Josephson junctions (JJs) in the presence of a magnetic field exhibit qualitatively different interference patterns depending on the spatial distribution of the supercurrent through the junction. In JJs based on two-dimensional topological insulators (2DTIs), the electrons/holes forming a Cooper pair (CP) can either propagate along the same edge or be split into the two edges. The former leads to a SQUID-like interference pattern, with the superconducting flux quantum $\phi_0$ (where $\phi_0=h/2e$) as a fundamental period. If CPs’ splitting is additionally included, the resultant periodicity doubles. Since the edge states are typically considered as being strongly localized, the critical current does not decay as a function of the magnetic field. Here we go beyond this approach and inspect a topological JJ in the tunneling regime featuring extended edge states. We consider the possibility that the two electrons of a CP propagate and explore the junction independently over length scales comparable with the superconducting coherence length. As a consequence of the spatial extension, we obtain a decaying pattern with different possible periods. In particular, we show that, if crossed Andreev reflections (CARs) are dominant and the edge states overlap, the resulting interference pattern features oscillations whose periodicity approaches $2\phi_0$.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

Background: RSV, or respiratory syncytial virus, is a deadly condition that is present all over the world today. The infection is initially contained in the lower respiratory tract without systemic transmission. The objective of the study: Bioinformatics was used in Egypt to create an mRNA vaccine against the Respiratory syncytial virus (RSV). Methodology: In the present screening experimental study, a lipid nanoparticles vaccine of mRNA of the surface fusion protein of Respiratory syncytial virus was manufactured. The present vaccine delivery system was lipid nanoparticles with a particle size of approximately 90 nanometres, manufactured by the hot micro-emulsion method. In stages 1 and 2 of clinical trials, the immunogenicity of the current mRNA RSV vaccine was evaluated. Results: The current vaccine demonstrated 81% immunogenicity in animal testing, but only 69% in stages 1 and 2 of clinical trials. Its side effects were manageable. The results persisted for a while. In the current trial, the vaccination proved effective as a preventative measure against RSV infection. The current vaccination lacked antibody-dependent enhancement, which causes non-protective antibodies to develop. These non-neutralizing antibodies exacerbate infection by activating cytokines and complement cascade through the formation of immune complexes or enhancement of the virus entry and replication in the host cells. On the other hand, the current RSV mRNA vaccine of the surface fusion protein consequent on the production of powerful neutralizing antibodies with prolonged immunity especially to infants and elderly candidates who received the optimal dosage regimen.

Arboviruses are infections caused by arboviruses that may be either symptomatic or asymptomatic, according to individuals' resistance and immune response, which dietary patterns can influence. Thus, this study aimed to investigate the possible association between the occurrence of clinical manifestations of arboviruses and the dietary pattern of the population studied. The study was conducted in a rural population in the metropolitan area of Belém, Pará State, Brazil. The sampling consisted of 95 individuals during a febrile outbreak. Two investigations were conducted: clinical-epidemiological-dietary and laboratory investigation based on blood samples taken for arbovirus analysis. Out of the 95 individuals studied, more than half (57.89%) showed clinical manifestations. Following the laboratory serology (HI and IgM ELISA) analyses, viral isolation in C6/36 cells, and viral genome detection (RT-qPCR), the final diagnosis of the cases was 47.37% Oropouche Fever, 2.11% Oropouche Fever and Chikungunya Fever, and 1.05% Mayaro Fever. Regarding dietary pattern, as for the comparison analyses, statistical significance was observed between dietary pattern and classification regarding the presence of symptoms (p<0.05); after the correspondence analysis, symptomatic cases were more associated with a bad dietary pattern, while asymptomatic cases were more associated with a good dietary pattern.

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) dD, CO2 and CH4 records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve the understanding regarding the features of intensity, amplitude, and asymmetry of 73 marine isotope stages (MIS) and seven terminations. The Antarctic stack record can be described by a variance-weighted interference model of ten thermal waves of different origins (mid-term oscillation, orbitals and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, intensity, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low interference regions where dominant destructive patterns minimise the thermal envelope. The positive skewness of the EPICA stack resulted from the constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect resulted in the saw-tooth shape of glacial cycles which is heavily induced by interference and related to the intermediate feedback mechanisms controlled by short eccentricity.

1. Heterospecific pollen interference has recently been proposed as a mechanism contributing to the success of alien invaders, as heterospecific pollen of alien plants interferes with the reproduction of natives by reducing fruit and seed set. However, no study has looked at the opposite interaction. Moreover, few studies have considered the roles of phylogenetic and trait distances between pollen donors and recipients. 2. We did a large multi-species experiment in which we used alien and native species both as pollen recipients and as pollen donors, and included phylogenetic as well as trait distance as explanatory variables. 3. We found that both alien and native recipients suffered from heterospecific pollen from donors of the opposite status in terms of seed and fruit set. Phylogenetic distance and trait distance both affected heterospecific pollen interference, but the effect depended on recipient and donor statuses. 4. We conclude that heterospecific pollen interference affects both native and alien recipients, thus indirectly altering community composition and increasing biotic resistance against invaders.

Three-dimensional transfer functions (3D TFs) are generally assumed to fully describe the transfer behavior of optical topography measuring instruments such as coherence scanning interferometers in the spatial frequency domain. Therefore, 3D TFs are supposed to be independent of the surface under investigation resulting in a clear separation of surface properties and transfer characteristics. In this paper we show that the 3D TF of an interference microscope differs depending on whether the object is specularly reflecting or consists of point scatterers. In addition to the 3D TF of a point scatterer, we will derive an analytical expression for the 3D TF corresponding to specular surfaces and demonstrate this as being most relevant in practical applications of coherence scanning interferometry (CSI). We additionally study the effects of temporal coherence and disclose, that in conventional CSI temporal coherence effects dominate. However, narrowband light sources are advantageous if high spatial frequency components of weak phase objects are to be resolved, whereas for low-frequency phase objects of higher amplitude the temporal coherence is less affecting. Finally, we present an approach that explains the different transfer characteristics of coherence peak and phase detection in CSI signal analysis.

This article proposes an interferometer which should in principle split further an initially split beam to yield new sets of beams, effectively multiplying the number of beams that can be subjected to detectable interference. It can be considered a modification to the Michelson interferometer that introduces additional arrays of beam splitters, mirrors and detectors. It is expected of the interferometer to provide us with a set or sets of data holding details of phase changes in multiple interference patterns detectable by multiple detectors, enabling comparative analysis of data for multiple interference patterns recorded from a single measurement or activity. The number of multiplied beams possible is not limited, as it only depends on the specific amount of beam splitters required for certain experiments and practicals. The interference of multiple beams may improve sensitivity and detection for instrumentation purposes. The use of multiplied beam interferometry may also extend to quantum computation, particularly in linear optical quantum computation scheme as it enable production of multiple coherent beams which may exhibit properties of entanglement, making it suitable for developing optical multi-qubit systems.

We present an analysis of recent experiments in femtoscopy by the STAR collaboration in terms of the protocol of entanglement witnessing involving purity measurements. The entanglement is between the charge and momentum degrees of freedom of pions and the state purity measurements ultimately rely on the bosonic nature of the detected pions. The pion experiment is intended to measure the size of nuclei and the distance between the nuclei involved, however it indirectly confirms that the states of dfferently charged pions are entangled through an entanglement witness based on the purity of various pionic states. The entangled state of pions can be modelled straightforwardly dynamically using a simple Hamiltonian. Quantum indistinguishability plays a key role in this analysis and we make comparison with the equivalent photonic experiments.

The presence of the quantum Rayleigh scattering, or spontaneous emission, inside a dielectric medium such as a beam splitter or an interferometric filter, prevents a single-photon from propagating in a straight-line. Modelling a beam splitter by means of a unitary transformation is physically meaningless because of the loss of photons. Additional missing elements from the conventional theory are: 1) the quantum Rayleigh stimulated emission which can form groups of photons of the same frequencies, and 2) the unavoidable parametric amplification of single-photons in the original parametric crystal. An interference filter disturbs, through multiple internal reflections, the original stream of single-photons, thereby confirming the existence of groups of photons being spread out to lengthen the coherence time. The approach of modelling individual, single measurements with statistical ensemble probability amplitudes leads to the counterintuitive explanations of the experimental outcomes and should be replaced with pure states describing instantaneous measurements which are afterwards averaged.

The role of innate immunity in neutralization of viral infections (including COVID-19) and forming long-lasting and specific immune memory is considered. It is assumed that antiviral protection is generated by the mechanism of RNA interference (RNAi) and is based on the presence of specific viral patterns in the DNA library of the host cells.

Satellite communication (Satcom) is an artificial geostationary satellite that facilitates a wide range of telecommunications. Considering its quality of service (QoS) and security is crucial in government/military applications. The most challenging situation for efficient Satcom is radio frequency interference (RFI) environment. Thus, it is necessary to ensure that transmissions are incorruptible or at least sense the quality of its spectrum. This paper presents a new method to recognize received signal characteristics using a hierarchical classification in a multi-layer perceptron neural network. We consider signal modulation and the type of RFI as the characteristics of a real-time video stream transmitted in the direct broadcast satellite. Four different modulation types are investigated in this study. Moreover, the combination of the communication signal with various kinds of interference and their effects on the classification method widely have been analyzed. Besides, two robust feature selection techniques have been developed to reduce the data-set dimensional, which leads to optimizing the classification process. The results show that the Genetic Algorithm (GA) slightly outperforms Principal Component Analysis (PCA) for feature selection. Furthermore, the robustness of the proposed techniques is assessed to detect unknown signals at different signal to noise ratios.

The digital representation of various signals allows, at the subsequent stages of their transmission, to apply correction codes that provide protection against possible errors arising from the action of interference in the communication channel. At the same time, it is important that, with the required correcting ability, these codes have the maximum possible speed. The article presents the results of calculations for linear codes, showing their really achievable limiting capabilities.

Dietary patterns were recently applied to examine the relationship between eating habits and prostate cancer (PC) risk. While the associations between PC risk with glycemic index and Mediterranean score have been reviewed, no meta-analysis is currently available on dietary patterns defined by “a posteriori” methods. Search was carried out (PubMed, Web of Science) to identify studies reporting the relationship between dietary patterns and PC risk. Relevant dietary patterns were selected and the risk estimated were calculated by a random-effect model. Multivariable-adjusted odds ratios (ORs) for a 1st-percentile increase in dietary pattern score were combined by a dose response meta-analysis. 12 observational studies were included in the meta-analysis which identified “Healthy pattern” and “Western pattern”. The Healthy pattern was not related to PC risk (OR=0.96; 95% CI: 0.88-1.04) while the Western pattern significantly increased it (OR=1.34; 95% CI: 1.08-1.65). In addition, a “Carbohydrate pattern”, identified in four articles, was positively associated with a higher PC risk (OR=1.64; 95% CI: 1.35-2.00). A significant linear trend between the Western (p=0.011) and the Carbohydrate (p=0.005) pattern and the increment of PC risk was observed. The small numbers of studies included suggest that further investigations are necessary to support these findings.

EMG analysis is becoming increasingly important in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, electromyographic signals can be contaminated by various types of noise, interference and artifacts, which can lead to misinterpretation of the data acquired using this method. Even assuming best practices, the collected signal may still be altered by such contaminants. The aim of this paper is to review methods employed to reduce contamination of single channel EMG signals. This review is limited to methods performed directly on the measured EMG signal and those that allow total reconstruction of the EMG signal. Subtraction methods used in the time domain, denoising methods performed after signal decomposition and hybrid methods are assessed. It is defended that individual methods may be more or less suitable for a particular application depending on contaminant(s) present in the signal and on the specific requirements of the application.

A well known result for the interference of two single-mode fields is that the degree of coherence and the degree of indistinguishablity are same when we consider the detection of a single photon. In this article we present the relation between degree of coherence, path indistinguishability and the fringe visibility considering interference of multiple number of single-mode fields while being interested in the detection of a single photon only . We will also mention how Born’s rule of interference for multiple sources is reflected in these results.

The influence of the film thickness and the substrate’s refractive index on the surface mode at the superstrate is an important study step that may help clearing some of the misunderstandings surrounding their propagation mechanism. A single sub-wavelength slit perforating a thin metallic film is among the simplest nanostructure capable of launching Surface Plasmon Polaritons on its surrounding surface when excited by an incident field. Here, the impact of the substrate and the film thickness on surface waves is investigated. When the thickness of the film is comparable to its skin depth, SPP waves from the substrate penetrate the film and emerge from the superstrate, creating a superposition of two SPP waves, that leads to a beat interference envelope with well-defined loci which are the function of both the drive frequency and the dielectric constant of the substrate/superstrate. As the film thickness is reduced to the SPP’s penetration depth, surface waves from optically denser dielectric/metal interface would dominate, leading to volume plasmons that propagate inside the film at optical frequencies. Interference of periodic volume charge density with the incident field over the film creates charge bundles that are periodic in space and time.

This paper presents the design and measurement of an IEEE 802.11ad standard compatible RF transceiver for 60GHz wireless communication system. In addition to the traditional half-duplex (HD) mode, this work supports full-duplex (FD) operation to deliver better channel utilization and faster response time for the system. The isolation between the transmitter and receiver from the architecture design to system integration for FD operation has been fully considered. A digital self-interference cancellation (DSIC) is implemented in MATLAB to verify the FD performance. The super-heterodyne architecture with an intermediate frequency (IF) of 12GHz is designed to suppress the image frequencies without using extra filters. A flexible phase-locked loop (PLL) synthesizer provides a local oscillator (LO) frequency with a 2kHz resolution. Other than the time division duplex (TDD) mode used in the conventional 60GHz system, a wide bandwidth baseband digital variable gain amplifier (DVGA) with a 3dB bandwidth of more than 4GHz also supports frequency division duplex (FDD) operation. The transceiver chip is fabricated in Tower Jazz 0.18µm SiGe BiCMOS process. With on-board antenna, the transceiver covers all four channels in 802.11ad standard with MCS-12 (7.04Gbps under 1.76GSym/s and 16-QAM) under 1.5m. In the proposed system design, the RF frontend based self-interference (SI) suppression from the local transmitter to receiver LNA is around 54dB. To achieve a practical FD application, the SI is further suppressed with the help of digital SI compensation. The measured power consumption for transmitter and receiver configuration is 194mW and 231mW, respectively, in HD mode and 398mW for FDD or FD operation mode.

The phenomenon of interference is a characteristic of all waves. This paper reviews the interference of classical waves and of matter waves in quantum mechanics. In quantum mechanics, there are two interference mechanisms between identical particles. One is that the de Broglie wavelengths of two interference waves are the same, which is called the equal wavelength interference mechanism. The other is that the wavelengths of interference waves can also be different, in which case there should be an exchange term in additional to the direction term in the wave function. There is a fixed phase difference between the two terms, which causes interference. This is called exchange effect interference mechanism. We propose an experiment, which is simpler to what has been done, to show the exchange effect interference. There is a special case where two interference waves can satisfy both the two mechanisms. We propose an experiment to discriminate that in this case which mechanism plays a role on earth.

This study investigates the applications of reconfigurable intelligent surfaces (RIS) in heterogeneous downlink networks (HetNet). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUE). In this paper, we utilize RIS to mitigate cross-tier interference in an HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider an RIS-assisted HetNet consisting of multiple SBS nodes and MUEs that utilize both direct paths and reflected paths. Therefore, the aim of this study is to maximize the sum rate of all MUEs by jointly optimizing the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficients-based optimization (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts.

RNA interference (RNAi) using small interfering RNAs (siRNAs) is a powerful tool to target any protein of interest and is becoming more implementable for in vivo applications due to recent developments in RNA delivery systems. To exploit RNAi for cancer treatment, it is expedient to increase its selectivity by e.g. a prodrug approach to activate the siRNAs upon external triggering, e.g. by using light. Red light is especially well suitable for in vivo applications due to its low toxicity and higher tissue penetration. Known molecular (not nanoparticle based) red light activatable siRNA prodrugs rely on singlet oxygen (1O2) mediated chemistry. 1O2 is highly cytotoxic. Additionally one of the side products in the activation of the known siRNA prodrugs is anthraquinone, which is also toxic. We here report on an improved red light activatable siRNA prodrug, which do not require 1O2 for their activation. The 5’ terminus of its antisense strand is protected with an electron-rich azobenzene promoiety. It gets reduced and cleaved upon red light exposure in the presence of Sn(IV)(pyropheophorbide a)dichloride acting as a catalyst and ascorbate required as a bulk reducing agent producing active siRNAs.

During the launch and return of a spacecraft, the intense combustion of propellants generates strong electromagnetic radiation, which interferes with the operation of electronic equipment in the spacecraft. To improve the electromagnetic compatibility of electronic equipment in spacecraft, it is necessary to study the electromagnetic radiation characteristics of rocket fuel. An electromagnetic radiation measurement system based on antennas is designed to measure the electromagnetic radiation generated by rocket fuel, and the electromagnetic radiation characteristics are obtained through data analysis. The mechanism of the electromagnetic radiation generated by rocket fuel is comprehensively analysed through the spatial, time-domain, frequency-domain, and energy-domain characteristics. A characterization model is established to provide a reliable scheme for evaluating the influence of rocket fuel electromagnetic radiation on electronic equipment in spacecraft.

In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.

RNA interference (RNAi) is one of the main mechanisms for disease resistance and small RNA production in plants. The main proteins involved in RNAi include Dicer-like (DCL), RNA-dependent RNA polymerase (RDR), double-stranded RNA-binding (DRB), and Argonaute (AGO). Juglandaceae contains a variety of important woody plants, and walnuts are one of the four major woody plant groups and one of the four major dried fruits in the world. To clarify the evolution and functional differentiation of RNAi-related proteins in the walnut (Juglans regia) genome, this study integrated various web resources from gene family acquisition to structural analysis and transcriptome data to correlate walnuts and their congeners. The walnut genome has 5 DCL, 13 RDR, 15 DRB and 15 AGO genes, similar genes encoding conserved protein structural domains and conserved motifs with similar subcellular localization. Walnut AGO proteins are classified into three classes and seven subclasses. The DCL is divided into four categories, while RDR is mainly divided into four categories, and DRB can be divided into six categories. The exception is that the copy number of walnut RDR1 is 9, in which seven RDR1 are distributed in clusters on chromosome 16. Purifying selection drove the formation of walnut genes, but protein classes were subjected to varying degrees of purifying selection. Additionally, these results showed some similarity in other plants of the walnut family. Moreover, different RNAi-related genes of walnut produced abundant selective expression in response to different tissues and stresses. In this study, DCL, RDR, DRB and AGO gene families were identified and analysed in the genome of the walnut family for the first time and preliminarily examined the evolution, structure and expression characteristics of these families to provide a preliminary basis for the evolution of the walnut RNAi pathway and breeding research.

This article is a big picture of how electrical noise or conducted Electromagnetic Interference (EMI) is generated and mitigated in power converters. It gives an overview of what EMI in power converters is – from generation through to conduction and mitigation. It is meant to cover the complete subject as a summary so that the reader will have an outline of how to control conducted EMI by design (where possible) and how to mitigate by filtering. A clear distinction is made between Differential Mode (DM) and Common Mode (CM) EMI generation and mitigation. By using a boost converter as an example the trade-offs for DM noise control are discussed. It is shown how CM EMI is generated in a boost converter using the concept of the “Imbalance Difference Model” (IDM). Practical measurements for an in-line power filter is given showing the effect of the filter on the total EMI of a boost converter. Measurements for the CM current produced due to the imbalance difference for different values of the boost conductor are also shown. The main contribution of this study is linking CM noise generation to DM EMI. It is shown that CM noise is a direct consequence of DM noise (although circuit imbalance and coupling to a common ground also play a role). This paper will be useful to designers seeking the “bigger picture” of how EMI is generated in power converters and what can be done to mitigate the noise.

Plant pathogenic fungi are the largest group of disease-causing agents on crop plants and represent a persistent and significant threat to agriculture worldwide. Conventional approaches based on the use of pesticides raise social concern for the impact on the environment and human health and alternative control methods are urgently needed. The rapid improvement and extensive implementation of RNAi technology for various model and non-model organisms has provided the initial framework to adapt this post-transcriptional gene silencing technology for the management of fungal pathogens. In this review, we describe exogenous RNAi involved in plant pathogenic fungi and discuss small RNA production, formulation, and RNAi delivery methods. We explore some challenges with possible solutions. Furthermore, exogenous RNAi holds great potential for RNAi-mediated plant pathogenic fungal disease control.

The use of antibiotics grown promoter has been banned, due led problems with drug residues in animal products and increased bacterial resistance. For several reasons there is a growing interest in the scientific community in immunoglobulin Y as antibiotic alternative and their oral administration in the polyclonal antibody (pAb) format, to maintain animal health and performance, do not require IgY purification for large-scale production, resulting in protein impurities and high concentration of biotin in the samples. The signal amplification through non-covalent interaction of biotin with streptavidin has been extensionally used by many laboratories for several diagnosis diseases and scientific research in enzyme-linked immunosorbent assay (ELISA). However, the riches sources of biotin as egg yolk, leading to high biotin concentrations in samples, harming the accuracy of diagnostic and proteins concentrations tests. This study aimed to evaluate the biotin influence on measurement of Immunoglobulin Y in egg yolk freeze dried samples from immunized laying hens by immunoassays using biotin-avidin/streptavidin. The IgY concentration changed down in immunoassays using biotin-avidin/streptavidin. The detection of IgY in yolk samples by ELISA using streptavidin–biotin binding as part of the assay methodology requires some technology to neutralize high concentration of biotin on sample or more steps beyond delipidation to isolate the target protein. Otherwise, an ELISA without the use of streptavidin-biotin binding would be more advisable to avoid biotin and targets protein relationship and prevent biotin interference on results.

The bonds of England and the UAE date back to over 220 years ago. This article explores the interference of Arabic prepositions in the English used in the United Arab Emirates (UAE), and their occurrences in light of gender and level of education, two important social variables related to linguistic behavior. To do so, participants will translate 20 sentences in Arabic into English as well as fill in 30 gaps in sentences in English with the missing prepositions. We will also experiment how musical intelligence may improve Emiratis’ performance regarding preposition. A study will be carried out to verify if participants from the experimental group, who will receive training on prepositions through music, obtains better results compared to the control group, who will receive training through a more traditional way (by listening to the instructor and repeating).

The demonstration of compliance of rolling stock against disturbance limits for railway signaling, and in particular track circuits, is subject to a large deal of variability, caused by the diverse values of the electrical parameters of the railway line and resulting transfer functions, as well as operating conditions of rolling stock during tests. Instrumental uncertainty is evaluated with a Type B approach and shown to be much less than the experimental variability. Repeated test runs in acceleration, coasting, cruising, braking conditions are considered, deriving both max-hold (spread) and sample dispersion curves compared to the respective mean values (Type A approach to the evaluation of uncertainty). The major source of variability affecting a significant portion of the spectrum is caused by the superposed oscillations of the onboard LC filter, for which different choices of the transformation window duration are discussed. The test runs and the acquired data covered overall 1 day of tests along about 300 km of the Italian 3 kV DC railway network.

Yaw misalignment can make a wake steer, which is an effective method to increase the power of wind farms, but it also increases the fatigue load of the turbines. In this paper, the method of combining yaw misalignment and pitch control (CYMP) is proposed to investigate the potential to mitigate wake interference, the wind velocity distribution and turbulence distribution in the wake, as well as the power and load changes of the wind turbine are studied, focusing on power in-crement and fatigue damage reduction. Although some studies have found that the method of CYMP are beneficial to increase power generation and reduce fatigue loads, there are no papers that have made a detailed analysis of the effects of wake turbulence, wind speed distribution, power, especially fatigue damage under this control. Simulation tool FAST.Farm is used to model and analyze wind farms, obtain the variation details of wake and provide simulation data for calculating power and fatigue load. The pitch control brings bias to the CYMP optimization results was neglected, the case studies show that the method of CYMP can reduce the fatigue load by 10.29% and increase the total power by 1.7% compared with only wake steering. The Model Predictive Control collaborative method based on CYMP is proposed, which can increase power by more than 2% and reduce thrust by more than 4% under 10m/s turbulent wind.

In modern Commercial Off-The-Shelf (COTS) multicore systems, cores can produce several simultaneous memory requests. The processing of such requests over the memory controller negatively impacts the interference delay triggered by running parallel tasks on the platform. In this paper, we propose a software-based testing approach for analyzing memory interference delay, when cores are exposed to extensive read/write requests that access in parallel their Cache Coherent Interconnect. The hardware targeted in this work is the well-known LayerScape QorIQ LS2085A, which can be approached as a potential successor to the Freescale QorIQ P4080. The test analysis was conducted based on a bare-metal operating system that we developed to guarantee a deterministic execution environment at all time points. Our testing was accomplished using a set of carefully designed synthetic benchmarks as well as TACLeBench benchmarks.

The main objective of this study is to conduct a bibliometric analysis of scholarly publications of Authorship Pattern. The present study covers 1723 research papers published in the area of authorship pattern and indexed in Scopus database from the year 2013 to 2022. These research publications considered for the present study have been analysed based on their year wise growth, pattern of authorship, times citations, type of publication, most productive publication source as well as countries and institutions. The study shows the positive growth of the literatures with collaborative authorship pattern and good citation status. This original research paper will be helpful to the researchers of library and information science, especially who are working in the area of bibliometrics studies.

Camera malfunctions or loss of storage elements in imaging devices may lead to loss of important image information or random impulse noise interference. Low rank is one of the important prior information in image optimization processing. This paper uses different low-rank constraint models of the image matrices to recover the impulse interference satellite images. Firstly, an overview of image inpainting models based on nuclear norm, truncated nuclear norm, weighted nuclear norm, and matrix-factorization-based F-norm is presented, and corresponding optimiza-tion iterative algorithms are provided. Then, we conducted experiments under three types of pulse interference and provided visual and numerical results. Finally, it is concluded that the WSVT_ADMM method based on the weighted nuclear norm can obtain the best image inpainting results; The UV_ADMM method based on F norm of matrix factorization has the least computa-tion time and can be used for large-scale low-rank matrix computation; The WSVT_ADMM method based on weighted nuclear norm and the TSVT_ ADMM method based on truncated nuclear norms can significantly improve the repair effect compared to the nuclear norm-based methods such as SVT, SVP, and n_ADMM.

As a high-frequency carrier, the Terahertz (THz) wave is essential for achieving high-data-rate wireless transmission due to its ultra-wide bandwidth. Phase stabilization becomes crucial to enable phase-shift-based multilevel modulation for high-speed data transmission. We developed a Mach-Zehnder interferometric phase stabilization technique for photomixing, which has proved a promising method for phase-stable continuous THz-wave generation. However, this method faces inefficiencies in generating phase-modulated THz waves due to the impact of the phase modulator on the phase stabilization system. By photomixing, which is one of the promising methods for generating THz waves, the phase of the generated THz waves can be controlled in the optical domain so that the stability of the generated THz wave can be controlled by photonics technologies. Thus, we have devised a new phase stabilization approach using backward-directional lightwave, which is overlapped with the THz wave generation system. This study presents a conceptual and experimental framework for stabilizing the phase differences of optical carrier signals. We compare the optical domain and transmission performances between forward-directional and backward-directional phase stabilization methods. Remarkably, our results demonstrate error-free transmission at a modulation frequency of 3 Gbit/s and higher.

Pump Sizing is the process of dimensional matching an impeller and stator to provide a satisfactory performance test result and good service life during the operation of progressive cavity pumps. In this process, historical data analysis and dimensional monitoring are done manually, consuming a large amount of man-hours and requiring a deep knowledge of progressive cavity pump behavior. This work presents the use of complex networks in the construction of a prototype to recommend interference during the Pump Sizing process in a Progressive Cavity Pump. For this, data from different expert applications were used in addition to individual control Excel spreadsheets to build the database used in the prototype. From the pre-processed data, complex network techniques and the Betweenness Centrality metric were used to calculate the degree of importance of each order confirmation, as well as to calculate the dimensionality of the rotors. The model was evaluated using the mean squared error (MSE), obtaining a MSE of 0.28 for the cases where there were recommendations for order confirmations. Based on the results obtained, it was realized that there is a similarity with the dimensional defined by design engineers during the Pump Sizing process.

Climate changes caused by anthropogenic actions can directly and indirectly affect living beings, including parasites and their hosts. Changes such as water temperature, pH, distribution of nutrients in the aquatic environment are some examples that can interfere with the fish community, whether in open water or in production systems. In this review, we will show how climate change can affect the adaptation of hosts and parasites in the aquatic environment and how these parasites can be used for environmental monitoring.

Elevation has been a cornerstone of biodiversity research, and changes in the environmental factors behind it influence biodiversity and community patterns. Exploring the potential reasons behind liverwort community patterns has been a matter of multiplied interest for ecologists. In the present study, we assessed the liverwort plants of the Sygera Mountain from 3100 m to 4500 m decaying wood, tree, soil, and rock using complex field surveys in 2017 and 2019, and investigated the effects of altitude and various climatic factors on the diversity and community composition of the Sygera Mountain. Also, we used including ANOVA, mixed effects modeling, NMDS, ANOSIM, and CCA, which helped to critically assess the liverwort diversity with respect to environmental variables. The results of the study showed a bimodal variation in the richness of liverwort communities with altitude, with peaks occurring at 3500 m and 4100 m. The variation with altitude was significant, with communities at 4100 m and 4300 m being associated with arid environments, and those at 3100 m and 3300 m favoring areas of higher mean annual temperatures and precipitation. Among the climatic factors, the variation in mean diurnal rang, precipitation, and annual temperature was found to be the determinant of liverwort communities. The results suggest that elevation and daily temperature fluctuations play a crucial role in the distribution and community structure formation of mountain liverwort plants. This study deepens our understanding of liverwort ecology and emphasizes the importance of climatic variables in determining plant community composition.

In the investment casting process, the pattern made of wax is obtained in a die for further formation of shell mold. This work investigates commercial pattern waxes fluidity with a newly developed injection fluidity test. A good correlation between wax fluidity and its viscosity is observed, which is different from metallic alloys, where the solidification behavior is more critical. The difference in investigated filled waxes fluidity can be associated with the type and amount of filler.

MRI shows in-vivo the three archetypal patterns of CNS volume loss underlying progressive ataxias, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Freidreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, and repurposing therapies or enlargement of drugs indications in progressive ataxias.

As a fundamental optical approach to interferometry, Sagnac interference has been widely used for reflection manipulation, precision measurements, and spectral engineering in optical systems. Compared to other interferometry configurations, it offers attractive advantages by yielding a reduced system complexity without the need for phase control between different pathways, thus offering a high degree of stability against external disturbance and a low wavelength dependence. The advance of integration fabrication techniques has enabled chip-scale Sagnac interferometers with greatly reduced footprint and improved scalability compared to more conventional approaches implemented by spatial light or optical fiber devices. This facilitates a variety of integrated photonic devices with bidirectional light propagation, showing new features and capabilities compared to unidirectional-light-propagation devices such as Mach-Zehnder interferometers (MZIs) and ring resonators (RRs). Here, we present our latest results for functional integrated photonic devices based on Sagnac interference. We outline the theory of integrated Sagnac interference devices with comparisons to other integrated photonic building blocks such as MZIs, RRs, photonic crystal cavities, and Bragg gratings. We present our latest results for Sagnac interference devices realized in integrated photonic chips, including reflection mirrors, optical gyroscopes, basic filters, wavelength (de)interleavers, and optical analogues of quantum physics.

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

It is claimed that classical mechanics (CM) in terms of its equivalent Koopman-von Neumann formulation (KvN) is indeed a ’real’ quantum theory since the formalism of quantum mechanics (FQM) does not, nor need it, exclude it as a such. This claim is made manifest by suggesting a common structure of which both KvN and ordinary quantum mechanics (OQM) correspond to unitary representations of, although unitarily inequivalent such. It is shown that OQM is obtained by enforcing the extra physical condition of quantized energy levels, which by itself does not constitute the ’quantum mystery’. It is furthermore shown that KvN in a physically realizable sense contain the hallmark quantum behavior of quantum interference. It is hence concluded that both CM and OQM are subjected to the same foundational issues. As the central part of both KvN and OQM is the introduction of probabilities via FQM it is suggested that the foundational issues regarding FQM are less about FQM itself and more about the concept of probability.

A growing number of studies suggest that SARS-CoV-2 could interfere with homeostatic mechanisms in the lung but the implications of this possible interference have not been fully explored in the literature. In this work, we examine the consequences that can be drawn from this hypothesis according to currently available knowledge. We suggest that one such consequence is the potential disruption of normal ventilation and perfusion of lung regions that may be distant from the infection sites. Loss of ventilation might result in local alveolar hypoxia and contribute to hypoxemia, which in turn could trigger homeostatic responses that enhance blood oxygenation by redistributing pulmonary blood circulation. Sudden changes in perfusion might then lead to the development of hydrostatic edema and eventually to vascular remodeling and inflammation. Therefore, the immune response might not be the only source of the substantial inflammation observed in lung tissues of patients with severe COVID-19, as is often assumed in the literature. The balance between the homeostatic and the immune reaction in each patient could account for the observed heterogeneity of the clinical manifestations of COVID-19.

Inflammation is the body’s response to infection, injury, or other stimuli. Acute inflammation is a crucial component of the immune system’s defense, aimed at eliminating infected or damaged cells and halting disease progression. A subtle interaction between pro- and anti-inflammatory processes determines its progression to inflammation resolution or to chronic inflammation. In this study, we propose a generic model of inflammation through a system of reaction-diffusion equations involving various inflammatory and anti-inflammatory cells and cytokines. We investigate the formation of patterns, determined by the emergence of Turing structures, through linear stability analysis and numerical simulations. These theoretical findings are further supported by observations of similar patterns in skin diseases.

This article introduces a novel approach, termed the Asymmetric Probabilistic Tsetlin (APT) Machine, which incorporates the Stochastic Point Location (SPL) algorithm with the Asymmetric Steps technique into the Tsetlin Machine (TM). APT introduces stochasticity into the state transitions of Tsetlin Automata (TA) by leveraging the SPL algorithm, thereby enhancing pattern recognition capabilities. To enhance random search processes, we introduced a decaying normal distribution into the procedure. Meanwhile, the Asymmetric Steps approach biases state transition probabilities towards specific input patterns, further elevating operational efficiency. The efficacy of the proposed approach is assessed across diverse benchmark datasets for classification tasks. The performance of APT is compared with traditional machine learning algorithms and other Tsetlin Machine models, including the Asymmetric Tsetlin (AT) Machine, characterized by deterministic rules for Asymmetric transitions, and the Classical Tsetlin (CT) Machine, employing deterministic rules for symmetric transitions. Strikingly, the introduced APT methodology demonstrates highly competitive outcomes compared to established machine learning methods. Notably, both APT and AT exhibit state-of-the-art performance, surpassing the Classical Tsetlin Machine, emphasizing the efficacy of asymmetric models for achieving superior outcomes. Remarkably, APT exhibits even better performance than AT, particularly in handling complex datasets.

Security patterns encompass security-related issues in secure software system development and operations that often appear in certain contexts. Since the late 1990s about 500 security patterns have been proposed. Although the technical components are well investigated, the direction, overall picture, and barriers to implementation are not. Here, a systematic literature review of 240 papers is used to devise a taxonomy for security pattern research. Our taxonomy and the survey results should improve communications among practitioners and researchers, standardize the terminology, and increase the effectiveness of security patterns.

The amorphous Fe77Cu1Si13B9 ribbons were treated with pulsed laser interference heating (PLIH). It was confirmed here that the use of the laser heating process allowed for obtaining two-dimensional crystallised micro-areas, periodically distributed (at a distance of 17µm) on the surface of the amorphous ribbons. The correlation between structural changes (SEM, TEM, HRTEM) and the distribution of magnetic field lines of heated amorphous Fe77Cu1Si13B9 (FeCuSiB) ribbons is presented. Particular attention is paid to structure changes in micro-areas where, by controlling the laser interference heating process, partial crystallisation of amorphous alloys and the formation of clusters or single nanocrystallites (α-Fe(Si)) embedded in an amorphous matrix are given. The addition of copper to the FeSiB alloy promoted inhibition of grain growth. Electron holography of micro-areas confirmed shifts of the magnetic field lines in the areas of nanocrystallites, the presence of which in the structure caused magnetisation of the surrounding amorphous matrix.

High-performance electromagnetic interference (EMI) shielding materials with ultralow density and environment friendly properties are greatly demanded to address electromagnetic radiation pollution. Herein, carbon nanotubes/polylactic acid (CNTs/PLA) materials with different CNTs contents, which exhibit characteristics of light weight, environmental protection and good chemical stability, are fabricated by 3D printing technology, where CNTs are evenly distributed and bind well with PLA. The performances of 3D printed CNTs/PLA composite are improved compared to pure 3D printed PLA composite, which include mechanical properties, conductive behaviors and electromagnetic interference (EMI) shielding. The EMI shielding effectiveness (SE) of CNTs/PLA composite could be improved when the contents of CNTs increase. When it reaches 15 wt%, the EMI SE of 3D printed CNTs/PLA composite could get up to 47.1 dB, which shields 99.998% of electromagnetic energy. Meanwhile, the EMI shielding mechanism of 3D printed CNTs/PLA composite is mainly of absorption loss, and it generally accounted for more than 80% of the total shielding loss. These excellent comprehensive performances endow the 3D printed CNTs/PLA composite with great potential for use in industrial and aerospace area.

Radio Frequency Interference (RFI) detection and characterization play a critical role to in ensuring the security of all wireless communication networks. Advances in Machine Learning (ML) have led to the deployment of many robust techniques dealing with various types of RFI. To sidestep an unavoidable complicated feature extraction step in ML, this paper proposes an efficient end-to-end method using the latest advances in deep learning to extract the appropriate features of the RFI signal. Moreover, this study utilizes the benefits of transfer learning to determine both the type of received RFI signals and their modulation types. To this end, the scalogram of the received signals is used as the input of the pre-trained convolutional neural networks (CNN), followed by a fully-connected classifier. This study considers a digital video stream as the signal of interest (SoI), transmitted in a real-time satellite-to-ground communication using DVB-S2 standards. To create the RFI dataset, the SoI is combined with three well-known jammers namely, continuous-wave interference (CWI), multi- continuous-wave interference (MCWI), and chirp interference (CI). This study investigated four well-known pre-trained CNN architectures, namely, AlexNet, VGG-16, GoogleNet, and ResNet-18, for the feature extraction to recognize the visual RFI patterns directly from pixel images with minimal preprocessing. Moreover, the robustness of the proposed classifiers is evaluated by the data generated at different signal to noise ratios (SNR).

Cable interference in cable-driven mechanisms (CDM) is a major challenge in their applications. The wrench closure workspace (WCW) in a fully constrained mechanism may not be realized unless cable interference is considered. This paper classifies all possible types of cable interferences for planar cable-driven mechanisms and presents an analytical solution to find the boundaries of the constant-orientation interference region. It is shown that interference between cables starts and ends when one end of a cable coincides with another cable which can be thought as lying a point on a line segment. This geometrical view is developed and applied to provide a framework for the analysis of cable interference. By subtracting the interference space form WCW, the interference-free workspace is obtained in which the robot is able to operate.

One of the most common limits to gas sensor performance is the presence of unwanted interference fringes or etalons arising, for example, from multiple reflections between surfaces in the optical path. Additionally, since the amplitude and the frequency of these interference depend on the distance and alignment of the optical elements, they are affected by temperature changes and mechanical disturbances, giving rise to a drift of the signal. In this work, we present a novel semi-parametric algorithm which allows the extraction of a signal, like the spectroscopic absorption line of a gas molecule, from a background containing arbitrary disturbances, without having to make any assumption on the functional form of these disturbances. The algorithm is applied first to simulated data and then to oxygen absorption measurements in presence of strong fringes.To the best of the authors' knowledge, the algorithm enables an unprecedented accuracy particularly if the fringes have a free spectral range and amplitude comparable to those of the signal to be detected. The described method presents the advantage of being based purely on post processing, and to be of extremely straightforward implementation if the functional form of the Fourier transform of the signal is known. Therefore it has the potential to enable interference-immune absorption spectroscopy. Finally, its relevance goes beyond absorption spectroscopy for gas sensing since it can be applied to any kind of spectroscopic data.

Ovarian tissue cryopreservation (OTC) or testicular tissue cryopreservation (TTC) are effective and often the only options for fertility preservation in female or male patients due to oncological, medical, or social aspects. While TTC and resumption of spermatogenesis, either in vivo or in vitro, has still be considered an experimental approach in humans, OTC and autotransplantation has been applied increasingly to preserve fertility with more than 200 live births worldwide. However, the cryopreservation of reproductive cells followed by the resumption of gametogenesis, either in vivo or in vitro, may interfere with sensitive and highly regulated cellular processes. In particular, the epigenetic profile, which includes not just reversible modifications of the DNA itself but also post-translational histone modifications, small non-coding RNAs, gene expression and availability, and storage of related proteins or transcripts, have to be considered in this context. Due to complex reprogramming and maintenance mechanisms of the epigenome in germ cells, growing embryos, and offspring, OTC and TTC are carried out at very critical moments early in the life cycle. Given this background, the safety of OTC and TTC taking into account the epigenetic profile has to be clarified. Cryopreservation of mature germ cells (including Metaphase II oocytes and mature spermatozoa collected via ejaculation or more invasively after testicular biopsy) or embryos has been used successfully for many years in Medically Assisted Reproduction (MAR). However, tissue freezing followed by in vitro or in vivo gametogenesis has become more attractive in the past, while few human studies have analysed the epigenetic effects, with most data deriving from animal studies. In this review, we highlight the potential influence of the cryopreservation of immature germ cells and subsequent in vivo or in vitro growth and differentiation on the epigenetic profile in humans and animals.

Footprints are powerful indicators for evaluating the impact of the bioeconomy of a country on environmental goods, domestically and abroad. In this study, we apply a hybrid approach combining a Multi-Regional Input-Output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. The German case study shows that the aLF abroad is larger by a factor of 2.5 to 3 than the aLF in Germany. In 2005 and 2010, conversion of natural and semi-natural land-cover types abroad allocated to Germany due to import increases was 2.5 times higher than the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy to the global average. The case study shows that the applied land footprint provides clear and meaningful information for policymakers and other stakeholders. The presented methodological approach can be applied to other countries and regions covered in the underlying database EXIOBASE. It can be adapted, also for an assessment of other ecosystem functions, such as water or soil fertility.

The effective management of Fusarium wilt of bananas (FW) depends on the knowledge of the disease dynamics in time and space. The objectives of this work were: To estimate disease intensity and impact, and to investigate the spatial and temporal dynamic of FW. Fields planted with Silk (n = 10), Pome (n = 17) or Cavendish (n = 3) banana subgroups were surveyed in Brazil, totaling 95 ha. In each field, all plants were visually assessed and diseased plants were georeferenced. The incidence of FW and the impact of the disease on yield on a regional scale were estimated. Spatial patterns were analyzed using quadrat- and distance-based methods. FW incidence ranged from 0.09 to 41.42%, being higher in Silk fields (median = 14.26%). Impacts of epidemics on yield ranged from 18.4 to 8,192.5 kg.ha-1.year-1, with a median of 935.2 kg.ha-1.year-1. The higher economic impact of the disease was observed on Silk cultivar with a median loss of US$ 910.5 ha-1.year-1. Overall, estimated losses increased on average by US$ 109.8 ha-1.year-1 at each 1% of incidence. Aggregation of FW was detected by all analytical methods in 13 fields (1 of Cavendish, 11 of Pome and 1 of Silk). In the other 17 fields, at least one analytical method did not reject the null hypothesis of randomness. One field (5 ha), composed of six plots, was selected for spatial and temporal studies during two years with bi-monthly assessments. A sigmoidal curve represented the FW progress and the Gompertz model best fitted disease progress. The level of aggregation varied over time, and evidence of secondary infection to neighboring and distant plants were detected. FW is a widespread problem in Brazil and yield losses can be of high magnitude. Epidemiology-based management strategies can now be better established.

The expression microarray technique was performed to investigate the differences in gene expression between Czech Large White pigs and wild boars in the longissimus lumborum et thoracis and biceps femoris muscle tissues. The NREP gene (neuronal regeneration related protein homolog) was selected for detailed study as an expressional and functional candidate gene. NREP plays a role in the transformation of neural, muscle and fibroblast cells and in smooth muscle myogenesis. Quantitative real-time PCR results confirmed that the porcine NREP gene was expressed in both skeletal muscles and significantly overexpressed in Czech Large White pigs compared to wild boars (P &lt; 0.05). We identified 9 polymorphic sites in genomic DNA of NREP gene. Six of these polymorphisms were in complete linkage disequilibrium and therefore only 4 polymorphisms were informative. Associations of these 4 polymorphisms (HF571253:g.103G&gt;A, HF571253:g.134G&gt;A, HF571253:g.179T&gt;C and HF571253:g.402_409delT) with meat performance traits were assessed in Czech Large White pigs. New polymorphisms in NREP gene were significantly associated with parameters of daily weight gain, lean meat and backfat thickness in Czech Large White pigs. Our primary study suggested that porcine NREP may play an important role in skeletal muscle growth, fat metabolism and meat performance traits.

Agriculture and farming worldwide are responsible for numerous environmental threats, including degradation of land and water resources depletion. Underlining the dynamic interaction between bio-physical and socio-economic drivers is the key towards a more sustainable land and water management. With regard to a highly developed agricultural area in southern Italy, multi-regression models were developed to interpret the observed inter-annual variability of cropped land. Main drivers related to Common Agricultural Policy support, product market prices, crop yield and irrigation water availability were investigated. The adopted models revealed the different weighs of each driver. The findings reported the role that direct payments played in supporting the extension of irrigated crops, such as processing tomato. Likewise, the models pointed to decoupled payment scheme as the most important driver of change in the crop pattern over the last years.

In this paper, a study was conducted on the Ramsey interference and spectral line locking techniques based on rubidium-87 cold atoms. Using sequential control technique, the timing design of a three-dimensional magneto-optical trap (MOT), cold atoms’ free fall, Ramsey microwave interference, and two-level fluorescence detection was realized, achieving the state preparation of cold atoms and clock transitions. By designing an automatic peak-finding algorithm, numerical integration was performed on the time-of-flying (TOF) signal, and narrow linewidth cold atom Ramsey interference fringes were obtained. Based on this, a frequency-hopping method was used to lock the frequency of the 10MHz oven-controlled crystal oscillator (OCXO) in a closed loop, achieving a linewidth of 38Hz. This preliminary result verifies the feasibility of the system design.

Spontaneous parametric downconversion At the heart of all quantum optics experiments is called as Spontaneous parametric downconversion. This is a downconversion process when the output frequency is smaller than the input frequency. The whole process is Spontaneous. Experimentally we have to downconvert the photons and convert them into pairs of a photon. We use the Beta-barium borate(BBO) crystals to downconvert the coming violet-blue laser. We find the maximum number of counts on detectors and their coincidence. When the BBO crystals is well aligned, we find no difference in detecting vertically or horizontally polarized photons because they are orthogonal to each other. Proof of existence of photons We want to investigate the properties and verification of quantization of light. Experimently we want to establish the existence of single photon which shows the grainy-ness of individual photon quantum mechanically and shows wave like behaviour classically. We get the coincidences counts on detectors with addition of detector B’ by using PBS in the path of signal beam. Experimentally we prove the Quantum as well as classical nature of light by the measurement of second-order degree coherence in light g²(0). For classically the g²(0)≥1 and quantum mechanically g²(0)=0.When we add the delay time interval of 1ns after reflected and transmitted photons from PBS signal beam. The delay generator did not create a significant difference in the coincidence counts detection in the value of g²(τ ). Single photon interference and quantum eraser we want to observe the interference by making the single photons pass through the interferometer, and we will see the interference of the single photons. If the light passes through the interferometer, the visibility of the interference pattern to which extent these fringes are observed is dependent on the extent to which the ’which-way’ or ’which-path’ information is available to the experimenter. If the observer knows the information about the ’which-way’ of the light path, then we cannot observe the inference pattern. Because we only can make an interference pattern if we erase the which-way information of the light path. If you erase the information about the’ which-way,’ we can observe a very high interference pattern. We can erase the information about the light path’s ’which-way’ or ’which-path’ by using a polarizer and orienting at 45^o. In this way, we can observe a very high pattern. If we introduce the angle of the polarizer at 0^o or 90^o, we see very low interference.

Generally, when cognitive radio users are in Underlay mode, through the analysis of the electromagnetic spectrum in time, frequency, space, and field of multiple dimensional data accounts for judging the inherent correlation of the radio spectrum used/idle state, this is the realization of cognitive radio users (secondary users, SUs) efficient access to the foundation of the limited spectrum resources. Therefore, how to efficiently use of spectrum status of each SU implementation of reception multidimensional combination forecasting is the core of this paper addressing the problem. In this paper, we propose a deep-learning hybrid model called TensorGCN-LSTM based on the tensor data structure. The model treats SUs deployed at different spatial locations under the same frequency and the spectrum status of SUs themselves under different frequencies in the task area as nodes and constructs two types of graph structures. Graph convolutional operations are used to sequentially extract corresponding spatial-domain and frequency-domain features from the two types of graph structures. Then, the long short-term memory (LSTM) model is used to fuse the spatial, frequency, and temporal features of the cognitive radio environment data. Finally, the prediction task of the spectrum distribution situation is accomplished through fully connected layers. Specifically, the model constructs a tensor graph based on the spatial similarity of SUs' locations and the frequency correlation between different frequency signals received by SUs, which describes the electromagnetic wave's dependency relationship in spatial and frequency domains. LSTM is used to capture the electromagnetic wave's dependency relationship in the temporal domain. To evaluate the effectiveness of the model, we conducted ablation experiments on LSTM, GCN, GC-LSTM, and TensorGCN-LSTM models using simulated data. The experimental results show that our model achieved better prediction performance in RMSE, and the correlation coefficient R2 of 0.8753 also confirmed the feasibility of the model.

Music acoustics is an interdisciplinary field and mathematics is the basis in the music art form. Music and mathematics correlation exist since the inception of music. Various philosophers, scientists, mathematicians and musicians have expressed their views about this relationship. This paper attempts to explore this association with focus on melodic pattern identification. Mathematics in Indian Classical music with raga as the basis and just intonation tuning system is discussed. Indian vocal music clips are used for different pitch estimation algorithms in the experimentation. Harmonic product spectrum and auto-correlation algorithms are tested for accurate pitch estimation. Enhanced auto-correlation function using audio segmentation is compared with other approaches for effective pitch extraction. Results indicate pitch extraction with enhanced auto-correlation function provides accurate results as compared with other approaches tested.

Despite increased protection globally, climate change and other anthropogenic factors have caused a significant decline in seagrass cover. Identifying the specific causes of this decline is paramount if they are to be addressed. Therefore, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in the Bluefields Bay Special Fish Conservation Area (BBSFCA), a marine protected area on Jamaica’s southern coast. We used two random forest regression (RFr) models that included 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary data, reflectance data from level 2 processed 2013 Landsat 7 and 8 images and image band texture statistics maps (mean and variance) as predictors to generate 24 SAV percentage cover maps for the period 1984 – 2021 (37 years) using data from Landsat 4-5, 7 and 8 images., from which benthic features maps (SAV present, absent and coral reef) were created. Rainfall and map data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed using a pixel-based regression. Finally, the most important spatial pattern predictors (two rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance)) of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified using spatial Bayesian INLA generalized linear mixed models. SAV area/extent was largely stable with &gt; 70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or a 13%) during 2002 – 2006 and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by &gt;1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change. The pixel-based regression highlighted areas where mean monthly rainfall had a positive overall effect on SAV cover percentage change (across the entire bay) and gain (closer to the mouth of a river). The most frequently selected important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Hurricane Gilbert, which made landfall in 1988, resulted in higher SAV percentage cover loss in 1987 - 1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002 – 2006. Although some locations impacted by Ivan and not by Dean recovered during 2006 – 2008, exposure to Ivan explained percentage cover loss during 2006 – 2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013 – 2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

Disruptive selection arises when extreme phenotypes have a fitness advantage compared to more intermediate phenotypes. Theory and evidence suggest that intraspecific resource competition is a key driver of disruptive selection. However, while competition can be indirect (exploitative) or direct (interference), the role of interference competition in disruptive selection has not been tested, and most models of disruptive selection assume exploitative competition. We experimentally investigated whether the type of competition affects the outcome of competitive interactions using a system where disruptive selection is common: Mexican spadefoot toads (Spea multiplicata). Spea tadpoles develop into alternative resource-use phenotypes: carnivores, which consume fairy shrimp and other tadpoles, and omnivores, which feed on algae and detritus. Tadpoles intermediate in phenotype have low fitness when competition is intense, as they are outcompeted by the specialized tadpoles. Our experiments revealed that the presence of carnivores significantly decreased foraging behavior in intermediate tadpoles, and that intermediate tadpoles had significantly lower growth rates in interference competition treatments with carnivores but not with omnivores. Interference competition may therefore be important in driving disruptive selection. As carnivore tadpoles are also cannibalistic, the ‘fear’ effect may have a greater impact on intermediate tadpoles than exploitative competition alone, similarly to non-consumptive effects in predator-prey or intraguild relationships.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

Ground penetrating radar (georadar, GPR), widely used in geology, archeology and road construction, is an efficient tool for searching and studying subsurface objects and structures. When planning GPR missions, it is necessary to predict the resolution of the device and the achievable probing depth. The article discusses the methods and results of assessing these characteristics of the Loza-V and Loza-N radars obtained in the course of archaeological and geographical expedition works.

For personalized recommender systems,matrix factorization and its variants have become mainstream in collaborative filtering.However,the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless,most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper,we propose a metric learning-based social recommendation model called SRMC.SRMC exploits users' co-occurrence pattern to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations.Experiments on three public datasets show that our model is more effective than the compared models.

Existing implementations of game design patterns have largely been confined to theoretical or research settings. Weaknesses in these implementations have prevented game design patterns from being properly evaluated as an educational and practical development tool. This paper examines these weaknesses, describes a method of developing and applying patterns that overcome the weaknesses, and evaluates use of the method for game design education and practice. Weaknesses in existing pattern implementations are: omission of design problems, presumption of functional completeness at the level of pattern languages, narrow topical focus, and lack of a concise, repeatable method for pattern production. Several features of the proposed method were specifically built to address these weaknesses, namely the pattern template, the process for connecting patterns into a language and assessing the language’s scope, a rubric for assessing pattern confidence and interconnectivity confidence, and pattern-building exercises. This method was applied in a classroom setting. Results, as assessed by the evaluation of student work, suggest that creating patterns/pattern languages is an effective pedagogical approach. De-signs produced using designer-created patterns closely align with existing design theory and are clearly understood by students. The above results may indicate that the path to gaining wider acceptance of pattern theory as a design framework within game design is not to produce a universal pattern language but to facilitate the creation of case-specific languages, by students and professional designers, that use a shared ontology and thus can be combined easily to solve the diverse sets of problems faced by these groups.

The study aimed to evaluate the association between the changes in ventilatory variables (tidal volume (Vt), respiratory rate (RR), and lung ventilation (VE)) and deoxygenation of m.intescostales (∆SmO2-m.intercostales) during a maximal incremental exercise in nineteen male competitive marathon runners. The ventilatory variables and oxygen-consumption (VO2) were recorded breath-by-breath by exhaled gas analysis. A near-infrared spectroscopy device (MOXY) located in the right-hemithorax allowed recording SmO2-m.intercostales. To explore changes in oxygen levels in muscles with high demand during exercise, a second MOXY records SmO2-m.vastus laterallis. The triphasic model of exercise intensity was used for evaluating changes in SmO2 in both muscle groups. We found that ∆SmO2-m.intercostales correlated with VO2-peak (r=0.65; p=0.002) and the increase of VE (r=0.78; p=0.001), RR (r=0.54; p=0.001), but not Vt (p=0.210). The interaction of factors (muscles X exercise-phases) in SmO2 expressed as an arbitrary unit (a.u) was significant (p=0.005). At VT1 were no difference (p=0.177), but SmO2-m.intercostales was higher at VT1 (p&lt;0.001) and VO2-peak (p&lt;0.001). In competitive marathon runners, the m.intercostales deoxygenation during incremental exercise is directly associated with the aerobic capacity and increased lung ventilation and respiratory rate, but not tidal volume. Besides, it shows less deoxygenation than m.vastus laterallis at intensities above the aerobic ventilatory threshold.

Recent advancements in web-based geospatial software and smartphone technology have popularized the process of voluntary production and sharing of geospatial data by individual citizens. Through such Volunteered Geographic Information (VGI) activities, people across the world participate in online mapping projects (such as OpenStreetMap) to insert their spatial information. The quality of data generated by such VGI activities has profound impacts on online mapping projects and their spatial database. In this study, we examine the VGI contribution pattern in OpenStreetMap through three case study neighborhoods located in three major cities: Tehran, London, and Los Angeles, and investigate how it might affect the process of quality assessment of VGI.

Global navigation satellite system (GNSS) array antenna receivers are widely used to suppress wideband interference in navigation countermeasures. However, existing array antenna receivers all adopt digital array structure and digital beamforming technique, and it has limited analog-front-end (AFE) dynamic range. In strong interference scenarios, AFE saturation will occur, which limits the maximum interference suppression ability of the array receiver. Aiming at this issue, this paper proposes a robust wideband interference suppression method for GNSS array antenna receivers based on hybrid beamforming technique. Firstly, a novel fully connected hybrid array receiver structure is proposed; Secondly, the corresponding hybrid beamforming method is proposed at the same time, and it realizes the complete elimination of strong interference by jointly suppression in analog domain and digital domain. After mathematical simulation experiments, it is verified that compared to the digital beamforming-based anti-jamming technique, the proposed method can effectively suppress strong wideband interference, and the maximum interference suppression ability is improved by 36 dB.

In the Aharonov-Bohm setup, a double-slit experiment, coherent beams of electrons passing through two slits form an interference pattern on the observing screen. However, when a long but thin solenoid of current is introduced behind the slits between the two electron beams, an extra phase difference between them appears, as shown by a shift in the interference pattern. This happens even though there is no magnetic field outside the solenoid, at the location of the beams. This is known as Aharonov-Bohm effect, though the idea was mooted apparently a decade earlier, and the effect sometimes is called Ehrenberg-Siday-Aharonov-Bohm effect. This mysterious effect, purportedly arises owing to an electromagnetic momentum, attributed to the presence at the location of either beam, a vector potential due to the solenoid of current even when there exists no magnetic field outside the solenoid. The first experimental confirmation came soon and It has since been amply verified using clever experimental setups, leaving hardly any doubts that the observed effect is real. However, on the theoretical side the picture is not so clear and a satisfactory physical explanation of the existence of momentum, at least under the aegis of classical electromagnetism, is still missing since inception of the idea more than half a century back. It has remained a puzzle, how just potential, thought to be a mere mathematical tools for calculating electromagnetic field, can give rise to an electromagnetic momentum in a system, in lieu of field itself. We here show that a subtle momentum can be seen to lie in the product of the drift velocities of the current carrying charges and the mass equivalent of their non-localized potential energies in the electric field of the interfering electrons, which manifests, from a classical point of view, a linear momentum in the system. It is this hard-to-pinpoint, additional momentum, reflected through an extra phase difference between the interfering beams of electrons, which exhibits from a classical physics perspective, the presence of an elusive, long sought-after electromagnetic momentum in the system.

Motor control, movement impairment and postural control recovery targeted in rehabilitation could be affected by pain. The main objective of this comprehensive review is to provide a synthesis of the effect of experimental and chronic pain on postural control throughout the available literature. After presenting the neurophysiological pathways of pain, we demonstrated that pain, preferentially localized at low back or in the leg induced postural control alteration. While proprioceptive and cortical excitability seems modified with pain, spinal modulation assessment might provide new understanding of the pain phenomenon related to postural control. Literature highlight that the motor control of trunk muscles in patient presenting with low back pain could be dichotomized in two populations, where the first one over-activate trunk muscles, the second one under-activate trunk muscles, and both generating increase of tissues loading. Taking account all this findings, will help clinician to provide adapted treatment for managing both pain and postural control.

In this paper, we propose a multi-zone service control scheme to maximize the performance of each service zone when a large number of cellular service zones and D2D (Device-to-Device) service zones are composed to 5G cellular network. This paper also improves performance of service zone by dividing traffic into real-time traffic and non-real-time traffic in order to minimize traffic interference. Real-time traffic and non-real-time traffic have a significant impact on communication performance. We propose a new self-detection traffic interference control technique to improve the QoS and throughput of D2D and C2D communication in a cellular network, STICS (Self-detecting Traffic Interference Control Scheme). The proposed STICS scheme distinguishes between short-term traffic congestion process and long-term traffic congestion process according to traffic characteristics to detect and control traffic. When the proposed scheme is applied to the 5G-based cellular network environment, it is expected that the traffic type will be efficiently classified by self-detecting the traffic according to the flow. Such classified traffic is less sensitive to communication between the D2D and C2D links, thereby reducing traffic overload. We evaluate the performance of the proposed scheme through simulation and show that the proposed scheme is more efficient than other comparison schemes.

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

Background: Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. The lack of or inadequate information about the circumstances, substances and populations at risk are considered barriers to the actual prevention of poisoning and effective intervention strategies in Saudi Arabia. The aim of the current study was to describe the pattern and determinants of chemical and drug overdose poisoning in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the Environmental Health and Occupational Safety Department in Makkah over two years (2018-2019) were reviewed.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions of Saudi Arabia. Further in-depth studies are needed to elaborate other social and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning.

Pressure drop and flow pattern of oil-water flows were investigated in a 19 mm ID clear polyvinyl chloride pipe consisting of U-bend with radius of curvature of 100 mm. The range for oil and water superficial velocities tested were and respectively. Measurements were carried out under different flow conditions in a test section that consisted of four different parts: upstream of the bend, at the bend and at two redeveloping flow locations after the bend. The result indicated that the bend had limited influence on downstream flow patterns. However, the shear forces imposed by the bend caused some shift flow pattern transition and bubble characteristics in the redeveloping flow section after the bend relative to develop flow before the bend. Generally, pressure gradient at all the test sections increased with both oil fraction and water superficial velocity and there was a sharp change of pressure gradient profile during phase inversion. The transition point where phase inversion occurred was always within the range of . Pressure losses differed at the various test sections and the difference was strongly linked to the superficial velocity of the phases and the flow pattern. At high mixture velocity, pressure losses at the redeveloping section after the bend were higher than that at the bend and that for fully developed flows. At low mixture velocity, pressure losses at the bend are higher than in the straight sections. Pressure drop generally decreased with level of flow development downstream of the bend.

For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher threshold level owing to the presence of RFI. In this paper, we propose a method to detect and mitigate RFI contamination using the threshold level from statistical criteria based on a spectrogram technique. Mean and skewness spectrograms are created from a brightness temperature spectrogram by shifting the 2-D window to discriminate the form of the symmetric distribution as a natural thermal emission signal. From the remaining bins of the mean spectrogram eliminated by RFI-flagged bins in the skewness spectrogram for data captured at 0.1-s intervals, two distribution sides are identically created from the left side of the distribution by changing the standard position of the distribution. Simultaneously, kurtosis calculations from these bins for each symmetric distribution are repeatedly performed to determine the retrieved brightness temperature corresponding to the closest kurtosis value of three. The performance is evaluated using experimental data, and the error in the retrieved brightness temperature is observed to be less than approximately 3 K from a window with a size of 100 × 100 time-frequency bins according to the RFI levels and cases.

Pregestational and gestational diabetes mellitus are relevant complications of pregnancy and antidiabetic drugs are prescribed to obtain glycemic control and improve perinatal outcomes. The objective of this study was to highlight the prescription pattern of antidiabetics before, during and after pregnancy in Italy and to evaluate its appropriateness. A multi-database cross sectional population study using a Common Data Model was performed. In a cohort of about 450,000 women, the prescribing profile of antidiabetics seemed to be in line with the Italian standards for the treatment of GDM which currently do not recommend the use of oral antidiabetics and non-insulin injection, even if a small share of new users (up to 3.8% in the third trimester) used oral antidiabetics. A substantial variability in the prescription pattern was observed among the Italian regions considered: the highest increase was registered in Tuscany (4.2%), Umbria (3.5%) and Emilia-Romagna (2.6%) while the lowest in Lombardy (1.5%), Veneto (1.7%) and Apulia (1.7%). Analysing the prevalence of use of antidiabetics between foreign women we observed that the consumption during pregnancy was higher than Italians (second trimester: 1,8% vs 0,9%, third trimester: 3,6% vs 1,8%).

Traditionally, neutron scattering is an essential method for the analysis of spin structures and spin excitations in bulk materials. Over the last 30 years, polarized neutron scattering in terms of reflectometry has also contributed largely to the analysis of magnetic thin films and magnetic multilayers. More recently it has been shown that polarized neutron reflectivity is, in addition, a suitable tool for the study of thin films laterally patterned with magnetic stripes or islands. We provide a brief overview of the fundamental properties of polarized neutron reflectivity, considering different domain states, domain fluctuations, and different domain sizes with respect to the neutron coherence volume. The discussion is exemplified by a set of simulated reflectivities assuming either complete polarization and polarization analysis, or a reduced form of polarized neutron reflectivity without polarization analysis. Furthermore, we emphasize the importance of the neutron coherence volume for the interpretation of specular and off-specular intensity maps, in particular when studying laterally non-homogeneous magnetic films. Finally, experimental results, fits, and simulations are shown for specular and off-specular scattering from a magnetic film that has been lithographically patterned into a periodic stripe array. These experiments demonstrate the different and mutually complementary information that can be gained when orienting the stripe array parallel or perpendicular to the scattering plane.

The human proteome is composed from diverse and heterogeneous gene products/proteoforms. Previously, we have been discussing the main technical aspects in developing for inventory of human proteoforms that would be visually attractive, clear, and easy to search (Naryzhny S. J. Proteomics 2018, S1874-3919(18) 30220-3). Here, we present our first draft of the database of proteoforms that is based on this discussion. The database principles and structure are described. The database is called “2DE-pattern” as it contains multiple isoform-centric patterns of proteoforms separated according to 2DE principles.

This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens from the unique patterns of their tails. Starting from a dataset composed of images of whale tails, all the phases of the process of creation and training of a neural network are detailed – from the analysis and pre-processing of images to the elaboration of predictions, using TensorFlow and Keras frameworks. Other possible alternatives are also explained when it comes to tackling this problem and the complications that have arisen during the process of developing this paper.

Forensic anthropologists play a key role in skeletal trauma analysis and commonly use macroscopic features to distinguish between trauma types. However, this approach can be challenging, particularly in cases of highly comminuted or incompletely recovered fractures. Histological analysis of microscopic fracture characteristics in fractured bones may thus help provide additional information on trauma type and bone fracture biomechanics in general. This study analysed the extent of microcrack damage to osteons in long bones with blunt force trauma (BFT) and gunshot trauma (GST), from both traumatic death cases and post-mortem experimental fractures. We identified four types of osteonal damage (OD). In traumatic death cases, OD affecting the inside of the osteon and compromising the Haversian canal (type 1) was found to be indicative of BFT. Moreover, OD affecting the cement line (type 3) and interstitial lamellae (type 4) was more common in the GST samples. OD affecting the inside of the osteon without compromising the Haversian canal (type 2) was not found to be indicative of either trauma type. In cases of experimental fractures, our study revealed that post-mortem fractures in dry bone samples featured the highest amount of OD, particularly of type 4. This study also found that the experimentally produced GST featured similar OD pattern to GST death cases. These findings support our hypothesis that there are distinct osteonal damage patterns in human long bones with BFT and GST, which are of relevant value for trauma analysis in forensic anthropology.

Background: Myocardial infarction (MI) is a major cause of mortality worldwide. Its presentation as ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI) is influence by atherosclerosis risk factors. Aim: To assess the patterns of presentation and predicting risk factors of acute MI in Kosovo. Methods: This is a cross sectional study from the Clinic of Cardiology of the University Clinical Center of Kosovo, which included all patients hospitalized with acute MI over a period of 7 years (January 1st, 2014 to December 31st, 2020). Data was collected using a structured questionnaire and epidemiological patterns and risk factors were analyzed. Results: Among 7353 patients admitted with acute MI (age 63 ± 12 years, 29% female), 4366 (59.4%) patients had STEMI, and 2987 (40.6%) NSTEMI. Patients age was not different between the two groups (p=0.077). NSTEMI patients smoked less (48.3% vs. 54%, p<0.001), but were more diabetics (37.8% vs. 33.6%, p<0.001), more hypertensives (69.6% vs. 63%, p<0.001), frequently had family history for coronary artery disease (CAD) (40% vs 38%, p=0.009), and included more females compared to STEMI patients (32% vs 27%, p<0.001). The two groups of patients, did not differ in the prevalence of significant CAD on angiography (66.8% vs. 67.8%, p = 0.396), but NSTEMI patients underwent less primary percutaneous interventions compared with STEMI patients (43.6% vs. 55.2%, p < 0.001). Conclusion: In Kosovo, STEMI is commoner than NSTEMI, who were mostly males, more likely to have diabetes, hypertension and family history for CAD compared to those with NSTEMI. Smoking and arterial hypertension proved the strongest predictors of acute MI, in Kosovo, thus highlighting the urgent need for better atherosclerosis risk control and education strategy.

Galectins have been shown to have roles in cancer progression via contributions to angiogenesis, metastasis, cell division, and evasion of immune destruction. This study analyses galectin-1, -3, and -9 serum concentrations in breast cancer patients by enzyme-linked immunosorbent assay (ELISA) against the characteristics of the patient and tumor such as stage, molecular subtype, and receptor expression. Galectin-9 was found to be statistically significantly increased in HER2 enriched tumors as well as being reduced in patients with hormone receptor positive tumors and increased in patients with HER2 amplified tissues. Galectin-1 was found to be statistically significantly increased in the serum of patients who had undergone hormonal, immunotherapy, or chemotherapy. These findings provide insight as to the changes in galectin levels during cancer progress, response to treatment and molecular phenotype. These findings are valuable in the further understanding of the relationships of galectin and tumor biology and can inform future research on therapeutic targets for galectin inhibitors and the utility of galectin biomarkers.

The nutraceutical value of pomegranate in the treatment of many neoplastic, cardiovascular, viral, inflammatory, metabolic, microbial, intestinal, reproductive and skin diseases is well-documented and is linked to its richness in phenolic compounds. This study aims to evaluate nutraceutical and genetic diversity of novel pomegranate genotypes (G1-G5) in comparison to leading commercial pomegranate varieties i.e. ‘Wonderful’, ‘Primosole’, ‘Dente di Cavallo’ and ‘Valenciana’. Morphometric measurements were carried out on fruits, accompanied by chemical characterization and the development of four new polymorphic SSR markers involved in the flavonoid pathway. The cultivars displayed a marked variability in the weight and shape of fruits, as well as in the weight of arils and juice yield. The highest level of total phenolic content and antioxidant activity was found in ‘Wonderful’ and G4, while the lowest was in ‘Dente di Cavallo’. Furthermore, the results showed that the pomegranate juice, is an excellent source of minerals, especially potassium, which plays a key role in organ functioning. The new flavonoid-related markers effectively differentiated the cultivars with the same diversity pattern as morpho-chemical characterization, so the SSRs developed in the present study can be used as a rapid tool for the identification of pomegranate cultivars with relevant nutraceutical traits.

Data on the KIT mutation rate in skin melanoma in the central European region is missing. Accordingly, in a cohort of 79 double wild type (BRAF/NRAS) skin melanoma KIT mutation was assessed by Sanger sequencing of exons 9,11,13,17 and 18. In this skin melanoma cohort KIT mutation frequency was found to be 34/79 (43%) with a significantly higher rate in acrolentiginous melanoma (ALM) as compared to UV-induced common variants (20/34, 58.8% versus 14/45, 31.1%, p=0.014). Exon 11 was the most frequent mutation site (44.7%) followed by exon 9 (21.1%) equally characterizing UV-induced common histotypes and ALM tumors. KIT mutation hotspots were identified in exon 9 (c491/492), in exon 11 (c559,c572, c570), in exon 13 (c642), in exon 17 (c822) and in exon 18 (c853). The relatively high KIT mutation rate in skin melanoma in this central-European cohort justifies regular testing of this molecular target.

The effect of divergence of chute sidewalls with three different baffle block geometries namely USBR, trihedral and semicircular blocks, as well as the depth and dimensions of the scour hole downstream of the chute were studied using a physical model. For this purpose, 9 models of baffled chutes were designed and constructed with divergence ratios of 1.45, 1.75, and 2.45 and without divergence (with a divergence ratio of 1). Comparing the results on the effect of block geometry at different divergence ratios revealed that the use of blocks proposed in this study instead of standard USBR blocks reduced the mean and maximum scour hole by 50%. For a given block geometry, the mean depth, maximum depth, and length of scour hole were reduced by 75%, 58%, and 50%, respectively.

Stingless bee beekeeping provides new opportunities to improve the incomes of many households in Malaysia through the sale of honey and other bee products. While Heterotrigona itama is one of the most commonly cultured species of stingless bees, its behavior is not very well understood. Hence, we conducted this study to investigate the behavior of H. itama in exploiting food sources by ascertaining the nectar sugar concentration preferred by the bee. We also aimed to determine the preferred distance of food source from the bee hive. Our results suggest that H. itama prefers high sugar concentrations of 35% and above, and they would fly up to 7 m from the hive to collect food. We discuss how nectar concentration and food distance influence the number of bees exploiting food sources and the overall foraging pattern of H. itama.

This paper aims to investigate carbon monoxide (CO) concentrations on roadways of Karachi, potential blood levels carboxy-hemoglobin (COHb) in Karachi. Geographical information system (GIS) was used for spatial analysis of diseases potentiality while an interpolation technique has been applied for surface generation with town boundaries and later evaluates risk areas.The higher concentration of carbon monoxide in the ambient is mainly due to automobile emissions. The City center and CBD areas are more perilous.

In order to monitor the diversity of terrestrial biomes, the Earth Exploration Satellite Services demand a high data rate for downlink transmissions while sharing their frequency spectrum with, and suffering interferences from, cellular Base Stations. Both highlight the dilemmas of spectral efficiency (bps/Hz) and spectral coexistence. Our research aims to mitigate interference on low orbit satellite downlinks using Cognitive Radio (CR) and Adaptive MODulation and CODing (MODCOD) techniques. To fulfill this: 1) we present CR approaches to enhance spectrum exploitation. Next, 2) we detail Adaptive MODCOD (ACM) technique to increase RF power and spectral efficiencies. Then, 3) we suggest the solution by combining 1) and 2). Afterwards, 4) we analyze it by monitoring the signal to interference plus noise ratio and the CR/MODCOD strategy. Finally, 5) we provide case studies to demonstrate the strategy’s effectiveness through the practical operation of satellite services, and 6) we conduct a bench test of the communication system.

The interference-fit size has a significant effect on CFRP/Al-alloy laminates riveted lap joints, the requirements for the interference-fit size are different because of the strengthening of heterogeneous materials. However, in the process of the riveted CFRP/Al-alloy, the heterogeneous laminates lead to poor structural strength because of the different requirements of interference-fit size. Therefore, the different assembly types of riveting mold are designed to acquire a novel interference-fit size, and the tensile test is adopted to evaluate the tensile property. In addition, the fracture failure of CFRP/Al-alloy laminates riveted lap joint is observed by the ultra-depth of field microscope. Finally, the best assembly type is the trapezoid riveting mold combined with an arc riveting die, and the sidewall intersection angle of the trapezoid riveting mold is 66° which could achieve a suitable interference-fit size and a better mechanical performance.

The interactions between work and personal life are important for ensuring well-being especially during COVID-19 where the lines between work and home are blurred. Work-life interference/imbalance can result in work-related burnout, which has been shown to have negative effects on faculty members’ physical and psychological health. Although our understanding of burnout has advanced considerably in recent years, little is known about the effects of burnout on nursing faculty turnover intentions and career satisfaction. Thus, this study aimed to test a hypothesized model examining the effects of work-life inference on nursing faculty burnout (emotional exhaustion and cynicism), turnover intentions and ultimately, career satisfaction. A predictive cross-sectional design was used. An online national survey of nursing faculty members was administered throughout Canada in Summer 2021. Nursing faculty who held full-time or part-time positions in Canadian academic settings were invited via email to participate in the study. Data was collected from an anonymous survey housed on Qualtrics. Descriptive statistics and reliability estimates were computed. The hypothesized model was tested using structural equation modeling. Data suggest that work-life interference significantly increase burnout which contribute to both higher turnover intentions and lower career satisfaction. Turnover intentions in turn was negatively associated with career satisfaction. The findings add to the growing body of literature linking burnout to turnover and dissatisfaction, highlighting key antecedents and/or drivers of burnout among nurse academics. These results provide suggestions for suitable areas for the development of interventions and policies within the organizational structure to reduce the risk of burnout during and post-COVID-19 and improve faculty retention.

With recent advancements in network technology and spread of Internet, use of social network services and Internet of Things devices has flourished, leading to a continuous generation of large volumes of graph stream data, where changes, such as additions or deletions of vertices and edges occur over time. Additionally, owing to the need for efficient use of storage space and security requirements, graph stream data compression has become essential in various applications. Even though various studies on graph compression methods have been conducted, most of them do not fully reflect the dynamic characteristics of graph streams and complexity of large graphs. In this paper, we propose a compression scheme using provenance data to efficiently process and analyze large graph stream data. It obtains provenance data by analyzing graph stream data and builds a pattern dictionary based on this to perform dictionary-based compression. By improving the existing dictionary-based graph compression methods, it enables more efficient dictionary management through tracking pattern changes and evaluating their importance using provenance. Furthermore, it considers the relationships among sub-patterns using an FP-tree and performs pattern dictionary management that updates pattern scores based on time. Our experiments show that the proposed scheme outperforms existing graph compression methods in key performance metrics, such as compression rate and processing time.

As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable for intrusion detection systems (IDS) requirements. Over the years, many studies have proposed various solutions in this regard including signature-based and machine-learning (ML) based systems. More recently, researchers are considering deep learning (DL) based anomaly detection approaches. Most proposed works in this research field aimed to achieve either one or a combination of high accuracy, considerably low false alarm rates (FARs), high classification specificity and detection sensitivity, achieving lightweight DL models, or other ML and DL-related performance measurement metrics. In this study, we propose a novel method to convert a raw dataset to an image dataset to magnify patterns. Based on this we devise an anomaly detection for IDS using a lightweight convolutional neural network (CNN) that classifies denial of service and distributed denial of service. The proposed methods were evaluated using a modern dataset, CSE-CIC-IDS2018, and a legacy dataset, NSL-KDD. We have also applied a combined dataset to assess the generalization of the proposed model across various datasets. Our experimental results have demonstrated that the proposed methods achieved high accuracy and considerably low FARs with high specificity and sensitivity. The resulting loss and accuracy curves have also demonstrated the excellent generalization of the proposed lightweight CNN model, effectively avoiding overfitting. This holds for both the modern and legacy datasets, including their mixed version.

The fate of critically sick patients with infections in intensive care units (ICUs) is significantly influenced by antimicrobial resistance, which has become a serious concern in developing nations. This observational study was conducted at the IBN Sina Specialised Hospital in Dhaka, Bangladesh, over a 12-month period from January 2021 to December 2021, in order to track the pattern of antibiotic resistance among the patients admitted to the intensive care unit (ICU). Aspiration pneumonia (29%) and diabetes mellitus (24%), among 200 patients, were the most common main diagnoses. 65 samples (or 26%) of the 250 samples had 85 bacteria identified from them. Urine (14.12%) and tracheal aspirate (64.71%) were the most frequently found sites of infection. In the sample from the tracheal aspirate, Pseudomonas spp. (30.59%), Escherichia coli (24.71%), Acinetobacter spp. (20%), and Klebsiella spp. (14.12) were the most frequently isolated microorganisms. The following antibiotics were shown to have the highest overall patterns of resistance: levofloxacin (68.24), amikacin (64.71), meropenem (49.41), ceftazidime (75.29), ciprofloxacin (78.82), and gentamicin (82.35). The most effective antibiotic against Klebsiella species was meropenem (64.61%), while Acinetobacter species were mostly susceptible to cotrimoxazole (64.67%) and piperacillin + tazobactam (60.50%). Most susceptible to netilmicin (70.48%) and meropenem (49.32%) were Escherichia coli, while Pseudomonas spp. were mostly responsive to colistin (55.14%) and netilmicin (52.25%). Antibiotic resistance is common among intensive care unit (ICU) patients, and most isolated microbes have resistance to traditional medicines.

E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user-item rating matrix input of collaborative filtering. This reviews focuses on algorithmic techniques of existing E-commerce recommendation systems that are sequential pattern based such as ChoRec05, ChenRec09, HuangRec09, LiuRec09, ChoiRec12, Hybrid Model RecSys16, Product RecSys16, SainiRec17, HPCRec18 and HSPCRec19. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potentials for solving more important problems in this domain. The review showed that integrating sequential pattern mining of historical purchase and/or click sequences into user-item matrix for collaborative filtering (i) improved recommendation accuracy (ii) reduced user-item rating data sparsity (iii) increased novelty rate of recommendations and (iv) improved scalability of the recommendation system.

The popularity of online retail is followed by decreasing transactions at shopping centres. Leisure and companionship trips to restaurants and cafés are replacing the frequency of intra-urban shopping trips. Several studies demonstrated a notable trend in urban commercial areas, wherein functionality has shifted from shopping centres to primarily focused on restaurants and cafes. Leisure and companionship places in the urban south have greater diversity than formal restaurants and cafés. This article employs a comprehensive framework to examine the categorization of restaurants and cafés in the urban south, referred to as food services. This study aims to investigate the spatial pattern of food service in Surabaya and ascertain whether there is a concentration of all food service variants around existing shopping centres. This research employs the POI of food service units gathered through web scraping from Google Maps. Applying the k-means cluster analysis demonstrates that the spatial pattern of food services is categorized into several distinct clusters. This article discloses five types of urban spaces characterized by varying compositions of food service variants within them. These spaces include the city centre, sub-city centre, areas along main roads, residential neighbourhoods, and peri-urban areas.

Life in the modern century is heavily reliant on an enormous amount of electricity consumption as technology has become the most integral part of daily life. In this context, smart grid systems play a pivotal role to maintain the uninterrupted power supply which needs to be monitored in a timely fashion to keep track of the electric consumers’ usage pattern. The smart meter is the one of smart applications of the smart grid that collects huge amounts of consumer load data on a daily basis which has become a focus for various researchers and analyzers to study load characterization. In this paper, an approach has been proposed to recognize the energy consumption patterns among diverse types of consumers ranging from residential to industrial levels. This approach is worth considering not only for load pattern recognition but also for involving customers in different events such as demand response or peak shaving. In such a way, this analytical mechanism certainly assists in reducing power wastage and saving costs. The proposed methodology is based on a two-fold clustering algorithm with the use of state-of-the-art technology, machine learning. The primary goal is to classify electric customers' data collected from smart meters. Then, analyzing the classified results with an aim to predict power consumption patterns for the customers in the future and making the right energy policy that will benefit both the grid operator and consumers as well.

The key to ensuring the sustainability of transportation operations on the roads is to manage traffic flows homogeneously. By homogenizing the behavior of various drivers, traffic operation can be optimized, and traffic safety can be improved. However, the advent of autonomous vehicles is expected to have a major impact on the homogeneity of sustainable transportation operations. In this study, a method of driving in harmony with surrounding vehicles was studied to minimize the impact of autonomous vehicles on current traffic operation. In particular, in this study, a methodology was developed to optimize the driving behavior of autonomous vehicles by analyzing the driving behavior of following vehicles using spectrum analysis. Specifically, a method for calculating three indicators that can analyze the driving behavior of a following vehicle, such as reaction time, stimulus adaptation index, and collision risk avoidance index, was proposed. These indices produced consistent and robust results for all traffic conditions. If these indicators are used, it is expected that sustainable traffic management will be possible even when autonomous vehicles and human drivers are mixed on the road.

Brugada Syndrome is a cardiac channelopathy closely related to lethal arrhythmias and sudden death in people without underlying structural pathology. The diagnosis is usually assumed with electrocardiographic patterns strictly limited to the right precordial leads, V1 or V2; but this is not so at all. In our article, we describe the clinical case of a patient with a novel and different electrocardiographic presentation: the typical diagnostic pattern was presented in a lower lead of the electrocardiogram, and next to it, another pattern was presented in a contiguous lead. In addition, we propose the possible association of a structural pathology (non-compaction cardiomyopathy) with Brugada Syndrome, since both share a possible common genetic origin in the SCN5A gene.

Food security is a matter of global interest, as the provision of food resources is the primary determinant of human existence. Food is one of the basic needs, ensuring the survival of the species. The trend of globalization and development of the global economy has shifted the responsible local consumption patterns to an increased homogeneity of diets, food products being disconnected from their source. This disconnection led to two major results: (1) increased global consumption, with seasonal foods now available throughout the year, and a decrease in food prices on the global market, and (2) increased uncertainty in the supply chain, susceptible to disruptions, as was the case during the Covid-19 pandemic. The present study, based on the research and analysis of third-party data on food security, sustainable diets, consumption patterns and recommended actions to change the current unsustainable consumer behaviour towards a careful approach to food, environment and personal health, aims to identify consumption patterns that have the potential to increase the sustainability of the food system and a positive correlation with food security. Adopting sustainable dietary patters, based on short supply chains and mindful consumption, has great potential in restoring food security and resilience to adversity.