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Fulltext Unilateral ankle dorsiflexor spasticity: an uncommon, disabling complication of transverse myelitis

Mazlan M, Hamzah N, Ramakrishnan K

Arch Med Sci, 2012 Nov 9;8(5):939-41.
PMID: 23185208 DOI: 10.5114/aoms.2012.28594
Electrophoresis and Quartz Crystal Microbalance Instrumentation to Sense Nanoplastics in Water

Lim WY, Lau EV, Ramakrishnan N

Anal Chem, 2024 Dec 10;96(49):19213-19219.
PMID: 39607411 DOI: 10.1021/acs.analchem.4c05466

We report a Technical Note on detecting nanoplastics in water samples through electrophoresis and quartz crystal microbalance (QCM) instrumentation. We conducted electrophoresis experiments by immersing a QCM in a sample of ultrapure water containing polyethylene (PE) nanoplastics. It was interesting to observe that nanoplastics were attracted toward the QCM and adhered to one side of the QCM electrode. The attached particles introduced mass loading to the QCM and were characterized by a decrease in resonance frequency of the crystal. Furthermore, when a small region around the center of electrode was alone exposed for direct contact in water and the rest of the electrode was masked using photoresist, the nanoplastics were concentrated only in the exposed electrode region, significantly enhancing detection sensitivity. To further investigate the applicability for real-life water samples, we experimented with the technique with readily available bottled drinking water and mineral water, where we spiked these water samples with nanoplastics. It was observed that the resonance frequency shifts were significantly larger for samples with nanoplastics compared to samples without nanoplastics. In addition, Raman spectroscopy and microscopy imaging were used to further confirm the presence and locations of nanoplastics on the electrode surface. This study highlights the combination of electrophoresis and QCM effectiveness in detecting nanoplastics across different water types and their potential for broader applications in environmental monitoring.
Optimizing Machine Learning Models for Accessible Early Cognitive Impairment Prediction: A Novel Cost-effective Model Selection Algorithm

Shubar AG, Ramakrishnan K, Ho CK

IEEE Access, 2024;12:180792-180814.
PMID: 39902153 DOI: 10.1109/access.2024.3505038

Cognitive impairment and dementia-related diseases develop several years before moderate or severe deterioration in cognitive function occurs. Nevertheless, most dementia cases, especially in low- and middle-income countries, remain undiagnosed because of limited access to affordable diagnostic tools. Additionally, the development of accessible tools for diagnosing and predicting cognitive impairment has not been extensively discussed in the literature. The objective of this study is to develop a cost-effective and highly accessible machine learning model to predict the risk of cognitive impairment for up to five years before clinical insight. We utilized easily accessible data from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) to train and evaluate various machine learning and deep learning models. A novel algorithm was developed to facilitate the selection of cost-effective models that offer high performance while minimizing development and operational costs. We conducted various assessments, including feature selection, time-series analyses, and external validation of the selected model. Our findings indicated that the Support Vector Machine (SVM) model was preferred over other high-performing neural network models because of its computational efficiency, achieving F2-scores of 0.828 in cross-validation and 0.750 in a generalizability test. Additionally, we found that demographic and historical health data are valuable for early prediction of cognitive impairment. This study demonstrates the potential of developing accessible solutions to predict cognitive impairment early using accurate and efficient machine learning models. Future interventions should consider creating cost-effective assessment tools to support global action plans and reduce the risk of cognitive impairment.
Fulltext Various ways of continuous intraocular pressure monitoring in glaucoma patients: a narrative review

Ramakrishnan, G., Che Hamzah, J., Sharanjeet-Kaur S.

Medicine & Health, 2019;14(2):17-29.
MyJurnal

Glaucoma is a group of neurodegenerative disease linked with imbalance in the aqueous humor flow due to resistance in the aqueous drainage system. This increases the intraocular pressure (IOP), which causes damage to the optic nerve head and leads to irreversible blindness. As IOP is the only treatable risk factor for glaucoma, its 24 hours biorhythm need to be understood before managing it. Monitoring IOP is a critically important part in the management of glaucoma. Various approach and technology have been initiated and on-going for a frequent, round-the-clock IOP measurement to determine the IOP peaks and fluctuations. We review the current innovative approach and its importance as well as discussing the shortcomings of each method to obtain the 24 hour IOP profile.
Health-seeking behaviour among patients with faecal incontinence in a Malaysian academic setting

Roslani AC, Ramakrishnan R, Azmi S

Med J Malaysia, 2017 12;72(6):333-337.
PMID: 29308769 MyJurnal

BACKGROUND: Faecal incontinence (FI) is not a common presenting complaint in Malaysia, and little has been published on this topic. Since it is a treatable condition, a greater understanding of factors contributing to healthseeking behaviour is needed in order to plan effective provision of services.
METHODS: A survey of 1000 patients and accompanying relatives, visiting general surgical and obstetrics and gynaecology clinics for matters unrelated to FI, was conducted at University Malaya Medical Centre between January 2009 and February 2010. A follow-up regression analysis of the 83 patients who had FI, to identify factors associated with health-seeking behaviour, was performed. Variables identified through univariate analysis were subjected to multivariate analysis to determine independence. Reasons for not seeking treatment were also analysed.
RESULTS: Only eight patients (9.6%) had sought medical treatment. On univariate analysis, the likelihood of seeking treatment was significantly higher among patients who had more severe symptoms (OR 30.0, p=0.002), had incontinence to liquid stool (OR 3.83, p=0.002) or when there was an alteration to lifestyle (OR: 17.34; p<0.001). Nevertheless, the only independently-associated variable was alteration in lifestyle. Common reasons given for not seeking treatment was that the condition did not affect patients' daily activities (88.0%), "social taboo" (5.3%) and "other" reasons (6.7%).
CONCLUSIONS: Lifestyle alteration is the main driver of healthseeking behaviour in FI. However, the majority do not seek treatment. Greater public and physician-awareness on FI and available treatment options is needed.
Earnings among people with spinal cord injury

Ramakrishnan K, Loh SY, Omar Z

Spinal Cord, 2011 Sep;49(9):986-9.
PMID: 21556013 DOI: 10.1038/sc.2011.47

Secondary analysis of cross-sectional data.
Effect of Solution Properties and Operating Parameters on Needleless Electrospinning of Poly(Ethylene Oxide) Nanofibers Loaded with Bovine Serum Albumin

Ramakrishnan R, Gimbun J, Ramakrishnan P, Ranganathan B, Reddy SMM, Shanmugam G

Curr Drug Deliv, 2019;16(10):913-922.
PMID: 31663478 DOI: 10.2174/1567201816666191029122445

BACKGROUND: This paper presents the effect of solution properties and operating parameters of polyethylene oxide (PEO) based nanofiber using a wire electrode-based needleless electrospinning.
METHODS: The feed solution was prepared using a PEO dissolved in water or a water-ethanol mixture. The PEO solution is blended with Bovine Serum Albumin protein (BSA) as a model drug to study the effect of the electrospinning process on the stability of the loaded protein. The polymer solution properties such as viscosity, surface tension, and conductivity were controlled by adjusting the solvent and salt content. The morphology and fiber size distribution of the nanofiber was analyzed using scanning electron microscopy.
RESULTS: The results show that the issue of a beaded nanofiber can be eliminated either by increasing the solution viscosity or by the addition of salt and ethanol to the PEO-water system. The addition of salt and solvent produced a high frequency of smaller fiber diameter ranging from 100 to 150 nm. The encapsulation of BSA in PEO nanofiber was characterized by three different spectroscopy techniques (i.e. circular dichroism, Fourier transform infrared, and fluorescence) and the results showed the BSA is well encapsulated in the PEO matrix with no changes in the protein structure.
CONCLUSION: This work may serve as a useful guide for a drug delivery industry to process a nanofiber at a large and continuous scale with a blend of drugs in nanofiber using a wire electrode electrospinning.
Keratin based bioplastic film from chicken feathers and its characterization

Ramakrishnan N, Sharma S, Gupta A, Alashwal BY

Int J Biol Macromol, 2018 May;111:352-358.
PMID: 29320725 DOI: 10.1016/j.ijbiomac.2018.01.037

Plastics have been one of the highly valued materials and it plays an significant role in human's life such as in food packaging and biomedical applications. Bioplastic materials can gradually work as a substitute for various materials based on fossil oil. The issue like sustainability and environmental challenges which occur due to manufacturing and disposal of synthetic plastics can be conquering by bio-based plastics. Feathers are among the most inexpensive abundant, and renewable protein sources. Feathers disposal to the landfills leads to environmental pollutions and it results into wastage of 90% of protein raw material. Keratin is non-burning hydrophilic, and biodegradable due to which it can be applicable in various ways via chemical processing. Main objective of this research is to synthesis bioplastic using keratin from chicken feathers. Extracted keratin solution mixed with different concentration of glycerol (2 to 10%) to produce plastic films. The mixture was stirred under constant magnetic stirring at 60 °C for 5 h. The mixtures are then poured into aluminum weighing boat and dried in an oven at 60 °C for 24 h. The mechanical properties of the samples were tested and the physic-chemical properties of the bioplastic were studied. According to the results, Scanning Electron Microscopy test showed good compatible morphologies without holes, cavity and edge. The difference in chemical composition was analyzed using Fourier transform infrared spectroscopy (FTIR). The samples were also characterized by thermo gravimetric analysis (TGA), differential scanning calorimetry (DSC), X-Ray diffraction (XRD) to check the thermal and crystallinity properties. Other than that, bioplastic made up from keratin with 2% of glycerol has the best mechanical and thermal properties. According to biodegradability test, all bioplastic produced are proven biodegradable. Therefore, the results showed possible application of the film as an alternative to fossil oil based materials which are harmful to the environment.
Fulltext COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques

Kannan R, Wang IZW, Ong HB, Ramakrishnan K, Alamsyah A

F1000Res, 2021 09 16;10:932.
PMID: 34925768 DOI: 10.12688/f1000research.72976.2

Background: The Malaysian government reacted to the pandemic's economic effect with the Prihatin Rakyat Economic Stimulus Package (ESP) to cushion the novel coronavirus 2019 (COVID-19) impact on households. The ESP consists of cash assistance, utility discount, moratorium, Employee Provident Fund (EPF) cash withdrawals, credit guarantee scheme and wage subsidies. A survey carried out by the Department of Statistics Malaysia (DOSM) shows that households prefer different types of financial assistance. These preferences forge the need to effectively customise ESPs to manage the economic burden among low-income households. In this study, a recommender system for such ESPs was designed by leveraging data analytics and machine learning techniques. Methods: This study used a dataset from DOSM titled "Effects of COVID-19 on the Economy and Individual - Round 2," collected from April 10 to April 24, 2020. Cross-Industry Standard Process for Data Mining was followed to develop machine learning models to classify ESP receivers according to their preferred subsidies types. Four machine learning techniques-Decision Tree, Gradient Boosted Tree, Random Forest and Naïve Bayes-were used to build the predictive models for each moratorium, utility discount and EPF and Private Remuneration Scheme (PRS) cash withdrawals subsidies. The best predictive model was selected based on F-score metrics. Results: Among the four machine learning techniques, Gradient Boosted Tree outperformed the rest. This technique predicted the following: moratorium preferences with 93.8% sensitivity, 82.1% precision and 87.6% F-score; utilities discount with 86% sensitivity, 82.1% precision and 84% F-score; and EPF and PRS with 83.6% sensitivity, 81.2% precision and 82.4% F-score. Households that prefer moratorium subsidies did not favour other financial aids except for cash assistance. Conclusion: Findings present machine learning models that can predict individual household preferences from ESP. These models can be used to design customised ESPs that can effectively manage the financial burden of low-income households.
Fulltext Functional and preliminary characterisation of hydrocolloid from tamarillo (Solanum betaceum Cav.) puree

Gannasin SP, Ramakrishnan Y, Adzahan NM, Muhammad K

Molecules, 2012 Jun 05;17(6):6869-85.
PMID: 22669042 DOI: 10.3390/molecules17066869

Hydrocolloid from tamarillo (Solanum betaceum Cav.) puree was extracted using water and characterised for the first time. Proximate compositions of the extracted hydrocolloid were also determined. Functional characteristics such as water-holding capacity, oil-holding capacity, emulsifying activity, emulsion stability, foaming capacity and stability of the hydrocolloid were evaluated in comparison to that of commercial hydrocolloids. Its functional groups and degree of esterification were determined using Fourier Transform Infrared (FT-IR) spectroscopy. Monosaccharide profiling was done using reverse-phase high pressure liquid chromatography (RP-HPLC). Screening of various fruits for high hydrocolloid yield after water extraction resulted in tamarillo giving the highest yield. The yield on dry weight basis was 8.30%. The hydrocolloid constituted of 0.83% starch, 21.18% protein and 66.48% dietary fibre with 49.47% degree of esterification and the monosaccharides identified were mannose, ribose, rhamnose, galacturonic acid, glucose, galactose, xylose and arabinose. Higher oil-holding capacity, emulsifying activity and emulsion stability compared to commercial hydrocolloids propose its possible application as a food emulsifier and bile acid binder. Foaming capacity of 32.19% and good foam stabilisation (79.36% of initial foam volume after 2 h of foam formation) suggest its promising application in frothy beverages and other foam based food products. These findings suggest that water-extracted tamarillo hydrocolloid can be utilised as an alternative to low methoxyl pectin.
Fulltext Prevalence of faecal incontinence and its related factors among patients in a Malaysian academic setting

Roslani AC, Ramakrishnan R, Azmi S, Arapoc DJ, Goh A

BMC Gastroenterol, 2014;14:95.
PMID: 24885285 DOI: 10.1186/1471-230X-14-95

Prevalence data is essential for planning of healthcare services. The prevalence of faecal incontinence (FI) varies worldwide, and in Malaysia is not known. We sought to estimate its prevalence among patients with various conditions in a Malaysian academic setting.
Tocopherol and tocotrienol contents of different varieties of rice in Malaysia

Shammugasamy B, Ramakrishnan Y, Ghazali HM, Muhammad K

J Sci Food Agric, 2015 Mar 15;95(4):672-8.
PMID: 24841131 DOI: 10.1002/jsfa.6742

The present study examined the contents of tocopherols and tocotrienols and their distribution in 58 different varieties of whole rice cultivated in Malaysia. The analytical method used was saponification of samples followed by dispersive liquid-liquid microextraction and reverse phase high-performance liquid chromatography.
Combination of saponification and dispersive liquid-liquid microextraction for the determination of tocopherols and tocotrienols in cereals by reversed-phase high-performance liquid chromatography

Shammugasamy B, Ramakrishnan Y, Ghazali HM, Muhammad K

J Chromatogr A, 2013 Jul 26;1300:31-7.
PMID: 23587317 DOI: 10.1016/j.chroma.2013.03.036

A simple sample preparation technique coupled with reversed-phase high-performance liquid chromatography was developed for the determination of tocopherols and tocotrienols in cereals. The sample preparation procedure involved a small-scale hydrolysis of 0.5g cereal sample by saponification, followed by the extraction and concentration of tocopherols and tocotrienols from saponified extract using dispersive liquid-liquid microextraction (DLLME). Parameters affecting the DLLME performance were optimized to achieve the highest extraction efficiency and the performance of the developed DLLME method was evaluated. Good linearity was observed over the range assayed (0.031-4.0μg/mL) with regression coefficients greater than 0.9989 for all tocopherols and tocotrienols. Limits of detection and enrichment factors ranged from 0.01 to 0.11μg/mL and 50 to 73, respectively. Intra- and inter-day precision were lower than 8.9% and the recoveries were around 85.5-116.6% for all tocopherols and tocotrienols. The developed DLLME method was successfully applied to cereals: rice, barley, oat, wheat, corn and millet. This new sample preparation approach represents an inexpensive, rapid, simple and precise sample cleanup and concentration method for the determination of tocopherols and tocotrienols in cereals.
Fulltext Unlocking the secrets of exchange rate determination in Malaysia: A Game-Changing hybrid model

Butt S, Ramzan M, Wong WK, Chohan MA, Ramakrishnan S

Heliyon, 2023 Aug;9(8):e19140.
PMID: 37636448 DOI: 10.1016/j.heliyon.2023.e19140

Nominal exchange rate determination is a puzzling phenomenon throughout the literature. Thus, the study aims to analyze the nominal exchange rate determination with a hybrid approach of macroeconomic and microstructure determinants, i.e., interest rate differential, oil price, order flow, and bid-ask spread over the long- and short-run horizons in the context of Malaysia. The dataset consists of high-frequency daily data from 2010 to 2017, employing a nonlinear ARDL approach. The results indicate that the bid-ask spread and interest rate differential were found to be key determinants of exchange rate dynamics in the long and short run. The findings show strong evidence of long-run asymmetry in the interest rate differential, while short-run asymmetry effects exist between microstructure determinants and the exchange rate. In addition, it indicates that the bid-ask spread holds informative content to explain the dynamics of the exchange rate in Malaysia. Additionally, the negative changes in the oil price could potentially act as macroeconomic news announcements and the bid-ask spread as liquidity determinants in Malaysia, which play a significant role in exchange rate determination. The study concluded that the prominent short-run asymmetry effects captured in cumulative order flow and bid-ask spread While a long-run asymmetry exists between the oil price and exchange rate in Malaysia. The empirical results allow for long-run and short-run asymmetric pricing impacts of a hybrid approach on the nominal exchange rate in Malaysia. This study is helpful in providing policy direction and practical implications for monetary authorities and market dealers. The bid-ask spread and oil price could be considered influential exchange rate determinants in the short run in Malaysia.
Fulltext Industrialization, globalization, ICT, and environmental degradation in Malaysia: A frequency domain analysis

Ehigiamusoe KU, Lean HH, Mustapha M, Ramakrishnan S

Heliyon, 2023 Oct;9(10):e20699.
PMID: 37876485 DOI: 10.1016/j.heliyon.2023.e20699

This paper examines the causal relationship between industrialization, globalization, information communication technology (ICT) and environmental degradation in Malaysia during 1970-2019. It uses two indicators of environmental degradation (carbon emissions and ecological footprint), three dimensions of globalization (political, social, and economic) and three indicators of ICT (users of internet, mobile cellular, and fixed telephone subscriptions). It utilizes Granger causality technique in frequency domain which differentiates between permanent and temporary causality, Vector Error Correction approach as well as Variance Decompositions. The bound test shows that the variables have cointegration relationship. It reveals joint long-run and short-run causality from industrialization, globalization, and ICT to carbon emissions, albeit the causality to ecological footprint is tenuous. It indicates that industrialization, globalization, and ICT significantly predict carbon emissions at high frequency than at low frequency. A substantial percentage of the forecast error variance in environmental degradation are explained by industrialization, globalization, and ICT. The robustness of the empirical outcomes is confirmed by the alternative proxies of the variables. Our study implies that industrialization, globalization, and ICT are determinants of environmental degradation. Therefore, policies to mitigate environmental problem should prioritize these variables to attain green economy.
Fulltext Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction

Kannan R, Reddiar Y, Ramakrishnan K, Eastaff MS, Ramesh S

F1000Res, 2021;10:1052.
PMID: 36225238 DOI: 10.12688/f1000research.73234.2

Background: Banks and financial institutions are vulnerable to money laundering (ML) as a result of crime proceeds infiltrating banks in the form of significant cash deposits. Improved financial crime compliance processes and systems enable anti-ML (AML) analysts to devote considerable time and effort to case investigation and process quality work, thereby lowering financial risks by reporting suspicious activity in a timely and effective manner. This study uses Job Characteristics Theory (JCT) to evaluate the AML system through the job satisfaction and motivation of its users. The purpose of this study is to determine how satisfied AML personnel are with their jobs and how motivated they are to work with the system. Methods: This cross-sectional study used JCT to investigate the important elements impacting employee satisfaction with the AML system. The five core dimensions of the job characteristics were measured using a job diagnostic survey. The respondents were employees working in the AML department of a Malaysian bank, and the sample group was chosen using a purposive sampling approach. A total of 100 acceptable replies were gathered and analysed using various statistical approaches. A motivating potential score was generated for each employee based on five main job characteristics. Results: Findings revealed that five core job characteristics, namely, skill diversity, task identity, task importance, autonomy and feedback, positively influence the AML system employees' job satisfaction. However, skill variety and autonomy are found to be low, which are reflected in the poor motivating potential score. Conclusion: This study examined the characteristics of the AML system and its users' job satisfaction. Findings revealed that task significance is the most widely recognised characteristic, followed by feedback and task identity. However, there is a lack of skill variety and autonomy, which must be addressed to improve employee satisfaction with the AML system.
Sweat gland morphology and physiology in diabetes, neuropathy, and nephropathy: a review

Singaram S, Ramakrishnan K, Selvam J, Senthil M, Narayanamurthy V

Arch Physiol Biochem, 2024 Aug;130(4):437-451.
PMID: 36063413 DOI: 10.1080/13813455.2022.2114499

Context: Sweat glands (SGs) play a vital role in thermal regulation. The function and structure are altered during the different pathological conditions.Objective: These alterations are studied through three techniques: biopsy, sweat analytes and electrical activity of SG.Methods: The morphological study of SG through biopsy and various techniques involved in quantifying sweat analytes is focussed on here. Electrical activities of SG in diabetes, neuropathy and nephropathy cases are also discussed, highlighting their limitations and future scope.Results and Conclusion: The result of this review identified three areas of the knowledge gap. The first is wearable sensors to correlate pathological conditions. Secondly, there is no device to look for its structure and quantify its associated function. Finally, therapeutic applications of SG are explored, especially for renal failure. With these aspects, this paper provides information collection and correlates SG with pathologies related to diabetes. Hence this could help researchers develop suitable technologies for the gaps identified.
How does technological innovation moderate the environmental impacts of economic growth, natural resource rents and trade openness?

Ehigiamusoe KU, Dogan E, Ramakrishnan S, Binsaeed RH

J Environ Manage, 2024 Dec;371:123229.
PMID: 39522189 DOI: 10.1016/j.jenvman.2024.123229

The objective of this study is to unravel the linear impacts of economic growth, technological innovation, natural resource rents and trade openness on carbon emissions in Malaysia during 1980-2021. It also unveils the moderating role of technological innovation on the impacts of economic growth, natural resource rents and trade openness on carbon emissions. It further analyses the nonlinear relationship between technological innovation and carbon emissions. It estimates the parameters with the Autoregressive Distributed Lag model technique. The results of the linear model reveal that economic growth, natural resource rents and trade openness contributes to carbon emissions while technological innovation mitigates carbon emissions. The disaggregated analysis of natural resource rents indicates that oil rents, natural gas rents and coal rents intensify carbon emissions while mineral rents and forest rents do not contribute to carbon emissions. The disaggregated analysis of trade openness shows that exports worsen carbon emissions while imports have tenuous effect. The disaggregated analysis of technological innovation indicates that innovation by non-residents mitigate carbon emissions while innovation by residents do not alleviate carbon emissions. Moreover, evidence from the interaction model reveals that technological innovation can favourably mitigate the adverse impacts of economic growth and trade openness on carbon emissions albeit it cannot alleviate the impact of natural resource rents on carbon emissions. Besides, the nonlinear model indicates a U-shaped relationship between technological innovation and carbon emissions. Unlike previous studies that typically focused on the direct impacts of these variables, this study unravels the impacts of the disaggregated components as well as provides insights into the moderating and nonlinear effects of technological innovation on carbon emissions. The implication of this study is that efforts to achieve a carbon-neutral economy should consider the direct and indirect impacts of economic growth, technological innovation, natural resource rents and trade openness. It is recommended for Malaysia to encourage technological innovation in her quest to abate the adverse environmental impacts of economic activities.
Cyclospora sp causing diarrhea in man

Sinniah B, Rajeswari B, Johari S, Ramakrishnan K, Yusoff SW, Rohela M

Southeast Asian J Trop Med Public Health, 1994 Mar;25(1):221-3.
PMID: 7825021
Fulltext Resonant frequency characteristics of a SAW device attached to resonating micropillars

Ramakrishnan N, Nemade HB, Palathinkal RP

Sensors (Basel), 2012;12(4):3789-97.
PMID: 22666001 DOI: 10.3390/s120403789

Recently we reported experimental and simulation results on an increase in resonance frequency of a SAW resonator caused by mass loading of micropillars made of SU-8, attached normal to the surface of the resonator. We concluded that SAW resonator and the SU-8 micropillars in unison form a system of coupled resonators. We have now extended this work and performed a finite element method simulation to study the resonance frequency characteristics of the SAW-based coupled resonator. In this paper we report the effect of the resonance frequency of the micropillars on the resonance frequency of the system of coupled resonators, and observe the coupling of micropillar resonance and the propagating SAW as described in the well known Dybwad system of coupled resonators.

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