Search

With the fast growth of 5G services and Internet of Things (IoT) applications, there is a critical need for creative solutions to handle the increasing backbone network traffic. This research presents a new method for machine-learning-based wavelength-routing networks with interactive transmission to improve optical connection smoothness in future data centers. Our method features a versatile transmitter capable of broadcasting at multiple coding rates (N), dynamically adjusting to connections based on expected Bit Error Rate (BER) levels. By employing a neural network (NN)-based classifier to pre-process data and classify BER, we demonstrate significant improvements in classification accuracy across various values of N and switching connections. This approach facilitates the development of adaptive and efficient optical data center networking, ultimately aiming to boost network performance and reliability.

Egypt’s agricultural sector plays a critical role in the country’s economy, with wheat cultivation being vital for ensuring food security. However, the challenges faced by wheat farming in Egypt, such as climate change, water scarcity, and pest infestations, contribute to yield fluctuations, highlighting the need for accurate and timely predictions of wheat productivity. To address this need, time series analysis is employed, which involves analyzing data collected at regular intervals over a specific time frame. Time series data can encompass multiple variables recorded simultaneously at each interval, known as multivariate time series data. Traditional statistical methods have been commonly used for time series analysis. However, these methods have limitations when dealing with nonlinear and complex data patterns, especially in agricultural data exhibiting spatiotemporal characteristics. Deep learning techniques have emerged as a promising solution to address these limitations. In this paper, we have developed the multivariate multi-head attention temporal convolutional networks (MATCN) model specifically to handle the spatiotemporal nature of multivariate time series data in the context of wheat crop productivity prediction in Egypt. The experimental results revealed that our proposed MATCN model exhibited the most effective prediction performance when compared to other state-of-the-art models, achieving a mean absolute percentage error (MAPE) values ranging from 0.091 to 5.5%.

With the introduction of ultrahigh efficiency columns and fast separations, the need to eliminate peak deformation contributed by the instrument must be effectively solved. Herein, we develop a robust framework to automate deconvolution and minimize its artifacts, such as negative dips, wild noise oscillations, and ringing, by combining regularized deconvolution and Perona–Malik (PM) anisotropic diffusion methods. A asymmetric generalized normal (AGN) function is proposed to model the instrumental response for the first time. With no-column data at various flow rates, the interior point optimization algorithm extracts the parameters describing instrumental distortion. The column-only chromatogram was reconstructed using the Tikhonov regularization technique with minimal instrumental distortion. For illustration, four different chromatography systems are used in fast chiral and achiral separations with 2.1 and 4.6 mm i.d. columns. Ordinary HPLC data can approach highly optimized UHPLC data. Similarly, in fast HPLC-circular dichroism (CD) detection, 8000 plates were gained for a fast chiral separation. Moment analysis of deconvolved peaks confirms correction of the center of mass, variance, skew, and kurtosis. This approach can be easily integrated and used with virtually any separation and detection system to provide enhanced analytical data.

Porosities exist as pores of different sizes within a structure to fabricate lightweight materials and the sintering process. The porous structure gives a lower loading capacity than the perfect design. Crack propagation is also a complicated behavior in this structure. The hybrid phase-field approach is suitable to provide an effective computational tool to model the crack propagation of functionally graded materials with porosity effects. We show the influence of porosity on both the critical force and crack path of the FGM structure. In the framework of isogeometric analysis (IGA), a local refinement multi-patch algorithm based on the Virtual Uncommon-Knot-Inserted Master–Slave (VUKIMS) technique allows us to reduce the computational cost of the phase-field model significantly. The study revealed that cubic NURBS elements with the effective element size of half length-scale parameter could be used to achieve the desired accuracy while maintaining a reasonable computational cost.

The aim of this work is to develop an electrothermal model capable of predicting the FinFET operating temperature in different drain and gate biases with different gate lengths. A new effective electron mobility that depends on mobility degradation due to phonon scattering, surface roughness, and to Colombian interaction is used to enhance the drift-diffusion (D-D) model. To better investigate the electrical characteristics, heat conduction equation is coupled with the D-D model. To achieve high evidence to the proposed model, the simulation of ID-VG and ID-VD is compared with experimental data and Monte Carlo (MC) simulation, and a good concordance is observed. The output characteristics degradation due to device temperature is analyzed. We demonstrated that a drain current of 1 mA/_m is obtained when the operating temperature is around 360 K for a 20-nm FinFET. The effect of FinFET biases on power dissipation and device temperature along the channel region and in the drain side channel region interface is investigated for 10- and 20-nm FinFET gate lengths. We found that: 1) the power dissipation is four times greater when the gate length decreases from 20 to 10 nm and 2) the critical temperature, which is responsible to vanish the drain current, is from 380 to 460 K for Lg = 20 and 10 nm, respectively. This work addresses a key reliability constraint for CMOS-based FinFET circuit designers while designing tuned gate and drain biases circuit.

A majority of enantiomeric separations show some degree of peak asymmetry, which is detrimental to quantitative and semiquantitative chiral analysis. This paper presents a simple and rapid peak symmetrization algorithm for the correction or reduction of peak tailing or fronting in exponentially modified Gaussians. Raw chromatographic data can be symmetrized by adding a correct fraction of the first derivative to the chromatogram. The area remains invariant since the area under the first derivative is zero for a pure Gaussian and numerically close to zero for asymmetric peaks. A method of easily extracting the distortion parameter is provided, as well as insight into how pre-smoothing the data with the “perfect smoother” algorithm can suppress high frequencies effectively. The central difference method is also used to compute the first derivative, reducing root-mean-square noise by up to 28% compared to the standard forward difference method. A survey of 40 chiral separations is presented, demonstrating the range of asymmetry observed in chiral separations. Examples of symmetrization of the peaks from enantiomers in comparable and disproportionate concentrations are also provided. Artifacts of deconvolution are discussed, along with methods to mitigate such artifacts.

The concept of coupling gas chromatography with molecular rotational resonance spectroscopy (GC-MRR) was introduced in 2020, combining the separation capabilities of GC with the unparalleled specificity of MRR. In this study, we address the challenge of the high data throughput of MRR spectrometers, as GC-MRR spectrometers can generate thousands to millions of data points per second. In the previous GC-MRR studies, a free induction decay (FID) measurement was Fourier transformed to generate each point on the chromatogram. Such extensive calculations limit the performance, sensitivity, and speed of GC-MRR. A direct approach is proposed here to extract peak intensity from FID using the Gram–Schmidt vector orthogonalization method. First, analyte-free FIDs are used to construct a basis set representing the instrument’s background noise, and then the remaining FIDs are orthogonalized to this fixed basis set. Each FID yields a single intensity value after Gram–Schmidt orthogonalization. The magnitude of the orthogonalized analyte FID is the signal intensity plotted in the chromatogram. This approach is computationally much faster (up to 10 times) than the conventional Fourier transform algorithm, is at least as sensitive as the FT algorithm, and maintains or improves the chromatographic peak shape. We compare the sensitivity, linearity, and chromatographic peak shapes for the Fourier transform and Gram–Schmidt approaches using both synthetically generated FIDs and instrumental data. This approach would allow the summed peak intensity to be displayed essentially in real-time, following which identified peaks can be further investigated to identify and quantify the species associated with each.

The Guadalquivir bridge is a large-scale twin steel truss bridge located in Spain that opened to traffic in 1929. Since the bridge has come into operation for a long time, structural health monitoring (SHM) is strictly necessary to guarantee safety and avoid serious incidents. This paper proposes a novel approach to model updating for the Guadalquivir bridge based on the vibration measurements combined with a hybrid metaheuristic search algorithm. Cuckoo Search (CS) is an evolutionary algorithm derived from global search techniques to look for the best solution. Nevertheless, CS contains some fundamental defects that may reduce its effectiveness in dealing with optimization issues. A main drawback of CS arises in the low convergence level because CS applies fixed values for parameters when looking for the optimal solution. In addition, CS relies a lot on the quality of original populations and does not have the capability to enhance the quality of the next generations. If the position of the original particles is far from the optimal places, it may be challenging to look for the best solution. To remedy the shortcomings of CS, we propose a hybrid metaheuristic algorithm (HGAICS) employing the advantages of both Genetic Algorithm (GA) and Improved Cuckoo Search (ICS) to solve optimization problems. HGAICS contains two outstanding characteristics as follows: (1) GA is employed to create original particles with the best quality based on the capacity of crossover and mutation operators and (2) those particles are then applied to look for the global best derived from the flexible and global search ability of ICS. This paper also presents the application of wireless triaxial sensors (WTSs) taking the place of classical wired systems (CWSs) to the measurements. The use of WTSs increases dramatically the freedom in setting up experimental measurements. The results show that the performance of the proposed hybrid algorithm not only determines uncertain parameters of the Guadalquivir bridge properly, but also is more accurate than GA, CS, and improved CS (ICS). A MATLAB package of the proposed method (HGAICS) is available via GitHub: https://github.com/HoatranCH/HGAICS.

This paper experimentally investigated the linear and third-order optical nonlinearities of a pure CuO thin film deposited on a soda-lime glass substrate. A single-phase film with 62 nm thickness was prepared using the direct current (DC) sputtering deposition process, the film structure was measured using x-ray diffraction (XRD) and a surface profilometer, while the film’s linear optical properties were measured using a UV-Vis spectrophotometer. The Z-scan technique was used to measure the nonlinear optical properties of a film that had been irradiated with 100 fs laser pulses using different excitation wavelengths at different incident laser powers. The results showed that increasing the excitation wavelength from 740 nm to 840 nm reduces the nonlinear absorption coefficient of the film from −3.5×10^−6 to −2.04×10^−6cm/W, and the nonlinear refractive index n_2 decreases from −4.98×10^−18 to −1.2×10^−18cm^2/W. The optical limiting of the CuO thin film was studied and found to be excitation wavelength dependent with limiting at high incident power.

A series of lithium borate glasses with V2O5were successfully prepared by melt annealing. The glass-ceramics were made by heating the glass to the glass transition temperature (Tg), then heating it to the crystallization temperature (Tc), converting it from a vitreous state to a crystalline state. This study found a link between the glass transition (Tg) and V2O5ratio in the host glass, with Tgrising from 345 °C for base glass to 419 °C for glass containing 2% V2O5. The glass stability of the base sample was higher than that of the V2O5samples. XRD analysis revealed the main crystalline phase in the derived glass-ceramics to be Li2B4O7tetragonal, with crystalline traces of Li2B2O4.16H2O phase. Similarly, crystallite growth on plane (112) decreased from 253 Å (the base) to 239 Å (2% V2O5). Vitreous structure was existed in the glass samples, while spherical particles were found in the derived glass-ceramic materials. The spherical particles began to take on large geometric shapes as the V2O5content increased from 1% to 2%. All glass-ceramic samples have traces of vitreous material. Glass and glass-ceramics with structural units of BO3, BO4, boroxol rings, and B–O–B linkages were also presented. The phonon-energy (Eph) and optical transition (Eg) showed a strong correlation with V2O5content. As V2O5increased between the conduction and valence bands, Ephincreased from 99 to 232 meV and Egdecreased from 3.164 to 2.250 eV.

AbstractChronic cough, defined as cough lasting 8 weeks or longer, is a condition for which there is currently no licensed treatment. Chronic cough affects approximately 16% of Canadian adults between the age of 45 and 85 years and is often associated with physical, social, and psychological impairments. The purpose of this state-of-the-art review is to highlight the investigations, management, current and future treatment options and mechanistic concepts underlying chronic cough. Assessments of chronic cough should include a detailed history and examination to identify potential causes and triggers. Conditions associated with chronic cough include ACE inhibitor use, smoking, asthma, non-asthmatic eosinophilic bronchitis, gastroesophageal reflux disease, and upper airways cough syndrome. The impact and severity of chronic cough can be assessed in clinic using subjective questionnaires. Persistent cough despite optimal treatment of the underlying condition is called refractory chronic cough (RCC). Persistent cough for which no underlying cause is found, is labeled unexplained chronic cough (UCC). If treatment of underlying disease is unsuccessful at controlling cough despite adequate duration and adherence to the treatment, neuromodulator treatments such as speech and language therapy and/or low dose opioid, gabapentin, and pregabalin may be therapeutic options. There is no licensed treatment for RCC/UCC but a new class of medication targeting the purinergic P2X3 receptor is currently under consideration for regulatory approval with other P2X3 antagonists in phase 2 and phase 3 clinical development. Approval of this new treatment class may represent a hopeful advancement for patients suffering with chronic cough.RÉSUMÉLa toux chronique, définie comme une toux qui dure huit semaines ou plus, est une affection pour laquelle il n’existe actuellement aucun traitement autorisé. La toux chronique affecte environ 16 % des adultes canadiens âgés de 45 à 85 ans et est souvent associée à des déficiences physiques, sociales et psychologiques. Le but de cette revue de l’état de l’art est de mettre en évidence les investigations, la prise en charge, les options de traitement actuelles et futures et les concepts mécanistes sous-jacents à la toux chronique. Les évaluations de la toux chronique devraient inclure un historique détaillé et un examen pour déterminer les causes et les déclencheurs potentiels. Les affections associées à la toux chronique comprennent l’utilisation d’inhibiteurs de l’ECA, le tabagisme, l’asthme, la bronchite éosinophile non asthmatique, le reflux gastro-oesophagien et le syndrome de toux des voies respiratoires supérieures. L’impact et la gravité de la toux chronique peuvent être évalués en clinique à l’aide de questionnaires subjectifs. Une toux persistante malgré un traitement optimal de l’affection sous-jacente est appelée toux chronique réfractaire (TCR). La toux persistante pour laquelle aucune cause sous-jacente n’est trouvée, est appelée toux chronique inexpliquée (TCI). Si le traitement de la maladie sous-jacente ne parvient pas à maîtriser la toux malgré une durée et une adhésion adéquates au traitement, les traitements par neuromodulateurs tels que l’orthophonie et/ou les opioïdes à faible dose, la gabapentine et la prégabaline peuvent être des options thérapeutiques. Il n’y a pas de traitement autorisé pour la TCR/TCI, mais une nouvelle classe de médicaments ciblant le récepteur purinergique P2X3 est actuellement à l’étude pour approbation réglementaire, avec d’autres antagonistes P2X3 en phase 2 et 3 de développement clinique. L’approbation de cette nouvelle classe de traitement peut représenter une avancée prometteuse pour les patients souffrant de toux chronique.

The electrical contact nature between metal and semiconductor plays a key role in the devices operating and performance. An investigation of the contact ohmicity of different metals with p-NiO and n-ZnO semiconducting material is addressed in the present work. The investigated metals are the commonly used ones: Au, Cu, Mo, Ti, Ag, and indium tin oxide (ITO). All the studied metals lead to an ohmic contact with NiO and ZnO semiconductors expected in the case of ITO on NiO where the contact was rectifying. The formation of ohmic contact is explained in terms of the difference between the metal work function and the semiconductors affinity in one hand and on the other hand, in terms of highly doped interface formation due to the oxygen vacancies appearance, reducing then the depletion layer width which favors the carrier transport through tunneling effect. High sheet resistance is measured when using Ag metal as a contact on both ZnO and NiO, due to the diffusion of the latter in the film bulk and to the formation of Ag cluster. Mo, as well, leads to higher sheet resistance when used on NiO due to the metal diffusion. However, due to the conduction band gap offset at the interface ITO/NiO and ITO /ZnO, ITO leads to a Schottky contact with NiO and ohmic one with ZnO.

Advances in computer-aided translation technology have made tremendous progress in accuracy in the past few years. Chemical Abstracts Service of the American Chemical Society summarizes scientific works from more than 50 languages and allows the users to search papers in nine selected languages. Currently, only the abstracts are rendered into English by human experts or by machine translation because full text translation of millions of articles is beyond the human capacity today. An English translation of a research paper, scientific book, or patent is often required for research, data mining, and for historical purposes from various foreign languages. Many fundamental papers in chemistry, quantum chemistry, physics, and mathematics contain a significant number of chemical or mathematical equations. One of the major known problems in machine translation of such symbolically dense texts is incorrect or meaningless output. This article describes how to optimize the existing machine translation tools to read foreign language papers embedded with chemical/mathematical equations. German and French languages have been selected for illustrative purposes for English translation. Direct upload of text with extensive symbolism is possible with certain services, but this also occasionally produces erroneous rendition into English. A facile solution to the associated problems with embedded equations and mathematical formulas is replacing the equations and notations with “dummy” variables. The placeholder or dummy symbols can be removed after translation, and the original equations are substituted again. This approach, which can be automated in future, relies on the idea that chemical formulas and mathematical notations are universal. Following the guidelines in the article, excellent translations can be produced from a text having interspersed equations and chemical symbols.

A new series of co-sputtered Cu1-xTixO films and diodes have been scrutinized. The Cu1-xTixO films are grown onto quartz and Si substrates via a co-sputtering approach. The X-ray analysis revealed that the as-sputtered Cu1-xTixO films show (1¯11) preferential orientation. The grain size depends on the amount of Ti-ions doped into the CuO films. The surface morphology showed that the Ti-ions govern the surface roughness of the CuO films. The sputtered films showed high transmittance reaches 87% and low reflectance around 8%. The optical bandgap decreases from 1.23 ​eV to 1.03 ​eV as a result of the incorporation of Ti-ions in the Cu-sites. The ideality factor, barrier height, and the series resistance of the constructed Ag/Cu1-xTixO/n-Si diodes are determined using thermionic emission and Norde models. The optoelectronic properties of Ag/Cu0.99Ti0.01O/n-Si photodiode were emphasized. This photodiode showed high photosensitivity with fast photo-response and high reproducibility and stability.

The Generative Pre-Trained Transformer known as ChatGPT-4 has undergone extensive pretraining on a diverse data set, enabling it to generate coherent and contextually relevant text based on the input it receives. This capability allows it to perform tasks from answering questions and has attracted significant interest in material sciences, synthetic chemistry, and drug discovery. In this work, we posed four advanced task-specific problems to ChatGPT, which were recently published in leading journals for topics in analytical chemistry, spectroscopy, bioimage super-resolution, and electrochemistry. ChatGPT-4 successfully implemented the four ideas after assigning the “persona” to the AI and posing targeted questions. We show two cases where “unguided” ChatGPT could complete the assignments with minimal human direction. The construction of a microwave spectrum from a free induction curve and super-resolution of bioimages was accomplished using this approach. Two other specific tasks, correcting a complex baseline with morphological operations of set theory and estimating the diffusion current, required additional input, e.g., equations and specific directions from the user. In each case, the MATLAB code was eventually generated by ChatGPT-4 even when the original authors did not provide any code themselves. We show that a validation test must be implemented to detect and correct mistakes made by ChatGPT-4, followed by feedback correction. These approaches will pave the way for open and transparent science and eliminate the black boxes in measurement science when it comes to advanced data processing.

•Ethylene-insensitive3/ethylene-insensitive3-like (EIN3/EILs) proteins in rice exhibit three clads in a Maximum Likelihood (ML) tree.•The gene structures and motif composition of EIN3/EILs genes suggest potential stress-mitigation functions.•OsEIN3/EILs genes are responsive to exogenous abscisic acid and jasmonic acid treatment, highlighting their potential role in growth mediation and abiotic stress tolerance•OsEIN3/EILs genes are highly responsive to drought and salt stresses

More than 40 cosolvents have been used with carbon dioxide to alter its solvation strength. Among the most interesting systems is the subcritical/supercritical CO2/alkanol eluents. Using small amounts of water in CO2/MeOH is known to be beneficial in chiral subcritical/supercritical chromatography. However, the ramifications of introducing water as a cosolvent component is not entirely understood. In this work, we demonstrate important aspects of the CO2/MeOH/H2O system on nine chiral stationary phases with very different surface chemistries, encompassing derivatized polysaccharides, macrocyclic glycopeptides, iso-butylmercaptoquinine, isopropyl macrocyclic oligosaccharides, and π-electron acceptor/π-electron donor phases. A hydrophilicity scale has been shown to be useful in predicting if a given chiral column chemistry would show a significant enhancement in separation efficiency in the presence of water in the CO2/MeOH system. We demonstrate up to 8-fold enhancements in plate counts of chiral separations with a concomitant decrease in retention times, as predicted by the qualitative test. The same chiral analysis can now be completed in almost a third of the time with the addition of small amounts of water, thereby decreasing organic solvent consumption by a considerable amount. Hydrophobic stationary phases show a minimal increase in efficiency and decrease in analysis times and optimized separations show much larger reduced plate heights, compared to more hydrophilic stationary phases. Furthermore, the presence of water can alter the nature of the adsorption isotherm under nonlinear conditions. Small amounts of water can be used to tune nonlinear tailing peaks into fronting ones, significantly improving preparative enantiomeric separations.

Online multi-attribute reverse auctions (OMARA), which include many non-price attributes, aligns better to practice, and is prevalent in many fields such as project bidding and public sector procurement. In such auctions, the decision makers often face varying degrees of cognitive and environmental uncertainty. This renders the traditional winner (supplier) determination method based on deterministic values impracticable. Hence, from the standpoint of the auctioneer (purchaser), a new integrated decision framework under an uncertain situation is proposed. Firstly, the fuzzy set theory is applied to the winner determination problem in OMARA to recognize the uncertainty in the bidding attribute values. Secondly, the detail description of the winner determination problem in OMARA is provided. Thirdly, the comprehensive weights of the evaluation attributes are obtained by using fuzzy AHP and fuzzy deviation maximizing method together. Lastly, the five fuzzy multi-attribute decision-making methods are combined with simple dominant principle to evaluate the bidding alternatives and determine the winner (supplier). A numerical example is used to demonstrate the process of the proposed integrated decision frame-work, and the comparative analysis illustrates its feasibility and effectiveness.

ABSTRACTFriction-Stir-Welding (FSW) involves many critical process variables that affect the overall quality of the weld produced; consequently, it is difficult to accurately predict the most favourable process parameters to acquire high-quality defect-free welds. Quality of an FSW joint is influenced by several crucial factors including welding process parameters, and many others. Since the new invention of FSW process, investigators have researched the influence of process parameters and pin tool profiles on microstructures and mechanical properties with a view to optimise FSW process, thereby keeping the degradation of the weld strength to a minimum. In this study weld defects in Friction-Stir (FS) welded thick (8.13 mm) aerospace grade aluminium alloy (AA 2219-T87) are correlated with weld process parameters from an assortment of a large matrix of weld schedules. In this investigation, a novel FSW process parameter window was established for the effective joining of aerospace grade aluminium which could successfully distinguish several types of weld schedules with characteristic and intrinsic weld-defects. Using experimental results obtained from various schedules, an empirical force index (Effective Force Index), which is a function of the critical weld process parameters is proposed to identify regions of weld schedules.

Lubricant oils in cars engines are essential components for reducing friction and fuel consumption. The lubrication process can be improved by including effective additives. Carbon nanostructures have been recognized as excellent additives in lubricant oils. Amongst them carbon nanotubes (CNTs) produced from carbon rich fly ash, are found to have excellent tribological properties in the sunflower base oil. In this work, these CNTs along with other micro and nanostructures produced from carbon rich fly ash are tested as lubricant additives in the 150SN base oil. The impregnated oils with these additives are evaluated to reduce the friction between two metallic surfaces using the ball-on-disk tribometer. The obtained results showed that CNTs of fly ash have significantly reduced the frictional coefficient by around 25% at a concentration of 0.1wt%. This result is much better than that of the other fly ash micro and nanostructures produced by sonication and ball milling techniques. It is also compared with that of a commercial multiwall CNTs and is found to be superior. The friction coefficient values are investigated as a function of load and temperature. Moreover, the rheological behavior is also studied for the pure and 0.1wt% CNTs-impregnated oil. No significant changes are observed in the viscosity of the impregnated oil. The present CNTs of carbon rich fly ash have been proved to be effective additives for the 150SN lubricant oil, and might be useful for variety of lubricants.

•Water deficiency is a limiting factor for the growth, productivity and quality of Guinea grass in semi-arid regions.•The study evaluated the application of different sources of nitrogen fertilization on the growth and performance of Guinea grass under water deficiency conditions in a newly reclaimed area.•Nano-nitrogen fertilization was the most effective in improving vegetative, physiological, anatomical, biochemical and quality traits of Guinea grass under water deficiency condition.•Inorganic urea had the second rank after Nano-nitrogen in alleviating water deficiency effects on Guinea grass plant performance.