Search Results (793)

The overprescription of antibiotics in medicine and agriculture has accelerated the development and spread of antibiotic resistance in bacteria, which severely limits the arsenal available to clinicians for treating bacterial infections. This work discovered a new class of heteroarylcyanovinyl quinazolones and quinazolone pyridiniums to surmount the increasingly severe bacterial resistance. Bioactive assays manifested that the highly active compound 19a exhibited strong inhibition against MRSA and Escherichia coli with extremely low MICs of 0.5 μg/mL, being eightfold more active than that of norfloxacin (MICs = 4 μg/mL). The highly active 19a with rapid bactericidal properties displayed imperceptible resistance development trends, negligible hemolytic toxicity, and effective biofilm inhibitory effects. Preliminary explorations on antibacterial mechanisms revealed that compound 19a could cause membrane damage, embed in intracellular DNA to hinder bacterial DNA replication, and induce metabolic dysfunction. Surprisingly, active 19a was found to trigger the conformational change in PBP2a of MRSA to open the active site, which might account for its high inhibition against MRSA. In addition, the little effect of molecule 19a on the production of reactive oxygen species indicated that bacterial death was not caused by oxidative stress. The above comprehensive analyses highlighted the large potential of quinazolone pyridiniums as multitargeting broad-spectrum antibacterial agents. Full article

Macromolecule bactericides present challenges such as low biocompatibility and not being biodegradable, so broad-spectrum bactericides without accumulated bacteria resistance are now in urgent demand all over the world. Lysozyme, a kind of wide-spread natural enzyme easily extracted from nature, has become attractive for agriculture and medicine use. However, Gram-negative bacterial strains are highly resistant to natural lysozymes, which limits their practical application. In this study, rather than directly modifying antibacterial-active substance with lysozyme, we show an effective way to improve antibacterial performance by altering the hydrophobic functional groups of natural lysozymes and synthesize a type of hydrophobic modified lysozyme (HML). Compared with other modification methods, the antibacterial performance has been increased by over 50%. We investigated its antibacterial mechanism against Gram-negative bacteria and showed that HML could be used to treat pathogenic bacteria without obvious accumulated resistance appearance, which is a great advantage over commercial antibiotics. Overall, it is anticipated that HML could be potentially applied to food safety, infection therapy, and enzyme-medicine applications. Full article

Antibiotic-resistant bacteria are usually found in food-producing animals worldwide. Ciprofloxacin, an antibiotic, can lead to antibiotic residues in food products, posing health risks to consumers and contributing to the development of antimicrobial resistance. Foodborne illnesses occur when adequate attention is not paid to food hygiene and safety, raising the potential for resistant bacteria to spread to humans through the food chain. This study aims to determine the presence of antibiotic-resistant organism contamination and ciprofloxacin residue in raw pork and chicken. Forty-three pork and 33 chicken meat samples were collected from fresh markets in Chiang Mai, Thailand. Antibiotic-resistant organisms were detected by microbial culture and identified by MALDITOF-MS. The antimicrobial sensitivity tests were used to confirm antibiotic resistance. The ciprofloxacin was detected by using an immunochromatographic-based test kit for screening. The results found Extended Spectrum β-lactamase (ESBL)-producing E. coli and K. pneumoniae were detected at 46.51% and 9.30% in pork and 69.70% and 6.06% in chicken meat samples, respectively. Moreover, ciprofloxacin residues were detected in nine samples (11.84%). Based on this study’s findings, the people who are involved in the food chain must be concerned about food safety and food hygiene. Full article

The application of spread-spectrum signals (arbitrary pulse width and position (APWP) sequences) in air-coupled resonant ultrasound spectroscopy is studied. It was hypothesized that spread-spectrum signal optimization should be based on te signal to noise ratio (SNR). Six APWP signal optimization criteria were proposed for this purpose. Experimental measurements were conducted using a thin polycarbonate sample using two standard spread-spectrum signals, linear and nonlinear frequency modulation, together with six optimized APWP signals. It was found that the performance of APWP signals derived from linear frequency modulation was better. The two best performing optimization criteria are SNR improvement on a linear scale with the SNR as an additional weight and energy improvement on a dB scale. The influence of spectral coverage on measurement errors was evaluated. It was found that it is sufficient to cover the sample resonance peak and the valley. The lowest error rates for density, 3%, and for thickness, 3.5%, were achieved when the upper valley was covered. For velocity, the best result, 5%, was achieved when the lower valley was covered. The lowest error rate for attenuation, 3.8%, was achieved in the case when both valleys were covered. Yet no significant performance degradation was noted when a whole −30 dB passband was covered. Full article

Despite the fact that countless IoT applications are arising frequently in various fields, such as green cities, net-zero decarbonization, healthcare systems, and smart vehicles, the smart grid is considered the most critical cyber–physical IoT application. With emerging technologies supporting the much-anticipated smart energy systems, particularly the smart grid, these smart systems will continue to profoundly transform our way of life and the environment. Energy systems have improved over the past ten years in terms of intelligence, efficiency, decentralization, and ICT usage. On the other hand, cyber threats and attacks against these systems have greatly expanded as a result of the enormous spread of sensors and smart IoT devices inside the energy sector as well as traditional power grids. In order to detect and mitigate these vulnerabilities while increasing the security of energy systems and power grids, a thorough investigation and in-depth research are highly required. This study offers a comprehensive overview of state-of-the-art smart grid cybersecurity research. In this work, we primarily concentrate on examining the numerous threats and cyberattacks that have recently invaded the developing smart energy systems in general and smart grids in particular. This study begins by introducing smart grid architecture, it key components, and its security issues. Then, we present the spectrum of cyberattacks against energy systems while highlighting the most significant research studies that have been documented in the literature. The categorization of smart grid cyberattacks, while taking into account key information security characteristics, can help make it possible to provide organized and effective solutions for the present and potential attacks in smart grid applications. This cyberattack classification is covered thoroughly in this paper. This study also discusses the historical incidents against energy systems, which depicts how harsh and disastrous these attacks can go if not detected and mitigated. Finally, we provide a summary of the latest emerging future research trend and open research issues. Full article

Dengue fever, caused by the dengue virus (DENV), poses a significant global health challenge, particularly in tropical and subtropical regions. Recent increases in indigenous DENV cases in Europe are concerning, reflecting rising incidence linked to climate change and the spread of Aedes albopictus mosquitoes. These vectors thrive under environmental conditions like temperature and humidity, which are increasingly influenced by climate change. Additionally, global travel accelerates the cross-border spread of mosquito-borne diseases. DENV manifests clinically in a spectrum from asymptomatic cases to severe conditions like dengue hemorrhagic fever and dengue shock syndrome, influenced by viral serotype and host factors. In 2024, Brazil experienced a fourfold increase in dengue cases compared to 2023, accompanied by higher mortality. Conventional control measures, such as vector control, community engagement, and vaccination, proved insufficient as climate change exacerbated mosquito proliferation, challenging containment efforts. In this regard, our review analyzes prevention measures and therapeutic protocols during the outbreak while addressing DENV transmission dynamics, clinical presentations, and epidemiological shifts. It also evaluates diagnostic strategies combining clinical assessment with serological and molecular testing, providing information to improve diagnostic and preventive measures. The global expansion of dengue-endemic regions, including outbreaks in Europe, highlights the urgent need for enhanced surveillance, proactive interventions, and international collaboration to mitigate the growing threat of Dengue and other arboviruses like West Nile, Zika, Chikungunya, Oropouche, and Yellow Fever viruses. Full article

Avian pox is a globally spread viral disease affecting a wide spectrum of wild and domesticated bird species. The disease is caused by a diverse group of large DNA viruses, namely, avipoxviruses (genus Avipoxvirus, family Poxviridae). In this study, gross pathological examination and histopathological examination of skin lesions and several organs suggested acute poxvirus infection of a Eurasian crane (Grus grus, Linnaeus, 1758). Avipoxvirus infection was confirmed by testing wart-like lesions via gene-specific PCR assay and sequencing the obtained amplicon. Phylogenetic analysis of the gene encoding the DNA polymerase revealed that the crane poxvirus clustered in clade A, subclade A3. A large fragment of the poxvirus genome (306,477 bp in length) was assembled from the DNA of a skin specimen. Our study reaffirms previous findings that even complex virus genomes can be determined from a metagenomic assemblage generated directly from avian tissue samples without prior virus isolation, a promising approach for the epidemiologic surveillance of avipoxvirus infections in wild birds and domestic poultry. Full article

Watermarking is widely employed to protect audio files. Previous research has focused on developing systems that balance performance criteria, including robustness, imperceptibility, and capacity. Most existing systems are designed to work with pre-recorded audio signals, where the characteristics of the host signal are known in advance. In such cases, processing time is not a critical factor, as these systems generally do not account for real-time signal acquisition or report tests for real-time signal acquisition nor report the elapsed time between signal acquisition and watermarking output, known as latency. However, the increasing prevalence of audio sharing through real-time streams or video calls is a pressing issue requiring low-latency systems. This work introduces a low-latency watermarking system that utilizes a spread spectrum technique, a method that spreads the signal energy across a wide frequency band while embedding the watermark additively in the time domain to minimize latency. The system’s performance was evaluated by simulating real-time audio streams using two distinct methods. The results demonstrate that the proposed system achieves minimal latency during embedding, addressing the urgent need for such systems. Full article

Mass gatherings are associated with the spread of communicable diseases. Some studies have suggested that acquisition of antimicrobial resistance (AMR) may be associated with attendance at specific mass gatherings. This systematic review aimed to synthesise evidence on the association between attendance at mass gatherings and antimicrobial resistance (AMR) and assess the prevalence of AMR at mass gatherings. A literature search of the Cochrane, Medline, Scopus, and Embase databases was performed. Studies were included if they reported original data, involved mass gatherings, and reported AMR results. Of 5559 titles screened, 44 studies met the inclusion criteria, most of which (n = 40) involved religious mass gatherings. The heterogeneity of the studies precluded a meta-analysis, hence a narrative synthesis by organism was conducted. A significant increase in antibiotic-resistant Escherichia coli and Klebsiella pneumoniae was reported following Hajj, as was a rise in gastrointestinal carriage of extended-spectrum β-lactamase (ESBL) or carbapenemase genes. Carriage of Streptococcus pneumoniae isolates non-susceptible to one or more antibiotics was also shown to increase from pre-Hajj to post-Hajj. There appears to be an association between attendance at mass gatherings and the acquisition of some AMR phenotypes and genotypes in some significant human pathogens, including E. coli and S. pneumoniae. Full article

Fusarium wilt of banana is a soil-borne vascular disease caused by Fusarium oxysporum f. sp. cubense. The rapid and accurate detection of this disease is of great significance to controlling its spread. The research objective was to explore rapid banana Fusarium wilt latency and onset detection methods and establish a disease severity grading model. Visible/near-infrared spectroscopy analysis combined with machine learning methods were used for the rapid in vivo detection of banana Fusarium wilt. A portable visible/near-infrared spectrum acquisition system was constructed to collect the spectra data of banana Fusarium wilt leaves representing five different disease grades, totaling 106 leaf samples which were randomly divided into a training set with 80 samples and a test set with 26 samples. Different data preprocessing methods were utilized, and Fisher discriminant analysis (FDA), an extreme learning machine (ELM), and a one-dimensional convolutional neural network (1D-CNN) were used to establish the classification models of the disease grades. The classification accuracies of the FDA, ELM, and 1D-CNN models reached 0.891, 0.989, and 0.904, respectively. The results showed that the proposed visible/near infrared spectroscopy detection method could realize the detection of the incubation period of banana Fusarium wilt and the classification of the disease severity and could be a favorable tool for the field diagnosis of banana Fusarium wilt. Full article

This paper presents an extensive investigation into the application of artificial intelligence, specifically Convolutional Neural Networks (CNNs), in image steganography detection. We initially evaluated the state-of-the-art steganalysis model, SRNet, on various image steganography techniques, including WOW, HILL, S-UNIWARD, and the innovative Spread Spectrum Image Steganography (SSIS). We found SRNet’s performance on SSIS detection to be lower compared to other methods, prompting us to fine-tune the model using SSIS datasets. Subsequent experiments showed significant improvement in SSIS detection, albeit at the cost of minor performance degradation as to other techniques. Our findings underscore the potential and adaptability of AI-based steganalysis models. However, they also highlight the need for a delicate balance in model adaptation to maintain effectiveness across various steganography techniques. We suggest future research directions, including multi-task learning strategies and other machine learning techniques, to further improve the robustness and versatility of steganalysis models. Full article

This study demonstrates a rich complexity of the time–frequency ionospheric signal spectrum, dependent on the measurement type and platform. Different phenomena contributing to satellite-derived and ground-derived geophysical data that only selected signal bands can be potentially sensitive to seismicity over time, and they are applicable in lithosphere–atmosphere–ionosphere coupling (LAIC) studies. In this study, satellite-derived and ground-derived ionospheric observations are filtered by a Fourier-based band-pass filter, and an experimental selection of potentially sensitive frequency bands has been carried out. This work focuses on band-pass filtered ionospheric observations and seismic activity in the region of the Aegean Sea over a two-year time period (2020–2021), with particular focus on the entire system of tectonic plate junctions, which are suspected to be a potential source of ionospheric disturbances distributed over hundreds of kilometers. The temporal evolution of seismicity power in the Aegean region is represented by the record of earthquakes characterized by M ≥ 4.5, used for the estimation of cumulative seismic energy. The ionospheric response to LAIC is explored in three data types: short inspections of in situ electron density (Ne) over a tectonic plate boundary by Swarm satellites, stationary determination of three Ne density profile parameters by the Athens Digisonde station AT138 (maximum frequency of the F2 layer: foF2; maximum frequency of the sporadic E layer: foEs; and frequency spread: ff), and stationary measure of vertical total electron content (VTEC) interpolated from a UPC-IonSAT Quarter-of-an-hour time resolution Rapid Global ionospheric map (UQRG) near Athens. The spectrograms are made with the use of short-term Fourier transform (STFT). These frequency bands in the spectrograms, which show a notable coincidence with seismicity, are filtered out and compared to cumulative seismic energy in the Aegean Sea, to the geomagnetic Dst index, to sunspot number (SN), and to the solar radio flux (F10.7). In the case of Swarm, STFT allows for precise removal of long-wavelength Ne signals related to specific latitudes. The application of STFT to time series of ionospheric parameters from the Digisonde station and GIM VTEC is crucial in the removal of seasonal signals and strong diurnal and semi-diurnal signal components. The time series formed from experimentally selected wavebands of different ionospheric observations reveal a moderate but notable correlation with the seismic activity, higher than with any solar radiation parameter in 8 out of 12 cases. The correlation coefficient must be treated relatively and with caution here, as we have not determined the shift between seismic and ionospheric events, as this process requires more data. However, it can be observed from the spectrograms that some weak signals from selected frequencies are candidates to be related to seismic processes. Full article

Background/Objectives: The increasing occurrence of extended-spectrum β-lactamase (ESBL)–producing Enterobacterales, most commonly Escherichia coli, has become a serious problem. The aim of this study was to determine the presence of ESBL-producing Gram-negative bacteria in dairy cattle, goat and sheep farms located in southern Türkiye. Methods: Samples (409 quarter milk samples and 110 fresh faecal samples from cattle, 75 bulk tank milk samples and 225 rectal swab samples from goats and sheep) were subjected to selective isolation on MacConkey agar with ceftazidime (2 µg/mL). Isolates were identified by MALDI-ToF MS. The antimicrobial susceptibility profile of the isolates was determined by the broth microdilution method. To obtain a deeper insight into the genetic diversity of isolates substantially contributing to an efficient spread of their ESBL-determinants (23-MO00001: an E. coli from mastitis and 23-MO00002 Citrobacter freundii), the transmission potential and the genetic background of the plasmid carrying the bla_CTX-M determinant was studied with whole genome analysis using Illumina sequencing. Results: Of the samples tested, 47 from the bovine faecal samples, 1 from the subclinical mastitis milk sample, 9 from the goat/sheep rectal swab samples and 5 from the goat/sheep bulk tank milk samples had ceftazidime-resistant Gram-negative strains with the ESBL phenotype. Of the 33 ESBL-producing E. coli isolates, 66.6% were resistant to tetracycline, 57.6% to sulfamethoxazole, 48.9% to nalidixic acid, 42.4% to ciprofloxacin and 33.3% to trimethoprim. Pulsed field gel electrophoresis (PFGE) results showed that the majority of E. coli isolates (16/33) and all Enterobacter spp. isolates (n = 5) were not clonally related (80% similarity cut value). The sequenced strains were observed to efficiently transfer their ceftazidime resistance to the recipient strain E. coli J53 at 37 °C (transfer rates: 10¹–10² transconjugants per donor cell). S1-PFGE showed that the transconjugants J53(p23MO01-T1) and J53(p23MO02-T1) had acquired plasmids of about 82 kb and 55 kb plasmids, respectively. According to WGS results, the E. coli isolate was assigned to ST162, while the C. freundii isolate was assigned to ST95. Conclusions: This study demonstrates that dairy animals are reservoirs of ESBL-producing bacteria. Full article

Unlike terrestrial radio, the speed of sound in the ocean is relatively slow, which results in mobile underwater M-ary spread spectrum communication typically exhibiting significant and variable multipath effects along with strong Doppler effects, leading to rapid carrier phase shifts in the received signal that severely impact decoding accuracy. This study aims to address the issue of rapid carrier phase shifts caused by significant time-varying Doppler shifts during mobile underwater M-SS communication. This paper innovatively proposes a method for updating matched filters based on correlation cost factors. By calculating the correlation cost factors for each received symbol, the method guides the direction of Doppler estimation and updates the matched filters. After identifying the optimal match, the received symbols are shifted, correlated, and decoded. Simulation and sea trial results indicate that this method demonstrates higher computational efficiency and improved decoding accuracy compared to traditional Doppler estimation matched filters under low signal-to-noise ratio conditions, and exhibits greater robustness under complex motion conditions. Full article

In order to improve the concealment and security of a point-to-point transparent forwarding satellite communication system, a signal structure based on aperiodic long code spread spectrum is designed in this paper. This structure can achieve reliable signal acquisition without special physical layer synchronization overhead, which can effectively shorten signal transmission time and improve the concealment of communication. In addition, the performance of burst spread spectrum signal acquisition is analyzed in detail by establishing a mathematical model, and the influencing factors and design criteria of the matching filter length for aperiodic long code acquisition are determined. On this basis, a matched filter acquisition method based on high-power clock multiplexing and an adaptive decision threshold design method based on an auxiliary channel are proposed. The above methods effectively reduce hardware complexity and resource consumption caused by long code acquisition, and realize reliable acquisition under the condition of low SNR. The simulation results show that under the condition of Eb/N0 = 3 dB, the transmission efficiency for a 128-symbol burst frame can be increased by 50%, thereby significantly reducing the burst communication time. Furthermore, the acquisition success probability can reach 99.99%. Full article