Reliable Signal Research Articles

Are accreditation signals being recognised? Business professionals’ awareness and views on accredited university business programmes

ABSTRACT In an increasingly global educational environment, business school accreditations are used by institutions as a signal of quality, credibility, and reliability. While academics’ perspectives on accreditation are well documented, the perspective of the external stakeholder group, ‘business professional’, is scarce. This research addresses this gap by empirically exploring business professionals’ perspectives regarding international and professional discipline-based accreditation of university business schools. A structured online survey attracted 110 valid responses from business professionals. A Bayesian Network (BN) model (implemented in Netica software) was developed for statistical analysis of the dataset, permitting the nuanced characterisation of complex interrelationships between the variables of interest. The findings indicate a low level of awareness of international accreditation among the survey participants. This questions the effectiveness of these accreditations as quality signals. Nevertheless, both international and professional accreditation were perceived as beneficial for employment and career prospects, and membership of professional bodies was seen as advantageous for networking and professional development. The practical implications suggest that information on accreditation, including quality indicators and benefits, could be more consistently and iteratively communicated to stakeholders. Furthermore, professional bodies and business schools could explore additional opportunities to enhance awareness about the value and career-related benefits of professional body memberships.

Development of an IoT-based Traffic Signal Violation Detection System

This study tackles the pressing issue of traffic signal stop-line violations, which poses significant threat to road safety, by designing and implementing an intelligent traffic signal violation system (Internet-of-things (IoT) based technology). The system utilizes infrared (IR) sensors for vehicular detection and an ESP32 Camera to capture images of violating vehicles, which are then sent to a server via notification bots for media platforms. Also, the IR sensors are embedded with the ESP32 Camera and programmed microcontroller to detect traffic stop-line signal violations, capture images, and transmit them to designated authorities. The system was implemented using a prototype build and the result showed a 98% accuracy rate in detecting violations. The system reduces response time for violation detection by 60% success rate. In conclusion, this project demonstrates a reliable and efficient traffic signal violation system, leveraging IoT and Artificial Intelligence (AI) technologies to enhance road safety. The real-world significance of this system entails an enabled rapid intervention, identifying and disciplining offenders, enhance resource allocation, repository of data generated and enforcing legal actions thereby contributing to enhanced road traffic operations and user safety.

A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain-Computer Interfaces to Enhance Motor Imagery Classification.

Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain-computer interfaces (BCIs), which establish a direct communication pathway between users and machines. This technology holds the potential to revolutionize human-machine interaction, especially for individuals diagnosed with motor disabilities. Despite this promise, extracting reliable control signals from noisy brain data remains a critical challenge. In this paper, we introduce a novel approach leveraging the collaborative synergy of five convolutional neural network (CNN) models to improve the classification accuracy of motor imagery tasks, which are essential components of BCI systems. Our method demonstrates exceptional performance, achieving an accuracy of 79.44% on the BCI Competition IV 2a dataset, surpassing existing state-of-the-art techniques in using multiple CNN models. This advancement offers significant promise for enhancing the efficacy and versatility of BCIs in a wide range of real-world applications, from assistive technologies to neurorehabilitation, thereby providing robust solutions for individuals with motor disabilities.

Plug-In Design of the Microneedle Electrode Array for Multi-Parameter Biochemical Sensing in Gouty Arthritis.

Gouty arthritis is one of the most common forms of inflammatory arthritis and has brought a significant burden on patients and society. Current strategies for managing gout primarily focus on long-term urate-lowering therapy. With the rapid advancement of point-of-care testing (POCT) technology, continuous monitoring of gout-related biomarkers like uric acid (UA) or inflammatory cytokines can provide rapid and personalized diagnosis for gout management. In this study, a plug-in design of a microneedle electrode array (PIMNA) was developed and integrated into a multi-parameter sensing portable system in combination with embedded circuits and a mobile application. The system enabled real-time, in situ, and dynamic monitoring of biomarkers, including UA, reactive oxygen species (ROS), and pH at gouty joints. The multi-parameter monitoring system demonstrated a wide linear response range, excellent selectivity, stability, reproducibility, and reliable signal transmission performance. In vivo experiments demonstrated the real-time monitoring capability of PIMNA for UA, ROS, and pH, showing the potential to facilitate urate-lowering management and inflammation assessment. Prospectively, the system enables quantitative analysis of the complexity and diversity of gout, presenting promising applications in clinical practice. This work provides a unique strategy with potential for broader applications in gout management and arthritic disease treatment.

Unraveling Serial Degradation Pathways of Supported Catalysts through Reliable Electrochemical Liquid-Cell TEM Analysis.

Electrochemical liquid-cell transmission electron microscopy (e-LCTEM) offers great potential for investigating the structural dynamics of nanomaterials during electrochemical reactions. However, challenges arise from the difficulty in achieving the optimal electrolyte thickness, leading to inconsistent electrochemical responses and limited spatial resolution. In this study, we present advanced e-LCTEM techniques tailored for tracking Pt/C degradation under electrochemical polarization at short intervals with high spatial resolution. Our innovative approach combines microfabrication-based sample preparation with in situ control of electrolyte thickness, ensuring reliable electrochemical signal acquisition and direct observation of sequential catalyst degradation. Quantitative imaging analyses conducted at both global areas and single-particle levels unveil a distinctive degradation mechanism primarily driven by nanoparticle migrations. Smaller nanoparticles exhibit a higher susceptibility to migration, leading to coalescence and final detachment in series. This migration-gated degradation mechanism provides a new perspective on the size-dependent durability of supported nanoparticles, complementing the prevailing explanation centered on the size-dependent dissolution kinetics of nanoparticles.

Increasing the dual-enzyme cascade biocatalysis efficiency and stability of metal-organic frameworks via one-step coimmobilization for visual detection of glucose.

In biosensing analysis, the activity of enzyme systems is limited by their fragility, and substrates catalyzed by monoenzymes tend to undergo spontaneous decomposition during ineffective mass transfer processes. In this study, we propose a novel strategy to encapsulate the glucose oxidase and horseradish peroxidase (GOx&HRP) cascade catalytic system within the hydrophilic zeolite imidazole framework ZIF-90. By leveraging the specific pore structure of ZIF-90, we effectively immobilized GOx and HRP molecules in their three-dimensional conformations, which improved the catalytic activity of the encapsulated enzymes compared with that of free GOx and HRP in various harsh environments. Additionally, our strategy reduced the occurrence of ineffective mass transfer and enhanced the sensitivity of the biosensor through an enzyme cascade system. When this biosensor was applied to serum samples containing complex biological matrices, the degradation of GOx&HRP by various proteases and the surface adsorption of diverse biomolecules were effectively prevented, thereby generating stable and reliable signals of glucose levels. The sensor shows remarkable sensitivity and selectivity for determining glucose concentrations ranging from 0 to 2.5 μg ml-1, with a detection limit as low as 0.034 μg ml-1. Furthermore, we developed a paper-based colorimetric sensor utilizing GOx&HRP@ZIF-90 integrated with a smartphone platform for the visual detection of blood glucose.

Searching for HI around MHONGOOSE galaxies via spectral stacking

The observed star formation rates of galaxies in the Local Universe suggests that they are replenishing their gas reservoir across cosmic time. Cosmological simulations predict that this accretion of fresh gas can occur in a hot or a cold mode, yet the existence of low column density (∼1017 cm−2) neutral atomic hydrogen (HI) tracing the cold mode has not been unambiguously confirmed by observations. We present the application of unconstrained spectral stacking to attempt to detect the emission from this HI in the circumgalactic medium (CGM) and intergalactic medium (IGM) of six nearby star-forming galaxies from the MHONGOOSE sample for which full-depth observations are available. Our stacking procedure consists of a standard spectral stacking algorithm coupled with a one-dimensional spectral line finder designed to extract a reliable signal close to the noise level. In agreement with previous studies, we find that the amount of signal detected outside the HI disk is much smaller than implied by simulations. Furthermore, the column density limit that we achieve via stacking (∼1017 cm−2) suggests that direct detection of the neutral CGM and IGM component might be challenging in the future, even with the next generation of radio telescopes.

INSIHGT: an accessible multi-scale, multi-modal 3D spatial biology platform

AbstractBiological systems are complex, encompassing intertwined spatial, molecular and functional features. However, methodological constraints limit the completeness of information that can be extracted. Here, we report the development of INSIHGT, a non-destructive, accessible three-dimensional (3D) spatial biology method utilizing superchaotropes and host-guest chemistry to achieve homogeneous, deep penetration of macromolecular probes up to centimeter scales, providing reliable semi-quantitative signals throughout the tissue volume. Diverse antigens, mRNAs, neurotransmitters, and post-translational modifications are well-preserved and simultaneously visualized. INSIHGT also allows multi-round, highly multiplexed 3D molecular probing and is compatible with downstream traditional histology and nucleic acid sequencing. With INSIHGT, we map undescribed podocyte-to-parietal epithelial cell microfilaments in mouse glomeruli and neurofilament-intensive inclusion bodies in the human cerebellum, and identify NPY-proximal cell types defined by spatial morpho-proteomics in mouse hypothalamus. We anticipate that INSIHGT can form the foundations for 3D spatial multi-omics technology development and holistic systems biology studies.

Rapid non-invasive measurement of mitochondrial oxygen tension after microneedle pre-treatment: a feasibility study in human volunteers.

Mitochondrial oxygen tension (MitoPO2) is a promising novel non-invasive bedside marker of circulatory shock and is associated with organ failure. The measurement of mitoPO2 requires the topical application of 5-aminolevulinc acid (ALA) to induce sufficient concentrations of the fluorescent protein protoporphyrin-IX within (epi)dermal cells. Currently, its clinical potential in guiding resuscitation therapies is limited by the long induction time prior to obtaining a reliable measurement signal. We investigated whether microneedle pre-treatment of the skin before ALA application allows for earlier measurement of mitoPO2 in healthy human volunteers. 9 healthy human volunteers were included as part of physiological feasibility study. All participants had two ALA-care plasters administered on the chest after cleaning. One part of the skin was pretreated with microneedling, which perforates the epidermis with a depth of 0.30mm. The time-to-sufficient signal was recorded for both untreated and microneedled ALA-care application. After induction mitoPO2 was varied using different FiO2 and the agreement between untreated and microneedled skin for mitoPO2 and mitoVO2 was recorded. Pre-treatment with microneedling induced reliable signal at 2 (IQR: 2-2) hours after topical ALA administration compared to 3 (IQR: 3-4) hours without pre-treatment (p = 0.02). The intraclass correlation of mitoPO2 simultaneously measured on microneedling and untreated skin was 0.892 (95%CI 0.821-0.936). MitoVO2 showed poor agreement between untreated and microneedling with an ICC of 0.316 (0.04-0.55). We demonstrate that pre-treatment with microneedling before topical application of 5-aminolevulinic acid enables obtaining a reliable and accurate mitoPO2 signal at least an hour faster than on untreated skin in our population of human volunteers. This potentially increases the applicability of mitoPO2 measurements in acute settings.Trial registration number: R21.106 (01-01-2022).

Lignin nanoparticle/MXene-based conductive hydrogel with mechanical robustness and strain-sensitivity property via rapid self-gelation process towards flexible sensor.

Conductive hydrogels have been showcased with substantial potential for soft wearable devices. However, the tedious preparation process and poor trade-off among overall properties, i.e., mechanical and sensing performance, severely limits flexibility of electronics' applications. Herein, we have developed a rapid self-gelation system for achieving high-performance conductive hydrogel within several minutes at ambient condition. The rapid gelation mechanism is attributed to the hydroxyl radical species generated with the help of lignin nanoparticle-Mn+1 (Ag+, Ca2+, Mg2+, Al3+ and Fe3+) based on reversible redox reaction and MXene activization effect. By adjusting the material components, the cross-linked polymer network can be highly strengthened by multiple physical interactions and nano-reinforcement, strongly supporting the mechanical performance. Comparatively, Fe3+-based conductive hydrogel displays integrated merits of mechanical robustness, high stretchability and good electrical conductivity. Meanwhile, due to excellent mechanical and electrical performance, such hydrogel-based sensor possesses good sensing performance, i.e., high sensitivity (maximum GF: 1.08), cyclic reliability and wide work window (0-860%), displaying promising application in strain-induced detection. Our sensors also produce stable and reliable signal output for signature/vocal recognition. Apparently, the strategy developed herein sets up an innovative concept for highly-efficient green fabricating advanced hydrogel materials for emerging wearable electronics.

Stress Wave Characteristics and Damage Analysis of the Helicopter Tail Drive Shaft with the High-Speed Projectile Impact

The tail drive shaft is easily hit by the ground antiaircraft machine gun in low-altitude helicopter combat, resulting in projectile penetration damage and directly jeopardizing the helicopter’s safety during flight. The projectile penetration damage will cause elastic–plastic deformation and failure damage to the tail drive shaft, and excite high-frequency stress waves suitable for projectile impact monitoring. To examine the effects of different impact parameters on the stress wave characteristics and damage from the tail drive shaft during projectile impact, the LS-DYNA is used to establish a dynamic model of projectile impact on the tail drive shaft. The passive monitoring experiment of projectile impact on the tail drive shaft is carried out based on the PZT piezoelectric sensor. It is concluded that both methods can obtain reliable stress wave signals and damage conditions through the comparison of experimental and simulation results. Then, the wavelet transform and short-time Fourier transform three-dimensional time–frequency are used to select the best frequency band for extracting the stress wave eigenvalues, along with the statistics and analysis of the stress wave characteristic values and damage degree under different impact parameters. The results show that the impact stress waveforms and high-frequency components are significantly different with the change in projectile impact parameters. There are significant differences among different impact parameters on the first trough amplitude, the two peak time intervals, the kurtosis factor, and the bullet hole damage generation laws. The functional relationship between the projectile impact parameters and the characteristic parameters of the stress wave, as well as the damage degree, are established. The research conclusion can provide theoretical reference and data support for projectile impact monitoring and damage assessment of the helicopter tail drive shaft.

Outcome of IWGT workshop on transcriptomic biomarkers for genotoxicity: Key considerations for bioinformatics.

As a part of the International Workshop on Genotoxicity Testing (IWGT) in 2022, a workgroup was formed to evaluate the level of validation and regulatory acceptance of transcriptomic biomarkers that identify genotoxic substances. Several such biomarkers have been developed using various molecular techniques and computational approaches. Within the IWGT workgroup on transcriptomic biomarkers, bioinformatics was a central topic of discussion, focusing on the current approaches used to process the underlying molecular data to distill a reliable predictive signal; that is, a gene set that is indicative of genotoxicity and can then be used in later studies to predict potential DNA damaging properties for uncharacterized chemicals. While early studies used microarray data, a technological shift occurred in the past decade to incorporate modern transcriptome measuring techniques such as high-throughput transcriptomics, which in turn is based on high-throughput sequencing. Herein, we present the workgroup's review of the current bioinformatic approaches to identify genes comprising transcriptomic biomarkers. Within the context of regulatory toxicology, the reproducibility of a given analysis is critical. Therefore, the workgroup provides consensus recommendations on how to facilitate sufficient reporting of experimental parameters for the analytical procedures used in a transcriptomic biomarker study, including the recommendation to develop a biomarker-specific reporting module within the OECD Omics Reporting Framework.

Wearable Systems of Reconfigurable Microneedle Electrode Array for Subcutaneous Multiplexed Recording of Myoelectric and Electrochemical Signals.

The real-time monitoring of in vivo electrophysiological and biochemical signals provides critical insights into the activities of tissues and organs. As the activity and metabolic state of different sites in the muscle vary, multichannel detection is necessary to capture the functional state of the whole muscle, yet the access to the bio-information in subcutaneous space remained challenging. This work reports the development of a reconfigurable microneedle electrode array integrated system designed to achieve painless and minimally invasive monitoring of subcutaneous electromyogram (EMG), oxygen species, and pH through an array of thumbtack-shaped microneedle (TSMN) electrode. By assembling discrete TSMNs into an array, the system enables multi-parameter detection with single microneedle resolution. The PEDOT: PSS layer is electrochemically deposited on the TSMNs, enhancing their signal-sensing capabilities and electrochemical properties. Additionally, the design of the pogo pin interface ensures reliable signal transmission and stable device performance, while allowing flexible replacement of the TSMNs, which enhances system maintainability and longevity. Validation experiments conducted on in vivo animal models demonstrate the system's capability in real-time monitoring of muscle fatigue and indicators related to sciatic nerve injury. These results advance the development of wearable technologies for monitoring subcutaneous physiological and biochemical information for diagnosing neuromuscular disorders.

Enhancement of the signal resolution in aptamer assay upon target binding by employing DNA probes and dual fluorophores

In this study, we aimed to significantly enhance the resolution of aptamer assays by using DNA probes and dual fluorophores. The resolution is defined as the smallest change in the target concentration that causes a reliable and distinguishable signal change. Therefore, resolution enhancement in the aptamer assay ensures improved analytical performance. We first examined four aptamer-probe combinations in the aptamer assay and investigated the resolution by observing a percentage signal response difference (% ΔAAD/SYBR). A large % ΔAAD/SYBR means a discernable signal change for a certain concentration difference, which indicates a high-resolution assay. Consequently, significant resolution enhancement (approximately 3–7 times) was achieved using two DNA probes. The improved analytical performance of the resolution-enhanced aptamer assay was further demonstrated by a wide working range of quantification (i.e., 10−2–102 mg/L, four orders of magnitude), a regression curve with improved fitness, and a lower limit of detection (LOD) response (2–6 times lower).

Longitudinal changes in electrophysiology and widefield calcium imaging following electrode implantation

Objective. Intracortical microelectrode arrays often fail to deliver reliable signal quality over chronic recordings, and the effect of an implanted recording array on local neural circuits is not completely understood.Approach. In this work we examined the degree of correlation and the spatial dependence of that relationship between widefield calcium imaging and electrophysiology in awake mice from 4 to 44 d post-implantation. Both correlation maps and spike-triggered averaging (STA) are used to characterize the relationship.Main results. We find that calcium imaging and electrophysiological signal are highly correlated in all animals, however, spatial variability in the correlation is affected by inherent correlation in the calcium imaging signal. Some animals exhibit a high degree of apparent neuronal synchrony in the vicinity of the probe at 4 d, while more diversity of response is detected at later time points.Significance. Degree of synchrony appears to be related to the acute injury response to the implanted electrode, with later time points displaying less synchrony. STA may be used to uncover the diverse cortical connections of spiking units.

Self-assembly Pt hollow nanospheres for highly selective and ultrasensitive detection of dopamine

Abnormal concentration of dopamine, one critical neurotransmitter in central nervous system, causes several neurological diseases associated with behavioral responses and brain functions in human beings. Highly sensitive detection of dopamine is of great significance yet challengeable. In this work, Pt hollow nanospheres (Pt HNSs) with a uniform diameter of 30 nm were successfully synthesized in water by self-assembly method under room temperature. The fabricated Pt hollow/Nafion nanospheres modified glassy carbon electrode (Pt HNSS/Nafion/GCE) exhibited superior electrocatalytic performance, with peak currents 2.24 and 4.54 times higher than those of Nafion-modified glassy carbon electrode (Nafion/GCE) and bare glassy carbon electrode (GCE), respectively. Theoretical calculations indicate that dopamine has an adsorption energy of −3.18 eV on the Pt(111) surface, with an electron transfer of + 1.84 |e|, aligning with the 2-electron transfer mechanism. Furthermore, the low energy barrier observed during dopamine oxidation process suggests that the Pt(111) surface is highly favorable for dopamine oxidation. Meanwhile, Pt HNSS/Nafion/GCE electrochemical sensor exhibits highly sensitive and selective response in determination of dopamine ranging from 0.01 to 250 μM with low detection limits of 0.804 nM (S/N = 3). Moreover, the electrochemical sensor shows reliable signals in real test with great anti-interference and stability during the experiments, making it a promising candidate for applications in dopamine sensing.

Sparse Spike Feature Learning to Recognize Traceable Interictal Epileptiform Spikes.

Interictal epileptiform spikes (spikes) and epileptogenic focus are strongly correlated. However, partial spikes are insensitive to epileptogenic focus, which restricts epilepsy neurosurgery. Therefore, identifying spike subtypes that are strongly associated with epileptogenic focus (traceable spikes) could facilitate their use as reliable signal sources for accurately tracing epileptogenic focus. However, the sparse firing phenomenon in the transmission of intracranial neuronal discharges leads to differences within spikes that cannot be observed visually. Therefore, neuro-electro-physiologists are unable to identify traceable spikes that could accurately locate epileptogenic focus. Herein, we propose a novel sparse spike feature learning method to recognize traceable spikes and extract discrimination information related to epileptogenic focus. First, a multilevel eigensystem feature representation was determined based on a multilevel feature representation module to express the intrinsic properties of a spike. Second, the sparse feature learning module expressed the sparse spike multi-domain context feature representation to extract sparse spike feature representations. Among them, a sparse spike encoding strategy was implemented to effectively simulate the sparse firing phenomenon for the accurate encoding of the activity of intracranial neurosources. The sensitivity of the proposed method was 97.1%, demonstrating its effectiveness and significant efficiency relative to other state-of-the-art methods.

Clustered temporal memory networks: A hybrid approach for signal strength prediction

The rapid expansion of 5G networks has revolutionized mobile communication by offering unprecedented speed, low-latency connections, and the ability to support vast numbers of connected devices. However, these advancements bring new challenges in maintaining consistent and reliable signal strength, critical for ensuring optimal Quality of Service (QoS). Traditional models, such as ARIMA, Random Forest (RF), and K-means clustering, struggle to capture the complex, nonlinear, and dynamic behaviour of 5G networks, leading to suboptimal prediction accuracy. In this study, we propose a novel hybrid model, Clustered Temporal Memory Networks (CTMN), which integrates DBSCAN clustering with Long Short-Term Memory (LSTM) networks to improve signal strength prediction in mobile networks. The CTMN model combines DBSCAN's ability to handle spatial variability and outliers in 5G data, combined with LSTM's capacity for modelling long-term dependencies and nonlinear time-series patterns. Our empirical analysis demonstrates that CTMN outperforms traditional methods, achieving up to a 20.82% improvement in prediction accuracy across key performance metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). These findings indicate that CTMN provides a scalable, robust solution for enhancing signal strength prediction and optimizing network performance in next-generation mobile networks.

The Utility of Visual and Olfactory Maize Leaf Cues in Host Finding by Adult Spodoptera frugiperda (Lepidoptera: Noctuidae).

The fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae) (FAW), is an invasive and destructive polyphagous pest that poses a significant threat to global agricultural production. The FAW mainly damages maize, with a particular preference for V3-V5 (third to fifth leaf collar) plant stages in northern China. How the FAW moth precisely locates maize plants in the V3-V5 stage at night remains unclear. The aims of this study were to evaluate the visual and olfactory cues used by the FAW to identify its host plant, maize, in order to select attractants with better trapping efficacy. Hyperspectral analysis of maize plants at different growth stages using the ASD Fieldspec 4 spectrometer was performed using mimics (moths or maize leaves sealed with transparent plastic sheets) and black cloth-covered plants for single visual and single olfactory attraction experiments. Gas chromatography-mass spectrometry (GC-MS) was used to analyze volatiles emitted from V3-V5 stage maize leaves. Volatile organic chemicals (VOCs) were screened using electroantennography (EAG) and Y-tube. Attractor efficacy was validated using mimics + VOCs. Results showed very little variance in the spectral reflectance curve of the maize at different growth stages. Fifteen VOCs were identified in the V3-V5 stage leaves of three different maize varieties, of which cis-3-hexenyl acetate and myrcene were found in relatively high concentrations in these maize varieties. The frequency of visits attracted by single visual stimuli was significantly lower than that attracted by single olfactory or olfactory + visual cues. The attractiveness of foliar cis-3-hexenyl acetate increased as its concentration decreased. The combination of mimics + cis-3-hexenyl acetate (1 ng/μL) increased host detection efficiency and stimulated mating behavior. These results indicate that the nocturnal insect FAW primarily uses olfactory cues for host identification, with visual cues serving as a complementary modality. The synergistic effect of olfactory and visual cues increases the efficiency of host recognition. We found that cis-3-hexenol acetate at a concentration from maize leaves is a reliable olfactory signal for the FAW. When using host plant VOCs as attractants to control adult FAWs, the role of visual cues must be considered.

Relay aided UWOC-SMF-FSO based hybrid link for underwater wireless optical sensor network

The Internet of Underwater Things (IoUTs) connects underwater devices to communicate, sense surroundings, and transmit data. Acoustic communication faces bandwidth limitations, making underwater wireless optical communication-free space optics (UWOC-FSO) hybrid systems a promising alternative. However, maintaining sufficient power budget and signal-to-noise ratio (SNR) is a challenging task, making wavelength translation (WT) from visible to infrared (IR) at the water-fiber-air interface crucial for reliable signal transmission. In this paper, we propose an underwater wireless optical communication-single mode fiber-free space optics (UWOC-SMF-FSO) hybrid link based on a photo-detection, remodulate, and forwarding (PRF) relay and intensity modulation-direct detection (IM/DD) scheme for 8 × 1-Gb/s underwater optical wireless sensor network (UWOSN). The PRF relay is installed at a remotely operated underwater vehicle (ROV) to perform WT from visible range to IR. The performance of the sensors is analyzed for different water bodies and weather conditions of underwater and free space optics channels, respectively using metrics of Bit-error rate (BER) and Quality factor (Q-factor) employing Gamma–Gamma channel model. The simulation results show that forward-error correction (FEC) target BER of 10−4 for sensors is achieved under different water bodies and weather conditions. The results obtained from this study show that the proposed UWOC-SMF-FSO hybrid link is flexible, resilient to adverse channel effects, and can be a potential candidate for implementation of high-speed long-distance future IoUTs.