Titanium-based metal-matrix composites manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing high reinforcement content remains challenging. This study reports an improved manufacturing process for Ti-TiC enabling high reinforcement content and significant fracture strain concurrently: mechanical blending, followed by laser powder bed fusion and a single heat treatment. As-built microstructure shows both un-melted TiC particles and sub-stoichiometric TiC dendrites resulting from a partial dissolution of TiC particles. The heat treatment is shown to fully convert TiC dendrites into equiaxed TiC grains. Reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. Ti-TiC tensile samples reached fracture strains of up to 1.7%, Young’s moduli of up to 149 GPa and ultimate tensile strengths of up to 827 MPa. Lower TiC initial powder size distributions displayed the best mechanical performance.

This study outlines a 3-step production process for Ti-TiC Metal Matrix Composite (MMC) employing powder Mechanical Blending, Laser Powder Bed Fusion (LPBF), and a heat treatment. A TiC fraction of more than 20 vol% was formed in-situ through the reaction of titanium with carbon during the LPBF process. The manufactured MMC pieces showed a record stiffness and fracture strain combination. The LPBF energy density impacted strongly porosity type. The as-built microstructure displayed an homogeneous distribution of sub-stoichiometric TiC dendrites which were fully converted into equiaxed TiC grains during the heat treatment. The TiC C/Ti ratio was found to be close to 0.5, resulting in an effective reinforcement content nearly twice the one expected for stoichiometric TiC, leading to stronger reinforcement. The mechanical analysis revealed a Young’s modulus of up to 149 GPa and an ultimate tensile strength of up to 770 MPa, indicating a 27% and 34% improvement, respectively, compared to commercially pure Titanium produced by LPBF and heat treated in the same conditions. A fracture strain of up to 2.8% was achieved. The combination of in-situ formation of defect-free TiC reinforcement and subsequent heat treatment enables to reach an exceptional ductility, considering the 20 vol% reinforcement content.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

A compact Mach-zehnder interferometer with a novel design of directional couplers and a phase shifter has been presented as a thermo-optical sensor. With the aim of reducing device size to micro and nano dimension silicon-on-insulator technology was employed. That allowed miniaturization of device size through the reduction of its cross sectional area to 0.066 µm² and the radius of curvature of both the arms of the directional coupler and S-bends of the phase shifter to 5 µm and C-bends to 3 µm. These nano size device dimensions made it possible to reduce the coupling gap to 0.2 µm, which resulted in a significant reduction in the coupling length. The device geometry and its performance characteristics were analyzed and optimized using coupled mode analysis and finite difference time domain simulation tools, respectively. The wavelength dependent transmission loss of the device was measured at different temperature to verify and validate its performance characteristics. Tested devices showed a remarkable temperature dependent transmission characteristic offering significant changes in transmission loss band – with as low as 0.45 ⁰C change in substrate temperature. The extinction ratio and the free spectral range of the device were 26 dB and 0.26 nm respectively in the wavelength range of 1549.5 nm – 1550.5 nm. These results imply that the devices presented here can be used as compact and highly sensitive thermal sensors and optical switches.

Researchers are exploring solutions to meet the growing demand for protein due to the expected increase in global population by 2050. Interest in alternative protein sources like insects has risen, driven by concerns about environmental impact and the need for sustainable food production. This study aimed to develop and evaluate the physicochemical properties of soy protein-based burger enriched with insect protein from Alphitobius diaperinus. Three formulations were developed: a control (B0), and burgers with 5% (B5) and 10% (B10) insect protein - Whole Buffalo Powder (WBP). Results showed that adding insect protein decreased the burger analogue's pH. There was observed a clear trend of increasing total lipids and SFA, and decreasing MUFA and PUFA, as the WBP concentration increases from 0% to 10%. No significant differences with increasing WBP concentration in the protein content of the burger analogue, as well as the cooking yield, were noted. The WBP addition had a notable effect on the color change, especially decrease in brightness (L*). It was shown that as the WBP concentration increased, there were no significant differences in the texture profile of the burger analogues. The formulation with 5% WBP concentration was the most acceptable in sensory analysis.

Usually in quantum optics, the theory of large- and small-scale waveguide beam splitters is the same. In this paper it is shown that the theory of the nanoscale waveguide beamsplitter has a significant difference from a similar device, but of a larger scale. It is shown that the previously known theory of the waveguide beam splitter is a particular case of the theory presented here. The wave function at the output ports of the nanoscale beam splitter is analyzed. The results obtained are sensitive to the size of the beam splitter, the coupling parameter of the two waveguides, and the degree of nonmonochromaticity of the photons entering the first and second ports of the beam splitter. The results are important for quantum technologies using a nanosized beam splitter.

We present theoretical designs of high performance optical filters in integrated silicon photonic nanowire resonators. We use mode interference in formed by zig-zag waveguide coupled Sagnac loop reflectors (ZWC-SLRs), tailored to achieve diverse filtering functions with good performance. These include compact bandpass filters with improved roll-off, optical analogues of Fano resonances with ultrahigh spectral extinction ratios (ERs) and slope rates, and resonance mode splitting with high ERs and low free spectral ranges. The analysis verifies the feasibility of multi-functional integrated photonic filters based on ZWC-SLR resonators for flexible spectral engineering in diverse applications.

For this research we are selected three indicators of wheat: yield (t/ha), producer price (USD/t) and share of the harvested area under wheat in relation to the total land area of country (%). The mentioned indicators were analyzed for the period 2006-2021 in thirty-two European countries. The purpose of the research is to determine which of the mentioned indicators achieve average annual growth/decrease rates, what is the correlation between them, how European countries are grouped with their similarities and differences. The research examines the impact of the COVID-19 pandemic on the mentioned indicators in a two time phases: Phase I, before the pandemic (2006-2019); Phase II, during the pandemic (2020-2021). The methodological approach to the research topic involved the application of descriptive statistics, as the method of principal components analysis (abbr. PCA) with graphics. A positive correlation exists only between the yield of wheat and the share of the harvested area under wheat in the total area of the land (0.291). PCA method showed that countries are grouped differently depending on the observed indicator and the analyzed time phase.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

Germanium (Ge) nanostrip is embedded in polymer and studied as a waveguide. Measurement reveals that this new type of semiconductor/polymer heterogeneous waveguide exhibits strong absorption for the TE mode from 1500 nm to 2004 nm, while the propagation loss for the TM mode declines from 20.56 dB/cm at 1500 nm to 4.89 dB/cm at 2004 nm. The transmission characteristics serves as an essential tool to verify the optical parameters (n-κ) of the thin strips, addressing to the ambiguity raised by spectroscopic ellipsometry regarding highly absorbing materials. Furthermore, the observed strong absorption for the TE mode at 2004 nm is well beyond the cut-off wavelength of the crystalline bulk Ge (~1850 nm at room temperature). This redshift is modeled to manifest the narrowing of the Tauc-fitted bandgap due to the grain order effect in the amorphous Ge layer. The accurate measurement of the nanometer-scale light-absorbing strips in a waveguide form is a crucial step toward the accurate design of integrated photonic devices that utilize such components.

Environmental monitoring is an important topic and serves a vibrant scientific role by revealing long-term trends that can lead to new knowledge and understanding. Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as the number of nodes in the Giant Connected Component (GCC) or average pairwise connectivity. In contrast, we propose a unique metric that concurrently targets nodes with the highest degree and reduces the GCC size. Given the NP-hard nature of optimizing this metric, we introduce MaxShot, an innovative end-to-end solution that leverages graph representation learning and reinforcement learning. Through comprehensive evaluations on both synthetic and real-world datasets, our method consistently outperforms leading benchmarks in accuracy and efficiency. These results highlight MaxShot’s potential as a superior approach to address the network dismantling problem effectively.

Despite soccer popularity, comparatively little scientific information is available concerning the assessment of youth players’ physiological characteristics. The use of medical software integrating wearable sensors to provide accurate and objective data is necessary. In the present study, the objective assessment of physical performance of 128 adolescent soccer players at two timepoints (pre-season and end-season) has been performed. Participants completed a comprehensive test battery including stability, countermovement jumps (CMJ), plyometric jumps (PJ), agility, and quick feet tests. A single Inertial Measurement Unit (IMU) sensor provided quantitative data on various performance metrics. Principal Component Analysis (PCA) reduced the dataset to four principal components (PCs) explaining over 80% of the variance: power (PC1), balance (PC2), speed/agility (PC3), and stiffness (PC4). Paired samples t-test between the two timepoints showed no significant differences in the PCs between the two timepoints, indicating that the training program did not significantly alter the assessed physical attributes. However, subtle individual changes may still inform personalized training adjustments. The study highlights the importance of continuous monitoring and individualized training strategies to optimize athlete performance and reduce injury risk.

Silicon photonics is emerging as a competitive platform for electronic-photonic integrated circuits (EPICs) at the 2 µm wavelength band where GeSn photodetectors (PDs) have proven to be efficient PDs. Here, we present a comprehensive theoretical study of GeSn vertical p-i-n homojunction waveguide photodetectors (WGPDs) that have a strain-free and defect-free GeSn active layer for 2-µm Si-based EPICs. The use of a narrow-gap GeSn alloy as the active layer can fully cover entire the 2 µm wavelength band. The waveguide structure allows for decoupling the photon-absorbing path and the carrier-collection path, thereby allowing for simultaneous achievement of high-responsivity and high-bandwidth (BW) operation at the 2-µm wavelength band. We present the theoretical models to calculate the carrier saturation velocities, optical absorption coefficient, responsivity, 3-dB bandwidth, zero-bias resistance, and detectivity, and optimize this device structure to achieve highest performance at the 2-µm wavelength band. The results indicate that the performance of the GeSn WGPD has strong dependence on the Sn composition and geometric parameters. The optimally designed GeSn WGPD with 10% Sn concentration can give responsivity of 1.55 A/W, detectivity of 6.12×1010 cmHz½W-1 at 2 µm wavelength, and ~97 GHz BW. Therefore, this optimally designed GeSn WGPD is a potential candidate for silicon photonic EPICs offering high-speed optical communications.

Bending waveguide is one of the building blocks of on-chip photonic integrated circuits (PICs). Previous bending waveguides (BWs) usually suffer from larger footprint size in the bending region, which is are not conducive to develop large-scale and high-density PICs. To this end, we propose and numerically investigate an ultra-compact silicon-on-insulator 180-degree waveguide bend with a bending radius of 2 µm. Being different from the previous BWs, the design is based on topologically optimized digital metamaterials, which is implemented by using intelligent genetic algorithms. Simulated results show that the proposed structure has a -1.36 dB bend efficiency per 180-degree at a wavelength of 1.55 µm and occupies a footprint of only 4 × 4 µm2. Moreover, the crosstalk is <−20 dB and the loss is <2.6 dB over a >100 nm operating bandwidth (1.6-1.7 µm) for TE0 modes. With the wide operating bandwidth and ultra-compact footprint, the proposed silicon-based 180-degree waveguide bend shows a potential application as the fundamental component for optical communication interconnect in the ultra-highly integrated photonic circuit.

Based on the sensitive sum frequency generation cross-correlation frequency-resolved optical gating (SFG-XFROG) measurement setup, besides the pulse broadening, blue shift, red shift and obvious pulse acceleration, we observed the soliton evolution when the low energy soliton pulse with wavelength of 1555nm transmit through the Si photonic crystal waveguide. The measurements were nicely matched with the simulation results, which are achieved with an optimized nonlinear Schrödinger equation (NLSE) modeling. The effects of various parameters of the silicon photonic crystal waveguides and the incident pulses on the pulse transmission were also analyzed, including the nonlinear effects and dispersion such as the self-phase modulation (SPM), self-steepening (SS) and intra-pulse Raman scattering(IRS). The results help us understand further the ultra-fast nonlinear dynamics of soliton in silicon-based waveguides, and even open a novel way for soliton-based functional elements in CMOS-compatible platforms.

This paper presents a novel high-power rotary waveguide phase shifter based on circular polarizers specifically engineered for high-power microwave (HPM) applications. The phase shifter is capable of performing a precise 360° linear phase shift through rotation and consists of three parts: a linear polarized to left-handed circular polarized (LP-LHCP) mode converter, a left-handed to right-handed circular polarized (LH-RHCP) mode converter, and a linear polarized to right-handed circular polarized (LP-RHCP) mode converter. The paper analyzes the phase shifting principle, optimizes the three parts of the X-band rotary waveguide phase shifter, and conducts simulation studies on the entire phase shifter made of aluminum. The results show that the reflection is less than -20dB and the transmission efficiency is over 95% within 9.5GHz to 10.2GHz. The phase shift has a linear relationship with the rotation angle by a factor of two within this frequency range. Specifically, the phase shifter can achieve a linear phase shift of 360° when rotated from 0° to 180°, with a maximum deviation of less than 1.2°. Moreover, the power-handling capacity of the phase shifter in vacuum exceeds 242mW.

This paper presents an extensive performance analysis of open-ended waveguide elements for direct radiating arrays with high scan angle (± 50º/60º). The evaluated designs are based on square and hexagonal apertures loaded with ridges. Both square and triangular lattices are considered in the framework of Ka-band downlink design requirements for future LEO mega-constellations. The parameter space defined by the monomodal condition has been explored to find an optimum value for each structure. The analyses are validated with both infinite and finite full-wave models in terms of active reflection coefficient, scan loss and cross-polar discrimination.

Optical parametric amplification (OPA) represents a powerful solution to achieve broadband amplification in wavelength ranges beyond the scope of conventional gain media, for generating high-power optical pulses, optical microcombs, entangled photon pairs and a wide range of other applications. Here, we demonstrate optical parametric amplifiers based on silicon nitride (Si₃N₄) waveguides integrated with two-dimensional (2D) layered graphene oxide (GO) films. We achieve precise control over the thickness, length, and position of the GO films using a transfer-free, layer-by-layer coating method combined with accurate window opening in the chip cladding using photolithography. Detailed OPA measurements with a pulsed pump for the fabricated devices with different GO film thicknesses and lengths show a maximum parametric gain of ~24.0 dB, representing a ~12.2 dB improvement relative to the device without GO. We perform a theoretical analysis of the device performance, achieving good agreement with experiment and showing that there is substantial room for further improvement. This work demonstrates a new way of achieving high photonic integrated OPA performance by incorporating 2D materials.

In this study, we design a new refractive index sensor based on a metal–insulator–metal waveguide coupled with a notched ring and vertical rectangular resonators. We use the finite element method to study the propagation characteristics of the sensor. According to the calculation results, the transmission spectrum exhibits a typical Fano resonance shape. The phenomenon of Fano resonance is caused by the coupling between the wide spectrum and narrow spectrum. In the design, the wide spectrum signal is generated by the vertical rectangular resonator, while the narrow spectrum signal is generated by the notched ring resonator. In addition, we varied the structural parameters of the resonators and filled the structure with media of different refractive indices to study the sensing properties. The maximum achieved sensitivity of the sensor reached 1071.4 nm/RIU. The results reveal potential applications of the coupled system in the field of sensors.

Principal Component Analysis (PCA) is a method that identifies common directions within multivariate data and presents the data in as few dimensions as possible. One of the advantages of PCA is its objectivity, as the same results can be obtained regardless of who performs the analysis. However, PCA is not a robust method and is sensitive to noise. Consequently, the directions identified by PCA may deviate slightly. If we can teach PCA to account for this deviation and correct it, the results should become more comprehensible. The methods for doing this and an issue with this are presented.

While some research supports utilizing plain radiography for measuring biomechanical alignment of the spine for prognosis and treatment, there are contrasting viewpoints regarding both the value and utilization of these procedures in conservative care. Evaluation of both conservative and non-conservative approaches to spinal care revealed vast differences in radiographic utilization and interpretation between orthopedic surgeons, primary care physicians, chiropractic physicians, and physical therapists, which may account for the different viewpoints and rationale in the literature. A research summary is provided regarding the various methods of spinal analysis utilized by these professions to help determine if there is any unique diagnostic or prognostic value associated with radiographic utilization that could assist in advancing conservative spinal assessment and treatment. Understanding any unique value provided through biomechanical assessment utilizing plain radiography of the spine established in the literature may help chiropractic physicians determine the appropriate use of radiographic procedures in clinical practice and how to coordinate efforts with other conservative and non-conservative professions to improve spinal healthcare.

Due to its application as an anti-cancer drug, pazopanib (1) has attracted the interest of many researchers and several studies on pazopanib synthesis have been reported over the years. This paper provides a novel route for synthesizing N,2,3-trimethyl-2H-indazol-6-amine (5) which is a crucial building block in the synthesis of pazopanib from 3-methyl-6-nitro-1H-indazole (6). By alternating between the reduction and two methylation steps compound 5 was obtained in comparable yield (55.0%) to what has been reported (54%). Noteworthy, the last step of N2-methylation also yielded N,N,2,3-tetramethyl-2H-indazol-6-amine (5’) as a new compound ever reported. Furthermore, the data presented in this paper can serve as instrumental for future research aimed at further refining the synthesis process of pazopanib.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated in microchannel structures and characterized with various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was post-processed using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of -47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg grating-based waveguide sensor demonstrates high potential for applications based on lab-on-a-chip concept.

Herein, a novel cavity design of racetrack integrated circular cavity established on metal-insulator-metal (MIM) waveguide is suggested for refractive index sensing application. Over the past few years, we have witnessed several unique cavity designs to improve the sensing performance of the plasmonic sensors created on the MIM waveguide. The optimized cavity design can provide the best sensing performance. In this work, we have numerically analyzed the device design by utilizing the finite element method (FEM). The small variations in the geometric parameter of the device can bring a significant shift in the sensitivity and FOM of the device. The best sensitivity and FOM of the anticipated device are 1400 nm/RIU and ~12.01, respectively. We believe that the sensor design analyzed in this work can be utilized in the on-chip detection of biochemical analytes.

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

A monocular vision pose estimation and identification algorithm used on a small spacecraft for future orbital servicing is studied in this paper. A tracker spacecraft equipped with a short-range vision system is proposed to recover the 3D structural model of a space target in orbit and automatically identify its solar panels and main body using only visual information from an onboard camera. The proposed reconstruction and identification framework is tested using structure-from-motion and point cloud identification methods. The Efficient Perspective-n-Points (EPnP) descriptor is used for pose estimation. Triangulated points are used for component segmentation by means of orientation histogram descriptors. Experimental results based on laboratory images of a spacecraft model show the effectiveness and robustness of our approach.

Abrus precatorius is a medicinal herb originated from Southeast Asia and native to India. The Hindustani centre of origin was found to possess lot of variability especially with respect to seed color. However, no previous researchers have focused on studying the variability by including the entire variability of the region. A total of 99 accessions were analyzed for its biochemical components like moisture content, total phenols, antioxidants, ash content, protein content, total monomeric anthocyanin and flavonols. Principal component analysis (PCA) shown that first three components viz., seed color, phenols and antioxidants are major principal components that contribute to 80.86% of total variability in the germplasm. The dendrogram constructed based on the biochemical data and by using the software Darwin version 6.0. formed three main clusters i.e. cluster 1, cluster 2 and cluster 3 which contain 55 accessions, 40 accessions and 1 accession respectively. Seed color was found to be the main criteria based on which the Abrus accessions were grouped. Accessions from different clusters also differ for their mean phytochemical constituents. Germplasm curators / plant breeders can select such elite genotypes and utilize them in crop improvement programmes.

In large-scale parallel computing and communication systems, an interconnect network structure is usually modeled as a graph, in which vertices and edges correspond to processors and communication links, respectively. In a graph, the vertices and edges are likely to fail, so we must think about the fault tolerance of a graph. Connectivity is an important parameter in the study of faulty tolerance for a graph. In this paper, we study a special class of connectivity: $m$-component connectivity, this is a natural generalization of the classical connectivity of graphs defined in terms of the minimum vertex-cut. Let $F$ is a vertex set of $G$ $(i.e, F\subseteq V(G))$, if the following conditions are satisfied, we say $F$ is a $m$-component cut: $(1)$ $G-F$ is disconnected; $(2)$ the number of components in $G-F$ is greater than or equal to $m$. In another word, the $m$-component connectivity $c\kappa_{m}(G)$ is defined as $min\{|F|~|~F\subseteq V(G)$ and $F$ is a $m$-component cut$\}$. Determining $m$-component connectivity is still unsolved in most interconnection networks even for small $m'$s. Leaf-sort graph is a special Cayley graph, it has many special properties that are different from other Cayley graphs. So we need to pay attention to some of it's special properties when we study it. In this paper, we can get the values: $c\kappa_{3}(CF_{n})=3n-6$ $(n$ is odd$)$ and $c\kappa_{3}(CF_{n})=3n-7$ $(n$ is even$)$ for $n\geq3$; $c\kappa_{4}(CF_{n})=\frac{9n-21}{2}$ $(n$ is odd$)$ and $c\kappa_{4}(CF_{n})=\frac{9n-24}{2}$ $(n$ is even$)$ for $n\geq4$; $c\kappa_{5}(CF_{n})=6n-16$ $(n$ is odd$)$ and $c\kappa_{5}(CF_{n})=6n-18$ $(n$ is even$)$ for $n\geq5$.

The nuclear factor-ĸB (NF-ĸB) transcriptional system is a major effector pathway involved in inflammatory responses. Previous studies found that a Gardenia decoction (GD) inhibited the expression of NF-κB in a lipopolysaccharide (LPS)-stimulated mouse intestinal injury model. Herein, we hypothesized that geniposide (GE), a component of Gardenia jasminoides Ellis, also exerts anti-inflammatory effects and inhibits NF-ĸB activity in LPS-induced intestinal epithelial cells (IEC-6). IEC-6 cells were stimulated with LPS, following which the effects of GE on NF-ĸB signaling in the IEC-6 cells were examined by western blotting to detect IĸB phosphorylation/degradation. The expression of NF-κB was determined by immunofluorescence assay (IFA). Enzyme-linked immunosorbent assay (ELISA) was used to detect the inhibitory effect of GE on the release of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) activated by LPS in IEC-6 cells. In addition, the migration ability of IEC-6 cells was observed by the scratch method. These results showed that GE dose-dependently downregulated levels of the proinflammatory cytokines TNF-α, IL-6 and IL-1β that had been upregulated by LPS and suppressed the phosphorylation of IĸB and NF-ĸB induced by LPS. Our findings indicated that GE could reduce LPS-induced NF-ĸB signaling and proinflammatory expression in IEC-6 cells and significantly enhance the migration of IEC-6 cells. Moreover, GE inhibited the expression of NF-κB, nuclear transfer, and transcriptional activity in IEC-6 cells. GE could block the synthesis of inflammatory factors of IEC-6 cells by inhibiting activation of the IĸB/NF-κB signaling pathway induced by LPS.

The electronics industry is a significant contributor to environmental challenges, generating approximately 50 million tons of electronic waste annually and high levels of carbon dioxide emissions throughout the production and disposal of devices. This paper investigates the interplay between reliability and sustainability by analyzing how degraded components affect the environmental footprint of electronic products. Using a board with 215 components as a baseline, we calculate the mean time between failures (MTBF) and compare it to scenarios involving degraded components. Our findings demonstrate that degraded components can reduce MTBF by up to 50%, resulting in higher failure rates, increased electronic waste, and up to 30% more CO2 emissions due to shortened product lifespans. This study underscores the crucial importance of component quality control in the production process to improve both reliability and sustainability. Additionally, the broader economic and environmental impacts of using unchecked components are highlighted, showing their contribution to elevated failure rates, shortened product lifespans, and an estimated 20% increase in e-waste. By adopting a 100% inspection protocol, leveraging advanced technologies, and enforcing stringent material quality controls, manufacturers can significantly enhance the reliability of electronic products while reducing their environmental impact, thus fostering a more sustainable electronics industry.

Immunoglobulin G (IgG) adopts a modular multidomain structure that mediates antigen recognition and effector functions, such as complement-dependent cytotoxicity. IgG molecules are self-assembled into a hexameric ring on antigen-containing membranes, recruiting the complement component, C1q. To provide deeper insights into the initial step of the complement pathway, we report a high-speed atomic force microscopy study for quantitative visualization of the interaction between IgG and the C1 complex composed of C1q, C1r, and C1s. Results showed that C1q in the C1 complex is restricted regarding internal motion and has a stronger binding affinity for on-membrane IgG assemblages than C1q alone, presumably because of smaller conformational entropy loss upon binding. Furthermore, we visualized a 1:1 stoichiometric interaction between C1/C1q and an IgG variant that lacks the entire CH1 domain in the absence of antigen. In addition to the canonical C1q-binding site on Fc, their interactions are mediated through a secondary site on the CL domain that is cryptic in the presence of the CH1 domain. Our findings offer clues for novel-modality therapeutic antibodies.

Redundancy in ship systems is provided to ensure operational resilience through equipment backups which ensures system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems, hence is provided with good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired black outs are common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensure a more robust maintenance and support platform for efficient ship operations. In this regard hybrid reliability and fault detection analysis were conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of 4 marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate overall low system reliability of less than 70 per cent within the first 24 months of the 78 operational months. Component criticality using reliability importance measures was used to identify all components with more than 40 per cent contribution to sub systems failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Networks classification. The ANN has identified failure patten threshold at about 200kva which can be attributed to overheating, hence establishing link between component failure and generator performance.

This article presents the theoretical study, numerical simulation and the fabrication of a phase shifter and stub resonator in microstrip ridge gap waveguide (MGCW) technology with the use of liquid crystal (LC) in its substrate as a reconfigurable material. The phase shifter and the stub resonator are filled with LC and thanks to LC's dielectric anisotropy properties, the phase shift and resonance response can be easily controlled using an external electric or magnetic bias field. The phase shifter was designed to operate in the range of 10 to 20 GHz and the resonator was designed to operate in the range of 7.8 to 8.8 GHz. The phase shifter's insertion losses, associated with both parallel and perpendicular LC's permittivity, as well as the phase response were computed and measured. Finally, the figure of merit (FoM) was extracted. The resonator's frequency response, associated with both parallel and perpendicular LC's permittivity, was computed. The resonator's frequency responses, provided different polarization voltages, were measured and compared to the simulation results. The technological issues were discussed. The good agreement between simulation and measurement results establishes this technology as a viable approach to the development of RF reconfigurable devices.

We investigate molecular beam epitaxy growth conditions of micrometers-thick In0.52Al0.48As designed for waveguide of InGaAs/InAlAs/InP quantum cascade lasers. Effect of growth temperature and V/III ratio on the surface morphology and defect structure were studied. The growth conditions which were developed for the growth of cascaded In0.53Ga0.47As/In0.52Al0.48As active region, e.g. growth temperature of TG=520°C and V/III ratio of 12, turned out to be not optimum for the growth of thick In0.52Al0.48As waveguide layers. It has been observed that after exceeding ~1µm thickness the quality of In0.52Al0.48As layers deteriorates. The in-situ optical reflectometry showed increasing surface roughness caused by defect forming, which was further confirmed by High Resolution X-Ray reciprocal space mapping, optical microscopy and atomic force microscopy. The presented optimization of growth conditions of In0.52Al0.48As waveguide layer led to the growth of defect free material, with good optical quality. This has been achieved by decreasing the growth temperature to TG=480 °C with appropriate increasing V/III ratio. At the same time the growth conditions of the cascade active region of the laser were left unchanged. The lasers grown using new recipe have shown lower threshold currents and improved slope efficiency. We relate this performance improvement to reduction of the electron scattering on the interface roughness and decreased waveguide absorption losses.

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.

We define a spinor-Minkowski metric for SL(4,C). It is not a trivial generalization of the SL(2,C) metric and it involves the Minkowskian one. We define 4x4 version of the Pauli matrices and eight 4-component associated generalized eigenvectors that can be regarded as undotted covariant spinors. The 4-component spinors can be grouped into four categories. Each category transforms in its own way. The outer products of pairwise combinations of 4-component spinors can be associated with 4-vectors. Including the dotted covariant, undotted and dotted contravariant forms totally we have sixteen pairs of spinors. Eight of them live in the conjugate space which has no countepart in SL(2,C).

Accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understand their structure-function relationships and electrochemical properties. Current method of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly / partially resolved and unresolved spectra, which is a common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

Analyzing big data poses a great challenge for numerous researchers to explore the data structure. Dimension reduction methods can be used to reduce data dimensionality, taking it from occupying a high-dimensional space to existing in a lower-dimensional space while retaining as much information as possible. Principal Component Analysis is one of the most popular used to reduce the dimensional space. The bootstrap sample is obtained by randomly sampling n times with replacement from the original sample, the method provides easy tool to understand the interactive component and develop the process. There are not enough researches discussed the stability of PCA method using bootstrap method. In this paper, the bootstrap method is used to analyze the stability of PCA results and to estimate the number of PCA in efficient way. The method is used to estimate the number of PCA that needed to classify the data set, and the effectiveness of the discussed techniques is demonstrated through real data sets.

In this study, the autofrettage method, which is used to increase the durability of cylindrical parts, was applied to a barrel made of steel material according to the AISI 4340 standard. Assuming that the barrel works continuously under the pressure of 400 MPa, optimum autofrettage was performed. The stresses occurring on the barrel before and after autofretage were calculated. Additionally, analytical equivalent stress values (Von-Mises) formed on the part's wall were compared with numerical analysis results obtained with a commercial finite element program ANSYS®, and their compatibility was examined. As a result of the calculations and analysis performed, it was observed that autofretage has positive effect on increasing the pressure carrying capacity of the barrel. After autofrettage the cylindrical part, it was determined that the Von-Mises stress values formed in the part wall changed and these stresses took the lowest value at a point (elastic-plastic interface). It has been evaluated that this point gives the optimal autofretage pressure value for a certain operating pressure. After the autofrettage application, it was determined that the Von-Mises Stress value in the barrel wall decreased by 25.27 % and the pressure carrying capacity of the barrel increased without any design or dimensional change. It has been seen that the analytical and numerical analysis results are consistent with each other, and it is expected that this study will guide and contribute to the studies to be conducted on increasing the strength or lightening the weight of the parts.

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.

It is shown that the termination of the channeling of the fundamental radiation mode in the waveguide can be observed upon heating of an optical integrated circuit based on proton exchange channel waveguides formed in a lithium niobate single crystal. This process is reversible, but restoration of waveguide performance takes tens of minutes. The effect of the waveguide disappearance is observed upon rapid heating (5 °C/min) from a low temperature (minus 40 °C). This effect can lead to a temporary failure of navigation systems using fiber optic gyroscopes with modulators based on a lithium niobate crystal

In this paper, a multi-mode waveguide-based optical resonator is proposed for an integrated optical refractive index sensor. Conventional optical resonators have been studied for single-mode waveguide-based resonators to enhance the performance, but mass production is limited owing to the high fabrication costs of nano-scale structures. To overcome this problem, we designed an S-bend resonator based on a micro-scale multi-mode waveguide. In general, multi-mode waveguides cannot be utilized as optical resonators, because of a performance degradation resulting from modal dispersion and an output transmission with multi-peaks. Therefore, we exploited the mode discrimination phenomenon using the bending loss, and the resulting S-bend resonator yielded an output transmission without multi-peaks. This phenomenon is utilized to remove higher-order modes efficiently using the difference in the effective refractive index between the higher-order and fundamental modes. As a result, the resonator achieved a Q-factor and sensitivity of 2.3x10³ and 52 nm/RIU, respectively, using the variational finite-difference time-domain method. These results show that the multi-mode waveguide-based S-bend resonator with a wide line width can be utilized as a refractive index sensor.

Three-layer structures based on various multi-component films of III–V semiconductors heavily doped with Fe were grown by pulsed laser sputtering of InSb, GaSb, InAs, GaAs and Fe solid targets. The structures comprising InAsSb:Fe, InGaSb:Fe and InSb:Fe layers with Fe concentrations up to 24 at. % separated by GaAs spacers were deposited on (001) i-GaAs substrates at 200ºC. Transmission electron microscopy showed that the structures have a rather high crystalline quality and do not contain secondary-phase inclusions. X-ray photoelectron spectroscopy investigations revealed significant diffusion of Ga atoms from the GaAs regions into the InAsSb:Fe layers, which has led to the formation of an InGaAsSb:Fe compound with a Ga content up to 20 at. %. It has been found that the ferromagnetic properties of the InAsSb:Fe magnetic semiconductor improve with increasing Sb:As ratio. It has been concluded that the indirect ferromagnetic exchange interaction between Fe atoms occurs predominantly via Sb atoms.

Currently, two-component integrable nonlinear equations from the hierarchies of the vector nonlinear Schrodinger equation and the vector derivative nonlinear Schrödinger equation are being actively investigated. Usually, such two-component integrable nonlinear evolutionary equations are considered, the form of which does not depend on the replacement of one component with another. In this paper, we propose for consideration and usage a new hierarchy of two-component integrable nonlinear equations, which have an important difference from the already known equations. Among the hierarchy equations there are analogues of the two-component nonlinear Schrödinger equation (second equation from hierarchy) and the two-component modified Korteweg-de Vries equation (fourth equation from hierarchy). The third equation of the hierarchy is a combination of the nonlinear Schrödinger equation for one component and the modified Korteweg-de Vries equation for the second component. The equations for the individual components are very different from each other, even if they have the same order. Let us note that even hierarchy equations can be reduced to well-known variants of the scalar derivative nonlinear Schrödinger equations, and odd equations can’t be reduced. To construct the hierarchy equations, we use the monodromy matrix method, first proposed by B.A. Dubrovin. Knowledge of the monodromy matrix makes it possible to construct spectral curves of multiphase solutions, as well as to find stationary equations that these solutions satisfy. The last section presents the simplest solutions in the form of solitons and periodic one-phase waves, as well as spectral curves corresponding to these solutions.

This study aims to develop novel automated computer vision algorithms and systems for component replacement inspection for Printed Circuit Boards (PCBs). The proposed algorithms are able to identify locations as well as sizes of different components. They are object detection algorithms based on keypoints of the target components. The algorithms can be implemented as neural networks consisting of two portions: frontend networks and backend networks. The frontend networks are used for the feature extractions of input images. The backend networks are adopted for producing component inspection results. Each component class can has its own frontend and backend networks. In this way, the neural model for the component class can be effectively reused for different PCBs. To reduce the computation time for the inference of the networks, different component classes can share the same frontend networks. A two-stage training process is proposed for effectively exploring features of different components for accurate component inspection. The proposed algorithm has the advantages of the simplicity for training data collection, high accuracy for defect detection, and high reusability and flexibility for online inspection. The algorithm is an effective alternative for the automated inspection in smart factory with growing demand for product quality and diversification.

The coombs (in Catalan comes) form an integral part of the landscape. These are small valleys, with the deepest and flattest part cultivated for agriculture. They are predominantly found in the most arid regions of Catalonia, particularly around the cities of Tarragona and Lleida. They are generally dry land areas. We propose that these coombs gained significance in the early centuries of the Middle Ages, a period marked by intense erosion. It is important to identify their locations and establish connections with medieval written documents, the settlements that thrived throughout the Middle Ages, archaeological sites such as necropolises, and the valuable data derived from to-ponymy studies. We think that understanding these coombs can greatly contribute to under-standing how the territory was organized in the Middle Ages, the extent of cultivated lands that were established, and the distribution of many settlements. Ultimately, this knowledge can aid in acquiring better understanding of the current landscape.

The aim of this study was to examine whether H2O2, generated in such beverages as tea and coffee, is formed also in infusions of medicinal herbs and propose the possible mechanism of its formation. Infusions of sixteen herbs were studied and the presence of H2O2 was found in all cases. The highest concentrations of H2O2, exceeding 50 µM, were found in the infusions of leaves of Betula and Polygonum, and of the inflorescence of Tilia. These low amounts of H2O2 should not have a harmful effect and may even exert beneficial action, perhaps contributing to the health effects of the herbs. Generation of semiquinone and superoxide radicals was detected in herbal infusions, indicating that oxidation of phenolic compounds is the main source of H2O2 in these infusions. Herbal infusions were cytotoxic to human ovary cancer SKOV-3 and PEO1 cells; this cytotoxicity was compromised by catalase added to the growth medium, demonstrating the contribution of hydrogen peroxide to the cytotoxic action of herbal extracts.

The well-known coupling between the magnetic and electric fields in electromagnetic radiation is revisited in light of the recent introduction of a microscopic theory for the Ørsted magnetic field induction. I argue that, if the Ørsted magnetic field induction does indeed have a microscopic origin rather than the continuum solution offered by the Maxwell-Ampere equation, the "electromagnetic wave"' propagating in vacuum will not have a magnetic component.

In this paper, the quantum theory of the infinite-component Majorana field for the fermionic tower is formulated. This study proves that the energy states with increasing spin are simply composite systems made by a bradyon and antitachyons with half-integer spin. The quantum field describing these exotic states is obtained by the infinite sum of four-spinor operators, which each operator depends on the spin and the rest mass of the bradyon in its fundamental state. The interaction between bradyon-tachyon, tachyon-tachyon and tachyon-luxon has also been considered and included in the total Lagrangian. The obtained theory is consistent with the CPT invariance and the spin-statistics theorem and could explain the existence of new forms of matter not predictable within the standard model.

In this work we explore the utilization of plasmonic resonance (PR) in silver nanowires to enhance the performance of organic solar cells. Plasmonic resonance is a phenomenon in which nanoscale conductive materials exhibit oscillation of conduction electrons, resulting in the creation of an electric field. Enhancing light absorption is crucial for improving organic solar cell efficiency and incorporating metallic nanostructures to induce surface plasmon resonance (SPR) shows promise in achieving this goal. We discuss the two key mechanisms of plasmonic effects: far-field scattering and near-field resonance modes. Far-field scattering extends the optical path of incident light, while near-field plasmonic effects involve localized surface plasmon resonance (LSPR) and plasmonic cavity modes, enhancing absorption by strengthening electric fields near the nanostructures. Silver nanowires are the focus of this study, and finite-difference time-domain (FDTD) simulation software is used to investigate their plasmonic resonance behavior in a ZnO/Silver nanowires/ZnO (ZAZ) electrode structure. The simulations reveal the dominance of LSPR in this configuration, with intense electric fields inside the nanowire and propagation into the surrounding medium, offering opportunities for enhanced light absorption in the organic solar cell's active layer.

Abstract Big datasets are becoming increasingly common and can be challenging to understand and apply in public health. One method for lowering the dimensionality of these datasets and improving interpretability while minimizing information loss is data reduction using principal component analysis (PCA). It achieves this by successively maximizing variance through the creation of new, uncorrelated variables. PCA is an adaptive data analysis technique because it simplifies the process of finding new variables, or principal components, by solving an eigenvalue or eigenvector problem. These new variables are determined by the dataset being used, rather than by the analyst starting from scratch. It is also adaptable in another way because varieties of the method have been designed to adjust to various data structures and types. However, there are serious problems in the theoretical understanding and practical application of PCA in public health researchers, whereas its application is becoming popular in developing countries. Therefore, this article, which concentrated on using PCA to reduce data, began by outlining the fundamental concepts of PCA and going over what it can and cannot do, as well as when and how to use it. We also discussed the fundamental assumptions, benefits, and drawbacks of PCA. Furthermore, this article demonstrated and resolved PCA practical application problems in public health that most scholars are unaware of, such as variable preparation, variable inclusion and exclusion criteria for PCA, iteration steps, wealth index analysis, interpretation, and ranking.

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.

In this paper we review dynamics and roughness of bonds in proteins on example of albumin, that is important from the physiological point of view. We have performed computer simulations of albumin chain. Statistics were collected by performing many simulations realizations for each experimental setting. We concentrate on hydrogen bonds, cation-π and π- π interactions and NP contacts. Histograms of hydrogen bonds length are positively skewed in contrary to histograms of interactions and HP contacts that are negatively skewed. Scaling exponents of power spectra of energies of bonds / interactions /contacts are in range -0.2 to -0.5 and significantly differ between various hydrogen bonds or interactions. Varying scaling of such spectra can be used to classify between distinct bonds or contacts. Concerning particular amino-acids, largest amount of HBO H20 bonds are between Glutamate (GLU) amino-acids and water particle, while large amount of HBO bonds are formed with Lysine (LYS). For HP contacts the mayor role plays Phenylalanine (PHE) and Leucine (LEU) amino-acids. From decay curves HBO H2O bonds decays in fastest rate, while HBO bonds and HP contacts at slowest rate. We present as well decay curves of bonds formed by particular amino-acids, that gives interesting results.

Ulcerative colitis has a significant impact on the quality of life for the patients, and can substantially increase the risk of colon cancer in patients suffering long-term. Conventional treatments provide only modest relief paired with a high risk of side effects, while complementary and alternative medicines can offer safe and effective options. Over the past decade, we have shown that American ginseng has anti-oxidant and anti-inflammatory properties that can suppress mouse colitis and prevent colitis associated colon cancer. With the goal of isolating a single active compound, we further fractionated the hexane fraction, and found the most abundant molecule in this fraction was the polyacetylene, Panaxynol. After isolating and characterizing Panaxynol, we tested the efficacy of Panaxynol in the treatment and prevention of colitis in mice and studied the mechanism of action. We demonstrate here that Panaxynol effectively treats colitis in a Dextran Sulfate Sodium mouse model by targeting macrophages for DNA damage and apoptosis. Positive outcomes from this study could take American ginseng one-step further towards becoming a conventional drug for the treatment of colitis, and possibility exploring other autoimmune diseases associated with macrophage dysfunction.

This work develops a new method for vector data augmentation. The proposed method applies the Principal Component Analysis (PCA) and determines the Eigenvectors of a set of training vectors for a Machine Learning (ML) method and uses them to generate the distilled vectors. The training and the PCA distilled vectors have the same dimension. The user chooses the number of vectors to be distilled and augmented to the set of training vectors. A statistical approach determines the lowest number of vectors to be distilled such that when augmented to the original vectors the extended set trains a ML classifier to achieve a required accuracy. Hence, the novelty of this study is, the distillation of vectors with the PCA method and their use to augment the original set of vectors. The advantage that comes from the novelty is that it increases the statistics of ML classifiers. To validate the advantage, we conducted experiments with four public databases and applied four classifiers: Neural Network, Logistic Regression, Support Vector Machine with linear and polynomial kernels. For the purpose of augmentation, we conduct several distillations including nested (double distillation). The latter notion means that new vectors were distilled from already distilled vectors. We train the classifiers with three sets of vectors: original vectors; original augmented with vectors distilled by PCA; original augmented with distilled and double distilled, by PCA, vectors. The experimental results are presented in the paper, and they confirm the advantage that the PCA distilled vectors increase the classification statistics of ML methods, if the distilled vectors augment the original training vectors.

This study introduces a new procedure for three-component spectral matching of seismic ground acceleration records. The procedure involves preserving the phase angle and varying the Fourier amplitudes to match the spectra of the recorded records with a provided target spectrum that represents the spectral values of ground motions in three orthogonal directions. Several three-component recorded records were matched against two target response spectra to test the method. An accurate convergence was achieved in the velocity and displacement records. In addition, the scales among the components’ magnitude were maintained, creating realistic three-component ground motions. Such ground motion inputs are important to qualify critical structures sensitive to three-component motions. Our proposed procedure is novel because the present practices are mostly created based on one-component ground motions.

Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated a simple, interpretable, and transferable quantitative-RASAR (q-RASAR) model which can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials. The data set involves 29 TiO2-based nanomaterials which contain specific amounts of noble metal precursors in the form of Ag, Au, Pd, and Pt. The data set was rationally divided into training and test sets and the Read-Across-based predictions for the test set were generated using the tool Read-Across-v4.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The hyperparameters were optimized based on the training set data and using this optimized setting, the Read-Across-based predictions for the test set were obtained. The optimized hyperparameters and the similarity approach, which yields the best predictions, were used to calculate the similarity and error-based RASAR descriptors using the tool RASAR-Desc-Calc-v2.0 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. These RASAR descriptors were then clubbed with the physicochemical descriptors and were subjected to features selection using the tool Best Subset Selection v2.1 available from https://dtclab.webs.com/software-tools. The final set of selected descriptors was used to develop multiple linear regression based q-RASAR models, which were validated using stringent criteria as per the OECD guidelines. Finally, a random forest model was also developed with the selected descriptors. The final machine learning model can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials superseding previously reported models in the prediction quality.

Micro turbojets are used for propelling radio-controlled aircraft, aerial targets and personal air vehicles. When compared to full-scale engines, they are characterized by relatively low efficiency and durability. In this context, the degraded performance of gas path components could lead to an unacceptable reduction in the overall engine performance. In this work, a data-driven model based on a conventional Artificial Neural Network (ANN) and an extreme learning machine (ELM) was used for estimating the performance degradation of the micro turbojet. The training datasets containing the performance data of the engine with degraded components were generated using the validated GSP model and the Monte Carlo approach. In particular, compressor and turbine performance degradation were simulated for three different flight regimes. It was confirmed that component degradation had a similar impact in flight than at sea level. Finally, the datasets were used in the training and testing process of the ELM algorithm with four different input vectors. Two vectors had an extensive number of virtual sensors, and the other two were reduced to just fuel flow and Exhaust Gas Temperature. Even with the small number of sensors, the high prediction accuracy of ELM was maintained for takeoff and cruise but was slightly worse for variable flight conditions.

Multispectral remote sensing data may contain component images which are heavily corrupted by noise and pre-filtering (denoising) procedure is often applied to enhance these component images. To do this, one can use reference images – component images having relatively high quality and which are similar to the image subject to pre-filtering. Here we study the following problems: how to select component images that can be used as references (e.g., for the Sentinel multispectral remote sensing data) and how to perform the actual denoising. We demonstrate that component images of the same resolution as well as component images of a better resolution can be used as references. Examples of denoising of real-life images demonstrate high efficiency of the proposed approach.

Anomaly occurrences in hydraulic machinery may lead to massive systems shut down, jeopardizing the safety of the machinery and its surrounding human operator(s) and environment, and the severe economic implications succeeding the faults and their associated damage. Hydraulics are mostly placed in ruthless environments, where they are consistently vulnerable to many faults. Hence, not only the machines and their components are prone to anomalies, but also the sensors attached to them, which monitor and report their health and behavioral changes. In this work, a comprehensive applicational analysis of anomalies in hydraulic systems extracted from a hydraulic test rig is thoroughly achieved. Firstly, we provided a combination of a new architecture of LSTM autoencoders and supervised machine and deep learning methodologies to perform two separate stages of fault detection and diagnosis. The two phases are condensed by: the detection phase using the LSTM autoencoder. Followed by the fault diagnosis phase represented by the classification schema. The previously mentioned framework is applied to both component and sensor faults in hydraulic systems, deployed in the form of two in-depth applicational experiments. Moreover, a thorough literature review of the past decade related work for the two stages separately is successfully conducted in this paper.

Some studies investigated the relationship between frequency domain analysis of heart rate variability and the cognitive performance at the Stroop task. We propose a combined assessment also of trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac and motor variables based on a principal component analysis. We also assessed the change on this result after an intervention of two months aiming at improving the perception-action link. At baseline, the PCA correctly identified 3 components: one related to cardiac variables, one to trunk motion and one to the performance of Stroop task. After the intervention, only two components were found with trunk symmetry and range of motion, accuracy and time to complete the Stroop task and low frequency heart rate variability aggregated in a single component by PCA. It suggested that this protocol was effective in investigating the embodied cognition and we defined this approach as “embodimetrics”.

State Forest Management Organizations (SFMOs) play a crucial role in the European forest sector, managing almost half the forests in the region. SFMOs are often managed for timber production only whereas, being publicly owned, they should play an important role in providing a vast range of public goods (e.g. soil protection, biodiversity conservation). Their management goals depend on the history and current conditions of the forest sector at a national level, as well as different challenges and the potential for development. Although there is a lack of knowledge about the current performance of SFMOs, there have been recent changes to their management goals and practices in response to the new demands expressed by society (e.g. transparency, social inclusion). The main purpose of this study is to analyse the current situation of SFMOs by clustering them according to indicators that reflect three pillars of the common understanding of sustainable forest management (SFM) concept. With the help of Principal Component Analysis (PCA), we grouped countries according to common characteristics of the forest sector at the national level. Results show three main clusters of SFMOs in Europe. The first cluster has rather small but commercially-oriented forestry unit together with other business activities and a strong focus on public services. The second sees itself as the protector of public interest, rather than commercially-oriented organisations. The third is mainly profit-seeking. The existence of diverse SFMO clusters shows the possibility of different approaches for SFM with a focus on different goals (e.g. profit gaining, public service delivery).

Citrus essential oils (EOs) have various bioactivities like antioxidants, with many applications. Antioxidant activities depend on the chemical compositions of the EOs, which are affected by climate, soil, and geographical region. Thus, investigations on chemical compositions and antioxidant activities of Citrus EOs in different countries are valuable. In this study, we distilled EOs from peels of Indonesian-grown Citrus, including C. nobilis, C. limon, C. aurantifolia, C. amblycarpa, and Citrus spp.Chemical compositions of EOs were analyzed using Gas Chromatography-Mass Spectrometer (GC-MS), whereas the antioxidant activities were determined by employing 2,2-diphenyl-2-picrylhydrazyl (DPPH) method. Furthermore, principal component analysis (PCA) was applied to elucidate the main contributing compounds for antioxidant activity. The results show that all EOs possess unique chemical characteristics, with limonene as the majority constituent. For antioxidant activities, C. limon and C. amblycarpa EOs are the two strongest, IC50 values below 7.00 μL/mL. PCA approach suggests that -terpinene mainly contributes to the high antioxidant activities of C. limon and C. amblycarpa. Moreover, o-cymene, thymol, p-cymene, and α-pharnesene may also be responsible for the antioxidant activity of C. limon EO. These results are valuable information for the applications of Citrus EOs as antioxidant sources.

In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-Wavelet-ANN models are compared with those obtained from Wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid Wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the Wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-Wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicators in rivers.

The Independent Component Analysis (ICA) has been recently introduced as a reliable alternative to identify canonical scattering mechanisms within Polarimetric Synthetic Aperture Radar (PolSAR) images. This manuscript addresses two important aspects when applying such methods on real data, namely speckle filtering and statistical classification with ICA. A novel PolSAR data processing framework is introduced by adjusting the Lee's sigma filter to the particular nature of the Touzi's polarimetric decomposition. In its current form, it allows the use of the ICA mixing matrix in the derived speckle filter. An extension of the Fromont at al. iterative segmentation is introduced, equally. This proposed framework is tested using P band airborne PolSAR data acquired for the ESA campaign TropiSAR campaign.

Introduction and objectives: a close association between metabolic syndrome among subjects with erectile dysfunction has been addressed, since mechanisms underlying metabolic syndrome compromise the blood flow to the penis in numerous ways. This study aims to analyze the relationship between erectile dysfunction and metabolic syndrome in a group of Mexican patients, to study the influence of other morbidity factors on erectile dysfunction, and to define the specific metabolic syndrome components most associated with erectile dysfunction severity. Methods: a descriptive and cross-sectional study was completed in a group of 86 adult Mexican patients with previous diagnosis of erectile dysfunction. Participants were classified as with or without metabolic syndrome. Erectile dysfunction severity, alcohol or tobacco consumption, and depressive behavior were identified through validated questionnaires and compared between both groups, as well as anthropometric, biochemical, and clinical parameters. Results: anthropometric measures, laboratory values, clinical characteristics and the Beck Depression Inventory score were significantly different among both groups. Additionally, more patients affected by severe and moderate erectile dysfunction were identified in the group with metabolic syndrome. Among the metabolic syndrome components, HbA1c >5.7% and fasting glucose >110 mg/dl were significantly associated to the development of erectile dysfunction (p = 0.004 and 0.04, respectively). Conclusions: metabolic syndrome components aggravate erectile dysfunction, particularly the lack of glycemic control manifested by Hb1Ac >5.7% and/or fasting glucose >110 mg/dL. The inclusion of fasting glucose and HbA1c as a complementary biochemical screening among patients with erectile dysfunction should be assessed.

We demonstrate hybrid integration of a lithium niobate microring resonator with a silicon nitride waveguide in the vertical configuration to achieve efficient light coupling. The microring resonator is fabricated on a lithium niobate on insulator (LNOI) substrate using photolithography assisted chemo-mechanical etching (PLACE). A fused silica cladding layer is deposited on the LNOI ring resonator. The silicon nitride waveguide is further produced on the fused silica cladding layer by first fabricating a trench in the fused silica using focused ion beam (FIB) etching for facilitating the evanescent coupling, followed by formation of the silicon nitride waveguide on the bottom of the trench. The FIB etching ensures the required high positioning accuracy between the waveguide and the ring resonator. We achieve Q-factors as high as 1.4*10^7 with the vertically integrated device.

Background The Delta Neutrophil Index (DNI), a prodiagnostic marker for sepsis, utilizes leukocyte count. Platelet activation, similar to leukocytes, plays a crucial role in host defence against pathogens and may serve as a predictor of sepsis outcome. However, the combined evaluation of Mean Platelet Component (MPC) and DNI in assessing sepsis has been rarely used. Methods To assess the prodiagnostic validity of simultaneous utilization of DNI and MPC in cases of human febrile sepsis, we conducted measurements of cellular indices, including DNI and MPC, as well as molecular biomarkers such as procalcitonin (PCT) and C-reactive protein (CRP). This study was carried out on patients admitted to the emergency department with suspected sepsis. Results Using a cutoff value of 2.65%, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DNI in sepsis were found to be 69%, 73.9%, 77.9%, and 64.1%, respectively. Furthermore, significant differences in DNI and MPC levels were observed between the sepsis and non-sepsis groups (6.7±7.8% versus 2.1±2.2%, P=0.000 and 26.0±1.9 g/dl versus 26.8±1.4 g/dl, P=0.002), respectively. Notably, there was a negative correlation between DNI and MPC, with the strength of the correlation varying based on the cause of sepsis. By setting the cutoff value for DNI at 6.2%, the sensitivity, specificity, and NPV improved to 100%, 80.3%, and 100%, respectively, although the PPV remained at 10.6%. Importantly, the DNI≥6.2 group exhibited a higher incidence of death (10.9%, 5/46) and multiorgan failure (19.6%, 9/46) compared to the DNI<6.2 group (0.0%, 0/46 and 0.0%, 0/167, respectively) (P=0.000 and P=0.000, respectively). Conclusions In our study, DNI demonstrates superior effectiveness compared to other molecular biomarkers such as CRP and procalcitonin in distinguishing febrile septic patients from febrile nonseptic patients and predicting prognosis. Additionally, there exists a negative correlation between MPC and DNI, making MPC a valuable marker for differentiating the etiology of sepsis. These findings hold significant clinical implications as DNI/MPC is a cost-effective and readily applicable approach in various impending sepsis scenarios. Notably, this study represents the first examination of the prodiagnostic validity of simultaneously employing DNI and MPC in human cases of febrile sepsis.

The (benzylthio)acetic acid (HBTA) and some aminopyrimidines, namely 2-aminopyrimidine (2-AP), 5-aminopyrimidine (5-AP), 2-amino-4,6-dimethylpyrimidine (2-A-4,6-DMP) and 2,4,6-triaminopyrimidine (2,4,6-TAP), were successfully embodied as structural units into the construction of a total of four novel supramolecular organic frameworks. The received crystalline solids were inspected by single crystal X-ray diffraction (SC XRD) in order to obtain insight into the structural and supramolecular facets. The SOFs deriving from 2-AP, 5-AP as well as 2-A-4,6-DMP crystallize in the form of true co-crystals (1-3), while the one originating from 2,4,6-TAP crystallizes as salt solvate (4). The SC XRD results indicated the different contents of structural residues present in the asymmetric units of the crystals 1-4 despite the using the same molar ratio of molecular co-formers in each case. The molecular structures of co-crystals 1-3 consist of either one neutral residue of each starting components (1 and 3) or a half nonionized residue of aminopyrimidine ingredient and one neutral residue of acidic specie (2). The asymmetric unit of salt solvate 4 is composed of two ionized residues of each co-former (two 2,4,6-TAP+ cations and two BTA- anions) and one MeOH solvent molecule. The most extensive H-bonding network is observed in the crystal structure of salt solvate 4. The relevant molecular ingredients in co-crystals 1-3 are mainly hold together by the neutral Ocarboxylic–H···Npyrimidine and Namine–H···Ocarboxylic H-bonds. In the case of aggregate 4, the corresponding ionic residues are predominantly sustained by the charged-assisted Npyrimidinium–H···Ocarboxylate and Namine–H···Ocarboxylate hydrogen interactions. The MeOH solvent incorporated into the crystal lattice of adduct 4 is also involved in H-bonding by simultaneously serving as the single donor in OMeOH–H···S and the single acceptor in Namine–H···OMeOH H-bonds afforded the structural diversity within the 2,4,6-TAP+ cations and BTA- anions. Other weaker sets of additional non-covalent contacts existing in the crystal structures of analyzed conglomerates are involved in the self-assembly, stabilization and expansion of total supramolecular organic frameworks. The fact of the formation of non-covalent bonded supramolecular organic frameworks in question is also reflected in corresponding results obtained through elemental analysis (EA), Fourier transform infrared spectroscopy (FT−IR) and thermal analysis (TG/DSC).

Cardiovascular disease is the number one cause of death in the world and Quoting from WHO, around 31% of deaths in the world are caused by cardiovascular diseases and more than 75% of deaths occur in developing countries. The results of patients with cardiovascular disease produce many medical records that can be used for further patient management. This study aims to develop a method of data mining by grouping patients with cardiovascular disease to determine the level of patient complications in the two clusters. The method applied is principal component analysis (PCA) which aims to reduce the dimensions of the large data available and the techniques of data mining in the form of cluster analysis which implements the K-Medoids algorithm. The results of data reduction with PCA resulted in five new components with a cumulative proportion variance of 0.8311. The five new components are implemented for cluster formation using the K-Medoids algorithm which results in the form of two clusters with a silhouette coefficient of 0.35. Combination of techniques of Data reduction by PCA and the application of the K-Medoids clustering algorithm are new ways for grouping data of patients with cardiovascular disease based on the level of patient complications in each cluster of data generated.

The Inefficient water use, varying and low productivity in Kenya public irrigation schemes is a major concern. It is therefore necessary to periodically monitor and evaluate the performance of public irrigation schemes. The performance of public irrigation in western Kenya was assessed by combining benchmarking methodology and principal component analysis. The aim was to quantify and rank the performance of pumped public irrigation schemes in Kenya. Eleven benchmarking indicators were computed for the period from 2012 to 2016 and compared to global benchmark values. The indicators used fall under agricultural productivity, water supply and financial performance categories. The computed agricultural productivity was 36%–51% in Ahero, 23%–42% in West Kano and 26%–50% Bunyala irrigation scheme. Water supply performance in Ahero, West Kano and Bunyala irrigation schemes varied from 24% to 58%, 3% to 49% and 19% to 43% respectively. Financial performance varied from 46% to 54% in Ahero, 25% to 32% in West Kano and 54%–56% in Bunyala irrigation scheme. An average overall performance efficiency of 46%, 39% and 31% was obtained in Ahero, Bunyala and West Kano irrigation schemes respectively. The performance of the irrigation schemes is very poor and measures on improving performance are needed.

Background: Metastasis is a complex process that involves the spread of the tumor to distant parts of the body from its original site. Metastatic dissemination represents the main physiopathology of cancer. Soluble factors such as cytokines have been closely related to breast cancer (BC) metastasis. Bisphenol A (BPA) is an endocrine disrupting chemical compound with estrogenic properties, which exposure in the early stages of neonatal life leads to an increase in the size and weight of breast tumors and cellular changes in the tumoral immune microenvironment. Methods: Thus, we used female BALB/c mice that were exposed neonatally to a single dose of BPA. Once sexual maturity was reached, a mammary tumor was induced injecting 4T1 cells in situ. After 25 days of injection, we evaluated endocrine alterations, cytokine expression, tissue alterations denoted by macro and micro metastases in the lung, and metastasis-induced cell infiltration. Results: BPA neonatal treatment did not show significant endocrine alterations. Nevertheless, BPA induced a great rate of metastasis to the lung associated with higher intratumoral expression of IL-1b, IL-6, IFN-g, TNF-a and VEGF. Conclusions Our data suggest that cytokines are key players in BC metastasis induction, and that BPA is a risk factor to be considered. This knowledge must be considered with the aim of recognizing environmental pollution in the clinical history of patients to possibly counter BC metastases.

Asphalt cement will not last for a long time as the world encounters a diminishment in the crude oil. For sustainable, flexible pavement development, new resources can provide a contribution to replace it partially or entirely. In this study, asphalt was partially and entirely replaced by guayule resin as a bioresource by-product, extracted during the guayule natural rubber production. Crumb rubber modifier (CRM) was used as an asphalt enhancer. The Superpave grading system was followed at high, intermediate, and low temperatures to evaluate such innovative binder for rutting, fatigue, and thermal cracking, respectively, in addition to viscosity. Therefore, the original, short-term aging and long-term aging were simulated using tank, rolling thin film oven, and pressure aging vessel materials. Additionally, component analysis using Fourier-transform infrared spectroscopy was provided to link the rheological properties with the chemical changes. Outcomes showed a relatively much lower viscosity of guayule in the same high-temperature asphalt grade indicating savings in plant energy consumption and reduced environmental emissions. CRM enhanced guayule, but not as much as asphalt, proven by polymeric component migration through liquid binder. This enhancement was reflected in the rheological performance besides other factors. As-received guayule seems to have high oxygen content proven by strong absorption peak intensities of oxidative bonds (e.g., Carbonyl and sulfoxide). Such pre-oxidation was negatively reflected in the intermediate- and low-temperature performance of guayule and guayule-based binders. However, the investigated guayule had potential to compensate for asphalt replacement in the presence of CRM by 23–42% by weight of blend.

A compositional data vector is a special type of multivariate observation in which the elements of the vector are non-negative and sum to a constant, usually taken to be unity. A compositional data does not have zero and only retains relative information. Furthermore, comparisons can only be made between compositional data of the same component. The relevant sample space is the standard simplex. A simplex space is a space that is a generalized form of a triangle. For compositional data, many of the operations defined in Euclidean space are meaningless. Microbiome analyzes have become popular in recent years. Operational Taxonomic Units (OTU) and Amplicon Sequence Variants (ASVs) used in microbiome analysis are one type of compositional data. The microbiome data are counts of different species within a sample and it is compositional. Although there is an order of bacterial abundance within a sample, there is no order of bacterial abundance between samples. Firmicutes and Bacteroidetes, the major phyla in the colon, have been observed in humans worldwide. Gut microbiome analyses often use the Firmicutes/Bacteroidetes ratio and principal coordinates analysis (PCoA). Alpha and beta diversities are used as indicators of bacterial flora diversity. However, misinformation is pervasive in the human microbiome literature and analysis. There is a lot of misunderstanding regarding compositional data and its analysis. An attempt was made to demonstrate how to analyze using the “National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN JMD) (Public Data).” The results showed that PCoA did not work, and principal component analysis (PCA) was useful for analyzing the gut microbiome relative diversity.

This paper focuses on the application of principal component analysis (PCA) to conduct a source apportionment of atmospheric aerosols from 8 sampling locations along the Marilao-Meycauayan-Obando River System (MMORS). Aerosols were collected on May 2016 during the same time that water samples were collected. Elemental analysis was conducted using a scanning electron microscope coupled with energy dispersive x-ray (SEM-EDX). Carbon (C), nitrogen (N), oxygen (O), sodium (Na), magnesium (Mg), aluminum (Al), silicon (Si), sulfur (S), chlorine (Cl), potassium (K), calcium (Ca), titanium (Ti), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), bromine (Br), niobium (Nb), barium (Ba), mercury (Hg), and lead (Pb) concentrations were measured and used as inputs in Principal Component Analysis (PCA). The aerosol samples showed the presence of heavy metals Pb and Hg, elements that were also detected in trace amounts in the water measurements. Concentrations of heavy metals Fe, Pb, Hg in the aerosols were attributed to industrial sources. However, it was determined that the primary source of aerosols in the area were traffic and crustal emissions (C, N, O, Si, Al, Ca). Thus, control of traffic emissions would be more beneficial in reducing aerosol emissions in Meycauayan.

Frequency, amplitude and phase information of the grid voltage are of great importance in constructing a robust controller structure for grid connected inverter systems. This paper presents a simple and robust approach for the instantaneous estimation of positive and negative sequence voltage components under distorted voltage conditions. A second order generalized integrator (SOGI) is used to filter the distorted voltage and to generate orthogonal voltage components for each of the three phases. These filtered and orthogonal components are used for instantaneous calculation of symmetrical components. The implemented method is frequency adaptive; the method is demonstrated and compared to a conventional phase locked loop (PLL) technique with both MATLAB/Simulink simulations and experiments utilizing the dSPACE ds1103 digital controller.

The increasing concern regarding climate change continues to motivate research in the Arctic. Within the delicate cycle of the cryosphere, leads are an important kinematic feature that regulate heat balances in the Arctic. Therefore, it is necessary to quantify the genesis of leads over time to identify when and where changes are occurring. The use of a principal component analysis (PCA) is one such tool that is used to identify the characteristics of seasonal ice variability. The PCA not only identifies “normal” or “dominant” conditions or features, but also extract anomalous spatial features from an archive of long-term sequence of images.

: In this article, the authors propose an algorithmic approach to building a model of the dynamics of economic and, in particular, innovation processes. The approach under consideration is based on a complex algorithm that includes (1) decomposition of the time series into components using singular spectrum analysis; (2) recognition of the optimal component model based on fuzzy rules, and (3) creation of statistical models of individual components with their combination. It is shown that this approach corresponds to the high uncertainty characteristic of the tasks of the dynamics of innovation processes. The proposed algorithm makes it possible to create effective models that can be used both for analysis and for predicting the future states of the processes under study. The advantage of this algorithm is the possibility to expand the base of rules and components used for modeling. This is an important condition for improving the algorithm and its applicability for solving a wide range of problems.

(1) Background: In order to study the effects of different electric cookers on the nutritional components of millet porridge, five different electric cookers were selected to cook millet porridge, and sensory and nutritional components in millet porridge, millet soup, and millet grains were analyzed. (2) Methods: Using principal component and cluster analysis, a variety of nutritional components were comprehensively compared. (3) Results: The results showed that among the different cooked samples, the content of amylose and reducing sugar was the highest in the samples cooked by electric cooker no. 3. The electric cooker no. 4 samples had the highest sensory evaluation score, crude fat, and protein content. The contents of ash, fatty acids, bound amino acids, and minerals were the highest in the electric cooker no. 5 samples. The sensory evaluation score and content of crude fat, ash, reducing sugar, direct starch, and Cu were higher in millet grains than in millet soup or porridge. The content of fatty acid, protein, amino acid, Zn, Fe, Mg, Mn, and Ca was highest in millet soup. Different electric cookers produced millet porridge with varying nutritional levels. (4) Conclusions: This study provides a reference for the further development of new electric cookers.

The aim of this study was to synthesize and characterize a novel Methacrylate- functionalized Calcium Phosphate (MCP) used as a bioactive compound for innovative dental composites. The characterization was accomplished by Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR), X-Ray Diffraction Analysis (XRDA), Scanning Electron Microscopy (SEM), and EnergyDispersive Spectroscopy (EDS). The incorporation of MCP as a bioactive filler in esthetic dental composite formulations and the ability of MCP containing dental composites to promote precipitation of hydroxyapatite (HAp) on the surfaces of those dental composites was explored. The translucency parameter, depth of cure, degree of conversion, ion release profile, and other physical properties of composites were studied with respect to the amount of MCP added to the composites. Composites containing 3 Wt.%, 6 Wt.%, and 20 Wt.% MCP were evaluated at 7, 14, and 21 days. The progress of surface precipitation of hydroxyapatite on MCP-containing dental composites was studied by systematically increasing the MCP content in the composite and the time of specimen storage in Dulbecco’s phosphate-buffered solution with calcium and magnesium. It was found that there was a direct correlation between the percentage of MCP in a composite formulation, the amount of time the specimen was stored in PBS, and the deposition of hydroxyapatite on the composite’s surface

This article presents a self balanced multistage DC-DC step-up converter for photovoltaic applications. Proposed converter topology is designed for unidirectional power transfer and provides a doable solution for photovoltaic applications where voltage is required to be stepped up without magnetic components (Transformer-less and Inductor-less). The output voltage obtained from renewable sources will be low and must be stepped up by using a DC-DC converter for photovoltaic applications. K diodes and K capacitors along with two semiconductor control switch are used in the K-stage proposed converter to obtain an output voltage which is (K+1) times the input voltage. The conspicuous features of proposed topology are i) Magnetic components free (Transformer-less and Inductor-less). ii) Continuous input current iii) Low voltage rating semiconductor devices and capacitors iv) Modularity v) Easy to add a higher number of levels to increase voltage gain vi) Only two control switches with alternating operation and simple control. The proposed converter is compared with recent existing transformer-less and Inductor-less power converter in term of voltage gain, number of devices and cost. The application of proposed circuit is discussed in detail. The proposed converter has been designed with rated power of 60W, input voltage is 24V, output voltage is 100V and switching frequency is 100 kHz. The performance of the converter is verified through experimental and simulation results.

This study x-rays the philosophical meanings, interpretations, and intersections of death and wealth in Igbo cosmology. Using such tools as oral interviews, ethnography and participant observations, the researcher extracted data from both primary and secondary sources to clarify some misconceptions surrounding wealth and death in Igbo religious and philosophical thought. This research is timely because amidst a growing literature on the Igbo people and culture, discourses on the complementarity and convergence of good death and wealth have lacked attention over the years. This work fills this gap through the application of hermeneutic approach which enabled an informed conclusion that the Igbo recognise two categories of death: the bad death and the good death. While The bad death is abhorred and avoided, the good death is the expectation of every Igbo human person as it is a strong component of wealth. The findings provide a better understanding of African Igbo culture, death, wealth, and the meanings they attach to life which is equally important for a harmonious relationship and a stable social order. The paper calls for a reexamination of the narratives surrounding peripheral interpretations given to this aspect of Igbo culture. It further contributed to the growing volumes of literature on Igbo history, indigenous philosophy, and religion, among others.

The inherent capabilities of the K-means++ algorithm to approximate system dynamics within complex systems are subjected by constructing a network structure that captures interconnections among identified components, extending its original purpose as a data clustering method and transforming it into a tool for systems analysis. Leveraging advanced measurement technologies and sophisticated data collection systems, the K-means++ algorithm unveils hidden relationships among components and identifies critical elements. This study explored the algorithm's potential, facilitating the identification of critical components to enhance system operation, control, optimization, and decision-making and examining the practicality and resiliency of the method in real-world application with noisy and limited data. A case study conducted on power systems (IEEE 39-bus and IEEE 300-bus systems) exemplifies K-means++'s capacity to accurately identify critical components and approximate system dynamics, supported by performance metrics affirming its effectiveness and robustness in system analysis through measurements of bus similarity within clusters based on standard deviation and comparison of net tie-line flows in equivalent networks with the original network across scenarios. Performance metrics, including the Silhouette Score, Davies-Bouldin Index, and Variation of Information (VI) score, further validated K-means++'s performance, yielding reliable and consistent results.

Coenzyme Q (CoQ) is a lipidic compound widely distributed in nature with crucial functions in metabolism, protection against oxidative damage and ferroptosis, and other processes. CoQ biosynthesis is a conserved and complex pathway involving several proteins. COQ2 is a member of the UbiA family of transmembrane prenyltransferases that catalyzes the condensation of the head and tail precursors of CoQ, a key step in the process because its product is the first intermediate that will be modified in the head by the next component of the synthesis process. Mutations in this protein have been linked to primary CoQ deficiency in humans, a rare disease predominantly affecting organs with a high energy demand. The reaction catalyzed by COQ2 and its mechanism are still unknown. Here we aimed at clarifying COQ2 reaction by exploring possible substrate binding sites using a strategy based on homology, comprising the identification of ligand-bound homologs with solved structures available in the Protein Data Bank (PDB) and their subsequent structural superposition to the AlphaFold predicted model for COQ2. The results highlight some residues located on the central cavity or the matrix loops that may be involved in substrate interaction, some of them mutated in primary CoQ deficiency patients. Furthermore, we analyze the structural modifications introduced by the pathogenic mutations found in humans. These findings shed new light on the understanding of COQ2 function and, thus, CoQ biosynthesis and pathogenicity of primary CoQ deficiency.

With the deterioration of the bridge performance and ever-increasing amount of traffic, the bridge safety is becoming a concern for engineering community. A method that can assess the bridge's condition in real-time is urgently needed. The main factors that hinder the bridge condition assessment are the uncertain operational environments. A new moving principal component analysis (MPCA) based method is developed for structural damage detection of bridges in operational environments in this paper. Two main operational environmental factors: the environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed method. The numerical and experimental results show that the proposed method is effective and accurate to assess the bridge condition in operational environments.

The main advantage of using the ferroelectric material as a component of complex heterostructure is the ability to tune various properties of the whole system by means of external electric field. In particular, the electric field may change the polarization direction within the ferroelectric material and consequently affect the structural properties, which in turn affects the electronic and magnetic properties of the neighboring material. Besides, the ferroelectrics proceed the electrostriction phenomenon, which is promising to be used to affect the magnetic states of interface state in the heterostructure with a magnetic component. The interfacial phenomena are of a great interest since they provide an extended functionality useful for electronic devices of a new generation. Following an idea of utilizing a ferroelectric in heterostructures component in the present work we consider 2DEG, Rashba effect, the effect of magnetoelectric coupling and magnetostriction in order to emphasize the advantages of such heterostructures as components of devices. For this purpose model systems of LaMnO3/BaTiO3, La2CuO4/BaTiO3, Bi/BaTiO3 and Bi/PbTiO3, Fe/BaTiO3 heterostructures are investigated by density functional theory calculations.

Rapeseed meal (RM) is an important agroindustrial by-product produced in large quantities by oil extraction from seeds. However, the efficient utilization of RM as animal feed is limited by its low metabolizable energy, poor palatability, and high levels of fiber and anti-nutritional components. Here, we investigate the potential of enriching RM with single-cell protein by fermentation with conventional and unconventional yeasts, to make a nutritionally improved feed component. The process of simultaneous saccharification and fermentation improved the parameters of the waste biomass, especially the protein content, the amount of crude fiber, and the degree of biotransformation of isoflavone compounds present in the waste material. Fermentation yielded the highest protein gain for the Saccharomyces cerevisiae Ethanol Red strain (ΔN=2.38%) at a biomass load of 12.5 g and for Scheffersomyces stipitis (ΔN=2.34%) at an enzyme dose of 0.125ml/10g DM. Crude fiber content (CF) was reduced by 2.55–7.18%. The SSF process resulted in the conversion of isoflavones to forms with fewer adverse effects and lower estrogenic activity.

Molecular iodine (I2) induces apoptotic, antiangiogenic, and antiproliferative effects in breast cancer cells. Little is known about its effects on the tumor immune microenvironment. We studied the effect of oral (5 mg/day) I2 supplementation alone (I2) or together with conventional chemotherapy (Cht+I2) on the im-mune component of breast cancer tumors from a previously published pilot study conducted in Mexico. RNA-seq, I2 and Cht+I2 samples showed significant increases in expression of Th1 and Th17 pathways. Tumor immune composition determined by deconvolution analysis revealed significant increases in M0 macrophages and B lymphocytes in both I2 groups. Real-time RT-PCR showed that I2 tumors overexpress T-BET (p = 0.019) and interferon-gamma (IFNγ; p = 0.020) and silence tumor growth factor-beta (TGFβ; p = 0.049); whereas in Cht+I2 tumors, GATA3 is silenced (p = 0.014). Preliminary methylation analysis shows that I2 activates IFNγ gene promoter (by increasing its unmethylated form) and silences TGFβ in Cht+I2. In conclusion, our data showed that I2 supplements induce the activation of the immune response and that when combined with Cht, the Th1 pathways are stimulated. The molecular mechanisms involved in these responses are being analyzed, but preliminary data suggest that methylation/demethylation mechanisms could also participate.

Objective: The aim of the study was to evaluate the influence of a suburethral sling implantation on the urge symptoms in patients suffering mixed urinary incontinence (MUI) with predominant stress component in case of. Material and methods: The study group was 220 woman with stress urinary incontinence (SUI), among them 35 women with stress-predominant MUI, treated primary with suburethral sling implantation. In 85.7% (N=30) TOT and in 14.3% (N=5) TVT was performed. The clinical symptoms and QOL were assesed before and after treatment using bladder diary and QOL questionnaire. Other additional treatment was also evaluated.Results: Subjective improvement of urge symptoms was observed in 97.1% of woman in the study group. ‘Wet OAB’ symptoms were reduced from 68.6% to 28.6% after sling procedure. Nocturia and pollakiuria were reduced from 45.7% to 11.4% and 8.6% respectively. Nocturia and pollakiuria de novo were observed in 2 (5.4%) and 1 (2.7%) patients respectively. After the sling procedure in 28.6 % (N=10) pharmacotherapy with solifenacin was administered for 2-4 months, in 8.6% (N=3) intravesical injection of botulinum toxin was performed due to persisting OAB symptoms.Conclusion: suburethral sling implantation in woman with stress- predominant MUI, although dedicated to treat SUI symptoms, seems to improve also the urge component of MUI.

This research seeks to interpret the component analysis of an innovative bio-asphalt binder using guayule resin in addition to crumb rubber modifier (CRM) at high concentrations. Such asphalt modification aims to minimize the dependency on virgin asphalt binder and provide new solutions concerning sustainable, flexible pavement industry. Guayule resin is a promising bioresource for asphalt binder replacement. By now, it could be considered a no value byproduct extracted during the guayule natural rubber production. CRM is a recycled material derived from scrap tires. The provided interpretation could help in understanding the asphalt-rubber-guayule interaction mechanism. Fourier transform infrared spectroscopy (FTIR), supported by thermo-gravimetric analysis (TGA), was used to investigate the component analyses of guayule resin composition, asphalt guayule interaction, and asphalt rubber guayule interaction, compared to corresponding asphalt rubber interaction. Additionally, the rheological properties at elevated temperatures were provided to link the microscale properties with the final product performance. The study clarified the distinct carbon and hydrogen compositional elements of guayule resin. Asphalt and guayule resin have similarities in chemical composition and rheological behavior with temperature susceptibility. The asphalt guayule binder had physical interaction. However, when both interacted with rubber, a chemical interaction was attributed, with no difference in rubber dissolution tendency, in asphalt rubber guayule, compared to asphalt rubber. A bio-binder composed of 62.5% asphalt, 25% guayule and 12.5% CRM had the potential to provide rheological properties better than base asphalt. Such behavior was interpreted by a high release of rubber components.

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection and the modification of risk factors, such as diet, can reduce its incidence. Among food components the polyamines are important for maintaining gastrointestinal health and are metabolites of gut microbiota. Their disruption is linked to CRC, making polyamines a potential marker of the disease. This study analyzed the relationship between dietary components, including polyamines, and the presence of polyamines in feces to determine whether their presence could contribute to predicting the occurrence of colorectal lesions in patients. Fifty-nine participants of both sexes (aged 50 to 70 years) who had undergone colonoscopy screening for CRC (18 without and 41 with colorectal lesions) participate in the study. A nutritional survey and determination of fecal polyamine content were performed. Specific dietary components and putrescine levels were higher in patients with colorectal lesions. The diet ratio of putrescine/spermidine and the fecal content of N-acetyl putrescine and cadaverine were elevated in patients with precancerous lesions and adenocarcinomas, showing a potential predictive value for the presence of colorectal lesions. These findings suggest that N-acetyl putrescine and cadaverine could be complementary markers for the diagnosis of suspected colorectal lesions.

This article presents, for the first time, the kinetics and the general conversion features of free radical polymerization (FRP) in a 3-component system (A/B/N), with [A] being the initiator, and [B] and [N] are additives, based on the proposed mechanism of Rahal et al. Higher FRP can be achieved by additives [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals (R) via the radicals (S' and S) produced by N.The initiator (coumarin) shows a dual photo-oxidation and photo-reduction character for high efficacy. The FRP conversion efficacy (CE) depends not only on the property of the initiator [A], the additives [B] and [N}, but also the types of monomers. For example, when [A]=CoumC, [A]/NPG is more efficient than [A]/Iod, but revserse trend occurs in some monomers. However, 2-component systems (with CE=0% to 80%) are always less efficient than that of 3-component systems (with CE=70% to 86%, in TMPTA). Specific systems with [A]=coumarins, [B]=Iodonium salt, and N=NPG are analyzed. Analytical formulas for the role of each component concentration, light intensity and coupling rates on the conversion efficacy are derived.

The formation and localization of sporadic E(Es) layers predicted by the ions vertical drift velocity and its vertical change in the lower thermosphere during nighttime are shown analytically and by numerical simulations. The consideration of existence of a minimum negative value of the vertical change of the ions vertical drift velocity as a necessary condition of formation of Es layer and determining ions convergence rate into this layer, is extended in case of the presence of vertical wind. Upward vertical wind can shift the convergence regions upward, while downward vertical wind shift them downward, unlike the cases of presence of only meridional and zonal winds. It also changes the ion convergence rate compared to the one with just a horizontal wind. It is shown for the first time that the upward constant wind also causes the convergence of ions with maximum rate in the region where the ion-neutral collision frequency is equal to their cyclotron frequency. While demonstrating the presented theory by numerical simulations, HWM14 data is used for the meridional and zonal wind velocity profiles and the presence of its vertical component is assumed. In this case, in addition to the estimated ion drift velocity and its vertical changes, their initial distribution and ambipolar diffusion also determine the development of ion convergence/divergence processes. For small magnitude of vertical wind velocity, its significant influence on the ions/electrons behavior is demonstrated, which shows the importance of both tidal wind and wind changes caused by the propagation of atmospheric gravity waves on the formation of the Es layer. In this theoretical research it is shown that the realistic profile of the wind velocity, which takes into account the vertical component along with its zonal and meridional ones, is important for prediction of the Es layers formation, as well as regions of ion depletion.

Strain L. fermentum U-21 secretes chaperones into the medium and it is considered as the candidate for the development of drugs, so-called disaggregases, for Parkinson’s disease therapy. This study is devoted to characterization of secreted protein encoded by C0965_000195 locus. Analysis of sequence and predicted structure of the protein encoded by C0965_000195 allows us to attribute it to the ClpL, homologs of which are known to be chaperones. The chaperone activity of ClpL L. fermentum U-21 was evaluated in vivo by refolding of differing in thermostability luciferases from Aliivibrio fischeri and Photorhabdus luminescens in Escherichia coli cells. It was observed that clpL from L. fermentum U-21 can compensate for the deficiency in the clpB gene and enhance the ability to refold thermodenatured proteins in clpB- cells. In vitro experiments have demonstrated the ability of a spent culture medium containing proteins secreted by L. fermentum U-21 cells, including ClpL, to prevent thermodenaturation of luciferases partially.We suggest that the ClpL protein from L. fermentum U-21 strain, which exhibits disaggregase properties against aggregating proteins, may be one of the clue components that play a role in the pharmabiotic properties of this strain.

The splitting method developed in a previous study for linear, multi – component, convection-diffusion mass transfer equations is extended to non-linear, multi-component, convection-diffusion mass transfer equations. The diffusion term is non-linear (the diffusion coefficients depend on chemical species concentrations). Theoretical results about the splitting error are presented, as well as numerical simulations for mixtures with n ≤ 5. The numerical experiments show second-order accuracy and stability for the present splitting algorithm.

Juvenile idiopathic arthritis (JIA) is a disease with unknown causes within all forms of arthritis in children under 16 years of age. The diagnosis is made when another joint pathology is excluded. Difficulties in early and differential diagnosis lead to the rapid disability of patients and an unfavourable life prognosis. Therefore, timely diagnosis is necessary to prevent irreversible damage to the joints and preserve their function. Due to the widespread use of new technologies, modern multimodal imaging has gained recognition, which includes X-ray, ultrasound, and MRI. The combination of methods plays a key role in confirming the diagnosis, monitoring disease activity, prognosis during the course, and outcome in children with JIA. Each method has its own advantages and disadvantages. The introduction of the method of passive microwave radiometry (MWR), in combination with other imaging methods, makes it possible to expand the possibilities of screening the disease in the preclinical and early clinical phases.

This article presents the development of the theoretical background and the design of an electronic device for monitoring the condition of a gapless Metal Oxide Surge Arrester (MOSA). The device is intended to be used online. Due to the inaccessibility and possible remote location of most surge arresters, it is equipped with a communication system, allowing the device to convey the measurement of the surge arrester characteristics under any conditions. By gathering measurements of the surge arrester’s resistive component of leakage current, it is possible to determine the condition of the MOSA. After interpreting the results, these can be sent via a data transfer unit to a server, which, in turn, sends it onward to the authorised personnel through the surge arrester control centre.

Nine components (C1-C9) were isolated from chloroform fraction of fractionated methanol extracts of Vernonia amygdalina leaves (FMEVA) by column chromatography. All the components C1 to C9 were purified and screened for hypoglycaemic activities in type-2 diabetic rats. The most potent hypoglycaemic component was elucidated on the basis of extensive spectroscopic (1D-, 2D-NMR, GC-MS, FTIR) data analysis. The Component C5 was found to be the most potent hypoglycaemic in reducing blood glucose by 12.55 ± 3.55% at 4 h post-oral administration, when compared to the positive (18.07 ± 1.20%) and negative (-1.99 ± 0.43%) controls. The spectroscopic data analysis reveals that the isolated compound has a structure consistent with 11β,13-dihydrovernolide. The isolated compound is part of the hypoglycaemic components present in V. amygdalina leaves that is responsible for the anti-diabetic activities. Further research is needed in the development of this compound or its derivatives for pharmaceutical use.

In recent times, the increasing concern for climate control has led to the widespread application of grid-connected inverter (GIC) based renewable energy systems. In addition, the increased usage of non-linear loads and electrification of the transport sector cause ineffective grid-frequency management and the introduction of harmonics. These grid conditions affect power quality and result in uncertainty and inaccuracy in monitoring and measurement. Incorrect measurement leads to overbilling/underbilling, ineffective demand and supply forecasts for the power system, and inefficient performance analysis. To address the outlined problem, a novel three-phase frequency component extraction and power measurement method based on Digital Lock-in Amplifier (DLIA) and Digital Lock-in Amplifier Frequency-Locked Loop (DLIA-FLL) is proposed to provide accurate measurement under the conditions of harmonics and frequency offset. A combined filter with a lowpass filter and notch filter for DLIA is employed to improve computation speed. A comparative study is performed to validate the performance of the proposed power measurement method, by comparing the proposed method to the windowed interpolated fast Fourier transform (WIFFT). The ZERA COM 3003 (a commercial high-accuracy power measurement instrument) is used as the reference instrument in the experiment