Conventional Analysis Methods Research Articles

Advancing predictive maintenance: a deep learning approach to sensor and event-log data fusion

Purpose This study aims to introduce an innovative approach to predictive maintenance by integrating time-series sensor data with event logs, leveraging the synergistic potential of deep learning models. The primary goal is to enhance the accuracy of equipment failure predictions, thereby minimizing operational downtime. Design/methodology/approach The methodology uses a dual-model architecture, combining the patch time series transformer (PatchTST) model for analyzing time-series sensor data and bidirectional encoder representations from transformers for processing textual event log data. Two distinct fusion strategies, namely, early and late fusion, are explored to integrate these data sources effectively. The early fusion approach merges data at the initial stages of processing, while late fusion combines model outputs toward the end. This research conducts thorough experiments using real-world data from wind turbines to validate the approach. Findings The results demonstrate a significant improvement in fault prediction accuracy, with early fusion strategies outperforming traditional methods by 2.6% to 16.9%. Late fusion strategies, while more stable, underscore the benefit of integrating diverse data types for predictive maintenance. The study provides empirical evidence of the superiority of the fusion-based methodology over singular data source approaches. Originality/value This research is distinguished by its novel fusion-based approach to predictive maintenance, marking a departure from conventional single-source data analysis methods. By incorporating both time-series sensor data and textual event logs, the study unveils a comprehensive and effective strategy for fault prediction, paving the way for future advancements in the field.

IMAX FRET (Information Maximized FRET) for Multipoint Single-Molecule Structural Analysis.

Understanding the structure of biomolecules is vital for deciphering their roles in biological systems. Single-molecule techniques have emerged as alternatives to conventional ensemble structure analysis methods for uncovering new biology in molecular dynamics and interaction studies, yet only limited structural information could be obtained experimentally. Here, we address this challenge by introducing iMAX FRET, a one-pot method that allows ab initio 3D profiling of individual molecules using two-color FRET measurements. Through the stochastic exchange of fluorescent weak binders, iMAX FRET simultaneously assesses multiple distances on a biomolecule within a few minutes, which can then be used to reconstruct the coordinates of up to four points in each molecule, allowing structure-based inference. We demonstrate the 3D reconstruction of DNA nanostructures, protein quaternary structures, and conformational changes in proteins. With iMAX FRET, we provide a powerful approach to advance the understanding of biomolecular structure by expanding conventional FRET analysis to three dimensions.

Robust Methods for Assessing the Characteristics of Locomotor Activity Based on Markerless Video Capture Data

Introduction. Analysis of locomotor activity is essential in a number of biomedical and pharmacological research designs, as well as environmental monitoring. The movement trajectories of biological objects can be represented by time series exhibiting a complex multicomponent structure and non-stationary dynamics, thus limiting the effectiveness of conventional correlation and spectral time series analysis methods. Recordings obtained using markerless technologies are typically characterized by enhanced noise levels, including both instrumental noise and anomalous errors associated with false estimates of the location of the points of interest, as well as gaps in the trajectories, promoting an urgent need in the development of robust methods to assess the characteristics of locomotor activity.Aim. Development of robust methods for assessing the characteristics of locomotor activity capable of efficient processing of noisy recordings obtained by markerless video-based motion capture systems.Materials and methods. In order to assess the characteristics of locomotor activity, the relative movements of body parts of laboratory animals were analyzed using the stability metrics of the mutual dynamics of their trajectories, their relative delays, as well as the relative duration of the recording fragments when relatively stable mutual dynamics could be observed. The local maxima of the cross-correlation function of two body fragments, the minima of the standard deviation of the difference between their Hilbert phases, as well as their relative delays, were used as the metrics of mutual dynamics.Results. The considered phase metrics were shown to explicitly reflect changes in locomotor activity, while the assessment of time delays using phase metric was shown to be prone to periodic error. The above limitation could be largely overcome using the correlation metrics, assuming that phase and correlation metrics could be combined.Conclusion. The proposed robust methods provide stable estimates of the characteristics of locomotor activity based on markerless video capture recordings, altogether increasing the efficiency of diagnostic procedures and assessment of the therapeutic effect during rehabilitation.

The Open SprayBot: A high-throughput paper spray mass spectrometry platform for disease screening

Newborn disease screening increases survival, improves quality of life and reduces treatment costs for healthcare systems. Mass spectrometry (MS) is an effective method for metabolic screening. However, conventional analytical methods require biofluid handling and cooling conditions during transport, making the logistics difficult and expensive, especially for remote regions. ’Paper-spray’ (PS) ionization generates a charged solvent spray from samples deposited on paper strips. Therefore, samples can be applied on a suitable matrix and shipped as dried spots to diagnostic laboratories with standard postal or messenger services. We built a robotic platform, the ’Open SprayBot’, to automatically analyze paper-deposited samples via PS-MS and increase the sample throughput. The system is operated via RUMBA32 and Arduino Mega boards. A commercial syringe pump and power supply provide solvent application and electrical current required for PS-MS. The usability of the Open SprayBot was demonstrated by quantifying palmitoyl-l-carnitine, a common biomarker in newborn screening.

Quantification of membrane fluidity in bacteria using TIR-FCS

Plasma membrane fluidity is an important phenotypic feature that regulates the diffusion, function, and folding of transmembrane and membrane-associated proteins. In bacterial cells, variations in membrane fluidity are known to affect respiration, transport, and antibiotic resistance. Membrane fluidity must therefore be tightly regulated to adapt to environmental variations and stresses such as temperature fluctuations or osmotic shocks. Quantitative investigation of bacterial membrane fluidity has been, however, limited due to the lack of available tools, primarily due to the small size and membrane curvature of bacteria that preclude most conventional analysis methods used in eukaryotes. Here, we develop an assay based on total internal reflection-fluorescence correlation spectroscopy (TIR-FCS) to directly measure membrane fluidity in live bacteria via the diffusivity of fluorescent membrane markers. With simulations validated by experiments, we could determine how the small size, high curvature, and geometry of bacteria affect diffusion measurements and correct subsequent measurements for unbiased diffusion coefficient estimation. We used this assay to quantify the fluidity of the cytoplasmic membranes of the Gram-positive bacteria Bacillus subtilis (rod-shaped) and Staphylococcus aureus (coccus) at high (37°C) and low (20°C) temperatures in a steady state and in response to a cold shock, caused by a shift from high to low temperature. The steady-state fluidity was lower at 20°C than at 37°C, yet differed between B. subtilis and S. aureus at 37°C. Upon cold shock, the membrane fluidity decreased further below the steady-state fluidity at 20°C and recovered within 30 min in both bacterial species. Our minimally invasive assay opens up exciting perspectives for the study of a wide range of phenomena affecting the bacterial membrane, from disruption by chemicals or antibiotics to viral infection or change in nutrient availability.

Rapid Measurement of Antioxidant Properties of Dendrobium officinale Using Near-Infrared Spectroscopy and Chemometrics.

Dendrobium officinale (D. officinale), often used as a dual-use plant with herbal medicine and food applications, has attracted considerable attention for health-benefiting components and wide economic value. The antioxidant ability of D. officinale is of great significance to ensure its health care value and safeguard consumers' interests. However, the common analytical methods for evaluating the antioxidant ability of D. officinale are time-consuming, laborious, and costly. In this study, near-infrared (NIR) spectroscopy and chemometrics were employed to establish a rapid and accurate method for the determination of 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) scavenging capacity, 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging capacity, and ferric reducing antioxidant power (FRAP) in D. officinale. The quantitative models were developed based on the partial least squares (PLS) algorithm. Two wavelength selection methods, namely the genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) method, were used for model optimization. The CARS-PLS models exhibited superior predictive performance compared to other PLS models. The root mean square errors of cross-validation (RMSECVs) for ABTS, FRAP, and DPPH were 0.44%, 2.64 μmol/L, and 2.06%, respectively. The results demonstrated the potential application of NIR spectroscopy combined with the CARS-PLS model for the rapid prediction of antioxidant activity in D. officinale. This method can serve as an alternative to conventional analytical methods for efficiently quantifying the antioxidant properties in D. officinale.

Transition experiences of patients with post stroke dysphagia and family caregivers: A longitudinal, qualitative study.

Stroke patients with dysphagia and family caregivers will experience multiple transitions during the whole process of the disease and various nursing needs will be generated. There is a lack of knowledge about their experiences at different transition stages. Thus, we aimed to explore the transition experiences of patients with post stroke dysphagia and family caregivers from admission to discharge home. A semi-structured interview based on Meleis's transition theory was used during hospitalization and telephone follow-up interviews were conducted in the first, third, and sixth month after the diagnosis of dysphagia. Interview transcripts were analyzed using the conventional content analysis method. A total of 17 participants enrolled in the first face-to-face interview, 16 participants took part in the first month's telephone follow-up interview, 14 participants in the third month, and 12 participants in the sixth month. The transition experiences of patients with post stroke dysphagia and family caregivers could be summarized into three themes: (1)transition from onset to admission; (2)transition from discharge to other rehabilitation institutions; and (3)transition from discharge to home. Each theme had identified interrelated subthemes. The experiences of patients with post stroke dysphagia and family caregivers during transition are a dynamic process with enormous challenges in each phase. Collaboration with health care professionals, follow-up support after discharge, and available community and social support should be integrated into transitional nursing to help patients facilitate their transition.

Care Bermuda, families of the patients with chronic mental disorders in Iran surrounded by psychosocial problems and needs: a qualitative study

Background: A mental disorder is characterized by a clinically significant impairment of cognition, emotion regulation, or behavior. As a result of the shift in care from medical centers and hospitals to home care, we now see a change in the treatment of patients with chronic mental disorders. Consequently, families have become the main support system in the progressive care of these patients, leading to psychological and social problems. The current qualitative study investigated the social and psychological health needs and problems of family caregivers of patients with chronic mental disorders in Iran’s cultural and social context. Methods: This was a content analysis qualitative study. The study was conducted in three psychiatric hospitals in Farabi, Noor, Modares. Purposive sampling was done and continued until data saturation. Semi-structured, face-to-face, and individual interviews were conducted with 49 participants (15 family caregivers of patients with CMD and 34 members of the mental health care team). Data analysis was done using the conventional content analysis method. Results: Eight hundred seventy-five primary codes were obtained, which were classified into 10 subcategories and 3 main categories of ʻhealth challenges of caregiverʼ, ʻconfused concept of careʼ and “the need for a coherent support system. Conclusion: In Iranian society, after the patient is discharged from the hospital or care center, family members will change their role to the most important caregivers of these patients. The psychological and social health of these caregivers is destroyed because of the problems they have in providing care for their patients and their needs, which are not met.

Building functional networks for complex response analysis in systems of coupled nonlinear oscillators

Some aspects of engineering dynamics, such as nonlinearities and transient motion of many interconnected parts, remain difficult to handle today. To comply with increasing demands on resilience and safety, the dynamics of large machines need to be better understood. Complex network methods, already present in many scientific disciplines, provide a tool set complementary to conventional methods of system analysis. This work aims at providing a new, function-based view on mechanical systems by generating functional networks. To this end, a network algorithm is applied to sets of cyclically coupled Duffing oscillators as a common example of a complex nonlinear mechanical system. In the functional network, each node represents an oscillator while the direction of the network edges represents a functional coupling. Results show that the network method is capable of identifying dynamical transitions and synchronization between components, as well as determining the number of different states present within a system. Additionally, the time evolution of the component interactions, especially in response to a disturbance, is studied via a sliding-window approach. The results of this analysis might hopefully open new ways for a more efficient system analysis through optional sensor placement, and for effective countermeasures against unwanted dynamics through improved analysis of transient dynamics.

The experiences of patients with COVID-19 and their relatives from receiving professional home care nursing: a qualitative content analysis

BackgroundTo overcome of patients with COVID-19 over the capacity of hospitals and mild to moderate severity of the disease in most cases, the World Health Organization and the Centers for Disease Control and Prevention in the United States, recommend home care for these patients. Receiving care at home will face challenges that can be context-based, especially in crises like the Coronavirus pandemic. The present study aimed to describe the experiences of patients with COVID-19 and their relatives from receiving professional home care nursing.MethodsThis study was conducted using a qualitative content analysis method. Nine participants with COVID-19 who were receiving home care nursing in Semnan participated in this study. The purposive sampling method was used. Sampling continued until no new categories appeared, meaning the category’s theoretical saturation. Deep and semi-structured interviews were used to collect data based on the research question. Data was analyzed using the conventional content analysis method using Graneheim and Lundman’s approach.ResultsAfter analyzing the interviews and comparing codes based on similarities and differences, three main themes, 11 categories, and 30 subcategories were identified. The main themes included “The value of home care” (personalization of care, being economical, providing intellectual security, and reducing the concern of family), “Comprehensive care” (professional commitment, empathy, mastery in care, and patronage), and “Care challenges” (cultural barriers, inadequate services, and lack of information about costs and conditions).ConclusionThe patients with COVID-19 who received professional nursing care at home mentioned some challenges, such as the caregiver not being of the same sex as the patient, delay in receiving the service, the inadequacy of the centers, the limitation of the right to choose the care provider, and insufficient information about the cost of services received before receiving each care.

Ion-selective paper-based chromogenic strip and electrochemical sensor for the detection of ammonium ions

The fraudulent practice of adding ammonium salts to milk in order to enhance the nitrogen content has serious health implications including renal failure. Ammonium ion detection has been targeted through the conventional analytical methods however, lack of portability and complex operation limits their use for field applications. In this scenario, paper-based test strips and electrochemical sensors can provide strategies for point-of-test applications. Here, an ion-selective paper-based chromogenic strip and an electrochemical sensor has been developed for detection and quantification of ammonium ions. The developed paper-based chromogenic strip showed detection limit of 0.008 % (w/v) for ammonium ions, whereas, electrochemical sensor showed an LOD of 0.0062 ± 0.0023 % (w/v) with a sensitivity of 1.6 × 10−5 A.% −1.mm−2. The developed paper-based chromogenic strip and electrochemical sensor can be employed by regulatory bodies and dairy industries to ensure the safety and quality of milk.

Numerical Investigation of Seismic Behaviour for a Flexible Cantilever Retaining Wall with Cohesive Backfill

In the seismic design of flexible cantilever walls retaining cohesive backfill soil, the common practice is to neglect the cohesion effect. Dynamic lateral earth pressure is typically evaluated based on approaches primarily intended for cohesionless soils or through analytical pseudo-static methods. Nevertheless, both experimental and theoretical evidence has demonstrated significant effects due to soil cohesion that are not accounted for by these methods. This study involved finite element modeling (FE) of a flexible cantilever wall with a height of 5.4m, supporting homogeneous cohesive backfill under initial static and seismic loadings. The calculated active earth thrust was then compared with values obtained experimentally and through conventional analytical methods. The obtained results indicate that the presence of soil cohesion significantly reduces seismic demands on flexible cantilever retaining walls, resulting in a substantial reduction of seismic active earth pressures and total seismic thrust by up to 50% and 52%, respectively. It enhances also the overall stability of the system by shifting the point of application of seismic thrust toward the base of the wall, thereby increasing the safety margin. In addition, it significantly decreases the wall displacement at the stem top, with reductions of up to 104% compared with the case involving cohesionless backfill. It was observed that the conventional methods recommended by some seismic regulations largely underestimate seismic active pressure.

Qualitative exploration of sexual dysfunction and associated coping strategies among Iranian prostate cancer survivors.

Our understanding of the experiences of prostate cancer survivors regarding their sexual life and related issues remains limited. Therefore, this study aimed to explore sexual dysfunction and associated coping strategies among Iranian prostate cancer survivors. A qualitative study was undertaken. Participants were 15 Iranian prostate cancer survivors chosen using purposeful sampling. Data collection involved conducting in-depth semi-structured interviews, followed by the utilization of the conventional qualitative content analysis method for data analysis. Three themes were developed: (a) suspension of sexual life-treatment for prostate cancer significantly impacted participants' sexual lives; (b) emotional resilience and psychological coping strategies-various psychological strategies were used to tackle sexual dysfunction; (c) efforts to regain sexual function-several strategies were applied to enhance sexual performance. Our study findings provide insights into the experiences of prostate cancer survivors and subsequent shifts in their sexual dynamics and coping with the disease. Healthcare providers should actively identify patients' concerns and develop culturally tailored care strategies to address sexual challenges and improve coping among prostate cancer survivors.

Magnetic anisotropy in heterogeneous amorphous thin films: insights from thickness- and temperature-driven spin-reorientation

Magnetization orientation in thin films is intricately influenced by multiple anisotropy components, with the dominant anisotropy serving as a key determinant. This complexity becomes particularly intriguing when considering thin films composed of subnanometer-scale heterogeneous amorphous structures. Our investigation builds upon this foundation, specifically focusing on the Fe–Ni–B–Nb alloy system, known for its moderate glass-forming ability and susceptibility to nanocrystallization. In this study, we present thickness- and temperature-driven spin-reorientation (SRT) transition, attributed to competing magnetic anisotropy energies in thin films featuring a heterogeneous amorphous structure. Thermogravimetric investigations unveiled a unique heterogeneous amorphous structure, a revelation unattainable through conventional structural analysis methods. The observed spontaneous perpendicular magnetization in amorphous films, as evidenced by transcritical hysteresis loops and magnetic stripe domains, is ascribed to the pronounced residual stress arising from the substantial magnetostriction of the alloy system. The temperature-driven SRT is correlated to the order-disorder magnetic transition of the heterogeneous amorphous phase, characterized by a Curie temperature of ∼225 K. This transformative magnetic state of the heterogeneous amorphous matrix limits the exchange interaction among the densely distributed α-Fe nuclei regions, ultimately governing the dynamic magnetic responses with varying temperature. This work provides valuable insights into the dynamic magnetic orientation of thin films, especially those with heterogeneous amorphous structures, contributing to the broader understanding of the underlying mechanisms of magnetization reversals.

Antecedents of Spiritual Health Affecting Family Management and Sexual Relationships of Couples: A Conventional Content Analysis

Background: Spiritual Health (SH) is the most meaningful and universal part of health affecting all human dimensions functions. Given that community health depends on the health of the family environment, Islam pays special attention to the basic foundation of the family and its persistence. Therefore, this qualitative study aimed to determine the antecedents of SH in Muslim couples according to Islamic sources. Methods: To collect the required data, some keywords, including “spiritual health”, “spirituality”, “spouses”, “couples”, and “Islam” were searched both in Persian and Arabic in Google Scholar, Noormags, SID, and Magiran databases in 1980-2023. After examining 37 documents, the conventional content analysis method was adopted to determine the antecedents of SH. Results: The 139 extracted codes were then classified into six categories (affecting the family management and their sexual, spiritual, behavioral, emotional, and cognitive relations). This paper elaborates on the antecedents of SH “affecting the family management”, and “sexual relationships” of couples. The first category includes four subcategories, “family boundaries and management”, “mutual and exclusive rights”, “planning”, and “cooperation and division of labor”. The second includes five subcategories, “encouragement to marry with trust in God”, “having offspring”, “preparation and contextualization”, “request and response”, and “infidelity prevention”. Conclusion: Both categories of “affecting the family management” and “sexual relationships” affect the lives of Muslim couples as antecedents and consequences of the concept of SH. It is suggested to perform more research by considering the texts of Sunni scholars.

Composition and influencing factors of professionals' capacity in public health emergency rescues: a qualitative study.

To explore the composition and influencing factors of professionals' capacity in public health emergency rescues. A descriptive qualitative design was used in this study. Medical workers, managers, and members of an emergency rescue team in Hangzhou, Zhejiang, were recruited for participation through a purposive sampling method. The data were collected using semi-structured interviews and analyzed using a conventional content analysis method. A total of 2 themes and 13 sub-themes emerged from the analysis: ability composition (knowledge reserve, early warning assessment, information reporting, emergency response, self-protection, personal ability, coordination and cooperation, health education) and influencing factors (educational background, region, experience, hospital level, human resources, and financial investment). These findings offer a basis for the construction of a related indicator system and provide a reference for relevant departments to further optimize their emergency education and training, strengthen their emergency drills, and improve their emergency rescue abilities. The findings indicate that it is necessary to pay attention to the construction of an emergency rescue team, adjust the ratio of personnel, improve their remuneration, and promote work enthusiasm to improve the emergency rescue ability of an organization.

Integrating security in hazard analysis using STPA-Sec and GSPN: A case study of automatic emergency braking system

Hazard analysis is a vital step in developing intelligent connected vehicles, aiming to eliminate or control hazards in the initial stages of system development and to provide theoretical support for the system’s safety design. However, conventional hazard analysis methods, such as Fault Tree Analysis and Failure Mode and Effects Analysis, suffer from two shortcomings: they do not account for the impact of cybersecurity factors on system safety and do not provide sufficient quantification of hazard scenarios. To this end, we propose a quantifiable hazard analysis method with security consideration, which integrates System Theoretic Process Analysis for Security (STPA-Sec) and Generalized Stochastic Petri Net (GSPN), supporting the extraction, modeling, and quantification of hazards. Specifically, we employ STPA-Sec for qualitative analysis to identify causal scenarios, safety requirements, security requirements, and the corresponding mitigations. Then, based on the identified causal scenarios, a GSPN model is established to quantify system-level hazards. A case study on a real open-source test vehicle demonstrates that the proposed method not only offers a comprehensive analysis of hazards but also provides a quantitative assessment. Comparative assessments suggest that the proposed method exhibits an advantage in terms of analysis processes (integrating security) and results (quantification).

Effects by geothermal gradient on thermal response tests for boreholes

A thermal response test (TRT) on a borehole provides information needed in the design of ground heat exchangers for ground source heat pump systems. Conventional analysis of TRT data sets uses the late-time period to estimate the ground thermal conductivity and the effective borehole resistance. During this quasi-steady-state period, the transient average fluid temperature has a logarithmic linear trend, which is consistent with conventional heat transfer models that assume a uniform undisturbed ground temperature. As the depth of the borehole increases the undisturbed ground temperature increases with depth following the geothermal gradient. This paper focuses on how the geothermal gradient affects a TRT. As the geothermal gradient increases, the required time to reach the conventional logarithmic linear trend may increase beyond any practical testing duration in coaxial boreholes. Then, conventional analysis methods based on a quasi-steady-state period incorrectly estimate the ground thermal conductivity. The magnitude of this effect is controlled through a dimensionless parameter |qratio|, which includes the geothermal gradient and other test parameters. In place of conventional models, a transient model that includes the geothermal gradient and fluid thermal storage can estimate the ground thermal conductivity and local borehole resistance within the typical TRT testing duration.

USER PERCEPTION TOWARDS STOCK PRICE PREDICTION USING LINEAR REGRESSION MODEL

Stock market prediction is a critical area of research with profound implications for investors, financial analysts, and policymakers. This study explores the efficacy of linear regression analysis within the domain of business analytics for forecasting stock market movements. Leveraging historical stock prices and relevant economic indicators, we employ a rigorous methodology to construct and evaluate predictive models using linear regression techniques. Technological advancement increases the study on stock and share market industry. Decision making is enhanced by various statistical and machine learning algorithms. Enormous research work has been concentrated on the feature prediction of stock prices based on historical prices and volume. Performance measures are analyzed in this work with S&P 500 Index using statistical methods in Python environment. Results obtained in this study are superior than the existing methods. The conventional methods for financial market analysis are based on linear regression. This paper focuses on the best independent variables to predict the closing value of the stock market. This study is used to determine specific factors which are providing the most impact on the prediction of the closing price.

A Review of Fabrication Techniques and Optimization Strategies for Microbial Biosensors

Challenges of stability and specificity associated with early generation sensors necessitate the fabrication and optimization of microbial biosensors. More so, the global biosensors market size currently valued at USD25.5 billion in 2021 is expected to grow at a compound annual growth rate (CAGR) of 7.5% to USD36.7 billion in 2026. Microbial biosensors are bioanalytical systems that integrate microorganisms with a physical transducer to generate signals, thus, aiding the identification of analytes. The biosensors are fabricated through a series of steps comprising microbe selection, immobilization onto a matrix, microfabrication, calibration, and validation. The transducers integrated microorganisms generate quantifiable signals, enabling real-time monitoring of a diversity of analytes within food samples. The optimization strategies are scrutinized, with a particular focus on the integration of sundry nanoparticles, such as magnetic, gold, and quantum-dot nanoparticles, which enhance sensor performance. Distinct advantages offered by microbial biosensors promise to revolutionize food quality assessment via cost-effectiveness, rapid sample testing, and the ability to provide access to real-time data. Literature have highlighted certain limitations including interference from complex matrices, instability of microorganisms, and microbial lifespan. In assessing their economic importance, a comparative analysis is presented against conventional food analytical methods like ELISA, PCR, and HPLC; thus, highlighting the unique strengths of microbial biosensors. The future perspectives focus on the potential of the technology in addressing the need for continuous monitoring challenges, and research for further improvements in the biocompatibility of fabrication processes and long-term reusability.