design. The study, however, focused on short-term muscle activation, not long-term Cobb angle progression, pointing to the need for further research in this area.

In a recent paper, we calculate spectral energy distributions (SEDs) for 1425 Fermi blazars, classifications of low synchrotron peak sources (LSPs) if log $\nu_{\rm p} (\rm Hz) \leq $ 14.0, intermediate synchrotron peak sources (ISPs) if $14.0 < \,\log\, \nu_{\rm p} (\rm Hz) \leq 15.3 $, and high synchrotron peak sources (HSPs) if $ \log\, \nu_{\rm p} (\rm Hz) > 15.3$ are made based on 999 logarithms of synchrotron peak frequencies with known redshift, and we obtain an empirical relation to estimate the synchrotron peak frequency, $\nu_{\rm p}^{\rm Eq.}$ from effective spectral indexes $\alpha_{ox}\, {\rm and}\, \alpha_{ro}$ as $\log \nu_{\rm p}^{\rm Eq.} = 16+4.238X $ if $X < 0$, and $\log \nu_{\rm p}^{\rm Eq.} = 16+4.005Y $ if $X > 0$, where $X = 1.0 - 1.262 \alpha_{ro} - 0.623 \alpha_{ox}$, and $Y = 1.0 + 0.034 \alpha_{ro} - 0.978 \alpha_{ox}$ \cite{Fan16}. In the present work, we investigate the correlation between the peak frequency and the radio to X-ray spectral index, that between peak luminosity (integrated luminosity) and $\gamma$-ray/optical luminosity, and that between peak luminosity and integrated luminosity. Some discussions are presented.

In this work, we'll present the power spectra density, auto-correlation function, dentrended fluctuation analysis and multifractal spectrum are performed to the daily light curves of Blazars monitored by Fermi LAT. Some signs of power law are found.

The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness in several settings. The EU's regulatory framework advise for deploying one air quality monitoring unit per roughly 170,000 people or 15 square kilometers which is insufficient for capturing high spatio-temporal variance in complex urban scenarios. Often these settings are characterized by distributed emissions in small roads subjected to intense cars traffic, house heating driven emissions and frequently subjected to canyon effects. The Air Heritage project in Portici, funded by the EU's Urban Innovative Actions (UIA) program, addressed these challenges by integrating low-cost sensors with traditional monitoring systems and engaging the community in pervasive measurement strategies. The project highlights the importance of individualized sensor calibration and frequent recalibrations to maintain accuracy. It also showcases the benefits of citizen science approaches, IoT infrastructures, AI components, and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements. This paper reports on the lessons learned and experiences from the Air Heritage project, aiming to guide future implementations in similar contexts. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, public authorities, and citizens, about effective strategies for deploying and utilizing LCAQMS to enhance air quality monitoring and public awareness.

Blazars show rapid and high amplitude variability. In this work , Fermi daily light curve of 130 sources are analyzed, distribution of daily variability are compared with each other by using Kolmogorov-Smirnov (K-S) test. results show: 1)Some pairs of the distributions are similar; 2) In most cases, the distributions are not Gaussian.

The work carried out first-principles calculations within the framework of density functional theory to study the structural stability of the CsSnI₃ compound and the influence of phase transitions on their electronic and optical properties. Using the GGA and SCAN functionals, the relaxed structures of the CsSnI₃ phases were obtained and their geometric characteristics were assessed. Using the Phonopy code based on VASP, calculations of phonon and thermodynamic properties were performed, and the temperatures of phase transitions of CsSnI₃ were determined. The temperature dependences of the thermodynamic parameters α-, β-, γ- and δ-phases of CsSnI₃ were analyzed. The trends in free energy, entropy, enthalpy, heat of formation energy and heat capacity were justified in terms of the pattern of changes in the total energy of the four phases of CsSnI₃ from VASP calculations. It is shown that at 0 K the non-perovskite structure of the CsSnI₃ compound (δ-CsSnI₃) is the most stable (followed by γ-CsSnI₃), and the tetragonal phase (β) is quite unstable, having the highest energy among the perovskite phases. It was revealed that at temperatures above 450 K the tetragonal phase becomes stable, and when the temperature drops, it transforms into the cubic phase (α-CsSnI₃). The phase transition between the β and γ phase of perovskite occurs in the range of 300-320 K, and at 320 K a black-yellow transformation of CsSnI₃ occurs in which the cubic phase (black perovskite) undergoes a phase transition to a non-perovskite conformation (yellow phase). The presence of temperature phase transitions between two orthorhombic phases of CsSnI₃ at 360 K was discovered, although direct transitions of the α⟷γ and γ⟷δ types have not yet been reported in any experiment, except for γ→δ transitions under the influence of moisture. Based on well-relaxed structures (from the SCAN calculations), the band gap widths for four CsSnI₃ phases were calculated and compared with experimental measurements. Electronic properties and Fermi level shifts as a result of phase transformations of CsSnI₃ were assessed using the HSE06 functional and machine learning prediction. The values of the complex dielectric constant and the refractive index of all phases of the CsSnI₃ were determined.

Two distinct measures of information, connected respectively to the amplitude and phase of the wave function of a particle, are proposed. There are relations between the time derivatives of these two measures and their gradients on the configuration space, which are equivalent to the wave equation. The information related to the amplitude measures the strength of the potential coupling of the particle (which is itself aspatial) with each volume of its configuration space, i.e. its tendency to participate in an interaction localized in a region of ordinary physical space corresponding to that volume. The information connected to the phase is that required to obtain the time evolution of the particle as a persistent entity starting from a random succession of bits. It can be considered as the information provided by conservation principles. The meaning of the so-called "quantum potential" in this context is briefly discussed.

The superconductivity of CaC6 as a function of pressure and of abundant Ca isotopes is revisited using DFT calculations on a 2c – double hexagonal superlattice. The introduction of superlattices is motivated by previous synchrotron absorption and Raman spectroscopy results on other superconductors that show evidence of superlattice vibrations at low (THz) frequencies. A 2c superlattice for CaC6 is illustrative of atomic orbital symmetry and periodicity, including bonding and antibonding s-orbital character implied by cosine modulated electronic bands. Inspection of the cosine band reveals that the cosine function has a small (meV) energy difference between bonding and antibonding regions relative to a midpoint non-bonding energy. Fermi surface nesting is apparent in an appropriately folded Fermi surface using a superlattice construct. Nesting relationships identify phonon vectors for conservation of energy and for phase coherency between coupled electrons at opposite sides of the Fermi surface. Detailed analysis of this Fermi surface nesting provides accurate estimates of the superconducting gaps for CaC6 with change in applied pressure. Recognition of superlattices within a rhombohedral or hexagonal representation provides consistent mechanistic insight on superconductivity and electron−phonon coupling in CaC6.

A typical halogen-free flame-retardant (HFFR) formulation for electric cables may contain polymers, various additives, and fire-retardant fillers. In this study, composites are prepared by mixing natural magnesium hydroxide (n-MDH) with linear low-density polyethylene (LLDPE) and a few types of ethylene-octene copolymers (C₈-POE). Depending on the content of LLDPE and C₈-POE, we obtained composites with different crystallinity that affected the final mechanical properties. The nucleation effect of the n-MDH and the variations in crystallinity caused by the blending of C₈-POE/LLDPE/n-MDH were investigated. In the C₈-POE/LLDPE blend, we found a decrease in the crystallization temperature of LLPDE compared to pure LLDPE and an increase in the crystallization temperature of C₈-POE compared to pure C₈-POE. On the contrary, the addition of n-MDH led to an increase in the crystallization temperature of LLDPE. As expected, the increase in the crystallinity of the polyolefin matrix of composites led to higher elastic modulus, higher tensile strength, and lower elongation at break. Overall, these results show how to obtain the required mechanical features for halogen-free flame-retardant compounds for electric cable applications depending on the quantities of the two miscible components in the final blend.

To understand the mystery of final unification, in our earlier publications, we proposed two bold concepts: 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions. 2) There exists a strong elementary charge in such a way that its squared ratio with normal elementary charge is close to reciprocal of the strong coupling constant. In this paper we propose that, can be considered as a compound physical constant associated with proton mass, electron mass and the three atomic gravitational constants. With these ideas, an attempt is made to understand nuclear stability and binding energy. In this new approach, nuclear binding energy can be fitted with four simple terms having one unique energy coefficient with a formula, where is an estimated mean stable mass number. With this new approach, Newtonian gravitational constant can be estimated in a verifiable approach with a model relation of the form, where is the Fine structure constant. Estimated and is 62 ppm higher than the CODATA recommended It needs further investigation. Proceeding further, an attempt is made to fit the recommended quark masses.

Generative Adversarial Networks (GANs) are powerful models for generative tasks but face significant challenges such as instability, mode collapse, and inefficient convergence. This paper introduces a theoretical framework leveraging Fermi-Dirac statistics, Ruppeiner geometry, phase transition dynamics, and graph theory to address these issues. The proposed theorems provide a robust mathematical foundation for enhancing GAN stability, diversity, and convergence. Experimental validation on the MNIST dataset demonstrates that the application of these theorems results in improved Inception Scores, reduced Fr´echet Inception Distances, and stable training dynamics, as indicated by Ruppeiner curvature analysis. The findings suggest that these theoretical insights offer a comprehensive solution to the persistent challenges in GAN training, paving the way for more reliable and effective generative models.

Negative temperature coefficient (NTC) materials are usually based on ceramic semiconductors and electrons are involved in their transport mechanism. A new type of NTC material, adequate for alternating current (AC) applications, is represented by zeolites. Indeed, zeolites are single-charge carrier ionic conductors with a temperature-dependent electrical conductivity. In particular, electrical transport in zeolites is due to the monovalent charge-balancing cations, like K⁺, capable of hopping between negatively charged sites in the aluminosilicate framework. Owing to the highly non-linear electrical behavior of the traditional electronic NTC materials, the possibility to have alternative types of materials, showing linearity in the electrical behavior, is very desirable. Among different zeolites, the natural clinoptilolite has been selected for investigating the NTC behavior since it is characterized by high zeolite content, convenient Si/Al atomic ratio, good mechanical strength, due to its compact microstructure, and low toxicity. Clinoptilolite has shown a rapid and quite reversible impedance change under heating, characterized by a linear dependence on temperature. X-ray diffraction (XRD) has been used to identify the natural zeolite, to establish all types of crystalline phases present in the mineral, and to investigate the thermal stability of these phases up to 150°C. X-ray photoelectron spectroscopy (XPS) analysis has been used for the chemical characterization of the natural clinoptilolite sample, providing important information on the cationic content and framework composition. In addition, since electrical transport takes place in the zeolite free-volume, a Brunauer–Emmett–Teller (BET) analysis of the mineral has been also performed.

CrHZSM-5 was placed in an electric field with appropriate strength in a quartz packed bed reactor with CO2 as oxidant to analyze its catalytic activity. Olefin yield increases with decrease in band gap since lattice oxygen mobility increases by reducing band gap. Fermi level change at the catalyst surface affects the catalytic activity. One way to change Fermi level is use electric field. In high voltage electric field, energy band was curved, bending of the energy band promoted the activity and Fermi level position is increasing. The CCD experiments were carried out with Design-Expert 7.3 software to determine the interaction between four operating variables, namely: temperature, electrical current, gap distance and metal loading. The levels of the independent variables were: temperature (550-700 °C), electrical current (0-12 mA), gap distance (6-14 mm), metal loading (0.5-7.5 %wt.). The conversion of LPG (Liquefied petroleum gas) was greatly increased by weak and effective application of an electric field to the catalyst bed. The obtained results indicated that the maximum yield value (46.94%) can be achieved under 673.66 °C, input electrical current of 11.01 mA, gap distance of 6.55 mm and metal loading of 3.98 wt.%.

In the field of Natural Language Processing (NLP), Large Language Models (LLMs) have shown great potential in document-level event extraction tasks, but existing methods face challenges in the design of prompts. To address this issue, we propose an optimization strategy called "Definition-driven Document-level Event Extraction (DDEE)." By adjusting the length of the prompt and enhancing the clarity of heuristics, we have significantly improved the event extraction performance of LLMs. We used data balancing techniques to solve the long-tail effect problem, enhancing the model's generalization ability for event types. At the same time, we refined the prompt to ensure it is both concise and comprehensive, adapting to the sensitivity of LLMs to the style of prompts. In addition, the introduction of structured heuristic methods and strict limiting conditions has improved the precision of event and argument role extraction. These strategies not only solve the prompt engineering problems of LLMs in document-level event extraction but also promote the development of event extraction technology, providing new research perspectives for other tasks in the NLP field.

We investigate the tunneling of quasiparticles through a potential barrier of finite height and width, in a system with a band structure consisting of a quadratic band crossing point (QBCP). We compute the results of the transmission coefficient at various incident angles, and also the conductivity and the Fano factor. We discuss the distinguishing signatures of these transport properties in comparison with other semimetals, as well as electrons in normal metals.

We calculate the sound velocity and the damping rate of the collective excitations of a 2D fermionic superfluid in a non-perturbative manner. Specifically, we focus on the Anderson-Bogoliubov excitations in the BEC-BCS crossover regime, as these modes have a soundlike dispersion at low momenta. The calculation is performed within the path integral formalism and the Gaussian pair fluctuation approximation. From the action functional, we obtain the propagator of the collective excitations and determine their dispersion relation by locating the poles of this propagator. We find that there is only one kind of collective excitation, which is stable at $T=0$ and has a sound velocity of $v_{F}/\sqrt{2}$ for all binding energies, i.e. throughout the BEC-BCS crossover. As the temperature is raised, the sound velocity decreases and the damping rate shows a non-monotonous behavior: after an initial increase, close to the critical temperature $T_{C}$ the damping rate decreases again. In general, higher binding energies provide higher damping rates. Finally, we calculate the response functions and propose that they can be used as another way to determine the sound velocity.

The polarised emission from AGN jets carries information about the physical conditions at the emitting plasma elements while its temporal evolution probes the physical processes that introduce variability and dynamically modify the local conditions. Here we present the analysis of multi-frequency radio linear and circular polarisation datasets with the aim to exactly quantify the conditions in blazar jets. Our analysis includes both the careful treatment of observational datasets and numerical modelling for the reproduction of synthetic polarisation curves that can be compared to the observed ones. In our approach the variability is attributed to traveling shocks. The emission from the cells of our jet model is computed with radiative transfer of all Stokes parameters. The model also accounts for Faraday effects which map the low-energy particle populations. We present two extreme cases in terms of the significance of Faraday conversion in the production of circular polarisation. As we show, in both regimes the model gives realistic reproduction of the observed emission.

ACL instability poses a significant challenge in traumatology and orthopedic medicine, often requiring accurate diagnosis for appropriate treatment. While the pivot-shift test offers a crucial means of assessment, its reliance on subjective interpretation underscores the need for supplementary imaging studies. This study aims to address this limitation by developing a Bayesian classification algorithm tailored for integration into a mobile application. Using the built-in inertial sensors of smartphones, this new approach aims to dynamically evaluate rotational stability during knee examinations. Orthopedic specialists conducted knee evaluations on 52 subjects, with subsequent analysis revealing interesting insights. Intraobserver and interobserver analyses, as measured by ICC, demonstrated strong agreement both in terms of timing between maneuvers (ICC = 0.94) and signal amplitude (ICC = 0.71-0.66). Notably, the Bayesian algorithm successfully classified 95% of joint hypermobility cases, with an additional 7 cases of hyperlaxity identified by the Pivot-Shift Meter (PSM). These findings highlight the practicality and effectiveness of implementing a Bayesian classification algorithm within a mobile application for assessing and categorizing signals captured by smartphone inertial sensors during the pivot-shift test.

Machine Learning deals with creating algorithms capable of learning from the provided data. These systems have a wide range of applications and can also be a valuable tool for scientific research which in recent years has been focused on finding new diagnostic techniques for particle accelerator beams. In this context SPARC_LAB is positioned, a facility located at the Frascati National Laboratories of INFN, where the progress of beam diagnostics is one of the main developments of the entire project. With this in mind, you aim to present the design of two neural networks aimed at predicting the spot size of the electron beam of the plasma-based accelerator at SPARC_LAB, which powers an undulator for the generation of x-ray Free Electron Laser (XFEL). Data-driven algorithms use two different data preprocessing techniques, namely autoencoder neural network and PCA. With both approaches, the predicted measurements can be obtained with an acceptable margin of error and most importantly without activating the accelerator, thus saving time, even compared to a simulator that can produce the same result but much more slowly. The goal is to lay the groundwork for creating a digital twin of linac and conducting virtualized diagnostics using an innovative approach.

In the realm of metal steel and iron manufacturing, there is a constant drive to optimize production efficiency and enhance the quality of the final products. This abstract explores a paradigm shift in this industry through the utilization of Computational Fluid Dynamics (CFD) as a powerful tool for achieving these goals .The study focuses on various critical aspects of the manufacturing process. Firstly, it delves into three-phase processes such as slag and gas entrainment in liquid steel, which have a significant impact on the overall product quality. Understanding and optimizing these processes is crucial to ensure the desired chemical composition and physical properties of the final metal.The abstract investigates the role of CFD in vacuum degassing, a process that plays a pivotal role in removing impurities, such as hydrogen and oxygen, from the liquid steel. By leveraging CFD to simulate and analyze the fluid flow patterns, researchers and engineers can design more efficient vacuum degassing systems, leading to improved product purity and reduced waste.Another crucial aspect explored in this abstract is the alloy melt and mixing process. By employing CFD simulations, researchers can gain insights into the movement of different alloy components and optimize their distribution within the melt. This aids in achieving the desired alloy composition, ensuring uniformity, and enhancing the mechanical properties of the final product.In addition, the study delves into the movement and flotation of inclusions, which are unwanted impurities present in the metal. CFD can be utilized to model and analyze the behavior of these inclusions, enabling engineers to design efficient strategies for their removal, thereby enhancing the purity and integrity of the final product.Moreover, the abstract considers the impact of melt temperature losses, which can occur during different stages of the manufacturing process. By employing CFD, it becomes possible to understand and mitigate these temperature losses, leading to improved energy efficiency and better control over the manufacturing parameters.Part 1 of this abstract critically evaluates the use of CFD in iron making, analyzing its benefits and limitations. It highlights how CFD can aid in process optimization, improving the understanding of complex phenomena involved in iron making, and ultimately leading to enhanced production efficiency.Part 2 focuses on the application of CFD in steel making and steel operation. It explores the fluid flow dynamics during different stages of steel production, including refining, casting, and rolling. By leveraging CFD, engineers can optimize these processes, leading to improved product quality, reduced defects, and increased productivity.This abstract demonstrates the transformative potential of Computational Fluid Dynamics in metal, steel, and iron manufacturing. By utilizing CFD as a tool to model and analyze complex fluid flow phenomena, researchers and engineers can revolutionize the production process, maximizing efficiency, and ensuring high-quality end products.

This paper investigates the impact of price and real exchange rate volatility on Foreign Direct Investment (FDI) inflows in a panel of 10 Latin American and Caribbean countries, observed between 1990 and 2012. Both price and exchange rate volatility series are estimated through the Generalized Autoregressive Conditional Heteroscedasticity model (GARCH). Our results, obtained employing the Fixed Effects estimator, confirm the theory of hysteresis and option value, in so far it is found a statistically significant negative effect of exchange rate volatility on FDI. Price volatility, instead, turns out to be positive but insignificant. Moreover, we show that human capital and trade openness are key for attracting foreign capital. From the policy perspective, our analysis suggests the importance of stabilization policies as well as the one of government credibility in promoting trade openness and human capital formation.

Scientific, technical and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure and other product- and process-related attributes are comparable within the limits of testing then a biosimilar candidate would have safe safety and efficacy as its reference products. The current model of animal and human testing becomes redundant since all of these studies have much lower sensitivity and reproducibility in confirming biosimilarity. The recent AI-based protein structure prediction model has confirmed that the 3D structure can be predicted from the amino acid sequence, reducing the need for structural analysis; however, the new test methods based on MS are millions of times more sensitive and accurate. While the regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, removing clinical pharmacology profiling brings a dramatic paradigm shift, reducing development costs without compromising safety and efficacy. Also shared is a list of 160+ products ready to enter as biosimilars. Major actions from regulatory agencies and developers are required to make this paradigm shift.

We propose and experimentally realize a scheme of the optical nonreciprocity (ONR) using degenerate two-level atoms embedded in an optical ring cavity. For the degenerate transition Fg=4→Fe=3, we first study the cavity-transmission property in different coupling field, and verify that within the strong-coupling regime, the single-dark-state peak formed by electromagnetically induced transparency (EIT) shows ONR. Qualitative theoretical analysis shows that the stable ground-state Zeeman coherence is necessary for intracavity EIT. However, due to the frequency degeneracy, the large Rabi frequency of counter-propagating coupling field can reduce the number of effective atoms and weaken the strong-coupling of the atom-cavity, which determines that ONR based on intracavity EIT occurs only at weaker probe intensity. Furthermore, the ONR transmission with high contrast, linewidth-narrowed and broadband is experimentally demonstrated.

The arsRBC operon encodes a 3-protein arsenic resistance system. ArsR regulates the transcription of the operon, while ArsB and ArsC are involved in exporting trivalent arsenic and reducing pentavalent arsenic respectively. Previous research in Agrobacterium tumefaciens 5A demonstrated ArsR has regulatory control over a wide range of metal related proteins and metabolic pathways. We hypothesized that ArsR has broad regulatory control in other Gram-negative bacteria and set out to test this. Here, we use differential proteomics to investigate changes caused by the presence of the arsR gene in human microbiome-relevant Escherichia coli during arsenite (AsIII) exposure. We show that ArsR has broad-ranging impacts such as the expression of TCA cycle enzymes during AsIII stress. Additionally, we found that the Isc [Fe-S] cluster and molybdenum cofactor assembly proteins are upregulated regardless of the presence of ArsR under these same conditions. An important finding from this differential proteomics analysis was the identification of response mechanisms that were strain, ArsR, and arsenic specific, providing new clarity to this complex regulon. Given the widespread occurrence of the arsRBC operon, these findings should have broad applicability across microbial genera, including sensitive environments such as the human gastrointestinal tract.

This study proposes a flexible and adaptable protocol for the establishment of agricultural management zones that utilises remote sensing, ground truthing (apparent electrical conductivity and soil sampling), the IRRIGOPTIMAL® system and machine learning. This protocol could contribute significantly to the rational use of inputs (water, fertilizers and pesticides) and to the further efficient development of an optimal irrigation system with variable irrigation rates. The methodology to develop this protocol was applied to olive and alfalfa plots in Heraklion (Crete, Greece) to monitor soil and crop responses for the period 2022-2024. Spatial and temporal assessment of selected soil and plant parameters (moisture, photosynthetic activity) using ground and vegetation reflectance mapping by satellites and unmanned aerial systems provides important information in both the pre- and main phases of the management zone delineation. Geophysical methods such as electromagnetic induction, applied in the main phase of management zone delineation, provide a robust technique to determine the spatial and temporal distribution of apparent electrical conductivity. The Random Forest machine learning model was found to be most suitable for predicting soil electrical conductivity based on satellite-derived salinity indices and ground electromagnetic induction. Finally, the IRRIGOPTIMAL® system provides real-time monitoring of a variety of weather and soil parameters to determine the optimal cultivation of crops based on the creation of agricultural management zones.

The research paper provides a mathematical framework for understanding phase shift in wave phenomena, bridging theoretical foundations with real-world applications. It emphasizes the importance of phase shift in physics and engineering, particularly in fields like telecommunications and acoustics. Key equations are introduced to explain phase angle, time delay, frequency, and wavelength relationships. The study also introduces the concept of time distortion due to a 1° phase shift, crucial for precise time measurements in precision instruments. The research also addresses infinitesimal wave energy loss related to phase shift, enriching our understanding of wave behavior, and impacting scientific and engineering disciplines.

Nutrigenetics concerns individual differences in the reaction to food based on the genetic factors. Nutrigenomics analyses direct influences of nutrients on gene expression. Both terms are explained in our review article. Nutrigenetics and nutrigenomics require a deep understanding of nutrition, genetics and biochemistry and of new ‘omic’ technologies. It is often difficult to appreciate their relevance in the practice of preventive approaches for optimizing health, delaying onset of disease and diminishing its severity. This paper represents a review about the current research on Nutrigenomics and Nutrigenetics, and provide scientific data for a new integrated clinical approach.

The Covid-19 pandemic was a challenge for the whole world and it had major secondary effects on humans and environmental health. The viral infection induced, in many situations, secondary bacterial infections, especially enteric infections by destabilizing the balance of the gastrointestinal microbiota. The large-scale use of antibiotics and biocides both for curative and preventive purposes has determined an increase in bacterial resistance and at the same time the possibility of pathogenic microorganisms’ multiplication and their dissemination to natural environments. Wastewater is the main vector of faecal microorganisms that favour their dissemination into natural aquatic ecosystems. The present paper aimed to analyze the effect of Covid-19 pandemic on the microbiological quality of wastewater from sewage treatment plants in Romania and its impact on receiving rivers. In order to highlight different and important areas of Romania, 3 cities from the east, center and west were selected for a microbiological evaluation of their WWTPs influent and effluent between ante-Covid-19 and Covid-19 pandemic peak period, when the Covid-19 pandemic had a direct impact on WWTPs microbial composition. Our study showed a higher contamination with fecal bacteria linked to a higher Covid-19 incidence. The increased usage of pharmaceutical compounds, at their turn, increased the number of resistant bacteria reaching the environment via WWTP effluents.

In our previous papers, we demonstrated that inflammation and aging are the common roots of cancer and Alzheimer’s disease (AD). In both diseases, there is an inhibition of the mitochondria. In cancer, the alkaline intracellular pH (pHi) is associated with cell proliferation; acidic pHi causes apoptosis in AD. This difference is because cancer feeds on chemically neutral glucose, while neurons feed on acidic lactic acid. Increased uptake of lactic acid is responsible for acidic pH and cell death. Similarly, to AD, inflammation is responsible for metabolic shifts in age-related macular degeneration (AMD). In AD, there is hyperosmolarity responsible for increased lactic secretion by glial cells. Increased lactic secretion will cause neo-angiogenesis and neural cell death. Drugs increasing hyperosmolarity (Polyethylene Glycol) cause neo-angiogenesis and drusen-like structures in rodents. The link between AMD and inflammation is reinforced by the fact that treatments aiming at restoring mitochondrial activity, such as lipoic acid and/or methylene blue, have been experimentally shown to be effective in each set of diseases. The role of osmolarity has been demonstrated in the pathologies of the anterior segment of the eye, such as dry eye, corneal ulceration, cataracts, and glaucoma. The role of increased osmolarity in age-related macular degeneration (AMD) has been largely overlooked. We herein suggest that metabolic shift, inflammation, and hyperosmolarity are key players in the pathogenesis of AMD.

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

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

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

High-spin states of 192Tl are populated by the heavy ion fusion-evaporation reaction 181Ta(16O, 5n)192Tl at 97 MeV beam energy. A new level scheme with eight new levels is constructed and the level spins are tentatively assigned. The negative-parity yrast band is extended up to 23^{-}\hbar. Subsequently, the systematics of signature splitting and signature inversion are discussed for the negative-parity yrast band of odd-odd Tl isotopes including 192Tl, 194Tl, 196Tl, and 198Tl. With the increase of neutron number signature inversion is found in 196,198Tl at high-spin state in these four Tl isotopes. The reason may be due to the competition between neutron-proton interaction and Coriolis force.

Background and Objectives: Knee osteoarthritis (KOA) is a degenerative disease that is targeting continuously people of different ages, but especially the elderly population, the number of which tends to increase continuously at the global level. Apart from age, excess weight can influence the evolution of the disease, with obesity being associated with a weak inflammation stage, and an imbalance between pro-inflammatory and anti-inflammatory cytokines. The present work aimed to identify specific biomarkers alike ACRP-30, IL-10, TNF-α, and IL-6 in synovial fluid and correlate them with patients’ clinical data. Materials and Methods: 24 subjects with KOA and over 50 years of age are involved in the present study. All patients performed a supine X-ray at the target knee. Ultrasound was performed using an ESAOTE MyLab Omega (ESAOTE Spa, Italy) ultrasound device and a 6-19 MHz linear array transducer. Results: The obtained results highlighted a significant correlation between age and adiponectin level (p=0.0451, r=-0.412). Also, the IL-10 values are lower in cases where the intensity of the pain is more pronounced (p=0.0405, r=-0.421). In addition, analyzing the data by gender, it was observed that in the case of males, stiffness is more related to age (p=0.0079, r=0.7993), compared to women (p=0.0203, r=0.6223). In the case of women, the progression of the disease tends to increase more intensively total WOMAC score’s values (p=0.00031, r=0.8342), compared with men (p=0.0289, r=7013). Regarding interleukins and BMI, significant correlations were observed only in the case of men. Conclusions: A significant correlation between age and adiponectin, and adiponectin and IL-6, suggests that advanced age may contribute to adiponectin reduction. Comparing men with women, it was observed that men's age is more related to rigidity, and IL-6 and IL-10 are directly correlated to BMI and women seem to be more sensitive to pain and stiffness.

We discuss how the interaction of electrons with an overdamped optical phonon can give rise to a strange-metal behavior over extended temperature and frequency ranges. Although the mode has a finite frequency, an increasing damping shifts spectral weight to progressively lower energies so that, despite the ultimate Fermi liquid character of the system at the lowest temperatures and frequencies, the transport and optical properties of the electron system mimic a marginal Fermi liquid behavior. Within this shrinking Fermi liquid scenario, we extensively investigate the electron self-energy in all frequency and temperature ranges, emphasizing similarities and differences with respect to the marginal Fermi liquid scenario.

Undernutrition and micronutrient deficiencies such as anemia are considered significant public health challenges in Bangladesh, which enhancing fish consumption is a well-established food-based intervention to address these. This paper documents the establishment of community-based fish chutney production and reports the impact of its consumption on mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels among targeted 150 pregnant and lactating women (PLW) in rural Bangladesh. A fish chutney was developed using locally available ingredients followed by a series of laboratory tests, including nutrient composition, shelf-life and food safety. A community-based fish chutney production process was designed to: 1) supply locally available ingredients for processing; 2) establish two fish drying sites; 3) initiate a community-based production site, and 4) distribute fish chutney to PLW by six women nutrition field facilitators for one year. Then a pre- and post-intervention study was designed for a selected 150 PLW to receive 30g of fish chutney daily for 12 months. Differences in mean mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels pre- and post-consumption were analyzed using one-way analysis of variance. Consumption of 30g of fish-chutney resulted in significant increases of the mean values of Hb levels and MUAC among the targeted PLW.

The aim was to evaluate the agreement between plaque detection with intraoral scanner system (IOS) and a conventional clinical method and to evaluate the inter-rater reliability for scoring 3D models with and without a disclosing agent. 14 participants were recruited from the Department of Operative Dentistry, School of Dentistry, University name blinded to reviewers, it is completed after the reviewing process. Participants eligible for inclusion were adults with good general health and a minimum of 20 teeth. Participants were clinically examined with plaque assessment according to the modified Quigley-Hein plaque index before and after using a disclosing agent (GC-Tri Plaque ID-Gel, GC). Before and after the application of the disclosing agent, all study participants were scanned using the IOS (TRIOS5, 3Shape TRIOS A/S). The clinical examiner and additional three examiners blinded to the clinical examination assessed plaque status on the acquired 3D models with and without disclosing agent using the same index to evaluate the inter-rater agreement. Intraclass coefficient correlation, one sample t-test and Cronbach’s α for inter-rater reliability were calculated. All methods showed moderate to strong correlations (Spearman’s rho ranging from 0.527 to 0.618) and Cronbach’s α ranged from 0.551 to 0.766. Level of agreement between con-ventional clinical registration and registration from 3D models was acceptable overall.

Damage detection based on modal parameter changes becomes popular in the last decades. Nowadays are available robust and reliable mathematical relations to predict the natural frequency changes if damage parameters are known. Using these relations, it is possible to create databases containing a large variety of damage scenarios. Damage can be thus assessed by applying an inverse method. The problem is the complexity of the database, especially for structures with more cracks. In this paper, we propose two machine learning methods, namely the random forest (RF) and the artificial neural network (ANN) as search tools. The databases we developed contain damage scenarios for a prismatic cantilever beam with one crack and ideal and non-ideal boundary conditions. The crack assessment is made in two steps. First, a coarse damage location is found from the networks trained for scenarios comprising the whole beam. Afterward, the assessment is made involving a particular network trained for the segment of the beam on which the crack is previously found. Using the two machine learning methods, we succeed to estimate the crack location and severity with high accuracy for both simulation and laboratory experiments. Regarding the location of the crack, which is the main goal of the practitioners, the errors are less than 0.6%. Based on these achievements, we concluded that the damage assessment we propose, in conjunction with the machine learning methods, is robust and reliable.

Pollution, urbanization and technological advancements have posed stress on the ecosystem and its matrices. Globally, pollutants are observed in all compartments of ecological communities which affect the integrity of the atmosphere, hydrosphere, lithosphere and biosphere. Xenobiotics bioaccumulate and biomagnify across trophic levels or webs. Heavy metals have been implicated in impacts towards biodiversity and environmental declination. In Nigeria, wastes issues are a cause of concern and landfilling or are waste disposal approaches that cause deleterious effects such as depauperation of diversity and species decline, prompting the non-invasive ecotoxicological hazard assessments. Feathers were used to assess concentration levels of 13 metals (Fe, Mn, Zn, Cu, Co, Cr, Cd, Pb, Ni, Al, B, Se and Hg) using fast atomic absorption spectrophotometer (FAAS), one-way ANOVA was used in comparing variations in mean concentrations across trophic levels, diversity indices and point count methods were used to estimate diversity and abundance. Four avian species were assessed Hirundo aethiopica (insectivore), Streptoptelia senegalensis (granivore), Turdus pelios (omnivore), and Anthus leucophrys. (insectivore). Observed concentrations of important metals like iron were high with the insectivores having the highest concentrations of iron (2.6985 ± 0.1975 ppm) and granivores having the lowest (2.0100 ± 0.3172 ppm). The insectivores had the highest concentrations for cadmium, cobalt and chromium (0.0005 ± 0.0005ppm), nickel (at 00.0012 ± 0.0017 ppm) and least was observed in the granivores (0.0003 ± 0.0006 ppm). Selenium concentrations were quite high in insectivores (0.0775 ± 0.0035 ppm) and lowest in granivores (0.0433 ± 0.0015 ppm) likewise mercury for insectivores (0.0280 ± 0.0010 ppm) and granivores (0.0213 ± 0.0015 ppm). From the study, it is apparent that landfills are sources of pollution and poor management of wastes can affect biota (causing effects such as asymmetry and bioaccumulation) and ecosystem balance. The observation of heavy metals in the feathers serve as good sentinels due to their trophic levels and could be signs for what could be yet to occur. The heavy metal concentrations were significantly different at p < 0.05.

Agroforestry practices evolve with the development of basic and advanced facilities, changes in natural and artificial factors of land use change. The study aims to examine the socioeconomic characteristics and compare satisfaction levels across forest products and vegetable farming of the agroforestry community in Khost Province. Data were collected from 662 farmers and was analyzed using univariate Analysis of Variances (ANOVA) and Multivariate Analysis of Variances (MANOVA). The results found that forest and vegetable products, including fruits, berries, herbs, mushrooms, wild animals, oils, wood, honey, okra, eggplant, carrot, cucumber, pine nuts, pepper, and timber has different impact in terms of satisfaction with basic and advanced facilities, knowledge about land use and impacts, natural and artificial factors of land use change, and positive and negative impact of land use change. The limitation of the study included an absence of exogenous factors in the model such as climate change, financial conditions, market fluctuations, regulatory system, an area in which the study is selected, research design, and current condition of endogenous factors. Overall, agroforestry practices can improve the socioeconomic development of agroforestry-dependent communities in Khost Province, Afghanistan. This study provided useful insights for policymakers and development practitioners to promote agroforestry practice adoption and improve the socioeconomic development of agroforestry-dependent communities. Future works could explore the implications of agroforestry practices on the socioeconomic development of other dependent communities in Afghanistan.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

Abstract This study delved into the application of various machine learning (ML) models for the classification of lung cancer levels. Through meticulous monitoring of parameters such as minimum child weight and learning rate, efforts were made to mitigate overfitting while optimizing model performance. The Deep Neural Network (DNN) emerged as a standout performer, showcasing robust performance across training, validation, and testing stages. Ensemble methods like voting and bagging also demonstrated promising results. However, Support Vector Machine (SVM) models with the Sigmoid kernel faced challenges in achieving satisfactory performance. Overall, the investigation sheds light on the efficacy of different ML models in lung cancer level classification and underscores the importance of parameter tuning to address overfitting concerns.

Student-centered active learning (SCAL) shifts the focus from the teacher to the student. Implementing SCAL requires the development of new forms of assessment beyond memorization and comprehension. This paper aims to demonstrate the effectiveness of SCAL by analyzing student performance at different cognitive levels. In flipped classrooms, students completed tasks with varying cognitive demands. The tests measured knowledge (level 1), comprehension (level 2), application (level 3) and analysis (level 4). This approach to assessment assesses not only the acquisition of content, but also skills that are critical to a health science student's future career. The results of expository learning were compared with student-centered collaborative learning in the Anatomy and Embryology I course over three academic years. Student opinions were collected through 326 anonymous Wooclap® surveys. No differences in performance were found for low cognitive level questions. However, SCAL significantly improved performance on higher cognitive level questions that required problem solving and application of knowledge. Despite the benefits of SCAL, it requires more effort from both teachers and students. The current assessment system, which measures the quality of teaching, penalizes this effort and requires teachers to believe strongly in the effectiveness of SCAL.

Magnetic quantum oscillations (MQO) are traditionally applied to investigate the electronic structure of metals. In layered quasi-two-dimensional (Q2D) materials the MQO have several qualitative features giving additional useful information, provided their theoretical description is developed. Within the framework of the Kubo formula and the self-consistent Born approximation, we reconsider the phase of beats in the amplitude of Shubnikov oscillations of interlayer conductivity in Q2D metals. We show that the phase shift of beats of the Shubnikov (conductivity) oscillations relative to the de Haas - van Alphen (magnetization) oscillations is larger than expected previously and, under certain conditions, can reach the value of π/2, as observed experimentally. We explain the phase inversion of MQO during the 3D - 2D crossover and predict the decrease of relative MQO amplitude of interlayer magnetoresistance in a strong magnetic field, larger than the beat frequency.

The geological and hydrological conditions of tunnels near reservoirs are complex, and the impact of water level changes on the stability and leakage assessment of the lining structure is not considered in the current leakage evaluation. In order to construct an evaluation model for leakage level of tunnels near reservoirs, the influence of water level changes on tunnel stability and changes in environmental conditions on the leakage of tunnels were researched. Based on the AHP and extensibility theory, a hierarchical system for leakage assessment, incorporating values from nine indexes representing three aspects: geological conditions, hydrological conditions, and tunnel engineering. Numerical simulation was used to analyze the influence of water level changes. It was found that the water level change index greatly influences the displacement and stress distribution inside the tunnel structure. The leakage evaluation model was applied to the Tiebeishan Tunnel, resulting in a rating of 3, indicating medium-level leakage. Attention should be paid to water leakage in tunnels with changes in reservoir water levels. The leakage evaluation model for tunnels near reservoirs can effectively assess leakage levels under various conditions, providing a reference for safety assessments of tunnel leakage near reservoirs.

In the field of quality analysis of food and flavoring products, gas chromatography – quadrupole mass spectrometry – ion mobility spectrometry (GC-QMS-IMS) is a powerful technique for the simultaneous detection of volatile organic compounds (VOC) by both QMS and IMS. GC is an established technique for the separation of complex VOC-rich foods such as beverages, dairy and fruit products as well as flavorings in general. While the subsequent detection by IMS features soft ionization of fragile compounds (e.g., terpenes) with characteristic drift times, MS provides the analytes’ m/z-values for database substance identification. A limitation of the prominently used static headspace-based GC-QMS-IMS systems is the substantially higher sensitivity of IMS in comparison to full scan QMS, which results in the detection of relevant VOC only in IMS, but not in the QMS analyzer. The present study describes a new prototypic trapped-headspace (THS)-GC-QMS-IMS setup, with optimized active flow regulation, able to gain valuable data of both detectors. This ultimately allows the combination of a soft ionization with m/z values obtained from database-searchable electron ionization (EI) spectra and as such, offers a substantial advantage in fields of quality control. The new setup features aligned retention times for IMS and MS and sufficient signal intensities for QMS and IMS. The analytical setup was evaluated with a set of mango puree samples from various provenances and the data was evaluated by suitable machine learning approaches. The results demonstrate that THS-GC-QMS-IMS allows for the classification of mango purees from different cultivars and can be a promising alternative method for authenticity control of food, flavors, and beverages.

It is shown that the Lambda component in the cosmological Lambda-CDM model can be conceived as vacuum energy, consisting of gravitational particles subject to Heisenberg’s energy-time uncertainty. These particles can be modelled as elementary polarisable Dirac-type dipoles (“darks”) in a fluidal space at thermodynamic equilibrium, with spins that are subject to the Bekenstein-Hawking entropy. Around the baryonic kernels, uniformly distributed in the universe, the spins are polarized, thereby invoking an increase of the effective gravitational strength of the kernels. It explains the dark matter effect of galaxies to the extent that a numerical value of Milgrom’s acceleration constant can be assigned by theory. Non-polarized vacuum particles beyond the baryonic kernels compose the dark energy at the cosmological level. The result is an interpretation of gravity at the quantum level in terms of quantitatively established shares in baryonic matter, dark matter and dark energy, which correspond with the values of the Lambda-CDM model.

European strategic policy directions towards a sustainable blue economy have strengthened interest in maritime investments, thus increasing sectoral competition for marine space. Emerging repercussions out of such a rising interest need to be handled by Marine Spatial Planning (MSP) as a means for: properly allocating marine space to diverse uses; managing conflicts and promoting synergies among them; and pursuing a multi-use perspective of this space. A critical stage of each MSP exercise is the exploration of land-based spatial/developmental directions and their current or potential repercussions in the marine environment in order for constraints but also perspectives in policy choices/maritime uses in the MSP context to be featured; and attainment of a successful coherence or coordination between land and marine spatial/developmental policies to be ensured, by analyzing Land-Sea-Interaction (LSI) and embedding it in the MSP. The latter is the focus of this paper aiming to illuminate critical issues emerging from land-based (terrestrial) policy frameworks for feeding MSP endeavors; and is accomplished in the Northern Aegean Sea, Greece. Towards this end, a multilevel approach is adopted, delving into diverse policy contexts at the local, regional and national/European level and aiming to attain more informed MSP decisions in the specific study region.

Purpose: to assess any differences on marginal bone loss between bone-level or tissue-level dental implants through a review of literature until September 2019. Materials and methods: MEDLINE, Embase and other database were searched by two independent authors. The search was limited to articles in English. Results: The search provided 1028 records and, after removing the duplicates through titles and abstracts screening, 45 full-text articles were assessed for eligibility. For qualitative analysis 20 articles were included, 17 articles of them for quantitative analysis. A total of 1161 patients (mean age 54,4 years) and 2933 implants were observed, 1427 (Tissue-level) and 1506 (Bone-level). The survival rate and the success rate were more than 90%, except for 2 studies with a success rate of 88% and 86.2%. No studies reported any differences between groups in term of success and survival rates. Three studies showed that BL-implants had statistically less marginal bone loss (P< 0.05). Only one study reported statistically less marginal bone loss in TL-implants (P< 0.05). In the most part of the studies, differences between implant types in marginal bone loss were not statistically significant. Conclusion: Despite to the peri-implant tissue around transmucosal implants has been reported to be inflammation-free because of the absence of bacterial infiltration in the micro-gap between the fixture and abutment, no clinical and radiological differences were highlighted between groups from the included studies after a variable period of follow-up ranged between 1 to 5 years.

In western societies about one in six employees works in shifts. Shiftwork is associated with a number of poor somatic and psychological health outcomes, especially sleep issues. Higher rates of absenteeism and accidents in the workplace are possible consequences. Still, prevention programs and treatment options that are specifically tailored to shift workers’ needs are rare. We devised a 4-week online sleep intervention (n = 21) and compared treatment outcomes to our outpatient treatment for shift workers (n = 12). Measures included the WHO-5, ISI, and ESS scales as well as sleep diaries. Shift workers reported worse symptoms of insomnia than other participants. Results show significant average increases in sleep efficiency (+ 7%) and total sleep time (+ 25 min.), as well as significant improvements regarding insomnia symptoms and wellbeing in the online sample. Rates of improvement did not differ between the online and outpatient samples. Sleep disorders affect a relevant part of the working population, especially shift workers. Online approaches to treatment of these issues seem feasible and effective. Randomized controlled trials are needed.

The paper suggests that the physical priciple of special relativity's space-time transformation effect is wrong, Uniform linear motion without acceleration does not exist objectively, nor does its same reference frames. Therefore, it is inferred that the space-time transformation effect of special relativity is caused by the acceleration of moving objects, special relativity is only a part of general relativity, not a theoretical system that exists independently from general relativity. The corresponding mathematical demonstration and calculation verification are carried out, and the result proves that the inference of the paper is correct. At the same time, it further explains that the concept of absolute airspace is correct. Special relativity has serious errors in the concept of space, the principle of relativity and the physical principle of space-time transformation effect. Therefore, it is necessary to make a series of revisions to the theory of relativity and to reinterpret some related physical problems.

We propose that the coexistence of gapless Fermi arcs with the metal-insulator crossover of in-plane resistivity in strongly underdoped cuprates can be explained by the FL* fractionalized Fermi liquid nature of these systems and it is not due simply to disorder effects. The particle excitations of this FL* system derived from variants of the t-J model are: the gapless holon carrying charge with small Fermi momentum proportional to the doping, the gapful spinon carrying spin 1/2, gauge fluctuations coupling them and the hole as a spinon-holon bound state or resonance due to gauge binding with a Fermi surface respecting the topological Luttinger theorem. In our proposal Fermi arcs are determined by the hole resonance, whereas the metal-insulator crossover is dominated by spinon-spinon (with subleading holon-holon) gauge interactions and this dichotomy is able to explain their coexistence.

In physics, thought experiments are impressive heuristic tools. They are valuable instruments to help scientists find new results and to teach students the known ones. However, as we shall show, they should always be received with prudence, even when they are a shortcut to 'prove' well-established results. Here, we show that the most widely known thought experiments devised to derive the gravitational frequency shift from energy conservation are, in fact, problematic. When properly set and correctly read, those thought experiments reveal that the existence of the gravitational frequency shift is, in fact, at odds with energy conservation. We also propose two new simple thought experiments, one using the conservation of energy and the other the conservation of linear momentum, that corroborate that conclusion, showing that those conservation principles do not imply the gravitational frequency shift. We think that our results may be of some epistemological interest and could serve as a warning sign on how thought experiments should be received and trusted.

Specialized, reductionist, and linear approaches are applied in clinical research; they are based on linear logic and used towards therapeutic molecule-based targets. However, those approaches do not consider a systemic vision that describes the remote cause of the pathogenic activation. We propose new theoretical and practical methods for the next drug generation development. Self-organization, network structure, hierarchical organization, non-linearity, feedback circuits, reactions to information, and the view of drugs as information clarify the existing pharmacological methods. We suggest a perspective and hierarchical vision of the human organism based on six levels (mechanic and structural; metabolic; bodily dynamic; emotional, cognitive, spiritual). The therapy should restore the self-organization of every level using the “intelligent” modulation of the network responses. Multi-targeted drugs should act on the remote cause of the pathogenic cascade and be administered based on personal variability and networks. This approach may help the development of individualized, precise, and integrated medicine.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

Several Lung diseases can result in lung damage structural changes, with lung transplantation as a only therapeutic option when the disease reaches an advanced progression, unfortunately, the success of lung transplantation is limited. In this context, lung bioengineering is considered a potential therapeutic alternative and the current approach is based on the use of the natural extracellular matrix (ECM) of the decellularized lung. The use of undifferentiated cells to seed an ECM can be a more practical strategy for lung bioengineering but the sterilization of the organ for this recellularization process is still a challenge. In this sense, Low-Level Laser Therapy (LLLT) can emerge as a potential treatment alternative. Therefore, the objective of this study was to verify if LLLT, can optimize lung recelularization with mesenchymal stem cells by cytokine modulation. For this, we decellularized lungs from C57BL/6 mice perfusing SDS 1% via pulmonary artery, sterilized with LLL (660nm, 100mW, 30s). Whole lung scaffolds were recellularized: (1) Recellularized Lung (2) Recellularized Lung + LLLT. Mesenchymal stem cells derived from human tooth pulp (DPSc) were seeded into lungs and incubated for 24 hours at 37ºC, 5% CO₂, in a bioreactor-like conditions, maintaining CPAP at 20cmH2O, 90% O2, and LLL at wavelength of 808nm, 100mW, 30s. Culture medium were analyzed at 24 hours. H&amp;E, immunostaining, SEM and ELISA assay were performed. We produced viable biological scaffolds absent of DNA content, preserving glycosaminoglycans and collagen I, III and IV, fibronectin, laminin and elastin and lung structure (SEM). The levels of IL-6 and IL-8 were stable during the 24 hours of culture. IFN-γ levels showed significant difference in the DPSc and DPSc+LLLT group in the 24-hour evaluation. The levels of IL-10 decreased after LLLT. These findings highlight LLLT's role in cytokine regulation and contamination prevention during lung recellularization with mesenchymal stem cells. Overall, these results demonstrated that LLLT's modulated cytokine levels and could prevent contamination during the lung recellularization process with mesenchymal stem cells, offering promise for enhanced therapeutic strategies in lung bioengineering.

A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets stronger with higher statistical power. Fourth, the tested statistical hypotheses usually lack biological justification and are often uninformative. Despite these problems, a screen of 48 papers from the 2020 volume of the Journal of Evolutionary Biology exemplifies that significance testing is still used almost universally in evolutionary biology. All screened studies tested default null hypotheses of zero effect with the default significance threshold of p = 0.05, none presented a pre-specified alternative hypothesis, pre-study power calculation, and the probability of ‘false negatives’(beta error). The results sections of the papers presented 49 significance tests on average (median 23, range 0–390). Of 41 studies that contained verbal descriptions of a ‘statistically non-significant’ result, 26 (63%) falsely claimed the absence of an effect. We conclude that studies in ecology and evolutionary biology are mostly exploratory and descriptive. We should thus shift from claiming to ‘test’ specific hypotheses statistically to describing and discussing many hypotheses (possible true effect sizes) that are most compatible with our data, given our statistical model. We already have the means for doing so, because we routinely present compatibility (‘confidence’) intervals covering these hypotheses.

Japanese encephalitis (JE) is a vaccine preventable disease caused by the Japanese encephalitis virus (JEV), which is primarily prevalent in Asia. JEV is a Flavivirus, classified into a single serotype with five genetically distinct genotypes (I, II, III, IV, and V). JEV genotype III (GIII) had been the most dominant strain and caused numerous out breaks in the JEV endemic countries until 1990. However, recent data shows the emergence of genotype I (GI) as a dominant genotype and it is gradually displacing GIII. The exact mechanism of this genotype displacement is still unclear. The virus can replicate in mosquito vectors and vertebrate hosts to maintain its zoonotic life cycle; pigs and aquatic wading birds act as an amplifying/reservoir hosts, and humans and equines are the dead end hosts. The important role of pigs as an amplifying host for JEV is well known. However, the influence of other domestic animals especially birds that live in high abundance and close proximity to human is not well studied. Here, we strive to briefly highlight the role of birds in JEV zoonotic transmission, discovery of birds as a natural reservoirs and amplifying host for JEV, species of birds susceptible to JEV infection, and the proposed effect of JEV on poultry industry in future perspective which have been neglected for a long times. We also discussed the recent in vitro and in vivo studies which show that the newly emerged GI viruses replicated more efficiently in bird-derived cells and ducklings/chicks than GIII, and an important role of birds in the JEV genotype shift from GIII to GI.

This conceptual article is aimed at evaluating the COVID19 impacts on the global economy and to postulating an ‘economic paradigm shift’. We argue that the existing economic, political, and trade principles have been challenged due to the global pandemic issue. We also compare the COVID19 impact on Western countries and Eastern countries with their control mechanisms. The emerging of new economies is due to the travel restrictions and disrupt of the global economies are discussed that pave a gateway to the economic paradigm shift. The article finally assesses the advent of 5G technology and its implications to face any future health threats that will lead to the next economic paradigm shift in the modern world.

Neonatal mortality remains a public health concern and timely identification and prompt intervention in the delivery room could improve the outcome in neonatal morbidity and mortality. We performed a retrospective study to help us finding the profile of the high-risk newborn regarding the need for NICU admission, necessary to establish a protocol regarding the mobilization of human and material resources for the urgent management of these situations. All deliveries and neonates born in Maternity of Bihor County Emergency Clinical Hospital from Romania were reviewed, including relevant maternal, foetal and perinatal data to identify risk factors that result in birth of newborns needing resuscitation at birth between 2012-2019. The number of births showed a downward trend but around 90% of the births were on term. The incidence of neonatal emergencies is increasing, the most frequently were respiratory, sepsis and other infections, cardiovascular emergencies, and extreme prematurity. It is noted that in 2021 the incidence of these neurological emergencies increased by three times compared to previous years. The neonatal and maternal risk factors associated with admission to the NICU were mother's age over 35 years, low level of education, second/more gestation, weight under 2500 g, Apgar score under 7, premature rupture of membranes, macrosomia and mother's infectious pathology. Accurate identification of risk factors and anticipation at the birth of a high-risk neonate would result in adequate preparation and prompt resuscitation of neonates who need some level of intervention and thus, reducing neonatal morbidity and mortality.

In Indonesia, types of meat are still identified manually due to increasing prices for beef and buf-falo ahead of Idul Fitri. Traders mix beef with pork to thwart the beef scam. Haar wavelet and GLCM, GLCM with angles of 0°, 45°, 90°, and 135°, as well as matrices using contrast, correlation, energy, homogeneity, and entropy, are used in feature extraction. The following are the results of meat image classification testing using k-NN, Haar wavelet, and GLCM: The k-NN algorithm shows superiority in identifying fresh (99%), frozen (99%), and rotten (96%) meat texture images with the most fantastic accuracy results in every situation. Meanwhile, GLCM routinely provides good results, especially regarding the texture image of fresh meat (183.21) and rotten meat (115.79). However, despite delivering less throughput than k-NN and GLCM, Haar wavelets are still helpful, especially when dealing with fresh meat texture images (89,96).

A platform for indoor monitoring inside buildings, integrating both conventional and environmentally friendly devices with energy-harvesting sources, is proposed. Biomaterials such as gelatin and chitosan, derived from renewable resources, have been utilized to fabricate hydrogel and active layers for sensors and supercapacitors. These devices enhance the environmental profile of the proposed solution by employing sustainable materials and optimizing energy consumption. The developed electronic board prototype provides a versatile platform for testing various sensor configurations while accommodating different energy-harvesting sources. The article details the design of an energy harvesting system for indoor monitoring, covering various aspects regarding energy sources, power management circuits, and low-power microcontroller units. It examines energy storage devices and sensors, including both eco-friendly and commercial ones, as well as radio transceivers with different communication technologies. Additionally, an energy analysis to evaluate the performance and energy efficiency of the platform is presented.

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. The article presents both the theoretical consideration of the proposed solution and its experimental verification, along with the concept of the in-plane displacement/strain sensor using the described head.

The origin of the nucleus remains a great mystery in life science, although nearly two centuries have passed since the discovery of nuclei. To date, studies of eukaryogenesis have focused largely on micro-evolutionary explanations. Here, we examined macro-patterns of C-values (the total amount of DNA within the haploid chromosome set of an organism) for over 110,000 species and the chromosome numbers for over 11,000 species and their potential links with the state of atmospheric oxidation over geological time. Eukaryogenesis was in sync with an over 2.5 order-of-magnitude increase in genome size from prokaryote to eukaryote, and also with a rapid rise of atmospheric oxidation, suggesting that eukaryogenesis would have resulted from a regime shift of genomes driven by the oxidation-driven complexification and structuralization (e.g. chromatin packing).

The pandemic caused by SARS-CoV-2 virus obstructed the Chinese economy and has expanded to the rest of the world at a rapid pace affecting at least 215 countries, areas and territories. The advancement of the disease and its economic repercussions is profoundly ambiguous, making it challenging for policymakers to formulate suitable microeconomic and macroeconomic policy responses. The scenarios in this paper illustrate how an outbreak could significantly affect the global economy in the short run. It has been estimated that each additional month of crisis would cost from about 2.5-3% of the global GDP and that the GDP growth would take a blow, reaching about 3-6%, depending on the country. Scenarios also suggest that GDP can drop by more than 10% and even exceed 15% in some countries. Via addressing the economic consequence of COVID-19 in different industries and countries, the paper presents assessments of the likely global economic costs of COVID-19 and the GDP growth of different countries. Economies will be negatively affected because of the high number of jobs at risk. Countries highly dependent on foreign trade are more negatively affected. Given that disease and its economic influence are highly unpredictable in numerous aspects, the global economy at the moment is the most critically threatened in history.

It has recently been shown that, contrary to the wide belief that a shift-enabled condition (necessary for any shift-invariant filter to be representable by a graph shift matrix) can be ignored because any non-shift-enabled matrix can be converted to a shift-enabled matrix, such a conversion in general may not hold for a directed graph with non-symmetric shift matrix. This paper extends this prior work, focusing on undirected graphs where the shift matrix is generally symmetric. We show that while, in this case, the shift matrix can be converted to satisfy the original shift-enabled condition, the converted matrix is not associated with the original graph, that is, it does not capture anymore the structure of the graph signal. We show via a counterexample, that a non-shift-enabled matrix cannot be converted to a shift-enabled one and still maintain the topological structure of the underlying graph, which is necessary to facilitate localized signal processing.

Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

Under the dual background of underemployment and health inequality, this paper empirically analyzes the impact of education level on underemployed workers’ health based on CLDS2016 data. The results show that underemployment is significantly related to the decline of self-rated health, increased depression tendency, and morbidity in a certain period. The results indicate that underemployment can significantly reduce the health level of workers in the low education level group and the high education level group. However, it has no significant impact on workers’ health in the middle education level group; even if we change the measurement method of indicators and consider endogeneity, the research conclusion is still robust. Moreover, this kind of health inequality mainly comes from the difference in economic effect and leisure effect of underemployment to workers with different educational levels. This paper provides empirical support for increasing the labor protection mechanism of underemployed people and reducing the health inequality caused by educational level differences.

Lower cutoff levels in screening programs have led to an increase in the proportion of detected cases with transient hypothyroidism, leading to increase of the overall incidence of primary congenital hypothyroidism (CH) in several countries. We have performed retrospective evaluation on the data from 251,008 (96.72%) neonates screened for thyroid-stimulating hormone (TSH) level in dried blood spot specimens taken 48 hours after birth, between 2002 and 2015, using DELFIA method. A TSH value of 15 mIU/L was used as the cutoff point until 2010 and 10 mIU/L thereafter. Primary CH was detected in 127 newborns (1/1976) of which 81.1% had permanent and 18.9% had transient CH. The incidence of primary CH was increased from 1/2489 until to 2010 to 1/1585 thereafter (p=0.131). However, the incidence of permanent CH was slightly increased (p=0.922), while the transient CH incidence had 8-fold increasing after lowering the TSH cutoff level (p<0.001). In cases with permanent CH, we observed lower frequency for thyroid dysgenesis (82.7 vs. 66.7%) and higher frequency for normal in-situ thyroid gland (17.3 vs. 33.3%), for the period with reduced TSH cutoff value. Our findings support the impact of lower TSH cutoff on the increasing incidence of congenital hypothyroidism.

Computational neuroscience has undergone a significant transformation in recent years, driven by the exponential growth of neural data and advancements in data science and machine learning. While traditional theoretical models remain valuable, there is a growing emphasis on integrating data-driven approaches to develop more accurate, biologically plausible, and predictive models of neural function. This shift has led to a new equilibrium in the field, where data-driven model development, machine learning techniques, and hybrid approaches that combine data and theory are increasingly prevalent. In this article, we discuss the evolving landscape of computational neuroscience, highlighting the importance of data-driven methods and the emergence of a more integrative approach that leverages both data and theory to unlock the mysteries of the brain. We also explore the implications of this shift for future research and clinical applications, emphasizing the potential for data-driven computational neuroscience to revolutionize our understanding of neural function and pave the way for new treatments for neurological disorders.

Ferroptosis is a unique variety of non-apoptotic cell death, driven by massive lipid oxidation in an iron-dependent manner. Since Ferroptosis was introduced as a concept in 2012, it was shown it's essential role in the pathogenesis in neurodegenerative diseases and an important role in therapy-resistant cancer cells. Thus, a detailed molecular understanding of both canonical and alternative ferroptosis pathways are required. There is a set of widely used chemical agents to modulate ferroptosis using different pathway targets: Erastin blocks cystine-glutamate antiporter, system xc-; ML210 directly inactivate GPX4; L-buthionine sulfoximine (BSO) inhibits γ-glutamylcysteine synthetase, an essential enzyme for glutathione synthesis de novo. Most studies were focused on lipidomic profiling of model systems undergoing death in a ferroptotic modality.

Study of perihelion shift of Mercury and deflection angle are important aspects for the verification of general relativity. For Schwarzschild geometry both the perihelion shift and weak deflection angle were independent of charge whereas for ReissnerNordstrom space-time charge should effect on both the perihelion shift and deflection angle. This paper shows the perihelion shift decreases with the increases of charge. Effect of other parameters like angular momentum, mass parameter, distance of closest approach on perihelion precession and deflection angle has also discussed. This paper also includes the graphical behavior which verifes our theoretical calculations.

The overarching purpose of this review was to highlight the utility of different aerobic field tests in terms of the parameters they provide, with a specific focus on shuttle running and all-out testing. Various field tests are discussed in detail and are categorised according to linear continuous running tests (e.g. 12-minute Cooper Test, University of Montreal Track Test [UMTT], 1200/1600 m time trials, 3-minute all-out test for running [3MT]), intermittent shuttle running tests (e.g. yo-yo inter-mittent recovery test level 1 [YYIR1], 30-15 intermittent fitness test [IFT], and the intermittent all-out shuttle test [IAOST]), and continuous shuttle running tests (e.g. 1.2 km shuttle run test [1.2SRT], maximal multi-stage 20-m shuttle test [MSR], 25-m, 30 m and 50-m 3-minute all-out shuttle test [AOST]). Readers will be guided through the theoretical and practical underpinnings of the 3MT methodology, where the all-out testing methodology is stationed within the testing paradigm, and how to practically implement and interpret the results thereof.

Cutaneous melanoma (CM) is a candidate for screening programs, since its prognosis is excellent when diagnosed in an early disease stage. Targeted screening of those at high risk for developing CM, a cost-effective alternative to population-wide screening, requires valid procedures to identify the high-risk group. Self-assessment of the number of nevi has been suggested as a component of such procedures, but its validity has not yet been established. We analyzed the level of agreement between self-assessments and expert assessments of the number of melanocytic nevi in the area between the wrist and the shoulder of both arms based on 4548 study subjects in whom mutually blinded double counting of nevi was performed. Nevus counting followed the IARC protocol. Study subjects received written instructions, photographs, a mirror, and a “nevometer” to support self-assessment of nevi larger than 2 mm. Nevus counts were categorized based on the quintiles of the distribution into five levels defining a nevus score. Cohen’s weighted kappa-coefficient was estimated to measure the level of agreement. In the total sample, agreement between self-assessments and expert-assessments was moderate (raw agreement: 50.29%, weighted κ=0.596). Self-assessed nevus counts were higher than those determined by experts (mean differ-ence: 3.33 nevi). The level of agreement was independent of sociodemographic and cutaneous factors; however, participants’ eye color had a significant impact on the level of agreement. Our findings show that even with comprehensive guidance, only a moderate level of agreement between self-assessed and expert-assessed nevus counts can be achieved. Self-assessed nevus information does not appear to be reliable enough to be used in individual risk assessment to target screening activities.

This article provides a comprehensive exploration of the electric vehicle (EV) business, investigating its current state, market dynamics, and pivotal role in sustainable transportation. It delves into factors driving EV adoption, challenges faced by the industry, and the landscape of key players. The discussion extends to investments, infrastructure development, consumer trends, and the technological innovations shaping the future. The article concludes with insights into the anticipated growth and transformative impact of EVs, emphasizing their significance in fostering a cleaner, more sustainable future for global transportation.

The effect of Localized Surface Plasmon (LSP) of 5 nm mean size Au particles deposited on TiO2 P25 was investigated during the photo-thermal water gas shift reaction (WGSR). The effects of CO concentration, excitation light flux and energy, and molecular oxygen addition during the reaction were investigated. The photocatalytic WGSR rate under light excitation with wavelengths extending from 320 to 1100 nm was found to be higher than the thermal reaction alone at the same temperature (85 oC). A ratio H2/CO2 of near unity was found at high concentrations of CO. Addition of molecular oxygen during the reaction resulted in a slight decrease of molecular hydrogen production while the rates of CO2 formation and that of CO consumption changed by one order of magnitude. More important, it was found that the WGSR rates were still high under only visible light excitation (600 - 700 nm). The results prove that Au LSP alone triggers this chemical reaction without the need to excite the semiconductor on which they are deposited.

In the context of all-digital radar systems, phase-modulated continuous wave (PMCW) based on pseudorandom binary sequences (PRBSs) appears a prominent candidate modulation scheme for applications such as autonomous driving. Among the reasons for that are its simplified transmitter architecture and lower linearity requirements, e.g., compared to orthogonal-frequency division multiplexing radars, as well as its high velocity unambiguity and multiple-input multiple-output operation capability that are characteristic of digital radars. For appropriate operation of a PMCW radar, choosing a PRBS whose periodic autocorrelation function (PACF) has low sidelobes and high robustness to Doppler shifts is paramount. In this sense, this article performs an analysis of Doppler shift tolerance of the PACFs of typically adopted PRBSs in PMCW radar systems supported by simulation and measurement results. To accurately measure the Doppler-shift-induced degradation of PACFs, peak power loss ratio (PPLR), peak sidelobe level ratio (PSLR), and integrated-sidelobe level ratio (ISLR) were used as metrics. Furthermore, to account for effects on targets whose ranges are not multiples of the range resolution, oversampled PACFs are analyzed.

This article analyses three recent shifts in what [1] called the geography of ‘Big Things’ meaning the contemporary functions and adaptability of modern city centre architecture. We periodise the three styles conventionally into the fashionable ‘Starchitecture’ of the 1990s, the repurposed ‘Agritecture’ of the 2000s and the parodising ‘Parkitecture’ of the 2010s. Starchitecture was the form of new architecture coinciding with the rise of neo-liberalism in its brief era of global urban competitiveness prevalent in the 1990s. After the Great Financial Crash of 2007-8 the market for high-rise emblems of iconic, thrusting, skyscrapers and giant downtown and suburban shopping malls waned and online shopping and working from home destroyed the main rental values of the CBD. In some illustrious cases ‘Agritecture’ caused re-purposed office blocks and other CBD accompaniments to be re-purposed as settings for high-rise urban farming, especially aquaponics and hydroponic horticulture. Now, Covid-19 has further undermined traditional CBD property markets causing some administrations to decide to bulldoze their ‘deadmalls’ and replace them with urban prairie landscapes, inviting the designation ‘Parkitecture’ for the bucolic results. The paper presents an account of these transitions by reference to questions raised by urban cultural scholars like Jane M. Jacobs and Jean Gottmann to figure out answers in time and space to questions their work poses.

Covid-19 pandemic lockdown has slow down the world economic system. The pandemic has cleared the roads, close factories and grounded planes causing severe economic challenges. The damaging impact of the pandemic amid lockdown has been a blessing in guise for the environment because of significant drop in pollution level as transport and industrial sectors shutdown. Transport and industrial sectors are major contributors to environmental degradation through various emissions as a result of fossil fuel consumption. Energy consumed by transport and industrial sectors will have to shift to viable, readily available, economically and environmentally friendly with no carbon build up post Covid-19 pandemic. Hydrogen energy remains the best alternative option technologies containing green house gas emission and pollutions of several forms. Hydrogen holds the potential to provide a clean, reliable, renewable and economical source of energy for meeting the growing and unending global energy needs post pandemic. The present paper explores the economic feasibility and potential of hydrogen to serve as a competitive fuel option post pandemic. In this paper, the role of hydrogen as an energy carrier hydrogen economy structure, potential of hydrogen economy, hydrogen production methods, hydrogen application and the economic and environmental importance of hydrogen as a viable fuel option post covid-19 pandemic were discussed. There will be a surge in demand and investment for hydrogen economy post Covid-19.

Education for Sustainable Development (ESD) is a global initiative towards transforming education for sustainability. The integration of SD into the education portfolio is considered to be an important approach that ensures strategic alignment of higher education with SDGs. A document review was used to identify and discuss the difference between transmissive and transformative education in relation to SDGs and in the context of Somali education. In this trajectory, it is expected that the concept of ‘‘transformative education is likely to become more common to meet the emerging social, economic and environmental issues, yet practical challenges remain in Somaliland HE sector. The roadmap towards addressing transformative education for sustainability is not included in the Somaliland national portfolios; particularly ESD has not been presented. In this regard, this paper proposed a generic framework that spotlights the integration of HEIs and the national development goals (NDGs) in Somaliland. Meanwhile, developed and developing countries are prioritizing structural transformation in their HEIs that are tailored to national and regional development programs. Consistent with the Rio + 20 outcomes, the authors analyzed the concept of the ‘‘sustainable university’’ and identified the fact that it is practically divided into three interrelated and complementary categories, namely social-, environmental-, and economic-oriented university in pursuit of actualizing SD. The paper recommends major reforms in the education sector including availing investment portfolios for R&D, renovation of education goals and transforming universities for sustainability

This paper proposes a novel single-stage buck-boost three-Level neutral-point-clamped (NPC) inverter with two independent dc sources coupled for the grid-tied photovoltaic (PV) application, which can effectively solve the unbalanced operational conditions generally appeared between two coupled independent PV sources induced by the unequal irradiation and temperature distribution. The proposed control scheme can simultaneously guarantee the maximum power point (MPP) operation of both PV sources and maintain the output waveform quality. Compared to the traditional two-stage PV inverter, the proposed NPC inverter could reduce the PV array voltage requirement and dc-link capacitors’ voltage rating, meanwhile show the advantage in operational efficiency. MATLAB simulations and the captured experimental results are presented to show the performance of the proposed three-level inverter.

Reverse water gas shift reaction (RWGS) is an important process which plays a vital role in many CO2 utilization related reactions. Noble metals are the most active catalysts in RWGS, but the high price and low reserve strangled their applications. In the present work, we reported a non-transition-metal MgAl2O4 catalyst which showed outstanding activity and stability at high temperatures in the RWGS reaction and improved performance after doping of single atomic Nin+. The catalyst can obtain 46% of CO2 conversion in durability test of 75 h at 800 °C under high weight hourly space velocities (225 000 ml g-1 h-1). The adsorption sites, possible reaction route, and effects of Nin+ single atoms on the (111) surface of MgAl2O4 for RWGS were investigated by in situ DRIFTS and DFT calculations. The results indicated that the rate determining reaction step of RWGS on MgAl2O4 and Ni (SA)/MgAl2O4 were both the reaction of OH* + H* → H2O* + *, but the energy barrier was significantly reduced after introducing single atomic Nin+. Nin+ atoms can increase the hydroxyl coverage on the surface of catalyst and Al3+ sites near the Nin+ ion are considered as the predominant active sites for RWGS reactions.

Multimission satellite altimetry (e.g. ERS, Envisat, TOPEX/Poseidon, Jason) data have enabled a synoptic view of ocean variations in the past decades, including sea-level rise and mesoscale circulations. Since 2016, the Sentinel-3 mission has provided better spatial and temporal sampling compared with its predecessors. The Sentinel-3 Ku/C Radar Altimeter (SRAL) is one of the synthetic aperture radar altimeters (SAR Altimeter) which is more precise in coastal and lake observations. In this study, we validate Sentinel-3 Level-2 products in Baltic Sea coastal areas and two lakes in Estonia. Moreover, the Copernicus Marine Environment Monitoring Service (CMEMS) Level-3 sea-level anomaly data and the Nucleus for European Modelling of the Ocean (NEMO) reanalysis model outcomes are compared with measurements from a tide gauge network. A dense in situ water level network deployed along the coast for geodetic observation was utilised to provide ground truths for validating altimetry results. Three validation methods were used for Level-2 data: (i) collocated Sentinel-3 and GNSS ship measurements; (ii) a national geoid model (EST-GEOID2017) with sea-level anomaly correction; (iii) collocated Sentinel-3 and buoy measurements. The validations were carried out in seven Sentinel-3A/B overpasses in 2019. Our results show that the uncertainty of the Sentinel-3 Level-2 altimetry product is below decimetre level on the Estonian coast and the targeted lakes. Results from CMEMS Level-3 showed a correlation of 0.8 (RMSE 0.19 m) and 0.91 (RMSE 0.27 m) when compared against tide gauge measurements and NEMO model, respectively.

Due to the long duration and high cost of traditional pumping tests, the response of well water level to seismic wave, earth tide, and barometric pressure provides a feasible method for determining continuous changes in aquifer hydraulic parameters. Aiming at the problem that the response phase shift of well BB water level to tidal tide M2 is greater than that of tide O1, this paper preferentially calculated the time series changes of S, Be, n and BKu based on the response mechanism of well water level to barometric pressure and earth tide and with the help of smooth moving method. Then by using the mixed flow model, the variation of transmissivity and leakage coefficient over time were simultaneously obtained, and the evolution process and characteristics of aquifer parameters near well BB caused by the Wenchuan earthquake were ultimately discussed. The calculation results are basically consistent with the previous pumping test, and have been verified and compared by using other scholars' methods. This solving process avoids the problems such as excessive dependence on initial values, multiple solutions, and unstable tide O1, which has a promoting effect on the study of the impact of seismic activity on aquifer systems.

Fashion industry is the second most polluting industry in the world representing a 2 trillion dollars and growing valuation (Pal, 2017). This dual context makes its challenges hard to address. From one side, fashion design education and practice systems have been perpetuating an industrial-focused approach which relies mostly in the economic improvement through fast cycles of product development (Pal, 2017). On the other side, fashion industry has also been closed to either multidisciplinary and transdisciplinary initiatives outside the scope of the artistic disciplines. Therefore, innovative approaches are needed to solve fashion industrial challenges. One of the most promising fields to tackle fashion current environment and technological problems is microbiology (Mazzoto et al., 2021). During the past 50 years, microbiology has played a vital role in solving human grand challenges in health, agriculture, food, and waste management sectors, and it also represents an opportunity for fashion industry as well. Microbiology biotechnological potential for the fashion industry relies mostly on the improvement of toxic waste bioremediation and the development of novel biomaterials and biomolecules. Moreover, the emergent field of synthetic biology is expanding the tools and approaches available, and they can already be seen in the development of engineered living materials that have functional properties (Mazzoto et al., 2021). Despite the urgent need for change, there is still a long way until a more sustainable fashion industry is achieved. Therefore, microbiological research and innovation need maturation to be able to scale-up and reach a global impact for tackling fashion industrial problems.

With the rapid population growth, there is an urgent need for innovative crop improvement approaches to meet the increasing demand for food. Classical crop improvement approaches involve, however, a backbreaking process that cannot equipoise with increasing crop demand. RNA based approaches i.e. RNAi-mediated gene regulation and site-specific nuclease based CRISPR/Cas9 system for gene editing has made advances in the efficient targeted modification in many crops for the higher yield and resistance to diseases and different stresses. In functional genomics, RNA interference (RNAi) is a propitious gene regulatory approach that plays a significant role in crop improvement by permitting down-regulation of gene expression by small molecules of interfering RNA without affecting the expression of other genes. Gene editing technologies viz. clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (CRISPR/Cas) have appeared prominently as a powerful tool for precise targeted modification of nearly all crops genome sequence to generate variation and accelerate breeding efforts. In this regard, the review highlights the diverse roles and applications of RNAi and CRISPR/Cas9 system as powerful technologies to improve agronomically important plants to enhance crop yields and increase tolerance to environmental stress (biotic or abiotic). Ultimately, these technologies can prove to be important in view of global food security and sustainable agriculture.

The possibility to test a radio frequency transceiver through the use of appropriate channel emulators allows to evaluate their performance under various operating conditions. Many systems are able to operate with a relatively limited instantaneous bandwidth by applying known statistical models. Sometimes it is necessary to evaluate the performance of a RF transceiver installed on high or very high speed platforms over predictable trajectories using optionally DEMs (Digital Elevation Models)data of the terrain to estimate the number of stimulated paths and their contributions during the flight. When the instantaneous bandwidth of the signal becomes high (over several hundred of MHz), one of the most important phenomenon to consider is the Doppler spread induced by the channel and traditional narrowband models become unuseful. In this paper there are presented some results when a time expansion is adopted in order to emulate the transceiver dynamic and the consequent Doppler spread with the aim to control the spectral purity of the emulated propagation channel.

Nowadays, unmanned vehicles are widely used in various fields. However, the safety of unmanned vehicles is directly determined by the autopilot systems, and sensor faults are a very critical factor that affects the normal operation of the autopilot systems. To efficiently and comprehensively test unmanned systems for sensor faults, this paper proposes a chip-level testing platform for unmanned vehicle autopilot systems based on FPGA hardware-in-the-loop simulation. Unlike existing testing platforms, the introduction of FPGA technology allows us to achieve nanosecond real-time simulation frequency, thus realizing chip-level simulation of sensors and black-box automated testing. Firstly, we propose a set of general platform and modeling methods, and the paper presents a detailed application of the four most common necessary sensors in autopilot systems as examples. Secondly, we propose for the first time a chip-level fault testing method for unmanned systems, and build a test platform with a quadrotor vehicle, the PX4 software platform, and the Pixhawk4 hardware platform as examples. Finally, the experimental results verify that the testing platform proposed in this paper can adapt to various autopilot systems and has high simulation test reliability.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

This article explores the pressing need for a paradigm shift in economics, challenging the dominance of classical economic theories and models that have long held sway. We delve into the limitations of traditional economic paradigms, which often rely on unrealistic assumptions and fail to capture the complexities of human behavior and the modern global economy. Drawing from insights in behavioral economics, environmental economics, and complexity theory, we argue for a more nuanced and multidisciplinary approach to economic analysis. Our discussion addresses the challenges of breaking away from deeply entrenched academic norms and the resistance to change within the economics profession. We highlight strategies for individuals and groups to advocate for the incorporation of modern economic theories in education and research. By fostering interdisciplinary collaboration, encouraging critical thinking, and engaging with policymakers and the public, we aim to catalyze a shift toward economics that is better equipped to address the intricate challenges of the 21st century. This article serves as a call to action for economists and educators alike to embrace a more dynamic and responsive approach to understanding human behavior and decision-making in the modern world.

Anthropogenic disturbances interacting with natural disturbances, ecological and socio-economic factors can provoke forest degradation and modulate ecosystem resilience. In Haiti, protected areas recently created to reduce forest loss, require studies about forest dynamics and land use to assure the development of sustainable management policies. We combine field interview with Landsat satellite images of the Macaya National Park collected between 1985 and 2021 to investigate: 1) how much of the original forest area has been converted into agricultural or logged area since 1985; and 2) how do elevation and slope influence the expansion of human-induced land-use changes. Our results indicate an increase of 11.36% in forest cover and a reduction of 75.34% in agriculture class cover, despite the passage of seven hurricanes in the region. Forest recovery was apparently unrelated to elevation and slope, and likely reflected the implementation of new environmental laws and policies with the creation of the Macaya National Park in 1983. Restoration and protection programs contributed to ensure access to financial resources, technical assistance and new technology, thus promoting a shift into a more resilient forest system. This study brings hope for forest conservation in Haiti by showing that positive results can be achieved through inclusive collaboration.

An exhaustive list of thirteen instances of reports confirming experimentally the relativistic Doppler relation, are examined. For those involving longitudinal Doppler, the non-relativistic relation is seen to be confirmed, within the reported experimental accuracies, to the same degree as the standard relativistic relation. Higher values of the speed of the emitter would be required to examine further the claimed confirmations. For those reports involving saturation spectroscopy, there is much confusion over the appropriate Doppler relation to be used, together with some serious analytical flaws. For the two cases that involve transverse Doppler, there are seen to be either serious faults in the theoretical part, or intrusion from the first order effect. Therefore, the reported conclusions - that the results for the experiments confirm the relativistic SR relation - cannot be justified by any of the experimental works.

Approximately 20% of the world's population resides in coastal areas at risk of rising sea levels due to climate change. This could lead to severe weather events and ecological impact on critical infrastructure. To combat the effects of water-based environmental forces on the land, hard engineering methods such as seawalls have been utilized. However, a more sustainable solution is emerging in nature-based engineering, which involves growing vegetation. This approach can help extend the lifespan of existing technology and provide climate change adaptation and resilience for coastal and riverine communities. The following paper will review seaweed farms as an advanced nature-based mitigation approach. The paper also outlines the findings of experiments at RWTH Aachen University's hydraulic laboratory. These tests involved using seaweed as a natural solution to dampen waves in a model system to test a hypothesis. One result involving a system with two lines of seaweed revealed 15 percent wave damping. Using seaweed as a nature-based solution, a gentle engineering approach to designing future vegetated protection systems can extend the design life of existing coastal infrastructure. This can also provide protection against climate-induced sea level rise, promote coastal risk mitigation, restore ecosystems, and foster blue bio-economic development.

Food insecurity is a multidimensional concept adequately challenging not only the complex operationalization effort but also judgments of who is food secure and who is not. This study aimed to assess the level of household food insecurity in the study area. Both probability and non-probability sampling procedures were employed to draw the 367 respondents, key informants, and focus group discussants. The Consolidated Approach for Reportig Indicators (CARI) console model was constructed with four indicators: Food consumption score, Food energy shortfall, Food expenditure share, and Livelihood asset depletion. Descriptive statistics was used to analyze data in the models. The CARI result revealed that 41.1%, 9.3%, 20.4% and 29.2% of households were food secure, marginally food secure, moderately food insecure and severely food insecure, respectively. The overall prevalence showed that 49.6% households were food insecure and 50.4% were food secure. Moreover, female-headed households and households living the Belg and CHV livelihood zones were more food insecure than their counterparts. The study concluded that the problem of food insecurity is pervasive in the study area in general and Belg and CHV livelihood zones, in particular. Therefore, more attention and intervention should be given by policymakers and concerned development partners to alleviate the problem.

Cartilage degeneration is a characteristic of osteoarthritis (OA) which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties, primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying potential solutions could have significant economic and societal implications, ultimately enhancing the quality of life. This review provides an overview of developments in the field of AC, focusing on its mechanical and tribological properties. The emphasis is on the role of lubrication in degraded AC, offering insights into its structure and function relationship. Further it explores the fundamental connection between AC mechano-tribological properties and the advancement of its degradation and puts forth recommendations for strategies to boost its lubrication efficiency.