Search Results (37)

This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a dispersive optical link up to 120 km. DFE is essential for improving signal quality in several communication systems, including WiFi networks, cable modems, and long-term evolution (LTE) systems. Its capacity to mitigate inter-symbol interference (ISI) and rapidly adjust to channel variations renders it a flexible option for high-speed data transfer and wireless communications. Conversely, MLD is utilized in applications that require great precision and dependability, including multi-input–multi-output (MIMO) systems, satellite communications, and radar technology. The ability of MLD to optimize the probability of accurate symbol detection in complex, high-dimensional environments renders it crucial for systems where signal integrity and precision are critical. Lastly, RDE is implemented as an alternative algorithm to the CMA-based equalizer, utilizing the idea of adjusting the amplitude of the received distorted symbol so that its modulus is closer to the ideal value for that symbol. The algorithms are tested using a converged 5G mm-wave analog radio-over-fiber (A-RoF) system at 60 GHz. Their performance is measured regarding error vector magnitude (EVM) values before and after equalization for different optical fiber lengths and modulation formats (QPSK, 16-QAM, 64-QAM, and 128-QAM) and shows a clear performance improvement of the output signal. Moreover, the performance of the proposed algorithms is compared to three commonly used algorithms: the simple least mean square (LMS) algorithm, the constant modulus algorithm (CMA), and the adaptive median filtering (AMF), demonstrating superior results in both QPSK and 16-QAM and extending the transmission distance up to 120 km. DFE has a significant advantage over LMS and AMF in reducing the inter-symbol interference (ISI) in a dispersive channel by using previous decision feedback, resulting in quicker convergence and more precise equalization. MLD, on the other hand, is highly effective in improving detection accuracy by taking into account the probability of various symbol sequences achieving lower error rates and enhancing performance in advanced modulation schemes. RDE performs best for QPSK and 16-QAM constellations among all the other algorithms. Furthermore, DFE and MLD are particularly suitable for higher-order modulation formats like 64-QAM and 128-QAM, where accurate equalization and error detection are of utmost importance. The enhanced functionalities of DFE, RDE, and MLD in managing greater modulation orders and expanding transmission range highlight their efficacy in improving the performance and dependability of our system. Full article

Background: Neisseria meningitidis (N. meningitidis) is a leading cause of acute meningitis and is classified into 13 serogroups, six of which are predominantly associated with invasive meningococcal disease. This study aimed to investigate the genotype, subgenotype, and antigenic profiles of N. meningitidis serogroup B strains isolated in Vietnam. Methods: Genotyping was performed on 106 N. meningitidis strains isolated from clinical samples from Vietnamese patients and nasopharyngeal swabs of healthy adolescents between 2019 and 2024. The genetic profiles, including the porA, porB, fetA, fHbp, abcZ, adk, aroE, fumC, gdh, pdhC, and pgm genes, were analyzed using Sanger sequencing and bioinformatic methods. Results: We found that 84.9% of the strains carried VR3 families 36 or 35-1, with VR1, VR2, and VR3 families 22-25, 14, and 36 being the most prevalent. Among the 106 serogroup B isolates, 20 variants of the porB allele 3 were identified, with porB 3-1212 being the most frequent (30.2%). Dominant PorB variable loops included L1.6, L4.5, L5.7, L6.6, and L7.13. fHbp variant group 2 was predominant (104/106 strains), and 12 FetA allele variants were identified, with F1-7 being the most common (47.2%). Three clonal complexes were identified, and clonal complex ST-32 was the most predominant. Fifty-five strains (51.9%) belonged to sequence types that have not yet been assigned to any clonal complexes, and 15 strains (14.1%) with allelic profiles were not assigned to STs. The 3-253 and 3-1212 alleles of porB, the F1-7 variant of FetA, the ST-44 and ST-1576 sequence types, and the ST-41/44 complex were observed more frequently in patients compared to asymptomatic carriers, suggesting their association with more virulence. Conclusions: This study showed a high genetic and antigenic diversity of N. meningitidis serogroup B isolates in Vietnam, with VR3 family 36 most common and porB 3-1212 as the predominant allele. fHbp variant group 2 and FetA allele F1-7 were most frequent. ST-32 was the dominant clonal complex, though many strains remained unassigned, highlighting the need for ongoing molecular surveillance. Full article

Significant advances have been made in emotional speech synthesis technology; however, existing models still face challenges in achieving fine-grained emotion style control and simple yet precise emotion intensity regulation. To address these issues, we propose Easy-Control Emotion Text-to-Speech (ECE-TTS), a zero-shot TTS model built upon the F5-TTS architecture, simplifying emotion modeling while maintaining accurate control. ECE-TTS leverages pretrained emotion recognizers to extract Valence, Arousal, and Dominance (VAD) values, transforming them into Emotion-Adaptive Spherical Vectors (EASV) for precise emotion style representation. Emotion intensity modulation is efficiently realized via simple arithmetic operations on emotion vectors without introducing additional complex modules or training extra regression networks. Emotion style control experiments demonstrate that ECE-TTS achieves a Word Error Rate (WER) of 13.91%, an Aro-Val-Domin SIM of 0.679, and an Emo SIM of 0.594, surpassing GenerSpeech (WER = 16.34%, Aro-Val-Domin SIM = 0.627, Emo SIM = 0.563) and EmoSphere++ (WER = 15.08%, Aro-Val-Domin SIM = 0.656, Emo SIM = 0.578). Subjective Mean Opinion Score (MOS) evaluations (1–5 scale) further confirm improvements in speaker similarity (3.93), naturalness (3.98), and emotional expressiveness (3.94). Additionally, emotion intensity control experiments demonstrate smooth and precise modulation across varying emotional strengths. These results validate ECE-TTS as a highly effective and practical solution for high-quality, emotion-controllable speech synthesis. Full article

Phaeodactylum tricornutum is rich in bioactive substances, rendering it valuable in nutrition and medicine. Epigenetic editing mediated by human RNA demethylase FTO can significantly increase the yields of rice and potato and offers significant potential for the genetic breeding of microalgae. This study aimed to enhance the production of certain metabolites in P. tricornutum via FTO-mediated epigenetic editing. Phenotypic analysis revealed that transgenic P. tricornutum exhibits significantly reduced RNA m⁶A modification levels and faster growth, producing markedly higher levels of lipids, proteins, and carotenoids than the wild type. Transcriptome analysis revealed 1009 upregulated genes and 378 downregulated genes. KEGG analysis demonstrated the upregulated expression of multiple key enzymes involved in long-chain fatty acid synthesis (e.g., ACSL, fabF, and fabG), carotenoid synthesis (e.g., crtQ, PDS, and PSY1), and amino acid synthesis (e.g., dapF, glyA, and aroK) in transgenic P. tricornutum, consistent with our phenotypic results. These results indicate that FTO can promote growth and increase the bioactive compound content in P. tricornutum by regulating the m⁶A modification of RNA, and further suggest that FTO has the potential to serve as a new tool for the epigenetic editing of microalgae. Full article

This research presents a novel approach to 28 $\mathrm{GHz}$ impulse radio ultra-wideband (IR-UWB) transmission using pulse position modulation (PPM) over an analog radio-over-fiber (ARoF) link, investigating the impact of fiber-based fronthaul on the overall performance of the communication system. In this setup, an arbitrary waveform generator (AWG) is employed for PPM signal generation, while demodulation is performed with a commercial time-to-digital converter (TDC) based on an event timer. To enhance the reliability of transmitted reference PPM (TR-PPM) signals, the transmission system integrates Gray coding and Consultative Committee for Space Data Systems (CCSDS)-standard-compliant Reed-Solomon (RS) error correcting code (ECC). System performance was evaluated by transmitting pseudorandom binary sequences (PRBSs) and measuring the bit error ratio (BER) across a 5-m wireless link between two 20 $\mathrm{d}\mathrm{B}\mathrm{i}$ gain horn (Ka-band) antennas, with and without a 20 $\mathrm{k}\mathrm{m}$ single-mode optical fiber (SMF) link in transmitter side and ECC at the receiver side. The system achieved a BER of less than 8.17 × 10⁻⁷, using a time bin duration of 200 $\mathrm{p}\mathrm{s}$ and a pulse duration of 100 $\mathrm{p}\mathrm{s}$, demonstrating robust performance and significant potential for space-to-ground telecommunication applications. Full article

Metabolic engineering of the shikimate pathway offers a promising strategy for enhancing the production of aromatic compounds in microbial hosts. However, feedback inhibition of key enzymes, such as the 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase (DAHP synthase), often limits the yield of target products. In this study, we focused on the DAHP synthase (AroF-I) from Pseudomonas putida. Through computational modeling and experimental validation, we identified specific amino-acid residues responsible for tyrosine-mediated feedback inhibition. By targeted mutagenesis, we engineered DAHP synthase variants that exhibit reduced sensitivity to feedback inhibition. The introduction of these engineered enzymes into a metabolically engineered Pseudomonas putida strain resulted in significantly increased production of p-coumaric acid. Our findings provide valuable insights into the regulation of the shikimate pathway and demonstrate the potential of protein engineering to improve microbial production of aromatic compounds. Full article

Usually, hyperspectral data captured from an airborne UAV or satellite contain some noise that can be severe in some channels. Often, channels that are badly affected by the noise are discarded. This is because the corrupted channels cannot be reclaimed by common filtering techniques, making important information in the affected channels different from those of field spectroscopy of similar wavelengths. In this study, a fast-denoising method is implemented on some channels of oil palm hyperspectral data that are badly affected by noise. The amount of noise is unknown, and it varies across the noisy channels from bad to severe. This is different from the data normally used by many studies, which are essentially clean data spiked with mild noise of known variance. The process starts by identifying which noisy channels to filter based on the level of the estimated noise in them. Then, filtering is conducted within each channel and across channels. Once the noise is removed, the improvement in signal-to-noise ratio (SNR) is calculated for each channel. The performance of Kalman, Wiener, Savitzky–Golay, wavelet, and cosine filters is tested in the same framework and the results are compared in terms of execution time, signal-to-noise ratio, and visual quality. The results show that the Kalman filter slightly outperformed the other filters. The proposed scheme was implemented using MATLAB R2023b running on an Intel i7 processor, and the average execution time was less than 1 second for each channel. To the best of our knowledge, this is the first attempt to filter real oil palm hyperspectral data containing speckle noise using a Kalman filter. This technique can be a useful tool to those working in the oil palm industry. Full article

This study investigates the fabrication, microstructural characteristics and plasma resistance of Y–Al–Si–O (YAS) glass-ceramics coated on alumina ceramics. YAS frits were initially prepared using a melt-quenching method, then homogenously milled and coated onto alumina ceramics. The melt-coating process was conducted at 1650 °C for 1 h. The composition and microstructure of the glass frits and coatings were thoroughly characterized using X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. These analyses revealed a dense microstructure with a polycrystalline structure predominantly composed of Y₃Al₅O₁₂ (YAG) phase and a minor phase of Y₂Si₂O₇. The YAS coatings on alumina revealed a dense layer with strong adhesion to the substrate. Subsequently, the coatings underwent C₄F₆/Ar/O₂ plasma treatment for 1 h. Plasma exposure tests demonstrated that the YAS-coated alumina exhibited significantly better etching resistance compared to uncoated alumina, with minimal surface damage observed on the YAS coating, confirming its protective properties against plasma. The superior plasma resistance of YAS coatings is attributed to the predominance of its YAG phase. This research offers a more stable and cost-efficient solution for protecting ceramics in demanding plasma environments. Full article

This study presents a method to enhance the contrast and luminosity of fundus images with boundary reflection. In this work, 100 retina images taken from online databases are utilized to test the performance of the proposed method. First, the red, green and blue channels are read and stored in separate arrays. Then, the area of the eye also called the region of interest (ROI) is located by thresholding. Next, the ratios of R to G and B to G at every pixel in the ROI are calculated and stored along with copies of the R, G and B channels. Then, the RGB channels are subjected to average filtering using a 3 × 3 mask to smoothen the RGB values of pixels, especially along the border of the ROI. In the background brightness estimation stage, the ROI of the three channels is filtered by binomial filters (BFs). This step creates a background brightness (BB) surface of the eye region by levelling the foreground objects like blood vessels, fundi, optic discs and blood spots, thus allowing the estimation of the background illumination. In the next stage, using the BB, the luminosity of the ROI is equalized so that all pixels will have the same background brightness. This is followed by a contrast adjustment of the ROI using CLAHE. Afterward, details of the adjusted green channel are enhanced using information from the adjusted red and blue channels. In the color correction stage, the intensities of pixels in the red and blue channels are adjusted according to their original ratios to the green channel before the three channels are reunited. The resulting color image resembles the original one in color distribution and tone but shows marked improvement in luminosity and contrast. The effectiveness of the approach is tested on the test images and enhancement is noticeable visually and quantitatively in greyscale and color. On average, this method manages to increase the contrast and luminosity of the images. The proposed method was implemented using MATLAB R2021b on an AMD 5900HS processor and the average execution time was less than 10 s. The performance of the filter is compared to those of two other filters and it shows better results. This technique can be a useful tool for ophthalmologists who perform diagnoses on the eyes of diabetic patients. Full article

SF₆ is a strong greenhouse effect gas, which is widely used in high-voltage electrical equipment such as circuit breakers and high-voltage switchgear because of its excellent insulation performance and arc extinguishing ability. In recent years, the use and emission of SF₆ have been rising, and with the proposal of the dual carbon strategic goal, its harmless degradation has become an urgent problem to be solved. In this paper, SF₆ was degraded by pulsed DBD plasma technology and O₂. Studies have shown that the addition of O₂ can effectively promote the degradation of SF₆. With the increase in the added O₂ content, the DRE and EY of SF₆ first increased and then decreased. Under the conditions of the input power of 50 W, SF₆ concentration of 2%, and gas flow rate of 50 mL/min, the reaction system obtained the highest DRE and EY of 58.40% and 5.24 g/kWh when the O₂ content was 1%, respectively. In the SF₆/Ar/O₂/H₂O system, the addition of H₂O could improve the product selectivity of SO₂F₂, and when the O₂ concentration was 1%, the highest selectivity of SO₂F₂ was 48.96%, and the concentration was 8006.76 ppm. The addition of O₂ inhibited the production of SO₂, and with the addition of the O₂ system, SO₂F₂ and SOF₄ were the main components of degradation products; however, there were also SOF₂, SO₂, SiF_4, SF₄, etc. In this paper, the decomposition path of O₂ under SF₆ was analyzed in detail according to infrared spectroscopy and decomposition products. Full article

Biological control is a scientific management method used in modern agricultural production, and microbially derived biopesticides are one effective method with which to control weeds in agricultural fields. In order to determine the key genes for weed control by Trichoderma polysporum, transcriptome sequencing was carried out by high-throughput sequencing technology, and the strains of T. polysporum HZ-31 infesting Avena fatua L. at 24, 48, and 72 h were used as the experimental group, with 0 h as the control group. A total of 690,713,176 clean reads were obtained, and the sequencing results for each experimental group and the control group (0 h) were analyzed. In total, 3464 differentially expressed genes were found after 24 h of infection with the pathogen, including 1283 down-regulated genes and 2181 up-regulated genes. After 48 h of infection, the number of differentially expressed genes was 3885, of which 2242 were up-regulated and 1643 were down-regulated. The number of differentially expressed genes after 72 h of infection was the highest among all the groups, with 4594 differentially expressed genes, of which 2648 were up-regulated and 1946 were down-regulated. The up-regulated genes were analyzed by GO and KEGG, and the results showed that the up-regulated differentially expressed genes were mainly enriched in the biosynthesis of phenylalanine, tyrosine, and tryptophan; the degradation of aromatic compounds; methane metabolism; and other pathways. Among them, the PHA2, GDH, ADH2, and AROF genes were significantly enriched in the above-mentioned pathways, so they were hypothesized to play an important role in the synthesis of the herbicidally active substances of T. polysporum HZ-31. The results of this study can provide a theoretical basis for further studies on the pathogenicity of T. polysporum to A. fatua L., and accelerate the development and utilization of new and efficient bioherbicides. Full article

The proliferation of Internet of Things (IoT) devices and their integration into critical infrastructure and business operations has rendered them susceptible to malware and cyber-attacks. Such malware presents a threat to the availability and reliability of IoT devices, and a failure to address it can have far-reaching impacts. Due to the limited resources of IoT devices, traditional rule-based detection systems are often ineffective against sophisticated attackers. This paper addressed these issues by designing a new framework that uses a machine learning (ML) algorithm for the detection of malware. Additionally, it also employed sequential detection architecture and evaluated eight malware datasets. The design framework is lightweight and effective in data processing and feature selection algorithms. Moreover, this work proposed a classification model that utilizes one support vector machine (SVM) algorithm and is individually tuned with three different optimization algorithms. The employed optimization algorithms are Nuclear Reactor Optimization (NRO), Artificial Rabbits Optimization (ARO), and Particle Swarm Optimization (PSO). These algorithms are used to explore a diverse search space and ensure robustness in optimizing the SVM for malware detection. After extensive simulations, our proposed framework achieved the desired accuracy among eleven existing ML algorithms and three proposed ensemblers (i.e., NRO_SVM, ARO_SVM, and PSO_SVM). Among all algorithms, NRO_SVM outperforms the others with an accuracy rate of 97.8%, an F1 score of 97%, and a recall of 99%, and has fewer false positives and false negatives. In addition, our model successfully identified and prevented malware-induced attacks with a high probability of recognizing new evolving threats. Full article

This study aimed to explore the phenotype and relationship of drug resistance genes in livestock and poultry farm wastewater and drinking water reservoirs to provide evidence for the transmission mechanisms of drug resistance genes, in order to reveal the spread of drug resistance genes in wastewater from intensive farms in Central China to urban reservoirs that serve as drinking water sources and provide preliminary data for the treatment of wastewater from animal farms to reduce the threat to human beings. DNA extraction and metagenomic sequencing were performed on eight groups of samples collected from four water reservoirs and four related wastewaters from animal farms in Central China. Metagenomic sequencing showed that the top 20 AROs with the highest abundance were vanT_gene, vanY_gene, adeF, qacG, Mtub_rpsL_STR, vanY_gene_, vanW_gene, Mtub_murA_FOF, vanY_gene, vanH_gene, FosG, rsmA, qacJ, RbpA, vanW_gene, aadA6, vanY_gene, sul4, sul1, and InuF. The resistance genes mentioned above belong to the following categories of drug resistance mechanisms: antibiotic target replacement, antibiotic target protection, antibiotic inactivation, and antibiotic efflux. The resistomes that match the top 20 genes are Streptococcus agalactiae and Streptococcus anginosus; Enterococcus faecalis; Enterococcus faecium; Actinomyces viscosus and Bacillus cereus. Enterococcus faecium; Clostridium tetani; Streptococcus agalactiae and Streptococcus anginosus; Streptococcus agalactiae and Streptococcus anginosus; Acinetobacter baumannii, Bifidobacterium bifidum, Bifidobacterium breve, Bifidobacterium longum, Corynebacterium jeikeium, Corynebacterium urealyticum, Mycobacterium kansasii, Mycobacterium tuberculosis, Schaalia odontolytica, and Trueperella pyogenes; Mycobacterium avium and Mycobacterium tuberculosis; Aeromonas caviae, Enterobacter hormaechei, Vibrio cholerae, Vibrio metoecus, Vibrio parahaemolyticus, and Vibrio vulnificus; Pseudomonas aeruginosa and Pseudomonas fluorescens; Staphylococcus aureus and Staphylococcus equorum; M. avium, Achromobacter xylosoxidans, and Acinetobacter baumannii; Sphingobium yanoikuyae, Acinetobacter indicus, Morganella morganii, Proteus mirabilis, Proteus vulgaris, Providencia rettgeri, and Providencia stuartii. Unreported drug resistance genes and drug-resistant bacteria in Central China were identified in 2023. In the transmission path of drug resistance genes, the transmission path from aquaculture wastewater to human drinking water sources cannot be ignored. For the sake of human health and ecological balance, the treatment of aquaculture wastewater needs to be further strengthened, and the effective blocking of drug resistance gene transmission needs to be considered. Full article

Functional electrical stimulation (FES) has been widely used to treat spinal cord injury (SCI) patients. Many research studies employ a closed-loop FES system to monitor the stimulated muscle response and provide a precise amount of charge to the muscle. However, most closed-loop FES devices perform poorly and sometimes fail when muscle nonlinearity effects such as fatigue, time delay response, stiffness, spasticity, and subject change happen. The poor performance of the closed-loop FES device is mainly due to discrepancies in the feedback control algorithms. Most of the existing feedback control algorithms were not designed to adapt to new changes in patients with different nonlinearity effects, resulting in early muscle fatigue. Therefore, this research proposes an adaptive sliding mode (SM) feedback control algorithm that could adapt and fine-tune internal control settings in real-time according to the current subject’s nonlinear and time-varying muscle response during the rehabilitation (knee extension) exercise. The adaptive SM feedback controller consists mainly of system identification, direct torque control, and tunable feedback control settings. Employing the system identification unit in the feedback control algorithm enables real-time self-tuning and adjusting of the SM internal control settings according to the current patient’s condition. Initially, the patient’s knee trajectory response was identified by extracting meaningful information, which included time delay, rise time, overshoot, and steady-state error. The extracted information was used to fine-tune and update the internal SM control settings. Finally, the performance of the proposed adaptive SM feedback control algorithm in terms of system response time, stability, and rehabilitation time was analysed using a nonlinear knee model. The findings from the simulation results indicate that the adaptive SM feedback controller demonstrated the best control performance in accurately tracking the desired knee angle movement by having faster response times, smaller overshoots, and lower steady-state errors when compared with the conventional SM across four reference angle settings (20°, 30°, 40°, and 76°). The adaptive feedback SM controller was also observed to compensate for muscle nonlinearities, including fatigue, stiffness, spasticity, time delay, and other disturbances. Full article

Polystyrene (PS)/Gold (Au) is used for a wide range of applications, including composite nanofibers, catalysis, organic memory devices, and biosensing. In this work, PS films were deposited on silicon substrates via a spin coating technique followed by treatment with argon (Ar) plasma admixed with ammonia (NH₃), oxygen (O₂), or tetrafluoroethane (C₂H₂F₄). X-Ray photoelectron spectroscopy (XPS) analysis revealed modified surface chemistry for Ar/O₂, Ar/NH₃, or Ar/C₂H₂F₄ plasma treatment through the incorporation of oxygen, nitrogen, or fluorine groups, respectively. Size-controlled magnetron sputter deposition of Au nanoparticles (NP) onto these plasma-treated PS films was investigated via XPS and AFM techniques. The interaction of the Au NPs, as probed from the XPS and AFM measurements, is discussed by referring to changes in surface chemistry and morphology of the PS after plasma treatment. The results demonstrate the effect of surface chemistry on the interaction of Au NPs with polymer support having different surface functionalities. The XPS results show that significant oxygen surface incorporation resulted from oxygen-containing species in the plasma itself. The surface concentration of O increased from 0.4% for the pristine PS to 4.5 at%, 35.4 at%, and 45.6 at% for the Ar/C₂H₄F₄, Ar/NH₃, and Ar/O₂, respectively. The water contact angle (WCA) values were noticed to decrease from 98° for the untreated PS to 95°, 37°, and 15° for Ar/C₂H₂F₄, Ar/NH₃, and Ar/O₂ plasma-modified PS samples, respectively. AFM results demonstrate that surface treatment was also accompanied by surface morphology change. Small Au islands are well dispersed and cover the surface, thus forming a homogeneous, isotropic structure. The reported results are important for exploiting Au NPs use in catalysis and sensing applications. Full article