Joint clock recovery and feed-forward equalization for PAM4 transmission.

With the rapid development of cloud services, data-center applications and the Internet of Things, short-reach communications have attracted much more attention in recent years. 4-level pulse amplitude modulation (PAM4) is a promising modulation format to provide both high data rate and relatively low cost for short-reach optical interconnects. In this paper, a joint clock recovery and feed-forward equalization algorithm (CR-FFE) is proposed to simultaneously eliminate the inter-symbol interference (ISI) and track large sampling clock offset (SCO) in PAM4 transmission. The algorithm estimates timing error according to the difference between two tap coefficients of fractionally spaced equalizers, thus solving the problem of incompatible prerequisites between clock recovery and channel equalization. A 10GHz directly modulated laser (DML) based 50-Gbit/s PAM4 transmission experiment is implemented to investigate the performance of the proposed algorithm. Experimental results show that the proposed CR-FFE algorithm can resist SCO up to 1000 ppm after 40 km standard single-mode fiber (SSMF) transmission under the 2x10-2 SD-FEC BER threshold, which is dramatically improved comparing with that of 20 ppm in traditional CR cascaded by FFE algorithm.

Adsorption and Oxidation of As(III) on Iron (Hydro)Oxides.

Iron (hydro)oxides, including poorly crystalline ferrihydrite and the more crystalline forms, hematite and magnetite, play an important role in the biogeochemical cycling of arsenic in aquatic environments. In this study, adsorption and oxidation experiments for As(III) were performed on ferrihydrite, hematite, and magnetite, respectively. The results showed that the three iron (hydro)oxides acted as a catalyst for the oxidation of As(III) in the presence of oxygen. The variation in the oxidation states of As(III) on iron (hydro)oxides were confirmed by X-ray Absorption Near-Edge Structure (XANES) spectra. Adsorption kinetics of As(III) followed a pseudo-second-order equation in the three iron (hydro)oxides systems. Oxidation of As(III) on the three iron (hydro)oxides was observed by the determination of total As(V) concentration. The pseudo-first-order equations satisfactorily described the oxidation kinetics data. The oxidation rate constants in the different iron (hydro)oxide systems followed the order: hematite > ferrihydrite > magnetite, that is, 0.0111, 0.0021, and 0.0009 h-1, respectively.

Study on 100-Gb/s reconfigurable all-optical logic gates using a single semiconductor optical amplifier.

We experimentally demonstrated all-optical NOR, OR and AND logic gates at 100 Gb/s with a single semiconductor optical amplifier (SOA) assisted by optical filtering. The logics can be conveniently reconfigured by deploying or not continuous wave (CW) light at the input of the SOA and adjusting the tunable optical band pass filter (OBPF) at SOA output. Correct logic functions and high quality of the output signals can be achieved as proved by clear eye opening and bit error rate (BER) measurement. Influences of optical filter parameters and the SOA device length on the logical performance are experimentally investigated.

Progress of photocatalytic oxidation-adsorption synergistic removal of organic arsenic in water.

Photocatalytic oxidation-adsorption synergistic treatment of organic arsenic pollutants is a promising wastewater treatment technology, which not only degrades organic arsenic pollutants by photocatalytic degradation but also removes the generated inorganic arsenic by adsorption. This paper compares the results of photocatalytic oxidation-adsorption co-treatment of organic arsenic pollutants such as monomethylarsonic acid, dimethylarsinic acid, phenylarsonic acid, p-arsanilic acid, and 3-nitro-4-hydroxyphenylarsonic acid on titanium dioxide, goethite, zinc oxide, and copper oxide. It examines the influence of the morphology of organic arsenic molecules, pH, coexisting ions, and the role of natural organic matter. The photocatalytic oxidation-adsorption co-treatment mechanism is investigated, comparing the hydroxyl radical oxidation mechanism, the hydroxyl radical and superoxide anion radical cooxidation mechanism, and the hydroxyl radical and hole cooxidation mechanism. Finally, the future prospects of metal oxide photocatalytic materials and the development of robust and efficient technologies for removing organic arsenic are envisioned.

Causality between six psychiatric disorders and digestive tract cancers risk: a two-sample Mendelian randomization study.

Associations between psychiatric disorders and digestive tract cancers have been proposed. However, the causal link between these factors remains unclear. This study pioneers Mendelian randomization (MR) analysis to explore the genetic link between psychiatric disorders and digestive tract cancers risk. We analysed data on six psychiatric disorders [schizophrenia, bipolar disorder, major depressive disorder (MDD), attention deficit hyperactivity disorder, autism spectrum disorder, and panic disorder (PD)] and digestive tract cancers [esophagus cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)] from genome-wide association studies databases. Using instrumental variables identified from significant single nucleotide polymorphism associations, we employed the inverse variance weighted (IVW) method alongside the weighted median (WM) method and MR-Egger regression. The results revealed no causal link between psychiatric disorders and the risk of EC or GC. Psychiatric disorders were not identified as risk factors for CRC. Notably, PD demonstrated a lower CRC risk (OR = 0.79, 95% CI 0.66-0.93, P = 0.01). This MR analysis underscores the lack of a causal association between psychiatric disorders and digestive tract cancers risk while suggesting a potential protective effect of PD against CRC.

Multimodal Deep-Learning Framework for Accurate Prediction of Wettability Evolution of Laser-Textured Surfaces.

The lengthy process through which laser-textured surfaces transform from hydrophilic to hydrophobic severely restricts their practical applications. Accurately predicting the wettability evolution curve is crucial; however, developing a reliable prediction model remains challenging. Herein, a data-driven multimodal deep-learning framework was developed, in which multimodal data of micro/nanostructure morphology images, composition distribution images, and time information are effectively coupled and fed into a convolutional neural network (CNN). Rich data input and in-depth data mining make the framework more robust, achieving accurate prediction of the wettability evolution curves of various typical micro/nanostructures. Additionally, accurate prediction of input images with varying magnifications and untrained laser-textured surfaces demonstrates the generalizability of the multimodal CNN framework. The visualization results of the convolution layer confirmed the rationality of the information learned by the model. Additionally, the proposed multimodal CNN framework was successfully utilized to investigate the optimization process. Further, a laser-textured surface with a shorter evolution period and a larger final contact angle was realized. The proposed multimodal CNN framework offers an efficient and cost-effective method for predicting the wettability evolution curves and exploring the optimization processes, enhancing the application potential of laser micro/nanofabrication of superhydrophobic surfaces.

Application of infrared spectroscopy and its theoretical simulation to arsenic adsorption processes.

Accurate detection and analysis of arsenic pollutants are an important means to enhance the ability to manage arsenic pollution. Infrared (IR) spectroscopy technology has the advantages of fast analysis speed, high resolution, and high sensitivity and can be monitored by real-time in situ analysis. This paper reviews the application of IR spectroscopy in the qualitative and quantitative analysis of inorganic and organic arsenic acid adsorbed by major minerals such as ferrihydrite (FH), hematite, goethite, and titanium dioxide. The IR spectroscopy technique cannot only identify different arsenic contaminants but also obtain the content and adsorption rate of arsenic contaminants in the solid phase. The reaction equilibrium constants and the degree of reaction conversion can be determined by constructing adsorption isotherms or combining them with modeling techniques. Theoretical calculations of IR spectra of mineral adsorbed arsenic pollutant systems based on density functional theory (DFT) and analysis and comparison of the measured and theoretically calculated characteristic peaks of IR spectra can reveal the microscopic mechanism and surface chemical morphology of the arsenic adsorption process. This paper systematically summarizes the qualitative and quantitative studies and theoretical calculations of IR spectroscopy in inorganic and organic arsenic pollutant adsorption systems, which provides new insights for accurate detection and analysis of arsenic pollutants and arsenic pollution control. PRACTITIONER POINTS: This paper reviews the application of infrared spectroscopy in the qualitative and quantitative analyses of inorganic and organic arsenic acid adsorbed by major minerals such as ferrihydrite, hematite, goethite, and titanium dioxide, which can help identify and evaluate the type and concentration of arsenic pollutants in water bodies. In this paper, theoretical calculations of infrared spectra of mineral adsorbed arsenic pollutant systems based on density functional theory reveal the adsorption mechanism of arsenic pollutants in water at the solid-liquid interface and help to develop targeted arsenic pollution control technologies. This paper provides a new and reliable analytical detection technique for the study of arsenic contaminants in water bodies.

Preparation of magnetic composites and their dimethyl arsonic acid adsorption performances.

Dimethyl arsonic acid, the most common organic arsenic pollutant, is widely present in the environment and seriously threatens the safety of drinking water. Syntheses of magnetite, magnetic bentonite, and magnetic ferrihydrite via hydrothermal methods, and the magnetic composites were examined using XRD, BET, VSM, and SEM. SEM images revealed that many monodispersible pellets were attached to the surface of magnetic bentonite. The magnetic ferrihydrite contained abundant pores and had a rich pore structure, which expanded the specific surface area of the original magnetite. The specific surface areas of the magnetic bentonite and magnetic ferrihydrite were 65.17 and 220.30 m2·g-1, respectively. The adsorption kinetics and adsorption isotherms of dimethyl arsonic acid on magnetic composites were studied. The adsorption of dimethyl arsonic acid on the magnetic composites conformed to the pseudo-second-order model and Freundlich isothermal adsorption model. By comparing the isotherms of the adsorption of dimethyl arsonic acid by the magnetic composites at pH values of 3, 7, and 11, respectively, it was found that the adsorption of dimethyl arsonic acid was the greatest at neutral pH of 7. The adsorption mechanism was analyzed via zeta potential determination, Fourier transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS). The zeta potential results revealed that magnetic bentonite electrostatic activity occurred with dimethyl arsonic acid, and the magnetic ferrihydrite indicated a coordination complex with dimethyl arsonic acid. The XPS results revealed that the Fe-O bonds on the surfaces of the magnetic ferrihydrite had coordination complexation effects on the As-O of the dimethyl arsonic acid.

Design of a Femtosecond Laser Percussion Drilling Process for Ni-Based Superalloys Based on Machine Learning and the Genetic Algorithm.

Femtosecond laser drilling is extensively used to create film-cooling holes in aero-engine turbine blade processing. Investigating and exploring the impact of laser processing parameters on achieving high-quality holes is crucial. The traditional trial-and-error approach, which relies on experiments, is time-consuming and has limited optimization capabilities for drilling holes. To address this issue, this paper proposes a process design method using machine learning and a genetic algorithm. A dataset of percussion drilling using a femtosecond laser was primarily established to train the models. An optimal method for building a prediction model was determined by comparing and analyzing different machine learning algorithms. Subsequently, the Gaussian support vector regression model and genetic algorithm were combined to optimize the taper and material removal rate within and outside the original data ranges. Ultimately, comprehensive optimization of drilling quality and efficiency was achieved relative to the original data. The proposed framework in this study offers a highly efficient and cost-effective solution for optimizing the femtosecond laser percussion drilling process.

Application of surface-enhanced Raman scattering to qualitative and quantitative analysis of arsenic species.

Given the toxicity of arsenic, there is an urgent need for the development of efficient and reliable detection systems. Raman spectroscopy, a powerful tool for material characterization and analysis, can be used to explore the properties of a wide range of different materials. Surface-enhanced Raman spectroscopy (SERS) can detect low concentrations of chemicals. This review focuses on the progress of qualitative and quantitative studies of the adsorption processes of inorganic arsenic and organic arsenic in aqueous media using Raman spectroscopy in recent years and discusses the application of Raman spectroscopy theory simulations to arsenic adsorption processes. Sliver nanoparticles are generally used as the SERS substrate to detect arsenic. Inorganic arsenic is chemisorbed onto the silver surface by forming As-O-Ag bonds, and the Raman shift difference in the As-O stretching (∼60 cm-1) between As(V) and As(III) allows SERS to detect and distinguish between As(V) and As(III) in groundwater samples. For organic arsenicals, specific compounds can be identified based on spectral differences in the vibration modes of the chemical bonds. Under the same laser excitation, the intensity of the Raman spectra for different arsenic concentrations is linearly related to the concentration, thus allowing quantitative analysis of arsenic. Molecular modeling of adsorbed analytes via density functional theory calculation (DFT) can predict the Raman shifts of analytes in different laser wavelengths.

Anisotropic and Lightweight Carbon/Graphene Composite Aerogels for Efficient Thermal Insulation and Electromagnetic Interference Shielding.

High-performance and lightweight carbon aerogels (CAs) have attracted considerable attention in various fields such as electrochemistry, catalysis, adsorption, energy storage, and so on. However, finding an environmentally friendly and efficient preparation method and achieving a controllable performance of CAs are still a challenge. Herein, a series of anisotropic carbon/graphene composite aerogels were synthesized by unidirectional freezing of polyamic acid ammonium salt/graphene oxide (PAS/GO) suspension followed by lyophilization, thermal imidization, and carbonization. The prepared aerogels presented a tubular pore structure oriented along the freezing direction. The GO dispersed in the polymer matrix reinforced the skeleton of aerogels, which significantly inhibited the volume shrinkage during the preparation process, thus giving low densities of 0.074-0.185 g cm-3. In addition, the oriented pore structure endowed the composite aerogels with obviously anisotropic heat insulation performance. The radial thermal conductivity was as low as 0.038 W m-1 K-1 at the density of 0.074 g cm-3. When the initial content of GO rose to 20 phr, the resultant aerogels exhibited a high electrical conductivity of about 0.77 S cm-1 in the radial direction and the electromagnetic interference shielding effectiveness (EMI SE) reached 54.6 dB at the same time. Therefore, this study provided a facile and environmentally friendly method to prepare lightweight and anisotropic carbon aerogels.

Fractionation of heavy metals in shallow marine sediments from Jinzhou Bay, China.

This work investigated the distribution and speciation of Cd, Cu, Pb, Fe and Mn in the shallow sediments of Jinzhou Bay, Northeast China, which has been heavily contaminated by nonferrous smelting activities. The concentrations of Cd, Cu and Pb in sediments were found to be 100, 13 and 7 times, respectively, being higher than the national guideline (GB 18668-2002). Sequential extraction test showed that 39%-61% of Cd were exchangeable fractions, indicating that Cd in the sediments posed a high risk to local environments. While Cu and Pb were at moderate risk levels: According to the relationships between percentage of metal speciation and total metal concentration, it was concluded that the distributions of Cd, Cu and Pb in some geochemical fractions were dynamic in the process of pollutants migration and the stability of metals in sediments of Jinzhou Bay decreased in the order of Pb > Cu > Cd.

Effect of sulfide on As(III) and As(V) sequestration by ferrihydrite.

The sulfide-induced change in arsenic speciation is often coupled to iron geochemical processes, including redox reaction, adsorption/desorption and precipitation/dissolution. Knowledge about how sulfide influenced the coupled geochemistry of iron and arsenic was not explored well up to now. In this work, retention and mobilization of As(III) and As(V) on ferrihydrite in sulfide-rich environment was studied. The initial oxidation states of arsenic and the contact order of sulfide notably influenced arsenic sequestration on ferrihydrite. For As(III) systems, pre-sulfidation of As(III) decreased arsenic sequestration mostly. The arsenic adsorption capacity decreased about 50% in comparison with the system without sulfide addition. For As(V) systems, pre-sulfidation of ferrihydrite decreased 30% sequestration of arsenic on ferrihydrite. Reduction of ferrihydrite by sulfide in As(V) system was higher than that in As(III) system. Geochemical modeling calculations identified formation of thioarsenite in the pre-sulfidation of As(III) system. Formation of arsenic thioanions enhanced As solubility in the pre-sulfidation of As(III) system. The high concentration of sulfide and Fe(II) in pre-sulfidation of ferrihydrite system contributed to saturation of FeS. This supplied new solid phase to immobilize soluble arsenic in aqueous phase. X-ray absorption near edge spectroscopy (XANES) of sulfur K-edge, arsenic K-edge and iron L-edge analysis gave the consistent evidence for the sulfidation reaction of arsenic and ferrihydrite under specific geochemical settings.

Adsorption and heterogeneous oxidation of As(III) on ferrihydrite.

Redox transformation of arsenic strongly influences its fate and transport in the environment. It is of interest to investigate heterogeneous oxidation of As(III) on the surface of major metal oxide in sediments. Whether As(III) can be oxidized on ferrihydrite and the role ferrihydrite plays as catalyst or oxidant are inconsistent in previous researches. In this work, oxidation of As(III) on ferrihydrite was studied by analysis of dissolved and adsorbed As(III) and As(V) quantitatively and qualitatively. X-ray absorption near edge spectroscopy (XANES) and pH(pznpc) (point of zero net proton charge) of ferrihydrite with adsorbed As(III) showed clear evidence for partial oxidation on ferrihydrite. Oxidation of As(III) occurred when it was brought to contact with ferrihydrite at high Fe/As molar ratio (i.e. 50, 200). The concentration of As(V) in solid phase increased gradually while adsorbed As(III) concentration dropped. Fe(II) was not detectable during the oxidation of As(III). These results showed that ferrihydrite had the catalytic effect on oxidation of As(III). Only a fraction of As(III) was oxidized even when the system was exposed to air. The effects of ferrihydrite aging, media pH, coexistence of ions on As(III) oxidation were also investigated. The results suggest that catalytic oxidation of As(III) on ferrihydrite may play a role in geochemical cycling of arsenic in environment.

Transformation of arsenic in offshore sediment under the impact of anaerobic microbial activities.

Sediment bound arsenic usually undergoes phase transformation processes when it is transported and buried in deeper settings. This work investigated anaerobic microbial mediated speciation change of the arsenic in offshore sediment and monitored the transformation process of oxyhydroxide associated arsenate to sulfide associated forms. The fate of arsenic and possible pathways of transformation were discussed based on quantitative analysis of aqueous and solid arsenic and iron, and qualitative characterization using X-ray absorption near edge spectroscopy (XANES). Arsenic was released and reduced upon development of anoxic conditions but was resequestered by authigenic minerals later. Most of the arsenic in the sediment was converted to orpiment-like material. Sulfide may have played double roles in arsenic redistribution process, i.e. promoting arsenic release from host oxyhydroxides in early stage and removal of arsenite from solution in the form of arsenic sulfide in later stage. The findings have implications about the pathways of arsenic transformation when arsenate is transported and buried below redox boundaries in offshore sediment.