Search Results (62)

Fiber fault detection based on the time-delay signature of an optical feedback semiconductor laser has the advantages of high sensitivity, precise location, and a simple structure, which make it widely applicable. The sensitivity of this method is determined by the feedback strength inducing the nonlinear state of the laser. This paper proposes a feedback compensation method to reduce the requirement of the fault echo intensity for the laser to enter the nonlinear state, significantly enhancing detection sensitivity. Numerical simulations analyze the impact of feedback compensation parameters on fault detection sensitivity and evaluate the performance of the laser operating at different pump currents. The results show that this method achieves a 9.33 dB improvement in sensitivity compared to the original approach, effectively addressing the challenges of detecting faults with high insertion losses in optical networks. Full article

Optical chaos generated by a semiconductor laser under cascaded optical injection is experimentally and numerically investigated. A semiconductor slave laser under continuous-wave optical injection from a master laser is employed as the chaotic laser. The chaotic output optically injects a third laser to enhance the chaotic properties. Using three semiconductor lasers coupled in a master-slave configuration without any delay-based components, optical chaos is generated without any time-delay signatures present. Flat broadband chaos is observed with standard and effective bandwidths reaching six and three times the relaxation resonance frequency of the semiconductor laser, respectively. For simultaneous flat and broadband chaos, the chaotic optical injection of the second stage is adjusted for weak injection strength and a high positively detuned frequency. Full article

Bulk 2D electronic–vibrational (2D-EV) and 2D vibrational–electronic spectroscopies (2D-VE) were previously developed to correlate the electronic and vibrational degrees of freedom simultaneously, which allow for the study of couplings between electronic and vibrational transitions in photo-chemical systems. Such bulk-dominated methods have been used to extensively study molecular systems, providing unique information such as coherence sensitivity, molecular configurations, enhanced resolution, and correlated states and their dynamics. However, the analogy of interfacial 2D spectroscopy has fallen behind. Our recent work presented interface-specific 2D-EV spectroscopy (i2D-EV). In this work, we develop interface-specific two-dimensional vibrational–electronic spectroscopy (i2D-VE). The fourth-order spectroscopy is based on a Mach–Zehnder IR interferometer that accurately controls the time delay of an IR pump pulse pair for vibrational transitions, followed by broadband interface second-harmonic generation to probe electronic transitions. We demonstrate step-by-step how a fourth-order i2D-VE spectrum of AP3 molecules at the air/water interface was collected and analyzed. The line shape and signatures of i2D-VE peaks reveal solvent correlations and the spectral nature of vibronic couplings. Together, i2D-VE and i2D-EV spectroscopy provide coupling of different behaviors of the vibrational ground state or excited states with electronic states of molecules at interfaces and surfaces. The methodology presented here could also probe dynamic couplings of electronic and vibrational motions at interfaces and surfaces, extending the usefulness of the rich data that are obtained. Full article

Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green’s function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green’s function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions. Full article

With the development of mobile communication, digital signatures with low latency, low area, and high security are in increasing demand. Elliptic curve cryptography (ECC) is widely used because of its security and lightweight. Elliptic curve scalar multiplication (ECSM) is the basic arithmetic in ECC. Based on this background information, we propose our own research objectives. In this paper, a low-latency and low-area ECSM architecture based on the comb algorithm is proposed. The detailed methodology is as follows. The recoding-k algorithm and randomization-Z algorithm are used to improve security, which can resist sample power analysis (SPA) and differential power analysis (DPA). A low-area multi-functional architecture for comb is proposed, which takes into account different stages of the comb algorithm. Based on this, the data dependency is considered and the comb architecture is optimized to achieve a uniform and efficient execution pattern. The interleaved modular multiplication algorithm and modified binary inverse algorithm are used to achieve short clock cycle delay and high frequency while taking into account the need for a low area. The proposed architecture has been implemented on Xilinx Virtex-7 series FPGA to perform ECSM on 256-bits prime field $GF\left(p\right)$. In the hardware architecture with only 7351 slices of resource usage, a single ECSM only takes 0.74 ms, resulting in an area-time product (ATP) of 5.41. The implementation results show that our design can compete with the existing state-of-the-art engineering in terms of performance and has higher security. Our design is suitable for computing scenarios where security and computing speed are required. The implementation of the overall architecture is of great significance and inspiration to the research community. Full article

Aspergillus carbonarius causes severe decays on berries in vineyards and is among the main fungal species responsible for grape contamination by ochratoxin A (OTA), which is the foremost mycotoxin produced by this fungus. The main goal of this study was to investigate at the transcriptome level the comparative profiles between two table grape varieties (Victoria and Fraoula, the white and red variety, respectively) after their inoculation with a virulent OTA-producing A. carbonarius strain. The two varieties revealed quite different transcriptomic signatures and the expression profiles of the differential expressed genes (DEGs) highlighted distinct and variety-specific responses during the infection period. The significant enrichment of pathways related to the modulation of transcriptional dynamics towards the activation of defence responses, the triggering of the metabolic shunt for the biosynthesis of secondary metabolites, mainly phenylpropanoids, and the upregulation of DEGs encoding phytoalexins, transcription factors, and genes involved in plant–pathogen interaction and immune signaling transduction was revealed in an early time point in Fraoula, whereas, in Victoria, any transcriptional reprogramming was observed after a delay. However, both varieties, to some extent, also showed common expression dynamics for specific DEG families, such as those encoding for laccases and stilbene synthases. Jasmonate (JA) may play a critical modulator role in the defence machinery as various JA-biosynthetic DEGs were upregulated. Along with the broader modulation of the transcriptome that was observed in white grape, expression profiles of specific A. carbonarius genes related to pathogenesis, fungal sporulation, and conidiation highlight the higher susceptibility of Victoria. Furthermore, the A. carbonarius transcriptional patterns directly associated with the regulation of the pathogen OTA-biosynthesis gene cluster were more highly induced in Victoria than in Fraoula. The latter was less contaminated by OTA and showed substantially lower sporulation. These findings contribute to uncovering the interplay beyond this plant–microbe interaction. Full article

Combining an Internet of Things-driven approach with machine learning algorithms holds great promise in discerning pure gases across various applications. Interconnecting gas sensors within a network allows for continuous monitoring and real-time environmental analysis, producing valuable data for machine learning models. Utilizing supervised learning algorithms, like random forests, enables the creation of accurate classification models that can effectively distinguish between different pure gases based on their distinct features, such as spectral signatures or sensor responses. This groundbreaking integration of the Internet of Things and Machine Learning fosters the development of robust, automated gas detection systems, ensuring high accuracy and minimal delay in recognizing pure gases. Consequently, it opens avenues for enhanced safety, efficiency, and environmental sustainability in numerous industrial and commercial scenarios. Full article

In this paper, we propose using a chaotic system composed of nanolasers (NLs) as a physical entropy source. Combined with post-processing technologies, this system can produce high-quality physical random number sequences. We investigated the parameter range for achieving time-delay signature (TDS) concealment in the chaotic system. This study demonstrates that NLs exhibit noticeable TDS only under optical feedback. As mutual injection strength between the master NLs (MNLs) increases, the TDS of the MNLs is gradually suppressed until they are completely concealed. Compared to MNLs, the slave NL (SNL) exhibits better TDS suppression performance. Additionally, we investigated the chaotic and highly unpredictable regions of the SNL, demonstrating that high-quality chaotic signals can be produced over a wide range of parameters. Using TDS hidden and highly unpredictable chaotic signals as the source of random entropy, the effects of different post-processing techniques on random number extraction were compared. The results indicate that effective post-processing can enhance the unpredictability of the random sequence. This study successfully utilized NLs for random number generation, showcasing the potential and application prospects of NLs in the field of random numbers. Full article

Nowadays, technology is increasingly being adopted in different kinds of businesses to process, store, and share sensitive information in digital environments that include enormous numbers of users. However, this has also increased the likelihood of cyberattacks and misuse of information, potentially causing severe damage. One promising technology, which can provide the required security services with an improved level of efficiency, is blockchain. This research explores the use of Ethereum blockchain and smart contracts to create a secure and efficient quality assurance system (QAS) for academic programs. By utilizing blockchain and smart contracts, the proposed approach improves the integrity and reliability of sensitive information processed by the QAS, promotes transparency and governance, and reduces the time and effort required for quality operations. The current approach uses an additional access control layer to further enhance user privacy. Smart contracts automate various quality transactions and saves time and resources, and hence increases the efficiency of the QAS. The interplanetary file system (IPFS) is used to address the challenge of size limitations in blockchain. Additionally, this research investigates the use of various cryptographic schemes to provide robust security services at the application layer. The experimental results showed that the use of a hybrid cryptosystem relying on an Elliptic curve digital signature and AES encryption (AES_ECCDSA) outperforms other counterparts’ cryptosystems using an RSA digital signature and AES encryption (AES_RSADSA) and Elliptic Curve Integrated Encryption Scheme (ECIES) in terms of speed. The performance results showed that AES_ECCDSA consumes 188 ms to perform the required cryptographic operations for a standard-quality document with a size of 8088 KB, compared to the 231 ms and 739 ms consumed by the AES_RSADSA and ECIES schemes, respectively. This study presents a prototype implementation of the blockchain-based QAS, which outlines the processing model and system requirements for key QAS processes. It has been found that the cost and time required for blockchain operations vary depending on the size of the input data—a larger data size requires more time and costs more to process. The results of the current study showed that the time delay for blockchain transactions ranges from 15 to 120 s, while the cost ranges from USD 50 to USD 400. This research provides evidence that blockchain and smart contract technologies have the potential to create a secure, efficient, and trustworthy QAS environment for academic programs. Full article

Previous studies from our laboratory and others have established the dendritic cell (DC) as a key target of RSV that drives infection-induced pathology. Analysis of RSV-induced transcriptomic changes in RSV-infected DC revealed metabolic gene signatures suggestive of altered cellular metabolism. Reverse phase protein array (RPPA) data showed significantly increased PARP1 phosphorylation in RSV-infected DC. Real-time cell metabolic analysis demonstrated increased glycolysis in PARP1-/- DC after RSV infection, confirming a role for PARP1 in regulating DC metabolism. Our data show that enzymatic inhibition or genomic ablation of PARP1 resulted in increased ifnb1, il12, and il27 in RSV-infected DC which, together, promote a more appropriate anti-viral environment. PARP1-/- mice and PARP1-inhibitor-treated mice were protected against RSV-induced immunopathology including airway inflammation, Th2 cytokine production, and mucus hypersecretion. However, delayed treatment with PARP1 inhibitor in RSV-infected mice provided only partial protection, suggesting that PARP1 is most important during the earlier innate immune stage of RSV infection. Full article

Fabry disease is an invalidating multisystemic disorder affecting α-Galactosidase, a rate-limiting hydrolase dedicated to lipid catabolism. Non-metabolized substrates, such as Globotriaosylceramide and its derivatives trigger the direct or indirect activation of inflammatory events and endothelial dysfunction. In spite of the efficacy demonstrated by enzyme replacement therapy or pharmacological chaperones in delaying disease progression, few studies have analyzed whether these treatments can improve the pro-inflammatory state of FD patients. Therefore, the aim of this work was to assess cytokines and cardiovascular risk-related proteins detectable in plasma from FD patients, whether treated or not with ERT, to evaluate the reliability of these markers in monitoring disease stage and treatment effects. We identified inflammatory and endothelial dysfunction markers (ADAMTS-13, TNF-α, GDF-15, MIP-1β, VEGFA, MPO, and MIC-1) that cooperate in a common pathway and are increased in FD patients’ plasma samples. As shown by the assessment of these proteins over time, they can help to evaluate the risk of higher severity in FD, as well as ERT effects. Even though the analyzed proteins cannot be considered as proper biomarkers due to their non-specificity to FD, taken together they can provide a signature of reference molecules with prognostic value for early diagnosis, and evaluation of disease progression and treatment efficacy, using blood samples. Full article

Named Data Networking (NDN) stands out as a prominent architectural framework for the future Internet, aiming to address deficiencies present in IP networks, specifically in the domain of security. Although NDN packets containing requested content are signed with the publisher’s signature which establishes data provenance for content, the NDN domain still requires more holistic frameworks that address consumers’ identity verification while accessing protected contents or services using producer/publisher-preapproved authentication servers. In response, this paper introduces the NDN One-Time Authentication (NDNOTA) framework, designed to authenticate NDN online services, applications, and data in real time. NDNOTA comprises three fundamental elements: the consumer, producer, and authentication server. Employing a variety of security measures such as single sign-on (SSO), token credentials, certified asymmetric keys, and signed NDN packets, NDNOTA aims to reinforce the security of NDN-based interactions. To assess the effectiveness of the proposed framework, we validate and evaluate its impact on the three core elements in terms of time performance. For example, when accessing authenticated content through the entire NDNOTA process, consumers experience an additional time overhead of 70 milliseconds, making the total process take 83 milliseconds. In contrast, accessing normal content that does not require authentication does not incur this delay. The additional NDNOTA delay is mitigated once the authentication token is generated and stored, resulting in a comparable time frame to unauthenticated content requests. Additionally, obtaining private content through the authentication process requires 10 messages, whereas acquiring public data only requires two messages. Full article

Cervical cancer is a major cause of death in women despite the advancement of current treatment modalities. The conventional therapeutic agent, cisplatin (CCDP), is the standard treatment for CC; however, resistance often develops due to the cancer’s heterogeneity. Therefore, a detailed elucidation of the specific molecular mechanisms driving CC is crucial for the development of targeted therapeutic strategies. Retinoblastoma binding protein 6 (RBBP6) is a potential biomarker associated with cell proliferation and is upregulated in cervical cancer sites, exhibiting apoptosis and dysregulated p53 expression. Furthermore, RBBP6 has been demonstrated to sensitize cancer cells to radiation and certain chemotherapeutic agents by regulating the Bcl-2 gene, thus suggesting a crosstalk among RBBP6/p53/BCL-2 oncogenic signatures. The present study, therefore, investigated the relationship between cisplatin and RBBP6 expression in CC cells. Herein, we first explored bioinformatics simulations and identified that the RBBP6/p53/BCL-2 signaling pathway is overexpressed and correlated with CC. For further analysis, we explored the Genomics of Drug Sensitivity in Cancer (GDSC) and found that most of the CC cell lines are sensitive to CCDP. To validate these findings, RBBP6 was silenced in HeLa and Vero cells using RNAi technology, followed by measurement of wild-type p53 and Bcl-2 at the mRNA level using qPCR. Cells co-treated with cisplatin and siRBBP6 were subsequently analyzed for apoptosis induction and real-time growth monitoring using flow cytometry and the xCELLigence system, respectively. Cancer cells in the co-treatment group showed a reduction in apoptosis compared to the cisplatin-treated group. Moreover, the real-time growth monitoring revealed a reduced growth rate in RBBP6 knockdown cells treated with cisplatin. Although wild-type p53 remained unchanged in the co-treatment group of cancer cells, Bcl-2 was completely repressed, suggesting that RBBP6 is necessary for sensitizing cervical cancer cells to cisplatin treatment by downregulating Bcl-2. The Vero cell population, which served as a non-cancerous control cell line in this study, remained viable following treatment with both siRBBP6 and cisplatin. Findings from this study suggest that RBBP6 expression promotes cisplatin sensitivity in HeLa cells through Bcl-2 downregulation. Knockdown of RBBP6 limits apoptosis induction and delays cell growth inhibition in response to cisplatin. The knowledge obtained here has the potential to help improve cisplatin efficacy through personalized administration based on the expression profile of RBBP6 among individual patients. Full article

In response to the growing challenges in drone security and airspace management, this study introduces an advanced drone classifier, capable of detecting and categorizing Unmanned Aerial Vehicles (UAVs) based on acoustic signatures. Utilizing a comprehensive database of drone sounds across EU-defined classes (C0 to C3), this research leverages machine learning (ML) techniques for effective UAV identification. The study primarily focuses on the impact of data augmentation methods—pitch shifting, time delays, harmonic distortion, and ambient noise integration—on classifier performance. These techniques aim to mimic real-world acoustic variations, thus enhancing the classifier’s robustness and practical applicability. Results indicate that moderate levels of augmentation significantly improve classification accuracy. However, excessive application of these methods can negatively affect performance. The study concludes that sophisticated acoustic data augmentation can substantially enhance ML-driven drone detection, providing a versatile and efficient tool for managing drone-related security risks. This research contributes to UAV detection technology, presenting a model that not only identifies but also categorizes drones, underscoring its potential for diverse operational environments. Full article

The nonlinear dynamics of nanolasers (NLs), an important component of optical sources, has received much attention. However, there is a lack of in-depth research into the high-quality chaotic output of NLs and their applications in chaotic secure communications. In this paper, we make the NLs generate broadband chaotic signals whose time-delay signatures (TDS) are completely hidden by a phase conjugate feedback structure. And in the two-channel communication scheme, we make the NLs achieve a combination of a low-latency high degree of synchronization and two-channel transmission technique, which enhances the security of message encryption and decryption. We also investigate the effects of system parameters, Purcell factor $F$, spontaneous emission coupling factor $\beta$, and bias current $I$ on the TDS, as well as the effects of parameter mismatch and injection parameters on chaos synchronization and message recovery. The results show that the phase conjugate feedback-based NLs can achieve the suppression of the TDS within a certain parameter range, and it can achieve high-quality synchronization and enhance the security of chaotic communication under appropriate injection conditions. Full article