Under the quaternion group, $Q_8$, spin helicity emerges as an element of reality, and complementary to spin polarization. Here we show that the correlation in EPR coincidence experiments is conserved upon separation from a singlet, being divided between polarization and coherence. Including helicity accounts for the violation of Bell's Inequalities without non-locality.

This paper deals with developing a new class of quaternions, called hyper-dual Horadam quaternions which are constructed from the quaternions whose components are hyper-dual Horadam numbers. We investigate the algebraic properties of these quaternions.

Multi-level direct networks fueled by the evolving technology of active optical cables and increasing pin-bandwidth achieve reduced diameters and cost, with high-radix switches. These networks, like Dragonfly, are becoming the preferred aspirants for extreme high-performance parallel machines such as exa-scale computing. In this paper, we introduce a Hyper Z-Tree topology, which deploys the Z-Tree, a variant of fat-tree, as a computing node of a Generalized Hypercube (GHC) configuration. The resulting configuration provides higher bisection bandwidth, lower latency for some applications and higher throughput. Furthermore, the levels of the fat tree offer several path diversities across the GHC dimensions, hence conceding a more fault tolerant architecture. To profit from these path diversities, we propose two adaptive routing algorithms, which are extensions to the routing algorithm suggested in HyperX topology. These two algorithms exhibit better latencies and throughput than the HyperX.

We examine the extensions of the basic arithmetical operations of addition and multiplication on the natural numbers into higher-rank hyper-operations also on the natural numbers. We go on to define the concepts of prime and composite numbers under these hyper-operations and derive some results about factorisation, resulting in fundamental theorems analogous to the Fundamental Theorem of Arithmetic.

The separation of microparticles with respect to different properties such as size and material is a research field of great interest. Dielectrophoresis, a phenomenon which is capable of addressing multiple particle properties at once, can be used to perform a chromatographic separation. However, the selectivity of current dielectrophoretic particle chromatography (DPC) techniques is limited. Here we show a new approach for DPC based on differences in the dielectrophoretic mobilities and the crossover frequencies of polystyrene particles. Both differences are addressed by modulating the frequency of the electric field to generate positive and negative dielectrophoretic movement to achieve multiple trap and release cycles of the particles. A chromatographic separation of different particle sizes revealed a voltage dependency of this method. Additionally, we showed the frequency bandwidth influence on separation using one example. The DPC method developed was tested with model particles but offers possibilities to separate a broad range of plastic and metal microparticles or cells and to overcome currently existing limitations in selectivity.

We discuss the renormalization of the polarizability of a nanoparticle in the presence of either (i) a continuous graphene sheet or (ii) a plasmonic graphene grating, taking into account retardation effects. Our analysis demonstrates that the excitation of surface plasmon-polaritons in graphene produces a large enhancement of the real and imaginary parts of the renormalized polarizability. We show that the imaginary part can be changed by a factor of up to 100 relatively to its value in the absence of graphene. We also show that the resonance in the case of the grating is narrower than in the continuous sheet. In the case of the grating it is shown that the resonance can be tuned by changing the grating geometric parameters.

In this paper, a controlled-phase-flip (P-CPF) gate using the polarisation and orbital angular momentum degrees of freedom for single-photon two-qubit quantum logic is proposed. This is critical to the realisation of quantum cluster states and graph networks using transverse degrees of freedom. A generalisation of the proposed scheme to arbitrary number and kinds of degrees of freedom, for optical systems, as well as arbitrary operations to be conditionally performed is proposed.

Many combinatorial optimization problems are hard to solve within the polynomial computational time or NP-hard problems. Therefore, developing new optimization techniques or improving existing ones still grab attention. This paper presents an improved variant of the Ant Colony Optimization meta-heuristic called Enhanced Hyper Cube Framework ACO (EHCFACO). This variant has an enhanced exploitation feature that works through two added local search movements of insertion and bit flip. In order to examine the performance of the improved meta-heuristic, a well-known structural optimization problem of laminate Stacking Sequence Design (SSD) for maximizing critical buckling load has been used. Furthermore, five different ACO variants were concisely presented and implemented to solve the same optimization problem. The performance assessment results reveal that EHCFACO outperforms the other ACO variants and produces a cost-effective solution with considerable quality.

Using density functional theory (DFT) and the information-theoretic approach (ITA) quantities to appreciate the energetics and properties of biopolymers is still an unaccomplished and ongoing task. To this end, we studied the building blocks of nucleic acid base pairs and small peptides. For base pairs, we have dissected the relative importance of energetic components by using two energy partition schemes in DFT. Our results convincingly show that the exchange-correlation effect predominantly governs the molecular stability of base pairs while the electrostatic potential plays a minor but indispensable role, and the steric effect is trivial. Furthermore, we have revealed that simple density-based ITA functions are in good relationships with molecular polarizabilities for a series of 30 hydrogen-bonded base pairs and all 20 natural α-amino acids, 400 dipeptides, and 8000 tripeptides. Based on these lines, one can easily predict the molecular polarizabilities of larger peptides, even proteins as long as the total molecular wavefunction is available, rather than solving the computationally demanding coupled-perturbed Hartree-Fock (CPHF) equation or its DFT counterpart coupled-perturbed Kohn-Sham (CPKS) equation.

Timely processing of observations from hyper-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances for the physical retrieval of surface temperature and emissivity. The new radiative transfer model improves computational time by a factor of ≈ 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the simultaneous retrieval of surface temperature and emissivity in three infrared channels (8.7, 10.8, 12 μm). The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e. average differences are generally well below 0.01.

The identification of bloodstain is one of the most important approaches in obtaining evidence in criminalistics. A threshold method based on spectral co-efficient and interclass variance is proposed in this paper, it is a non-contact, non-destructive method for quickly identifying bloodstains. The spectra of bloodstains and other suspected substances were all extracted from their hyper-spectral image. Then calculate the correlation coefficients of these spectral and interclass variances, analyze the differences between substances. The best blood recognition threshold was determined as 0.9. After preprocessing for eliminating systematic errors, experiments with the threshold 0.9 are carried out to identify bloodstains on the calico and red T-shirt. The method can remarkably identify the bloodstain from other non-blood substances both quickly and efficiently. The blood extraction rate can reach to 93.35% and 89.19%, respectively. It is an important step toward the implementation of bloodstain non-contact and non-destructive identification in forensic casework.

Hyper-spectral imaging provides the possibility of describing specific characteristics of materials in air, land and water depending on reflections of each material in a specific zone of the electromagnetic spectrum. Hyper-spectral sensors capture images in continuous and narrow spectral bands in the visible, near-infrared, and mid-infrared spectral regions. These sensors look at objects using a large part of the electromagnetic spectrum. Some objects have unique characteristics in certain electromagnetic spectrums. These spectral signatures, known as "spectral signatures," help to identify materials in images. But the main problem with these sensors is that the images they get in bad weather conditions and in the presence of dust or rain or snow are of very poor quality. Therefore, we go to SAR images, which are able to form a high-resolution image even in bad weather conditions. The method proposed in this paper is to obtain the final elements of hyper-spectral images using the decomposition method into a multilayer negative matrix. The reason for using this method is that, unlike the high-spectral images that form the image in a number of high-traffic zones, we can create the image in 8 different frequencies, so the most important thing is to get all the hidden information at those frequencies. And also, we compare between the RDA, SENMAV, OMP, ISMA and ADMM algorithms.

The Hyper-Torus Universe Model (HTUM) proposes a novel framework to unify quantum mechanics, cosmology, and consciousness. This paper introduces HTUM's core concept: a higher-dimensional hyper-torus encompassing all possible states of existence. HTUM suggests that the universe functions as a quantum system where all outcomes are inherently connected, with consciousness playing a significant role in actualizing reality. The model introduces several key innovations, including the universe's 4-dimensional toroidal structure (4DTS), providing a new geometric interpretation of spacetime. HTUM presents dark matter and dark energy as nonlinear probabilistic phenomena within this toroidal framework, offering a unique perspective on their nature and interactions. The model proposes a mechanism for wave function collapse through universal self-observation, bridging quantum mechanics and gravity. It introduces a Topological Vacuum Energy Modulator (TVEM) function, offering a potential resolution to the cosmological constant problem. Furthermore, HTUM integrates consciousness as a fundamental aspect of the universe, influencing quantum state actualization and potentially resolving the hard problem of consciousness. The model explores the implications of a timeless singularity and the emergence of time as a product of causal relationships within the toroidal structure. This framework addresses critical challenges in modern physics, including the nature of quantum entanglement, the origin and fate of the universe, and the relationship between mind and matter. The paper discusses the mathematical formulation of HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. We present detailed predictions for the cosmic microwave background (CMB) power spectrum, gravitational wave signatures, and large-scale structure formation, demonstrating how HTUM differs from the standard ΛCDM model. Our analysis reveals distinctive oscillatory patterns in the relative difference between HTUM and ΛCDM predictions, with deviations reaching up to ±20% at certain scales. The paper also explores the unification of fundamental forces within the HTUM framework, proposing novel approaches to particle physics and quantum field theory. It introduces the concept of unified mathematical operations, suggesting a more holistic approach to mathematical thinking that aligns with the model's interconnected view of the universe. Additional testable predictions and proposed experimental approaches are discussed, including advanced space-based tests and laboratory experiments probing quantum gravity effects. These specific, quantifiable predictions offer multiple avenues for empirical validation, highlighting HTUM's potential to be distinguished from ΛCDM and other alternative cosmological models. HTUM represents a significant new perspective in our understanding of the universe, inviting further research and exploration into the nature of reality, consciousness, and the fundamental structure of the cosmos. By providing a comprehensive framework that unifies various aspects of physics, cosmology, and consciousness studies, HTUM offers a promising path toward a more complete understanding of our universe.

This paper reports a new global Mittag-Leffler synchronization criterion with regard to fractional-order hyper-chaotic financial systems by designing the suitable impulsive control and the state feedback controller. The significance of this impulsive synchronization lies in the fact that the backward economic system can synchronize asymptotically with the advanced economic system under the effective impulse macroeconomic management means. Matlab LMI-toolbox is utilized to deduce the feasible solution in numerical example, which shows the effectiveness of the proposed methods. It is worth mentioning that the LMI-based criterion usually requires the activation function of the system to be Lipschitz, but the activation function in this paper is fixed and truly nonlinear, which cannot be assumed to be Lipschitz continuous. This is another mathematical difficulty overcome in this paper.

In a continuation and extension of an earlier publication, the calculation of the refractivity and polarizability of organic molecules at standard conditions is presented, applying a commonly applicable computer algorithm based on an atom-group additivity method, where the molecules are broken down into their constituting atoms, these again being further characterized by their immediate neighbor atoms. The calculation of their group contributions, carried out by means of a fast Gauss–Seidel fitting calculus, used the experimental data of 5988 molecules from literature. An immediate subsequent ten-fold cross-validation test confirmed the extraordinary accuracy of the prediction of the molar refractivity, indicated by a correlation coefficient R^2 and a cross-validated analog Q^2 of 0.9997, a standard deviation σ of 0.38, a cross-validated analog S of 0.41, and a mean absolute deviation of 0.76%. The high reliability of the predictions has been exemplified with three classes of molecules: ionic liquids, silicon- and boron-containing compounds. The corresponding molecular polarizabilities have been calculated indirectly from the refractivity using the inverse Lorentz-Lorenz relation. In addition, it could be shown that there is a close relationship between the "true" volume and the refractivity of a molecule, revealing an excellent correlation coefficient R^2 of 0.9645 and a mean absolute deviation of 7.53%.

In this paper, a relatively new hyper convolution spectra for characterization liquid, viscoelastic and solid samples is presented. Special attention is paid to the biophysical characterization of epithelial tissues and early detection of cancer of the skin, cervix, colon, and oral cavity. The method is based on the use of two types of white light, diffuse and polarized, from the same LED light sources. Based on the subtraction of the intensity values of these two lights and using the hyper convolution algorithm, the ratio of paired and unpaired electrons of tissue is obtained. This ratio correlates well with the state of the tissue: normal, irritating, precancerous, and cancerous. First, a proof-of-concept studies were performed, and later clinical studies on samples from one thousand two hundred fifteen people were performed. It showed that hyper Opto-Magnetic Imaging Spectroscopy (OMIS) can detect epithelial tissue cancers with an accuracy of 85-96%. Bearing in mind that the OMIS method also acquires the biophysical characteristics of the deeper skin layers (epidermis, basement membrane, dermis) by analysing convolution spectra of RGB channels of both diffuse and polarized white light, it is possible to apply this method in cosmetics (skin hydration, collagen, and elastin states, etc.). During OMIS applications, we noticed places where improvements could be made to increase method’s accuracy using advanced machine learning methodologies.

The first hyperpolarizability of graphene quantum dots (GQDs) suspended in water was determined using the hyper-Rayleigh scattering (HRS) technique. To the best of our knowledge, this is the first application of the HRS technique to characterize GQDs. Two commercial GQDs (Acqua-Cyan and Acqua-Green) with different compositions were studied. The HRS experiments were performed with an excitation laser at 1064 nm. The measured hyperpolarizabilities were (1.0±0.1) × 10^(-27) esu and (0.9±0.1) × 10^(-27) esu for Acqua-Cyan and Acqua-Green, respectively. The results were used to estimate the hyperpolarizability per nanosheet obtained by assuming that each GQDs has five nanosheets with 0.3 nm thickness. The two-level model, used to calculate the static hyperpolarizability per nanosheet, provides the values of (2.4±0.1) × 10^(-28) esu (Acqua-Cyan) and (0.5±0.1) × 10^(-28) esu (Aqua-Green). The origin of the nonlinearity is discussed on the basis of polarized resolved HRS experiments, and an electric quadrupolar behavior with a strong dependence on surface effects is found. The nontoxic characteristics and order of magnitude indicate that these GQDs may be useful for biological microscopy imaging.

We have particularly investigated the correlation law of the effect of different carbon black fillings on the hyper-elastic mechanical behavior of natural rubber by conducting uniaxial tensile tests over a wide range of deformations with different volume fractions of carbon black fillings (0%, 4.7%, 8.9%, 12.8%, 16.4%, 19.7%, 22.7%, 25.2%). The results show that the stress-strain curve for carbon black filled rubber increases with the amount of filling, meaning that the rubber gradually becomes "harder". We explore the correlation between the carbon black filling volume and the parameters of the Yeoh constitutive model by examining the Yeoh constitutive model to characterize the hyper-elastic mechanical behavior of rubber with different carbon black fillings. A quantitative relationship between the material parameters and the carbon black filling volume in the Yeoh constitutive model is presented. A method for calculating the material parameters of the Yeoh constitutive model is developed and it predicts the correlation between the hyper-elastic properties of rubber and the volume fraction of carbon black filling.

Hyper spectral imaging (HSI) is a technique that is used to obtain the spectrum for each pixel in the image. It helps in finding objects and identifying materials etc. Such an identification is very difficult using other imaging techniques. It allows the researchers to investigate the documents without any physical contact. Nowadays detection of unequal Ink mismatch based on HSI has shown vast improvement in distinguishing the inks. Detection of unequal Ink mismatch is an unbalanced clustering problem. This paper used K-means Clustering for ink mismatch detection. K-means Clustering find same subgroups in the data based on Euclidean distance. This paper demonstrates performance in unequal Ink mismatch based on HSI.

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

The term Concept has been a prominent part of investigations in psychology and neurobiology where, mostly, it is mathematically or theoretically represented. The Concepts are also studied computationally through their symbolic, distributed and hybrid representations. The majority of these approaches focused on addressing concrete concepts notion, but the view of the abstract concept is rarely explored. Moreover, most computational approaches have a predefined structure or configurations. The proposed method, Regulated Activation Network (RAN), has an evolving topology and learns representations of Abstract Concepts by exploiting the geometrical view of Concepts, without supervision. In the article, the IRIS data was used to demonstrate: the RAN's modeling; flexibility in concept identifier choice; and deep hierarchy generation. Data from IoT's Human Activity Recognition problem is used to show automatic identification of alike classes as abstract concepts. The evaluation of RAN with 8 UCI benchmarks and the comparisons with 5 Machine Learning models establishes the RANs credibility as a classifier. The classification operation also proved the RAN's hypothesis of abstract concept representation. The experiments demonstrate the RANs ability to simulate psychological processes (like concept creation and learning) and carry out effective classification irrespective of training data size.

The soil and groundwater of Bhagobangola I block of Murshidabad district, West Bengal, India is severely arsenic contaminated. A bacterium was isolated from the garden soil of Mahishasthali village, which could tolerate 36.49 mM arsenic (III), 280.44 mM arsenic (V) and 63 mM chromium (III), which makes it arsenic (III & V) and chromium (III) hyper-tolerant bacterium. The growth pattern of this bacterium does not show much alteration in presence of 10 mM arsenic (III) and chromium (III), emphasizing its resistance to these heavy metals. Scanning electron microscopy depicted the size of this bacterium to be ~1.45 µm. 16S rDNA sequencing followed by subsequent phylogenetic analysis established the identity of this bacterium as Microbacterium paraoxydans. The bacterium is capable of bioremediation of arsenic and showed 30.8% & 22.6%, and 35.2% and 30.5% of bioremediation over a period of 24 and 48 hours in 1 mM and 4 mM arsenite, respectively. Microbacterium paraoxydans also exhibit plant growth promoting properties like nitrogen fixation, phosphate solubilization, indole-3-acetic acid production and production of siderophores. Therefore, the heavy metal resistance, bioremediation potential and plant growth promoting potential of the bacterium could be utilized not only for reduction of arsenic toxicity in soil and groundwater but also for plant growth promotion by using it as a biofertilizer.

The increased deployment of IoT devices in specific areas results in an interference among them and the quality of communications can be severely degraded. To deal with this interference issue, the IEEE 802.11ax standard has been established in hyper-densely wireless networking systems. The 802.11ax adopts a new candidate technology that is called multiple network allocation vector in order to mitigate the interference problem. In this paper, we point out potential problem in multiple network allocation vector which can cause delays to the communication among IoT devices in hyper-dense wireless networks. Furthermore, this paper introduces an adaptive beam alignment algorithm for interference issue resolution. In addition, we analyze potential delays of communications among IoT devices under interference conditions. Lastly, we simulate our proposed algorithm in densely deployed environment and show that the interference issue can be mitigated and the IEEE 802.11ax-based IoT devices can utilize the air interface more fairly compared to conventional IEEE 802.11 distributed coordination function.

Background: Laser therapies can cause hyper- and hypopigmentation of the skin. There is little evidence in the literature of effective treatments for these types of problems in Fitzpatrick IV-VI skin phototypes. The main aim of this retrospective study is to evaluate the effects of a new therapy combining the application of electromagnetic fields and vacuum on a subject with Fitzpatrick VI skin phototype, presenting an extensive, laser-induced facial dyschromia. The secondary aim is to test the effectiveness of a free imaging software for assessing skin pigmentation. Methods: The level of improvement after the therapy was evaluated, with a 5-point Likert scale, one month after the end of the treatment by both the subject, and the doctor who performed the treatment, and by two blinded dermatologists. With the free software, a three-dimensional reconstruction of the area treated and the evaluation of colour distribution were performed. Results: Both the subject and the doctors involved in the study positively evaluated the effects of the treatment. The image analysis highlighted the homogenization of the skin colour in the treated area. Conclusions: The combination of electromagnetic fields and vacuum for dyschromia treatments appears promising. The new method of assessing melanin levels resulted particularly efficient.

Type 2 diabetes (T2D) is characterized by hyperglycemia and insulin resistance. Cocoa may slow T2D development and progression. This study employed male and female BTBR.Cg-Lepob/ob/WiscJ and wild type (WT) controls to assess the potential for cocoa to ameliorate progressive T2D and compare responses between sexes. Mice received diet without (WT, ob/ob) or with cocoa extract (ob/ob + c) for 10 weeks. Glucose and insulin tolerance tests (GTT/ITT) were conducted at weeks 1, 5 and 2, 6, respectively. Cocoa provided mild non-significant protection against weight gain vs. ob/ob control in males but not females. Male ob/ob + c had increasing fasting glucose at weeks 1 and 5 GTTs, with significantly higher levels of fasting glucose than ob/ob control at week 5. This was not seen in females. Cocoa protected against elevated 4-hour fasting glucose in week 2, but not week 6, ITTs. Cocoa partly suppressed hyperinsulinemia in males but significantly amplified it in females and protected against loss of beta cell area in females only. The mechanisms of these sex-specific effects remain to be elucidated. This study informs additional experiments with larger sample sizes and demonstrates that sex differences must be considered when designing dietary interventions for T2D.

The Mediterranean basin is a hot spot of climate change where the Posidonia oceanica (L.) Delile (PO) and other seagrass are under stress due to its effect on marine habitats and the rising influence of anthropogenic activities (tourism, fishery). The PO and seabed ecosystems, in the coastal environments of Pantelleria and Lampedusa, suffer additional growing impacts from tourism in synergy with specific stress factors due to increasing vessel traffic for supplying potable water, fossil fuels for electrical power generation. Earth Observation (EO) data, provided by high resolution (HR) multi/hyperspectral operative satellite sensors of the last generation (i.e. Sentinel 2 MSI and PRISMA) have been successfully tested, using innovative calibration and sea truth collecting methods, for monitoring and mapping of PO meadows under stress, in the coastal waters of these islands, located in the Sicily Channel, to better support the sustainable management of these vulnerable ecosystems. The area of interest in Pantelleria was where the first prototype of the Italian Inertial Sea Wave Energy Converter (ISWEC) for renewable energy production was installed in 2015, and sea truth campaigns on the PO meadows were conducted. The PO of Lampedusa coastal areas, impacted by ship traffic linked to the previous factors and tropicalization effects of Italy southernmost climate change transitional zone, was mapped through a multi/hyper spectral EO-based approach, using training/testing data provided by side scan sonar data, previously acquired. Some advanced machine learning algorithms (MLA) were successfully evaluated with different supervised regression/classification models to map seabed and PO meadow classes and related Leaf Area Index (LAI) distributions in the areas of interest, using multi/hyperspectral data atmospherically corrected via different advanced approaches.

The lack of suitable autologous grafts and poor compliance of existing prostheses have prompted the study of novel materials for vascular graft design. Polyurethanes (PUs) were used in the past because they have high compliance and properties that are similar to those of native tissue. In this work, the mechanical properties of a group of PUs in two states (non-hydrated and hydrated) were studied using uniaxial tensile tests, strain sweep tests, and multi-step creep recovery tests. Additionally, a hyper-elastic model based on the Mooney–Rivlin strain density function was fitted and used to model the performances of the PUs under physiological pressure and geometry conditions. The tensile tests revealed a softening phenomenon after hydration, which could potentially reduce patient discomfort and risk of vascular trauma. The ultimate strength values after hydration were similar to those reported for other vascular conduits. The strain sweep showed a strong strain dependency of the modulus indicating non-linear viscoelasticity. In the creep-recovery tests, increasing the polyethylene glycol(PEG) content enhanced the viscous flow, while the elastic behavior was enhanced with the largest concentration of polycaprolactone diol (PCL). On the other hand, under simulated physiological conditions, the compliance of the PUs showed a cyclic behavior with the time and pressure but was not affected by the radii and thickness variation, which could increase the graft compliance and geometry mismatch. Nevertheless, the compliance could be tuned using the material composition. This paper studied the biomechanics of a group of materials under simulated physiological conditions (Temperature, hydration, and pressure) to select those that could perform better for further vascular graft design.

Full waveform (FW) LiDAR holds great potential for retrieving vegetation structure parameters at a high level of detail, but this prospect is constrained by practical factors such as lack of available handy processing tools and technical intricacy of waveform processing. This study introduces a new product, named the Hyper Point Cloud (HPC) derived from FW LiDAR data, and explore its potential applications such as tree crown delineation using the HPC-based intensity and percentile height (PH) surfaces, which show a promising solution to the constraints of using FW LiDAR data. Results of the HPC present a new direction to handle FW LiDAR data and offer prospects for studying the mid-story and understory of vegetation with high point density (~ 182 points/m2). The intensity-derived digital surface model (DSM) generated from the HPC shows that the ground region has larger maximum intensity (MAXI) and mean intensity (MI) than the vegetation region while having smaller total intensity (TI) and number of intensities (NI) at the given grid cell. Our analysis of intensity distribution contours at individual tree level exhibit similar patterns, indicating that the MAXI and MI are decreasing from the tree crown center to tree boundary while a rising trend is observed for TI and NI. These intensity variable contours provide a theoretical justification for using HPC-based intensity surfaces to segment tree crowns and exploit their potential for extracting tree attributes. The HPC-based intensity surfaces and the HPC-based PH Canopy Height Models (CHM) demonstrate promising tree segmentation results comparable to the LiDAR derived CHM for estimating tree attributes such as tree locations, crown widths and tree heights. We envision that products such as the HPC and the HPC-based intensity and height surfaces introduced in this study can open new perspectives to use FW LiDAR data and alleviate the technical barrier of exploring FW LiDAR data for detailed vegetation structure characterization.

This paper introduces new improvements to the modified version of the BIRECT (BI secting RECTangles) algorithm referred to as BIRECTv. We explore various approaches, by first including a grouping strategy for hyper-rectangles having almost the same sizes by categorizing them into different classes. Therefore constraining them not to exceed a certain pre-defined threshold (a small positive value to define the tolerance level). This approach allows for more efficient computation and can be particularly useful when dealing with a large number of hyper-rectangles with varying sizes. To avoid over-sampling, and preventing redundant or excessive sampling, at some shared vertices in descendant subregions, a particular vertex database is used to limit the number of samples taken within each subregion to two. The experimental investigation shows that these improvements have a positive impact on the performance of the BIRECTv(imp.) algorithm and the proposal is a promising global optimization algorithm compared to the original BIRECTv algorithm and its variants. Additionally, the BIRECTv(imp.) algorithm showed particular efficacy in solving high-dimensional problems.

In this research, the neutrosophic SuperHyperNotion, namely, neutrosophic SuperHyperGirth, is up. $E_1$ and $E_3$ are some empty neutrosophic SuperHyperEdges but $E_2$ is a loop neutrosophic SuperHyperEdge and $E_4$ is an neutrosophic SuperHyperEdge. Thus in the terms of neutrosophic SuperHyperNeighbor, there's only one neutrosophic SuperHyperEdge, namely, $E_4.$ The neutrosophic SuperHyperVertex, $V_3$ is neutrosophic isolated means that there's no neutrosophic SuperHyperEdge has it as an neutrosophic endpoint. Thus the neutrosophic SuperHyperVertex, $V_3,$ is excluded in every given neutrosophic SuperHyperGirth. $ \mathcal{C}(NSHG)=\{E_i\}~\text{is an neutrosophic SuperHyperGirth.} \ \ \mathcal{C}(NSHG)=jz^i~\text{is an neutrosophic SuperHyperGirth SuperHyperPolynomial.} \ \ \mathcal{C}(NSHG)=\{V_i\}~\text{is an neutrosophic R-SuperHyperGirth.} \ \ \mathcal{C}(NSHG)=jz^I~{\small\text{is an neutrosophic R-SuperHyperGirth SuperHyperPolynomial.}} $ The following neutrosophic SuperHyperSet of neutrosophic SuperHyperEdges[SuperHyperVertices] is the neutrosophic type-SuperHyperSet of the neutrosophic SuperHyperGirth. The neutrosophic SuperHyperSet of neutrosophic SuperHyperEdges[SuperHyperVertices], is the neutrosophic type-SuperHyperSet of the neutrosophic SuperHyperGirth. The neutrosophic SuperHyperSet of the neutrosophic SuperHyperEdges[SuperHyperVertices], is an neutrosophic SuperHyperGirth $\mathcal{C}(ESHG)$ for an neutrosophic SuperHyperGraph $ESHG:(V,E)$ is an neutrosophic type-SuperHyperSet with the maximum neutrosophic cardinality of an neutrosophic SuperHyperSet $S$ of neutrosophic SuperHyperEdges[SuperHyperVertices] such that there's only one neutrosophic consecutive sequence of the neutrosophic SuperHyperVertices and the neutrosophic SuperHyperEdges form only one neutrosophic SuperHyperCycle. There are not only four neutrosophic SuperHyperVertices inside the intended neutrosophic SuperHyperSet. Thus the non-obvious neutrosophic SuperHyperGirth isn't up. The obvious simple neutrosophic type-SuperHyperSet called the neutrosophic SuperHyperGirth is an neutrosophic SuperHyperSet includes only less than four neutrosophic SuperHyperVertices. But the neutrosophic SuperHyperSet of the neutrosophic SuperHyperEdges[SuperHyperVertices], doesn't have less than four SuperHyperVertices inside the intended neutrosophic SuperHyperSet. Thus the non-obvious simple neutrosophic type-SuperHyperSet of the neutrosophic SuperHyperGirth isn't up. To sum them up, the neutrosophic SuperHyperSet of the neutrosophic SuperHyperEdges[SuperHyperVertices], isn't the non-obvious simple neutrosophic type-SuperHyperSet of the neutrosophic SuperHyperGirth. Since the neutrosophic SuperHyperSet of the neutrosophic SuperHyperEdges[SuperHyperVertices], is an neutrosophic SuperHyperGirth $\mathcal{C}(ESHG)$ for an neutrosophic SuperHyperGraph $ESHG:(V,E)$ is the neutrosophic SuperHyperSet $S$ of neutrosophic SuperHyperVertices[SuperHyperEdges] such that there's only one neutrosophic consecutive neutrosophic sequence of neutrosophic SuperHyperVertices and neutrosophic SuperHyperEdges form only one neutrosophic SuperHyperCycle given by that neutrosophic type-SuperHyperSet called the neutrosophic SuperHyperGirth and it's an neutrosophic SuperHyperGirth . Since it 's the maximum neutrosophic cardinality of an neutrosophic SuperHyperSet $S$ of neutrosophic SuperHyperEdges[SuperHyperVertices] such that there's only one neutrosophic consecutive neutrosophic sequence of neutrosophic SuperHyperVertices and neutrosophic SuperHyperEdges form only one neutrosophic SuperHyperCycle. There are only less than four neutrosophic SuperHyperVertices inside the intended neutrosophic SuperHyperSet, thus the obvious neutrosophic SuperHyperGirth, is up. The obvious simple neutrosophic type-SuperHyperSet of the neutrosophic SuperHyperGirth, is: ,is the neutrosophic SuperHyperSet, is: does includes only less than four SuperHyperVertices in a connected neutrosophic SuperHyperGraph $ESHG:(V,E).$ It's interesting to mention that the only simple neutrosophic type-SuperHyperSet called the neutrosophic SuperHyperGirth amid those obvious[non-obvious] simple neutrosophic type-SuperHyperSets called the neutrosophic SuperHyperGirth , is only and only. A basic familiarity with neutrosophic SuperHyperGirth theory, SuperHyperGraphs, and neutrosophic SuperHyperGraphs theory are proposed.

The expansion of copper mining on the hyper-arid pacific slope of southern Peru has precipitated growing concern for scarce water resources in the region. Located in the headwaters of the Torata river, in the department of Moquegua, the Cuajone mine, owned by Southern Copper, provides a unique opportunity, in a little-studied region, to examine the relative impact of the landscape-scale mining on water resources in the region. Principal component analysis and cluster analysis of the water chemistry data from 16 sites, collected over three seasons during 2017 and 2018, show distinct statistical groupings indicating that, above the settlement of Torata, water geochemistry is a function of chemical weathering processes acting upon underlying geological units, and confirming that the Cuajone mine does not significantly affect water quality in the Torata river. Impact mitigation strategies that firstly divert channel flow around the mine and secondly divert mine waste to the Toquepala river and tailings dam at Quebrada Honda, below the Toquepala mine, in the department of Tacna, secure water quality in the Torata river for the foreseeable future. In the greater Moquegua river catchment, our results further suggest that water quality has been more significantly impacted by urban effluents and agricultural runoff than the Cuajone mine. The increase in total dissolved solids in the waters of the lower catchment reflects the cumulative addition of dissolved ions through chemical weathering of the underlying geological units, supplemented by rapid recharge of surface waters contaminated by residues associated with agricultural and urban runoff through the porous alluvial aquifer. Concentrations in some of the major ions exceeded internationally recommended maxima for agricultural use, especially in the coastal region. Occasionally, arsenic and manganese contamination also reached unsafe levels for domestic consumption. In the lower catchment, below the Cuajone mine, data and multivariate analyses point to urban effluents and agricultural run-off rather than weathering of exposed rock units, natural or otherwise, as the main cause of contamination.

Excessive extracellular histones can damage cells despite their importance in DNA structure and gene regulation. We previously showed the harmful effect of histone 3.3 (H3.3) and its acetylated form (AcH3.3) in chronic obstructive pulmonary disease (COPD), but further research is needed to understand the in vivo underlying mechanisms. To investigate this, we administered a single dose of recombinant histones via intra-tracheal instillation in C57BL/6 mice and analyzed the outcomes after 48 hours. Both rH3.3 and rAcH3.3 effectively reached the bronchial and alveolar space. Lung histology revealed severe immune cell infiltration, rupture, damage, and thickening of many alveolar walls. Micro-CT scans showed macroscopic structure changes with a decreased tissue volume to total volume ratio. The administration of rH3.3 and rAcH3.3 induced lung apoptotic activity, as indicated by increased levels of cleavage caspase 3 and 9. Moreover, elevated plasma levels of pro-inflammatory cell mediators, including TNF-alpha, IL-6, MCP-3, and CXCL-1, were observed. The pathological changes and pro-inflammatory cytokine response were more pronounced in animals treated with rAcH3.3, which also exhibited leukocytosis and lymphocytosis. These findings emphasize the crucial role of extracellular H3.3 acetylation in inducing cytotoxicity and a robust, acute inflammatory response similar to what occurs in the lungs of COPD patients.

The proper hydrogenation of Hyper-coal (HPC) using 1, 2, 3, 4-tetrahydroquinoline (THQ) was able to decrease the oxygen content and adjust the molecular structure of HPC for preparing the spinnable pitch with high softening point (SP). The spinnable pitch prepared from the THQ-soluble (QS) fraction of HPC as a precursor consisted more naphthenic carbon groups than that prepared from the 1-methylnaphthalene (1-MN) soluble (MNS) fraction of HPC. The HPC-QS derived pitch showed excellent spinnability even the SP of 260°C, and the tensile strength of the resultant carbon fiber was up to 1350 MPa with a diameter around 8 µm by only heat treatment at 800°C for 5 min.

U-Net, based on a deep convolutional neural network (CNN), has been clinically used to au-to-segment normal organs and potentially target volumes. However, CNNs with local geometric dependencies may limit the accuracy of segmentation. Additionally, the performance of CNNs can vary depending on the selection of network hyper-parameters, which was mitigated by the proposition of nnU-Net. We chose a vision transformer architecture called VT U-Net, which features a self-attention excluding the convolution layer, to overcome the limitations of CNNs by utilizing global geometric information of images. The VT U-Net v.2 became more powerful thanks to the adaptive hyper-parameter optimizer embedded in nnU-Net. However, despite leveraging the benefits of nnU-Net, VT U-Net v.2 still had additional network hyper-parameters that needed to be optimally chosen. Accordingly, among various hyper-parameters, this study attempted to find the optimal combination of the patch size and the embedded dimension regarding the transformer. From the 4-fold cross-validation, the modified VT U-Net v.2 showed the highest average performance for planning target volume (PTV) segmentation among the investigated networks. Though nnU-Net was based on convolution layers, the adaptive hyper-parameter optimizers turned out to enhance the performance. It was also confirmed that network hyper-parameters affected the segmentation accuracy of vision transformers.

The reconstruction of land use practices in hyper arid Saharan Africa is often hampered by the accuracy of the available tools and by unconscious biases that see these areas as marginal and inhospitable. Considered for a long time the living space of pastoral mobile communities, new research is showing of agriculture might have been more important in these areas than previously thought. In this paper, after a review of present-day land use strategies in Saharan Africa, we show how ethnographic and ethnoarchaeological data can offer us a different point of view and help in better defining land use and food production strategies in this area. Ultimately, these insights can be integrated into the ongoing effort of reconstructing past land use globally.

The hyper-arid environment is characterized by high inter-annual climatic fluctuations. The yearly average rainfall can change substantially for several years, forming wet or dry sub-periods. Observing rainfall trends over a sub-period can lead to a false perception of a change in the trend but may in fact represent a periodic cycle when examined on a larger time scale. We aimed to better characterize the rainfall regime prevailing in the hyper-arid Arava Valley (Israel/Jordan), and to examine the response of vegetation to annual rainfall. We hypothesized that annual and perennial vegetation would respond differently to wet and dry sub-periods, and that grazing activities will impact vegetation growth. We used a time series of monthly rainfall, from which we calculated Standard Precipitation Index (SPI), and calculated proxies of perennial and annual vegetation over the last four decades using Landsat-derived Normalized Difference Vegetation Index (NDVI). We found no clear trend in rainfall amounts during this period, however we did identify wet and dry sub-periods which were statistically distinct in rain and in vegetation patterns from each other. The highest levels of correlation between rainfall and the NDVI derived proxies were found when examining average rainfall over a period of two- three years for the annual vegetation and over four years for perennial vegetation. Using the Mann-Kendall test, we identified a time lag of two to four years, with the proxies of annual vegetation responding faster than the proxies of perennial vegetation, to shifts between wet and dry sub-period. In addition, we found a consistent difference between natural vegetation cover in Jordan (grazed) and Israel (non-grazed), favoring the development of natural vegetation on the Israeli side. We conclude that integrating between long-term remote sensing satellite imagery and climatic records revealed the greater resilience of perennial vegetation in the hyper-arid region to climatic fluctuation, and enabled us to identify the vegetation’s sensitivity to anthropogenic impact.

Osmotic demyelination syndrome (ODS) is an acute demyelinating disorder characterized by the loss of myelin in the center of the basis pons which is defined as central pontine myelinolysis (CPM) and demyelination process in locations outside the pons which is defined as extrapontine myelinolysis (EPM). ODS including CPM and EPM is mainly caused by the rapid correction of hyponatremia. However, there are several reports of ODS in medical condition such as malnutrition, alcoholism, liver transplantation, malignancy, sepsis, electrolyte imbalance including hypernatremia, hypokalemia, hypophosphatemia, and chronic illness. Rarely, ODS was reported in patients with hyperammonemia or hyperbilirubinemia without sodium fluctuations. The symptoms usually correspond to the lesion site and EPM precedes CPM. Because ODS may be irreversible, prevention is more important. Here, we report a case of ODS secondary to the hyperammonemia and hyperbilirubinemia, as it can have unfavorable prognosis.

An association between subtle changes in T2 white matter hyper-intense signals (WMHS) de-tected in fetal brain magnetic resonance imaging (fbMRI) and congenital cytomegalovirus (CMV) infection has been established. The research aim of this study is to compare children with congenital CMV infection with neurodevelopment outcome and hearing deficit with and with-out WMHS in a prospective historic cohort of 58 fbMRIs. Of these, WMHS was detected in 21. The median infection week of the WMHS group was earlier than the normal fbMRI group (8 and 17 weeks of gestation respectively). The proportion of infants treated with valganciclovir in the WMHS group was distinctly higher. Hearing impairment was not significantly different be-tween the groups. VABS scores in all 4 domains were within normal range in both groups. The median score of the motor skills corrected for week of infection was better in the WMHS group. A multivariate analysis using week of infection interaction variable of WMHS and valganciclo-vir treatment showed better motor score outcomes in the valganciclovir treatment group despite earlier week of infection. WMHS was not associated with neurodevelopmental outcome and hearing deficit. In our cohort valganciclovir treatment may have a protective effect on fetuses with WMHS by improving neurodevelopment outcome.

Vascular endothelial growth factors (VEGFs) are regarded as the key vasculogenic mediators in the human body, of which VEGF-A is considered as one of the important types. It is the major growth factor possessing increasing vascular permeability as well as angiogenesis properties. This article provides intuition into the different effects of VEGF-A on vessels in ovarian hyper stimulation syndrome (OHSS) which is defined as a complication of in-vitro fertilization for infertility treatment, and obesity, a universally health problem. These are two dissimilar pathways outcomes for VEGF-A effects, thereby This article reviews updated information about the mentioned disorders and reveals that how this kind of growth factor yields different results on vasculature by activating distinct intracellular signaling in endothelial cells.

Malaria remains a major public health problem worldwide, with eradication efforts thwarted by drug and insecticide resistance and the lack of a broadly effective malaria vaccine. In continuously exposed communities, polyclonal infections are thought to reduce the risk of severe disease and promote the establishment of asymptomatic infections. We sought to investigate the relationship between the complexity of P. falciparum infection and underlying host adaptive immune responses in an area with high prevalence of asymptomatic parasitaemia in Cameroon. A cross-sectional study of 353 individuals aged 2 to 86 years (median age = 16 years) was conducted in five villages in the Centre Region of Cameroon. Plasmodium falciparum infection was detected by multiplex nested PCR in 316 samples, of which 278 were successfully genotyped. Of these, 60.1% (167/278) were polyclonal infections, the majority (80.2%) of which were from asymptomatic carriers. Host-parasite factors associated with polyclonal infection in the study population included peripheral blood parasite density, participant age and village of residence. The number of parasite clones per infected sample increased significantly with parasite density (r = 0.3912, p<0.0001) but decreased with participant age (r = -0.4860, p<0.0001). Parasitaemia and number of clones per sample correlated negatively with total plasma levels of IgG antibodies to three highly reactive P. falciparum antigens (MSP-1p19, MSP-3 and EBA175) and two soluble antigen extracts (merozoite and mixed stage antigens). Surprisingly, we observed no association between the frequency of polyclonal infection and susceptibility to clinical disease as assessed by the recent occurrence of malarial symptoms or duration since the previous fever episode. Overall, the data indicate that in areas with high perennial transmission of P. falciparum, parasite polyclonality is dependent on underlying host adaptive immune responses, with the majority of polyclonal infections occurring in persons with low levels of protective anti-plasmodial antibodies.

Hyper duplex stainless steels, HDSS, are a new alloy group of duplex stainless steels with the highest corrosion resistance and mechanical properties among the existing modern stainless steel. Due to the addition of extra high content of alloying elements, e.g. Cr, Ni, Mo, etc., the crystallization behavior of the δ-ferrite from the liquid is of vital importance for controlling the steel properties. In this work, the effect of cooling rate (i.e. 4°C/min and 150 °C/min) on the growth process of δ-ferrite in S33207 during the solidification process was investigated using high-temperature confocal scanning laser microscopy (HT-CLSM) in combination with electron microscopes and thermodynamic calculation. The results showed that the solidification mode of S33207 steel was a ferrite-austenite type (FA mode). L→δ transformation occurred at a certain degree of supercooling, and merging occurred during the growth of δ phase dendrites. Similar microstructures were observed after solidification under these two different cooling rates. The variation of area fraction of δ ferrite at the free surface and temperature as well as time during solidification of S33207 steels were calculated at different cooling rates of 4 °C/min and 150 °C/min, respectively. The current HT-CLSM study provides in-situ experimental evidence to confirm that a low cooling rate favored the growth of primary δ-ferrite, whereas a high cooling rate favored the nucleation of primary δ-ferrite during the solidification process. The post-microstructure as well as composition evolution is also briefly investigated. This work shed light on the real time insights for the crystallization behavior of hyper duplex stainless steels during solidification, which aims to contribute to the process control of manufacturing of this steel grade.

This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and is relevant to satellite calibration/validation and the creation of new remote sensing data products. A case study is described for the rapid characterisation of the aquatic environment, over a period of just a few minutes we acquired thousands of training data points. This training data allowed our machine learning algorithms to rapidly learn by example and provide wide area maps of the composition of the environment. Along side these larger autonomous robots two smaller robots that can be deployed by a single individual were also deployed (a walking robot and a robotic hover-board), observing significant small scale spatial variability.

Microarray gene expression analysis is a powerful technique used in cancer classification and research to identify and understand gene expression patterns that can differentiate between different cancer types, subtypes, and stages. However, microarray databases are highly redundant, inherently nonlinear, and noisy. Therefore, extracting meaningful information from such a huge database is a challenging one. The paper adopts the Fast Fourier Transform (FFT) and Mixture Model (MM) for dimensionality reduction and utilizes the Dragonfly optimization algorithm as the feature selection technique. The classifiers employed in this research are Nonlinear Regression, Naïve Bayes, Decision Tree, Random Forest and SVM (RBF). The classifiers' performances are analyzed with and without feature selection methods. Finally, Adaptive Moment Estimation (Adam) and Random Adaptive Moment Estimation (RanAdam) hyper-parameter tuning techniques are used as improvisation techniques for classifiers. The SVM (RBF) classifier with the Fast Fourier Transform Dimensionality Reduction method and Dragonfly feature selection achieved the highest accuracy of 98.343% with RanAdam hyperparameter tuning compared to other classifiers.

Hyper-radiosensitivity (HRS) is the increased sensitivity to low doses of ionizing radiation observed in most cell lines. We previously demonstrated that HRS is permanently abolished in cells irradiated at a low dose rate (LDR), in a mechanism dependent on transforming growth factor β3 (TGF-β3). In this study, we aimed to elucidate the activation and receptor binding of TGF-β3 in this mechanism. T-47D cells were pre-treated with inhibitors of potential receptors and activators of TGF-β3, along with addition of small extracellular vesicles (sEVs) from LDR primed cells, before their radiosensitivity was assessed by the clonogenic assay. The protein content of sEVs from LDR primed cells was analyzed with mass spectrometry. Our results show that sEVs contain TGF-β3 regardless of priming status, but only sEVs from LDR primed cells remove HRS in reporter cells. Inhibition of the matrix metalloproteinase (MMP) family prevents removal of HRS, suggesting an MMP-dependent activation of TGF-β3 in the LDR primed cells. We demonstrate a functional interaction between TGF-β3 and activin receptor like kinase 1 (ALK1), by showing that TGF-β3 removes HRS through ALK1 binding, independent of ALK5 and TGF-βRII. These results are an important contribution to a more comprehensive understanding of the mechanism behind TGF-β3 mediated removal of HRS.

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.

This study focuses on the modification of ion-exchange membranes by incorporating phosphorylated dendrimer into sulfonated polytetrafluoroethylene membranes to enhance specific selectivity between mono-/divalent ions, using the Ca2+/Na+ pair as an example. The research employs mechanical, physico-chemical, and electrochemical analyses to explore the effects of P-H20 incorporation on membrane properties. Bulk modification significantly increases membrane selectivity towards calcium ions (specific permselectivity coefficient rises from 1.5 to 7.2), while maintaining the same level of the limiting current density. Other findings indicate that bulk modification significantly changes the transport-channel structure of the membrane and alters the mechanism of over-limiting mass transfer. The over-limiting current for the pristine membrane is mainly due to non-equilibrium electroconvection, while modified membranes actively participate in the water-splitting reaction, leading to the suppression of the electroconvection. Despite this drawback, the decrease of the over-limiting potential drop results in a decrease in specific energy consumption from 0.11 to 0.07 kWh/mol. In the under-limiting current mode, the specific energy consumption for all studied membranes remains within the same limits of 0.02-0.03 kWh/mol.

Recently, cases of antifreeze poisoning in companion animals, particularly cats, have surged in the Republic of Korea. Ethylene glycol (EG), the toxic primary component of antifreeze, is metabolized into glycolic acid (GA), leading to severe conditions such as metabolic acidosis and acute renal failure. Traditional detection methods, although effective, are often time-consuming owing to complex sample preparation. This study involved a novel analytical method utilizing GC-MS for EG and LC-MS/MS for GA detection, which streamlined the detection process by eliminating the need for derivatization. The method was validated for accuracy and reliability, enabling the rapid and precise identification of EG and GA in biological samples. The study also included the successful application of this method in a case where initial exposure to antifreeze was not apparent, which highlighted the effectiveness of this method in diagnosing poisoning even in cases where clinical history is unclear. The development of this rapid diagnostic approach addresses the urgent need for the efficient detection of antifreeze poisoning, improving animal welfare and supporting forensic investigations.

Conventional approaches in Structural Health Monitoring (SHM) tend to be complex, destructive, and time-intensive. Additionally, they often require a large number of sensors to thoroughly assess structural integrity. In this study, we present a novel, non-destructive SHM framework based on machine learning (ML) for the accurate detection and localization of structural cracks. This approach leverages a minimal number of strain gauge sensors linked via Bluetooth communication. The framework is validated through empirical data collected from 3D carbon fiber-reinforced composites, including three distinct specimens, ranging from crack-free samples to specimens with up to ten cracks of varying lengths and depths. Strain data from five sensors were analyzed using a combination of Shewhart charts, Grubbs Test (GT), and a hierarchical clustering algorithm, specifically designed to evaluate and classify fractures. Our ML-based framework offers a streamlined and efficient alternative to traditional laboratory procedures, delivering precise crack detection with significant potential for applications in the composites industry.

Fall armyworm (FAW), Spodoptera frugiperda, has been causing significant crop losses and has now become the most economically important pest of corn globally. With the challenges arising from the extensive use of synthetic chemicals such as reports that FAW gained resistance to various insecticides, researchers are developing environmentally sound control measures to address these issues. An example is the application of the RNA interference in managing FAW populations. RNA interference is a biological process where dsRNA molecules silence specific gene of interest. Here, dsRNA fragments were generated to target Cytochrome P450 monooxygenases CYP321A7 and CYP321A8 in FAW. Mortality and phenotypic effects of RNAi-mediated knockdown of essential genes of target CYP450s through RNAi in FAW were analyzed. Results showed that RNA in vitro transcription yielded ~14 μg/μL of dsCYP321A7 and dsCYP321A8. The mortality rate of dsCYP321A7- and dsCYP321A8-fed larvae following exposure to insecticide with dual active ingredient of Chlorantraniliprole and Thiamethoxam increased by 90% and 80%, respectively as compared to dsGFP-fed larvae with 40% at 2 days post insecticide exposure. This study provided evidence for the potential of RNAi for FAW management strategies particularly for insecticide-resistant populations, including the potential for biopesticide development.

Cancer ranks second among the causes of mortality worldwide,following cardiovascular diseases.Brain cancer, in particular, has lowest survival rate of any kind of cancer. Brain tumours vary in their morphology, texture, and location, which determine their classification. Accurate diagnosis of the tumour category enables physicians to select optimal treatment strategies and potentially prolong patients’ lives. Researchers who also implemented deep learning models for diagnosing diseases in recent years largely focused on deep neural network optimization to enhance neural network performance. This implicates implementing models with the best performance and incorporating various network architectures by configuring their hyperparameters. This paper presents a novel hybrid approach method for improved brain tumour classification by combining CNN and EfficientNetV2B3 as feature extraction, followed by (KNN) for classification. To evaluate the recommended method’s efficacy, two widely known benchmark MRI datasets were utilized in the experiments. The initial dataset consisted of 3064 MRI images depicting meningiomas,pituitary,and gliomas tumours.Images from two classes of normal brain and brain tumour were included in the second dataset, which was obtained from Kaggle.In order to enhance performance even more, the study concatenates the CNN and EfficientNetV2B3 flattened outputs before feeding them into the KNN classifier. The proposed framework run on two different dataset and demonstrates outstanding performance with an accuracy of 99.51% and 99.8% on each dataset.

Artificial Intelligence (AI) is fundamentally reshaping various industries by enhancing decision-making processes, optimizing operations, and unlocking new opportunities for innovation. This paper explores the applications of AI across four key sectors: healthcare, finance, manufacturing, and retail. Each section delves into the specific challenges faced by these industries, the AI technologies employed to address them, and the measurable impact on business outcomes and societal welfare. We also discuss the implications of AI integration, including ethical considerations, the future trajectory of AI development, and its potential to drive economic growth while posing challenges that need to be managed responsibly.

Background: In our recent publications pertaining to 4G model of final unification and based on strong and electroweak interactions, we have proposed the existence of a weak fermion of rest energy 585 GeV. Objective: To confirm the physical existence of the proposed 585 GeV weak fermion by analyzing weak and strong interactions in a unified approach via 4G model of final unification, super symmetry and string theory. Method: Considering the proposed nuclear charge of 2.95e, proton, electron mass ratio, specific charge ratios of proton and electron, Fermi’s weak coupling constant, Reduced Planck’s constant, nucleon magnetic moments, nuclear stability, nuclear binding energy, nuclear mass and neutron lifetime, it is planned to confirm the physical existence of the proposed 585 GeV weak fermion. Results: All proposed logics and formulae clearly establish the physical existence of 585 GeV weak fermion directly and indirectly. Conclusion: Believing in the physical existence of the proposed 585 GeV weak fermion, there is a scope for observing galactic TeV radiation coming by virtue of annihilation of 585 GeV fermions and radiation associated with various astrophysical acceleration mechanisms of 585 GeV fermions. Appeal: As we are beginners of astrophysics domain, we appeal the science community to see the possibility of considering the proposed 585 GeV weak fermion with a charge of $\pm\left(e\right)$ in place of electron and proton.

Knowledge is not merely the characteristic of certain pieces of information being deemed true, believed and justifiable, but rather a process. The sentences that reaches the status of knowledge forms a universe that provides an interpretation of the reality one aims to describe. Language exchanges information through communication and the justification, if concludes successfully with respect to a sentence, it elevates the information to the status of knowledge. We provide a model where we define the fundamental elements of communication and grammar. As a result, knowledge must be \open\ (everyone must be able to acquire it), \free\ (everyone must be able to justifiy) and \tidy\ (everyone must be able to retrace the justification process in all its parts recursively). Ultimately, the development of knowledge processing, referred to as \emph{knowmatic}, represents the evolution of the information technologies (\it).

Neurodegenerative diseases (NDDs) are a class of cognitive and motor disorders that include Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and others. They are caused by lesions in cells and tissues of the central nervous system, resulting in corresponding dysfunctions and consequent decline in cognitive and motor functions. Neural tissues are extremely vulnerable to oxidative stress, which plays critical biological roles in NDDs. Aromatic compounds are found extensively in natural plants and have substantial effects of anti-oxidative stress damage, which not only have a wide range of research applications in cosmetics, foods, etc., but are also frequently utilized in the treatment of various central nervous system diseases. This review summarizes the relevant oxidative stress mechanisms in NDDs (AD, PD, HD, and ALS) and reviews aromatic compounds such as polyphenols, terpenoids, and flavonoids that can be used in the management of neurodegenerative diseases, as well as their specific mechanisms of antioxidant action. This review will serve as a reference for future experimental studies on neurodegenerative illnesses while also offering fresh insights into clinical therapy.

This study profiled morphological and laboratory-derived performance biomechanics by position of American style football players training for the National Football League draft. Fifty-five players were categorized into Big (e.g., lineman; n=17), Big-skill (e.g., tight end; n=11), and Skill (e.g., receiver; n=27) groups. Body fat (BF%), lean body mass (LBM), total body mass, running force and ground contact time (GCT), countermovement jump height (CMJ-JH), CMJ normalized peak power (CMJ-NPP), and reactive strength were measured in a laboratory. Asymmetry was calculated for running force, GCT, and CMJ eccentric and concentric impulse (IMP). MANOVA determined between-group differences, and radar plots for morphological and performance characteristics were created using Z-scores. There was a significant between-group difference, F(26,80)=5.70, p&lt;0.001;Wilk’s Λ=0.123, partial η2=0.649. Fisher’s least squares difference post-hocs showed Skill had greater JH, CMJ-NPP, reactive strength, and running force versus Big but not Big-skill, p&lt;0.05. Big had greater BF%, LBM, total body mass, and GCT than Skill and Big-Skill, p&lt;0.05. Big-skill had greater GCT asymmetry than Skill and Big, p&lt;0.05. Asymmetries in running forces, and CMJ eccentric and concentric IMP were not different, p&gt;0.05. Morphological and performance biomechanics differences are pronounced between Skill and Big. Big-skill possess characteristics from both groups. Laboratory-derived results provide specialized profiles of draft trainees.

In an era of relentless technological change, accelerating the pace of innovation has become a critical imperative for organizations seeking to maintain a competitive edge and drive meaningful societal progress. Yet the complex, multifaceted innovation process - from ideation to commercialization - is often plagued by bottlenecks and challenges that can significantly delay the time-to-market for groundbreaking new products, services, and business models. This pioneering article represents an outstanding contribution to the burgeoning field of innovationology, offering a comprehensive, evidence-based playbook for shortening the innovation lifecycle. Drawing on an extensive review of over 180 cutting-edge academic sources, the paper maps the key stages of the innovation process - idea generation, concept development, prototyping, testing, and launch - and illuminates cutting-edge strategies that innovators can deploy to overcome common barriers and drive transformative innovations to market more quickly. From advanced idea generation techniques like design thinking and AI-powered creativity to innovative approaches to rapid prototyping, virtual experimentation, and data-driven commercialization, this seminal work equips scholars, practitioners, and policymakers with a transformative, globally-relevant toolkit for accelerating the innovation lifecycle. By synthesizing insights from a diverse array of industries and disciplines, the article establishes a new benchmark for innovationology research and empowers organizations to cultivate the conditions needed to translate visionary ideas into game-changing realities with unprecedented speed and efficiency. As the world grapples with ever-more complex, interconnected challenges, the ability to rapidly develop and scale breakthrough innovations has never been more crucial. This paradigm-shifting contribution to the field of innovationology represents a vital resource for driving the bold, disruptive changes needed to shape a more sustainable, equitable future.

Adolescence is a critical period for the development of self-perception, emotional well-being, and health-related behaviors. During this stage, adolescents undergo significant physical, emotional, and social changes that influence their overall health and interactions with their environment. This study analyzes the prevalence of behaviors related to self-perceived health, mood, and substance use among adolescents, identifies risk factors, and draws comparisons between different groups. It also examines how these factors interact with family and community dynamics to inform strategies for improving mental health care. Method: A descriptive cross-sectional study using questionnaires was conducted. Participants were adolescents aged 14 to 18 years from a school in the Baix Llobregat province of Catalonia. Descriptive and bivariate statistical analyses were performed using the chi-square test and p-value calculations with R Project software. Frequency and percentage analyses were employed to describe the health behaviors and emotional states of the participants. Results: The study reveals significant variations in adolescents' self-perceived health, emotional management, and substance use patterns. Adolescents with lower self-perceived health and negative mood states tend to exhibit higher rates of substance use, particularly alcohol and tobacco. Gender differences were observed, with girls generally reporting better health awareness and emotional regulation compared to boys. Conclusions: This study highlights the need for integrated approaches to family, community, and mental health care. Findings emphasize the importance of early intervention programs addressing emotional well-being and substance use in a holistic manner. Public health policies should prioritize comprehensive strategies involving schools, families, and communities to foster healthier behaviors and improve adolescent mental health outcomes.

Measurement in software projects is one of the activities that define engineering. In this article, it is defined as the competence of the computer engineer and its dimensions and indicators are determined. Subsequently, a pre-experiment is carried out where different empirical methods are applied in three moments to monitor the development of the competence.

This article presents a kinematic analysis of a 4-degree-of-freedom (DOF) robotic arm equipped with a 3-finger gripper, specifically designed for harvesting fruits of varying sizes. The kinematic modeling is thoroughly detailed, encompassing the equations of motion, homogeneous transformation matrices, and kinematic solutions required for the efficient operation of the robotic arm. This analysis is crucial for optimizing both the design and programming of agricultural robots, aiming to enhance harvesting efficiency and reduce labor costs. Additionally, an in-depth examination of the 3-finger gripper’s movement is provided, illustrating how MATLAB facilitates the simulation and visualization of its dynamic behavior during the opening and closing processes. The benefits of using MATLAB for this purpose are emphasized, including its ease of implementation, advanced simulation capabilities, and seamless integration with other tools to optimize the performance of robotic systems in agricultural settings. This study makes a valuable contribution to the field of agricultural robotics, offering technical insights that can be applied in the development of sophisticated robotic solutions for the modern agricultural industry.

Background: Parkinson’s Disease (PD) is a long-term condition, which is more common among people aged 65 years or more. People with Parkinson (PwP) tend to lose motor functions and find themselves in more fatigue and pain, sometimes leading to anxiety, distress and in extreme cases, even depression. So far, there is no cure for PD and they need support from family members, healthcare professionals and carers, as the disease progresses. A large proportion of carers for PwP are their spouses. Progression of PD can result in loss of employment, reduced work hours or premature retirement, for both PwP and their carers. This poses a huge financial burden as income reduces on one hand, and expenses increase on the other. There is a lack of evidence on the societal costs of Parkinson's disease, and this study tries to fill that gap. Objectives: To examine the impact of financial distress on quality of life (QoL) and wellbeing of PwP and their carers in the UK. Methods: A mix of online and postal, cross-sectional survey was administered, which received responses from 853 respondents, out of which 776 were PwP and 546 were carers. The survey sought data on management of the socioeconomic, health and living conditions of PwP and their carers. Net effect of financial distress (cost of healthcare use, non-health expenditure, societal costs and other direct / indirect cost components) on QoL (and VAS scores) as well as wellbeing scores (life satisfaction and happiness scores) of PwP and their primary carers are estimated using simple linear regression models. Results: Financial burden of treatment increase whereas quality of life and wellbeing of PwP decrease with progression of PD. Similar association but of a milder magnitude is observed on quality of life of their primary carers. A strong negative association is found between quality of life of PwP, with financial burden, while holding for demographic and socioeconomic factors, and for disease progression and treatment. The QoL of carers increase up to a financial burden threshold, before it starts declining. This could be because of the increased expenditure in initial phases is associated with improved activities of daily living and lesser reliance on carers. Financial distress is more pronounced among PwP having annual income below £20,000. Despite a small representation of persons from ethnic minority (5 per cent representation), it is observed that the impact of financial distress could be more pronounced on PwPs from other ethnicities. Also, it would be more on women than on men, irrespective of ethnicity. Conclusion and Policy Implications: Cost of care cuts both ways, reduced or lost employment as well as increased expenses on healthcare. This results into a considerable financial distress and deterioration in quality of life and wellbeing of both PwP and carers. Most carers are spouses of PwPs, thus their physical and psychological health and wellbeing is found to deteriorate with the progression of PD due to increased burden of care. Therefore, informal / family carers should get support in the form of respite care. This can help revitalise their energy and psychological wellbeing. Financial distress indicators need to be explored further.

Due to satisfactory mechanical properties, low specific weight and other advantages, a substantial utilization of laminated structural composites in many components and equipments of several industry sectors, especially in the past two decades, has been made. This class of materials has a good potential to be an important ally to support scientists and engineers with the main current world challenge: an energy transition process that must occur with sustainability, eco-friendly materials and based on an efficient reduction of greenhouse gas emissions. In this context, a microanalysis (scale length: 10μm to 1mm) of mechanical behavior that considers the multiphase characteristics, at leastwise a matrix and a reinforcement phase, of this kind of composites must be explored, i. e., a heterogeneous material is assumed to predict, for example, the effective tensors of stiffness or compliance by a homogenization process, modeling to damage analyses, studies about progressive delamination and other specific aspects of a composite can be previously investigated using micromechanical approaches. Therefore, the understanding of fundamental micromechanics as well as some advanced models are essential to apply these materials in structural industry components. In this sense, this literature review is designed to investigate and analize intrinsic physical hypothesis and theories behind the main basic and advanced models of polymer laminated composite micromechanics expanding possibilities to the development of more accurate approximations and showing future perspectives to the topic.

The high thrust linear motor used for electromagnetic launch is switched with the anti-shunt thyristor as the switch. During the switching process, different current path states will appear, which will lead to changes in motor parameters and current fluctuation. Aiming at the air-core synchronous linear motor with parallel and series power supply, this paper analyzes the change of current path caused by the change of trigger signal of anti-parallel thyristor in the process of sectionalized stator switching. The motor circuit model of the switching process is derived. A new sectionalized stator switching method is proposed to realize the smooth switching of the sectionalized stator powered linear motor. Finally, the correctness of the analysis and modeling is verified by simulation, and the effectiveness of the sectionalized stator switching method is tested by using the test prototype.

Following the economic and political transformations after 1991, including the autonomy of the Kurdistan Region and the establishment of Iraq's new federal government in 2003, extensive construction, including mosques, has reshaped the region. This requires examinations of evolving architectural features in new mosques and questioning their alignment with religious and aesthetic design objectives. This research focuses on the transformative impact of modern architectural styles on mosque evolution in Sulaymaniyah Governorate. Acknowledging the interplay of cultural evolution, technology, and artistic innovation, the study employs an in-depth case study approach to analyze selected mosques in Sulaymaniyah Governorate that blend traditional Islamic architecture with modern design principles. This synthesis of traditional and modern elements raises questions about religious legitimacy, historical symbolism, and architecture's role in reflecting and shaping religious values. Using quantitative methods including indicator-based impact assessment, the study identifies modern architectural indicators, determines religious objectives of mosque design through Islamic legitimacy references, and analyzes the case study data. By employing person coefficient correlation, the research aims to identify the causal relationship between modern architectural indicators and achieved design objectives. The results reveal that the overall influence of the modern architecture style tends to be more negative on the evol¬ution of mosques.

In this paper, we present a rigorous proof demonstrating the stabilization of percolation probability in supercritical regimes for percolation models. We analyze a sequence of expanding compact balls in ℝ

Urbanization growth has intensified the challenge of managing and treating increasing amounts of municipal solid waste (MSW). Landfills are commonly utilized for MSW disposal because of their low construction and operation costs. However, this practice produces huge volumes of landfill leachate, a highly polluting liquid rich in ammoniacal nitrogen (NH3-N), organic compounds and various heavy metals, making it difficult to treat in conventional municipal wastewater treatment plants (WWTPs). In recent years, research has shown that microbial biofilms, developed on carriers of different materials and called “Moving Bed Biofilm Reactors” (MBBRs), may offer promising solutions for bioremediation. This study explored the biofilm development and the nitrification process of moving bed biofilms (MBBs) obtained from high am-monia-selected microbial communities. Using Crystal Violet Staining and Confocal Laser-Scanning Microscopy, we followed the biofilm formation stages correlating nitrogen removal to metagenomic analyses. Our results indicate that MBBs unveiled a 10-fold more enhanced nitrification rate than the dispersed microbial community pre-sent in the native sludge of the Porto Sant’Elpidio (Italy) WWTP. Four bacterial families, Chitinophagaceae, Comamonadaceae, Sphingomonadaceae, and Nitrosomona-daceae accumulate in structured biofilms and significantly contribute to the high ammonium removal rate of 80% in 24 hours as estimated in leachate-containing wastewaters.

Coal mining activities frequently result in negative effects that spread to neighboring populations, affecting their general health and well-being. The lack of published research on these effects in the Limpopo province motivated the quest to have local communities assess how mining has affected their health. This study explored the perceived health and well-being outcomes of community members residing around a coal mine in the Limpopo Province, South Africa. The study was conducted in three sub-villages closest to Tshikondeni Coal Mine, namely, Mukomawabane, Bileni, and Mutele B. A qualitative methodology, adopting an exploratory design, was employed. Eighty-one participants, aged 18 to 80, were purposively sampled from the selected sub-villages. Data was collected through one-on-one unstructured interviews captured as field notes, complemented by audio recordings. Throughout the study, ethical research principles of approval and permission, informed consent, privacy anonymity and confidentiality as well as avoidance of harm and benefits were strictly adhered to. Content analysis was used to analyze the data. The findings of the study revealed that many members of the communities residing around the Tshikondeni coal mine are suffering from self-proclaimed respiratory-related conditions (fourteen Asthma, ten TB, three sinuses, three coughs, and one chest pain) perceived to be caused by coal dust. Participants expressed concerns about widespread deforestation from coal mine operations with resultant soil erosion and land degradation as well as the dam that the mine left unfenced, where their livestock is hunted and drowned by crocodiles. In addition, the study reveals twenty-four participants’ concerns about the non-compensation of their cracked houses resulting from mine blasting operations. This study highlights that communities closer to coal mines experience physical, mental, and social well-being challenges, emphasizing the urgent need for extensive research to validate the various self-proclaimed respiratory problems. The concerns of communities are justified as deforestation, soil erosion, and land degradation threaten food security due to the loss of soil fertility and reduced livestock grazing area subsequently impacting the community’s livelihoods. The non-compensation of cracked houses causes frustration, anxiety, sadness, and worry among community members, negatively impacting their mental health. The South African Department of Health, Environmental Affairs, and Mineral and Energy should work together, to ensure the implementation of policies to protect communities closer to mines against harmful mining operations, non-compliance, and negligence.

The objective of this research is to evaluate four distinct models for multi-population mortality projection in order to ascertain the most effective approach for forecasting the impact of COVID-19 pandemic on mortality. Utilising data from the Human Mortality Database for five countries Finland, Germany, Italy, the Netherlands, and the United States, the study identifies the generalized additive model (GAM) within the age-period-cohort (APC) analytical framework as the most promising for precise mortality forecasts. Consequently, this model serves as the basis for projecting the impact of the COVID-19 pandemic on future mortality rates. By examining various pandemic scenarios, ranging from mild to severe, the study concludes that projections assuming a diminishing impact of the pandemic over time are most consistent, especially for middle-aged and elderly populations. Projections derived from the superior GAM-APC model offer guidance for strategic planning and decision-making within sectors facing the challenges posed by extreme historical mortality events and the uncertain future mortality trajectories.

Chronic Myeloid Leukemia (CML) is one of the most commonly found types of myeloproliferative neoplasms, characterized by increased proliferation of granulocytic cells without losing their differentiation ability. Imatinib, a Tyrosine Kinase Inhibitor (TKI), can be effectively used as therapy for CML. However, imatinib can affect bone turnover, thus having clinical implications on the bones of CML patients undergoing long-term imatinib therapy. However, parameters that can accurately describe the bone condition in CML patients receiving imatinib still need further study. A combination of imaging techniques such as Bone Mineral Density (BMD) and bone turnover activity markers such as C-terminal telopeptide of type I collagen (CTX-1) and Osteocalcin has the potential to be used as monitoring parameters for bone density abnormalities in CML patients receiving imatinib. This article explains the rationale for using BMD, CTX-1, and Osteocalcin as monitoring parameters of bone remodeling in CML patients receiving imatinib. First, the physiological process of bone turnover will be explained. Then, we describe the role of tyrosine kinase in bone metabolism. Next, the impact of imatinib on BMD, CTX-1, and Osteocalcin will be explained. In conclusion, the assessment of bone health of CML patients on Imatinib should include both BMD tests and bone turnover marker assays such as CTX-1 and Osteocalcin.

This study aims at providing a climatological analysis of annual and long-term variability of dry periods in the Polish Carpathians in the period of 35 years between 1986 and 2020. Aside days with precipitation, dry periods, namely sequences of days with no precipitation, constitute an inherent characteristic of the climate. The input data for the research was formed by daily precipitation totals from 17 meteorological stations acquired from the Institute of Meteorology and Water Management - National Research Institute, and T. Niedźwiedź catalogue of circulation types over southern Poland. Frequency of dry periods of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. An analysis was performed regarding the change of the average quantity and average length of dry sequences in the 35-year period covered. At most stations, there were no statistically significant trends with respect to the analysed dry day characteristics. This is an obvious result of high variability year-to-year, which means that exclusively large changes may achieve statistical significance. Dry days have been evidenced to related to circulation types. A vast majority of dry days is related to anti-cyclonal systems, particularly the anti-cyclonal wedge (Ka) and western anti-cyclonal (Wa) situations.

Background/Objectives: This study investigates the relationship between diet quality and body image disturbance among young women aged 18-24, a crucial period for establishing lifelong health behaviors. Given the increasing exposure to social media, which often promotes unrealistic beauty standards, this research aims to explore how eating behaviors and diet quality, correlates with body image disturbance; Methods: A mixed-methods approach was employed, combining qualitative focus group discussions with quantitative analysis. Focus groups (n=19) explored themes of body image dissatisfaction. The Body Image Disturbance Questionnaire (BIDQ) was administered to 50 participants (young women aged 18-24) to quantitatively assess body image disturbance, while diet quality was evaluated using the Australian Recommended Food Scores (ARFS). The Three-Factor Eating Questionnaire (TFEQ-R18) was also used to assess eating be-haviors, including cognitive restraint, uncontrolled eating, and emotional eating. A social in-fluence questionnaire (SIQ) was administered to measure the effect of social influence. Pearson's correlation coefficient was used to determine the relationship between ARFS, BIDQ, and TFEQ-R18 scores; Results: Qualitative findings revealed persistent dissatisfaction with body shape, largely influenced by social media. Quantitatively, 65% of participants scored above the clinical threshold for body image disturbance (mean BIDQ score = 4.2, SD = 0.8). The correlation between ARFS scores and BIDQ scores was weak and not statistically significant (r = 0.057, p = 0.711). However, a sig-nificant positive correlation was found between time spent on social media and body image disturbance (r = 0.58, p < 0.01). Additionally, TFEQ-R18 results indicated that 45% of participants displayed moderate levels of uncontrolled eating, and 36.5% demonstrated moderate levels of emotional eating; Conclusions: While social media significantly influences body image concerns, its effect on eating behaviours and diet quality shows weak correlations, suggesting that other factors may mediate these outcomes. These results highlight the complexity of the relationship between body image, eating behaviors, and diet quality, indicating that interventions should address the psychological drivers behind these concerns, rather than solely focusing on reducing social media exposure.

This research explores a novel approach to integrating offshore wind farms into smart microgrids through the development of an advanced model predictive control (MPC) strategy for offshore wind turbines. The MPC strategy comprehensively incorporates complex wind dynamics, such as wind speed, direction, and turbulence, ensuring an accurate representation of turbine behavior. Additionally, the research includes models addressing wind farm layout, wake effects, and electrical infrastructure, enhancing the modeling framework's fidelity and applicability to real-world offshore wind energy systems within a smart microgrid environment. The inherent variability of wind power, transmission technology limitations, and the need for seamless transitions between grid-connected and islanded operation modes in smart microgrids necessitate robust control mechanisms. These mechanisms ensure efficient power capture, grid stability, and optimal energy utilization. To tackle these challenges, the research proposes a smart microgrid design incorporating both AC-DC and DC-DC conversion technologies. This design leverages renewable energy sources like solar and wind with AC-DC conversion for efficient power capture, integrates DC energy storage systems to store excess energy during low demand periods, and utilizes power control mechanisms to manage energy flow effectively within the smart microgrid. The study emphasizes the importance of modeling and control strategies for both AC-DC and DC-DC converters within the smart microgrid framework. To enhance the microgrid's cost-effectiveness, priority is given to the utilization of solar PV energy sources. It also highlights the integration of protection systems for DC faults and coordinated control of AC/DC breakers and converters. This comprehensive approach aligns with the core principles of adaptability, reliability, and sustainability in smart grids, aiming to advance smart microgrid technologies and pave the way for a more resilient, efficient, and secure energy future.

Surgical site infections (SSIs) are a major concern in public healthcare, leading to increased morbidity, pro-longed hospital stays length, and significant economic costs. Understanding the epidemiology and risk fac-tors of SSIs is crucial for developing effective prevention and management strategies. In the last century, CDC ‘s HICPAC improved a bundle for prevention of HAIs based on the use of aseptic procedures, disin-fection of the skin and correct use of antibiotics for SSIs. In our country, Gelli-Bianco law introduced the national health guidelines system that include the prophylaxis antibiotic therapy pre- and post-surgery. The aim of our study is to evaluate adherence and appropriateness of the use of antibiotic-preoperative prophylaxis in a province of southern Italy and to identify risk factors that may influence the development of an SSI. The study found many statistically significant associations among the factors examined, i.e. the timing of administration adherent to guidelines, with 47% of the analyzed files administering antibiotics within 60 min before the intervention and 62.7% using intravenous administration.

Background/Objectives: Monoclonal antibodies (mAbs) have revolutionized multiple myeloma (MM) treatment. However, post-marketing data on their neuropsychiatric safety is limited. This study aimed to evaluate neuropsychiatric adverse events (AEs) related to mAbs used for MM through a retrospective pharmacovigilance analysis using the Food and Drug Administration (FDA) Adverse Events Reporting System (FAERS) database. Methods: Individual case safety reports (ICSRs) from 2015 to 2023 with at least one neuropsy-chiatric AE and one of the MM-approved mAbs as the suspect drug (i.e., daratumumab, elo-tuzumab, isatuximab, belantamab mafodotin, teclistamab, elranatamab, and talquentamab) were analyzed using descriptive and disproportionality approaches. Results: Unknown signals of disproportionate reporting (SDR) included cerebral infarction for daratumumab (n = 45; reporting odds ratio (ROR) = 2.39, 95% confidence interval (CI) = 1.79-3.21; information component (IC) = 1.54, IC025-IC075 = 1.05-1.9), elotuzumab (25; 7.61, 5.13-11.28; 3.03, 2.37-3.51), and isatuximab (10; 2.56, 1.38-4.76; 1.67, 0.59-2.4); mental status changes for daratumumab (40; 2.66, 1.95-3.63; 1.67, 1.14-2.04) and belantamab mafodotin (10; 4.23, 2.28-7.88; 2.3, 1.22-3.03); altered state of consciousness for daratumumab (32; 1.97, 1.39-2.78; 1.32, 0.73-1.74) and belantamab mafodotin (6; 2.35, 1.05-5.23; 1.6, 0.19-2.52); Guil-lain-Barre syndrome (GBS) for daratumumab (23; 6.42, 4.26-9.69; 2.81, 2.11-3.3), isatuximab (8; 10.72, 5.35-21.48; 3.57, 2.35-4.37), and elotuzumab (3; 4.74, 1.53-14.7; 2.59, 0.52-3.8); and orthos-tatic intolerance for daratumumab (10; 12.54, 6.71-23.43; 3.75, 2.67-4.48) and elontuzumab (4; 28.31, 10.58-75.73; 5 , 3.24-6.08). Conclusions: Our analysis highlighted several previously unacknowledged SDRs for MM-approved mAbs. Given the complex and not entirely understood etiology of some neuropsy-chiatric AEs, including GBS, further investigations are necessary.

Lithium ascorbate (LiAsc) is a non-toxic lithium salt (LD50>5000 mg/kg) with normothymic and neuroprotective properties. Chemoreactomic modeling of LiAsc predicted possible hepatoprotective effects which were tested here on a rat model of a non-alcoholic fatty liver disease (NAFLD) with multiorgan pathology caused by combined intake of excess saturated fats (palm oil), carbohydrates (fructose) and inorganic iron salt (ferrous sulfate). Dynamics of biochemical parameters (biomarkers of liver function, kidneys, hematopoiesis, inflammation, thrombus formation, etc.) and histological evidence of hemosiderosis in the model upon reproduction of the model are described. Experimental confirmations of the hepatoprotective effects of LiAsc were obtained. Comparison of the effects of LiAsc with the effects of myoinositol (a substance with known hepatoprotective properties) shown a number of differences in pharmacological action. Both LiAsc and MI lowered ferritin, transferrin saturation, serum iron, AST, ALT, serum creatinine, leukocytes (LiAsc to a greater extent) and normalized lowered serum protein and glomerular filtration rate. However, only LiAsc lowered heightened reticulocytes (absolute and fraction) and platelets towards the corresponding reference intervals, normalized levels of vitamin B12 in blood and lowered the number of Kupffer cells in liver that were overloaded with iron (contained Prussian blue in morphometric studies). In a clinical perspective, hepatoprotective properties of a neuroprotector and it’s potential to reduce hemosiderosis might be useful for treating patients with hepatic encephalopathy.

Infective endocarditis (IE) results from infections by gram-positive bacteria, and, in this condition, the redox homeostasis is lost by overproduction of H2O2, leading to overstimulation of the immune system and up- regulation of the production of proinflammatory cytokines. The aim of this preliminary study of three cases with IE, was to evaluate the levels of oxidative biomarkers and of the enzymatic and non-enzymatic antioxidant systems, in subjects with IE. This is a preliminary retrospective analytical study of cases that had undergone aortic valve replacement surgery that was complicated by IE. We determined malondialdehyde (MDA), total antioxidant capacity (TAC), carbonyl groups, glutathione (GSH), thiols and the nitrate/nitrite ratio (NO3−/NO2−) in homogenized tissue of cardiac valves. We also measured the activities of GST, GPx, GR and TrxR. The super oxide dismutase (SOD) isoforms and peroxidase activities were determined using native gels. There were increases in the activities of antioxidant enzymes such as GST, SOD isoforms and peroxidases (p=0.01) and decreases in oxidative stress markers such as GSH, TAC, (p=0.01); however, MDA was increased (p=0.01). The results suggest that loss of the intricate redox homeostasis system in the aortic valve of patients with IE may favor the bacterial process and cause damage probably leading to a fatal outcome.

Perioperative dysglycemia in cardiac surgery is associated with poor outcomes. Glycemic variability rather than glucose levels are a predictor of length of ICU stay, rise in creatinine and acute kidney injury after cardiac surgery. Glycated haemoglobin (HbA1c) values correspond closely with average blood glucose levels and cut off values can be used to define diabetic and pre-diabetic status. These have been correlated with perioperative events. This narrative review discusses the role of glycated hemoglobin in cardiac surgery.

Background: Empathy and assertiveness are two essential soft skills for health professionals such as nurses or physiotherapists. Both professions are characterised by their contribution to preserving and improving health and human care, and for their vocation of service. One of the achievements of the training is the voluntary, conscious, and individually inspired career choice; Objetives: This study aimed to evaluate the empathy, assertiveness, and care vocational levels among undergraduate students enrolled in the Nursing and Physiotherapy Degree programmes and to investigate the relationship between these soft skills and the care vocation; Methods: A cross-sectional study of nursing and physiotherapy students was conducted in the 2022/2023 academic year. The Interpersonal Reactivity Index scales for empathy, the Rathus test for assertiveness, and the “Vocation of Service for Human Care” questionnaire were used as study tools. Finally, 226 students participated in the study; Results: The empathy, assertiveness and vocation of service for human care of the students was found to be acceptable. Significant differences were also observed according to the gender variable or career in the students, with female students presenting better results in empathy subscales or vocation (p < 0.05). Students who are working or have clinical experience in other professions score lower on the empathy personal distress subscale (p < 0.05); Conclusions: Both nursing and physiotherapy students demonstrate satisfactory levels of empathy, assertiveness and vocation for human care. However, gender and previous work experience do notably influence these scores. It would be beneficial to conduct long-term studies with educational interventions to train and develop empathy, assertiveness and vocation for human care.

The construction of an anaerobic digester coupled with post-digestion low level aeration for agricultural wastewater treatment is described. The digester employs underwater speakers to accelerate the anaerobic digestion process while retaining solids to reduce the strength of the effluent. The digester effluent is sent to a holding tank and fed at a low flow rate to an aeration tank to effect partial nitrification of the wastewater. The outlet of this tank is sent to a settling tank to retain biomass that developed in the aeration tank and the effluent is sent to a small, constructed wetland to further reduce wastewater nitrogen and phosphorus. The wetland was planted with the broadleaf cattail, Typha latifolia, and hence to a retention basin. The system has reduced energy consumption due to both the use of underwater sonic treatment and low-level aeration that is not designed to achieve full nitrification/denitrification but rather to achieve a mixture of ammonium, nitrite, and nitrate that might foster the development of a consortium of organisms (i.e. nitrifiers, Anammox bacteria) that can remediate wastewater ammonium at low cost. Biogas is sent to an inground condenser where different treatments may be tested to remove carbon dioxide and hydrogen sulfide. The system is meant to serve as a complex where various technologies and practices can be evaluated to improve the treatment of agricultural wastewater.

The present studies are specifically aimed at investigating the sensitivity of different dynamic stall models when exposed to various excitation frequencies targeted at the blade edgewise vibrations. The work is done on a modified version of the IEA 15 MW reference wind turbine employing a wind turbine design tool Bladed. The state-of-the-art dynamic stall models for wind turbine applications such as the ye model, Beddoes-Leishman (BL) model and the newly developed IAG model are evaluated. The beginning of the research work starts by evaluating different dynamic stall model effects on rigid blade section forces against known airfoil datasets. Then, the blade flexibility is considered to enable systematic evaluations of the blade flexibility influences in comparison to the rigid blade cases. It is observed that the range of the angle of attack grows depending on the excitation frequency and the adopted dynamic stall model. The critical excitation frequency range and the effects of twist distribution are then identified from the studies, which can be useful as a rough guidance when designing wind turbine blades.

Effective communication in automated chat systems hinges on the ability to understand and respond to context. Traditional models often struggle with determining when additional context is necessary for generating appropriate responses. This paper introduces Context-Aware BERT (CA-BERT), a transformer-based model specifically fine-tuned to address this challenge. CA-BERT innovatively applies deep learning techniques to discern context necessity in multi-turn chat interactions, enhancing both the relevance and accuracy of responses. We describe the development of CA-BERT, which adapts the robust architecture of BERT with a novel training regimen focused on a specialized dataset of chat dialogues. The model is evaluated on its ability to classify context necessity, demonstrating superior performance over baseline BERT models in terms of accuracy and efficiency. Furthermore, CA-BERT's implementation showcases significant reductions in training time and resource usage, making it feasible for real-time applications. The results indicate that CA-BERT can effectively enhance the functionality of chatbots by providing a nuanced understanding of context, thereby improving user experience and interaction quality in automated systems. This study not only advances the field of NLP in chat applications but also provides a framework for future research into context-sensitive AI developments.

The way in which a filtration membrane is woven influences its lifespan and purification performance. This study explores the impact of the weaving method on the hydrodynamic sta-bility of a membrane made from banana pseudotrunk fibres. After extraction, the yarns were characterised. Three membranes were obtained using different weaving methods (plain, twill and satin), and the hydrodynamic study was used to determine the surface density, porosity, per-meability and membrane resistance. Filtration tests were carried out on a suspension of 30 NTU, and the yarn obtained had a twist number of 10, a diameter of 0.75 mm and a tex of 168. The surface density and the percentage of surface voids for the three membranes, plain, twill and satin, were 8.82 g/m2 and 50%, 12.54 g/m2 and 30% and finally 15.77 g/m2 and 12.54%. The uni membrane showed the best permeability, i.e. 5.60.10-10m2, but lower particle retention with a residual turbidity of 12 NTU, compared with the twill and satin membranes, which have per-meability values of 5.31.10-10m2 and 4.80.10-10m2 and 9 and 7 NTU.The twill membrane appears to be the most suitable for filtration.

Background: Gestational trophoblastic neoplasia (GTN) is a rare tumor with an excellent prognosis. This study aimed to refine the FIGO risk score by incorporating immune nutritional factors. Methods: A retrospective analysis was conducted on women diagnosed with GTN between 2005 and 2019 who received chemotherapy (CT). Statistical tests (Wilcoxon, univariate, multivariate analyses) were used to assess associations with response to CT, and Cox regression models were applied to identify factors influencing overall survival (OS). immune nutritional FIGO (in-FIGO) risk score was calculated using significant variables and compared to the original FIGO score using ROC curves. Results: A total of 160 GTN patients were included. There was a positive association between CR and prognostic nutritional index (PNI) (p <0.0001) and neutrophils lymphocyte ratio (NLR) (p <0.001). In multivariate analysis, only PNI had a significant association (p= 0.001). A significant association was found between higher PNI (HR 0.95-IC 0.91-0.99, p= 0.019) and OS. ROC curves of the in-FIGO risk and FIGO risk scores were compared. For CR to chemotherapy, the in-FIGO score had higher sensitivity (71.6 vs. 61.5%), specificity (74.3 vs. 62.9%), and AUC (0.719 vs. 0.633) than the original FIGO score. For OS, the in-FIGO score demonstrated higher sensitivity (92% vs. 72.4%) but lower specificity (45.0% vs. 61.8%) and AUC (0.691 vs. 0.710) compared to the original FIGO score. Conclusions: PNI is a significant predictor of both CR and OS in women with GTN receiving CT. The in-FIGO score demonstrated improved sensitivity and specificity in predicting complete response to CT compared to the original FIGO score.

Treatment with herbal medicine continues to enjoy widespread popularity not only in the developing world, because of low costs, easy availability, and low risk of adverse effects. One such plant is Curcumin longa L., or turmeric, which has a long history of both culinary and medicinal uses throughout Asia, spanning thousands of years. In addition to traditionally being used as a dye, as a flavouring and colouring agent in foods, and, e.g., marriage rituals, turmeric is also notable for its long history of use to treat a variety of medical conditions, including inflammatory, bacterial, and fungal diseases and infections, jaundice, tumours, and ulcers among others. In light of this long history of use, it is not surprising to find that also modern biochemistry and clinical research studies show that a significant component of turmeric, curcumin, may have a multitude of therapeutic benefits, much of it attributed to the herb’s antioxidant qualities which are crucial for the prevention and treatment of, e.g., chronic inflammatory illnesses, conditions that often act as precursors for other serious diseases, including cancer and neurological disorders, such as Parkinsons and Alzheimer’s. Furthermore, investigations on the safety profile and toxicity of curcumin have shown that it is generally safe even at large dosages, although caution is necessary as curcumin also have documented anticoagulant effects. This article is focused on providing a better perspective into molecular mechanisms for possible actions along with an in-depth review of recent studies of curcumin, its beneficial role and therapeutic applications in chronic health conditions, with a focus on its cancer, inflammatory bowel disease, osteoarthritis, atherosclerosis, peptic ulcer, Covid19, psoriasis, vitiligo, and depression.

Background/Objectives: The global push to eliminate tuberculosis (TB) as a public health threat is in-creasingly urgent, particularly in high-burden areas like O.R. Tambo District Municipality, South Africa. Drug-resistant TB (DR-TB) poses a significant challenge to TB control efforts and is a leading cause of TB-related deaths. This study aimed to assess DR-TB transmission patterns and predict future cases using geospatial and predictive modeling techniques. Methods: A retrospective cohort study was conducted across five decentralized DR-TB facilities in O.R. Tambo District Municipality from January 2018 to De-cember 2020. Data were obtained from Statistics South Africa, and patient GPS coordinates were used to identify clusters of DR-TB cases via DBSCAN clustering. Hot Spot Analysis (Getis-Ord Gi) was performed, and two predictive models (Linear Regression and Random Forest) were developed to estimate future DR-TB cases. Analyses were conducted using Python 3.8 and R 4.1.1, with significance set at p < 0.05. Results: A total of 456 DR-TB patients were enrolled, with 56.1% males and 43.9% females. The mean age was 37.5 (±14.9) years. The incidence of DR-TB was 11.89 cases per 100,000 population, with males dispropor-tionately affected. Key risk factors included poverty, lack of education, and occupational exposure. DR-TB types included RR-TB (60%), MDR-TB (30%), Pre-XDR-TB (5%), XDR-TB (3%), and INHR-TB (2%). Spatial analysis revealed significant clustering in socioeconomically disadvantaged areas. A major cluster was identified, along with a distinct outlier. Predictive models indicated differing trends, with the Random Forest model predicting stabilization at 30 cases per year by 2022, while the Linear Regression model projected a decline to zero by 2026. Conclusions: The study highlights the need for targeted interventions in vulnerable populations to curb DR-TB transmission and improve treatment outcomes.

Coastal zones, although vital for human livelihoods and environmental services, are increasingly vulnerable to climate change, especially communities dependent on marine ecosystems. These areas face significant threats from urbanization, population growth, and climate impacts, leading to biodiversity loss and ecosystem degradation. Recognizing these challenges, the United Nations declared 2021--2030 the Decade for Ecosystem Restoration, led by the UNEP and FAO, with the aim of restoring degraded ecosystems to achieve sustainable development goals (SDGs). The link between healthy ecosystems and disaster risk reduction (DRR) has gained global prominence, especially through the Sendai Framework for Disaster Risk Reduction (SFDRR), which emphasizes the importance of ecosystems in mitigating risks. Despite this, many tools for assessing risks in different ecosystem scenarios remain inaccessible to key stakeholders in disaster management. Advances in spatial modelling have supported ecosystem management, policy-making, and ecosystem health assessment, particularly following the Millennium Ecosystem Assessment. These models have been applied in regions such as the Great Bahamas, Haiti, and the Republic of Congo, helping shape ecosystem-based approaches to development. Improving access to spatial tools and models is crucial to enabling effective ecosystem-based DRR and climate adaptation strategies.

A study was conducted to investigate the occurrence of Trypanosoma vivax infection in 72 Murrah buffaloes from Soure, a municipality located on Marajó Island. The aim of the research was to identify the presence of T. vivax in the buffalo population. Blood samples were collected, followed by DNA extraction and polymerase chain reaction (PCR) analysis using the primers TviCatL1 and DTO 155. T. vivax DNA was detected in one 36-month-old female with a body condition score of 2 (on a scale of 1 to 5), although the animal exhibited no clinical signs of infection. These findings suggest that T. vivax is not frequently circulating among the tested buffaloes, or that the animals may be in the chronic phase of infection, which is often characterized by low parasitemia levels. The identification of T. vivax in a clinically asymptomatic animal underscores the importance of using molecular diagnostics for early detection and monitoring of the parasite in buffalo herds, especially in regions where the presence of T. vivax may be underestimated. This study contributes to understanding the epidemiological status of T. vivax in buffaloes on Marajó Island, highlighting the need for ongoing surveillance in endemic areas.

Communication pathways are an underestimated source of synthetic particles in the environment. This study investigated the impact of traffic volume on microplastics (MPs) and tire wear particles (TWPs) pollution in road snow. An examination was conducted in a medium-sized city situated in northeastern Poland, known for being one of the cleanest regions in the country. MPs and TWPs were found at all 53 sites, regardless of the intensity of traffic. The average concentration for all samples was 354.72 pcs/L. Statistically significant differences were found between the average values of particles concentration on low, medium, and heavy traffic roads amounted 62.32 pcs/L, 335.97 pcs/L and 792.76 pcs/L respectively. Within all three studied groups of roads, MPs and TWPs with the smallest size, ranging from 50 to 200 μm, were prevalent. In all studied groups of roads, 4 analyzed shapes of particles were found, with irregular fragments being the most abundant form (89.23%). The most frequently recorded color among the collected samples was black (99.85%), and the least frequently recorded was blue, constituting only 0.01%. This study suggests that snow cover on the roads may act like temporary storage of pollutants during winter in the temperate climate zone and after thaw can significantly increase the concentration of MPs and TWPs in surface waters. Possible measures to decrease the release of MPs and TWPs into the environment in the city may include reducing traffic volume and speed, implementing street sweeping, utilizing filtration chambers, and installing stormwater bioretention systems or settling ponds.

Introduction & Objectives: Blood cells-(BC)count derived parameters have been inves-tigated in systemic inflammation, cancer, and various cutaneous diseases. Little is known about their usefulness in trichology, especially as prognostic and therapeutic biomarkers. We conducted a retrospective study on patients with not-cicatricial alopecia to assess differences in BC-count. Materials & Methods: Patients with alopecia areata (AA), telogen effluvium (TE), androgenic alopecia (AGA), psoriasis and hidradenitis suppurativa (HS) were included in the study. Baseline complete BC-count and derived parameters (i.e. NLR, PLR, MLR, SII; PIV) were recorded and analyzed for each patient and at different timepoints for AA patients on systemic agents. Results: 170 patients fulfilled inclusion criteria. BC-count and derived values were similar across the not-cicatricial alopecia groups, while general differences were observed compared to psoriasis and HS. TE displayed a closer inflammatory signature to psoriasis with respect to CRP, NLR, MLR, SII and PIV. We also found a significant reduction in RBCs in severe versus patchy-AA and an increase of SII in acute versus chronic AA. Modulation of platelet number and volume could be used as therapeutic marker in AA. Conclusions: In our experience, the BC-count and its derived parameters could represent potential tools in AA and TE.

Reverse osmosis (RO) and nanofiltration (NF) are ubiquitous technologies in modern water treatment, finding applications across various sectors. However, the availability of high-quality water suitable for RO/NF feed is diminishing due to droughts caused by global warming, increasing demand, and water pollution. As concerns grow over the depletion of precious freshwater resources, a global movement is gaining momentum to utilize previously overlooked or challenging water sources, collectively known as “marginal water.” Fouling is a serious concern when treating marginal water. In RO/NF, biofouling, organic and colloidal fouling, and scaling are particularly problematic. Of these, organic fouling, along with biofouling, has been considered difficult to manage. The major organic foulants studied are natural organic matter (NOM) for surface water and groundwater and effluent organic matter (EfOM) for municipal wastewater reuse. Polymeric substances such as sodium alginate, humic acid, and proteins have been used as model substances of EfOM. Fouling by low molecular weight organic compounds (LMWOCs) such as surfactants, phenolics, and plasticizers is known, but there have been few comprehensive reports. This review aims to shed light on fouling behavior by LMWOCs and its mechanism. LMWOC foulants reported so far are summarized, and the role of LMWOCs is also outlined for other polymeric membranes, e.g., UF, gas separation membranes, etc. Regarding the mechanism of fouling, it is explained that the fouling is caused by the strong interaction between LMWOC and the membrane, which causes the water permeation to be hindered by LMWOCs adsorbed on the membrane surface (surface fouling) and sorbed inside the membrane pores (internal fouling). Adsorption amounts and flow loss caused by the LMWOC fouling were well correlated with the octanol-water partition coefficient (log P). In part 2, countermeasures to solve this problem and applications using the LMWOCs will be outlined.

This paper compares Demand Response algorithms suitable for Short-term Forecasting based on Advanced Metering Infrastructure (AMI). It selects ARIMA (AutoRegressive Integrated Moving Average), SARIMA (Seasonal ARIMA), LSTM (Long Short-Term Memory), and SVM (Support Vector Machine) as the primary research algorithms and delves into their theoretical foundations and functional characteristics. The theoretical background section explores each algorithm’s applicability in analyzing time-series data, recognizing nonlinear patterns, and solving optimization and classification problems. The methodology section will detail the methods of AMI data collection, the implementation of the algorithms, and the experimental setup. In the experiments and results section, the performance of each algorithm will be assessed by applying AMI data and presenting the outcomes of comparative analyses, with a focus on evaluating the predictive accuracy of the algorithms. The discussion will interpret the experimental results, analyzing the advantages and disadvantages of each algorithm and their applicability in the AMI system. It will also explore the limitations of the current research and directions for future research. The conclusion will summarize the key findings of the study and affirm how this research contributes to understanding and improving short-term forecasting and demand response systems based on AMI.

Antimicrobial resistance (AMR) is a worsening global health crisis that has arisen due to antibiotic overuse and misuse. Antibiotic resistance renders standard treatments less effective, making it difficult to control some infections, thereby increasing morbidity and mortality. Medicinal plants are sustainable treatment options that are becoming increasingly important as antibiotics lose their efficacies. The present study evaluates the antibacterial activity of aqueous, methanolic and ethyl acetate extracts prepared using Terminalia bellirica and Terminalia chebula fruit against six bacterial pathogens using disc diffusion and broth microdilution assays. The aqueous and methanol extracts of T. bellirica and T. chebula showed substantial zones of inhibition (ZOIs) against S. aureus and MRSA. The activity against those bacteria was determined to be strong, with minimum inhibitory concentrations (MIC) ranging from 94 µg/mL to 392 µg/mL. Additionally, the T. bellirica methanolic extract showed noteworthy antibacterial activity against E. coli and an ESBL E. coli strain (MIC values of 755 µg/mL for both). The aqueous T. bellirica and T. chebula extracts also inhibited K. pneumoniae growth (MIC values of 784 µg/mL and 556 µg/mL respectively), whilst the methanolic extracts of these plants also inhibited ESBL K. pneumoniae growth (MIC values of 755 µg/mL and 1509 µg/mL respectively). Eighteen additive interactions were observed when extracts were combined with reference antibiotics. Notably, strong antagonistic interactions occurred when any of the extracts were mixed with polymyxin B. All extracts were subjected to LC-MS analysis, revealing several interesting flavonoids and tannins, including 6-galloylglucose, 1,2,6-trigalloyl-β-D-glucopyranose, 6-O-[(2E)-3-phenyl-2-propenoyl]-1-O-(3,4,5-trihydroxybenzoyl)-β-D-glucopyranose, propyl gallate, methyl gallate, sanguiin H4, hamamelitannin, pyrogallol, gallic acid, ellagic acid, chebulic acid, and chebuloside II. All extracts were nontoxic when tested in brine shrimp assays. This lack of toxicity, combined with their antibacterial activities suggests that these plant species may be promising sources of antibacterial compound(s) that warrant further study.

Cardiovascular disease (CVD) is a major global health concern. The number of people with CVD is expected to rise due to aging populations and increasing risk factors such as obesity and diabetes. Identifying new molecular markers is crucial for early diagnosis and treatment. Among these, plasma levels of some miRNAs specifically expressed in cardiac and skeletal muscle known as myomiRs, has gained attention for their roles in cardiovascular health. This study analyzed the plasma levels of myomiR-133a, -133b, and -206 in the pathogenesis of cardiovascular diseases. Exploiting of a case-control study design with patients recruited from several nursing homes form Calabria (Southern Italy) characterized by different types of CVD compared to non-CVD controls, we found downregulation of miR-133a in heart failure and miR-133b in stroke, along with the overall decreased expression of miR-133b and miR-206 in CVD patients. In silico functional characterization of their targets and signaling pathways revealed their involvement in critical cardiovascular processes. Although further research is necessary to fully elucidate their mechanisms and clinical utility, the results here reported support the idea that myomiRs could serve not only as biomarkers but also as therapeutic targets, offering new avenues for managing and potentially preventing CVD progression.

Occupational incidents in construction workplaces present a persistent challenge, with severe consequences for both workers and project outcomes. This study aims to examine the specific causal factors contributing to these incidents, focusing on the interaction between worker-related, environmental, and procedural factors. The objective is to identify key contributors to workplace accidents and develop a unified predictive model to mitigate future risks. To achieve this, we employed a machine learning approach on a comprehensive accidentology dataset collected from contractors across multiple construction sites. The dataset includes variables such as worker ex-perience, environmental conditions, adherence to safety protocols, and more. By analyzing direct, indirect, and root causes, the methodology uncovers hidden patterns and interdependencies that traditional analysis might overlook. The study’s findings indicate that worker experience and environmental factors are the most significant contributors to incident occurrence, with a clear interaction effect between these variables. The results not only confirm previous research but also offer enhanced predictive capabilities for future safety measures. This research demonstrates the value of machine learning in generating data-driven insights, ultimately aiding in the develop-ment of targeted interventions to improve safety standards in the construction industry.

In this work, studies were carried out on the extraction of silver and gold from cakes of pressure oxidation leaching of sulfide concentrate containing pyrite and arsenopyrite. The addition of gypsum at a consumption of 0.1 g/g of concentrate helps to increase silver extraction from 13.4 to 95–98% at the cyanidation stage, with no conditioning operation. Gold recovery was 99%. An increase in gypsum consumption contributes to the formation of BFAS with an increased content of sulfate sulfur, and a decrease in the As/S(sulfate) molar ratio in the cake from 3.7 down to 0.88 contributes to an increase in silver extraction at the cyanidation stage up to 98%, and its further decrease from 0.88 down to 0.58 leads to a gradual reducing silver transfer into solution from 98 down to 75.1% at the cyanidation stage. Basic ferric sulfate (BFS) is not formed in this case, since according to EDS mapping the distribution of arsenic and sulfur over iron-containing particles is uniform. According to TCLP analysis, the cake obtained after pressure oxidation leaching with the addition of gypsum and cyanidation is stable and suitable for disposal, since the final concentration of arsenic in the solution was 0.45 mg/dm3.

Acetylcholinesterase (AChE) activity is the most commonly used neurotoxicity biomarker in fish. It is measured mostly in the brain but can also be evaluated in muscle or (in the case of very small fish) in whole body homogenate. AChE activity is measured using standard methods, thus the results obtained by various authors are comparable. AChE seems to be a sensitive neurotoxicity biomarker since in most cases of fish exposure to various toxic agents a decrease in the enzyme activity was observed. The effects of toxic agents on AChE activity are concentration and time-related. An increase in AChE activity occurred very rarely. The results of the analysis showed that most aquatic pollutants may modulate AChE activity. Acetylcholinesterase activity can be also used to evaluate transgenerational neurotoxic effects.

Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combination of factors that might be affecting the pathway under certain conditions. For example, Brancati et al.1 observe that mutations in poliovirus receptor related protein 4 (PVRL4), encoding cell adhesion molecule nectin-4, causes Ectodermal dysplasia-syndactyly syndrome. Interaction with cad- herins also implies an influence of nectin-4 on Wnt signaling, which plays a relevant role in limb development (Brancati et al.1). However, not much work has been done to explore the relation of Wnts and PVR family. In CRC cells treated with ETC-1922159, both were found up regulated. In a recent unpublished work in Open Science Framework, Sinha2, we had the opportunity to rank these unknown biological hypotheses for both up and down regulated genes at 2nd order level after drug administration. The search engine alloted high nu- merical valued rankings to some combinations of PVR-WNT, thus indicating a possibility of high combinatorial synergy also. The in-silico derived influences can be represented graphically as - PVR w.r.t WNT with PVR <- WNT9A; and WNT w.r.t PVR with WNT-7B/9A <- PVR and WNT4 <- PVRL2; In the light of the recent findings of PVR with IFN (interferon) and the known interactions between IFN and Wnts, there might be a possibilty to explore the bridge of PVR, IFN and WNTs. The 3 fold (PVR - IFN; IFN - WNT; WNT - PVR), 2 way cross family analysis might shed light on the possible combinations that might be of import. Here, we present a 2-way cross family analysis of multiple, such in-silico ranked 2nd order synergistic combinations, after ETC-1922159 treatment of CRC cells. Via this 2-way cross family analysis, we are able to discover through majority voting, the combinations that might of interest to biologists and also derive plausible influences of components of combinations among themselves. Note that these form biological hypotheses which indicate whether a particular combination and the direction of influence within the combination, exist synergistically in CRC cells. Wet lab tests will indicate the veracity of these combinations and if proven true, will lead to further study of mechanism between the components.

An untrained couch potato involuntarily forced to undergo a long strenuous exercise towards exhaustion will feel it at the end as a discomforting fatigue. A well-trained athlete will feel the same but after a longer time. Patients of various neurological diseases will do so much earlier. All may also finally experience muscle pain and soreness the next day.Muscle fatigue is an exercise-induced reduction in maximal voluntary muscle force. Muscle fatigability varies with muscle use, age and sex. It is commonly divided into two broad categories: peripheral and central fatigue. The first refers to the many processes in the fatiguing muscle(s), the second to subsequent processes in the central nervous system (CNS). Peripheral muscle fatigue can be caused by numerous different mechanisms, ranging from the accumulation of metabolites within muscle fibers to their damage. Central fatigue involves the inadequacy of the CNS to generate and maintain sufficiently strong motor command. There must of course be a mediator relating the two fatigue types, and this is the collection of small-diameter group III (Aδ) and IV (C) nerve fibers emanating from the muscle and distributing their activation effects throughout the CNS.Muscle fatigue develops during eventually exhausting exercise that goes along with activations of the cardio-vascular and respiratory system to supply oxygen and energy resources. While these functions are supported by a number of sensory afferents, fatigue-activated group III/IV muscle afferents have been proposed to contribute their share to cardio-vascular and ventilatory reflex responses that are mediated in the brainstem. Neural feedback from working skeletal muscle is a vital component in providing a high capacity for endurance exercise because muscle perfusion and O₂ delivery determine the fatigability of skeletal muscle (Amann 2012).The development of chronic muscle fatigue is related to muscle wasting mediated by aging, myopathies, muscle dystrophies, immobilization, insulin resistance, diseases associated with systemic inflammation (arthritis, sepsis, infections), trauma, cardio-vascular (heart failure) and respiratory disorders (chronic obstructive pulmonary disease (COPD)), chronic kidney failure, multiple sclerosis (MS), and, more recently, coronavirus disease 2019 (COVID-19).

This paper addresses a critical concern in intrusion detection within the broader realm of cyber security, particularly focusing on login activity involving the majority of normal users. Utilizing the AdaBoost classifier, the study employs various optimizers to enhance performance by selecting optimal control parameters. A specially tailored version of Crayfish Optimization Algorithm (COA) is introduced to cater to the unique requirements of this investigation. Through a comparative analysis of a simulated publicly available dataset, models optimized by the modified algorithm demonstrate superior outcomes, achieving an accuracy of 94.6128% and displaying an adaptive convergence rate capable of navigating local minima to identify optimal solutions. The best-performing model undergoes SHapley Additive exPlanations (SHAP) analysis to identify key contributing features. Limitations arise from the computational intensity of the optimization process, necessitating consideration of limited populations and smaller numbers of estimators during simulations. Future endeavors will extend the methodology to incorporate additional user actions in classification, with a focus on addressing computational constraints as hardware advancements occur. Proposed, modified algorithm could be applied to deal with various optimization tasks, beyond the scope of this study.

Afghanistan is located on the Eurasian tectonic plate's edge, a highly seismically active region. It is bordered by the northern boundary of the Indian plate and influenced by the collisional Arabian plate to the south. The Hindu Kush and Pamir Mountains in Afghanistan are part of the western extension of the Himalayan orogeny and have been uplifted and sheared by the convergence of the Indian and Eurasian plates. These tectonic activities have generated numerous active deep faults across the Hindu Kush-Himalayan region, many of which intersect Afghanistan, resulting in frequent high-magnitude earthquakes. This tectonic interaction produces ground shaking of varying intensity, from high to moderate and low, with the epicenters often located in the northeast and extending southwest across the country. The reoccurrence and severity of earthquakes have been increasing since 1900. This study maps Afghanistan's tectonic structures, identifying the most active geological faults and regions with heightened seismicity. The increasing trend in recurrence and intensity of the earthquakes are drawn. Historical earthquake data were reviewed, and recent destructive events were incorporated into the national earthquake dataset to improve disaster management strategies. Additionally, the study addresses earthquake hazards related to building and infrastructure design, offering potential solutions and directions to mitigate risks to life and property.

This study examines the historiography of early Islam by assessing the reliability of Qurʾānic exegeses as sources documenting the early history of Islam and the biography of the Prophet Muḥammad in Mecca. Focusing on Qurʾānic exegetical practices from late antiquity to the medieval period, this article argues that there is a significant discontinuity in how Qurʾānic exegeses align with the historical context of the Qur'an, especially in relation to Meccan sūras such as Q 107. Significantly, this challenges the continuity of tradition, the fundamental concept upon which the “Islamic sciences” are based. This discontinuity is herein revealed through a historical-critical analysis of the exegesis of Q 107:4 that demonstrates how Qurʾānic exegetical practices have reinterpreted and reshaped early Islamic history in response to the pressures of new identity formation and made Qurʾānic exegeses more reflective of the social and political contexts of the exegetes than of the historical milieu of the Qurʾān itself. This analysis contributes to the ongoing discussion of the role exegesis played in reshaping the history of Islam. Indeed, it emphasises the importance of critically evaluating these sources in order to uncover a more nuanced historical narrative of early Islam.